Spatial heterogenicity of tuberculosis and dengue in Nepal

Nepal, a geographically diverse country in South Asia, faces significant public health challenges, including high burdens of tuberculosis (TB) and dengue. Understanding the spatial and temporal distribution of these issues are essential for developing effective interventions. This study aimed to identify spatial-temporal tuberculosis clusters for fiscal years (FY) 2020-2021 to 2022-2023 and dengue for 2021 to 2023 in Nepal using spatial-temporal analysis. A retrospective analysis using Kulldorff's spatial-temporal scan statistics was conducted, offering a reference for infectious disease research and guiding policymakers in resource prioritization and targeted interventions. In addition, this study employed a discrete Poisson probability model to analyze the TB cases from FY 2020-2021 to 2022-2023 and dengue cases from 2020 to 2023 with a spatial window covering up to 50% of the population at risk. This study revealed significant geographic disparities in tuberculosis and dengue incidence across Nepal. For TB, primary clusters like Rautahat, Bara, Sarlahi, Mahottari and Kathmandu showed high Log-Likelihood Ratios (LLRs), indicating a persistent excess of observed cases, particularly in urban areas in FY 2022-2023. Secondary clusters also demonstrated elevated LLRs suggesting widespread TB risk. Similarly, dengue incidence was notably higher than expected in primary clusters such as Sankhuwasabha, Lalitpur, Bhaktapur and Kathmandu over three years, with urban areas experiencing sharp increases in 2022. This present study identified significant high-risk clusters for TB and dengue, emphasizing the need for targeted public health interventions in Nepal. Ongoing spatial-temporal analysis is crucial for adapting responses to evolving health challenges.