The role of socioeconomic and climatic factors in the spatio-temporal variation of human rabies in China

Abstract

BackgroundRabies is a significant public health problem in China. Previous spatial epidemiological studies have helped understand the epidemiology of animal and human rabies in China. However, quantification of effects derived from relevant factors was insufficient and complex spatial interactions were not well articulated, which may lead to non-negligible bias. In this study, we aimed to quantify the role of socio-economic and climate factors in the spatial distribution of human rabies to support decision making pertaining to rabies control in China.MethodsWe conducted a multivariate analysis of human rabies in China with explicit consideration for spatial heterogeneity and spatial dependence effects. The panel of 20,368 cases reported between 2005 and 2013 and their socio-economic and climate factors was implemented in regression models. Several significant covariates were extracted, including the longitude, the average temperature, the distance to county center, the distance to the road network and the distance to the nearest rabies case. The GMM was adopted to provide unbiased estimation with respect to heterogeneity and spatial autocorrelation.ResultsThe analysis explained the inferred relationships between the counts of cases aggregated to 271 spatially-defined cells and the explanatory variables. The results suggested that temperature, longitude, the distance to county centers and the distance to the road network are positively associated with the local incidence of human rabies while the distance to newly occurred rabies cases has a negative correlation. With heterogeneity and spatial autocorrelation taken into consideration, the estimation of regression models performed better.ConclusionsIt was found that climatic and socioeconomic factors have significant influence on the spread of human rabies in China as they continuously affect the living environments of humans and animals, which critically impacts on how timely local citizens can gain access to post-exposure prophylactic services. Moreover, through comparisons between traditional regression models and the aggregation model that allows for heterogeneity and spatial effects, we demonstrated the validity and advantage of the aggregation model. It outperformed the existing models and decreased the estimation bias brought by omission of the spatial heterogeneity and spatial dependence effects. Statistical results are readily translated into public health policy takeaways.

A cointegration analysis of rabies cases and weather components in Davao City, Philippines from 2006 to 2017

“…In the long-run, an approximate increase by 0.7916 rabies case per month is expected in Davao City if the temperature of the preceding month remains on the average at 28.27˚C (i.e., 0.0280 � 28.27 = 0.7916). A similar finding has been observed for human rabies cases in China [48][49][50]. Increased dog activity on months with high temperatures is a probable cause of the rise in the number of dog bites [50].…”

“…Temperature is a potential risk factor of rabies spread as the dog's temper is sensitive to high temperatures [48]. Furthermore, animals are more active and travel with greater distance at warmer temperatures, thereby contributing to rabies spread especially with warmer climate [49].…”

The impact of anthropogenic and environmental factors on human rabies cases in China

“…Main roads and rivers were previously found to directly influence the distribution of domestic dogs (Brunker et al., 2018; Onyango et al, Sahin, Awiti, Chu, & Mackey, 2016; Patz et al, Olson, Uejio, & Gibbs, 2008; Zarza et al, Martínez‐Meyer, Suzán, & Ceballos, 2017). In general, the farther a place is from a main road, the more difficult it is to implement public health interventions (Guo, Yin, et al, 2018) and dog vaccination campaigns (Wera et al, Mourits, & Hogeveen, 2015), and as a consequence, the higher the risk of human rabies following bites by RABV‐infected dogs. In contrast, our study showed that the closer of areas to a main road, the higher the risk of human rabies cases.…”

“…Human rabies distribution is associated with environmental factors such as temperature (positive correlation) and elevation (negative correlation) (Guo, Yin, et al, 2018). Environmental factors also play a key role in the occurrence of rabies vectored by other mammals, such as raccoons and striped skunks (Brunker et al., 2018; Recuenco et al, Eidson, Cherry, Kulldorff, & Johnson, 2008; Russell et al, Real, & Smith, 2006; Smith et al, Lucey, Waller, Childs, & Real, 2002; Smith et al, Waller, Russell, Childs, & Real, 2005).…”

A Spatio-Temporal Pattern and Socio-Economic Factors Analysis of Improved Sanitation in China, 2006–2015

“…In recent years, more and more public health researchers have begun to apply the spatial analysis methods to investigate the influencing factors of diseases related with environmental health and environmental pollution [ 22 , 23 ], it was a trend to merge different spatial effect socio-economic indicators into the panel data model for analyzing the influencing factors of ISRs. However, there is a lack of research that has scientifically analyzed the spatial pattern and spatiotemporal characteristics of ISR, and possible factors that influencing ISRs over time.…”