Spatiotemporal analysis of environmental and physiographic factors related to malaria in Bareilly district, India
Objectives The 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. Methods Malaria surveillance data were collected from t...
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| Format: | Article |
| Language: | English |
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Korea Disease Control and Prevention Agency
2022-04-01
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| Series: | Osong Public Health and Research Perspectives |
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| Online Access: | http://ophrp.org/upload/pdf/j-phrp-2021-0304.pdf |
| _version_ | 1797725527934500864 |
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| author | Shikhar Chaudhary Biju Soman |
| author_facet | Shikhar Chaudhary Biju Soman |
| author_sort | Shikhar Chaudhary |
| collection | DOAJ |
| description | Objectives The 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. Methods Malaria 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. Results In 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. Conclusion The 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. |
| first_indexed | 2024-03-12T10:32:33Z |
| format | Article |
| id | doaj.art-3cf1ff17b5ad438a8658ebdc459b8247 |
| institution | Directory Open Access Journal |
| issn | 2210-9099 2210-9110 |
| language | English |
| last_indexed | 2024-03-12T10:32:33Z |
| publishDate | 2022-04-01 |
| publisher | Korea Disease Control and Prevention Agency |
| record_format | Article |
| series | Osong Public Health and Research Perspectives |
| spelling | doaj.art-3cf1ff17b5ad438a8658ebdc459b82472023-09-02T09:06:24ZengKorea Disease Control and Prevention AgencyOsong Public Health and Research Perspectives2210-90992210-91102022-04-0113212313210.24171/j.phrp.2021.0304653Spatiotemporal analysis of environmental and physiographic factors related to malaria in Bareilly district, IndiaShikhar Chaudhary0Biju Soman1 Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, IndiaObjectives The 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. Methods Malaria 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. Results In 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. Conclusion The 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.http://ophrp.org/upload/pdf/j-phrp-2021-0304.pdfcluster analysisgeographical information systemsmalariameteorologicalspatiotemporalsurveillance |
| spellingShingle | Shikhar Chaudhary Biju Soman Spatiotemporal analysis of environmental and physiographic factors related to malaria in Bareilly district, India Osong Public Health and Research Perspectives cluster analysis geographical information systems malaria meteorological spatiotemporal surveillance |
| title | Spatiotemporal analysis of environmental and physiographic factors related to malaria in Bareilly district, India |
| title_full | Spatiotemporal analysis of environmental and physiographic factors related to malaria in Bareilly district, India |
| title_fullStr | Spatiotemporal analysis of environmental and physiographic factors related to malaria in Bareilly district, India |
| title_full_unstemmed | Spatiotemporal analysis of environmental and physiographic factors related to malaria in Bareilly district, India |
| title_short | Spatiotemporal analysis of environmental and physiographic factors related to malaria in Bareilly district, India |
| title_sort | spatiotemporal analysis of environmental and physiographic factors related to malaria in bareilly district india |
| topic | cluster analysis geographical information systems malaria meteorological spatiotemporal surveillance |
| url | http://ophrp.org/upload/pdf/j-phrp-2021-0304.pdf |
| work_keys_str_mv | AT shikharchaudhary spatiotemporalanalysisofenvironmentalandphysiographicfactorsrelatedtomalariainbareillydistrictindia AT bijusoman spatiotemporalanalysisofenvironmentalandphysiographicfactorsrelatedtomalariainbareillydistrictindia |