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

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/semiarid 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.

Spatial-temporal heterogeneity and meteorological factors of hand-foot-and-mouth disease in Xinjiang, China from 2008 to 2016

“…The correlations between the incidence of HFMD and various meteorological factors such as relative humidity [ 1 , 11 , 12 ], precipitation [ 12 ] and temperature [ 12 , 13 ] have been extensively explored. The incidence of HFMD showed different characteristics in various countries and regions with distinct climate conditions [ 14 ]. In Vietnam [ 15 ], when monthly average air temperature above 26 °C increased by every 1 °C and monthly average relative humidity above 76% increased by every 1%, the incidence of HFMD respectively increased by 7% (RR:1.07; 95%CI: 1.052–1.088) and 3.1% (RR: 1.031, 95%CI: 1.024–1.039).…”

Spatial-temporal mapping of hand, foot and mouth disease in relation to climate factors in Xinjiang, China from 2008 to 2016

“…For instance, a study in Japan, with the increase in temperature, Herpangina & HFMD incidence increased. In a warm environment, the transmission of the HFMD virus was enhanced, but cold and hot climate limited the transmission [5,6,24].Similarly, a study was implemented in Ningxia which located in the upper reaches of the Yellow River in Western China, it demonstrated that average temperature, relative humidity, and wind speed played significant roles in the spatial-temporal distribution of HFMD risk [14]. In our research, the relationship between monthly average temperature and HFMD relative risk represents inverted V-shape, a similar pattern was observed for the association between the monthly average relative humidity and HFMD, the monthly average precipitation and HFMD, the monthly average sunshine duration and HFMD, the monthly average wind speed and HFMD.…”

“…At present, several studies have extensively explored the correlation between HFMD and meteorological factors such as relative humidity [1,[11][12], precipitation [12] and temperature [12][13]. The occurrence of HFMD showed apparent different characteristics in countries or regions with distinct climate conditions [14]. In Vietnam [15], HFMD increased 7% (RR:1.07; 95%CI: 1.052-1.088) and 3.1% (RR: 1.031, 95%CI: 1.024-1.039) for 1 °C increase in monthly temperature above 26 °C and 1% increase in monthly humidity above 76%.Whereas HFMD decreased 3.1% associated with a 1mm increase in monthly cumulative rainfalls.…”

“…Meteorological factor changes and time lag model of HFMD: the generalized additive model [19], the negative binomial multivariable regression model [20], the distributed lag non-linear model [21]. Determinants of the drivers of HFMD: spatial panel data models [22], GeoDetector models [14]. To quantify the determinants powers of driving factors of HFMD in Xinjiang, the Geographical detector is an appropriate model for this study.…”

Bolstering Maternity Insurance to Support Family Health of Ethnic-Minority Women under Universal Two-Child Policy: Empirical Evidence from China’s Ningxia-Hui Autonomous Region

“…Ningxia-Hui Autonomous Region is one province that is highly vulnerable to depleting maternal insurance scheme which can damage an already precarious maternal health conditions in the region. Ningxia-Hui Autonomous Region is located between Shaanxi Province (East), Gansu Province (South and West), Inner Mongolia Autonomous Region (North) 27 . In the past, Ningxia was part of another poor Province (Gansu) but in 1958, it was reconstituted as an autonomous region to recognise the distinctive heritage and culture of the Hui minority ethnic group in China 28 .…”