ArticleParasites & vectors2025
Epidemiological characteristics and influencing factors of scrub typhus in Jiangxi Province.
Article in Parasites & vectors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Influence of meteorological factors on scrub typhus in Southeast China: a study across 100 districts in Jiangxi Province.Tropical medicine and health · 2025Article
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9 authors.
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Abstract
backgroundThe large-scale outbreaks of scrub typhus, coupled with the discovery of this vector-borne disease in new regions, indicate that the disease discovery of this vector-borne disease in new regions, indicate that the disease This study aimed to explore the epidemiological characteristics of scrub typhus (ST) in Jiangxi Province and to examine the impacts of meteorological, socioeconomic, and land-cover factors on its incidence.
methodsData on reported cases of ST in Jiangxi from 2014 to 2023 were collected. The spatial trend of ST was analyzed via the standard deviation ellipse method. On the basis of the 2022 spatial data, global regression analysis was conducted via ordinary least squares (OLS), whereas local regression analysis was conducted via geographically weighted regression (GWR). The geodetector approach was used to identify the dominant influencing factors and assess the interactions among them.
resultsFrom 2014 to 2023, the average annual incidence of ST in Jiangxi was 2.025 per 100,000 people, with the peak incidence reported between June and November. Cases were more prevalent among females, with the majority of cases occurring in individuals aged 40-84 years. Farmers represented the most affected occupational group, accounting for 8404 cases (92.06%). The spatial distribution of ST showed an expanding trend across the province. The risk factors identified included elevation, gross domestic product (GDP) per capita, the percentage of agricultural GDP, temperature, and relative humidity. Conversely, a higher percentage of forestry GDP was found to be a protective factor. The effects of these variables exhibited sustained spatial heterogeneity across different regions. The GDP per capita, percentage of forestry GDP, and elevation emerged as the dominant influencing factors. All interactions among variables were enhancement types, primarily characterized by bifactor enhancements.
conclusionsThe incidence of ST in Jiangxi is expanding geographically and is affected by a combination of environmental, socioeconomic, and climatic factors. Strengthening public awareness and preventive measures, particularly in high-incidence areas and among vulnerable populations, is recommended to increase the effectiveness of ST control and prevention efforts.
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