Precision and geographical prevalence mapping of schistosomiasis and soil-transmitted helminthiasis among school-aged children in selected districts of north-western Tanzania

BACKGROUND

The identification and mapping of at-risk populations at a lower administrative level than the district are prerequisites for the planning, resource allocation and design of impactful control intervention measures. Thus, the objective of the current study was to conduct sub-district precision mapping of soil-transmitted helminthiasis (STH) and schistosomiasis in 29 districts of north-western Tanzania using the current recommended World Health Organization criteria.

METHODS

A cross-sectional survey was conducted in 145 schools between March and May 2021. A urine filtration technique was used for the quantification of Schistosoma haematobium eggs, whereas quantification of Schistosoma mansoni and STH eggs was done using the Kato-Katz technique. Microhaematuria was examined using a urine dipstick.

RESULTS

The overall prevalences of any STH and schistosome infections were 9.3% [95% confidence interval (95%CI) 8.6-9.9] and 14.6% (95%CI 13.9-15.4), respectively. The overall prevalence of S. mansoni was 8.7% (95%CI 8.1-9.3), and 36.4%, 41.6%, and 21.9% of the children had low, moderate, and heavy infections, respectively. The overall prevalence of S. haematobium was 6.1% (95%CI 5.5-6.5), and 71.7% and 28.3% of the infected children had light and heavy intensity infections, respectively. The prevalence of microhaematuria was 7.3% (95%CI 6.7-7.8), with males having the highest prevalence (8.4%, P < 0.001). The prevalences of Trichuris trichiura, Ascaris lumbricoides and hookworm were, respectively, 1.3% (95%CI 0.1-1.5), 2.9% (95%CI 2.5-3.3) and 6.2% (95%CI 5.7-6.7). Most of the children infected with STH had light to moderate intensities of infection. The overall prevalence of co-infection with STH and schistosomiasis was 19.1%. The prevalence of schistosomiasis (P < 00.1) and STH (P < 0.001) varied significantly between schools and sub-districts. Schistosoma mansoni and S. haematobium were observed in 60 and 71 schools, respectively, whereas any STH was observed in 49 schools. In schools where schistosomiasis was observed, prevalence was < 10% in 90.8% of them, and ranged from ≥ 10% to < 50% in the other 9.2%. In schools where any STH was observed, the prevalence was < 10% in 87.7% of them.

CONCLUSIONS

The data reported here show that schistosomiasis and STH are widely distributed around Lake Victoria. In most of the schools where schistosomiasis and STH occurred the transmission thresholds were low. These data are important and need to be taken into consideration when decisions are made on the implementation of the next round of mass chemotherapies for schistosomiasis and STH in Tanzania.

GPS-based fine-scale mapping surveys for schistosomiasis assessment: a practical introduction and documentation of field implementation

BACKGROUND

Fine-scale mapping of schistosomiasis to guide micro-targeting of interventions will gain importance in elimination settings, where the heterogeneity of transmission is often pronounced. Novel mobile applications offer new opportunities for disease mapping. We provide a practical introduction and documentation of the strengths and shortcomings of GPS-based household identification and participant recruitment using tablet-based applications for fine-scale schistosomiasis mapping at sub-district level in a remote area in Pemba, Tanzania.

METHODS

A community-based household survey for urogenital schistosomiasis assessment was conducted from November 2020 until February 2021 in 20 small administrative areas in Pemba. For the survey, 1400 housing structures were prospectively and randomly selected from shapefile data. To identify pre-selected structures and collect survey-related data, field enumerators searched for the houses' geolocation using the mobile applications Open Data Kit (ODK) and MAPS.ME. The number of inhabited and uninhabited structures, the median distance between the pre-selected and recorded locations, and the dropout rates due to non-participation or non-submission of urine samples of sufficient volume for schistosomiasis testing was assessed.

RESULTS

Among the 1400 randomly selected housing structures, 1396 (99.7%) were identified by the enumerators. The median distance between the pre-selected and recorded structures was 5.4 m. A total of 1098 (78.7%) were residential houses. Among them, 99 (9.0%) were dropped due to continuous absence of residents and 40 (3.6%) households refused to participate. In 797 (83.1%) among the 959 participating households, all eligible household members or all but one provided a urine sample of sufficient volume.

CONCLUSIONS

The fine-scale mapping approach using a combination of ODK and an offline navigation application installed on tablet computers allows a very precise identification of housing structures. Dropouts due to non-residential housing structures, absence, non-participation and lack of urine need to be considered in survey designs. Our findings can guide the planning and implementation of future household-based mapping or longitudinal surveys and thus support micro-targeting and follow-up of interventions for schistosomiasis control and elimination in remote areas. Trial registration ISRCTN, ISCRCTN91431493. Registered 11 February 2020, https://www.isrctn.com/ISRCTN91431493.