ArticleOsong public health and research perspectives2022
Spatiotemporal analysis of environmental and physiographic factors related to malaria in Bareilly district, India.
Article in Osong public health and research perspectives, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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2 citing papers in PubMed, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.
- Association between temperature and malaria (1959-2019): a systematic review and meta-analysis.Archives of public health = Archives belges de sante publique · 2025Pooled it
- Spatial Analysis of Malaria in Bangladesh: Insights from Bayesian Disease Mapping Models.PloS one · 2026Article
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Authors and funding
2 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
objectivesThe aim of this study was to explore the spatiotemporal clustering of reported malaria cases and to study the effects of various environmental and physiographic factors on malaria incidence in Bareilly district, Uttar Pradesh, India.
methodsMalaria surveillance data were collected from the state health department and cleaned into an analyzable format. These data were analyzed along with meteorological, physiographic, and 2019 population data, which were obtained from the Indian Meteorological Department, National Aeronautics and Space Administration web portal, the Bhuvan platform of the Indian Space Research Organization, and the 2011 Census of India.
resultsIn total, 46,717 malaria cases were reported in Bareilly district in 2019, of which 25.99% were Plasmodium vivax cases and 74.01% were P. falciparum cases. The reported malaria cases in the district showed clustering, with significant spatial autocorrelation (Moran's I value=0.63), and space-time clustering (p<0.01). A significant positive correlation was found between monthly malaria incidence and the monthly mean temperature (with a lag of 1-2 months) and rainfall (with a lag of 1 month). A significant negative correlation was detected between the elevation of blocks (i.e., intermediate-level administrative districts) and annual malaria reporting.
conclusionThe presence of space-time clustering of malaria cases and its correlation with meteorological and physiographic factors indicate that routine spatial analysis of the surveillance data could help control and manage malaria outbreaks in the district.
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