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Seasonality of influenza and its association with meteorological parameters in two cities of Pakistan: A time series analysis
BACKGROUND: Influenza is known to have a specific pattern of seasonality the reasons for which are yet to be fully ascertained. Temperate zones show influenza epidemic during the winter months. The tropical and subtropical regions show more diverse influenza outbreak patterns. This study explores th...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6641468/ https://www.ncbi.nlm.nih.gov/pubmed/31323025 http://dx.doi.org/10.1371/journal.pone.0219376 |
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author | Nisar, Nadia Badar, Nazish Aamir, Uzma Bashir Yaqoob, Aashifa Tripathy, Jaya Prasad Laxmeshwar, Chinmay Munir, Fariha Zaidi, Syed Sohail Zahoor |
author_facet | Nisar, Nadia Badar, Nazish Aamir, Uzma Bashir Yaqoob, Aashifa Tripathy, Jaya Prasad Laxmeshwar, Chinmay Munir, Fariha Zaidi, Syed Sohail Zahoor |
author_sort | Nisar, Nadia |
collection | PubMed |
description | BACKGROUND: Influenza is known to have a specific pattern of seasonality the reasons for which are yet to be fully ascertained. Temperate zones show influenza epidemic during the winter months. The tropical and subtropical regions show more diverse influenza outbreak patterns. This study explores the seasonality of influenza activity and predicts influenza peak based on historical surveillance time series data in Islamabad and Multan, Pakistan. METHODS: This is a descriptive study of routinely collected monthly influenza sentinel surveillance data and meteorological data from 2012–16 in two sentinel sites of Pakistan: Islamabad (North) and Multan (Central). RESULTS: Mean number of cases of influenza and levels of precipitation were higher in Islamabad compared to Multan. Mean temperature and humidity levels were similar in both the cities. The number of influenza cases rose with decrease in precipitation and temperature in Islamabad during 2012–16, although the same cannot be said about humidity. The relationship between meteorological parameters and influenza incidence was not pronounced in case of Multan. The forecasted values in both the cities showed a significant peak during the month of January. CONCLUSION: The influenza surveillance system gave a better understanding of the disease trend and could accurately forecast influenza activity in Pakistan. |
format | Online Article Text |
id | pubmed-6641468 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-66414682019-07-25 Seasonality of influenza and its association with meteorological parameters in two cities of Pakistan: A time series analysis Nisar, Nadia Badar, Nazish Aamir, Uzma Bashir Yaqoob, Aashifa Tripathy, Jaya Prasad Laxmeshwar, Chinmay Munir, Fariha Zaidi, Syed Sohail Zahoor PLoS One Research Article BACKGROUND: Influenza is known to have a specific pattern of seasonality the reasons for which are yet to be fully ascertained. Temperate zones show influenza epidemic during the winter months. The tropical and subtropical regions show more diverse influenza outbreak patterns. This study explores the seasonality of influenza activity and predicts influenza peak based on historical surveillance time series data in Islamabad and Multan, Pakistan. METHODS: This is a descriptive study of routinely collected monthly influenza sentinel surveillance data and meteorological data from 2012–16 in two sentinel sites of Pakistan: Islamabad (North) and Multan (Central). RESULTS: Mean number of cases of influenza and levels of precipitation were higher in Islamabad compared to Multan. Mean temperature and humidity levels were similar in both the cities. The number of influenza cases rose with decrease in precipitation and temperature in Islamabad during 2012–16, although the same cannot be said about humidity. The relationship between meteorological parameters and influenza incidence was not pronounced in case of Multan. The forecasted values in both the cities showed a significant peak during the month of January. CONCLUSION: The influenza surveillance system gave a better understanding of the disease trend and could accurately forecast influenza activity in Pakistan. Public Library of Science 2019-07-19 /pmc/articles/PMC6641468/ /pubmed/31323025 http://dx.doi.org/10.1371/journal.pone.0219376 Text en © 2019 Nisar 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Nisar, Nadia Badar, Nazish Aamir, Uzma Bashir Yaqoob, Aashifa Tripathy, Jaya Prasad Laxmeshwar, Chinmay Munir, Fariha Zaidi, Syed Sohail Zahoor Seasonality of influenza and its association with meteorological parameters in two cities of Pakistan: A time series analysis |
title | Seasonality of influenza and its association with meteorological parameters in two cities of Pakistan: A time series analysis |
title_full | Seasonality of influenza and its association with meteorological parameters in two cities of Pakistan: A time series analysis |
title_fullStr | Seasonality of influenza and its association with meteorological parameters in two cities of Pakistan: A time series analysis |
title_full_unstemmed | Seasonality of influenza and its association with meteorological parameters in two cities of Pakistan: A time series analysis |
title_short | Seasonality of influenza and its association with meteorological parameters in two cities of Pakistan: A time series analysis |
title_sort | seasonality of influenza and its association with meteorological parameters in two cities of pakistan: a time series analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6641468/ https://www.ncbi.nlm.nih.gov/pubmed/31323025 http://dx.doi.org/10.1371/journal.pone.0219376 |
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