1. Epidemiology and Global Health
  2. Microbiology and Infectious Disease
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Impact of community piped water coverage on re-infection with urogenital schistosomiasis in rural South Africa

  1. Polycarp Mogeni  Is a corresponding author
  2. Alain Vandormael
  3. Diego Cuadros
  4. Christopher Appleton
  5. Frank Tanser
  1. Africa Health Research Institute, South Africa
  2. School of Nursing and Public Health, University of KwaZulu-Natal, South Africa
  3. KwaZulu-Natal Innovation and Sequencing Platform (KRISP), University of KwaZulu-Natal, South Africa
  4. Heidelberg Institute of Global Health, Faculty of Medicine, University of Heidelberg, Germany
  5. Department of Geography and Geographic Information Science, University of Cincinnati, United States
  6. Health Geography and Disease Modeling Laboratory, University of Cincinnati, United States
  7. School of Life Sciences, University of KwaZulu-Natal, South Africa
  8. Lincoln International Institute for Rural Health, University of Lincoln, United Kingdom
Research Advance
Cite this article as: eLife 2020;9:e54012 doi: 10.7554/eLife.54012
6 figures, 2 tables and 6 additional files

Figures

Baseline screening for Schistosoma haematobium infection and re-infection follow-up rounds of the study participants.

Participants who were not linked to the population-based cohort study were excluded from the baseline analysis presented in our previous analyses (Tanser et al., 2018) and those not treated for infection at baseline were excluded from the re-infection analysis. Participants who were treated at baseline but not screened at round 1 were eligible for screening at round 2 if they provided informed consent.

Histograms of Schistosoma haematobium egg counts and community piped water coverage for the re-infection cohort participants (n = 378).

Panel (A) shows the distribution of egg counts/10 mL among children observed at follow-up round 1 and 2, and panel (B) shows the distribution of community piped water coverage among all study participants. Community piped water coverage in the community surrounding each child was derived from the population-based 2007 piped water use survey conducted in all households in the study area.

Prevalence of Schistosoma haematobium re-infection and intensity of re-infection by age and sex among children taking part in the re-infection cohort (n = 378).

Blue represents light re-infections (<50 eggs per 10 ml urine) and Red represents heavy re-infections (≥50 eggs per 10 ml urine). Panels A and B show the prevalence of Schistosoma haematobium for female and male children respectively.

Margin plot of piped water coverage and re-infection intensity.

The margin plot was constructed from the final parsimonious multivariable negative binomial regression model for the pooled dataset (n = 378, incidence rate ratio = 0.96, p=0.004). Piped water coverage was estimated using the Gaussian kernel density methodology.

Geospatial heterogeneity in Schistosoma haematobium geometric mean egg counts (intensity of re-infection) across the study area.

The map shows the geographical distribution of mean egg counts/10 mL estimated using the Gaussian kernel of 3 km radius for the pooled re-infection cohort datasets (n = 378). Superimposed on the map is the local cluster (radius = 6.93 km, geometric mean egg count = 54.95, p=0.006) detected using Kulldorff’s spatial scan statistic.

Location of the study area in South Africa.

Panel A displays the map of South Africa highlighting the major towns and the location of the study area. Panel B displays the map of the study area showing the major roads and the coverage of piped water (%) in 2007. Community piped water coverage was estimated using the Gaussian kernel methodology (Tanser et al., 2018).

Tables

Table 1
Characteristics of children enrolled in the re-infection cohort.
Follow-up round 1
(N = 253)
Follow-up round 2
(N = 125)
TotalInfected n(%)(95% CI)TotalInfected n(%)(95% CI)
Overall25361 (24.1)(19.0–29.9)12524 (19.2)(12.7–27.2)
Gender
Female8616 (18.6)(11.0–28.4)335 (15.2)(5.1–31.9)
Male16745 (27.0)(20.4–34.3)9219 (20.7(12.9–30.4)
Age group
≤104113 (31.7)(18.1–48.1)287 (25.0)(10.7–44.9)
117115 (21.1)(12.3–32.4)345 (14.7)(5.0–31.1)
127418 (24.3)(15.1–35.7)296 (20.7)(8.0–39.7)
≥136715 (22.4)(13.1–34.2)346 (17.6)(6.8–34.5)
Community piped water coverage (%)
<705817 (29.3)(18.1–42.7)315 (16.1)(5.5–33.7)
70 - < 906613 (19.7)(10.9–31.3)288 (28.6)(13.2–48.7)
≥9012931 (24.0)(16.9–32.3)6611 (16.6)(8.6–27.9)
Altitude class (meters)
<50175 (29.4)(10.3–56.0)146 (42.9)(17.7–71.1)
50–10014031 (22.1)(15.6–29.9)6211 (17.7)(9.2–29.5)
100–1508421 (25.0)(16.2–35.6)425 (11.9)(4.0–25.6)
150–20072 (28.6)(3.7–71.0)30 (0)(0–70.8)
≥20052 (40.0)(5.3–85.3)42 (50.0)(6.8–93.2)
Distance water body class
<1 km9220 (21.7)(13.8–31.6)4611 (23.9)(12.6–38.8)
1–2 km9825 (25.5)(17.2–35.3)428 (19.1)(8.6–34.1)
2–3 km4613 (28.3)(16.0–43.5)265 (19.2)(6.6–39.4)
>3 km173 (17.7)(3.8–43.4)110 (0)(0–28.5)
School grade
Grade 514437 (25.7)(18.8–33.6)7413 (17.6)(9.7–28.2)
Grade 610924 (22.0)(14.6–31.0)5111 (21.6)(11.3–35.3)
Toilet
No Toilet4713 (27.7)(15.6–42.6)231 (4.3)(0.1–21.9)
Toilet20648 (23.3)(17.7–29.7)10223 (22.6)(14.9–31.9)
Land cover classification
Closed shrubland14535 (24.1)(17.4–31.9)6512 (18.5)(9.9–30.0)
Open shrubland5914 (23.7)(13.6–36.6)346 (17.7)(6.8–34.5)
Sparse shrubland4111 (26.8)(14.2–42.9)196 (31.6)(12.6–56.6)
Thickett81 (12.50)(0.3–52.7)70 (0)(0–41.0)
Baseline intensity of infection
Light infection10535 (33.3)(24.4–43.2)5012 (24.0)(13.1–38.2)
Heavy infection14826 (17.6)(11.8–24.7)7512 (16.0)(8.6–26.3)
Sample size (N)253125
Table 2
Predictors of intensity of re-infection with Schistosoma haematobium (pooled analysis, n = 378).

Model 1 presents results from the univariable negative binomial model and Model 2 presents results from the final parsimonious multivariable negative binomial model. Homestead level piped water coverage was derived from a Gaussian kernel density estimation using data from a survey conducted in 2007.

Model 1: univariable
(n = 378)
Model 2: multivariable
(n = 378)
CovariatesIRR95%P-valueIRR95%P-value
Female0.170.06–0.540.0030.140.06–0.32<0.001
Community piped water coverage (continuous effect)0.960.93–0.980.0020.960.93–0.980.004
Age at baseline (years)0.680.50–0.930.0170.780.59–1.040.094
Altitude class (ref < 50)
50–1003.650.91–14.50.0671.200.31–4.560.793
100–1500.720.21–2.540.6120.410.1–1.740.226
≥1500.110.02–0.620.0120.050.01–0.320.001
Land cover class (ref. Sparse shrubland)
Closed shrubland1.960.51–7.570.3270.860.34–2.210.754
Open shrubland/grassland1.770.33–9.490.5081.410.48–4.160.533
Thickett0.010.00–0.06<0.0010.020.00–0.200.001
Toilet in household (ref. no toilet)2.710.70–10.40.1480.770.24–2.460.662
Grade (ref. Grade 5)0.240.08–0.750.0141.350.52–3.480.540
Visit (ref. Follow up 1)1.010.21–4.920.9890.740.31–1.760.494
Distance to water body class
(ref. < 1 km)
1–2 km0.110.03–0.34<0.001
2–3 km0.180.04–0.850.031
>3 km0.080.01–0.540.010
Household wealth index
(ref. 1st quintile)
23.750.49–28.70.203
30.380.08–1.830.233
43.220.63–16.30.159
51.710.03–1.700.432
Square root of slope0.770.45–1.320.340
Baseline intensity of infection (ref. Light infection)2.590.81–8.300.110
Alpha (overdispersion parameter)22.617.9–28.3<0.001

Data availability

The datasets used for the analysis presented in this study are available from the Africa Health Research Institute (AHRI) data repository https://data.africacentre.ac.za/index.php/auth/login/?destination=. To access the licensed datasets, the applicant must agree to the terms and conditions of use by completing an Application for Access to a Licensed Dataset. This request will be reviewed by the AHRI Data Release Committee, who may decide to approve the request, to deny access to the data, or to request additional information from the applicant.

Additional files

Source data 1

Prevalence of re-infection, intensity of re-infection and re-infection rate (per 100-person year of follow-up) among individuals treated at baseline for S. haematobium infection.

https://cdn.elifesciences.org/articles/54012/elife-54012-data1-v2.docx
Supplementary file 1

Predictors of Schistosoma haematobium re-infection using data from follow up round 1 only.

Model 1 presents results from a univariable negative binomial model and Model 2 presents results from a multivariable negative binomial model (N = 253).

https://cdn.elifesciences.org/articles/54012/elife-54012-supp1-v2.docx
Supplementary file 2

Predictors of Schistosoma haematobium re-infection using data from follow up round 2 only.

Model 1 presents results from a univariable negative binomial and Model 2 presents results from a multivariable negative binomial model (N = 125).

https://cdn.elifesciences.org/articles/54012/elife-54012-supp2-v2.docx
Supplementary file 3

Characteristics of participants who dropped out of the study at follow-up round 1.

Piped water coverage (exposure variable) was similar between participants who dropped out of the study and those that were enrolled and examined. Significantly higher dropouts were only observed among participants residing further from water bodies. Piped water coverage was derived from the Gaussian kernel density estimation of radius three kilometers.

https://cdn.elifesciences.org/articles/54012/elife-54012-supp3-v2.docx
Supplementary file 4

Characteristics of participants who dropped out of the study at follow-up round 2.

Piped water coverage (exposure variable) was similar between participants who dropped out of the study and those that were enrolled and examined. Significantly higher dropouts were only observed among girls. Piped water coverage was derived from the Gaussian kernel density estimation of radius three kilometers.

https://cdn.elifesciences.org/articles/54012/elife-54012-supp4-v2.docx
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https://cdn.elifesciences.org/articles/54012/elife-54012-transrepform-v2.docx

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