Spatiotemporal characteristics and meteorological determinants of hand, foot and mouth disease in Shaanxi Province, China: a county-level analysis

Abstract

Background: Hand, foot and mouth disease (HFMD) is one of the common intestinal infectious diseases worldwide and has caused huge economic and disease burdens in many countries. The average annual incidence rate of HFMD was 11.66% in Shaanxi during the time span from 2009 to 2018. There are distinct differences within Shaanxi, as it is a special region that crosses three temperature zones. Hence, in this study, a spatiotemporal analysis of Shaanxi was performed to reveal the characteristics of the distribution of HFMD and to explore the meteorological determinants of HFMD.

Methods: The county-level and municipal data from Shaanxi Province from 2009 to 2018 were applied to research the spatiotemporal characteristics of HFMD and its meteorological determinants. Time series and spatial autocorrelation analyses were applied to assess the spatiotemporal characteristics of HFMD. This study used spatial econometric panel models to explore the relationship between HFMD and meteorological factors based on the data of 107 counties and 10 municipalities.

Results: The incidence rate of HFMD displayed no variable trend throughout the whole research period. A high incidence rate of HFMD was observed from June to September, corresponding to a time when the climate is characterized by heavy rain, high temperature, and high humidity. The high-incidence areas were mainly located in the central region in Shaanxi, whereas the low-incidence spots were mainly found in Northern Shaanxi. Regarding the meteorological factors analysed in this study, in general, the incidence rate of HFMD in specific regions was positively associated with the rainfall, temperature and humidity.

Conclusion: These results could be applied by the government and the general public to take effective measures to prevent disease. Region-targeted policies could be enacted and implemented in the future according to specific situations in different areas and the relevant meteorological determinants. Additionally, meteorological conditions normally extend to a wide-ranging region; thus, cooperation among surrounding regions is necessary.

Fig. 1

The map of Shaanxi province, China (made through Microsoft PowerPoint, source of map: http://www.geodata.gov.cn/web/geo/index.html, under license without need for permission). *This figure was made by ourselves through Microsoft PowerPoint (Version 2013, Microsoft Crop, Redmond, WA, USA). The source of map was a public database, National Nature Resources and Geospatial basic information database of PRC (http://www.geodata.gov.cn/web/geo/index.html). This maps were under license without need for permission

Fig. 2

Time series analysis plots (made through Microsoft Excel). Note: The incidence rate (gray lines) were calculated through the incidence rate and population. Moving average data of 3 months (blue lines) and 12 months (pink lines) were shown. *This figure was made by ourselves through Microsoft Excel (Version 2013, Microsoft Crop, Redmond, WA, USA)

Fig. 3

Map showing the hierarchy of the incidence rates for HFMD (made through GeoDa and ArcGIS, source of shape files: http://www.geodata.gov.cn/web/geo/index.html, under license without need for permission). *This figure was made by ourselves through GeoDa (Version 1.8.61, the University of Chicago, Chicago, IL, USA) and ArcGIS (Version 10.0, ESRI Inc., Redlands, CA, USA). The source of shape files was a public database, National Nature Resources and Geospatial basic information database of PRC (http://www.geodata.gov.cn/web/geo/index. html). Those shape files were under license without need for permission

Fig. 4

The spatial clusters of incidence rate of HFMD (made through GeoDa and ArcGIS, source of shape files: http://www.geodata.gov.cn/web/geo/index.html, under license without need for permission). *This figure was made by ourselves through GeoDa (Version 1.8.61, the University of Chicago, Chicago, IL, USA) and ArcGIS (Version 10.0, ESRI Inc., Redlands, CA, USA). The source of shape files was a public database, National Nature Resources and Geospatial basic information database of PRC (http://www.geodata.gov.cn/web/geo/index. html). Those shape files were under license without need for permission

Fig. 5

Model selection procedures of the spatial panel econometric models (made through Microsoft PowerPoint). *This figure was made by ourselves through Microsoft PowerPoint (Version 2013, Microsoft Crop, Redmond, WA, USA)