Case study 1: Q-fever in air
Q-fever in air
Christensen, S., Donocik, A., Gkogka, E., Katuzika, A., Velten, S. & Zurbruegg, R.
Supervisor: Swart, A.N.
Abstract
Quantitative Microbial Risk Assessment was used to asses the risk of getting infected
with the bacteria Coxiella burnetii when passing an infected farm by bicycle during the
tourist season May-August in the Netherlands. The risk was estimated by calculating the
exposure in the affected areas and using two different beta Poisson models for the healthy
and the susceptible population. A safe distance of 20 km is recommended when passing
infected farms by bicycle. Recommendations should be targeted towards the
immunocompromised people since they are at much higher risk of contracting the disease.
Introduction
In 2007 the first incident of Q-fever in humans was reported from the Netherlands. The
following two year a rise in infections was observed with more than 3500 reported cases
of human infection (Karagiannis et al. 2009). Q-fever is spread worldwide with the
exception of New Zeeland. The first case of the disease occurred in Queensland,
Australia in 1935. In 1937 it was discovered that the disease was caused by a bacterium,
Coxiella burnetii, named after the researchers Cox and Burnet (RIVM 2010). In the
period 1981 -2007 53 Q-fever epidemic cases were described worldwide. An outbreak in
Uruguay in 1956 occurred among employees of a meat factory with 814 persons of 1358
getting infected. Another major outbreak occurred in Switzerland in 1987. This outbreak
became apparent three weeks after around 900 sheep went down from the alpine pastures
to the valley, and 21 % of the inhabitants along the route got infected (RIVM 2010). In
2007 there was an outbreak of Q fever in the Dutch province of Noord-Brabant with in
total 168 cases. In 2008 there was an outbreak in several regions with approx. 1000 cases
of Q fever reported. In 2009 the number of patients increased to around approx. 2300. At
that point it was the biggest epidemics of Q-fever in the world.
Coxiella burnetii is an obligately intracellular gram-negative bacteria in the size range
0.3-0.7 µm. C. burnetii is able to form small spores (0.1-0.2 µm)(McCaul & Williams
1981), which are resistant to drying or heat and hence remarkably stable in extracellular
environments (Snyder 2003). The spores can survive for months and years in the
environment (Hugo et al., 2004). C. burnetii is highly infectious, with one organism
causing clinical infection (Madariaga et al. 2003). The incubation period is 2-3 weeks
(Angelikalis and Raoult 2010) and the symptoms of Q fever are generally nonspecific.
There are multiple presentations, most commonly pneumonia, hepatitis, or fever only
(Raoult et al. 2001). Acute Q fever is characterized by sudden onset of high fever,
headache, muscle and joint pain, cough and, less frequently, rash or a meningeal
syndrome. Patients often have elevated liver enzyme levels and erythrocyte
sedimentation rates. Development of chronic Q fever can occur up to 20 years after the
initial infection. The major complication of chronic Q fever is endocarditis (Snyder 2003).
Only 60 % of infected persons have symptoms. 20% of infected persons seek medical
attention, and 2 to 3% are admitted to a hospital (Delsing & Kullberg 2008). Overall, the
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Case study 1: Q-fever in air
mortality rate of Q fever is low, approximately 1-2 % (Tissot-Dupont et al. 1992), but it
may be as high as 65% among those with chronic Q fever (Raoult et al. 2001).
Coxiella burnetii occur in nature and is responsible for infection in various mammals, and
in birds, reptiles and fish. Ticks are considered to be the natural primary reservoirs of C.
burnetii responsible for the spread of the infection in wild animals and for transmission of
C. burnetii from wild to domestic animals. Among domestic animals, cattle, sheep and
goats are considered to be the main reservoirs of the agent responsible for infection of
humans (Norlander 2000). Q-fever outbreaks have been associated with farm animals
specifically from animal birth products and excreta. Various routes of infections are
known but the primary path of infection in humans is by inhalation of air that contains
barnyard dust.
In 2007 the Dutch government made initiatives to avoid transmission of Q-fever from
animals to humans. Firstly goats were vaccinated in the risk regions. Another measures
included a breeding ban, a ban to spread manure on fields, a ban on visiting infected
farms, a duty to notify the authorities about Q-fever cases and a duty to test milk in bulk
tanks. Due to the lack of effect the Dutch government decided to kill (cull) pregnant
animals on infected farms in December 2009. This did not eradicate Q-fever in the
Netherlands but substantially decreased the number of infections (fig.1) (RIVM 2010).
Though the number of infected farms has decreased, the risk of infection when passing an
infected farm still needs to be considered. Transportation in open vehicles or by foot in
agricultural areas is a known way of contagion (Carrieri et al. 2002). During tourist
season a vast number of people pass through agricultural land by bike and are thereby in
risk of getting infected.
Figure 1. Number of patients with Q-fever in the period 010107 – 160610 (RIVM 2010)
Quantitative Microbial Risk Assessment (QMRA) can provide information on the risk
associated with presence in the vicinity of infected farms and provide us with guideline
values to concerning transportation in open vehicles in infected areas.
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Case study 1: Q-fever in air
In this study the risk when passing a Coxiella burnetii infected farm by bicycle is
assessed by QMRA, and recommendations of safe distances are given.
Methods
Background for assumptions
Detection of Coxiella burnetii
Molecular detection by PCR: This detection is rapid, sensitive and specific. PCR
(polymerase chain reaction) can be applied for different matrices such as: milk, semen,
urine, feces, placenta of animals but also in manure, aerosols etc. This method is still not
100 % reliable because there are some problems with inhibition of the primers.
Culture detection: Methods have only recently been developed and is not available in
most laboratories. There is also a high infection risk to laboratory personnel.
Serological detection: Mostly used in humans, but they are not useful to screen animals.
For example, serum antibodies are detectable about 2 weeks after the initial infection of
sheep. The antibody concentrations reach a maximum at 30 to 60 days, then rapidly
decline and phase into seasonal antibody cycle of the rest of the flock in relation to the
lambing season (Mc.Caul and Williams 1981). Therefore, if the infected sheep is tested
by serology during the low point of the cycle, when antibody concentration is below the
detection level, the results will be misleading.
Coxiella burnetii emission
Placenta contribution: The main emission of C. burnetii happens during birthing in the
form of amniotic fluids and the placenta. It is generally assumed that C. burnetii can
occur up to a concentration of 109 per placenta (van Woerden 2004). For this study this
source is assumed to be the main source of contamination.
Feces contribution: C. burnetii is also excreted with feces. The concentration of C.
burnetii in feces can be found in a range of 103–104 per g feces (Ryan G. Sinclair et al.
2008). Considering a daily production of 2.35 kg feces per goat (NCSU, 1994), the
concentration of C. burnetii results in 2.5 x 106– 2.5 x 107 per goat per day.
Assuming a homogeneous distribution of 500 to 4000 goats per barn and an infection rate
of 20%, this results in 2.5 x 108– 2 x 1010 per barn per day. Considering that this is in the
same order of magnitude the contribution of feces is relevant. Due to the high uncertainty
of available data we decide to consider the contribution of feces as an uncertain
parameter of 25 - 2000% of the concentration of one placenta by assuming a triangle
distribution with the median at 100%. We take the median at approximately 25% of the
range of values, since the infection rate of goats is also skewed towards the lower end.
Inactivation of Coxiella burnetii
C. burnetii spore like forms are resilient. They can withstand pressures of up to 20,000
lb/in2, elevated temperatures, desiccation, osmotic shock, UV light and chemical
disinfectants. Experimental studies of the survival of C. burnetii spore like forms have
not demonstrated survival beyond 8 years (Table 1) (van Woerden et al 2004). Whether
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Case study 1: Q-fever in air
experiments for longer durations were undertaken is not clear from the source documents.
Compared to other pathogens, the survival rate of C. burnetii is very high (Sinclair et al.
2008). Decimal reduction times (DRT) of C. burnetii in a manure pile are given in Table
2. The DRT, also known as D value, gives the time required at a certain temperature to
kill 90% of the organisms being studied. The data show that with increasing time the
decimal reduction of C. burnetii decreases. At 20 °C, the relevant temperature for this
case, the DCT takes 30.49 d. For this study the inactivation time of C. burnetii is
insignificant compared to the length of the investigation period. Therefore, based on the
available information, we consider the inactivation rate for C. burnetii spores to be
negligible in this assessment.
Table 1. Survival of Coxiella burnetiia in different media (van Woerden et al, 2004)
Environment
Temperature (°C)
Survival
Wool
15–20
7–9 mo
Wool
4–6 Approx.
12 mo
Sand
15–20
4 mo
Fresh meat
Cold storage
>1 mo
Salt meat
Not recorded
5 mo
Skimmed milk
Not recorded
40 mo
Tap water
Not recorded
30 mo
Tick feces
Room
Conclusive evidence: 586 d
Some evidence: 6 and 8 y
Not recorded
–20
2y
Not recorded
–65
8y
Table 2. DRT (decimal reduction time) of C. burnetii in a manure pile (Roest et al. 2010)
Temperature (°C)
DRT (sec)
DRT (min)
DRT (h)
DRT (d)
20
2634275.25
43904.59
731.74
30.49
30
191208. 29
3186.80
53.11
2.21
40
13878.81
231.31
3.86
0.16
50
1007.39
16.79
0.28
0.01
60
73.12
1.22
0.02
70
5.31
0.09
Transmission routes
Coxiella burnetii survives in stables, barns, pastures, manure, raw wool, skin and clothing.
People get infected primarily through inhalation of aerosolized C. burnetii. This can
happen by direct contact with an infected animal or indirectly, since C. burnetii can be
spread by wind.
Other transmission rates are:
- indigestion of contaminated diary products, especially unpasteurized goat milk
- bites from infected ticks (although this transmission way is very rare.)
Bacteria are not known to be transmitted from person to person.
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Case study 1: Q-fever in air
Model of transmission routes of Coxiella burnetii
source
excretion
transmission
host
Indirect transmission
important
tick
goat
Dust
sheep
Placenta
cattle
Feces/manure
Manure on fields
Urine
Weather conditions
Domestic animals
Goat,
sheep,
cattle
milk
(dogs, cats, horses)
Human
Wild animals
(rodents, ruminant)
Direct transmission
little important
Figure 2. Transmission routes of Coxiella burnetii (Central Veterinary Institute 2010)
As the primary path of infection in humans is by inhalation of air that contains barnyard
dust ingestion and bites are not taken into account in this assessment.
Dispersion
Dispersion of Coxiella burnetii is affected by the following factors:
 Wind speed and direction
 Seasons with temperature and humidity key factors; summer, winter, autumn. The
highest number of infections occur in the summer period
 Cloud cover
 Vegetation that traps particles from the air
 Turbulence in the atmosphere. This is incorporated parameter σ in the in the
model.
Concept
In order to accomplish a QMRA for q-fever infection for cyclists in the Netherlands an
emission – infection model was set up. The scenario is based on data from summer
season 2009 (1 June – 31 August 2009) in the area around Eindhoven, where Q-fever
primarily occurred in 2008 and 2009.
The scenario includes Coxiella Burnetii emissions from a goat farm, transport (plume
model) through air and uptake by a cyclist (dose-response model)
C ( x, y , z ) 
Q
2 z  y u

e
y2
2 y2

e
( z h)2
2 z2
(Eq. 1)
Emissions are assumed to happen by cells reaching the air from placentas after birth by
infected goats. As birth time and occurrence of Q-fever are not correlated temporally
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Case study 1: Q-fever in air
(Tissot-Dupont 1999), a constant birth rate was assumed during a 4 months period (May
– August) for simplicity. A gaussian point source plume model (Eq. 1) was used to model
air concentrations of cells at distance x in the main wind direction and distance y
perpendicular to the main wind direction which is North-Northeast (KNMI 2010). Only
the main wind direction was considered, since Schimmer at al. (2010) show that the main
direction is crucial for arerial C. burnetii spread. Steady state was assumed and clear
weather was assumed. Distances, where cells in air have been found in the Netherlands
previously range from 500 to 5000m (De Bruin et al. 2009).
The following model assumptions were used:
Assumptions for emission model
Distribution
Parameters:
Min: 500
Uniform
Max: 3900
Min: 0.05,
Triangular
Mean: 0.2
Max: 1.0
1
Parameter:
Unit
Farm size
goats
Goat infection
fraction
goat-1
Birth rate
yr-1
Birth period
Months
-
4 months (May –
August)
Cells per
placenta
cells
-
109
Reference
(VWA, 2010)
A. Swart, pers. Comm.
A. Swart, pers. Comm.
N  N 0 e  kt
Cell emission
from placentas
cells
Exponential
k
VBarn
 5s 1
u  ADoor
N 0  10 9 cells
Min: 1.18
Max: 7.19
α: 2.34
β: 4.36
Min: 2.5E8
Mean: 5E9
Max: 2E10
Accounting for higher
probability of cells leaving from
fresh placentas
Wind speed u
m/s
Beta (fit)
Cell emission
from feaces
cells/s
Triangular
m
-
variable
-
m
-
variable
-
m
-
1.8 m
s-1
-
0.33
m3
s
-
0.00125
10
Distance x
from souce
Lateral
distance y
Exposure
height h
Breathing
frequency
Breath volume
Exposure time
(KNMI, 2010)
(Sinclair et al. 2008)
-
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Case study 1: Q-fever in air
Hazard Characterization
Dose-response assessment
In order to relate concentrations of Coxiella burnetii in the atmosphere with cases in the
human population a dose response model in necessary. A summary of all existing dose
response models can be seen in the figure below.
1.2
1
Pinf
0.8
0.6
0.4
0.2
0
0
5
10
15
20
25
Dose (logcfu)
Beta Poisson - SCID immunocompromised mice
Exponential - C57BL/6J resistant mice
Beta Poisson - C57BL/10ScN male mice
Beta Poisson - human volunteers
Figure 3. Possible dose response models for Coxiella burnetii (Haas et al. 2010)
The equations and parameters for the models presented in Figure 3.1 can be found in
Appendix I. It was considered that the model based on human volunteer data (Tigertt and
Benenson, 1956) is the most representative one for the healthy human population since it
is based on healthy human subjects and involves inhalation as the route of infection in
contrast with all the mice models that are based on intra-peritoneal injection. Due to the
fact that the models based on healthy mice are all less conservative than the one based on
healthy humans it was considered appropriate to assume the very conservative model for
the immunocompromised SCID mice suitable for the susceptible part of the human
population consisted of old, pregnant and immunocompromised individuals. The
population at risk of infection was considered to be all the seronegative individuals
(Karagiannis et al, 2009) and the percentage of YOPI was based on data from the
Netherlands Bureau of Statistics (CBS, 2010).
Disability Adjusted Life Years
Cases estimated by combining the hazard characterization and the exposure assessment
part of the risk assessment were used to estimate DALY, selecting the formulas that do
7
Case study 1: Q-fever in air
not include age weighting or discounting (Arnesen and Kapiriri, 2004). For the purpose
of these calculations all cases were considered to be initially cases of acute Q fever and
1.86% of these cases were considered to result in chronic Q fever (ECDC, 2010). Cases
of acute Q fever most often present with influenza like symptoms (ECDC, 2010) and
therefore were assigned a disability weight of 0.220 based on the rationale of Murray
(Murray, 1994). We considered that 20% of acute cases develop pneumonia (ECD, 2010)
and therefore estimated YLD for this sequelae as well. For the chronic cases of Q fever,
endocarditis is the most common form of Q fever (Schimmer et al, 2009) was therefore
used for the estimation of DALY associated with this form of the disease. The value
choices for the DALY formula can be seen in Appendix II. Disability weights were
derived from the study of Lopez and Mathers (Lopez and Mathers, 2006).
Results
Distribution of dose and infection probability
The distribution of the dose (shown is 100 m distance from the farm) shows the highest
probability around 0.006 cells which equals to a infection probability of healthy people of
0.16%. The range of doses covers an interval of 0 – 0.015, the infection probability
ranges from 0 to 0.9%. Both parameters show a similar distribution shape, caused by the
compilation of the distribution of the input parameters.
Distribution of total cases and DALYs
A number of 1,000,000 inhabitats (healthy and immunocompromized) were assumed to
characterize the effect of Q-fever on the local population. The calculated distribution
(100 m distance) of the total cases has a mean of ca. 54,000, which corresponds to a
DALY of ca. 38,00 years.
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Case study 1: Q-fever in air
Effect of distance to the infected farm
The mean values of four parameters after 10,000 Monte Carlo simulations based on an
integrated dose when riding through the emission plume show declining numbers with
distance. The infection proability for healthy people decreases from 0.16% at 100 m
distance to < 0.01% at 20 km from the farm.
Means of parameters as function of distance from the barn
Dose
Infection
Distance
Total cases
Total DALY (yr)
(cells)
probability (%)
100 m
0.0059
0.160
53324
37617
2000 m
0.0022
0.059
50098
35341
20000 m
0.0003
0.009
40434
28523
Discussion
Safe distance from the farm – how uncertain is the distance?
Healthy individuals should avoid cycling at a distance closer than 2 km to the farm. This
distance should be increased to 20 km for the susceptible population. To prevent
confusion though it might be wiser to use the latter value for both groups.
Key uncertainties are the emission from the manure and the speed of the wind (see Annex
III).
There is no dose response model based on human data for the immunocompromised
population. Thus a dose response based on mice data was used that is not based on the
primary mode of infection of the disease (inhalation) but on intra-peritoneal injection.
Preventory measures to diminish the spread of Q-fever can be taken by:
 Burning and burying reproductive offal
 Antibiotic treatment for animals
 Vaccination for human beings
The estimates could be further improved by research in the following areas:
- Dose response relationship for Coxiella burnetii.
- Data on the concentration and survival of the pathogen in manure
- Data on the immunocompomised individuals: percentage among the population
and cycling habits
Communication: Surveys have shown that the greatest trust lie in local and national
authorities (de Roda Husman, pers. comm.). Homepages of these authorities will be used
to communicate the main messages: For immunocompromised people completely to
avoid infected areas and for the cyclist to keep a safe distance to infected farms. Signs
will be put up in areas warning people that they are entering an area of infection.
Conclusion
The following can be drawn from this risk assessment:
• The risk declines significantly based on the distance to the farm. People should be
advised not to cycle at a distance closer than 20 km.
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Case study 1: Q-fever in air
•
For all scenarios the risk for the immunocompromised is much higher than for the
healthy population. Therefore special advice should be given to this sensitive subgroup of the population.
References
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Haas et al. 2010. Dose-Response model of Coxiella burnetii (Q fever) (article in preparation)
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Sinclair. R.G., Christopher Y. Choi, C.Y.. Riley, M.R. and Gerba, C.P. 2008. Pathogen Surveillance
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Case study 1: Q-fever in air
Appendix I
Table I. Equations of plausible dose-response models for Q-fever infection (Haas et al, 2010)
Model
Equation
Parameters
Mode of
Test
Infection
subject
Beta Poisson – SCID
α = 0,492
intramice
immunocompromised
Ν50 = 6.77x10-5
peritoneal
mice
injection
Exponential –
C57BL/6J resistant
mice
k = 5.7x10-11
intraperitoneal
injection
mice
Beta Poisson –
C57BL/10ScN male
mice
α = 0,356
Ν50 = 4,925x108
intraperitoneal
injection
mice
Beta Poisson – healthy
human volunteers
α = 0,414
Ν50 = 6,623
inhalation
humans
Appendix II
Tables IIa and IIb. Value choices used in the DALY formula. Sources: ECDC, 2010;
Lopez and Mathers, 2006; CBS, 2010.
IIa
Acute Q fever
Chronic Q fever
Age of illness
52.8
52.8
Case fatality
0.015
0.3
Life span at the age of death
27.5
27.5
IIb
Acute Q fever (influenza like illness)
- acute Q fever associated pneumonia
Chronic Q fever (endocarditis)
Duration
(years)
0.038356164
0.038356164
27.5
Disability
weight
0.22
0.279
0.252
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Case study 1: Q-fever in air
ANNEX III
Key uncertainties in the estimation of total cases
13