Literature DB >> 33548552

SARIMA-modelled greater severity and mortality during the 2010/11 post-pandemic influenza season compared to the 2009 H1N1 pandemic in English hospitals.

Krystal Lau1, Ilaria Dorigatti2, Marisa Miraldo3, Katharina Hauck2.   

Abstract

OBJECTIVE: The COVID-19 pandemic demonstrates the need for understanding pathways to healthcare demand, morbidity, and mortality of pandemic patients. We estimate H1N1 (1) hospitalization rates, (2) severity rates (length of stay, ventilation, pneumonia, and death) of those hospitalized, (3) mortality rates, and (4) time lags between infections and hospitalizations during the pandemic (June 2009 to March 2010) and post-pandemic influenza season (November 2010 to February 2011) in England.
METHODS: Estimates of H1N1 infections from a dynamic transmission model are combined with hospitalizations and severity using time series econometric analyses of administrative patient-level hospital data.
RESULTS: Hospitalization rates were 34% higher and severity rates of those hospitalized were 20%-90% higher in the post-pandemic period than the pandemic. Adults (45-64-years-old) had the highest ventilation and pneumonia hospitalization rates. Hospitalizations did not lag infection during the pandemic for the young (<24-years-old) but lagged by one or more weeks for all ages in the post-pandemic period. DISCUSSION: The post-pandemic flu season exhibited heightened H1N1 severity, long after the pandemic was declared over. Policymakers should remain vigilant even after pandemics seem to have subsided. Analysis of administrative hospital data and epidemiological modelling estimates can provide valuable insights to inform responses to COVID-19 and future influenza and other disease pandemics.
Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  H1N1; Hospitalizations; Mortality; Pandemics; Time series

Mesh:

Year:  2021        PMID: 33548552     DOI: 10.1016/j.ijid.2021.01.070

Source DB:  PubMed          Journal:  Int J Infect Dis        ISSN: 1201-9712            Impact factor:   3.623


  2 in total

1.  Time trend prediction and spatial-temporal analysis of multidrug-resistant tuberculosis in Guizhou Province, China, during 2014-2020.

Authors:  Wang Yun; Chen Huijuan; Liao Long; Lu Xiaolong; Zhang Aihua
Journal:  BMC Infect Dis       Date:  2022-06-07       Impact factor: 3.667

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Authors:  Yunye Zhou; Anca Draghici; Jaffar Abbas; Riaqa Mubeen; Maria Elena Boatca; Mohammad Asif Salam
Journal:  Front Psychiatry       Date:  2022-02-07       Impact factor: 4.157

  2 in total

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