The incidence, and spatial trends of cholera in Sabah over 15 years: Repeated outbreaks in coastal areas

Abstract

Vibrio cholerae remains a notable public health challenge across Malaysia. Although the Malaysian state of Sabah is considered a cholera-affected area, gaps remain in understanding the epidemiological trends and spatial distribution of outbreaks. Therefore, to determine longitudinal and spatial trends in cholera cases data were obtained from the Sabah State Health Department for all notified cases of cholera between 2005–2020. A cholera outbreak is defined as one or more confirmed cases in a single locality with the evidence of local transmission. All records were geolocated to village level. Satellite-derived data and generalised linearized models were used to assess potential risk factors, including population density, elevation, and distance to the sea. Spatiotemporal clustering of reported cholera cases and zones of increased cholera risk were evaluated using the tau statistic (τ) at 550m, 5km and 10km distances. Over a 15-year period between 2005–2020, 2865 cholera cases were recorded in Sabah, with a mean incidence rate of 5.6 cases per 100,000 (95% CI: 3.4–7.9). From 2015–2020, 705 symptomatic cases and 727 asymptomatic cases were reported. Symptomatic cases primarily occurred in local Malaysian populations (62.6%, 441/705) and in children and adolescents under 15-years old (49.4%, 348/705). On average, cases were reported in areas with low population density (19.45 persons/km2), low elevations (19.45m) and near coastal areas. Spatiotemporal clustering of cholera cases was identified up to 3.5km, with increased village-level cholera risk within 500m and 5 days of initial case presentation to a health facility (Risk Ratio = 9.7, 95% CI: 7.5–12.4). Cholera incidence has high spatial and temporal heterogeneity within Sabah, with some districts experiencing repeated outbreaks. Cholera cases clustered across space and time, with village-level risk of cholera highest within 5 days and within close proximity to primary case villages, suggesting local transmission.

Spatiotemporal Modeling of Cholera, Uvira, Democratic Republic of the Congo, 2016−2020

“…We detected spatiotemporal clustering of cholera outbreaks during 2016–2020 in Uvira, DRC, that could inform early mitigation of seasonal outbreaks. The clustering methods produced aligned results compatible with a high-risk radius of ≤500 meters, as previously used for CATI in DRC ( 7 , 13 ) and similar to clustering in Matlab, Bangladesh, and coastal Sabah, Malaysia (500 meters, ≈5 days after cases began) ( 3 , 14 ). For RDT-positive cases within 5 days after cases began, we estimated a 1,105-meter high-risk radius, showing that a ≤1,000-meter risk window is optimal.…”