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Lag effect of climatic variables on dengue burden in India
Dengue is a widespread vector-borne disease believed to affect between 100 and 390 million people every year. The interaction between vector, host and pathogen is influenced by various climatic factors and the relationship between dengue and climatic conditions has been poorly explored in India. Thi...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6518529/ https://www.ncbi.nlm.nih.gov/pubmed/31063099 http://dx.doi.org/10.1017/S0950268819000608 |
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author | Kakarla, Satya Ganesh Caminade, Cyril Mutheneni, Srinivasa Rao Morse, Andrew P Upadhyayula, Suryanaryana Murty Kadiri, Madhusudhan Rao Kumaraswamy, Sriram |
author_facet | Kakarla, Satya Ganesh Caminade, Cyril Mutheneni, Srinivasa Rao Morse, Andrew P Upadhyayula, Suryanaryana Murty Kadiri, Madhusudhan Rao Kumaraswamy, Sriram |
author_sort | Kakarla, Satya Ganesh |
collection | PubMed |
description | Dengue is a widespread vector-borne disease believed to affect between 100 and 390 million people every year. The interaction between vector, host and pathogen is influenced by various climatic factors and the relationship between dengue and climatic conditions has been poorly explored in India. This study explores the relationship between El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and dengue cases in India. Additionally, distributed lag non-linear model was used to assess the delayed effects of climatic factors on dengue cases. The weekly dengue cases reported by the Integrated Disease Surveillance Program (IDSP) over India during the period 2010–2017 were analysed. The study shows that dengue cases usually follow a seasonal pattern, with most cases reported in August and September. Both temperature and rainfall were positively associated with the number of dengue cases. The precipitation shows the higher transmission risk of dengue was observed between 8 and 15 weeks of lag. The highest relative risk (RR) of dengue was observed at 60 mm rainfall with a 12-week lag period when compared with 40 and 80 mm rainfall. The RR of dengue tends to increase with increasing mean temperature above 24 °C. The largest transmission risk of dengue was observed at 30 °C with a 0–3 weeks of lag. Similarly, the transmission risk increases more than twofold when the minimum temperature reaches 26 °C with a 2-week lag period. The dengue cases and El Niño were positively correlated with a 3–6 months lag period. The significant correlation observed between the IOD and dengue cases was shown for a 0–2 months lag period. |
format | Online Article Text |
id | pubmed-6518529 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-65185292019-06-04 Lag effect of climatic variables on dengue burden in India Kakarla, Satya Ganesh Caminade, Cyril Mutheneni, Srinivasa Rao Morse, Andrew P Upadhyayula, Suryanaryana Murty Kadiri, Madhusudhan Rao Kumaraswamy, Sriram Epidemiol Infect Original Paper Dengue is a widespread vector-borne disease believed to affect between 100 and 390 million people every year. The interaction between vector, host and pathogen is influenced by various climatic factors and the relationship between dengue and climatic conditions has been poorly explored in India. This study explores the relationship between El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and dengue cases in India. Additionally, distributed lag non-linear model was used to assess the delayed effects of climatic factors on dengue cases. The weekly dengue cases reported by the Integrated Disease Surveillance Program (IDSP) over India during the period 2010–2017 were analysed. The study shows that dengue cases usually follow a seasonal pattern, with most cases reported in August and September. Both temperature and rainfall were positively associated with the number of dengue cases. The precipitation shows the higher transmission risk of dengue was observed between 8 and 15 weeks of lag. The highest relative risk (RR) of dengue was observed at 60 mm rainfall with a 12-week lag period when compared with 40 and 80 mm rainfall. The RR of dengue tends to increase with increasing mean temperature above 24 °C. The largest transmission risk of dengue was observed at 30 °C with a 0–3 weeks of lag. Similarly, the transmission risk increases more than twofold when the minimum temperature reaches 26 °C with a 2-week lag period. The dengue cases and El Niño were positively correlated with a 3–6 months lag period. The significant correlation observed between the IOD and dengue cases was shown for a 0–2 months lag period. Cambridge University Press 2019-04-03 /pmc/articles/PMC6518529/ /pubmed/31063099 http://dx.doi.org/10.1017/S0950268819000608 Text en © The Author(s) 2019 http://creativecommons.org/licenses/by/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Paper Kakarla, Satya Ganesh Caminade, Cyril Mutheneni, Srinivasa Rao Morse, Andrew P Upadhyayula, Suryanaryana Murty Kadiri, Madhusudhan Rao Kumaraswamy, Sriram Lag effect of climatic variables on dengue burden in India |
title | Lag effect of climatic variables on dengue burden in India |
title_full | Lag effect of climatic variables on dengue burden in India |
title_fullStr | Lag effect of climatic variables on dengue burden in India |
title_full_unstemmed | Lag effect of climatic variables on dengue burden in India |
title_short | Lag effect of climatic variables on dengue burden in India |
title_sort | lag effect of climatic variables on dengue burden in india |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6518529/ https://www.ncbi.nlm.nih.gov/pubmed/31063099 http://dx.doi.org/10.1017/S0950268819000608 |
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