Global Mortality Estimates for the 2009 Influenza Pandemic from the GLaMOR Project: A Modeling Study

Simonsen, Lone; Spreeuwenberg, Peter; Lustig, Roger; Taylor, Robert J.; Fleming, Douglas; Kroneman, Madelon; Kerkhove, Maria D. Van; Mounts, Anthony W.; Paget, W J

doi:10.1371/journal.pmed.1001558

Cited by 413 publications

(428 citation statements)

References 43 publications

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“…While we were aware that Poisson family models are conventionally used for statistical modeling of count data and incidence rates,21 we considered the mechanism by which influenza incidence leads to deaths and hypothesized that there should be a linear correlation between incidence and mortality 3. We therefore used an identity link rather than a logarithmic link to relate incidence to mortality in our model, as many others have done 3, 4, 6, 10, 11, 12, 13. We used a normal error distribution, but results would have been similar with a Poisson family error distribution as the numbers of deaths each week were not small.…”

Section: Discussionmentioning

confidence: 99%

Influenza‐associated mortality in Yancheng, China, 2011‐15

Zhang¹,

Xiong

et al. 2017

Influenza Resp Viruses

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IntroductionThe Yangtze river delta in eastern China, centered on Shanghai, is one of the most populated regions of the world with more than 100 million residents. We examined the impact of influenza on excess mortality in Yancheng, a prefecture‐level city with 8.2 million population located 250 km north of Shanghai, during 2011‐2015.MethodsWe obtained individual data on deaths by date, age, sex, and cause in Yancheng from the Chinese Centers for Disease Control and Prevention, and used these to derive weekly rates of mortality from respiratory causes, respiratory and cardiovascular causes combined, and all causes. We used data on influenza‐like illnesses and laboratory detections of influenza to construct a proxy measure of the weekly incidence of influenza virus infections in the community. We used regression models to estimate the association of influenza activity with mortality and excess mortality by age, cause, and influenza type/subtype.ResultsWe estimated that an annual average of 4.59 (95% confidence interval: 3.94, 7.41) excess respiratory deaths per 100 000 persons were associated with influenza, which was 4.6% of all respiratory deaths in the years studied. Almost all influenza‐associated excess deaths occurred in persons ≥65 years. Influenza A(H3N2) had the greatest impact on mortality and was associated with around 50% of the influenza‐associated respiratory deaths in the 5 years studied.ConclusionsInfluenza has a substantial impact on respiratory mortality in Yancheng, mainly in older adults. Influenza vaccination has the potential to reduce disease burden, and cost‐effectiveness analysis could be used to compare policy options.

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Section: Discussionmentioning

confidence: 99%

Influenza‐associated mortality in Yancheng, China, 2011‐15

Zhang¹,

Xiong

et al. 2017

Influenza Resp Viruses

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show abstract

“…The weekly number of hospitalizations (by date of admission) for each subgroup was modeled as a function of viral activity, seasonality, and trend using a quasi‐Poisson regression model similar to previously published estimates of the influenza burden in Canada (see Appendix S2 for details)6, 7 and internationally 3. The number of hospitalizations attributed to each virus was calculated for each week by subtracting the estimated baseline from the model‐predicted number of hospitalizations.…”

Section: Methodsmentioning

confidence: 99%

“…Since 2003, a regression approach has been widely used in many countries,3, 5 including Canada to estimate the excess burden associated with influenza and other respiratory viruses 6, 7, 8, 9. Because regression estimates are not available in real time, researchers have proposed other methods10, 11 to use surveillance data to predict the full burden in near real time, only some of which have been evaluated at year‐end against a regression approach 6, 12, 13, 14…”

Section: Introductionmentioning

confidence: 99%

Burden of influenza, respiratory syncytial virus, and other respiratory viruses and the completeness of respiratory viral identification among respiratory inpatients, Canada, 2003‐2014

Schanzer

Saboui

Lee

et al. 2017

Influenza Resp Viruses

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BackgroundA regression‐based study design has commonly been used to estimate the influenza burden; however, these estimates are not timely and many countries lack sufficient virological data. Alternative approaches that would permit a timelier assessment of the burden, including a sentinel surveillance approach recommended by the World Health Organization (WHO), have been proposed. We aimed to estimate the hospitalization burden attributable to influenza, respiratory syncytial virus (RSV), and other respiratory viruses (ORV) and to assess both the completeness of viral identification among respiratory inpatients in Canada and the implications of adopting other approaches.MethodsRespiratory inpatient records were extracted from the Canadian Discharge Abstract Database from 2003 to 2014. A regression model was used to estimate excess respiratory hospitalizations attributable to influenza, RSV, and ORV by age group and diagnostic category and compare these estimates with the number with a respiratory viral identification.ResultsAn estimated 33 (95% CI: 29, 38), 27 (95% CI: 22, 33), and 27 (95% CI: 18, 36) hospitalizations per 100 000 population per year were attributed to influenza, RSV, and ORV, respectively. An influenza virus was identified in an estimated 78% (95% CI: 75, 81) and 17% (95% CI: 15, 21) of respiratory hospitalizations attributed to influenza for children and adults, respectively, and 75% of influenza‐attributed hospitalizations had an ARI diagnosis.ConclusionsHospitalization rates with respiratory viral identification still underestimate the burden. Approaches based on acute respiratory case definitions will likely underestimate the burden as well, although each proposed method should be compared with regression‐based estimates of influenza‐attributed burden as a way of assessing their validity.

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“…However, global mortality studies have shown that the 2009 influenza A(H1N1) pandemic virus did in fact affect mortality in tropical climate countries 19, 20. Both Dawood and Simonsen estimated high rates of influenza‐associated respiratory death related to the emergence of influenza A(H1N1)pdm09 in some tropical climate countries compared to other parts of the world 19, 20. Specifically, the influenza mortality estimated among <65 years old was higher in South‐East Asia during the pandemic year (2009) when compared with seasonal influenza epidemics 20.…”

mentioning

confidence: 99%

“…Both Dawood and Simonsen estimated high rates of influenza‐associated respiratory death related to the emergence of influenza A(H1N1)pdm09 in some tropical climate countries compared to other parts of the world 19, 20. Specifically, the influenza mortality estimated among <65 years old was higher in South‐East Asia during the pandemic year (2009) when compared with seasonal influenza epidemics 20. In addition, Alonso et al indicated that influenza A(H1N1)pdm09 did not affect mortality rates in Madagascar.…”

mentioning

confidence: 99%

Reply to Alonso et al. “Bangladesh and Rwanda: Cases of high burden of influenza in tropical countries?”

Ahmed

Roguski

Tempia

et al. 2018

Influenza Resp Viruses

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Global Mortality Estimates for the 2009 Influenza Pandemic from the GLaMOR Project: A Modeling Study

Abstract: Lone Simonsen and colleagues use a two-stage statistical modeling approach to estimate the global mortality burden of the 2009 influenza pandemic from mortality data obtained from multiple countries. Please see later in the article for the Editors' Summary

Cited by 413 publications

References 43 publications

Influenza‐associated mortality in Yancheng, China, 2011‐15

Influenza‐associated mortality in Yancheng, China, 2011‐15

Burden of influenza, respiratory syncytial virus, and other respiratory viruses and the completeness of respiratory viral identification among respiratory inpatients, Canada, 2003‐2014

Reply to Alonso et al. “Bangladesh and Rwanda: Cases of high burden of influenza in tropical countries?”

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