https://doi.org/10.4081/gh.2020.849

Spatiotemporal analysis of hand, foot and mouth disease data using time-lag geographically-weighted regression

Vol. 15 No. 2 (2020)
Submitted: 10 December 2019
Accepted: 19 August 2020
Published: 29 December 2020
Hand, foot, and mouth disease, geographically weighted regression, time lag geographically weighted regression, spatiotemporal non-stationarity, China.
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Authors

Zhi-Min Hong
https://orcid.org/0000-0001-8189-527X
School of Sciences, Inner Mongolia University of Technology, Hohhot; Inner Mongolia Key Laboratory of Statistical Analysis Theory for Life Data and Neural Network Modeling, Inner Mongolia, Hohhot, China.
Hu-Hu Wang
zhiminhong@163.com
https://orcid.org/0000-0002-1716-674X
School of Sciences, Inner Mongolia University of Technology, Hohhot; Institute for infectious disease and endemic disease control, Inner Mongolia Autonomous Region Center for Disease Control and Prevention, Hohhot, China.
Yan-Juan Wang
School of Sciences, Inner Mongolia University of Technology, Hohhot, China.
Wen-Rui Wang
Institute for infectious disease and endemic disease control, Inner Mongolia Autonomous Region Center for Disease Control and Prevention, Hohhot, China.

Hand, Foot, and Mouth Disease (HFMD) is a common and widespread infectious disease. Previous studies have presented evidence that climate factors, including the monthly averages of temperature, relative humidity, air pressure, wind speed and Cumulative Risk (CR) all have a strong influence on the transmission of HFMD. In this paper, the monthly time-lag geographically- weighted regression model was constructed to investigate the spatiotemporal variations of effect of climate factors on HFMD occurrence in Inner Mongolia Autonomous Region, China. From the spatial and temporal perspectives, the spatial and temporal variations of effect of climate factors on HFMD incidence are described respectively. The results indicate that the effect of climate factors on HFMD incidence shows very different spatial patterns and time trends. The findings may provide not only an indepth understanding of spatiotemporal variation patterns of the effect of climate factors on HFMD occurrence, but also provide helpful evidence for making measures of HFMD prevention and control and implementing appropriate public health interventions at the county level in different seasons.

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How to Cite

Hong, Z.-M., Wang, H.-H., Wang, Y.-J., & Wang, W.-R. (2020). Spatiotemporal analysis of hand, foot and mouth disease data using time-lag geographically-weighted regression. Geospatial Health, 15(2). https://doi.org/10.4081/gh.2020.849
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