Data analysis at community level for optimizing the use of Praziquantel among communities requiring preventive chemotherapy in Senegal

Abstract Background Over the past two decades, preventive chemotherapy (PC) with Praziquantel is the major strategy for controlling schistosomiasis in Senegal. This data analysis was aimed at updating the endemicity of schistosomiasis at community level for better targeting of mass treatment with Praziquantel in Senegal. Methods Demographic and epidemiological data from 1610 community health areas were analyzed using the WHO/AFRO schistosomiasis sub-district data optimization tool 2021. The tool appliease a WHO/AFRO decision tree for areas without epidemiological data to determine if mass tretaments should be continued at community level. Results Overall, the endemicity of the 1610 community health areas (CHA) were updated based on the data in JRSM form (40.5%) and the use of endemicity at implementation unit (IU) (33.5%). Up to 282 (17.5%) and 398 (24.7%) community health areas were classified as moderate and high endemicity. 41.1% of communities were non endemic. High endemicity was more important in Tambacounda, Saint Louis, Matam, Louga and Kedougou. A change in endemicity category was observed when data was disagregted from district level to community level. The number of implementation units classified as non endemic was higher at community level (n = 666) compared to district level (n = 324). Among 540 areas previously classified as high endemic by district level data aggregation, 392 (72.6%) remained high prevalence category, while 92 (17%) became moderate, 43 (8.0%) low and 13 (2.4%) non-endemics at community level. Number of IU requiring PC was more important at district level (1286) compared to community level (944). Number of SAC requiring treatment was also more important at district level compared to community level. Conclusion The analysis to disaggregate data from district level to community level using the WHO/AFRO schistoisomiasis sub-district data optimization tool has allowed to target schistisomiasis interventions, optimize use of available PZQ and exposed data gaps.