ArticleBMC infectious diseases2023
Impact of COVID-19 on epidemic trend of hepatitis C in Henan Province assessed by interrupted time series analysis.
Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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Who cites it
3 citing papers in PubMed, 2 citations in OpenAlex.
- [Analysis of epidemiological characteristics and spatial clustering of hepatitis C virus in China from 2018 to 2022].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2026Article
- Time series analysis and seasonality trends of SARS-CoV-2 in Ecuador (2020-2024): a four-year study.Frontiers in public health · 2025Article
- Temporal disruption in tuberculosis incidence patterns during COVID-19: a time series analysis in China.PeerJ · 2024Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveHepatitis C presents a profound global health challenge. The impact of COVID-19 on hepatitis C, however, remain uncertain. This study aimed to ascertain the influence of COVID-19 on the hepatitis C epidemic trend in Henan Province.
methodsWe collated the number of monthly diagnosed cases in Henan Province from January 2013 to September 2022. Upon detailing the overarching epidemiological characteristics, the interrupted time series (ITS) analysis using autoregressive integrated moving average (ARIMA) models was employed to estimate the hepatitis C diagnosis rate pre and post the COVID-19 emergence. In addition, we also discussed the model selection process, test model fitting, and result interpretation.
resultsBetween January 2013 and September 2022, a total of 267,968 hepatitis C cases were diagnosed. The yearly average diagnosis rate stood at 2.42/100,000 persons. While 2013 witnessed the peak diagnosis rate at 2.97/100,000 persons, 2020 reported the least at 1.7/100,000 persons. The monthly mean hepatitis C diagnosed numbers culminated in 2291 cases. The optimal ARIMA model chosen was ARIMA (0,1,1) (0,1,1)
conclusionThe measures undertaken to curtail COVID-19 led to a diminishing trend in the diagnosis rate of hepatitis C. The ARIMA model is a useful tool for evaluating the impact of large-scale interventions, because it can explain potential trends, autocorrelation, and seasonality, and allow for flexible modeling of different types of impacts.
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