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Data Details

Experimental Dataset for Spatiotemporal Dynamic Simulation of Scrub Typhus Incidence in Guangdong Province, China (2010-2019)


FAN Peiwei1,2HAO Mengmeng1,2DING Fangyu*1,2JIANG Dong1,2
1 Institute of Geographic Sciences and Natural Resources Research，Chinese Academy of Sciences，Beijing 100101，China2 College of Resources and Environment，University of Chinese Academy of Sciences，Beijing 100049，China

DOI:10.3974/geodb.2026.02.03.V1

Published:Feb. 2026

Visitors：19       Data Files Downloaded：0      
Data Downloaded： 无      Citations：

Key Words：

Scrub typhus,driving factors,bimodal pattern,Bayesian hierarchical mixture model

Abstract：

Scrub typhus is a life-threatening and increasingly prevalent vector-borne infectious disease. This study took Guangdong Province as a case area and, based on monthly case data of scrub typhus from 2010 to 2019 along with environmental and vector-related datasets, systematically elucidated the spatiotemporal characteristics of the disease using a Bayesian hierarchical mixed model. Then the experimental dataset for spatiotemporal dynamic simulation of scrub typhus incidence in Guangdong Province, China (2010-2019) was obtained. The data shows that high-risk areas for scrub typhus in Guangdong are primarily concentrated in the western and southern regions. The disease prevalence shows a distinct bimodal pattern, with peaks typically occurring from May to July and from October to November. The dataset includes the following monthly data in each county of Guangdong during 2010-2019: (1) spatial distribution data of scrub typhus incidence in 1 km resolution; (2) table data of scrub typhus incidence. The dataset is archived in .tif and .xlsx formats, and consists of 121 data files with data size of 24.6 MB (compressed into one file with 13.4 MB). The analysis paper based on the data has been published in Tropical Medicine and Infectious Disease, No.10, 2025.

Foundation Item：

11；

Data Citation：

FAN Peiwei, HAO Mengmeng, DING Fangyu*, JIANG Dong. Experimental Dataset for Spatiotemporal Dynamic Simulation of Scrub Typhus Incidence in Guangdong Province, China (2010-2019)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2026. https://doi.org/10.3974/geodb.2026.02.03.V1.

Related Publication：

Fan, P. W.; Ma, T.; Meng, Z.; et al. Environmental conditions and mite vectors shape the spatiotemporal patterns of scrub typhus in Guangdong Province, Mainland China [J]. Tropical Medicine and Infectious Disease, 2025, 10: 326-339.
     

References：


     [1] Wang, Q., Ma, T., Ding, F. Y., et al. Global and regional seroprevalence, incidence, mortality of, and risk factors for scrub typhus: a systematic review and meta-analysis [J]. International Journal of Infectious Diseases, 2024, 146: 107151.
     [2] Kelly, D. J., Fuerst, P. A., Ching, W. M., et al. Scrub typhus: the geographic distribution of phenotypic and genotypic variants of Orientia tsutsugamushi [J]. Clinical Infectious Diseases, 2009, 48: 203-230.
     [3] Zheng, C. J., Jiang, D., Ding, F. Y., et al. Spatiotemporal patterns and risk factors for scrub typhus from 2007 to 2017 in Southern China [J]. Clinical Infectious Diseases, 2019, 69: 1205-1211.
     [4] Richards, A. L., Jiang, J. Scrub typhus: historic perspective and current status of the worldwide presence of Orientia species [J]. Tropical Medicine and Infectious Disease, 2020, 5: 49.
     [5] Walker, D. H., Mendell, N. L. A scrub typhus vaccine presents a challenging unmet need [J]. npj Vaccines, 2023, 8: 11.
     [6] Gong, J. R. The distribution and general situation on epidemiology studies of tsutsugamushi disease in China [J]. Chinese Journal of Disease Control & Prevention, 2016, 20, 1176-1181.
     [7] Tan, X. H., Pan, Z. Q., Li, W. Q., et al. Epidemiological characteristics trends and death related influencing factors of scrub typhus, Guangdong [J]. Modern Preventive Medicine, 2022, 49, 4259-4266.
     [8] Zhu, S. X., Zeng, M. H., Zhang, Y. M. Epidemic report of Tsutsugamushi disease in Guangzhou [J]. National Medical Journal of China, 1950, 36, 421-423.
     [9] Liu, Q. Y. Impact of climate change on vector-borne diseases and related response strategies in China: Major research findings and recommendations for future research [J]. Chinese Journal of Vector Biology and Control, 2021, 32(1): 1-11.
     [10] Morin, C. W., Comrie, A. C., Ernst, K. Climate and dengue transmission: evidence and implications [J]. Environmental Health Perspect, 2013, 121: 1264-1272.
     [11] Ma, T., Hao, M. M., Chen, S., et al. The current and future risk of spread of Leptotrombidium deliense and Leptotrombidium scutellare in Mainland China [J]. Science of the Total Environment, 2022, 843, 156986.
     [12] Fan, P., Ma, T., Meng, Z., et al. Environmental conditions and mite vectors shape the spatiotemporal patterns of scrub typhus in Guangdong Province, Mainland China [J]. Tropical Medicine and Infectious Disease, 2025, 10: 326-39.
     [13] Ding, F. Y., Wang, Q., Huang, M. M., et al. Climate drives the spatiotemporal dynamics of scrub typhus in China [J]. Global Change Biology, 2022, 28: 6618-6628.
     [14] Wang, Q., Ma, T., Ding, F. Y., et al. A systematic review of environmental covariates and methods for spatial or temporal scrub typhus distribution prediction [J]. Environmental Research, 2024, 263: 120067.
     [15] Lowe, R., Cazelles, B., Paul, R., et al. Quantifying the added value of climate information in a spatio-temporal dengue model [J]. Stochastic Environmental Research and Risk Assessment, 2016, 30: 2067-2078.

Data Product:

ID Data Name Data Size Operation
1 GuangdongST2010-2019.rar 13735.47KB
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