ArticleBMC public health2025
Evaluation of the impact of COVID-19 on hepatitis B in Henan Province and its epidemic trend based on Bayesian structured time series model.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- National trends in acute viral hepatitis in China from 1990-2023: An analysis of the Global Burden of Disease 2023 update.Chinese medical journal · 2026Article
- Characterizing the impact of the COVID-19 pandemic on HIV testing among Medicaid beneficiaries.medRxiv : the preprint server for health sciences · 2026Article
- Early warning of hepatitis B epidemics in Henan Province, China, from 2014 to 2023 based on Baidu Index and Bayesian Structural Time Series model.Archives of public health = Archives belges de sante publique · 2026Article
- Dynamic temporal partitioning enhanced transformer for pediatric viral load forecasting.Frontiers in public health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere may be evidence that COVID-19 affects illness patterns. This study aimed to assess the effects of COVID-19 epidemic on the declines in hepatitis B (HB) case notifications and to estimate the epidemiological trends of HB in Henan.
methodsThe Bayesian structured time series (BSTS) method was used to investigate the causal effect of COVID-19 on the decline in HB cases based on the monthly incidence of HB from January 2013 to September 2022. To assess how well the BSTS algorithm performs predictions, we split the observations into various training and testing ranges.
resultsThe incidence of HB in Henan was generally declining with periodicity and seasonality. The seasonal index in September and February was the smallest (0.91 and 0.93), and that in March was the largest (1.19). Due to the COVID-19 pandemic, the monthly average number of notifications of HB cases decreased by 38% (95% credible intervals [CI]: -44% to -31%) from January to March 2020, by 24% (95% CI: -29% to -17%) from January to June 2020, by 15% (95% CI: -19% to -9.2%) from January to December 2020, by 11% (95% CI: -15% to -6.7%) from January 2020 to June 2021, and by 11% (95% CI: -15% to -7.3%) from January 2020 to December 2021. From January 2020 to September 2022, it decreased by 12% (95% CI: -16% to -8.1%). From 2021 to 2022, the impact of COVID-19 on HB was attenuated. In both training and test sets, the average absolute percentage error (10.03%) generated by the BSTS model was smaller than that generated by the ARIMA model (14.4%). It was also found that the average absolute error, root mean square error, and root mean square percentage error generated by the BSTS model were smaller than ones generated by the ARIMA model. The trend of HB cases in Henan from October 2022 to December 2023 predicted by the BSTS model remained stable, with a total number of 81,650 cases (95% CI: 47,372 to 115,391).
conclusionsDuring the COVID-19 pandemic, the incidence of HB in Henan decreased and exhibited clear seasonal and cyclical trends. The BSTS model outperformed the ARIMA model in predicting the HB incidence trend in Henan. This information may serve as a reference and provide technical assistance for developing strategies and actions to prevent and control HB. Take additional measures to accelerate the progress of eliminating HB.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.