tetano
Editor, Senior Moderator
Epidemiol Infect. 2019 Jan;147:e217. doi: 10.1017/S0950268819001067.
[h=1]Real-time estimation of the influenza-associated excess mortality in Hong Kong.[/h] Wong JY[SUP]1[/SUP], Goldstein E[SUP]2[/SUP], Fang VJ[SUP]1[/SUP], Cowling BJ[SUP]1[/SUP], Wu P[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Statistical models are commonly employed in the estimation of influenza-associated excess mortality that, due to various reasons, is often underestimated by laboratory-confirmed influenza deaths reported by healthcare facilities. However, methodology for timely and reliable estimation of that impact remains limited because of the delay in mortality data reporting. We explored real-time estimation of influenza-associated excess mortality by types/subtypes in each year between 2012 and 2018 in Hong Kong using linear regression models fitted to historical mortality and influenza surveillance data. We could predict that during the winter of 2017/2018, there were ~634 (95% confidence interval (CI): (190, 1033)) influenza-associated excess all-cause deaths in Hong Kong in population ⩾18 years, compared to 259 reported laboratory-confirmed deaths. We estimated that influenza was associated with substantial excess deaths in older adults, suggesting the implementation of control measures, such as administration of antivirals and vaccination, in that age group. The approach that we developed appears to provide robust real-time estimates of the impact of influenza circulation and complement surveillance data on laboratory-confirmed deaths. These results improve our understanding of the impact of influenza epidemics and provide a practical approach for a timely estimation of the mortality burden of influenza circulation during an ongoing epidemic.
[h=4]KEYWORDS:[/h] Death; human influenza; impact
PMID: 31364545 PMCID: PMC6627011 DOI: 10.1017/S0950268819001067
Free PMC Article
[h=1]Real-time estimation of the influenza-associated excess mortality in Hong Kong.[/h] Wong JY[SUP]1[/SUP], Goldstein E[SUP]2[/SUP], Fang VJ[SUP]1[/SUP], Cowling BJ[SUP]1[/SUP], Wu P[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Statistical models are commonly employed in the estimation of influenza-associated excess mortality that, due to various reasons, is often underestimated by laboratory-confirmed influenza deaths reported by healthcare facilities. However, methodology for timely and reliable estimation of that impact remains limited because of the delay in mortality data reporting. We explored real-time estimation of influenza-associated excess mortality by types/subtypes in each year between 2012 and 2018 in Hong Kong using linear regression models fitted to historical mortality and influenza surveillance data. We could predict that during the winter of 2017/2018, there were ~634 (95% confidence interval (CI): (190, 1033)) influenza-associated excess all-cause deaths in Hong Kong in population ⩾18 years, compared to 259 reported laboratory-confirmed deaths. We estimated that influenza was associated with substantial excess deaths in older adults, suggesting the implementation of control measures, such as administration of antivirals and vaccination, in that age group. The approach that we developed appears to provide robust real-time estimates of the impact of influenza circulation and complement surveillance data on laboratory-confirmed deaths. These results improve our understanding of the impact of influenza epidemics and provide a practical approach for a timely estimation of the mortality burden of influenza circulation during an ongoing epidemic.
[h=4]KEYWORDS:[/h] Death; human influenza; impact
PMID: 31364545 PMCID: PMC6627011 DOI: 10.1017/S0950268819001067
Free PMC Article