Evidence map›Paper›PMID 41541067›Full record

ArticleInfectious medicine2025

Estimated incidence of influenza in Guangzhou, China, 2019-2022.

Di Wu, Zhaonian Tan, Yanhui Liu, Mengmeng Ma, Zhitao Chen, Dedong Wang, Lei Luo, Pengzhe Qin

Abstract read
In one paragraph

Article in Infectious medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Di WuGuangzhou Center for Disease Control and Prevention, School of Public Health, Guangzhou Medical University, Guangzhou 510440, Guangdong Province, China.
Zhaonian TanSchool of Public Health, Guangdong Pharmaceutical University, Guangzhou 510006, Guangdong Province, China.
Yanhui LiuGuangzhou Center for Disease Control and Prevention, School of Public Health, Guangzhou Medical University, Guangzhou 510440, Guangdong Province, China.
Mengmeng MaGuangzhou Center for Disease Control and Prevention, School of Public Health, Guangzhou Medical University, Guangzhou 510440, Guangdong Province, China.
Zhitao ChenDepartment of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, Guangdong Province, China.
Dedong WangGuangzhou Center for Disease Control and Prevention, School of Public Health, Guangzhou Medical University, Guangzhou 510440, Guangdong Province, China.
Lei LuoGuangzhou Center for Disease Control and Prevention, School of Public Health, Guangzhou Medical University, Guangzhou 510440, Guangdong Province, China.
Pengzhe QinGuangzhou Center for Disease Control and Prevention, School of Public Health, Guangzhou Medical University, Guangzhou 510440, Guangdong Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Influenza is a significant public health issue, particularly for vulnerable groups like children and the elderly. Despite widespread vaccination and public health measures, age-specific incidence data-crucial for targeted interventions-are limited in many areas, including Guangzhou. The epidemiological patterns of influenza have also been affected by non-pharmaceutical interventions during the COVID-19 pandemic, underscoring the need for updated local estimates. This study aimed to estimate the age-specific incidence of influenza infection in Guangzhou from 2019 to 2022-a period covering both pre-pandemic and pandemic phases-to inform regionally tailored prevention and control strategies. Methods: This study analyzed surveillance data on influenza-like illness (ILI) and virological test results from sentinel hospitals in Guangzhou covering the period from 2019 to 2022. A previously established multiplier model was employed, which integrated age-specific consultation rates, influenza positivity rates, as well as parameters related to symptom presentation and detection sensitivity. Monte Carlo simulations were utilized to estimate annual age-stratified influenza infection and incidence rates, accompanied by 95% confidence intervals. The population denominators were derived from the national census conducted in 2020. Results: 7.78% of the total population in Guangzhou were infected by influenza in 2019, 1.40% in 2020, 1.85% in 2021 and 12.13% in 2022 and incidence rates were 5.15% in 2019, 0.93% in 2020, 1.23% in 2021 and 8.04% in 2022. The highest influenza infection and incidence rates were observed in 2022 and the lowest in 2020. Infections in the 0-14 age group were 27.19%, 3.57%, 11.16% and 66.15% during 2019-2022 and respective incidence rates were 18.00%, 2.37%, 7.41% and 43.84%. Conclusions: 0-14-year-old infants and children were the main victims of influenza. Targeted strategies should be developed to prevent the spread in this age group.

Indexed as

Incidence rateInfection rateInfluenza

Identifiers

PMID41541067
PMCPMC12800747

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.