A One Health Framework for Estimating the
Economic Costs of Zoonotic Diseases on Society
Clare Narrod1), Jakob Zinsstag2) , Marites Tiongco1), Devesh Roy1)
1)International Food Policy Research Institute, 2033 K Street, NW Washington DC 20006, USA
c.narrod@cgiar.org
2)Swiss Tropical and Public Health Institute, PO Box, 4002 Basel, Switzerland;
jakob.zinsstag@unibas.ch
3)
World Bank/ECA
Table of Content
HOW TO READ THIS DOCUMENT: ................................................................................................................................3
INTRODUCTION ..........................................................................................................................................................3
Methodological gaps.............................................................................................................................................5
Gap 1: Need for intersectoral assessments ......................................................................................................................... 5
Gap 2: Need for integrated methods ................................................................................................................................... 6
AIM AND CONCEPTUAL BASIS OF THE FRAMEWORK ...................................................................................................6
MANUAL FOR THE INTER-SECTORAL ECONOMIC ASSESSEMENT OF THE IMPACT OF ZOONOSES ON SOCIETIES.............7
Step 1: Estimate the extent of the disease and potential spread ...........................................................................8
Impact of disease: ............................................................................................................................................................... 8
Burden of disease estimate ................................................................................................................................................. 8
DALY parameters ......................................................................................................................................................... 8
Required data collection ................................................................................................................................................ 9
Methods for estimating the initial prevalence of a disease and data needs .................................................................. 10
Step 2: Estimate the cost of zoonotic diseases on livelihoods outcomes, national economies and including
environmental impacts; ....................................................................................................................................... 12
Methods for modeling transmission and data needs ......................................................................................................... 12
Assessing effects on livestock productivity ...................................................................................................................... 13
Methods for modeling the economic cost of disease ........................................................................................................ 14
Macro-economic impact (please refer to Devesh et al, 2009 for a more detail discussion) ....................................... 14
Micro-economic impact (please see Birol et al. 2010 for a more detailed discussion) ............................................. 16
Step 3: Assess the cost-effectiveness of control strategies currently used to reduce the risk of human and
animal exposure to zoonotic diseases ................................................................................................................. 17
Methods for evaluation control measures ......................................................................................................................... 17
Use of decision trees/event trees to depict decision choices ........................................................................................ 17
Modeling cost of controlling disease and data needs ................................................................................................... 19
Modeling the direct costs of a disease ......................................................................................................................... 19
Modeling Approach to CBA of the Intervention .......................................................................................................... 20
Cost effectiveness analysis .......................................................................................................................................... 22
Step 4 Identify the factors preventing the adoption of cost-effective strategies by poor households, commercial
sector and government bodies and estimate the cost and benefits of applying zoonotic disease risk reduction
programs ............................................................................................................................................................. 25
Methods for capturing behavior ....................................................................................................................................... 25
Methods for modeling knowledge attitude, perception, and practices surrounding zoonotic disease .......................... 25
Willingness to pay and willingness to accept control options and data needs ............................................................. 27
Integrating results using bio-economic simulation models .......................................................................................... 29
Conclusions and Recommendations.................................................................................................................... 30
ANNEXES: ................................................................................................................................................................. 31
Annex I. Examples of most important zoonoses .................................................................................................. 31
Brucellosis ........................................................................................................................................................................ 31
Rabies ............................................................................................................................................................................... 32
Anthrax............................................................................................................................................................................. 32
Echinococcus granulosis .................................................................................................................................................. 33
Bovine Tuberculosis ......................................................................................................................................................... 33
Annex II: “One health” ...................................................................................................................................... 33
Contribution of the framework to the One Health strategy and future conceptual outlooks ............................................. 35
Annex III: Proposed Framework ........................................................................................................................ 35
Description ....................................................................................................................................................................... 35
Analytical approaches ...................................................................................................................................................... 37
Annex IV Impact of zoonotic diseases on society ................................................................................................ 42
Human health risks of zoonoses ....................................................................................................................................... 43
Economic impact on involved sectors .............................................................................................................................. 45
Economic impact of Health consequences ....................................................................................................................... 45
Livelihoods impacts ......................................................................................................................................................... 46
Sector and economy-wide impacts ................................................................................................................................... 46
Environmental impact and associated costs ..................................................................................................................... 47
Communication, public awareness and Education ........................................................................................................... 47
Annex V: Rationale for intervention for controlling the risk of zoonoses ........................................................... 47
Public good debate of zoonoses; State vs. public-private partnership interventions......................................................... 49
Difficulties in intervening to correct zoonotic problem in developing country case ........................................................ 50
REFERENCES: ........................................................................................................................................................... 52
How to read this document:
The presented framework is an annotated hands-on manual for the inter-sectoral
economic assessment of the impact of zoonoses on societies. Its primary objective is to serve as
a tool for technical experts and authorities to estimate societal cost of zoonotic diseases and
the profitability and cost-effectiveness of interventions. The first part is a straight forward
manual indicating items to consider for such an assessment. However, many of the issues
addressed are not straight forward and require broad technical, economic, political, ethical and
philosophical considerations, which are shaped by the different cultures, societies and
environments of the world. For this reason, the text of the manual is annotated with elements
of these reflections, which are given as annexes. In this way, practitioners can concentrate on
the practical aspects, while the interested reader can examine the broader ramifications of the
issues by reading the annexes.
Introduction
For centuries many human diseases have spread from the infections of domestic and
wild animals. Rabies for example, was already recognized by the Egyptians. As the ecology of
human/animal interactions enters a new phase of dynamic global change, the threat of “new”
diseases or what are called emerging zoonotic diseases threaten human health and livelihoods
is an immediate and growing concern. Zoonotic diseases can be caused by many different
pathogenic agents, of which a few are presented in Annex I. In most cases, humans are
accidental or “spill-over” hosts of a disease-ecological cycle that is maintained by a set of
animal hosts, including insects. Because of the circulation of zoonotic agents between animals,
humans and the environment, the cost of disease does not only affect human activity and
health but also other sectors like livestock production, pet ownership, the food and textile
industry, tourism, land use, foreign trade and, ultimately, Gross Domestic Product (GDP).
Because of this, many developed countries try to control the disease as fast as possible so as to
reduce or avoid human exposure and to eliminate and prevent it from spreading to livestock
populations and wildlife, but the effective mitigation of these often endemic and chronic
diseases requires more strategic interventions. In the past sixty years, many industrialized
countries have successfully controlled and/or eliminated many zoonotic diseases, including
brucellosis, bovine tuberculosis, rabies, anthrax and BSE, through significant public investment
into well coordinated interventions. Financially, not all interventions were profitable, but
economic considerations were not the only criteria of decision for control or elimination. Public
health concerns (Bovine Tuberculosis, Rabies) and consumer perception (BSE) strongly
influence policy decisions. Interventions against zoonoses included among others “test and
slaughter,” feed bans, mass vaccination of domestic animals and wildlife, health education, and
pasteurization of milk. “Test and slaughter” is a highly effective intervention if the prevalence of
a disease is low. It means that animals are tested and if they are revealed to be positive for the
disease, they are slaughtered and hence removed from the transmission cycle. This is a highly
effective way of eliminating a zoonotic disease, but requires important operational, legal and
financial commitment. Its application requires effective testing and communication of results
followed by rapid removal of positive animals with appropriate compensation for producers
and effective control of animal movement.
In developing countries zoonotic diseases are often not recognized as such because of
the lack of diagnostic capacity and poor infrastructure. For the most part, efforts have focused
on implementing prevention and eradication measures in livestock populations. However,
much less emphasis has been placed on the effect of mitigation strategies or measures aimed
at controlling the transmission, taking into consideration their economic and development
impacts at the macro (national economy and the environment) and micro (health, livelihoods
and food security of smallholder farmers) levels. Many developing and middle income countries
are lacking diagnostic and intervention capacity and they are often lacking the financial means
to compensate farmers for culled animals. Hence, effective interventions in industrialized
countries cannot be transferred automatically to developing and middle income countries.
Effective interventions against zoonoses need to be contextually adapted to local socio-cultural
and economic conditions and based on an in-depth knowledge of the local disease ecology,
which is most often different than in industrialized countries.
According to the World Bank (2010) “the direct costs of zoonotic diseases over the last
decade surpassed US$20 billion – including public and animal health service costs,
compensation for lost animals, and production and revenue losses to the livestock sector, and
over US$200 billion of indirect losses to affected economies as a whole.” Many industrialized
countries are able to control or reduce the risk of many zoonotic diseases by substantial public
investment in preventative measures, surveillance and the compensation of farmers for culled
stock. Such means however are not currently available in many developing and middle income
countries without outside aid in the form of donor assistance. Any investment in the control of
zoonoses requires an assessment of the cost of disease and the cost-effectiveness of
interventions. Seventy percent of the world’s rural poor depend on livestock, poultry and many
other animals (e.g. working elephants, dogs) as a component of their livelihoods (LID, 1999;
FAO, 2002). Many of the poor may not be able to implement control efforts even if it has large
impacts on profitability and understanding mechanisms that may influence behavior are thus
equally important.
Cost assessments of zoonoses first require an in-depth understanding of the ecology of
disease. Detailed knowledge on transmission pathways of zoonoses help to identify the
different sectors bearing cost of a particular disease, or of multiple diseases. This knowledge is
also essential for determining effective interventions, capable of interrupting transmission. A
specific feature of zoonoses control is that effective interventions for public health are often
outside the health sector. This is because there is often no transmission between humans;
therefore this route is not important to maintain transmission of the disease (see below). For
example, effective control of human rabies exposure is only possible by intervention in wildlife
or dog reservoirs. Brucellosis in humans can only by eliminated by effective control in ruminant
livestock.
There are several other ways in which zoonotic diseases might have economic impacts
beyond the cost of control: costs directly affecting income at the household level from
reduction in livestock sales; consumption impacts due to reduction in food and nutrition
security; increasing household vulnerability to risks since livestock is often used as a risk-coping
mechanism, and affecting household wealth which can affect savings (hence future livelihood
outcomes) and gender equality (since women often own smaller livestock). In addition to
household level impacts, there are also impacts at the sector level such as the feed and input
sector and at the economy wide level which would include other inputs sectors and other
outputs sectors which can be analyzed, such as restaurants, hotels and markets. These
associated costs may influence behavioral change at various levels (household, practitioner,
policy) with the regards to the decision whether or not to control a zoonotic disease.
Methodological gaps
Gap 1: Need for intersectoral assessments
The effectiveness of different institutions to implement control measures vary
depending on the current structure of the livestock and health sectors. Many countries,
particularly transitional countries, face institutional challenges in attempts to control disease.
Sims (2007) notes these include limited veterinary infrastructure, lack of coordination between
veterinary staff and local communities, inadequate funding and devolved authority for
veterinary services, which can cause differences in control policies even within small
administrative regions. That assessment, however, focuses mainly on the institutions that
provide disease control services. In addition, in many transitional countries the poor producers
and other actors in the value chains may not be formally linked to the system and their price
margins are so small that it is difficult for them to finance needed interventions and/or get
information about control/mitigation methods. In transitional countries more attention needs
to be placed on improving the interaction between mitigation agents and the value chain
actors.
Gap 2: Need for integrated methods
The transmission cycles between animal and humans are mostly well known. To
understand the effects of zoonoses on human and animal health, translated into cost of disease
to society, we require an in-depth understanding of the interfaces between different hosts. This
includes understanding how animal populations are connected to human populations, to
quantitatively assess the circulation of zoonotic pathogens. The circulation of zoonoses
between host-species is a complex non-linear process, depending on demographic dynamics of
each host species and their interconnection (Zinsstag et al 2005 and Zinsstag et al 2009). Most
existing studies look only at one species, not multi-species scenarios. Further, most existing
studies are descriptive and hence rarely tackle analytically the dynamics of disease transmission
between different hosts (e.g. livestock and humans) (Scotch et al 2009). Important preparatory
steps for the understanding of between host-interfaces include integrated study designs.
Integrated study designs provide a frame for the sampling of animals and humans
representatively and allow the establishment of statistical evidence for the relationship of
disease frequency in each species. At best, such studies are coupled to molecular strain analysis
which provides further biological evidence for between host zoonoses transmission (Zinsstag et
al, 2009). Based on a biologically and epidemiologically sound causal relationship of zoonoses
transmission, financial analyses on the cost of disease can be developed.
Aim and conceptual basis of the framework
The aim of this document is the development of integrated epidemiological and
economic methods of zoonoses assessments in developing countries. It is rooted on our field
experience in numerous Asian and African countries, where we were faced with the lack of
communication and understanding of the effects of zoonoses between multiple sectors of
societal activity, particularly between public and animal health. We suggest that this framework
that can be used by Governments in combination with the OIE Performance of Veterinary
Services (PVS) and WHO International Health Regulations (IHR) to advocate for investments in
One Health.
The framework will demonstrate how linking the outputs of various analyses associated
with animal health transmission model, economic impact, and risk analysis can inform the
planning of investments in the most promising interventions (or set of interventions). A better
understanding of the costs of the disease and the costs and benefits of control measures is
expected to promote wider implementation of the most efficient and effective control
measures, thereby contributing to improved health and livelihoods outcomes of the poor, and
macroeconomic growth. The team will draw on lessons learned from experiences with various
studies on the evaluation of (i) the macro and micro level economic impacts of HPAI and
brucellosis and (ii) the cost-effectiveness of alternative control measures.
An integrated systemic approach considering local social and ecological systems is the
best way to approach this analysis. Conceptually it is not new and has been successfully applied
in what is called an “ecosystem approach to health” or “ecohealth.”(Forget, et al, 2001).
Example of an “ecosystem approach to health”:
Lead poisoning of fish in the Amazon was related firstly to upstream gold mining. Only
by a comprehensive ecological analysis, deforestation and consecutive washing out of lead
from the soil was subsequently identified as the primary cause of fish lead poisoning (Forget, et
al. 2001).
This example shows that we want to be careful with identifying causality of health of
animals in humans in complex social and ecological systems. As part of “ecohealth”, “one
health” addresses the potential of closer cooperation between human and animal health. “One
health” evolved from “one medicine”, a term coined by the American veterinary epidemiologist
Calvin Schwabe in the 1960’s, and means that there is no difference of paradigm between the
human and veterinary medicines. Both sectors should work together as closely as possibly
(Schwabe, 1984) (More details are given in Annex II).
We propose here a comprehensive framework for estimating the cost of zoonotic
diseases on society using a “one health” concept. This document aims to develop a
methodological tool that can be used by Governments in combination with the OIE
Performance of Veterinary Services (PVS), WHO International Health Regulations (IHR) and
other operational analysis to advocate for investments in One Health. The methodology will use
in a stepwise approach, primary and secondary data and robust analytical tools to:
i.
Estimate the extent of the disease and potential spread;
ii.
Estimate the cost of zoonotic diseases on livelihoods outcomes (income, health, and
trade) and national economies (agriculture sector productivity, public health, food safety, trade,
tourism, etc) and including environmental impacts;
iii.
Assess the cost-effectiveness of control strategies currently used to reduce the risk of
human and animal exposure to zoonotic diseases.
iv.
Identify the factors preventing the adoption of cost-effective strategies by poor
households, commercial sector and government bodies and estimate the cost and benefits of
applying zoonotic disease risk reduction programs
Manual for the inter-sectoral economic assessement of the impact of zoonoses
on societies.
The framework of the inter-sectoral economic assessment aims at zoonoses assessments in
developing and middle income countries. Its rationale is presented in Annex III.
Step 1: Estimate the extent of the disease and potential spread
Impact of disease:
Zoonoses cause human illness, permanent disability and death. Animals may be
asymptomatic carriers but can also be clinically ill or die. In livestock illness my cause reduction
in productivity, in terms of live animals (reduced fertility) and reduced meat and milk
production. The pooled impact of zoonoses on humans and animals on society can be
estimated in terms of cost to different sectors. Obviously the loss of human life cannot be
costed and requires specific assessments, called “burden of disease”, which are expressed as
loss of disability adjusted life years (see below).
Burden of disease estimate
Zoonotic diseases cause losses of goods that could have been produced (live animals,
milk, meat, wool) and disability or loss of human life. The overall burden of disease to society
will always involve a quantifiable monetary term and a quantifiable term of loss of human life
(Annex IV Human health risks of zoonoses). The authors do recognize the inherent value of
animal life and emotional value to animal owners, but do not recommend attempts to estimate
disability adjusted life years for animals. For the time being they advocate quantifying the value
of animal life at the market prices for which they are traded. Estimating the cost of goods is
straightforward and involves relating quantities of goods with their market prices and assessing
their net present value using standard discounting procedures.
Loss of human life can be quantified against standard tables summing up the number of
expected life years at the age of death. Non fatal disease impairs human life during clinical
illness and may result in temporary or permanent disability. WHO has engaged in estimating
the level of impairment of ill health and permanent disability related to complete physical and
mental health and well-being (Disability weight =0) and to the death of a person (Disability
weight = 1). Disability weights of non fatal diseases are classified depending on the level of
impairment of human life, such as occupation, procreation and recreation. This classification is
controversial and raises ethical issues. Alternative ways of assessing the burden of disease build
on perceived quality of live, called Quality adjusted live years (QALYs). In this document, we
explicitly don’t address this controversy and concentrate on the development of DALY
parameters to zoonotic diseases. While we are aware of the ethical concerns about DALYs, we
believe that estimating the burden of disease of so far neglected zoonotic diseases using DALYs
brings them at least in the focus of attention and increases the probability of effective
interventions.
DALY parameters (please refer to Zinsstag et al, 2007 for more details)
Disability-adjusted life years (DALYs) are used in the global comparative assessments of
the burden of disease (Carabin et al, 2005) and enable costs of interventions to be related to a
standardized health outcome across diseases internationally (Murray, 1994 and Murray et al
1997). DALYs is an indicator of the time lived with a disability and the time lost because of
premature death (Formula 1).
DALYs = years of life lost + years of life with a disability
(1)
The duration of time lost due to premature death is calculated by using standard expected
years of life lost with model life tables. The reduction in physical capacity due to illness is
measured by using disability weights. To calculate the reduction in physical capacity, the
following formula is used (Formula 2) (Murray, 1994)
where a is the age at onset of disease, L is the duration of disability or time lost due to
premature mortality, D is the disability weight (or 1 for premature mortality), r is the discount
rate, C is the age-weighting correction constant, and β is the parameter from the age-weighting
function.
An estimate of the burden of disease for brucellosis is not readily available, so we
therefore estimated the DALYs as a result of the disease by assuming that brucellosis is
associated with a class II (0.2) disability weight (D), as the disease is perceived as very painful
and affects occupational ability even during periods of remission. For cost-effectiveness, we
used the median of the cumulated discounted DALYs, which corresponds to a median duration
(L) of brucellosis of 3.11 years (Roth et al , 2003).
For estimation of DALY averted for rabies, we assumed that 16% of the exposed persons
would develop clinical rabies without timely administered post-exposure prophylaxis. Because
of the short duration of clinical disease, years of life lost with a disability (YLD) are negligible
compare to years of life lost (YLL) (Zinsstag et al, 2009). In other studies losses due to
psychological fear and side effects of nerve tissue vaccines are added (Knobel et al, 2005).
Estimates of DALY losses are provided for echinococcosis (Budke, et al, 2004) and a summary
framework is provided for bovine tuberculosis (Zinsstag, et al 2006), but for the vast majority of
other zoonoses DALY estimates are not readily available. Zoonoses with multiple clinical forms,
like anthrax, require multiple approaches. For pulmonary or digestive forms of anthrax, which
are per-acute (rapidly fatal), require estimates of YLLs, while for more common skin forms
estimates of YLDs will be more important.
Required data collection
Estimating the impact of zoonoses on society relates to a population or a geographic
area as a sampling frame. E.g., assessing the impact of brucellosis to Kyrgyzstan requires a
representative estimate of the annual incidence of human cases and the prevalence in all
involved livestock species. Such data can be collected from official surveillance systems or by
representative studies. The latter is more laborious, but provides better results, as official
surveillance systems often under-report the true disease frequency. We recommend also
combinations of data from official sources and representatives studies. In this way the level of
underreporting can be estimated. If dynamic simulation of zoonoses transmission is envisaged,
we recommend the collection of time series data, like annual newly reported human cases over
several years, which allow then the simulation of non-linear effects of interventions (Figure 4).
Figure 4: Effect of livestock brucellosis vaccination on humans. Prevalence and cumulative
incidences are given as straight proportions (extracted from Roth et al. 2003).

Established disease frequency in humans and animals allows then their relation to cost data.
Cost data can be collected from official sources for public expenses and statistics. Private cost
requires patient based surveys of out of pocket expenses and income loss (see below).
Methods for estimating the initial prevalence of a disease and data needs (please refer to Zinsstag
et al, 2009 for a more detail discussion)
Integrated methods, investigating human and animal health simultaneously, is justified
if the incremental knowledge generated is higher than two separate human and animal health
studies, and if there are no concessions made with regard to the quality of methods used on
either side. The interfaces between species can be straight forward or at different levels, e.g.,
by occupational or consumer exposure. In-depth assessments are then necessary to understand
lifecycles and drivers of the reservoir or maintenance host populations. A variety of longitudinal
and cross-sectional designs exist to monitor animal-human transmission using proxy indicators,
such as dog bites for rabies (Cleaveland, et al 2002) or questionnaires of exposure (Kayali, et al
2003) or comparative seroprevalence in humans and potential animal reservoirs (Schelling et al,
2003). Studies at the animal-human interfaces should aim primarily at high risk human
populations considering the particular context of exposure, such as encroaching habitat, live
animal markets and risk groups of professional exposure e.g. livestock workers or veterinarians.
In the following we present a case example of the study design of a representative, national
human and animal brucellosis seroprevalence study and cost of disease to society for
Kyrgyzstan (Zinsstag et al, 2009 and Bonfoh et al, 2010.
Box 1
OSH Oblast
Cumulative number
Oblast
Osh
251137
792444
rayon
Alay
21396
121941
121941
rayon
Aravan
25567
53038
174979
rayon
Kara-Kuldzja 24504
101477
276456 182244.2
rayon
Kara-suu
72072
201897
478353 451468.2
rayon
Naukat
49843
122120
600473
rayon
Uzgen
45354
125925
726398 720692.2
rayon
Chong-Alay 12401
66046
792444
city
Osh
8577
15228
807672
Cumulative number
807672
Number of Rayons
3
Sampling interval
269224
Random starting point
113931.8 182244.2
Selected rayons
269224 451468.2
269224 720692.2
1
2
3
Box 1. In Osh Oblast, we select 3 Rayons. We divide the total number of animals (807672)
by 3 to obtain the sampling interval (269224). We select a random number among the total
population by a =Rand()*807672 and obtain 182244 which falls within Kara-Kuld rayon. We add
the sampling interval 269224 and obtain 451468, which falls into Kara-suu rayon. We add again
the sampling interval and drop into Uzgen rayon. Hence we select Kara-Kuld, Kara-suu and Uzgen
rayon.
Villages were sampled proportional to size of the sheep and goat population, which is
suspected to be the main reservoir of Brucellosis in Kyrgyzstan. Selected villages were informed
on the contents of the study and asked for their informed consent. In randomly selected
households, twenty sheep and goat were sampled. If a livestock species was not present in a
village, then no other completion of the sample was sought. If there were cattle in the
household, they were sampled equally up to a total number of 20 in the same way as the sheep.
In every village up to forty human blood samples were collected. In the selected
households, all humans are sampled after informed consent was given, following National
brucellosis examination guidelines (Decree 240, Epidemiology and surveillance of brucellosis of
the Kyrgyz Republic). Humans were sampled by public health physicians under supervision of the
Republican Centre for Quarantine and especially dangerous diseases. A questionnaire was filled
in with herders on i) observed abortion rates within herds, ii) life-history of sampled animals, iii)
vaccination status of herds, iv) predominant animal health problems, v) occurrence of human
brucellosis in the family including reproductive disorders.
The sampling frame was the national census of the sheep population. A multistage
cluster sampling proportional to size (Bennett et al, 1991), analogous to Schelling et al (2003),
was done by levels of Oblast (Province), Rayon (District) and village. In Box 1, an example of the
selection of administrative units proportional to the size of their sheep population is presented.
Table 2 shows the sampling on those animal species which are important for brucellosis
transmission. For rabies, for example we would concentrate on rabid dogs and exposed humans
(Kayali et al, 2003). For echinococcosis, fecal samples should be taken from dogs and sheep
should be inspected in abattoirs or be examined by ultrasound. In this way the animal-human
sampling must be adapted to the specific zoonoses ecology to obtain a representative estimate
of the intensity of disease transmission.
Table 2: Summary of livestock and human samples collected from an integrated
livestock-human representative cross-sectional study design.
Overview of Sample numbers
Species
Sheep
Goat
Cattle
Human
Total No. Of samples
per Oblast
No of Oblast
600
600
600
No of Repetitions
3
1
3
1
3
1
600
3
2
Total N
1800
1800
1800
3600
9000
Step 2: Estimate the cost of zoonotic diseases on livelihoods outcomes,
national economies and including environmental impacts;
Methods for modeling transmission and data needs
The cost and burden of zoonoses to society can be assessed in a static way from crosssectional data. In the same way benefit-cost analysis or cost-effectiveness of interventions can
be done by comparing cost of disease before (ex-ante) and after (ex-post) interventions. Such
approaches do not consider the time dependent dynamics of disease transmission with and
without interventions. Zoonoses transmission can be endemically stable but is most often
undergoing epidemic cycles, which cannot be captured by the above static approaches. In
particular animal to human transmission is determined by the population dynamics of animal
and human populations. Animal-human transmission models are capable to capture the nonlinear dynamics of between animal zoonoses transmission and the transmission to humans
(Zinsstag et al, 2005 and Zinnstag et al, 2009). In this way human disease burden can be directly
linked to the transmission in animals. Most importantly such models can be used to simulate
interventions and compare their outcomes with and without interventions (Figure 5). Dynamic
models of zoonoses transmission are of little value to predict future transmission, but they are,
with all their limitations, useful to compare different intervention strategies.
Figure 5: Flow chart of dog-human rabies transmission

Sources: Zinsstag et al 2009
Assessing effects on livestock productivity
Zoonoses like brucellosis or bovine tuberculosis do not affect only the productivity of an
individual animal but of the whole herd. Abortions reduce overall fertility of a cattle herd and
indirectly the number of live animals and the production of meat and milk. Addressing effects
of zoonoses on livestock production therefore requires the use of livestock production
simulation like the Livestock Development Planning System (LDPS) of the FAO
(http://www.fao.org/agriculture/lead/tools/livestock0/fr/). Livestock herd simulation uses
demographic model theory for the projection of livestock productivity. It requires information
about the herd composition by age and sex (Table 3). Such data can be obtained from national
statistical offices or could also be collected from larger field surveys. Demographic models are
driven by fertility and age-specific mortality. Fertility would be expressed as number of
newborn animals per female animal in reproductive age per year. Age-specific mortality is the
number of death per age group per year. Prior to simulate the effect of zoonoses on the
demographic composition, baseline productivity should be simulated with known fertility and
age-specific mortality.
Table 3: Example of a cattle herd composition needed for LDPS
Herd composition
Cattle (1999)
Total population
Number of female breeders in base year
Number of male breeders in base year
Number of female replacement in base year
Number of male replacement in base year
Number of other stock in base year
Number of female young in base year
Number of male young in base year
Annual calving rate
Survival rate of replacement
Survival rate of young stock
3824700
1449800
72490
391446
144980
678634
543675
543675
0.75
0.72
0.949
Effects of zoonoses on livestock productivity requires an understanding on how
productivity is actually reduced and how the presence of the disease is measured. A sheep that
is sero-positive for brucellosis, may not have aborted, or a cow which reacts to an intradermal
test for bovine tuberculosis may show no clinical signs. The linkage of disease to productivity is
critical and data are sparse. Bernues et al (1997) put forward a 15% reduction of overall fertility
in brucellosis sero-positive cattle. Overall meat production in tuberculin positive animals is
estimated to be 10% lower than in healthy animals (Meisinger, 1970). Such information allows
to relate disease data and productivity parameters. For example the overall fertility in a
diseased herd is decreased by a prevalence dependent proportion:
Fertility(diseased) = Baseline Fertility (1 – (0.15*Sero-Prevalence))
For example if the baseline fertility would be 0.7 calves per cow per year and the prevalence of
brucellosis would be 4%, the Fertility(diseased) would be 0.695 calves per cow per year. Such
differences appear to be small, but their effect on a national herd is remarkable.
In the same way the reduction of annual milk production would be expressed as a
prevalence dependent value. Productivity parameters like Fertility(diseased) are then used to rerun the productivity simulation over the same time period as the baseline productivity without
disease. The subtraction of the number of live animals and outputs in milk, meat and hides of
productivity simulations with and without disease results then in the actual losses due to a
specific disease. Losses in meat and milk are then related to their market value and discounted
to obtain net present values of losses in livestock production from a zoonosis. Live animals will
be considered as an asset whereas livestock products will be considered as net incremental
loss.
Methods for modeling the economic cost of disease
Macro-economic impact (please refer to Devesh et al, 2009 for a more detail discussion)
The macro-economic impact of zoonotic diseases on the economy can be modeled using
computable general equilibrium model or multi-market model. The choice of model depends
on the structure of the livestock sector and the extent of its structural linkages with other
sectors of the economy as well as available data. Disease shocks such as occurrence of a
zoonotic disease can affect the availability of supply of livestock (through disease control
measures such as eradication of infected livestock resulting to reduced stock or inventory of
livestock). Declining production of livestock will then affect household income through revenue
losses for livestock keepers and hence will affect total national income. This decline in sales will
also affect consumer prices.
Zoonotic disease outbreaks can also influence the demand side through reduction in
consumption expenditures on livestock products due to perceived food safety concerns or
trade restrictions. This will then cause prices to fall which can then affect the livelihoods of
producers through lower returns causing them to divert to non-livestock activities in order to
compensate for the falling returns from livestock. With non-livestock production increasing,
prices for these non-livestock products fall, and thus benefiting other sectors in the economy.
As in supply shocks, demand shocks could also affect other sectors of the economy including
tourism. The net effect of the demand and supply shocks will depend on income distribution
and structure of the whole economy.
The models discussed above use data from the national social accounting matrix,
household budget survey, and household living standard survey, disaggregated by region or
agro-ecological zones, and by type of livestock commodity. If data are available at the individual
or firm level, a micro-simulation can be performed to determine the effect of disease shocks (or
risk mitigating/control measures) on individuals’ income, wealth, and nutrition.
The macro-economic models can further be integrated with spatial disease spread
models, if developed, that determine disease transmission or spread. Spatial spread models are
usually based on state and transition probabilities that assess the severity of risk of disease
outbreaks. The transition probabilities depend on transmission routes of infected livestock and
also on the trade flows of these livestock products (within country or cross-border). For these
data to be useful, they have to be at the same level of disaggregation as the data used in
modeling macro-economic impacts. In cases where the actual severity, duration, and spread of
a disease outbreak are unknown, a series of simulations are run using different levels of
demand and supply shocks at varying dimensions of severity (e.g., 15% or minor to 30% or
major outbreak), spread (e.g., local or nationwide) and duration (one and up to three years) of
a disease outbreak. From this analysts can then estimate economic losses across a wide range
of possible outbreak scenarios (the baseline is without an outbreak).
Applications of this method in regards to HPAI are demonstrated by Thurlow (2010),
Diao (2009), Diao, Alpuerto, and Nwafor (2009), and Schmitz and Roy (2009). They estimated
the economic losses due to avian influenza outbreaks and its effect on economic growth.
Results of these studies suggested that demand shocks driven by consumer panic is a foremost
factor in the reduction of poultry production but the overall effect to the economy on average
is likely to be minimal due to the small size of the poultry sector and weak intersectoral
linkages. In addition, the effect on the income of the rural poor is not significant because they
have diversified income portfolio like income from crops and other livestock which make them
resilient to shocks such as HPAI outbreak. In terms of impact on nutrition, Ianotti et al (2008)
assessed the impact of HPAI on nutrition of young children in Indonesia. They found out that
reduced poultry product consumption resulting from a sustained HPAI shock with no animal
source food substitute (assuming a worst case scenario) have significant detrimental impacts in
terms of stunting, height for age, and hemoglobin concentration for children (1-3 years old).
Micro-economic impact (please see Birol et al. 2010 for a more detailed discussion)
A combination of the qualitative and quantitative analyses is used to enable a rigorous
investigation of the impact of zoonotic disease outbreak on income and wealth of households.
Qualitative methods (such as focus group discussions and participatory rapid appraisals) would
be useful to understand the flow of the livestock product along the value chain, and identify
bottlenecks and constraints, market failures, and institutional risk management strategies
(policies and regulations), as well as the social and political factors influencing livelihoods of
poor households. The impact of economic losses on income generating activities and
diversification patterns as well as dynamic changes in income generating activities can be
investigated using these qualitative methods.
Quantitative analysis of costs, income, and consumption would also be useful in
understanding the choices made by households and their effects on livelihood outcomes (e.g.,
increased income and food security). Then the impact of zoonotic diseases on household
income and wealth can be estimated by measuring changes in household income and wealth
due to supply and demand shocks and price changes with and without disease outbreaks. Data
for this type of analysis is often not readily available for a specific disease unless an actual
household survey was undertaken. If a household survey exists, a counterfactual (without
disease outbreak) can be analyzed in terms of changes in livelihood outcomes (with disease
outbreak). Such a survey would require a randomization of the sampling frame so as to
maximize quantitative accuracy and eliminate selection bias. Where randomization is not
possible, matching techniques such as the propensity score matching can be used where two
groups of households with similar observable characteristics (such as household demographics,
assets, income sources, and so on) are matched. The two groups of households would consist of
a treatment group representing those with the disease demand or supply shocks, and a control
group representing the baseline (without disease shocks). The differences between these
groups at different scenarios in terms of selected outcomes (such as income, productivity, and
wealth) would reveal the impact of zoonotic disease outbreaks on income and wealth.
To illustrate, Table 4 shows the impact of HPAI outbreak on livestock income and
wealth. Six scenarios were investigated: 1) if all small-scale poultry producers lost 100% of their
flocks to HPAI; 2) if those small-scale poultry producers who manage less than 25th percentile
of small flocks lost 100% of their flocks to HPAI; 3) if those small-scale poultry producers who
manage more than 25th percentile of small flocks lost 85% of their flocks to HPAI; 4) reduction
in output prices; 5) if all small-scale poultry producers in high risk areas lost 100% of their flocks
and 6) if those small-scale poultry producers in medium risk areas who manage more than 25th
percentile of small flocks lost 85% of their flocks to HPAI
Table 4: Livelihoods impact of HPAI: Loss in livestock income & wealth
ETHIOPIA
Scenarios:
Livestock
wealth
1 – All Country: Lose all
poultry
-
2 – All Country: Lose all
small flocks
-
3 – All Country: Large
flocks become small
flocks
51%
4 – Poultry Sellers: High
price falls to low price
-
5 – High HPAI Risk: Lose
all poultry
-
6 – Medium HPAI
Risk: Large flocks
become small flocks
31%
KENYA
GHANA
NIGERIA
Livestock
Income
(total
income)
Livestock
Wealth
(total
wealth)
Livestock
Income
(total
income)
Livestock
Wealth
(total
wealth)
Livestock
Income
(total
income)
Livestock
Wealth
(total
wealth)
-
-
17%
(0.8%)
-
-
-
-
-
-
-
-
-
28%
(7 %)
31%
(6 %)
-
23%
(12%)
42%
(7.4%)
-
67%
(8 %)
46%
(4 %)
-
-
-
-
-
41%
(9 %)
22%
(1.6%)
-
-
-
-
-
30%
(0.5%)
31%
(16%)
39%
(8%)
21%
(15%)
Step 3: Assess the cost-effectiveness of control strategies currently used
to reduce the risk of human and animal exposure to zoonotic diseases
Methods for evaluation control measures
Use of decision trees/event trees to depict decision choices
Optimal zoonotic control strategies are subject to chance events. These can be captured
in a simplified way by using a decision/event trees to depict (in approximately chronological
order) alternative courses of control actions (decisions choices) and chance events with the
time scale and associated costs (see Milne et al, 2007, Marsh, 1999). See figure 6 for a
hypothetical decision /event tree looking at the decision to implement a variety of HPAI control
measure that could be developed for any type of zoonotic disease. The net financial outcome
(cost and losses) for each event in this example can then be weighted by its probability of
occurrence and summed to give the expected value for each decision choice. As noted by Milne
et al (2007) “the simplest choice criterion would be to choose the action with the highest
expected value (or lowest where outcomes are costs), however in risky situations a decisionmaker may wish to avoid alternative with a chance of particularly undesirable or unacceptable
outcomes (Annex V).
Figure 6: A hypothetical decision tree for the control of HPAI
Vaccine
No infestation
X%
$w
Infestation controlled
X%
$y
Infestation not controlled
X%
$z
No infestation
X%
$w
$w
$
$
Culling
$x
HPAI Control
Infestation controlled
X%
$y
Infestation not controlled
X%
$z
No infestation
Target Vaccination
$x
Infestation controlled
X%
$y
Infestation not controlled
X%
$z
No infestation
No Control Measure
X%
$w
$
---------Expected value (medicine applied)
($w + (0.9x$y) + (0.01x$z))
$
$
$
-----------Expected value (medicine not applied)
($w + (0.9x$0) + (0.01x$z))
X%
$w
$x
Infestation controlled
X%
$y
Infestation not controlled
X%
$z
No infestation
Vaccinate Test & Culling
Expected financial outcome
X%
$w
$x
Decision node
Infestation controlled
X%
$y
Infestation not controlled
10%
$z
Chance node
Source: Adapted from Milne et al 2007 and Fasina et al 2007
Note: For each of the control measures, there are actually two decision choices: to apply or not
to apply; each decision will have the same chance of events: no infestation, infestation
controlled, and infestation not controlled with the assigned probability of occurrence based on
existing knowledge (from the disease risk outputs).
Modeling cost of controlling disease and data needs
Prevention and control strategies help minimize negative economic impacts of animal
disease outbreaks but there are costs associated with these strategies. It is therefore important
to assess the costs and benefits of prevention and control measures so as to inform policy
makers regarding development of effective prevention and control policies. The economic costs
associated with the prevention and control of a zoonotic disease is the summation of the value
of the expected losses in output due to fall in stock and fall in domestic prices and demand of
the livestock commodity because of the presence of the disease, and the costs of risk mitigating
strategies (such as preventative measures: vaccines, disinfectants). Benefits of prevention and
control strategies are calculated as the sum of the avoided losses of the expected output and
the decrease in the cost of the different risk-reducing strategies. Simulation can then be
performed using different sets of scenarios: do nothing or no risk reduction strategy (baseline
or no disease outbreak); a single risk reduction strategy; or a combination of risk reduction
strategies. The difference between the baseline and a risk reduction strategy or combination is
the gain in health (DALYs averted) or income (and welfare) due to the reduction in disease
burden from the prevention and control measures. The costs of each strategy are then
compared with the gains to identify the most cost-effective strategy (or a combination of
strategies) at different levels of resource availability. The comparison of the different strategies
against the most cost-effective shows areas of efficiency. The optimal risk reduction measure is
the point where the marginal benefit is equal to the marginal cost.
Cost-benefit analysis (CBA) is a tool commonly used by decision makers to systematically
estimate all the benefits and all the costs associated with a contemplated course of action in
comparison with alternative courses of actions. According to Arrow, et al. (1997), the role of
CBA in environment, health, and safety regulations is to inform the allocation of scare resources
to be put the greatest social good. However, in not all cases are the monetary costs most
important to decision makers. Cost-effectiveness analysis (CEA) is a tool commonly used to
evaluate the return of an intervention when it is impractical to consider the monetary value of
the benefit by the alternative under consideration. When it comes to disease risk reduction,
decision makers are also interested in the effectiveness of the measures in terms of risk
reduction. The distribution of costs among socio-economic groups may differ from the
distribution of benefits. A bio-economic simulation modeling approach described below will be
used to measure the changes in outcomes from alternative zoonotic control strategies, with
particular attention to the underserved populations. Below we provide more detail regarding
the methods
Modeling the direct costs of a disease
Effects of disease on livestock productivity (see above Assessing effects on livestock
productivity) can be used to estimate direct cost of disease. The direct costs of the disease will
be assessed using a partial budget model adapted from Bennett (2003) to measure the direct
cost of animal disease it is assumed that the direct costs of the zoonotic disease are related to
the loss in expected output, increases in expenditure on non-veterinary resources due to the
disease, cost of inputs to prevent the disease such that:
C=L+R+P+T
Where:
C = direct cost per year
L = annual loss in expected outputs and wasted inputs due to disease
R = the increase in expenditures on non-veterinary recourses due to the
disease
P = annual cost of disease prevention measures
T- treatment costs
Modeling Approach to CBA of the Intervention
In an analysis, the costs and benefits of the impacts of an intervention can be evaluated
either in terms of the public's willingness to pay for them (benefits) or willingness to pay to
avoid them (costs) or in terms of actual costs if control efforts have been implemented. CBA
allows decision makers to rank policies and those that have the larger impact on well being are
considered preferable. Cost benefit analysis is typically used by governments to evaluate the
desirability of a given intervention in markets. The goal of the analysis is to understand the
efficiency of the intervention relative to the status quo in an objective quantitative way of
determining whether protections should be initiated, continued, or abandoned. Economic
efficiency is measured as the net contribution of an intervention to overall social welfare.
The costs and benefits of the impact of an intervention are evaluated in terms of the public’s
willingness to pay for them (benefits) or the willingness to pay to avoid them (costs). An
intervention would be considered pareto optimal if it improves the situation for some people,
but does not make anybody worse off. It is recognized that it is often difficult to identify pareto
optimal solutions since rarely is it possible to design a policy such that someone is not made
worse off. Analysis that provides potential pareto solutions that recognize those who gain could
compensate those who lose for their losses and still be better off provides decision makers with
a mathematical way to determine efficient interventions. Thus for governments acceptable
(intervention) policies typically are when:
E(Benefits) ≥ E(Costs)
Glauber and Narrod (2001) have argued that an optimal policy is when a government chooses a
policy that maximizes net benefits such that:
E(MB) = E(MC)
Where:
MB = marginal benefits
MC = marginal cost
We propose to use initially a simple partial equilibrium model of disease control to get at the
global CBA similar to the one outlined in Rendleman and Spinelli (1999) and modified by
Glauber and Narrod (2001) for analyzing the costs and benefits of alternative policies. In this
approach WD was the welfare effect in the event of a disease outbreak and WN was the welfare
effect in the event of no outbreak such that WN > WD Thus if an outbreak occurs with
probability p, then the expected welfare, EW, can be written:
EW  pWD  (1  p)WN
(1)
Now consider a risk reduction measure,  , that affects the probability of an outbreak and
welfare such that:
(2)
EW ( )  p( )WD ( )  (1  p( ))WN ( )  C( )
where C ( ) is the cost of implementing the risk reduction measure. An optimal policy
maximizes (2) with respect to  such that:
W ( )
 0 , or

(3)
p '( )WD ( )  p( )WD ( )  p( )WN 
(1  p( ))WN ( )  C ( )  0
(4)
Rearranging the terms, an optimal risk reduction measure  *, can be defined so that the
marginal change in benefits is equal to the marginal change in costs.
p(WD  WN )  C   [ pWD  (1  p)WN ]
(5)
The left hand term reflects the net change in welfare due to the change in probability – the
benefits of reducing the risk of outbreak. The right hand terms reflect the expected change in
welfare due to the risk mitigation measure – the cost of implementing the measure.
The optimal risk reduction measure policy can be shown in figure 7. A, B, C, D, E, and F are risk
reduction measures with associated costs and benefits. Policies A, C, D, and F lie on an efficient
frontier of policy alternatives; that is, for a given cost, these policies result in the maximum
possible benefits. Policies B and E are inferior policies. Policy C is the optimal risk migration
policy,  *, that satisfies equation (5). At this point, the marginal benefit of the risk mitigation
policy is equal to the marginal cost. These options can be plotted and a frontier estimated
where options below the frontier are considered inferior.
Figure 7: Optimal Risk Reduction measures
Source: Glauber and Narrod (2001)
Though cost benefit analysis traditionally focuses on efficiency by providing policy makers with
an indication of the magnitude of net benefits associated with a particular policy, it also has the
potential to track the distribution of costs and benefits within different segments of the
population. Ideally for the case of a zoonotic disease one would be able to determine how costs
and benefits are distributed by sector or geographic location. It is thus important to that the
risk assessment identify the riskier pathways and sectors.
As uncertainty and variability exists with all variables used in the CBA estimates it is important
that sensitivity and scenario analysis be conducted to illustrate how results may change if the
value of a particular variable is changed.
Cost effectiveness analysis
Cost effectiveness analysis is closely related to CBA, but looks to achieve the specified
goal with the smallest loss in social welfare recognizing that the smallest loss might not be
associated with the smallest dollar cost. For the goal of analyzing the control options associated
with zoonotic diseases, the objective of the CEA analyses is to provide economic and disease
risk and information on the impact a set of control strategies that could be adopted in the
event of an a zoonotic disease. For the cost effectiveness analysis it is recognized that certain
strategies may have economies of scale that favour large producers.
Once the CBA analysis has been completed and the quantitative risk assessment under
the disease risk output, then CEA analysis can be used to pull together the results of the
different scenarios along with the results of the sensitivity and uncertainty analysis to provide
information on the cost and effectiveness of the various control strategies considered to
support decision making and the outputs can be plotted on a trade-off curve to make it
transparent to decision makers.
Figure 8 shows how four hypothetical control options (A, B, C, D) might be compared.
The x-axis is the marginal cost of adding one of the new options compared to the baseline. The
y-axis is the percentage reduction in risk over the baseline (no action). In this hypothetical
scenario option D can be excluded as a choice since strategy B dominates D in the sense that B
is both more effective and less costly. Choices of adoption strategy from a decision maker’s
perspective can then be limited to non-dominated options A, B, and C (Malcolm et al., 2004).
Figure 8: Risk Cost Trade-Off Curve
C
% Risk
Reduction
B
A
D
Cost per unit
Source: Malcolm, Narrod, Roberts, and Ollinger et al 2004
Zinsstag et al (2005) estimated the societal economic benefit, cost-effectiveness, and
distribution of benefit of improving human health through a mass vaccination campaign of
livestock in Mongolia to control Brucellosis. They used a livestock-human brucellosis
transmission model which was linked to a livestock productivity analysis to evaluate the impact
of a planned 10-year livestock mass vaccination campaign using Rev-1 livestock vaccine for
small ruminants and S19 livestock vaccine for cattle to determine the cost-effectiveness,
expressed as cost per disability adjusted life year (DALY) averted. A scenario of 52% reduction
of brucellosis transmission between animals through a mass vaccination campaign indicated, a
total of 49 027 DALYs could be averted. The intervention cost was estimated as US$ 8.3 million,
and the overall benefit estimated at US$ 26.6 million. The net present value of the campaign
was a US$ 18.3 million and an average benefit–cost ratio for society of 3.2 (2.27–4.37). The
authors argues that if the costs of the intervention were shared between the sectors in
proportion to the benefit to each, the public health sector would contribute 11%, which gives a
cost-effectiveness of US$ 19.1 per DALY averted (95% confidence interval 5.3–486.8). If private
economic gain because of improved human health was included, the health sector should
contribute 42% to the intervention costs and the cost effectiveness would decrease to US$ 71.4
per DALY averted. The authors concluded that if the costs of vaccination of livestock against
brucellosis were allocated to all sectors in proportion to the benefits, the intervention might be
profitable and cost effective for the agricultural and health sectors (adapted from Roth et al,
2003). Figure 9 below summarizes the costs and benefits of brucellosis control.
Figure 9: Costs and benefits of Brucellosis control
Zinsstag et al (2009) work in Africa found that human rabies in developing countries can
be prevented through interventions directed at dogs. Using available deterministic models of
rabies transmission between dogs and extending the models to include dog-to-human rabies
transmission they found potential cost-savings for the public health sector of interventions
aimed at animal-host reservoirs. In their analysis they fitted model parameters to routine
weekly rabid-dog and exposed-human cases reported in N’Djaména, the capital of Chad. The
effective reproductive ratio (Re) at the onset of our observations was estimated at 1.01,
indicating low-level endemic stability of rabies transmission. Human rabies incidence depended
critically on dog-related transmission parameters. They then simulated the effects of mass dog
vaccination and culling of a percentage of the dog population on human rabies incidence. They
found that a single parenteral dog rabies-mass vaccination campaign which achieved a
coverage of least 70% appeared to be sufficient to interrupt the transmission of rabies to
humans for at least 6 years. The cost-effectiveness of mass dog vaccination was also compared
to post exposure prophylaxis (PEP), which is the current practice in Chad but does not reduce
future human exposure. The cost-effectiveness of PEP is estimated at US $46 per disability
adjusted life-years averted while the cost-effectiveness for PEP along with a dog-vaccination
campaign, breaks even with cost-effectiveness of PEP alone after almost 5 years. Thus beyond a
time-frame of 7 years, it appears to be more cost-effective to combine parenteral dog
vaccination campaigns with human PEP compared to human PEP alone (adapted from Zinsstag
et al 2009). Figure 10 shows the cumulated and discounted costs of human PEP alone, with 95%
uncertainty interval (black line with black dotted limits), and human PEP with dog vaccination
with 95% uncertainty interval (gray line with gray dotted limits). Break-even points are
numbered diamonds for sensitivity analysis with 3%, 5%, and 10% discount rates (Zinsstag et al,
2009).
Combined cost of human and dog vaccination
Cost of human vaccination alone
Figure 10 Combined cost of human and dog vaccination.
Step 4 Identify the factors preventing the adoption of cost-effective
strategies by poor households, commercial sector and government bodies
and estimate the cost and benefits of applying zoonotic disease risk
reduction programs
Methods for capturing behavior
Methods for modeling knowledge attitude, perception, and practices surrounding zoonotic disease
To determine the knowledge, attitudes, and practices (KAP) towards mitigating the risk
of zoonotic disease, a household survey and/or focus group discussion can be administered
identified or targeted key stakeholders. Questions related to knowledge or degree of
understanding of the disease outbreak and related issues can be framed as open ended
questions or multiple choice questions that allows for multiple answers. Questions that will
assess attitude or behavior and perception of respondents’ about the disease outbreak can also
be formulated as open-ended or multiple choice questions. Questions on practices or actions
taken or will be taken in preventing or controlling disease outbreaks are usually structured as
open-ended so as to capture differences or common practices of households in different areas
or regions. Likert scales can be used across the questionnaire to identify attitudinal and
knowledge predictors of risk perceptions and behavior changes. Points are assigned to these
questions and can either be summed up to come up with an index or can be grouped into low,
moderate or high, or with and without. The knowledge index can be used to analyze the
differences of KAP of different socioeconomic groups using multivariate or multivariate
stepwise logistic analysis. The analysis also determines factors that affect the knowledge,
attitude, and practices of the respondents and also evaluate difference in knowledge level
across socioeconomic groups.
Knowledge, attitude, perception, and practices data collection and analysis is widely
used before and after intervention programs to evaluate the impact of education or
intervention programs. The knowledge refers to the degree of understanding of the topic and
associated issue. Attitude refers to respondents feelings toward the topic and issues of the
topic. Perception refers to what people perceive. Lastly, practices refer to past and current
actions towards the topic. There have been numerous attempts to investigate the KAP on
zoonotic diseases on general population (Fielding R. et al., 2005; Olsen S.J., et al., 2005; UNICEFGeorgia, 2007; Maton T., et al., 2007; Di Giuseppe et al., 2008; Leslie T., et al., 2008) and target
groups (UNICEF-Myanmar, 2006; Abbate R., et al., 2006; Leggat P.A., et al., 2007). These studies
used a Likert scale in the surveys from which questions were grouped into generalized groups
where answers to each question were scored and points summed across. These KAP scores
were then used to analyze the difference between different socioeconomic groups by
univariate and/or multivariate analytical tools.
Fielding R. et al (2005) surveyed households in Hong Kong over the phone and
determined exposure and risk perception of avian influenza from live chicken sales. Likert scales
were used across the questionnaire to identify attitudinal and knowledge predictors of risk
perceptions and behavior change with a number of statements addressing attitudes, avian
influenza protection practices, and perceptions of live chicken sales. Results indicated that the
magnitude of perception of the risk from live chicken sales seldom exceeded 60%, and that
hazard familiarity and experience reduced associated risk perceptions. The authors concluded
that in the long run public awareness campaigns have little impact, while in the short run the
effect was large and significant. Similarly Olsen S., et al. (2005) surveyed residents of rural
Thailand regarding AI KAP before and after the interviewees had heard about the AI. Median
and mean values of KAP responses study showed positive shifts in KAP among the targeted
group of poultry keepers. In a similar study done by UNICEF in Georgia and Myanmar found
that though the majority of respondents were familiar with AI, only few could list the symptoms
of AI in poultry and ways of its transmission. Similar finding was reported by Maton et al. (2007)
in AI KAP study in Thailand and the authors recommended that in addition to general public
awareness campaign a detailed and targeted campaign is beneficial in reducing the risk of AI
spread.
In the same way recommendations were outlined in study of individuals in Italy by Di
Giuseppe et al. (2008) regarding their knowledge, attitude and perceptions surrounding HPAI in
terms of modes of transmission, washing hands with soap before and after touching raw
poultry meat, and using gloves, and perception of risk of contracting AI. Similar to Fielding et al.
(2005) findings suggested that there was a moderate knowledge of AI and a limited knowledge
of details of symptoms, transmission and prevention, and a high perception of being at risk
contracting AI. Results from KAP and risk perception regression models were similar to the work
of Fielding et al (2005) showing that past experience with AI, higher level of education, and
higher socioeconomic status predict greater level of knowledge of AI and lower perception of
the risk. Leslie et al. (2008) found that though overall knowledge of AI in 5 provinces in
Afghanistan was low but that individuals from higher socioeconomic classes had higher
knowledge than others. Their study also indicated that though Information Education
Campaigns (IEC) were targeted at low-income rural poultry producers who had little access to
information and currently have limited detailed knowledge of AI.
IFPRI’s resent work evaluating producer’s knowledge, attitude, and practices of HPAI in
Indonesia in 2009 found that 80% of producers heard of HPAI; only few could correctly identify
symptoms (see table 5 below). They found that there was a not a significant variation in KAP
indices of free range/backyard and small-scale market oriented, however larger marketoriented producers had higher KAP indices. They also found that producers who have higher
KAP indices tended to have more diverse and larger flocks; history of poultry diseases & HPAI in
their villages. In addition they tended to have higher income and income from poultry activities,
and female household heads.
Table 5: KAP analysis results on HPAI – Indonesia 2009
These findings as well as the literature review suggest several common findings across
the different studies – (1) people who were aware of AI in general had very limited knowledge
of the details of AI symptoms, transmission modes, control and prevention; (2) rural households
had less knowledge than the urban and those households from higher socioeconomic class; (3)
households keeping poultry has no/little influence on AI knowledge level ; and (4) the
perception of risk is high among those who had no or limited knowledge of AI.
Willingness to pay and willingness to accept control options and data needs
The willingness to pay (WTP) for or adopt control strategies or interventions such as
vaccination can be estimated using stated preference methods. One of the methods that is
generally considered by many researchers as the most appropriate choice for measuring food
safety is called contingent valuation (CV), because it is a flexible tool which can be adapted to
analyze specific food safety policies (Buzby et al, 1995). It involves asking questions to
respondents to declare the amount they are willingness to pay for a certain product or service,
contingent upon its availability in the market. Subsequently, the estimated WTP can be
compared to the costs of control strategies to determine those that are the most economically
efficient. For more efficient estimates of individual’s WTP and tighter confidence intervals, a
double-bounded CV method is used. In this method, consumers will be given a hypothetical
scenario involving the likelihood and severity of the outcomes, for example the number of
people infected with rabies. Then consumers are presented with a price to see if they are
willing to pay a certain amount for a definite safety level and, after responding yes or no, they
are then presented with a second price bid, higher or lower than the first price. A limitation of
this direct valuation method is insufficient information of the respondents or information bias
to consider thoroughly the amount they would declare, since the consequences of the disease
outbreak such as severity and health costs are difficult to value (De Groote and Kimenju, 2008).
Finally, WTP can be modeled as a function of the severity and duration of illness, reduction in
probability and respondent characteristics (Hammitt and Haninger, 2007).
IFPRI has just implemented a study of small scale producer’s willingness to pay for six
types of bio-security measures to reduce the risk of HPAI in 4 countires in Africa and Indonesia.
The biosecutiry measures they looked at included: netting/cage, poultry house, footbath,
disinfection, vaccination, veterinary monitoring. Figure XXXXX below illustrates how the
questions were asked.
Figure 11 example of questions asked regarding farmers willingness to pay for HPAI
biosecurity measures
Figure 11: Examples of a WTP question regarding improved biosecurity
As control measures were not implemented yet they used a two-stage expert elicitation
(Delphi) study to determine the effectiveness of various control efforts. They found that
Producers in Nigeria who have higher WTP tended to be larger-scale producers, had higher
incomes, already have various biosecurity measures in place, and had higher control and
prevention KAP indices see table 6 which illustrates producers predicted WTP values, mean (95%
confidence interval) in USD.
Table6: WTP for HPAI Biosecurity measures in Nigeria
Integrating results using bio-economic simulation models
The outputs under this umbrella include a framework for decision makers to assess
various preventive/control risk management options being considered in terms of (1) a CBA of
various control options being considered, (2) a CEA of these control options in terms of risk
reduction, and (3) interplay between impact on livelihoods and adoption of control measures.
Given a variety of stochastic forces can alter the outcome of mitigations, the dynamic
simulation analysis will include a series of outputs based on simulations showing decision
makers the trade-offs that they would face as they try to balance the effect of various risk
management strategies on biological efficacy of disease, economic efficiency, social desirability,
and political feasibility while recognizing that the effectiveness of any strategy will be dictated
by level of adoption. The goal of these simulations is to provide decision makers the likely
performance of different strategies in terms of key decisions parameters (origin and length of
outbreak, spatial spread outbreak, cost of outbreak, effectiveness of response and control
measures). It should be noted that since a complete census of poultry producers is not the
focus of this project we will be using existing data sets, and in a selected set of countries,
sampling and aggregation will be used to describe the spatial distribution of poultry producers.
Each sub-regional unit of aggregation will include producers of different groups based on socioeconomic and production type classification.
A key output of the dynamic bio-economic model will be frequency distributions of
important indicators, such as disease detections, income lost by household cohort and others
that illustrate the impact of the zoonotic disease. This distribution can be expressed as:
Fi(z) = Probability of an outbreak in cohort i with control strategy z
Where:
z = set of control measures in place
i = a population of interest categorized, for example, by income group, region, or
the entire country.
The distributions will be compared to the baseline scenario, defined by the status quo in each
study country, denoted by Fi(0).
Difference between the distributions Fi(z) and Fi(0) will show how the benefits (costs) of
zoonotic control are distributed among different groups, thus informing decision makers of the
possible consequences of one course of action versus another. When plotted against the cost of
implementing zi a trade-off curve can be produced that shows the relative value of control
option set z. The advantage of the approach is that it provides a mechanism for decision makers
to evaluate a “portfolio” of mitigation techniques to obtain some desired level of safety (or
maximizing safety for a given cost). The strategy a risk manager chooses depends on the risk
preferences of the affected stakeholders and on their comparative advantage in implementing
particular risk-reduction options.
Conclusions and Recommendations
The present document provides the methodological basis for assessing the societal cost
of zoonotic diseases across all involved sectors. It provides also the theoretical framework for
the biological and financial effectiveness of decision making in zoonoses control. In this sense
the document is not a simple “blue print” where figures can just be added. The document
shows the importance of knowing the biology of the involved diseases and their hosts, which is
at the centre of any attempt of control. While the theoretical framework may appear to be
“heavy” on mathematics, the presented examples on AI, brucellosis and rabies are very
practical and provide hands-on approaches. We recommend that such assessments are done in
cooperation between epidemiologists, veterinarians, medical doctors and economists in the
spirit of “One health”, benefiting from true closer cooperation across the human and animal
health sectors. We recognize that not all countries may be able to undertake all the analysis at
once, but suggest that if they target the answers they immediately need, and filling in the other
analyses over time to gain more information so that they will be able in long run to implement
effective control strategies that ensure the poor’s evolvement and participation.
However we suggest that the “One health“ concept is a powerful concept with the potential:
• To reduce zoonotic disease which were previously thought be out of control
•
•
•
•
•
To identify novel interventions from closer cooperation between human and
animal health sectors, e.g. like packaged control against multiple zoonoses in a
given context.
To share resources e.g. by sharing transport and cold chains between public and
animal health.
Joint human and animal disease surveillance
Improve health and livelihood outcome via animal disease control
Reduce poverty & support economic development (in various sectors and
improve food safety, animal productivity, and nutritional security)
Annexes:
Annex I. Examples of most important zoonoses
Zoonotic diseases are transmissible between humans and animals depending on specific
contextual social and ecological conditions which largely determine their impact on society and
the environment. Zoonotic diseases can be caused by prions (Bovine Spongiform Encephalitis, BSE),
viruses (Rabies, influenza), bacteria (Brucellosis) or parasites (Echniococcosis). There exist more than
600 zoonotic diseases and we present here just a few examples which are particularly
important for developing and middle income countries. The presented comprehensive
analytical approach to their assessment is based on these examples, which are presented here
briefly, but can be adapted to any other zoonoses in an analogous way.
Brucellosis
Brucellosis is currently one of the most important and most neglected zoonotic diseases
world-wide (Boschiroli et al 2001, Pappas et al 2005, and Pappas et al 2006). Human brucellosis
is mainly caused by Brucella melitensis and Brucella abortus by direct contact with ruminant
livestock and the consumption of milk and milk products (Figure 1). Human-to-human
transmission of brucellosis is negligible. In humans, symptoms of disease are extreme
weakness, joint and muscle pain, headache, undulant fever, hepatomegaly, splenomegaly and
night sweats. Mortality, is reported to be negligible, but illness can last for several years
(Madkour, 2001). B. melitensis causes epidemic abortion in goat and sheep, but can also be
transmitted to cattle. Infected animals can remain chronically infected and may excrete
bacteria in the milk. B. abortus causes epidemic abortion in cattle and can remain as a chronic
infection, whereby it can be excreted in the milk of infected cows. Cost to the livestock sector
from brucellosis arises mainly from reduced fertility, reduced survival of newborns and reduced
milk yield. Mortality of adult animals is negligible (Handbook on Animal Diseases in the Tropics,
1990). Brucellosis is typically a livestock-to-human problem, which is prevailing in CentralAsia,
Africa, Asia, Latin America and the Mediterranean countries having larger small ruminant and
cattle populations (Pappas, 2006). Given its contagious risks, many countries ban imports of live
animals and animal products from countries with endemic brucellosis. Brucellosis is also
considered a candidate for biological weapons (Pappas, 2006).
Figure 1: Transmission pathways of Brucellosis, adapted from Krauss et al, 1997
dog
sheep
cattle
cattle
goat
person
cattle
milk
goat
milk
cheese
other
sheep
Rabies
Rabies is a viral disease infection of all warm blooded animals and humans. For the risk
of human rabies, we distinguish two main ecological cycles. A) In the sylvatic cycle, rabies is
maintained by transmission amongst wildlife. For example in Europe, rabies is maintained by
the red fox, or in North America by foxes and raccoons. B) In the urban cycle, rabies
transmission is maintained mainly by dogs. This is the case in most developing countries in Asia
and Africa. Humans are mostly exposed by rabid dogs. In a case study in Chad, 85% of the
exposure occurred by dogs in the same household (Kayali et al, 2003). Exposure occurs through
the bite of a rabid animal. The incubation time depends on the bite localization as the virus
moves along peripheral nerves into the brain. In the brain, the virus replicates rapidly and
produces clinical signs leading to paralysis and respiratory arrest within a week. Clinical rabies is
incurable. Humans can be protected from clinical rabies by post-exposure treatment. This is
comprises active immunization and the use of immuno-globulins. Human health costs arise
from the cost of post exposure treatment and bite related treatment cost. It is well recognized
that rabies in humans requires the elimination in the animal reservoir and today a blueprint for
rabies control exists from the Alliance of Rabies Control (http://www.rabiescontrol.net/).
Anthrax
Anthrax is a bacterial disease affecting mostly livestock. Livestock, primarily cattle and
sheep feeding on contaminated pasture, ingest Anthrax spores and die from a per-acute
generalized disease, typically bleeding from body openings. Dead animals, which are left on the
ground decompose and leave behind Anthrax spores which remain in the soil for decades if not
centuries. Antrhax spores can also be distributed by flooding. Contaminated fields are known,
and animal holders try to avoid grazing their animals on them. Dead animals should be disposed
or buried deeply to avoid surface contamination. Humans infect themselves a) by ingesting
infected meat from the consumption of carcasses or touching an infected animals, b) may
inhale spores in the air, for example in the wool factories and c) may develop a skin condition
from contact with wool, skins and hair from animals. Forms a) and b) most often produce fatal
shock, whereas the skin forms can be cured by antibiotic treatment. Losses to livestock occur
from premature death. Human health cost arises from treating of systemic and skin infections.
Anthrax is also known as a bio-terrorist agent, which has been applied as a powder in letters.
Echinococcus granulosis
As an example of a macro-parasitic zoonosis, Echinococcus granulosus is a small tape
worm, living in the intestinal tract of dogs, which are the definitive host. Adult E. granulosis
shed eggs, which are ingested by livestock, mostly sheep and goat, who are intermediary hosts.
In the intermediary hosts, ingested eggs penetrate the intestinal wall and produce hydatid cysts
in the liver, lungs and other organs. Cysts are variable in size and contain a fluid and
intermediary stages of the parasite (Protoscolex). When a dog feeds on an infected sheep, he
may ingest hydatid cysts which develop into adult tape worms, hence closing the cycle.
Infection of dogs typically happens also on waste dumping places of small abattoirs where dogs
feed directly on offal. Human infection occurs through contact with infected dog feces,
containing embryonated eggs and produces hydatid cysts in the liver and other organs, similarly
to sheep. Human infection cannot be cured and requires costly surgery to remove hydatid
cysts. Losses to livestock occur from confiscation of organs or carcasses at slaughter. Human
health costs arise from the debilitating nature of the disease, treatment costs and surgery.
Bovine Tuberculosis
Bovine tuberculosis (BTB) is a bacterial disease belonging to the Tuberculosis complex.
BTB has a broad host range but is mostly found in cattle. Cattle may suffer from a chronic lung
disease and may have granulomatous abcesses in other organs, including the udder. Clinically ill
cattle lose weight and may die. Livestock production is affected by losses in meat and milk and
premature death. Cattle excrete the pathogenic agent Mycobacterium bovis by coughing or in
the milk. Humans can be infected by direct contact with cattle or by ingestion of contaminated
milk and milk products. BTB was one of the main reasons for the introduction of the
pasteurization of milk. Infected humans may suffer from clinical tuberculosis which is not
distinguishable from human tuberculosis due to Mybobacterium tuberculosis and other extrapulmonary forms. It has been estimated that up to 10% of human tuberculosis was due to BTB
prior to the advent of milk pasteurization in Germany. Human health costs arise from the
effects of the disease and treatment costs of clinical cases.
Annex II: “One health”
“One health” considers broader systemic interaction of human and animal health,
emphasizing its importance to health systems and public health (Zinsstag et al, 2005). Many
people use the term “one health” today in different ways and not with the same meaning.
There is confusion about what it means and the term is suspected to be just a buzz word or
even hype. World Bank/ECA has adopted the following definition of One Health: A framework
for enhanced collaboration in areas of common interests (intersections), with initial
concentration on zoonotic diseases, which will reduce risk, improve public health globally and
support poverty alleviation and economic growth in developing countries (World Bank 2010).
We generalize this definition by extending it to beyond zoonotic diseases and propose that, in
the context of this work, “One health” is the added value of a closer cooperation of human
health, animal health and other sectors.
Understanding that human and animal health is interconnected does not mean that a
“one health” approach is already in place. This is conventional wisdom and can be experienced
by everybody, just reading the news. A “one health” approach benefits in one way or another
from closer cooperation between human and animal health in a way that the two medicines
alone could not achieve if they remain in their own working area. This approach has a huge
potential to improve public and animal health and to save cost to the public and private sectors,
of which we present here just a few examples:
Integrated disease surveillance: Zoonotic disease and their sources can be detected
much faster if humans and animals are sampled simultaneously through an integrated study
design (Schelling et al, 2003 and Zinsstag et al 2009). Such a design reduces time to detection
and can identify animal sources of human infection in one single study. This could not be
achieved if human health and veterinary studies on the same disease would be carried out
separately.
Societal cost of disease: The public and private health cost of brucellosis in Mongolia is
less than half of the total cost of this disease to society. Using an animal-human brucellosis
transmission model linked to a cross-sector economic analysis, we could show that societal cost
of brucellosis is two to three times higher than the human health cost alone (Roth et al 2003,
Zinsstag et al 2005). The cost of livestock mass vaccination, as proposed for Mongolia, is much
higher than the public health benefits and the intervention would not be considered profitable
and cost-effective from a public health perspective alone. However, the full societal cost of
brucellosis, including the private and agricultural sectors show that the intervention costs are
less than a third of the overall cost of disease and the societal benefit-cost ratio is 3.2 (Roth et
al 2003). Such assessments are important in the search for ways to advocate the control of
zoonotic diseases in resource poor countries and could not be demonstrated looking only at the
public health or only at the animal health side of the disease.
Cost sharing: Assessing cost of zoonoses in multiple sectors opens the way for costsharing options, using for example a separable cost method. While brucellosis control by
livestock mass vaccination is not cost-effective (Forgot et al 2001) from the perspective of the
public health sector alone if the public health sector should bear the full cost, it becomes highly
cost-effective if costs are shared between the public health and agricultural sectors
proportional to their benefits (Roth et al, 2003).
Contribution of the framework to the One Health strategy and future
conceptual outlooks
The approach is in line with the “one medicine” concept by Calvin Schwabe which has
seen unprecedented revival in the last decade and has evolved towards “one health”
conceptual thinking emphasizing epidemiology and public health (Zinsstag et al, 2005).
Professional organizations have declared their adhesion, governments have created joint public
and animal health working groups, and numerous research and surveillance programs have
been initiated (Zinsstag et al 2009). Notwithstanding these beneficial developments, we should
not forget that there remains a huge divide between human and veterinary medicine born from
unprecedented (over)specialization of disciplines and increasingly reductionist approaches to
scientific inquiry. What is required now is a radical paradigm shift in our approach to global
public health, drawing on practical approaches and hands on examples to facilitate application
of the “one health” approach. The proposed framework to estimate the societal cost of
zoonoses is an open tool translating the “one health” concept into practical methods, which we
hope could serve as a discussion basis for mutually agreed practical cooperation between
human and animal health, with a special emphasis on developing and middle income countries
(Zinsstag, 2008). This proposed framework is in line with the “One health” strategy adopted by
the World Bank and other organizations The strategy was developed at the IMCAPI ministerial
conference in Sharm el Shaik in 2008, and further developed in Winnipeg 2009 and at the
IMCAPI Hanoi 2010 meeting. The One Health approach anticipates that important human
health and livelihood benefits can be expected from aiming effective interventions in animals
and behaviour change in humans. Currently, the “One health” has become part of a broader
integrated development research approache, relating to Social-Ecological Systems (SES)
(Ostrom 2007). Health of humans and animals is considered as an outcome of SES. Hence “one
health” concept evolves towards “Health in Social-Ecological Systems” (HSES) (Zinsstag et al.
2010).
Annex III: Proposed Framework
The aim of the proposed framework is integrate epidemiological and economic methods
of zoonoses assessment in developing and middle income countries to support a one health
approach. The purpose is to inform policy makers on options to reduce the risks and costs of
zoonotic disease while also minimizing the consequences to different socio-economic groups,
with particular attention on the poor.
Description
In a perfectly competitive market, the outputs of the goods and services of the economy
and the set of prices for these outputs are determined in the marketplace in accordance with
consumers' preferences and incomes, as well as producers' minimization of cost for a given
output. In this market, the outcome is efficient and social welfare is maximized. When it comes
to disease control there are often situations in which the conditions required to achieve the
market-efficient outcome are not present due to market failures. Under such situations
governments may choose to intervene to correct the market failure. Due to stochastic forces it
is not always clear how to intervene optimally.
With uncertainty involved in disease spread, control, and adoption of control measures,
decision makers are increasingly using analysis based on probability theory to aid them in
making informed decisions regarding regulatory actions to prevent (or reduce) the incidence of
disease. Risk analysis, a probability-based analytical approach, typically consists of hazard
identification, risk assessment, risk management, and risk communication. Risk assessment
involves the evaluation of the likelihood of entry, establishment, and spread of disease
identified as the hazard as well as the biological and economic consequences of the disease.
Risk management involves evaluation of how to best mitigate the risk and to determine the
cost to society of the action. Risk communication involves identifying ways to interact with the
public as stakeholders and inform them of risk findings so that their decisions can be
adequately informed. Typically, approaches tend to be generic, and do not specifically focus on
the impact of risk reduction measures on the poor per se, nor on the effectiveness of the
institutions to implement the control measures.
We propose to use a modified risk analysis framework seen in figure 3 to enhance the
control of zoonotic diseases so as to improve economic outcomes such as poverty alleviation,
food security and improved livelihoods. This modified risk analysis framework involves
understanding the demand for the reduced risk of zoonotic diseases, particularly in a
developing country context, and hazard identification; it involves conducting a traditional risk
assessment which includes the release assessment, exposure assessment, consequence
assessment and risk estimation; risk management, and risk communication. In the release
assessment all potential pathways for disease introduction are identified. In the exposure
assessment all potential pathway leading to exposure of the zoonotic diseases both in animals
and humans are identified. The modification from the traditional approach under consequence
analysis is that we propose to include an analysis of the impact on livelihoods at the household
level.
Further, the modification to the traditional approach under risk management that we
propose includes also analysis of stakeholders’ knowledge, attitude and perceptions, as well as
their willingness to pay for various control strategies. In addition we propose to include
behavioral experiments where appropriate to assess the uptake of intervention, i.e., of
identified cost-effective risk minimization technologies. Further we propose that the uptake of
interventions and the impact on livelihoods (e.g., income, health and nutrition) outcomes be
monitored through a monitoring and evaluation plan. Through the course of the work we argue
it is important that the research teams work with national partners so as to build their capacity
in epidemiology socio-economic data collection, risk analysis, livelihood analysis and behavioral
experiments as well as work with national partners to develop a comprehensive
communication and outreach component to encourage adoption of the interventions.
Outputs of such modeling efforts will enable decision makers to evaluate the costeffectiveness of various control measures and their combinations in reducing risk from a variety
of angles. Note, not all analytical tools mentioned need to be done at once, but the goal of this
framework is to set out the menu of potential types of analysis a decision makers may want to
use to help inform them in areas where they may need more insight prior to taking action. This
is important as decision makers are often faced with the problem of evaluating a “portfolio” of
mitigation techniques to obtain some desired level of safety (or maximizing safety for a given
cost). The strategy a risk manager chooses depends on the risk preferences of the affected
stakeholders and on their comparative advantage in implementing particular risk-reduction
options. Often, however, it is difficult for them to discern which is better because in one
analysis they are looking at a strategy in terms of risk reductions and in another analysis they
are viewing it in terms of costs and benefits. If they are not able to discern, decisions that are
well intended can lead to losses in social welfare as unexpected outcomes develop, or as
outcomes have unexpected consequences. Thus decision makers have a great need for a
framework which structures information in a way which makes the complexity more tractable,
but still takes into account the implications of the complexity.
Analytical approaches
A variety of tools can be used to provide insight as how potential control strategies can
reduce the risk of zoonosis. We suggest the following types of tools and data needs to
understand the impact of the control strategy, as well as to inform on how to go forward:
 Improved prevalence data collection in both animals and humans (underreporting in
many developing countries)
 Quantitative/qualitative risk analysis (risk mapping, risk assessment, cost benefit/cost
effectiveness analyses-Daly analysis, dynamic disease transmission modeling)
 Livelihood impact analysis
• Qualitative approaches (participatory poverty assessment, focus group
discussions, etc.)
• Nutritional and household level impacts
• Demand and supply estimation
• Market modeling (internal and external effects on trade)
 Value chain and institutional analysis
 Analysis on knowledge, attitude, perception, and practices and willingness to pay
 Expert elicitation
 Experimental and quasi-experimental methods
Table 1 summarizes the types of analytical methods that can be used, their uses, and
the associated data needs. We recognize that each of these proposed approaches have
resource issues associated with them and suggest that not all of these need to be done at once.
The framework provides an approach that countries can build on so to ensure that the analyses
are integrated from the beginning, rather than at the end trying to understand how different
types of analysis fit together in an effort to make a decision.
Figure 3: A Modified Risk Analysis Framework to Enhance the reduction of Zoonotic Diseases
Table 1. Research methods to assess zoonotic issues
Methods/ Approaches
Improved prevalence data
collection in both animals and
humans (underreporting in
many developing countries)
Quantitative/qualitative risk
analysis including risk
assessments, risk maps, cost
benefit/cost effectiveness
analysis-Daly analysis,
dynamic disease transmission
modeling
Uses
To help policy makers make informed decisions;
To identify and describe the nature of the hazard, and quantify
the probability of its harmful effect to individuals or populations;
to evaluate the safety of food production systems and decide on
strategies to protect consumers;
To understand the risk-risk tradeoffs of the various prevention
methods; to assess the benefits and costs of food safety
regulations;
Data Needs
Information on the nature and effects of hazards
identified;
Disease/pathogen occurrence, prevalence and
concentration, pathways of exposure, and
consequences and how it differs by size of
producers/actor;
Direct and indirect economic costs and benefits
of interventions; sales and net revenues, and
how it differs by size of producers/actor;
Econometric methods
To measure the production, productivity, profitability, income
diversification, and poverty impacts;
To measure the compliance costs of food safety regulations,
To assess the impact of public-private partnership and collective
action to ensure reduction in disease risk
Household survey data taking into consideration
inter/intra household differences, as well as
gender differences in determinants; agricultural
statistics data; detailed costs and revenue and
input data
Value chain and institutional
analysis
To understand the entry points of risk along the value chain and
to assess the kind of control mechanisms that would be suitable
for different actors along the value chain;
To identify bottlenecks and constraints, market failures and
coordination problems;
To identify opportunities and constraints of institutions involved
in implementing and monitoring disease regulations,
To understand the role of PPP and collective action in enabling
smallholders to overcome constraints
Costs and returns at each stage of the value
chain; characteristics of specific
flows/linkages/transaction mechanisms/actors
along the value chain (including flows and
linkages of information and services).
Livelihood analysis
To understand the contribution of disease shocks/costs of control
mechanisms to income/nutrition/ household health to economic
well-being to different size producers and consumers;
To determine the effect of zoonotic diseases on poor households’
Household expenditure and consumption survey
data, paying attention on inter/intra household
differences as well as gender differences in
determinants and outcomes; dietary intake
livelihood outcomes and nutrition.
surveys, baseline nutritional status, biomarkers
of micronutrient status; clinical measures of
bodily attributes (anthropometric data
Demand and supply
estimation
To simulate how disease safety shocks and threats affect the
demand for food and how these shocks and threats affect
farmers’ production decisions.
Food balance sheets; commodity prices,
incomes, expenditures, elasticities of supply and
demand in response to price changes due to
disease outbreaks (or other shocks).
Partial equilibrium/multimarket -sector specific models
To simulate the impacts of risk reduction policies on the
agricultural sectors and the potential poverty and distributional
effects.
Data on production, consumption, prices,
expenditures ( incomes), factor inputs, imports
and exports
CGE (economy wide) models
To simulate the impact of global risk reduction policy changes and
the domestic policies adopted in response on economic growth
and poverty.
Nationally representative household data paying
attention on inter-household differences as well
as gender differences in determinants and
outcomes
Analysis on knowledge,
attitude, perception, and
practices and willingness to
pay
To understand what is driving peoples behavior
Data on knowledge, attitude, perception, and
practices and willingness to pay
Experimental and quasiexperimental methods
including stated and revealed
preference methods and
behavioral experiments
To capture the consumers’ demand for reduction in disease risk
and producers’ demand for different control mechanisms to
provide safer food;
To understand the acceptability or adoptability of interventions
or technologies or policies; to assess the economic impact of
interventions
Baseline and after intervention surveys;
household demographic characteristics, direct
and indirect costs, income, yield, health status,
hygiene and sanitation practices, observable
facts, knowledge, attitudes, and perceptions,
consumer and producer welfare
Other qualitative approaches
such as participatory poverty
assessment, focus group
discussions, etc.
To complement quantitative data analysis
Knowledge, attitude and perceptions taking into
consideration gender differences in perceptions,
motivations, and behavior
a. Integrated assessment of incidence / prevalence
Estimating the cost of zoonoses requires knowledge and understanding of the frequency of
their occurrence in a local ecosystem. This requires some form of interconnected assessment in
humans and animals. For example, for Echinococcosis we would want to understand the
frequency of occurrence in sheep/goat – dog – humans, for rabies we want to know the
frequency in dogs and humans, or for brucellosis we would measure disease frequency in
cattle, sheep, goat and humans. If multiple zoonoses exist in a given context, all above
mentioned examples could be combined for surveillance and control. But this depends on the
effective epidemiological situation in a given context. The general principle, which is new here,
is that we do not restrict the sampling to humans or animals, but sample both together,
depending on the local epidemiological situation.
b. Official reporting systems and estimation of under-reporting
Official surveillance and reporting systems exist for humans and animals in most
countries and are also more and more connected, for example by the GLEWs database (cited in
Zinsstag et al, 2009). Most of the disease surveillance systems are passive, which means that
they record reported cases and usually underreport the true prevalence. However in many
countries, mostly of the former Soviet Union, mass sampling for blood testing happens on
yearly basis, for example for brucellosis. This is done in view of culling of infected stock, which is
most often not sufficiently enforced. If mass sampling is done for reasons of surveillance, it
should be urgently modified by modern epidemiological methods based on cluster random
sampling. Modern active surveillance study designs are less costly and use much smaller sample
sizes with an acceptable precision.
c. Comprehensive cost of disease assessment
Often analyses when estimating the cost on society look at the impact of diseases at
either at economy wide, sector level, or household level alone without fully looking at the full
impact on society both in terms of public and private costs. Further, studies tend to either look
at the impact to the livestock sector or the impact on the health of humans. Lack of a
comprehensive understanding makes it difficult for public authorities to mobilize resources in
an effective way, as resources for disease control compete with other public interests,
particularly in a transitional country context. We argue there is a need to estimate both to get a
full picture of the cost to society.
d. Behavior and assessing the adoptionof an intervention
Having the analysis done that will not necessarily result in change. In addition to
understanding cost, it is also important to understand people’s knowledge, attitude, and
perceptions about a zoonotic disease, and to understand if the intervention actually results in
behavioral change. In addition there is a need to understand what amount people are willing to
pay to implement control strategies, or accept in terms of compensation so as to alter behavior.
This will serve to identify what may be efficient and effective solutions for reducing the risks of
zoonotic disease along value chains. Surveys can be developed to randomly interview a
targeted population about the potential benefits of risk reduction measures and the benefits of
adoption (increase productivity, reduce animal and human negative health outcomes). The
respondents can be invited to participate in a hypothetical market in which they are asked
about their willingness to pay to purchase the control measures. This is important as there may
exist control strategies to reduce the risk that are not currently in use in many transitional
countries, making it difficult to estimate the value of economic benefits of these control
strategies from health, production and market data. Lastly, behavior experiments on
interventions are needed to understand what really works on ground. We thus propose in the
countries where we evaluate the cost and benefits and effectiveness of various interventions
that randomized trials of specific zoonotic control mechanisms be done in addition to use of an
educational package aimed at subsistence farmers, incorporating a cost-effectiveness analysis
and the impact on human and animal health. This can later be followed by a monitoring and
impact evaluation to determine the adoption levels and the impacts on human and animal
health. Such experiments would include randomized selection of possible treatment and
control villages. In the treatment villages we will provide the educational package, and could try
a variety of different ways of presenting the information. The educational packages could then
provide information on the possible interventions to minimize the presence of a zoonotic
disease. Given the focus is on finding solutions for the poor, we suggest that the interventions
tested should focus on low and medium cost interventions, and promote the use of those
through the educational packages. Information on the more expensive alternatives would also
be included. The interventions considered will be based on a cost benefit and cost effectiveness
analysis study.
e. Financing of interventions
As mentioned above, a primary motivation for the proposed integrated framework is to
assess the full societal cost of disease of zoonoses. This is a first step in the analysis of options
for locally adapted intervention strategies. In this way government authorities are informed on
the financial feasibility of the control of zoonoses and can pave the way for sound negotiation
of their financing between the public and private sector (see point c) and looking toward
promoting public/private partnerships.
Annex IV Impact of zoonotic diseases on society
Over the last decade, a desire to reduce the potential of sick animals transmitting
diseases to humans has intensified with an increasing number of reports of zoonotic and
foodborne diseases originating from animals that do not necessarily cause visible signs of
disease in carrier animals (E.g. Echinococcosis in sheep or Cysticercosis in pigs, Salmonella and
Campylobacter in poultry are most often seen only at meat inspection). Some of the reasons for
the increasing interest in zoonotic diseases are thought to be: 1) alteration of the environment
affecting the size and distribution of certain animal species, vectors, and transmitters of
infectious agents of humans; 2) increasing human populations favoring an increased level of
contact between humans and animals; 3) industrialization of foods of animal origin causing
changes in food processing risks and consumer nutritional habits; and, 4) increasing movements
of people as well as trade of animals and animal products and decreasing activities for the
surveillance and control of major zoonoses (Meslin, 1997). These diseases place a heavy burden
on the poor who may lack information regarding the risks and often lack the access to
institutional support to aid them in controlling the diseases. Though there are a number of
ways to assess the impact of zoonoses on society this assessment depends on how the different
involved parts are valued. I. While estimating human health cost is comparatively straight
forward, valuing human life is controversial and an ongoing debate. For the estimation of the
impact of zoonoses on human health, we adopt here the approach of the World Health
Organization, using the method of estimating the disability adjusted life years (DALY). This
approach aligns our work with ongoing assessments of the burden of disease worldwide and
allows estimating the proportion of zoonoses in the global burden of disease. Ultimately this
proportion should be one of the strongest elements for the advocacy for investment in
zoonoses control in the human health sector but has been combined with other parameters to
provide for a more comprehensive analysis.
Zoonoses affect the lives of animals and can affect productivity. Rabies kills dogs,
livestock and wildlife. Brucellosis causes abortion and peri-natal death. Bovine tuberculosis
reduces animal well being by respiratory impairment. Animals are valued in different ways in
different cultures. A dog can be completely neglected and have no emotional or monetary
value in one country, while pet owners would spend thousands of dollars on feeding and
veterinary care in another country, or dogs would be fed in the street and protected because of
cultural and religious beliefs in a third country. Dogs are also work for specific tasks, such as
dogs for the blind, or police dogs. A framework for impact assessment of zoonoses on society
should be flexible to be contextually adapted and reflect the cultural perspective of the
investigator. In the following, we recognize the cultural and religious views on animals. While
we recognize different view points on valuing animal life, we will use here monetary value for
the effect of zoonoses on livestock, pet animals and wildlife.
The effect of zoonoses on society can be in terms of the burden of human disease which
can be expressed as the loss of DALYs and the cost of disease to the livestock sector, which can
be expressed as the income loss associated with either productivity or production losses due to
illness or death of animals plua all other costs – trade losses, food safety, tourism impact ant
others.
Human health risks of zoonoses
Government health information systems (HIS) and disease surveillance systems include
the reporting of zoonoses (World Health Organization, 2008). These depend on local casedefinitions which differ between countries but, for example, there exists no internationally
recognized standard for the reporting of new brucellosis cases. Many countries don’t have
laboratory capacity for routine diagnosis of brucellosis or bovine tuberculosis. Such diseases are
then mis-diagnosed or underreported. For example brucellosis can be clinically confused with
malaria or typhoid fever, Rift Valley fever is confounded with yellow fever, and bovine
tuberculosis is, in general, indistinguishable from human tuberculosis (Steinman et al and
Digoutte, 1999). Further, some diagnostic tests like rabies are only established in capital cities
because they require sophisticated fluorescent microscopy. Consequently, very little is known
about the incidence of disease in provincial towns and rural areas (Cleveland, 2002). Even if
well established country-wide disease surveillance and HIS are in place, official reporting
systems tend to underreport the true incidence of zoonoses for the above reasons. Hence, a
first step towards the assessment of the cost of specific zoonoses requires a case definition
which is recognized by the World Health Organization (WHO) and the international statistical
classification of diseases and related health problems (ICD-10). Diagnostic capacity, including
serological and culture facilities should be established in central, provincial and possibly district
laboratories including a quality control system, which assures the validity of diagnostic test
capacity. An estimate of the true incidence or prevalence can be obtained from representative
cluster sampling surveys proportional to size (Bennett, 1991) which are related to the official
reporting. In this way levels of underreporting can be estimated and the true incidence can be
extrapolated. At best, such representative surveys should be done at the national level. Against
common concerns, such surveys involve a few thousand samples and cost less than 100’000
US$ for medium sized countries (Zinsstag et al, 2009).
Knowledge on the local spectrum of zoonotic diseases essentially guides human health
risk assessment. We present here specific risks along the above examples: Human health risk
from brucellosis should be assessed for urban and rural populations likewise. Urban
populations may be more at risk from consumption of unpasteurized milk and milk products
(fresh goat cheese) from informal markets. Rural populations are subject to a double risk form
of occupational exposure (farmers, farm workers, veterinarians, butchers, livestock traders) and
from consuming of milk and milk products. In a very similar way human health risk from bovine
tuberculosis can be related to occupational (mostly intensive dairy in peri-urban areas) and
consumer exposure (milk and milk products). Human health risk from Anthrax is occasionally
related to the consumption of infected animals, but most often fromskin contact with
contaminated hides (cutanous forms), wool and hair (pulmonary and generalized symptoms in
wool factories). Human health risk from Echinococcosis is related to fecal-oral transmission
frominfected dog (Echinococcus granulosus) and fox faeces (Echinoccocus multilocularis) in
rural and urban areas. Human health risk from rabies arises from exposure to bites from rabid
dogs, cats and occasionally wildlife. We can thus summarize host species related disease cluster
such as the small ruminant cluster (brucellosis, echinococcosis), a dog cluster (echinococcosis,
rabies) and a cattle cluster (bovine tuberculosis, brucellosis, anthrax). Similar clusters can be
defined for pigs (trichinellosis, cysticercosis) or poultry (salmonellosis, campylobacterosis, H5N1
influenza virus). In depth understanding of local disease ecology of such disease clusters are the
backbone for developing integrated “one health” assessment approaches.
Human zoonotic infection is manifested by acute illness (rabies, anthrax, brucellosis)
and most often by chronic forms (echinococcosis, bovine tuberculosis, brucellosis), sequelae
such as permanent disabilities and death. The clinical picture of human zoonotic infection is
well known and described (e.g. for brucellosis (Madkour (2001), but none has been so far been
part of the official burden of disease assessments in terms of disability adjusted liveyears
(DALYs) lost. However, first estimates exist for rabies (Knobel, et al 2005). echinococcosis
(Budke, et al, 2004, Budke et al, 2006, and Carbin et al 2005) and brucellosis (Roth et al, 2003),
at the global level or for individual countries. Work is ongoing to include them in the global
assessments by WHO.
Economic impact on involved sectors
Zoonotic disease can have socio-economic impacts in terms of both health and income
consequences. The extent of the economic impact depends upon the economic size of the
sector and its linkages with other sectors, including effectiveness of the existing institutions to
monitor and reduce the risk of a disease and the costs associated with implementing control
measures. Diseases have both demand and supply effects and a disease does not necessarily
have to occur to have economic impacts; fear of a disease can also have supply side effects.
Costs associated with control efforts can impact stakeholder’s behavior in terms of controlling
disease. For instance, the cost of improved biosecurity or compensation efforts can affect
profitability and the incentives of farmers or other actors along the value chain to respond. The
disease can also economically affect the institutions established to control the diseases as well
as the environment in terms of disposal costs. It should be noted, however, that for an
assessment of the impact of a specific zoonosis on society, the involved sectors are determined
by the ecology of disease of the specific zoonosis. Below we discuss each of these areas in more
depth.
Economic impact of Health consequences
Disease can result in increased mortality and morbidity in livestock and human
populations. Disease may affect an animals’ performance through reduced fertility, delays in
reaching maturity for reproduction or sale, decreased production of milk, eggs, or wool,
decreased draught power, or decreased weight of fattening or cull animals. The long-term
effect of these outbreaks can be extremely costly when the result is depopulation,
compensation of producers, disease elimination, or potential loss of a country’s export market.
In the past, countries have justified efforts to eradicate diseases of food animals based on the
argument that such efforts serve either to increase productivity or eliminate from the food
supply sick animals that may transmit diseases to people. For instance the net economic
benefits from controlling animal disease have been very cost-effective, ranging from a 200
percent to 1,500 percent return on investment (Morris, 1999).
The economic impact of zoonoses on human health requires a disease specific
assessment, but can be separated into three main components: Public cost, private costs and
private coping cost. Public cost of zoonoses is composed of the use of public health facilities as
inpatient and outpatient cost, depending on the extent of public funding of those. Private
health cost is composed of transport cost, laboratory fees, drug cost, doctor’s fee and hospital
cost. Many patients use also informal medical care (traditional healers) for which they have to
pay too. Patients have additional cost from income loss and coping cost, which is the cost of
employment to perform work which the patient can no longer do.
Livelihoods impacts
Zoonoses affect agriculture directly by reduced livestock productivity and indirectly by
reduced crop productivity if animal traction is important. Costs occur from animal disease
surveillance and veterinary care. Further cost is expected from trade bans because of
communicable diseases like brucellosis or bovine tuberculosis (see below). Of particular
importance are diseases that affect the reproductive capacity of livestock. A reduction in
fertility reduces not only the offtake of meat and milk, but also the number of live animals,
which represent an asset value. Livelihood impacts also arise if there are impacts on household
health and associated coping cost when a household member is ill or has died from zoonoses.
Further impact is caused by losses in livestock production, or sales ban, death and replacement
cost for draught and production animals.
Health impacts on livestock which result in reduced output or death in animals can in
turn also have impacts on livelihood outcomes. Both of these can reduce income and food and
affect nutritional security. Such losses also have an impact on the value of livestock assets, i.e.,
household wealth from livestock which can affect savings, insurance, gender equality (Birol
2008). In rural areas where credit markets are missing, livestock functions as ‘insurance’ to
hedge against shocks and stresses (Binswanger and McIntire 1987; Rosenzweig and Wolpin
1993). Livestock also contributes to household nutrition, as many rural poor households rely on
their own production to supply animal source foods that can provide protein and a variety of
essential micronutrients such as iron, Vitamin A and zinc (Iannotti et al., 2008). Chronic
malnutrition and micronutrient deficiencies are very high in developing countries (Quinn et. al,
1990; Callens and Phiri, 1998) and hence livestock is particularly important for child nutrition
and health. Finally, livestock production is important for empowering women and promoting
gender equality in developing countries where livestock are mainly owned and/or managed by
women. Livestock provide them (as well as those they look after including children, elderly and
the invalid) with livelihoods (nutrition, food security, income, wealth, and consequently
empowerment) and hence contribute to gender equality. Control options are not without cost
and can effect profitability such that not all households may be able to afford nor have the
incentive to implement the more costly measures. Zoonotic diseases are therefore expected to
have negative impacts on the rural poor households’ livelihoods indicators, especially on those
pertaining to income, food needs, nutritional security, and gender equality. A review of the
literature on economic impacts of transboundary animal diseases reveals that rural poor
households in general suffer greater impact when disease outbreak occurs (FAO, 2002; Otte et.
al., 2004; 2006; FAO, 2008).
Sector and economy-wide impacts
The disease itself has impact on the specific livestock sector(s) affected and through its
linkages on other sectors (see Roy, 2009 for a more extensive discussion). At the sector level
which focuses on poultry production the impacts can affect the feed and other input sectors
such as vaccines through decrease demand in feed and possibly increase expenditure on
vaccines. At the economy-wide level impacts are felt at both the inputs sector as well as other
outputs sectors such as restaurants, hotels, and markets. Market impacts would include
impacts on trade and tourism. Efforts to control diseases mentioned earlier have resource costs
and depending upon the extent of allocation or reallocation of resources that it entails and the
strength of inter-linkages of the livestock sector, there will be economy wide impacts also
associated with zoonotic disease control measures. In addition impacts can be felt at the
institutional level depending on the infrastructure in place amongst the animal and human
health sectors (including the veterinary service and food safety agencies if separated) and the
coordination amongst them in terms of monitoring for disease so as to ensure food and animal
safety.
Environmental impact and associated costs
Environmental effects can be multiple. Disease related trade bans, for example,
currently lead to an accumulation of animals in Mongolia, exerting increased pressure on
pasture ecology. Such indirect effects are difficult to measure. Bovine tuberculosis has been
introduced into the Krüger National Park in South Africa and is now found in ruminants and in
large predators. Ecological consequences of changing predator-prey equilibria can have
unpredictable consequences. They can affect endemicity of rare species and biodiversity as a
whole (Davidson et al, 2002). Such events can hardly be generalized and are singular events in a
given context. In this report we will limit ourselves to highlighting these issues. (In addition
there can be costs of preventing environmental impacts associated with disposal of dead and
culled animals.
Communication and public awareness
Risk awareness is central to risk behavior towards zoonoses. Lack of knowledge of postexposure treatment of rabies is an important cause for human fatalities. In the same way, lack
of knowledge on handling animals killed by anthrax or aborted fetuses from brucellosis, or lack
of knowledge in meat inspection for bovine tuberculosis may lead to human exposure, illness
and death. Education [Enhanced awareness] is a highly important collateral measure which
must be part of any intervention strategy. Its cost is part of the interventions cost. Costeffectiveness can be measured as the ratio of reduction of disease incidence per degree of
knowledge and behavior change.
Annex V: Rationale for intervention for controlling the risk of zoonoses
With regard to zoonotic disease and the ability to have successful control efforts there are
three types of information problems. First, there often is incomplete information where basically
the strategies and payoffs of the agents are not known and without information being complete
the agents cannot be acting rationally. Secondly, there may be imperfect information such as
the actions of players are not known. Lastly, there may be asymmetric information where one
party has more information than another party. Broadly this could relate to hidden action
(moral hazard) or hidden type (adverse selection) problems.
Based on these concepts information economics provides a powerful tool in case of
arguing for interventions/mechanism designs to correct the market failures surrounding efforts
to combat zoonotic diseases. Below we list a number of potential information problems
surrounding the control of zoonotic diseases:
(i)
Problems arising from lack of information that there is a zoonotic disease concern
that can affect humans due to poor surveillance. – The agents do not know the
state, hence a case of imperfect information. With imperfect information, rational
behavior itself can be difficult and outcomes can hence be sub-optimal. There can
also be incomplete information regarding strategies and payoffs about different
players who together determine the occurrence or transmission of the disease.
(ii)
Problems arising from lack of credibility of institutions to diagnose the problem in
animals, thus limiting selling the idea to stakeholders along the value chain that
there is a problem (asymmetric information) – In interaction of livestock keepers
and those who test for disease status there is information asymmetry. The testers
presumably know that they have done the checks right or wrong. With information
asymmetry, the informed party has to signal that their tests are “high type”. In order
to signal, credibility is most important. Additionally there are moral hazard issues
with the contracts to testing agencies not being implemented with optimal effort in
the absence of monitoring.
(iii)
Adverse selection problems relating to the information asymmetry where livestock
keepers know the disease status and the public agencies do not. If incentives are not
right then this information may be concealed. Most likely mechanisms need to be
designed that results in screening i.e. the uninformed party (the agencies) create
systems where livestock keepers reveal the disease status.
Any safety or quality attribute requires different agents to exert efforts along the supply
chain. This applies to case of animal disease as well. With no direct correspondence between
the effort and the outcome (with stochastic factors playing a role), moral hazard issues exist
along the chain. Moral hazard problems exist as one cannot assume that producers/other
agents if they knew they had a sick animal would do the right thing and make sure the
potentially infected product gets out of the food chain. Smallholders in particular may be
disproportionally have limited access to information regarding zoonotic diseases, ways to
control for them, and assuring buyers that they are controlling for them due to transaction
costs. More specifically transaction costs are the costs of exchange that arise from asymmetries
across market actors in access to information and assets. If both buyers and sellers can easily
ascertain the quality of the item being sold at the time of sale and prices in alternative markets,
there are no asymmetries in information and the transactions costs of exchange are low.
However, if buyers cannot be sure of the true quality of the good they are purchasing, they will
be less willing to pay a premium for it based on claimed quality.
In principle when there are problems as described above government can intervene to
minimize such information problems. Similarly interventions could be suggested to correct for
market failures owing to externalities. Agents “capture” benefits from negative externalities if
they get a benefit (e.g. livestock sales), but someone else bears part of the cost (disease, odors,
polluted water, disease etc.). Agents “internalize” at least part of these negative externalities to
the extent that they themselves suffer from these ills, and also if they incur expenses to
compensate those who bear the cost, or to prevent the adverse side effects. Imperfect
information and asymmetry of information consumers are only partially aware of the hazards
and thus are unable to trade off the risks associated with the production of the good in an
informed way. If government is unable to correct for these problems, society bears the full cost.
Public good debate of zoonoses; State vs. public-private partnership
interventions
Though zoonotic diseases are communicable between animals and humans they are
typically transmitted among wildlife, livestock and pets without necessarily cycling through
humans. Attempts to control zoonoses in humans by treating exposed or diseased humans
won’t affect the transmission dynamics in humans. E.g. treating human brucellosis patients with
antibiotics will not reduce the risk of infection for humans. Rather the risk for infection to
humans needs to be reduced through behavioral change such as reducing exposure or through
interventions in the animal host. Thus threats from zoonoses cannot be eliminated without
successful interventions in animals. This linkage of interventions between humans and animals
requires coordination of activities between human and animal health sectors.
Government activities regarding zoonotic diseases typically include surveillance (both
animal and human), restrictions on movement of animals (at times humans) across internal and
external borders, destroying livestock, requiring at times vaccination and serological testing, as
well as research and development on the control of diseases. These activities are pervasive and
important and have large budget costs, but governments often are willing to invest as research
has documented the large benefits associated with increased productivity, lower costs of
production, improved food safety, reduced human health threat (Sumner 2003). For resourcepoor countries at risk of initial outbreaks, given the emphasis on timely and efficient
containment operations, investments may be needed in containment measures that can
address a wide range of scenarios of infectiousness (Dutta 2008) and diversity of types of
producers. In addition, there are many institutional challenges that many developing countries
face as they attempt to control zoonoses, including limited veterinary infrastructure, lack of
coordination between veterinary staff and local communities, inadequate funding and devolved
authority for veterinary services, which can cause difference in control policies even within
small administrative regions (Sims, 2007). In addition, public health and animal health efforts
tend to be separated from public health authorities focusing exclusively on interventions in
humans. Further, the private sector including producers, private veterinarians, and traders
tends to focus on areas where they can get economic returns.
Though the above clearly demonstrates the need for the human and animal health sectors
which encompass both the public and private sector to work together, this is not always done due
to market failures and externalities discussed above, as well as public sector resource and
credibility constraint situations. Public-private partnerships (PPPs) can play a key role in
mobilizing resources and creating such links within the sector, particularly for small producers
who may otherwise be limited in their ability to access key resources that traditional
institutions are set up to provide, such as monitoring for disease etc. Though there is a wealth
of information on the potential role of PPPs in supply chains (see Boselie, Henson, and
Weatherspoon 2003; Hartwich, Janssen, and Tola 2003; Duffy and Fearne 2004; Hartwich,
Gonzalez, and Vieira 2005, Rich and Narrod 2004), few studies have looked into the role of
PPP’s in providing some of the traditional institutional needs that the public sector currently is
not providing in developing countries, such as disease surveillance in both humans and animals.
The general argument for PPPs rests on the idea that partnering allows actors to pool
resources and risks towards investments in research and innovations in a manner that achieves
mutual benefits in ways that would not be possible without the partnership (Rich and Narrod,
2003, Hartwich, Gonzalez, and Vieira 2005). In the presence of market failures where some sort
of intervention is required, PPP’s often have an advantage over pure public intervention in that
they bring forth the best aspects of private sector involvement (namely, an orientation towards
efficiency and optimal resource use) with the social welfare aspects of the public sector
(Spielman and von Grember 2003).
Difficulties in intervening to correct zoonotic problem in developing country
case
Zoonoses have been largely eliminated in industrialized countries by massive state
funded interventions. These means are not available in most of the developing countries. New
ways for financing of zoonoses control have to be identified depending a) on the specific
disease and b) on the context in which a particular disease is to be controlled or eliminated.
Durr et al (2008) have found that livestock owners in Chad are willing to contribute to pay for
anthrax vaccine in livestock, provided the vaccine is of good quality. On the other hand, dog
owners in N’Djaména, Chad are hardly willing or able to contribute to dog rabies vaccination
(Figure 2) and a sufficient coverage to interrupt transmission seems not to be reachable if the
vaccination cost for dogs is not free of charge.
Figure 2: Vaccination costs in N’Djaména
Figure 2: Average probability of having a dog vaccinated against rabies by charge for
vaccination: observed versus owner-stated values for vaccination.
The observed values of charges to vaccinate an owned dog against rabies and
probability of vaccination came from 3 sources. Points A and B (recording vaccination coverage
for all owned dogs vs. costs charged) come from 2 vaccination campaigns held in N’Djaména in
2002 and 2006, respectively. Point C represents the midpoint of the range of recorded 2001
clinic charges in N’Djaména for vaccinating a dog against rabies (costs not adjusted for any
potential inflation). The owner-stated amounts that they would be willing to pay for their dogs
to be vaccinated against rabies came from a survey of 356 households, conducted in 2006. The
graph shows the reverse cumulative probability of the stated values (Durr et al 2008).
Financing the cost of zoonoses control requires negotiation of acceptable risk between
communities and authorities (Zinsstag, 2007). Good information on the economic and health
consequences of diseases may open up new ways of how communities would deal with them
and possibly about their willingness to contribute to the cost of control. Another line of private
involvement is by corporate engagement through value chains for food commodities. It is of
vital interest to the food industry to be provided with disease free animals source food.
Another difficulty facing developing countries is that animals are often affected by
multiparasitism (Zinsstag et al 1998) and multiple communicable diseases in the same time.
Interventions against zoonoses should be coupled with other interventions to save scarce
human and financial resources. For example, regular vaccination campaigns against contagious
bovine pleuro-pneumonia, (CBPP) or foot and mouth diseases (FMD) could be coupled with
vaccinations against brucellosis or anthrax, provided there is no negative effect on crossimmunity. A specific package depends on the prevailing animal disease spectrum and ongoing
interventions. Clearly, multiple interventions against multiple diseases applied during a single
farm visit are more profitable as only the marginal cost to an additional vaccine or drug adds to
existing logistic and personnel cost.
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