Development and use of a reproducible framework for spatiotemporal climatic risk assessment and its association with decadal trend of dengue in India.
Introduction: The study aimed to develop a reproducible, open-source, and scalable framework for extracting climate data from satellite imagery, understanding dengue's decadal trend in India, and estimating the relationship between dengue occurrence and climatic factors. Materials and Methods: A fra...
| Publicado en: | Indian Journal of Community Medicine Vol. 47; no. 1; pp. 50 - 55 |
|---|---|
| Autores principales: | , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wolters Kluwer India Pvt Ltd
Jan-Mar2022
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=155938395&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 155938395 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09700218 1CQJ jtl: Indian Journal of Community Medicine issn: 09700218 maglogo: N pubinfo: dt: Jan-Mar2022 vid: 47 iid: 1 pid: 16919 pub: Wolters Kluwer India Pvt Ltd artinfo: ui: 155938395 155938395 155938395 10.4103/ijcm.ijcm_862_21 155938395 ppf: 50 ppct: 5 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Development and use of a reproducible framework for spatiotemporal climatic risk assessment and its association with decadal trend of dengue in India. aug: au: Singh, Gurpreet Mitra, Arun Soman, Biju affil: Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala sug: subj: Dengue Trends Dengue Epidemiology Climate India Dengue Risk Factors Risk Assessment Disease Surveillance Methods Telemetry Utilization Human India Software Design Temperature Rain Algorithms Correlation Coefficient Public Health ab: Introduction: The study aimed to develop a reproducible, open-source, and scalable framework for extracting climate data from satellite imagery, understanding dengue's decadal trend in India, and estimating the relationship between dengue occurrence and climatic factors. Materials and Methods: A framework was developed in the Open Source Software, and it was empirically tested using reported annual dengue occurrence data in India during 2010–2019. Census 2011 and population projections were used to calculate incidence rates. Zonal statistics were performed to extract climate parameters. Correlation coefficients were calculated to estimate the relationship of dengue with the annual average of daily mean and minimum temperature and rainy days. Results: Total 818,973 dengue cases were reported from India, with median annual incidence of 6.57 per lakh population; it was high in 2019 and 2017 (11.80 and 11.55 per lakh) and the Southern region (8.18 per lakh). The highest median annual dengue incidence was observed in Punjab (24.49 per lakh). Daily climatic data were extracted from 1164 coordinate locations across the country for the decadal period (4,249,734 observations). The annual average of daily temperature and rainy days positively correlated with dengue in India (r = 0.31 and 0.06, at P < 0.01 and 0.30, respectively). Conclusion: The study provides a reproducible algorithm for bulk climatic data extraction from research-level satellite imagery. Infectious disease models can be used to understand disease epidemiology and strengthen disease surveillance in the country. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|