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Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India
BACKGROUND: Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remai...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4074030/ https://www.ncbi.nlm.nih.gov/pubmed/24971510 http://dx.doi.org/10.1371/journal.pone.0099867 |
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author | Goswami, Prashant Murty, Upadhayula Suryanarayana Mutheneni, Srinivasa Rao Krishnan, Swathi Trithala |
author_facet | Goswami, Prashant Murty, Upadhayula Suryanarayana Mutheneni, Srinivasa Rao Krishnan, Swathi Trithala |
author_sort | Goswami, Prashant |
collection | PubMed |
description | BACKGROUND: Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. METHOD: We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. RESULTS: For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. CONCLUSION: The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria. |
format | Online Article Text |
id | pubmed-4074030 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-40740302014-07-02 Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India Goswami, Prashant Murty, Upadhayula Suryanarayana Mutheneni, Srinivasa Rao Krishnan, Swathi Trithala PLoS One Research Article BACKGROUND: Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. METHOD: We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. RESULTS: For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. CONCLUSION: The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria. Public Library of Science 2014-06-27 /pmc/articles/PMC4074030/ /pubmed/24971510 http://dx.doi.org/10.1371/journal.pone.0099867 Text en © 2014 Goswami et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Goswami, Prashant Murty, Upadhayula Suryanarayana Mutheneni, Srinivasa Rao Krishnan, Swathi Trithala Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India |
title | Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India |
title_full | Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India |
title_fullStr | Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India |
title_full_unstemmed | Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India |
title_short | Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India |
title_sort | relative roles of weather variables and change in human population in malaria: comparison over different states of india |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4074030/ https://www.ncbi.nlm.nih.gov/pubmed/24971510 http://dx.doi.org/10.1371/journal.pone.0099867 |
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