Document Type

Journal Article




School of Medical and Health Sciences




National Science and Technology Major Project (2012ZX10005009-003, 2014ZX10004005-001

National 973 Project (Serial Number: 2011CB505404)

National Natural Science Foundation of China (serial no.: 81302516)


Wang, C., Li, X., Zhang, Y., Xu, Q., Huang, F., Cao, K., ... & Fang, L. (2016). Spatiotemporal cluster patterns of hand, foot, and mouth disease at the county level in mainland China, 2008-2012. PloS one, 11(1), e0147532.



Hand, foot, and mouth disease (HFMD) is known to be a highly contagious childhood illness. In recent years, the number of reported cases of HFMD has significantly increased in mainland China. This study aims at the epidemiological features, spatiotemporal patterns of HMFD at the county/district level in mainland China.


Data on reported HFMD cases for each county from 1 January 2008 to 31 December 2012 were obtained from the Chinese Center for Disease Control and Prevention. Cluster analysis, spatial autocorrelation, and retrospective scan methods were used to explore the spatiotemporal patterns of the disease.


The annual incidences varied greatly among the counties, ranging from 0 to 74.31‰with the median of 5.42‰ (interquartile range: 1.54‰–13.55‰) during 2008–2012 in mainland China. Counties close to provincial capital cities generally had higher incidences than rural counties. A seasonal distribution was observed between the northern and southern China, of which dual epidemic were shown in southern China and usually only one in northern China. Based on the global and local spatial autocorrelation analysis, we found that the spatial distribution of HFMD was presented a significant clustering pattern for each year (P < 0.001), and hotspots of the disease were mostly distributed in coastal provinces of China. The retrospective scan statistic further identified the dynamics of spatiotemporal clustering areas of the disease, which were mainly distributed in the counties of eastern and southern China, as well as provincial capitals and their surrounding counties.


The spatiotemporal clustering areas of the disease identified in this way were relatively stable, and imminent public health planning and resource allocation should be focused within those areas.



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This work is licensed under a Creative Commons Attribution 4.0 License.

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