Influenza as a Proportion of Pneumonia Mortality: United States, 1959–2009

Noymer, Andrew; Nguyen, Ann M.

doi:10.1080/19485565.2013.833816

Cited by 8 publications

(8 citation statements)

References 36 publications

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“…On the other hand, an advantage is that it could be applied to the tropics, where influenza circulation is more haphazard (see, e.g., Aungkulanon et al 2015), and therefore the colinearity of flu season and 'winter' is neither an appropriate identification strategy nor a lurking problem. Using nominal influenza mortality as an instrument instead of the seasons is another possibility, but it is not without its problems (Noymer and Nguyen 2013). Our results are broadly consistent with other seasonal analyses of mortality in the United States, going back to Rosenwaike (1966), as well as more recent work (Feinstein 2002).…”

Section: Discussionsupporting

confidence: 80%

Summertime, and the livin’ is easy: Winter and summer pseudoseasonal life expectancy in the United States

Ho¹,

Noymer²

2017

DemRes

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BACKGROUNDIn temperate climates, mortality is seasonal with a winter-dominant pattern, due in part to specific causes of death, including pneumonia, influenza, and cold-induced thrombosis. Cardiac causes, which are the leading cause of death in the United States, are winterseasonal, although the pathways are incompletely understood. Interactions between circulating respiratory viruses (e.g., influenza) and cardiac conditions have been suggested as a cause of winter-dominant mortality patterns. OBJECTIVEIn this paper we aim to quantify the total mortality burden of winter in the United States. METHODSWe calculate 'pseudoseasonal' life expectancy, dividing the year into two six-month spans, one encompassing winter, the other summer. RESULTSDuring the summer when cold weather is absent and the circulation of respiratory viruses is significantly reduced, life expectancy is about one year longer. We also quantify the seasonal mortality difference in terms of seasonal 'equivalent ages' (defined herein) and proportional hazards. CONTRIBUTIONWe quantify the effects of winter mortality. The population-level mortality reduction of a perfect influenza vaccine (which can only reduce a portion of winter-attributable mortality) would be much more modest than is often recognized. Summertime, And the livin' is easy Fish are jumpin' And the cotton is high -George Gershwin "Summertime" IntroductionThe primary goal of this paper is to quantify the mortality impact of winter in the United States, in terms of life expectancy.To accomplish this, we analyze life expectancy in the United States from a seasonal perspective. We calculate two life expectancies per 12-month period ('pseudowinter' and 'pseudosummer'), using methods described below.The point is to estimate life expectancy in the absence of respiratory viruses (most notably, influenza) and the effects of cold, using pseudosummer as an approximation. Pseudowinter, on the other hand, estimates life expectancy in the presence of these viruses and cold-induced conditions. The difference between life expectancy in pseudowinter and pseudosummer gives the total mortality impact of winter. The pseudoseasonal approach also illuminates within-year mortality fluctuations. Mortality in temperate climates is highly seasonal, with winter peaks and summer troughs (Rosenberg 1966;Land and Cantor 1983; Kalkstein and Davis 1989;Mackenbach, Kunst, and Looman 1992;Rau 2006; Deschênes and Moretti 2009; Deschênes and Greenstone 2011). Respiratory and cardiovascular causes, including stroke (Sheth et al. 1999;Yang et al. 2016), dominate the seasonal effects, with cancer being negligibly cyclical (Crombie et al. 1995). Heat wave mortality peaks are ephemeral interruptions of this overall pattern (e.g., Basu and Samet 2002;Klinenberg 2002;Valleron and Boumendil 2004; Kaiser et al. 2007;Toulemon and Barbieri 2008;Rocklöv, Ebi, and Forsberg 2011;Robine, Michel, and Herrmann 2012;Åström et al. 2013). Heat-wave-associated deaths have a different composition by cause compared to summer mortality...

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Section: Discussionsupporting

confidence: 80%

Summertime, and the livin’ is easy: Winter and summer pseudoseasonal life expectancy in the United States

Ho¹,

Noymer²

2017

DemRes

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“…On the other hand, an influenza infection could trigger a wide spectrum of secondary complications, such as bacterial infections, heart disease, or kidney and diabetes complications, among others (Simonsen et al 2011), and many deaths primarily due to influenza infections may be wrongly attributed to another cause. Previous analyses of U.S. death certificates confirm that reports of influenza as a standalone cause of death are not to be trusted and should be regrouped first with other causes of death prior its estimation and analysis (Noymer and Nguyen 2013). Given that our purpose is to specifically account for APC effects on influenza mortality, and not to precisely estimate general influenza mortality levels, we estimated the Serfling models based on the restricted P&I cause-of-death category.…”

Section: Methodsmentioning

confidence: 99%

Determinants of Influenza Mortality Trends: Age-Period-Cohort Analysis of Influenza Mortality in the United States, 1959–2016

et al. 2019

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This study examines the roles of age, period, and cohort in influenza mortality trends over the years 1959–2016 in the United States. First, we use Lexis surfaces based on Serfling models to highlight influenza mortality patterns as well as to identify lingering effects of early-life exposure to specific influenza virus subtypes (e.g., H1N1, H3N2). Second, we use age-period-cohort (APC) methods to explore APC linear trends and identify changes in the slope of these trends (contrasts). Our analyses reveal a series of breakpoints where the magnitude and direction of birth cohort trends significantly change, mostly corresponding to years in which important antigenic drifts or shifts took place (i.e., 1947, 1957, 1968, and 1978). Whereas child, youth, and adult influenza mortality appear to be influenced by a combination of cohort- and period-specific factors, reflecting the interaction between the antigenic experience of the population and the evolution of the influenza virus itself, mortality patterns of the elderly appear to be molded by broader cohort factors. The latter would reflect the processes of physiological capital improvement in successive birth cohorts through secular changes in early-life conditions. Antigenic imprinting, cohort morbidity phenotype, and other mechanisms that can generate the observed cohort effects, including the baby boom, are discussed.Electronic supplementary materialThe online version of this article (10.1007/s13524-019-00809-y) contains supplementary material, which is available to authorized users.

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“…17 However, as documented in other studies, 41,42 this could be potentially due to variation in coding practice across countries (e.g., respiratory diseases more or less likely to be coded as the underlying cause of death among patients with multiple chronic conditions) rather than a true difference in etiology of deaths or the consequences of influenza virus infections on mortality in different places. 43 …”

Section: Discussionmentioning

confidence: 99%

Influenza-Associated Excess Mortality in South Korea

Park

Goldstein

et al. 2016

American Journal of Preventive Medicine

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Introduction It is important to determine the health impact of influenza in order to calibrate public health measures. The objective of this study was to estimate excess mortality associated with influenza in Korea in 2003–2013. Methods The authors constructed multiple linear regression models in 2014 with weekly mortality rates stratified by age, region, and cause of death against weekly surveillance data on influenza virus collected in 2003–2013. Excess mortality rates were estimated using the difference between predicted mortality rates from the fitted model versus predicted mortality rates with the influenza covariate for each strain set to 0. Results During the study period, influenza was associated with an average of 2,900 excess deaths per year. The impact of influenza on mortality was significantly higher in older people; the overall all-cause excess annual mortality rate per 100,000 people was 5.97 (95% CI=4.89, 7.19), whereas it was 46.98 (95% CI=36.40, 55.82) for adults aged ≥65 years. It also greatly varied from year to year, ranging from 2.04 in 2009–2010 to 18.76 in 2011–2012. Conclusions The impact of influenza on mortality in Korea is substantial, particularly among the elderly and the rural population. More-comprehensive studies may be needed to estimate the full impact of influenza.

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Influenza as a Proportion of Pneumonia Mortality: United States, 1959–2009

Cited by 8 publications

References 36 publications

Summertime, and the livin’ is easy: Winter and summer pseudoseasonal life expectancy in the United States

Summertime, and the livin’ is easy: Winter and summer pseudoseasonal life expectancy in the United States

Determinants of Influenza Mortality Trends: Age-Period-Cohort Analysis of Influenza Mortality in the United States, 1959–2016

Influenza-Associated Excess Mortality in South Korea

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