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Influenza-associated excess mortality by age, sex, and subtype/lineage, in a subtropical city in China, 2015-2018: a population-based study with a distributed lag non-linear model (Preprint)

Authors: Ze-Lin Yan; Lei Luo; Wen-Hui Liu; Zhou Yang; Chen Shi; Bo-Wen Ming; Jun Yang; +3 Authors

Influenza-associated excess mortality by age, sex, and subtype/lineage, in a subtropical city in China, 2015-2018: a population-based study with a distributed lag non-linear model (Preprint)

Abstract

BACKGROUND Accurate estimation of influenza death burden is of great significance for influenza prevention and control. However, few studies have considered the short-term harvesting effects of influenza on mortality when estimating influenza-associated excess deaths by cause of death, age, sex, subtype/lineage. OBJECTIVE This study aimed to estimate cause-, age- and sex-specific excess mortality associated with influenza and its subtypes/lineages in Guangzhou from 2015 to 2018. METHODS Distributed lag non-linear models were fitted to estimate the excess mortality related to influenza subtypes/lineages for different causes of death, age groups, and sex based on the daily time-series data on mortality, influenza, and meteorological factors. RESULTS A total of 199.8 thousand death certificates were included in the study. The average annual influenza-associated excess mortality rate (EMR) was 25.06 (95% empirical confidence interval [eCI], 19.85–30.16) per 100,000 persons, among which 81.2% were due to respiratory and cardiovascular (R&C) mortality (EMR: 20.36 [95% eCI:16.75–23.74]). Excess R&C deaths in people aged 60–79 years and those aged ≥80 accounted for 32.9% and 63.7%, respectively. The average annual excess R&C mortality rates attributed to influenza A(H3N2), B/Yamagata, B/Victoria, and A(H1N1) were 8.47 (95% eCI:6.60–10.30), 5.81 (95% eCI:3.35–8.25), 6.21 (95% eCI:2.31–9.97), and 0.07 (95% eCI:-5.57–5.70), respectfully. The male-to-female ratio of excess death from respiratory diseases was 1.34 (95% CI:1.17–1.54), while the ratio for cardiovascular diseases was 0.72 (95% CI:0.63–0.82). The mortality displacement of influenza A(H1N1), A(H3N2), and B/Yamagata was 2–5 days, but 5–13 days for B/Victoria. CONCLUSIONS This study suggests that the mortality burden of influenza B cannot be ignored. Including influenza A subtypes and B lineages in active surveillance and vaccination with quadrivalent vaccines would help to curb the mortality burden of influenza. The mechanisms of sex differences in influenza-associated mortality warrant further investigation. Our findings will help to better understand the magnitude and time-course of the effects of influenza on mortality.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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