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ABSTRACT: 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.
SUBMITTER: Nisar N
PROVIDER: S-EPMC6641468 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Nisar Nadia N Badar Nazish N Aamir Uzma Bashir UB Yaqoob Aashifa A Tripathy Jaya Prasad JP Laxmeshwar Chinmay C Munir Fariha F Zaidi Syed Sohail Zahoor SSZ
PloS one 20190719 7
<h4>Background</h4>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.<h4>Methods</h4>This is a descriptive study o ...[more]