Supplement for ‘Risk factors for urinary schistosomiasis and active trachoma in
Burkina Faso before preventive chemotherapy: implications for monitoring and
evaluation of integrated control programmes’
Artemis Koukounari, Seydou Touré, Christl A. Donnelly, Amadou Ouedraogo,
Bernadette Yoda, Cesaire Ky, Martin Kaboré, Elisa Bosqué-Oliva, María-Gloria
Basáñez, Alan Fenwick, Joanne P. Webster
S.1
Here we present two tables that contain Pearson correlations. The first table (i.e. Table S.1)
contains correlations between the average values of weather and environmental variables as
derived from the 9 weather stations.
The second table (i.e. Table S.2) contains Pearson correlations between the school-level
prevalences of single and dual infections (i.e. n=21) with the interpolated values of the
weather and environmental variables through inverse distance weighting (i.e. assigned
values to unknown points of weather and environmental variables for schools from the
known average values as derived from the weather stations).
Table S.1
Mean
altitude
Mean
precipitation
Mean max
temp
Mean min
temp
Mean
temp
av
Mean
1
altitude
Mean
0.410
1
precipitation
p=0.273
Mean max
1
-0.711
-0.825
temp
p=0.032
p=0.006
Mean min
-0.435
0.650
1
-0.677
temp
p=0.241
p=0.058
p=0.045
Mean
av
-0.359
1
-0.885
0.800
0.875
temp
p=0.342
p=0.002
p=0.010
p=0.002
Mean
air
-0.639
-0.284
0.623
-0.047
0.096
pressure
p=0.064
p=0.459
p=0.073
p=0.905
p=0.806
Bold typeface is used for the results statistically significant at the 0.05 significance level.
Mean air
pressure
1
1
Table S.2
Altitude◊
Precipitation◊
Max temperature◊
Min temperature◊
Av temperature◊
Air pressure◊
S. haematobium
prevalence◙
Active trachoma
prevalence◘
-0.595
p=0.005
-0.631
p=0.002
0.688
p<0.001
0.440
p=0.046
0.543
p=0.011
0.413
p=0.063
0.771
p<0.001
0.470
p=0.031
-0.693
p<0.001
-0.384
p=0.086
-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
0.424
p=0.055
0.274
p=0.230
0.342
p=0.129
0.331
p=0.143
Bold typeface is used for the results statistically significant at the 0.05 significance level.
◊ 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.2
Scatter plots are displayed below to show values for the interpolated values of the
environmental variables and the school-level prevalences of single and dual infections.
Initially six scatter plots are displayed for the S. haematobium prevalences at the school
level and the interpolated values of the environmental variables; then another six scatter
plots are displayed between the active trachoma prevalences at the school level and the
interpolated values of the environmental variables. Finally six scatter plots 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.
2
60
S. haematobium school prevalence
S. haematobium school prevalence
60
50
40
30
20
10
0
0
100
200
300
400
50
40
30
20
10
0
500
0
0.5
1
Altitude (MSL)
school prevalence
40
30
20
10
0
33
2.5
3
3.5
34
35
36
37
38
50
40
30
20
10
0
21.5
Max temperature (celsius)
22
22.5
23
23.5
Min temperature (celsius)
60
60
S. haematobium school prevalence
school prevalence
2
60
50
S. haematobium
S. haematobium
school prevalence
60
S. haematobium
1.5
Precipitation (mm)
50
40
30
20
10
0
27
27.5
28
28.5
29
Av temperature (celsius)
29.5
30
50
40
30
20
10
0
960
965
970
975
980
Air pressure (millibar)
Points at all the six scatter plots above show 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.
3
40
Active trachoma school prevalence
40
Active trachoma
school prevalence
35
30
25
20
15
10
5
0
0
100
200
300
400
35
30
25
20
15
10
5
0
0
500
0.5
1
2
2.5
3
3.5
40
Active trachoma school prevalence
Active trachoma school prevalence
40
35
30
25
20
15
10
5
35
30
25
20
15
10
0
33
34
35
36
37
38
5
0
21.5
22
22.5
23
23.5
Min temperature (celsius)
M ax temperature (celsius)
40
40
35
35
Active trachoma school
prevalence
Active
trachoma school prevalence
1.5
Precipitation (mm)
Altitude (MSL)
30
25
20
15
10
5
0
30
25
20
15
10
5
0
27
27.5
28
28.5
29
Av temperature (celsius)
29.5
30
960
965
970
975
980
Air pressure (millibar)
Points at all the six scatter plots above show 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.
4
4.5
4
Co-infections school prevalence
Co-infections school prevalence
4.5
3.5
3
2.5
2
1.5
1
0.5
4
3.5
3
2.5
2
1.5
1
0.5
0
0
0
100
200
300
400
0
500
0.5
1
2
2.5
3
3.5
4.5
4.5
4
Co-infections school prevalence
Co-infections school prevalence
1.5
Precipitation (mm)
Altitude (MSL)
3.5
3
2.5
2
1.5
1
0.5
4
3.5
3
2.5
2
1.5
1
0.5
0
21.5
0
33
34
35
36
37
22
38
22.5
23
23.5
Min temperature (celsius)
Max temperature (celsius)
4.5
4
Co-infections school prevalence
Co-infections school prevalence
4.5
3.5
3
2.5
2
1.5
1
0.5
0
27
27.5
28
28.5
29
Av temperature (celsius)
29.5
30
4
3.5
3
2.5
2
1.5
1
0.5
0
960
965
970
975
980
Air pressure (millibar)
Points at all the six scatter plots above show prevalences of co-infections at the school level (single
infections are not included in these calculations) versus the interpolated values of the environmental
variables.
5
S.3
Scatter plots of predicted versus observed values were inspected in order to examine the
appropriateness of the binomial and multinomial multivariate fitted models. Figure S.3.1
shows predicted versus observed S. haematobium prevalence as derived from the single
pathogen binomial logistic regression model (results of which are indicated in Table 3 in
the main text). Figure S.3.2 shows predicted versus observed active trachoma prevalence
as derived from the single pathogen binomial logistic regression model (results of which
are indicated in Table 4 in the main text). Figure S.3.3 shows predicted versus coinfections prevalence by assuming independence and multiplying together the predictions
from these two single pathogen binomial logistic regression models. This figure suggests
that the individual models may overestimate co-infections and therefore a multinomial
logistic regression model was used in order to quantify risk factors for single and coinfections (results of which are indicated in Table 5 in the main text). Figure S.3. 4 shows
predicted versus observed co-infections as derived from the multinomial logistic
regression model.
Figure S. 3. 1
From binary logistic S. haematobium
regression model (Table 3 in paper)
50
40
Observed S.
haematobium
prevalence
30
20
10
0
0
10
20
30
40
50
Predicted S. haematobium prevalence
6
Figure S. 3. 2
From binary logistic active trachoma
regression model (Table 4 in paper)
Observed active
trachoma prevalence
40
35
30
25
20
15
10
5
0
0
10
20
30
40
Predicted active trachoma prevalence
Figure S. 3. 3
Observed co-infections
Multiplication of predictions of co-infections from the
two single pathogens logistic regression models.
8
7
6
5
4
3
2
1
0
0.00
2.00
4.00
6.00
Predicted co-infections
8.00
7
Figure S. 3. 4
From mutlinomial logistic regression
model (Table 5 in paper)
Observed coinfections
8
6
4
2
0
0
2
4
6
8
Pre dicte d co-infe ctions
8