Schistosomiasis and Infertility in East Africa

Abstract

Case reports and pathology series suggest associations of female genital schistosomiasis (Schistosoma haematobium) with infertility and ectopic pregnancy. Differential geographic distribution of infertility is not explained by analyses of known risk factors. In this cross-sectional multilevel semi-ecologic study, interpolated prevalence maps for S. haematobium and Schistosoma mansoni in East Africa were created using data from two open-access Neglected Tropical Diseases Databases. Prevalence was extracted to georeferenced survey sample points for Demographic and Health Surveys for Ethiopia, Kenya, Tanzania, and Uganda for 2000 and 2010. Exploratory spatial analyses showed that infertility was not spatially random and mapped the clustering of infertility and its co-location with schistosomiasis. Multilevel logistic regression analysis demonstrated that women living in high compared with absent S. haematobium locations had significantly higher odds of infertility (2000 odds ratio [OR] = 1.5 [confidence interval₉₅ = 1.3, 1.8]; 2010 OR = 1.2 [1.1, 1.5]). Women in high S. haematobium compared with high S. mansoni locations had significantly higher odds of infertility (2000 OR 1.4 [1.1, 1.9]; 2010 OR 1.4 [1.1, 1.8]). Living in high compared with absent S. mansoni locations did not affect the odds of infertility. Infertility appears to be associated spatially with S. haematobium.

Figure 1.

Predicted distribution of Schistosoma haematobium and Schistosoma mansoni in East Africa. Empirical Bayesian kriging interpolation surface, ArcGIS Pro Geostatistical Analyst. Demographic and Health Surveys (DHS) sample cluster sites. Data sources: Global Neglected Tropical Diseases Database, Global Atlas of Helminth Infection, World Health Organization Global Atlas of Schistosomiasis, and DHS (Measure DHS). This figure appears in color at www.ajtmh.org.

Figure 2.

Getis-Ord hotspot analysis, infertility in East Africa; overlying *major cities (known risk factor) and Schistosoma haematobium prevalence (hypothesized risk factor). ArcGIS Pro (ESRI). Data sources: Demographic and Heath Surveys (Measure DHS), Global Neglected Tropical Diseases Database, Global Atlas of Helminth Infection, and World Health Organization Global Atlas of Schistosomiasis. This figure appears in color at www.ajtmh.org.

Figure 3.

Association of infertility with schistosomiasis, East Africa. Bivariate Local Indicators of Spatial Association, as maps of local-scale associations. GeoDa 1.6.6. Data sources: Demographic and Heath Surveys (Measure DHS), Global Neglected Tropical Diseases Database, Global Atlas of Helminth Infection, and World Health Organization Global Atlas of Schistosomiasis. This figure appears in color at www.ajtmh.org.