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Estimation of scrub typhus incidence and spatiotemporal multicomponent characteristics from 2016 to 2023 in Zhejiang Province, China

Bibliographic Data

ID22072039
AuthorsHaocheng Wu (Zhejiang Center for Disease Control and Prevention, corresponding author), Ming Xue (0000-0002-5011-3842, Hangzhou Center for Disease Control and Prevention), Chen Wu (0000-0003-4954-1011, Zhejiang Center for Disease Control and Prevention), Qinbao Lu (Zhejiang Center for Disease Control and Prevention), Zheyuan Ding (Zhejiang Center for Disease Control and Prevention), Xinyi Wang (0009-0008-4477-6130, Zhejiang Center for Disease Control and Prevention), Tianyin Fu (Zhejiang Center for Disease Control and Prevention), Ke Yang (0000-0003-2757-5771, Zhejiang Center for Disease Control and Prevention), Junfen Lin (Zhejiang Center for Disease Control and Prevention, corresponding author)
Year2024
Volume12
Pages1359318-1359318
Publication date2024-09-26
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2024.1359318
PMID39391156
OpenAlexW4402895079
LanguageEN
References cited34

Background China is one of the main epidemic areas of scrub typhus, and Zhejiang Province, which is located in the coastal area of southeastern China, is considered a key region of scrub typhus. However, there may be significant bias in the number of reported cases of scrub typhus, to the extent that its epidemiological patterns are not clearly understood. The purpose of this study was to estimate the possible incidence of scrub typhus and to identify the main driving components affecting the occurrence of scrub typhus at the county level. Methods Data on patients with scrub typhus diagnosed at medical institutions between January 2016 and December 2023 were collected from the China Disease Control and Prevention Information System (CDCPIS). The kriging interpolation method was used to estimate the possible incidence of scrub typhus. Additionally, a multivariate time series model was applied to identify the main driving components affecting the occurrence of scrub typhus in different regions. Results From January 2016 to September 2023, 2,678 cases of scrub typhus were reported in Zhejiang Province, including 1 case of reported death, with an overall case fatality rate of 0.04%. The seasonal characteristics of scrub typhus in Zhejiang Province followed an annual single peak model, and the months of peak onset in different cities were different. The estimated area with case occurrence was relatively wider. There were 41 counties in Zhejiang Province with an annual reported case count of less than 1, while from the estimated annual incidence, the number of counties with less than 1 case decreased to 21. The average annual number of cases in most regions fluctuated between 0 and 15. The numbers of cases in the central urban area of Hangzhou city, Jiaxin city and Huzhou city did not exceed 5. The estimated random effect variance parameters σ λ 2 , σ φ 2 , and σ ν 2 were 0.48, 1.03 and 3.48, respectively. The endemic component values of the top 10 counties were Shuichang, Cangnan, Chun’an, Xinchang, Pingyang, Xianju, Longquan, Dongyang, Yueqing and Qingyuan. The spatiotemporal component values of the top 10 counties were Pujiang, Anji, Pan’an, Dongyang, Jinyun, Ninghai, Yongjia, Xiaoshan, Yinwu and Shengzhou. The autoregressive component values of the top 10 counties were Lin’an, Cangnan, Chun’an, Yiwu, Pujiang, Longquan, Xinchang, Luqiao, Sanmen and Fuyang. Conclusion The estimated incidence was higher than the current reported number of cases, and the possible impact area of the epidemic was also wider than the areas with reported cases. The main driving factors of the scrub typhus epidemic in Zhejiang included endemic components such as natural factors, but there was significant heterogeneity in the composition of driving factors in different regions. Some regions were driven by spatiotemporal spread across regions, and the time autoregressive effect in individual regions could not be ignored. These results that monitoring of cases, vectors, and pathogens of scrub typhus should be strengthened. Furthermore, each region should take targeted prevention and control measures based on the main driving factors of the local epidemic to improve the accuracy of prevention and control

Case fatality rate · China · Environmental health · Eschar · Geography · Orientia tsutsugamushi · Pathology · Scrub typhus · Typhus · Veterinary medicine · Demography · Mathematics · Medicine · Vector-borne infectious diseases · Viral Infections and Immunology Research · Yersinia bacterium, plague, ectoparasites research · Epidemiology · Internal Medicine · Virology

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