| Description |
Under-five children (U5-children) diarrhea is a significant public health threat, where the World Health Organisation (WHO) reported it as the second leading cause of children’s death worldwide. Nearly 1.7 billion cases occur annually with varied temporal and spatial factors. Identification of the spatiotemporal pattern and hotspot areas of U5-children diarrhea can assist targeted intervention and provide an early warning for more effective response measures. This study aimed at examining spatiotemporal variability along with the detection of hotspot areas for U5-children diarrhea in the Bench Maji Zone of southwestern Ethiopia, where resources are limited and cultural heterogeneity is highest. Retrospective longitudinal data of ten years of diarrhea records from January 2008 to December 2017 were used to identify hotspot areas. The incidence rate per 1,000 per year among children was calculated along with seasonal patterns of cases. The spatiotemporal analysis was made using SaTScan version 9.4, while spatial autocorrelations and hotspot identification were generated using ArcGIS 10.5 software. A total of 90,716 U5-children diarrhea cases were reported with an annual incidence rate of 36.1 per 1,000 U5-children, indicating a relative risk (RR) of 1.6 and a log-likelihood ratio (LLR) of 1,347.32 (p < 0.001). The highest incidence of diarrhea illness was recorded during the dry season and showed incidence rate increment from October to February. The risky clusters (RR > 1) were in the districts of Bero, Maji, Surma, Minit Shasha, Guraferda, Mizan Aman Town, and Sheko with annual cases of 127.93, 68.5, 65.12, 55.03, 55.67, 54.14 and 44.97 per 1,000, respectively. The lowest annual cases reported were in the four districts of Shay Bench, South Bench, North Bench, and Minit Goldiya, where RR was less than a unit. Six most likely clusters (Bero, Minit Shasha, Surma, Guraferda, South Bench, and Maji) and one lower RR area (North Bench) were hotspot districts. The U5-children's diarrhea in the study area showed an overall increasing trend during the dry seasons with non-random distribution over space and time. The data recorded during ten years and analyzed with the proper statistical tools helped to identify the hotspot areas with risky seasons where diarrhea could increase.#Theoretical sciences |