Exploration of potential risks of Hand, Foot, and Mouth Disease in Inner Mongolia Autonomous Region, China Using Geographically Weighted Regression Model

Zhimin Hong,Lidong Wei,Hui Hao,Wala Du,Huhu Wang,Chunyang Li

doi:10.1038/s41598-018-35721-9

Abstract

To quantify the associations between the spatial characteristics of hand, foot, and mouth disease (HFMD) epidemic and meteorological factors (average temperature (AT), relative humidity (RH), average pressure (AP), average wind speed (AW) and average rainfall (AR)), child population density (CPD) and Per capita GDP (GDP) in Inner Mongolia Autonomous Region, China, and to detect the variation of influence in different seasons and counties, geographically weighted regression (GWR) model was constructed. The monthly cumulative incidence (CI) of HFMD was worked out for children ≤9 years from June to December, 2016. The results revealed that GWR model had a far superior goodness-of-fit for describing the relationship between the risk factors and HFMD incidence. Meteorological factors had different significance in their effect on HFMD incidence depending on the season. AT and AR had the greatest impact on HFMD in summer. The influence of RH on HFMD was significant in early autumn. AW was negatively correlated with HFMD in summer and positively correlated in autumn and winter. The effects of AW and AP on the incidence of HFMD were statistically significant in winter. GDP and CPD were not significantly related to HFMD occurrence for most time periods.

Highlights

The geographically weighted regression (GWR) model, as a spatial statistics method to model and analyze the heterogeneity of space, was proposed based on local smooth ideas
The GWR model was used to speculate the effect of meteorological factors, child population density and Per capita GDP on HFMD occurrence at different time and county levels in Inner Mongolia, China
Our study showed that Average temperature (AT) and Average rainfall (AR) played the greatest role in HFMD occurrence

Summary

Introduction

The geographically weighted regression (GWR) model, as a spatial statistics method to model and analyze the heterogeneity of space, was proposed based on local smooth ideas. From 2009 to 2016, the average annual HFMD incidence rate for children 9 years and younger (≤9 years) in Inner Mongolia decreased to 41.36 from 137.51 per 100,000 child population (the statistical data was obtained from the Inner Mongolia Autonomous Region Center for Disease Control and Prevention). It could be very useful and important to detect the reasons and key risk factors that conduce to HFMD outbreaks for assisting prediction and control. Our aim was to detect and quantify the potential effects of meteorological factors, child population density and Per capita GDP on HFMD occurrence in Inner Mongolia using the GWR model at county level and monthly scale

Objectives

Methods

Results

Conclusion