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Conference Paper: The infection fatality risk of pandemic influenza A (H1N1) in Hong Kong in 2009

TitleThe infection fatality risk of pandemic influenza A (H1N1) in Hong Kong in 2009
Authors
Issue Date2012
PublisherISIRV.
Citation
The 2012 ISIRV International Conference on Seasonal and Pandemic Influenza, Munich, Germany, 5-8 September 2012. In Incidence, Severity, and Impact: oral presentations, 2012, p. 2-3 How to Cite?
AbstractBACKGROUND: One measure of the severity of a pandemic influenza at an individual level is the risk of death among people infected by the new virus. However, there are complications in estimating both the numerator and denominator. Regarding the numerator, statistical estimates of the excess deaths associated with influenza virus infections tend to exceed the number of deaths associated with laboratory-confirmed infection. Regarding the denominator, few infections are laboratory confirmed, while differences in case definitions and approaches to case ascertainment can lead to wide variation in case fatality risk estimates. Serologic surveillance can be used to estimate the cumulative incidence of infection as a denominator that is more comparable across studies. MATERIALS AND METHODS: We compared excess death estimates based on different measures of influenza activity, including pH1N1 incidence rates, influenza-like illness (ILI) data, laboratory (LAB) data, and ILI×LAB data. pH1N1 incidence rates were estimated by deconvoluting the pH1N1 hospitalizations allowing for the delay from infection to hospitalization and scaling to serial cross-sectional serologic data. We applied time series regression models to all-cause mortality rates from 2001-2009 and included one measure of influenza activity as a covariate, and also adjusted for covariates including seasonal influenza activity, respiratory syncytial virus activity, mean temperature, and absolute humidity. Trigonometric components were included to allow for cyclic annual seasonality. We defined the infection fatality risk (IFR) as the number of influenza-associated deaths divided by the number of infections in a population, and the IFRc and IFRe as the IFR where numerators are based on deaths of confirmed cases and estimated excess deaths respectively. RESULTS: We estimated that the first wave of 2009 H1N1 was associated with approximately 232 excess deaths (95% CI, 136-328 excess deaths) in all ages in Hong Kong, mainly in the elderly. The point estimates of the risk of death on a per-infection basis increased substantially with age, from below 1 per 100,000 infections in children to 1100 per 100,000 infections in those 60-69 y of age. We compared the correlation between the ILI data, the LAB data, and ILI×LAB data versus age-standardized incidence rates. ILI data tended to overestimate lower levels of pH1N1 incidence, as did the LAB data to a lesser extent, while the product of ILI×LAB had the strongest correlation with pH1N1 incidence. CONCLUSIONS: The ILI×LAB proxy was highly correlated with the estimated pH1N1 incidence rates suggesting that it may be a better proxy of influenza activity than either the ILI or LAB data alone. Substantial variation in the age-specific infection fatality risk complicates comparison of the severity of different influenza strains.
DescriptionOral Presentations
Persistent Identifierhttp://hdl.handle.net/10722/182161

 

DC FieldValueLanguage
dc.contributor.authorWong, JYTen_US
dc.contributor.authorWu, Pen_US
dc.contributor.authorNishiura, Hen_US
dc.contributor.authorGoldstein, Een_US
dc.contributor.authorLau, EHYen_US
dc.contributor.authorYang, Len_US
dc.contributor.authorChuang, SKen_US
dc.contributor.authorTsang, Ten_US
dc.contributor.authorPeiris, JSMen_US
dc.contributor.authorWu, JTKen_US
dc.contributor.authorCowling, BJen_US
dc.date.accessioned2013-04-17T07:28:05Z-
dc.date.available2013-04-17T07:28:05Z-
dc.date.issued2012en_US
dc.identifier.citationThe 2012 ISIRV International Conference on Seasonal and Pandemic Influenza, Munich, Germany, 5-8 September 2012. In Incidence, Severity, and Impact: oral presentations, 2012, p. 2-3en_US
dc.identifier.urihttp://hdl.handle.net/10722/182161-
dc.descriptionOral Presentations-
dc.description.abstractBACKGROUND: One measure of the severity of a pandemic influenza at an individual level is the risk of death among people infected by the new virus. However, there are complications in estimating both the numerator and denominator. Regarding the numerator, statistical estimates of the excess deaths associated with influenza virus infections tend to exceed the number of deaths associated with laboratory-confirmed infection. Regarding the denominator, few infections are laboratory confirmed, while differences in case definitions and approaches to case ascertainment can lead to wide variation in case fatality risk estimates. Serologic surveillance can be used to estimate the cumulative incidence of infection as a denominator that is more comparable across studies. MATERIALS AND METHODS: We compared excess death estimates based on different measures of influenza activity, including pH1N1 incidence rates, influenza-like illness (ILI) data, laboratory (LAB) data, and ILI×LAB data. pH1N1 incidence rates were estimated by deconvoluting the pH1N1 hospitalizations allowing for the delay from infection to hospitalization and scaling to serial cross-sectional serologic data. We applied time series regression models to all-cause mortality rates from 2001-2009 and included one measure of influenza activity as a covariate, and also adjusted for covariates including seasonal influenza activity, respiratory syncytial virus activity, mean temperature, and absolute humidity. Trigonometric components were included to allow for cyclic annual seasonality. We defined the infection fatality risk (IFR) as the number of influenza-associated deaths divided by the number of infections in a population, and the IFRc and IFRe as the IFR where numerators are based on deaths of confirmed cases and estimated excess deaths respectively. RESULTS: We estimated that the first wave of 2009 H1N1 was associated with approximately 232 excess deaths (95% CI, 136-328 excess deaths) in all ages in Hong Kong, mainly in the elderly. The point estimates of the risk of death on a per-infection basis increased substantially with age, from below 1 per 100,000 infections in children to 1100 per 100,000 infections in those 60-69 y of age. We compared the correlation between the ILI data, the LAB data, and ILI×LAB data versus age-standardized incidence rates. ILI data tended to overestimate lower levels of pH1N1 incidence, as did the LAB data to a lesser extent, while the product of ILI×LAB had the strongest correlation with pH1N1 incidence. CONCLUSIONS: The ILI×LAB proxy was highly correlated with the estimated pH1N1 incidence rates suggesting that it may be a better proxy of influenza activity than either the ILI or LAB data alone. Substantial variation in the age-specific infection fatality risk complicates comparison of the severity of different influenza strains.-
dc.languageengen_US
dc.publisherISIRV.en_US
dc.relation.ispartofIncidence, Severity, and Impact: oral presentationsen_US
dc.titleThe infection fatality risk of pandemic influenza A (H1N1) in Hong Kong in 2009en_US
dc.typeConference_Paperen_US
dc.identifier.emailWong, JYT: ytwongj@hku.hken_US
dc.identifier.emailWu, P: pengwu@hku.hken_US
dc.identifier.emailNishiura, H: nishiura@hku.hken_US
dc.identifier.emailGoldstein, E: egoldste@hsph.harvard.eduen_US
dc.identifier.emailLau, EHY: ehylau@hku.hken_US
dc.identifier.emailYang, L: linyang@hku.hken_US
dc.identifier.emailPeiris, JSM: malik@hkucc.hku.hken_US
dc.identifier.emailWu, JTK: joewu@hku.hk-
dc.identifier.emailCowling, BJ: bcowling@hku.hk-
dc.identifier.authorityNishiura, H=rp01488en_US
dc.identifier.authorityLau, EHY=rp01349en_US
dc.identifier.authorityPeiris, JSM=rp00410en_US
dc.identifier.authorityWu, JTK=rp00517en_US
dc.identifier.authorityCowling, BJ=rp01326en_US
dc.description.naturelink_to_OA_fulltext-
dc.identifier.hkuros213743en_US
dc.identifier.spage2en_US
dc.identifier.epage3en_US
dc.publisher.placeGermany-

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