Evidence map›Paper›PMID 39697280›Full record

ArticleFrontiers in public health2024

Trends and projections of Hepatitis A incidence in eastern China from 2007 to 2021: an age-period-cohort analysis.

Hui Peng, Yin Wang, Songting Wei, Weili Kang, Xuefeng Zhang, Xiaoqing Cheng, Changjun Bao

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Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Hui Peng *GuSu Center for Disease Prevention and Control, Suzhou, China.
Yin Wang *Yangzhou Center for Disease Control and Prevention, Yangzhou, China.
Songting Wei *Heilongjiang Provincial Center for Disease Control and Prevention, Harbin, China.
Weili KangYangzhou Center for Disease Control and Prevention, Yangzhou, China.
Xuefeng ZhangJiangsu Provincial Centre for Disease Control and Prevention (Jiangsu Institution of Public Health), Nanjing, China.
Xiaoqing ChengJiangsu Provincial Centre for Disease Control and Prevention (Jiangsu Institution of Public Health), Nanjing, China.
Changjun BaoJiangsu Provincial Centre for Disease Control and Prevention (Jiangsu Institution of Public Health), Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to analyze the trends in Hepatitis A incidence associated with age, period, and birth cohorts from 2007 to 2021 in Jiangsu Province, China, and projects the future burden through 2031. Methods: Data on Hepatitis A cases in Jiangsu Province from 2007 to 2021 were obtained from the National Notifiable Disease Reporting System. Joinpoint regression analysis identified significant changes in incidence trends. The age-period-cohort model assessed the effects of age, period, and cohort on Hepatitis A incidence rates. Projections for 2022-2031 were generated using the Bayesian age-period-cohort model. Results: From 2007 to 2021, Hepatitis A incidence in Jiangsu Province significantly declined, with an average annual percent change (AAPC) of -10.77%. The decline was more pronounced in males (AAPC = -12.87%) compared to females (AAPC = -7.46%). The overall net drift was -10.61% (95% CI: -11.14% to -10.07%), the net drift for males was -12.77% (95% CI: -13.40% to -12.13%), which was higher than that for females at -7.27% (95% CI: -7.93% to -6.60%). The local drift indicates the incidence of hepatitis A decreased gradually, with the rate of decline slowing in the later period. Descriptive analysis revealed the highest incidence of Hepatitis A cases in the 40-59 age group, while age-period-cohort analysis indicated higher incidence rates in younger individuals. The cohort effect showed a continuous decline from the earliest cohort in 1923-1927 (Overall RR = 64.93, 95% CI: 42.55 to 99.07) to the most recent cohort in 1993-1997 (Overall RR = 0.008, 95% CI: 0.004 to 0.01). But Bayesian age-period-cohort model projections for 2022-2031 suggest that incidence rates will remain low, though they may slightly increase by 2031, with peak incidence shifting to the 60-64 age group. Conclusion: The incidence of Hepatitis A in Jiangsu Province has significantly decreased from 2007 to 2021, primarily due to public health measures and vaccination programs. Future efforts should focus on maintaining vaccination coverage and improving sanitation and hygiene practices to sustain these achievements.

Indexed as

Hepatitis AAdolescentAdultAgedAge FactorsBayes TheoremChildChild, PreschoolChinaCohort StudiesFemaleForecastingHumansIncidenceInfantInfant, Newbornage-period-cohort modelbayesian age-period-cohort modelHepatitis Aincidence trendsJiangsu Provincepublic health

Identifiers

PMID39697280
PMCPMC11652658

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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.