An investigation of geographical clusters of leptospirosis during the outbreak in Pangandaran, West Java, Indonesia.

Leptospirosis is neglected in many tropical developing countries, including Indonesia. Our research on this zoonotic disease aimed to investigate epidemiological features and spatial clustering of recent leptospirosis outbreaks in Pangandaran, West Java. The study analysed data on leptospirosis notifications between September 2022 and May 2023. Global Moran I and local indicator for spatial association (LISA) were applied. Comparative analysis was performed to characterise the identified hotspots of leptospirosis relative to its neighbourhoods. A total of 172 reported leptospirosis in 40 villages from 9 sub-districts in Pangandaran District were analysed. Of these, 132 cases (76.7%) were male. The median age was 49 years (interquartile range [IQR]: 34-59 years). Severe outcomes including renal failure, lung failure, and hepatic necrosis were reported in up to 5% of the cases. A total of 30 patients died, resulting in the case fatality rate (CFR) of 17.4%. Moran's I analysis showed significant spatial autocorrelation (I=0.293; p=0.002) and LISA results identified 7 High-High clusters (hotspots) in the Southwest, with the total population at risk at 26,184 people. The hotspots had more cases among older individuals (median age: 51, IQR: 36-61 years; p<0.001), more farmers (79%, p=0.001) and more evidence of the presence of rats (p=0.02). A comprehensive One Health intervention should be targeted towards these high-risk areas to control the transmission of leptospirosis. More empirical evidence is needed to understand the role of climate, animals and sociodemographic characteristics on the transmission of leptospirosis in the area studied.

Geo-clusters and socio-demographic profiles at village-level associated with COVID-19 incidence in the metropolitan city of Jakarta: An ecological study.

The Special Capital Region of Jakarta is the epicentre of the transmission of COVID-19 in Indonesia. However, much remains unknown about the spatial and temporal patterns of COVID-19 incidence and related socio-demographic factors explaining the variations of COVID-19 incidence at local level. COVID-19 cases at the village level of Jakarta from March 2020 to June 2021 were analyzed from the local public COVID-19 dashboard. Global and local spatial clustering of COVID-19 incidence was examined using the Moran's I and local Moran analysis. Socio-demographic profiles of identified hotspots were elaborated. The association between village characteristics and COVID-19 incidence was evaluated. The COVID-19 incidence was significantly clustered based on the geographical village level (Moran's I = 0.174; p = .002). Seventeen COVID-19 high-risk clusters were found and dynamically shifted over the study period. The proportion of people aged 20-49 (incidence rate ratio [IRR] = 1.016; 95% confidence interval [CI]: 1.012-1.019), proportion of elderly (≥50 years) (IRR = 1.045; 95% CI = 1.041-1.050), number of households (IRR = 1.196; 95% CI = 1.193-1.200), access to metered water for washing, and the main occupation of the residents were village level socio-demographic factors associated with the risk of COVID-19. Targeted public health responses such as restriction, improved testing and contact tracing, and improved access to health services for those vulnerable populations are essential in areas with high-risk COVID-19.