Spatial-temporal heterogeneity of hand, foot and mouth disease and impact of meteorological factors in arid/ semi-arid regions: a case study in Ningxia, China

BMC Public Health. 2019 Nov 8;19(1):1482. doi: 10.1186/s12889-019-7758-1.

Abstract

Background: The incidence of hand, foot and mouth disease (HFMD) varies over space and time and this variability is related to climate and social-economic factors. Majority of studies on HFMD were carried out in humid regions while few have focused on the disease in arid/semi-arid regions, more research in such climates would potentially make the mechanism of HFMD transmission clearer under different climate conditions.

Methods: In this paper, we explore spatial-temporal distribution of HFMD in Ningxia province, which has an arid/semi-arid climate in northwest China. We first employed a Bayesian space-time hierarchy model (BSTHM) to assess the spatial-temporal heterogeneity of the HFMD cases and its relationship with meteorological factors in Ningxia from 2009 to 2013, then used a novel spatial statistical software package GeoDetector to test the spatial-temporal heterogeneity of HFMD risk.

Results: The results showed that the spatial relative risks in northern part of Ningxia were higher than those in the south. The highest temporal risk of HFMD incidence was in fall season, with a secondary peak in spring. Meteorological factors, such as average temperature, relative humidity, and wind speed played significant roles in the spatial-temporal distribution of HFMD risk.

Conclusions: The study provide valuable information on HFMD distribution in arid/semi-arid areas in northwest China and facilitate understanding of the concentration of HFMD.

Keywords: Foot and mouth disease; GeoDetector; Bayesian space-time hierarchical model; Hand; Ningxia; Spatial-temporal variation.

MeSH terms

  • Bayes Theorem
  • China / epidemiology
  • Climate
  • Climate Change
  • Female
  • Hand, Foot and Mouth Disease / epidemiology*
  • Hand, Foot and Mouth Disease / etiology
  • Humans
  • Incidence
  • Male
  • Meteorological Concepts*
  • Risk
  • Seasons
  • Spatio-Temporal Analysis
  • Temperature
  • Wind