Supplement for the manuscript ‘Integrated monitoring and evaluation and environmental
risk factors for urinary schistosomiasis and active trachoma in Burkina Faso before
preventative chemotherapy using sentinel sites’
S.1 Sample Size Calculations
Here we present further details about the sample size calculations. In order to calculate sample
sizes for this study, we used longitudinal monitoring data from the National Vertical
Schistosomiasis Control Program (NVSCP) in Burkina Faso which had been already collected
during 2004-2006. For instance, an overall drop-out rate of 55% comparing survey 3 to survey 1
had been observed in these data during 3 annual surveys over the course of the monitoring period,
so this figure was incorporated in our sample size calculations. The computer model EpiSchisto
was used to obtain infection intensity and prevalence predictions post-integration, taking into
account the effect that the NVSCP would already have had on infection levels as a vertical
programme before the integration. As a starting point of the integrated programme, we used the
NVSCP data corresponding to the 3rd annual survey during 2006 (i.e. follow-up year 2).
The relationship between prevalence and intensity of S. haematobium infection was assumed to
arise from a negative binomial distribution of parasites among hosts in order to estimate, using
maximum likelihood, the inverse overdispersion (k) parameter required to parameterize the
EpiSchisto model.
Figures 1A and 1B below illustrate these calculations, respectively, for pre-treatment baseline
(2004) and 2nd year post-treatment (2006) from the NVSCP longitudinal monitoring data. In
addition, these figures show that k values change over time with the intervention, a finding we
took into account in the sample size calculations.
1
Figure S.1
A
Prevalence vs. Mean intensity of S. haematobium infection in Burkina Faso at
baseline
100
90
Prevalence of infection (%)
80
70
60
observed
50
expected
40
30
20
10
0
0
100
200
300
400
500
600
700
800
900
1000
Mean intensity (e/10 ml)
B
Prevalence vs. Mean intensity of S. haematobium infection in Burkina Faso at follow-up
year 2
100
90
observed
80
Prevalence of infection (%)
70
expected
60
50
40
30
20
10
0
0
10
20
30
40
50
60
70
80
Mean intensity (e/10 ml)
Points represent observed data of 763 Burkinabé children while the green line represents the fitted
prevalence according to a negative binomial model with the overdispersion k parameter as a linear function
of the arithmetic mean infection intensity (m) with expression k(m)= k0+k1m. Parameters for baseline were
k0 = 0.050 and k1 = 0.001 and for the follow-up year 2 were k0 =0.017, and k1 = 0.0006. The figures above
indicate that k values change over time with the intervention. This was taken into consideration in the
calculations of the sample sizes.
2
S.2 Pearson Correlations
Below the readers can find two tables that contain Pearson correlations. Table S.2.1 contains
correlations between the average values of environmental variables as derived from the 9
meteorological stations.
Table S.2.2 contains Pearson correlations between the school-level prevalences of single and dual
infections (n = 21 sentinel sites) with the interpolated values of the environmental variables through
inverse distance weighting (i.e. assigned values to unknown points of environmental variables for
schools from the known average values derived from the meteorological stations).
Table S.2.1 Pearson correlations between the average values of the environmental variables
derived from the 9 meteorological stations across Burkina Faso
Mean
altitude
(MSL)
1
Mean
Mean min Mean
precipitation temp
max temp
(mm)
(ºC)
(ºC)
Mean
altitude
(MSL)
0.410
1
Mean
p=0.273
precipitation
(mm)
-0.435
1
Mean min
-0.677
p=0.241
temp (ºC)
p=0.045
0.650
Mean max
-0.711
-0.825
p=0.058
temp (ºC)
p=0.032
p=0.006
-0.359
Mean
-0.885
0.875
p=0.342
average
p=0.002
p=0.002
temp (ºC)
-0.639
-0.284
-0.047
Mean air
p=0.064
p=0.459
p=0.905
pressure
(mbars)
*Statistically significant at the 0.05 significance level.
Mean avg
temp
(ºC)
Mean air
pressure
(mbars)
1
0.800
p=0.010
1
0.623
p=0.073
0.096
p=0.806
1
3
Table S.2.2 Pearson correlations between the school-level prevalences of single and dual
infections (n = 21 sentinel sites) with the interpolated values of the environmental variables
through inverse distance weighting
S. haematobium
prevalence◙
Altitude◊
Precipitation◊
Min temperature◊
Max temperature◊
Av temperature◊
Air pressure◊
-0.595
p=0.005
-0.631
p=0.002
0.440
p=0.046
0.688
p<0.001
0.543
p=0.011
0.413
p=0.063
Active trachoma
prevalence◘
0.771
p<0.001
0.470
p=0.031
-0.384
p=0.086
-0.693
p<0.001
-0.399
p=0.073
-0.762
p<0.001
Prevalence of coinfections with
S. haematobium and
active trachoma□
-0.411
p=0.064
-0.436
p=0.048
0.274
p=0.230
0.424
p=0.055
0.342
p=0.129
0.331
p=0.143
◊ Interpolated values of environmental variables.
◙ S. haematobium prevalence at the school level (single infections with S. haematobium and co-infections
with active trachoma are included in these calculations).
◘ Active trachoma prevalence at the school level (single infections with active trachoma and co-infections
with S. haematobium are included in these calculations).
□ Only co-infections with S. haematobium and active trachoma at the school level are included in these
calculations.
S.3 Scatter Plots of Infection Prevalence and Environmental Variables
Scatter plots are displayed below to show the interpolated values of the environmental variables and
the school-level prevalences of single and dual infections with urinary schistosomiasis and active
trachoma. Scatter plots (a) to (f) are displayed for the S. haematobium prevalences at school level
vs. the interpolated values of the environmental variables; scatter plots (g) to (l) are displayed for
the active trachoma prevalences at the school level and the interpolated values of the environmental
variables. Finally, scatter plots (m) to (r) are displayed for the prevalences of co-infections with
S. haematobium and active trachoma at the school level and the interpolated values of the
environmental variables.
4
Figures S.3 (a) to (f)
b
S. haematobium school prevalence
60
50
40
30
20
10
0
960
50
40
30
20
10
0
28
27.5
27
980
975
970
965
60
S. haematobium school prevalence
a
50
40
30
20
10
0
33
34
35
36
37
38
40
30
20
10
0
21.5
22
40
30
S. haematobium
S. haematobium school prevalence
50
20
10
0
1
1.5
2
Precipitation (mm)
2.5
23
23.5
60
school prevalence
f
0.5
22.5
Min temperature (celsius)
60
0
30
50
Max temperature (celsius)
e
29.5
29
60
school prevalence
d
S. haematobium
school prevalence
60
S. haematobium
c
28.5
Av temperature (celsius)
Air pressure (millibar)
3
3.5
50
40
30
20
10
0
0
100
200
300
400
500
Altitude (MSL)
Scatter plots of S. haematobium prevalence at the school level (single infections with S. haematobium and
co-infections with active trachoma are included in these calculations) versus the interpolated values of the
environmental variables.
5
Figures S.3 (g) to (l)
g
40
Active
trachoma school prevalence
35
Active trachoma school
prevalence
40
h
30
25
20
15
10
5
35
30
25
20
15
10
5
0
0
960
965
970
975
27
980
27.5
28
Air pressure (millibar)
j
Active trachoma school prevalence
40
35
30
25
20
15
10
5
34
35
36
37
25
20
15
10
38
5
0
21.5
22
22.5
23
23.5
Min temperature (celsius)
l
40
40
35
35
30
30
Active trachoma
school prevalence
Active trachoma school prevalence
30
30
M ax temperature (celsius)
k
29.5
35
0
33
29
40
Active trachoma school prevalence
i
28.5
Av temperature (celsius)
25
20
15
25
20
15
10
10
5
5
0
0
0
0
0.5
1
1.5
2
2.5
3
3.5
100
200
300
400
500
Altitude (MSL)
Precipitation (mm)
Scatter plots of active trachoma prevalence at the school level (single infections with active trachoma and
co-infections with S. haematobium are included in these calculations) versus the interpolated values of the
environmental variables.
6
Figures S.3 (m) to (r)
n
4.5
4
4.5
Co-infections school prevalence
Co-infections school prevalence
m
3.5
3
2.5
2
1.5
1
0.5
0
960
965
970
975
4
3.5
3
2.5
2
1.5
1
0.5
0
980
27
Air pressure (millibar)
o
p
3.5
3
2.5
2
1.5
1
0.5
29
29.5
30
4
3.5
3
2.5
2
1.5
1
0.5
0
21.5
0
35
28.5
4.5
Co-infections school prevalence
Co-infections school prevalence
4
34
28
Av temperature (celsius)
4.5
33
27.5
36
37
22
38
22.5
23
23.5
Min temperature (celsius)
Max temperature (celsius)
q
r
4
4.5
Co-infections school prevalence
Co-infections school prevalence
4.5
3.5
3
2.5
2
1.5
1
0.5
0
0
0.5
1
1.5
2
Precipitation (mm)
2.5
3
3.5
4
3.5
3
2.5
2
1.5
1
0.5
0
0
100
200
300
400
500
Altitude (MSL)
Scatter plots of the prevalences of co-infections at the school level (single infections are not included in
these calculations) versus the interpolated values of the environmental variables.
7
S.4 Observed vs. Predicted Prevalence of Dual Infections with Urinary Schistosomiasis and
Active Trachoma
Figure S.4 below shows that the predicted prevalence of dual infections (on average 1.1%, based
on the product of the individual infection prevalence predictions obtained from binomial logistic
regression models with random effects for schools) was very similar to that observed, 0.98% on
average. The correlation between the observed and predicted school-level dual-infection
prevalence levels was 0.66, and a plot of these values was consistent with S.haematobium
infection and trachoma signs being independent.
Figure S.4
8