Figure S1. Flow diagram of study selection process - MDPI
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Figure S1. Flow diagram of study selection process - MDPI
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Figure S1. Flow diagram of study selection process
1
Figure S2. Deeks funnel plot asymmetry test for publication bias for S. haematobium diagnostic questions: (a) blood in urine; (b) pain during urination; and (c) history of schistosomiasis.
Figure S3. Deeks funnel plot asymmetry test for publication bias for S. mansoni diagnostic questions: (a) abdominal pain; (b) history of schistosomiasis; and (c) blood in stool; and (d) bloody diarrhea.
2
Figure S4. Quality assessment results for diagnostic questions used in S. haematobium meta-analysis: (a) blood in urine; (b) pain during urination; and (c) history of schistosomiasis.
3
Figure S5. Quality assessment results for diagnostic questions used in S. mansoni meta-analysis: (a) blood in stool; (b) bloody diarrhea; (c) history of schistosomiasis; and (d) abdominal pain.
4
Figure S6. Sensitivity forest plot, Specificity forest plot, and SROC plot for blood in urine question (S. haematobium): (a) Sensitivity forest plot; (b) Specificity forest plot; and (c) SROC curve with summary sensitivity and false positive rate (1-specificity) (circle) and the 95% confidence region (ellipse). Each triangle represents the summary sensitivity and false positive rate from one study.
5
Figure S7. Sensitivity forest plot, Specificity forest plot, and SROC plot for history of schistosomiasis question (S. haematobium): (a) Sensitivity forest plot; (b) Specificity forest plot; and (c) SROC curve with summary sensitivity and false positive rate (1-specificity) (circle) and the 95% confidence region (ellipse). Each triangle represents the summary sensitivity and false positive rate from one study.
6
Figure S8. Sensitivity forest plot, Specificity forest plot, and SROC plot for blood in stool question (S. mansoni): (a) Sensitivity forest plot; (b) Specificity forest plot; and (c) SROC curve with summary sensitivity and false positive rate (1-specificity) (circle) and the 95% confidence region (ellipse). Each triangle represents the summary sensitivity and false positive rate from one study.
7
Figure S9. Sensitivity forest plot, Specificity forest plot, and SROC plot for bloody diarrhea question (S. mansoni): (a) Sensitivity forest plot; (b) Specificity forest plot; and (c) SROC curve with summary sensitivity and false positive rate (1-specificity) (circle) and the 95% confidence region (ellipse). Each triangle represents the summary sensitivity and false positive rate from one study.
8
Figure S10. Sensitivity forest plot, Specificity forest plot, and SROC plot for abdominal pain question (S. mansoni): (a) Sensitivity forest plot; (b) Specificity forest plot; and (c) SROC curve with summary sensitivity and false positive rate (1-specificity) (circle) and the 95% confidence region (ellipse). Each triangle represents the summary sensitivity and false positive rate from one study.
9
Figure S11. Sensitivity forest plot, Specificity forest plot, and SROC plot for history of schistosomiasis (S. mansoni). (a) Sensitivity forest plot; (b) Specificity forest plot; and (c) SROC curve with summary sensitivity and false positive rate (1-specificity) (circle) and the 95% confidence region (ellipse). Each triangle represents the summary sensitivity and false positive rate from one study.
10
Figure S12. Proportion of students classified as S. haematobium- (red) or S. mansoni- (blue) positive in this study using different LR+ threshold values. The proportion classified as infected is shown to decrease as the LR+ threshold value is raised because of reductions in false positives. A LR+ of 3.5 was selected as the threshold value in this study to balance the need for obtaining adequate numbers of positive cases while keeping the false positive rate sufficiently low.
11
Figure S13. Distribution of individual wealth scores among 1704 Tanzanian schoolchildren with schistosomiasis status indicated by color: positive (blue) and negative (red).
12
Table S1. Characteristics of studies with data for the diagnostic questions used in the S. haematobium meta-analyses Diagnostic Question
First Author
Year of Publication
Country
Sample size
Prevalence
Ages
TP
FP
FN
TN
Blood in urine
Warren
1979
Kenya
390
83.6%
Schoolchildren
239
14
87
50
Blood in urine
Abdel-Wahab
1992
Egypt
422
33.6%
Schoolchildren
62
45
80
235
Blood in urine
Ekanem
1995
Nigeria
462
38.3%
Schoolchildren
107
30
70
255
Blood in urine
Mtasiwa
1996
Tanzania
404
67.6%
Schoolchildren
111
13
162
118
Blood in urine
Onayade
1996
Nigeria
105
88.6%
Schoolchildren
73
1
20
11
Blood in urine
Mafe
1997
Nigeria
1024
57.6%
All
259
49
331
385
Blood in urine
Traore
1998
Mali
1041
55.2%
All
252
59
323
407
Blood in urine
Traquinho
1998
Mozambique
994
84.4%
Schoolchildren
528
68
311
87
Blood in urine
Guyatt
1999
Tanzania
3928
58.1%
Schoolchildren
1175
342
1107
1304
Blood in urine
Takougang
2004
Cameroon
871
36.3%
Schoolchildren
138
94
178
461
Blood in urine
Bowie
2004
Malawi
1565
8.6%
Schoolchildren
90
289
44
1142
Blood in urine
Fatiregun
2005
Nigeria
592
12.2%
Schoolchildren
30
36
42
484
Blood in urine
French
2007
Tanzania
1976
13.2%
Schoolchildren
45
42
215
1674
Blood in urine
Kapito-Tembo
2009
Malawi
1139
10.8%
Schoolchildren
84
268
39
748
Blood in urine
Ahmed
2009
Yemen
515
21.4%
Schoolchildren
81
77
29
328
Blood in urine
Kihara
2011
Kenya
6183
24.5%
Schoolchildren
741
384
774
4284
Blood in urine
Banwat
2012
Nigeria
218
6.4%
Schoolchildren
6
16
8
188
Blood in urine
Bogoch
2012
Ghana
198
8.6%
All
9
27
8
154
Blood in urine
Abou-Zeid
2013
Sudan
2302
23.7%
Schoolchildren
140
194
405
1563
Blood in urine
Bassiouny
2014
Yemen
696
18.1%
Schoolchildren
58
18
68
552
Blood in urine
Ismail
2014
Sudan
200
59.0%
Schoolchildren
56
12
62
70
Pain during urination
Warren
1979
Kenya
390
83.6%
Schoolchildren
189
25
137
39
Pain during urination
Pugh
1980
Nigeria
4296
15.2%
All
171
380
484
3261
Pain during urination
King
1988
Kenya
639
64.8%
All
177
63
237
162
Pain during urination
Ekanem
1995
Nigeria
510
34.7%
Schoolchildren
90
41
87
292
Pain during urination
Traquinho
1998
Mozambique
994
84.4%
Schoolchildren
456
55
383
100
Pain during urination
Traore
1998
Mali
1041
55.2%
All
223
134
352
332
Pain during urination
Takougang
2004
Cameroon
871
36.3%
Schoolchildren
142
91
174
464
Pain during urination
Fatiregun
2005
Nigeria
592
12.2%
Schoolchildren
18
65
54
455
Pain during urination
French
2007
Tanzania
1976
13.2%
Schoolchildren
43
25
217
1691
Pain during urination
Kapito-Tembo
2009
Malawi
1124
10.9%
Schoolchildren
46
204
77
797
Pain during urination
Bassiouny
2014
Yemen
696
18.1%
Schoolchildren
99
108
27
462
Pain during urination
Ismail
2014
Sudan
200
59.0%
Schoolchildren
82
32
36
50
History of schistosomiasis
Hammam
2000
Egypt
10419
5.4%
All
262
2434
305
7418
History of schistosomiasis
Gabr
2000
Egypt
10331
9.3%
All
210
1423
749
7949
History of schistosomiasis Abdel-Wahab
2000
Egypt
3470
14.5%
All
164
830
339
2137
History of schistosomiasis
2000
Egypt
7665
6.5%
All
195
1374
306
5790
History of schistosomiasis Kapito-Tembo
Hammam
2009
Malawi
1133
10.9%
Schoolchildren
73
230
50
780
History of schistosomiasis
2014
Yemen
696
18.1%
Schoolchildren
34
56
92
514
Bassiouny
13
Table S2. Characteristics of studies with data for the diagnostic questions used in the S. mansoni meta-analyses. First Author
Year of Publication
Country
Sample size
Prevalence
Ages
Abdominal pain
Cook
1974
St Lucia
138
83.3%
Abdominal pain
Arap Siongok
1976
Kenya
416
82.5%
Abdominal pain
Hiatt
1976
Ethiopia
197
Abdominal pain
Hiatt
1977
Ethiopia
Abdominal pain
Cline
1977
Abdominal pain
Sukwa
1985
Abdominal pain
Guimaraes
1985
Brazil
696
44.7%
All
Abdominal pain
Gryseels
1988
Burundi
6203
32.8%
All
Abdominal pain
Proietti
1989
Brazil
512
50.0%
All
53
42
203
214
Abdominal pain
Lima e Costa
1991
Brazil
403
41.2%
All
57
91
109
146
Abdominal pain
Cancado
1995
Brazil
1971
53.3%
All
419
276
631
645
Diagnostic Question
TP
FP
FN
TN
Schoolchildren
78
14
37
9
All
54
8
289
65
47.7%
All
46
25
48
78
272
88.2%
Schoolchildren
35
6
205
26
Puerto Rico
256
50.0%
All
52
49
76
79
Zambia
703
69.6%
All
224
84
265
130
138
167
173
218
1628
2834 407
1334
Bloody diarrhea
Omer
1976
Sudan
1748
48.2%
All
330
154
513
751
Bloody diarrhea
Sukwa
1986
Zambia
693
69.4%
All
145
27
336
185
Bloody diarrhea
Gryseels
1988
Burundi
6203
32.8%
All
265
167 1770
4001
Bloody diarrhea
Utzinger
2000
Cote d'Ivoire
322
76.4%
Schoolchildren
89
35
157
41
Blood in stool
Cook
1974
St Lucia
138
83.3%
Schoolchildren
46
10
69
13
Blood in stool
Hiatt
1977
Ethiopia
272
88.2%
Schoolchildren
28
2
212
30
Blood in stool
Arap Siongok
1976
Kenya
416
82.5%
All
48
7
295
66
Blood in stool
Hiatt
1976
Ethiopia
197
47.7%
All
14
4
80
99
Blood in stool
Cline
1977
Puerto Rico
256
50.0%
All
19
6
109
122
Blood in stool
Sukwa
1986
Zambia
693
69.4%
All
82
11
399
201
Blood in stool
Guimaraes
1985
Brazil
696
44.7%
All
109
93
202
292
Blood in stool
Proietti
1989
Brazil
512
50.0%
All
42
11
214
245
Blood in stool
Lima e Costa
1991
Brazil
403
41.2%
All
21
6
145
231
Blood in stool
Utzinger
1998
Cote d'Ivoire
209
49.3%
Schoolchildren
48
25
55
81
Blood in stool
Utzinger
2000
Cote d'Ivoire
322
76.4%
Schoolchildren
108
37
138
39
Blood in stool
Handzel
2003
Kenya
748
6.0%
Schoolchildren
34
396
11
307
Blood in stool
Cancado
1995
Brazil
1971
53.3%
Community
113
11
937
910
Blood in stool
Jemaneh
2002
Ethiopia
8006
20.9%
Unknown
870
633
803
5700
Blood in stool
Booth
1998
Tanzania
4130
5.8%
Unknown
36
156
204
3734
History of schistosomiasis
Barreto
1991
Brazil
778
27.6%
Schoolchildren
32
48
183
515
History of schistosomiasis Abdel-Wahab
2000
Egypt
6901
28.0%
All
560
711 1375
4255
History of schistosomiasis
El-Hawey
2000
Egypt
9661
41.9%
All
1616
1691 2434
3920
History of schistosomiasis
Barakat
2000
Egypt
11272
40.4%
All
2524
3617 2027
3104
History of schistosomiasis
Habib
2000
Egypt
7085
20.9%
All
329
1016 1154
4586
History of schistosomiasis
Nooman
2000
Egypt
6246
42.0%
All
1133
1178 1493
2442
14
Table S3. Average asset ownership by cluster in the constructed wealth index. IV V (Least poor) Asset I (Poorest) II III 100.0% House 7.9% 46.6% 95.4% 100.0% 100.0% 100.0% Latrine 7.9% 71.2% 98.0% 100.0% Land 31.6% 53.4% 77.2% 87.1% 98.7% Radio 34.2% 37.0% 46.0% 58.7% 16.4% TV 13.1% 26.0% 13.9% 15.4% 30.3% Motorcycle 0.0% 15.1% 18.5% 25.7% 99.8% Bicycle 23.7% 53.4% 30.4% 63.0% 100.0% Phone 39.5% 52.1% 42.7% 87.1% 8.2% 10.4% Fridge 5.3% 15.1% 9.3%
