Impact of COVID-19 on epidemic trend of hepatitis C in Henan Province assessed by interrupted time series analysis

BMC Infectious Diseases

Research

Xinxiao Li¹  Chenlu Xue¹  YongBin Wang¹  Bingjie Zhang¹  Yanyan Li¹  Xianxiang Lan¹ 

[1] Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, 453000, Xinxiang, Henan Province, People’s Republic of China;

关键词: Interruption time series analysis;    Autoregressive comprehensive moving average model;    COVID-19;    Hepatitis C;    Intervention analysis;   

DOI  :  10.1186/s12879-023-08635-9

 received in 2023-02-28, accepted in 2023-09-23,  发布年份 2023

来源: Springer

【 摘 要 】

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)12 with AIC = 1459.58, AICc = 1460.19, and BIC = 1472.8; having coefficients MA1=-0.62 (t=-8.06, P < 0.001) and SMA1=-0.79 (t=-6.76, P < 0.001). The final model’s projected step change was − 800.0 (95% confidence interval [CI] -1179.9 ~ -420.1, P < 0.05) and pulse change was 463.40 (95% CI 191.7 ~ 735.1, P < 0.05) per month.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.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

【 图 表 】

Fig. 5

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