Evidence map›Paper›PMID 41618187›Full record

ArticleBMC infectious diseases2026

Impact of hemorrhagic fever with renal syndrome control policies in Hebei Province: an interrupted time series analysis.

Zhenkun Wang, Yamei Wei, Yanan Cai, Mengfan Zhang, Zhengguang Wang, Xu Han, Qi Li

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Article in BMC infectious diseases, 2026. 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

7 authors.

Zhenkun WangSchool of Public Health, Hebei Medical University, No.361, Zhongshan East Road, Shijiazhuang, Hebei Province, 050017, China.
Yamei WeiHebei Province Center for Disease Control and Prevention, No.97, Huai'an East Road, Shijiazhuang, Hebei Province, 050021, People's Republic of China.
Yanan CaiHebei Province Center for Disease Control and Prevention, No.97, Huai'an East Road, Shijiazhuang, Hebei Province, 050021, People's Republic of China.
Mengfan ZhangSchool of Public Health, Hebei Medical University, No.361, Zhongshan East Road, Shijiazhuang, Hebei Province, 050017, China.
Zhengguang WangHebei Province Center for Disease Control and Prevention, No.97, Huai'an East Road, Shijiazhuang, Hebei Province, 050021, People's Republic of China.
Xu HanHebei Province Center for Disease Control and Prevention, No.97, Huai'an East Road, Shijiazhuang, Hebei Province, 050021, People's Republic of China. hbcdchanxu@163.com.
Qi LiSchool of Public Health, Hebei Medical University, No.361, Zhongshan East Road, Shijiazhuang, Hebei Province, 050017, China. liqinew@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHebei Province is one of China’s high-incidence regions for hemorrhagic fever with renal syndrome (HFRS), posing significant public health challenges. This study aims to evaluate the efficacy of key Hemorrhagic Fever with Renal Syndrome (HFRS) control measures.

methodsThis study analyzed annual incidence data (1981–2024) and monthly data (2004–2024) using interrupted time series (ITS) analysis and the X-12 seasonal adjustment method. The X-12 procedure decomposes the series into trend, seasonal, and irregular components and removes seasonal variation to produce seasonally adjusted data. Specifically, we assessed the impact of two interventions: the 2002 Hebei Epidemic Hemorrhagic Fever Prevention and Control Plan and the 2008 Vaccination Work Plan for Key HFRS-endemic Counties in Hebei Province.

resultsThe results demonstrated that before 2002, the HFRS incidence rate increased significantly at 28.8% annually (β₁ = 0.25, p < 0.01). After policy implementation, the trend reversed, with an annual decline of 32.0% (β₁ + β₃ = −0.117, p < 0.05), indicating effective control. Notably, epidemic peaks temporarily elevated incidence levels (β₄ = 0.83, p < 0.01). Following the 2008 vaccination program, short-term incidence rate reductions of 1.229 cases per 100,000 (β₂ = -1.229, p = 0.044) and 0.351 cases per 100,000 (β₂ = -0.351, p = 0.10) were observed in Qinhuangdao and Tangshan, respectively, though the latter was not statistically significant. Long-term trends revealed slower monthly declines of 0.003 cases per 100,000 in Qinhuangdao (β₁ + β₃ = −0.003, p = 0.049) and 0.002 cases per 100,000 in Tangshan (β₁ + β₃ = −0.002, p = 0.019).

conclusionsThese findings highlight the differential effects of policy interventions on HFRS incidence, with the 2002 plan achieving sustained reduction, while the 2008 vaccination program showed limited long-term impact. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Health PolicyHemorrhagic Fever with Renal SyndromeChinaHumansIncidenceInterrupted Time Series AnalysisSeasonsVaccinationHFRSITSPolicy evaluationVaccinationX-12 seasonal adjustment

Identifiers

PMID41618187
PMCPMC12934090

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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.