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Influenza-Associated Excess Mortality by Age, Sex, and Subtype/Lineage: Population-Based Time-Series Study With a Distributed-Lag Nonlinear Model

BACKGROUND: Accurate estimation of the 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...

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Autores principales: Li, Li, Yan, Ze-Lin, Luo, Lei, Liu, Wenhui, Yang, Zhou, Shi, Chen, Ming, Bo-Wen, Yang, Jun, Cao, Peihua, Ou, Chun-Quan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9878364/
https://www.ncbi.nlm.nih.gov/pubmed/36630176
http://dx.doi.org/10.2196/42530
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author Li, Li
Yan, Ze-Lin
Luo, Lei
Liu, Wenhui
Yang, Zhou
Shi, Chen
Ming, Bo-Wen
Yang, Jun
Cao, Peihua
Ou, Chun-Quan
author_facet Li, Li
Yan, Ze-Lin
Luo, Lei
Liu, Wenhui
Yang, Zhou
Shi, Chen
Ming, Bo-Wen
Yang, Jun
Cao, Peihua
Ou, Chun-Quan
author_sort Li, Li
collection PubMed
description BACKGROUND: Accurate estimation of the 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, and subtype/lineage. OBJECTIVE: This study aimed to estimate the cause-, age-, and sex-specific excess mortality associated with influenza and its subtypes and lineages in Guangzhou from 2015 to 2018. METHODS: Distributed-lag nonlinear models were fitted to estimate the excess mortality related to influenza subtypes or lineages for different causes of death, age groups, and sex based on daily time-series data for mortality, influenza, and meteorological factors. RESULTS: A total of 199,777 death certificates were included in the study. The average annual influenza-associated excess mortality rate (EMR) was 25.06 (95% empirical CI [eCI] 19.85-30.16) per 100,000 persons; 7142 of 8791 (81.2%) deaths were due to respiratory or cardiovascular mortality (EMR 20.36, 95% eCI 16.75-23.74). Excess respiratory and cardiovascular deaths in people aged 60 to 79 years and those aged ≥80 years accounted for 32.9% (2346/7142) and 63.7% (4549/7142) of deaths, respectively. The male to female ratio (MFR) of excess death from respiratory diseases was 1.34 (95% CI 1.17-1.54), while the MFR for excess death from cardiovascular disease was 0.72 (95% CI 0.63-0.82). The average annual excess respiratory and cardiovascular 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), 3.68 (95% eCI 0.81-6.49), and 2.83 (95% eCI –1.26 to 6.71), respectively. Among these influenza subtypes/lineages, A (H3N2) had the highest excess respiratory and cardiovascular mortality rates for people aged 60 to 79 years (20.22, 95% eCI 14.56-25.63) and ≥80 years (180.15, 95% eCI 130.75-227.38), while younger people were more affected by A (H1N1), with an EMR of 1.29 (95% eCI 0.07-2.32). The mortality displacement of influenza A (H1N1), A (H3N2), and B/Yamagata was 2 to 5 days, but 5 to 13 days for B/Victoria. CONCLUSIONS: Influenza was associated with substantial mortality in Guangzhou, occurring predominantly in the elderly, even after considering mortality displacement. The mortality burden of influenza B, particularly B/Yamagata, cannot be ignored. Contrasting sex differences were found in influenza-associated excess mortality from respiratory diseases and from cardiovascular diseases; the underlying mechanisms need to be investigated in future studies. Our findings can help us better understand the magnitude and time-course of the effect of influenza on mortality and inform targeted interventions for mitigating the influenza mortality burden, such as immunizations with quadrivalent vaccines (especially for older people), behavioral campaigns, and treatment strategies.
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spelling pubmed-98783642023-01-27 Influenza-Associated Excess Mortality by Age, Sex, and Subtype/Lineage: Population-Based Time-Series Study With a Distributed-Lag Nonlinear Model Li, Li Yan, Ze-Lin Luo, Lei Liu, Wenhui Yang, Zhou Shi, Chen Ming, Bo-Wen Yang, Jun Cao, Peihua Ou, Chun-Quan JMIR Public Health Surveill Original Paper BACKGROUND: Accurate estimation of the 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, and subtype/lineage. OBJECTIVE: This study aimed to estimate the cause-, age-, and sex-specific excess mortality associated with influenza and its subtypes and lineages in Guangzhou from 2015 to 2018. METHODS: Distributed-lag nonlinear models were fitted to estimate the excess mortality related to influenza subtypes or lineages for different causes of death, age groups, and sex based on daily time-series data for mortality, influenza, and meteorological factors. RESULTS: A total of 199,777 death certificates were included in the study. The average annual influenza-associated excess mortality rate (EMR) was 25.06 (95% empirical CI [eCI] 19.85-30.16) per 100,000 persons; 7142 of 8791 (81.2%) deaths were due to respiratory or cardiovascular mortality (EMR 20.36, 95% eCI 16.75-23.74). Excess respiratory and cardiovascular deaths in people aged 60 to 79 years and those aged ≥80 years accounted for 32.9% (2346/7142) and 63.7% (4549/7142) of deaths, respectively. The male to female ratio (MFR) of excess death from respiratory diseases was 1.34 (95% CI 1.17-1.54), while the MFR for excess death from cardiovascular disease was 0.72 (95% CI 0.63-0.82). The average annual excess respiratory and cardiovascular 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), 3.68 (95% eCI 0.81-6.49), and 2.83 (95% eCI –1.26 to 6.71), respectively. Among these influenza subtypes/lineages, A (H3N2) had the highest excess respiratory and cardiovascular mortality rates for people aged 60 to 79 years (20.22, 95% eCI 14.56-25.63) and ≥80 years (180.15, 95% eCI 130.75-227.38), while younger people were more affected by A (H1N1), with an EMR of 1.29 (95% eCI 0.07-2.32). The mortality displacement of influenza A (H1N1), A (H3N2), and B/Yamagata was 2 to 5 days, but 5 to 13 days for B/Victoria. CONCLUSIONS: Influenza was associated with substantial mortality in Guangzhou, occurring predominantly in the elderly, even after considering mortality displacement. The mortality burden of influenza B, particularly B/Yamagata, cannot be ignored. Contrasting sex differences were found in influenza-associated excess mortality from respiratory diseases and from cardiovascular diseases; the underlying mechanisms need to be investigated in future studies. Our findings can help us better understand the magnitude and time-course of the effect of influenza on mortality and inform targeted interventions for mitigating the influenza mortality burden, such as immunizations with quadrivalent vaccines (especially for older people), behavioral campaigns, and treatment strategies. JMIR Publications 2023-01-11 /pmc/articles/PMC9878364/ /pubmed/36630176 http://dx.doi.org/10.2196/42530 Text en ©Li Li, Ze-Lin Yan, Lei Luo, Wenhui Liu, Zhou Yang, Chen Shi, Bo-Wen Ming, Jun Yang, Peihua Cao, Chun-Quan Ou. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 11.01.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Li, Li
Yan, Ze-Lin
Luo, Lei
Liu, Wenhui
Yang, Zhou
Shi, Chen
Ming, Bo-Wen
Yang, Jun
Cao, Peihua
Ou, Chun-Quan
Influenza-Associated Excess Mortality by Age, Sex, and Subtype/Lineage: Population-Based Time-Series Study With a Distributed-Lag Nonlinear Model
title Influenza-Associated Excess Mortality by Age, Sex, and Subtype/Lineage: Population-Based Time-Series Study With a Distributed-Lag Nonlinear Model
title_full Influenza-Associated Excess Mortality by Age, Sex, and Subtype/Lineage: Population-Based Time-Series Study With a Distributed-Lag Nonlinear Model
title_fullStr Influenza-Associated Excess Mortality by Age, Sex, and Subtype/Lineage: Population-Based Time-Series Study With a Distributed-Lag Nonlinear Model
title_full_unstemmed Influenza-Associated Excess Mortality by Age, Sex, and Subtype/Lineage: Population-Based Time-Series Study With a Distributed-Lag Nonlinear Model
title_short Influenza-Associated Excess Mortality by Age, Sex, and Subtype/Lineage: Population-Based Time-Series Study With a Distributed-Lag Nonlinear Model
title_sort influenza-associated excess mortality by age, sex, and subtype/lineage: population-based time-series study with a distributed-lag nonlinear model
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9878364/
https://www.ncbi.nlm.nih.gov/pubmed/36630176
http://dx.doi.org/10.2196/42530
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