ArticleData in brief2026
An integrated case-based leptospirosis surveillance dataset with environmental context from a tropical coastal city in Indonesia, 2018-2023.
Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
8 authors.
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Abstract
This dataset contains anonymised leptospirosis surveillance records collected in Semarang, Central Java, Indonesia between 2018 and 2023. Case data were derived from routine public health surveillance conducted by community health centre teams. The primary dataset includes patient demographic characteristics, case classification status, documented clinical events expressed as day offsets relative to registration date, exposure history to standing and contaminated water, animal contact variables, personal protective equipment usage, bathing practices, wound conditions, and household environmental characteristics. Spatial context is provided at the kelurahan level, the smallest formal government administrative unit in Indonesia with defined spatial boundaries, enabling geospatial analysis while preserving individual privacy. Secondary contextual datasets include administrative boundaries, land use classification, healthcare facility locations, flood related indicators, population statistics, and monthly weather variables such as temperature, relative humidity, and rainfall. Personally identifiable information and direct healthcare facility identifiers were removed prior to dataset construction. This dataset supports research in disease surveillance, spatial epidemiology, environmental health, zoonotic transmission, and climate sensitive disease modelling in tropical urban settings.
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