Burden of Disease Estimates for 2011 and the potential effects of the Essential Health Package
on Malawi’s health burden
Burden of Disease Estimates for 2011 and the
potential effects of the Essential Health Package on
Malawi’s health burden
Introduction
An evaluation of the essential health package (EHP) using WHO Burden of Disease (BOD)
methods suggests significant health gains were made by the first EHP associated with the first
SWAp [1]. An economic appraisal of the second EHP associated with the Health Sector
Strategic Programme (HSSP) is a useful tool to help make priorities and choose best buy
interventions. This appraisal can use various approaches. One approach is to build on previous
work based on Malawi’s Burden of Disease as measured by Disability Adjusted Life Years
(DALYs). Various assumptions and adjustments are required because of the shortage of vital
statistical data. This paper describes the methods used in updating the BOD estimates and how
they have been applied to the proposed HSSP.
Methods
2011 Burden of Disease
The estimates of the BOD are the foundation of later analysis. The 2002 WHO estimates for
Malawi were assessed in 2004 and found to be robust [2]. These estimates were updated in 2008
and used in the evaluation of the EHP [1]. WHO is in the process of updating their estimates,
using funding from the Gates Foundation, but these are not yet available. The 2002 estimates
have been used to update the Malawi estimates for this study. The following approach was used:
1. Age specific mortality rates were calculated from the 2008 census providing best estimates of
current infant, child and adult mortality (including females of reproductive age) using
National Statistics Office (NSO) published life tables created using INDEPTH
methodology. Actual deaths for 2011 were estimated using the specific death rates and 2011
population figures.
2. NSO population projections published in November 2010 were used.
3. Incidence rates of the 159 conditions that make up the BOD model have been assumed to
remain as in 2008 except for:a. HIV/AIDS where incidences of HIV and AIDS have been taken from the 2010
SPECTRUM projections used by the MOH HIV Unit.
b. Hypertension and diabetes disability levels increased to reflect results of STEP study
for disability but not mortality (because the natural history of these conditions is
unknown in Malawi).
4. Important diseases causing a heavy burden such as malaria have been assessed using recent
survey data and found to remain similar to those used in 2008.
Potential Burden averted by the EHP
The EHP2 updated model containing the new interventions such as mental health has been used
to calculate the incidence and burden (in DALYS) of preventable or treatable conditions chosen
in the EHP.
Assumptions used to predict the resource based and the ideal budgets
1. The ideal scenario budget uses the following assumptions:a. Indirect costs are based on expert MOH groups looking at
i. HR – not staff establishments which are being revised, but current staff
levels, attrition rates and recruitment rates based on planned pre-service
outputs
Burden of Disease Estimates for 2011 and the potential effects of the Essential Health Package
on Malawi’s health burden
ii. Infrastructure – based on a survey of health facilities – their location for GIS
analysis, their level of amenities such as water and electricity and their
functional equipment
iii. Transport based on planning assumptions about ambulance requirements –
1:50,000 etc.
b. Direct costs are derived from the cost-model assuming all targets are met. Access is
100%.
c. The overall apportionment of EHP to non-EHP costs assumes
i. Same split as between central hospitals and other cost centres with HQ costs
split 25% non-EHP and 75% EHP between 2002/3 and 2009/10 which were
84% EHP and 16% non-EHP.
ii. The apportionment does not change over the 5 years. This is because while
pressure to offer tertiary services such as the cancer centre arises from
medical advances and the profession, pressure is equally coming from the
HSSP and the need to hit EHP targets.
iii. This effects only direct costs as indirect costs are apportioned between EHP
and non-EHP services on the basis of location of cost centres:1. All central and 25% of HQ HR goes to non-EHP
2. All CHAM and district HR goes to EHP
3. All central and 25% of HQ other indirect costs goes to non-EHP
Assumptions used in the cost model for this exercise
The MOH cost model used for the first EHP has been adapted by the Ministry of Health
(MOH) for EHP2. The costs have been revised. Staff numbers have been revised to
accommodate recent revisions of the staff establishment. A number of assumptions have been
used to derive the activity estimated from the model under different funding scenarios. They
are:1. The model has been calibrated using 2009/10 activity based on HMIS data and 2010/11
estimated costs. The model over-predicts costs by 27%. This is due to drug and staff
costs being less than predicted by the model because of staff absences and drug stockouts. The effect is that activity over-predicts beneficial effect by some 20%. The model
has been re-calibrated to take this into account. It is assumed that as staffing levels
improve (as the Emergency HR plan increases pre-service outputs) and drug
procurement and supply becomes more reliable, the resource based scenario will improve
effectiveness to 90% of attendances and the ideal scenario to 100%.
2. The core scenario used is based on the MOH resource based estimate of budgets in
2011/12 and 2015/6. It is assumed that 75% of HQ activity is to do with the EHP and
the remaining 25% other non-EHP activity, and that central hospital indirect costs
including staff costs are non-EHP but that all district services are EHP. It also assumes
that the overall proportion spent on tertiary services of government budget stays as it
was on average and stable between 2002 and 2009 at 16%. This clearly is an imprecise
way of allocating the costs between EHP and non-EHP. For instance 70% of central
hospital services are primary or secondary level care and staff time has been allocated
only to non-EHP services. On the other hand all CHAM and MOH District level and
below HR costs have been allocated to the EHP although a proportion of their work is
non-EHP (perhaps 10% in MOH and 20% in CHAM institutions).
3. The second scenario is based on an ideal estimate – all the funds required to implement
the HSSP fully. This is based on an assessment by MOH expert groups looking at the
indirect costs of HR, infrastructure, transport and equipment. For instance for HR they
took the current staffing levels, adjusted for attrition and new recruits coming out of preservice institutions to estimate the level of staff available in year 5 of the plan. The
infrastructure costs are based on the building needs required to offer BEMOC access
(8km) to over 95% of the population. Direct costs are derived from the cost model
Burden of Disease Estimates for 2011 and the potential effects of the Essential Health Package
on Malawi’s health burden
4.
5.
6.
7.
which calculates the number of patients required to receive the EHP intervention at the
target level and their associated costs.
By 2016 the effectiveness of patient care is assumed to have increased from 80% to 90%
for the resourced based EHP scenario as facilities are better staffed and stock outs are
less. The ideal scenario is assumed will achieve 100% staffing and no stock outs.
Access improves in both scenarios. For the resource based scenario from an access level
of 65% access in 2011/2 the plan is to build new or upgrade dispensaries by 58 – 28% of
the ideal level (206) required to provide 8km access to over 95% of the population – the
BEMOC target. It should be noted that this 95% target has not been checked using GIS
but will be in the next 6 months. The 28% increase planned for the resource based
scenario improves access to 75%.
Total activity and associated burden averted for the 5 years is calculated from averaging
the first and 5th years of the plans and multiplying the results by 5.
The size of the burden of disease alleviated has been evaluated by assuming one DALY
alleviated is equivalent to the Gross Domestic Product of Malawi (based on IMF
projections).
Prevention interventions
Various assumptions were used to estimate the burden of disease that has already been
prevented by prevention interventions such as immunisations as to stop these would have the
effect of increasing these diseases in future. To gauge what would happen if immunisations were
reduced, the Sub-Saharan incidence rates of vaccine preventable diseases have been used to
calculate the effect of a suboptimal immunisation programme, adjusted by the estimated levels of
disease pre-immunisation era.
Clinical treatments
For those interventions involving clinical treatment 2009/10 HMIS data have been used, being
the most recent year of currently available data. Treatments have been adjusted in two ways; by
a factor for treatment effectiveness (as an example, antibiotics work in 84% of times for
pneumonia in children); and by a factor measuring the affected population (as an example, 50%
of adults and 70% of children registered in HMIS as malaria are not, so only half or less of the
number treated will benefit from antimalarial drugs). Treatment effectiveness factors are taken
from recent authoritative sources and referenced in the table.
Summation of benefits of the EHP
The burden of disease calculated in DALYS for each intervention for 2011 (and succeeding
years) can be summed to provide an overall estimate of burden averted by the programme. As
the costs are also contained in the EHP model it will be possible to measure the cost
effectiveness of each and all interventions combined at the levels of activity agreed once funding
is known.
Results
All results are found in a folder of spreadsheets available on the COM/Community Health
National Research website at
http://www.medcol.mw/commhealth/publications/national%20research/national_research.htm
There are excel files for all 159 conditions listed, and estimates of incidence, prevalence, deaths
and DALYs are available. Summary files are also available for DALYs, deaths, life expectancy,
healthy life expectancy (HALES) and risk factors, by age and sex group. Spreadsheets calculating
the DALYS averted by the EHP scenarios are also available for download.
Burden of Disease Estimates for 2011 and the potential effects of the Essential Health Package
on Malawi’s health burden
Deaths and life expectancy
Deaths are less than in 2002 and 2008 (the last time the BOD spreadsheets were updated) and
reflect the crude mortality rates found in the 2008 census (Table 1). HIV/AIDS remains the
leading cause of death in both sexes.
Table 1- Leading causes of death in Malawi in 2011
Table 2 – Life expectancy and Healthy Life Expectancy (HALE) in Malawi in 2011
The life expectancy estimates are similar and slightly longer than the census 2008 estimates of 48
in males and 51 years in females (Table 2).
Burden of disease in DALYS
There has been a reduction in DALYS since previous estimates despite the increase in
population (Table 3). This may partly be due to the last EHP. HIV/AIDS remains the leading
cause, followed by lower respiratory infections.
Table 3 – Leading causes of Disease Burden in Malawi in 2011 – all ages
The leading cause of disease burden in children remains lower respiratory disease, followed by
malaria and diarrhoeal diseases (Table 4).
Burden of Disease Estimates for 2011 and the potential effects of the Essential Health Package
on Malawi’s health burden
Table 4 – Leading causes of disease burden in Malawi in 2011 – children (0 – 15 years of age)
Risk factors
The leading risk factor remains unsafe sex, followed by under-nutrition.
Table 5 – Leading causes of disease burden (DALYs) due to selected risk factors in Malawi in
2011
The burden of disease alleviated by the EHP2
Estimates of disease burden averted and prevented by three scenarios and a baseline using 2010
data are found in Table 6. Estimates of the two components of the burden of disease (measured
in DALYS) years of life lost (YLL) and years lived with disability (YDL) are also shown. The
cost of each package is used to calculate the cost-effectiveness ratio for each scenario.
All scenarios for either year are cost-effective. Using the common yardstick of a cost-effective
ratio less than the country’s GDP Malawi would find a ratio of a whole health package below
$350, the current GDP for Malawi, good value for money. The 2011/12 ratios are higher than
the baseline for 2010 due mainly to higher levels of staff and their salaries and due to additional
interventions, such as mental illness services, which are not all as cost-effective as those in the
first EHP.
Serious under-funding reduces the cost-effectiveness of the package. This is because the
marginal cost of additional activity is less than the average cost of the chosen interventions. The
closer funding is to the ideal level, the better the cost-effectiveness. Ideal funding will allow all
targets to be met. This is not possible with the level of under-funding thought to be likely.
Table 6 – The burden of disease associated with the EHP2 based on actual activity for 2011
and two scenarios for 2011/12 and 2015/6
Scenario
Ideal
2010 actual
Actual DALYS averted by EHP interventions
% of all actual DALYs - EHP and non-EHP averted
2011/2
Resource based
2015/6
2011/2
2015/6
1,631,283
1,926,326
3,246,821
1,367,216
1,528,829
19%
22%
37%
16%
18%
Burden of Disease Estimates for 2011 and the potential effects of the Essential Health Package
on Malawi’s health burden
Potential DALYS averted by prevention activities
% of all potential DALYs averted
Total DALYS averted
657,891
715,762
2,200,826
329,108
457,658
22%
24%
73%
11%
15%
2,289,174
2,642,088
5,447,647
1,696,324
1,986,487
388,870,471
513,991,419
1,024,834,913
415,349,580
540,450,431
170
195
188
245
272
$800
$944
$2,291
$606
$835
DALYS
2,289,174
2,642,088
5,447,647
1,696,324
1,986,487
YLL
1,390,345
1,604,689
3,308,665
1,030,274
1,206,506
YLD
898,829
1,037,398
2,138,983
666,051
779,981
56,854
65,619
135,298
42,130
49,337
Cost of each scenario ($)
Cost per DALY of each scenario ($/DALY)
Benefit of EHP $m (DALYs averted * GDP per capita)
Deaths
Clearly the choice of intervention and the level of coverage will affect the cost effectiveness of
the package. The value of each intervention in terms of DALYs averted has been calculated for
each scenario. The activity of each intervention and the associated DALYs averted are shown
for the 2011/2 scenario using the resource based budget in Error! Reference source not
found..
References
1. Bowie C, Mwase T (2011) Assessing the use of an essential health package in a sector wide
approach in Malawi. Health Res Policy Syst 9: 4. doi:10.1186/1478-4505-9-4
2. Bowie C (2006) The burden of disease in Malawi. Malawi Medical Journal 18: 103-110.
Table 7 Burden of disease (in DALYS) associated with the 2011/12 “resource based, assuming direct
donor funding of $185m” EHP2 in Malawi for each of the chosen interventions
Table 7 – The resource based and ideal scenarios for 2011/2 and 2015/6 by intervention and
associated burden of disease averted – Malawi’s HSSP