Spatial analysis on human brucellosis incidence in mainland China: 2004–2010

Abstract

ObjectivesChina has experienced a sharply increasing rate of human brucellosis in recent years. Effective spatial monitoring of human brucellosis incidence is very important for successful implementation of control and prevention programmes. The purpose of this paper is to apply exploratory spatial data analysis (ESDA) methods and the empirical Bayes (EB) smoothing technique to monitor county-level incidence rates for human brucellosis in mainland China from 2004 to 2010 by examining spatial patterns.MethodsESDA methods were used to characterise spatial patterns of EB smoothed incidence rates for human brucellosis based on county-level data obtained from the China Information System for Disease Control and Prevention (CISDCP) in mainland China from 2004 to 2010.ResultsEB smoothed incidence rates for human brucellosis were spatially dependent during 2004–2010. The local Moran test identified significantly high-risk clusters of human brucellosis (all p values <0.01), which persisted during the 7-year study period. High-risk counties were centred in the Inner Mongolia Autonomous Region and other Northern provinces (ie, Hebei, Shanxi, Jilin and Heilongjiang provinces) around the border with the Inner Mongolia Autonomous Region where animal husbandry was highly developed. The number of high-risk counties increased from 25 in 2004 to 54 in 2010.ConclusionsESDA methods and the EB smoothing technique can assist public health officials in identifying high-risk areas. Allocating more resources to high-risk areas is an effective way to reduce human brucellosis incidence.

Epidemic characteristics, high-risk townships and space-time clusters of human brucellosis in Shanxi Province of China, 2005–2014

“…This trend is consistent with the profile of the whole nation [21, 22, 24, 31] and other northern provinces, such as the Inner Mongolia Autonomous Area [25] and Shandong Province [27]. Sero-prevalence studies have also indicated an increasing drift in both livestock (0.7% in 2005–2006, and 1.5% in sheep in 2009, 3.71% in 2014) and occupational population (13.3% in 2005–2006, 22.0% in 2007, and 22.8% in 2011) [18–20, 44].…”

Exploratory study of factors associated with human brucellosis in mainland China based on time-series-cross-section data from 2005 to 2016

“…From the time series plot, it 199 could be inferred that: ①The human brucellosis incidence rate went up significantly 200 during the study period; ②There was an overall upward trend of the epidemic in the 201 south area (especially in southeastern provinces) while the northern provinces still 202 kept high records of incidence rates. This indicated that the pastoral areas were still 203 high epidemic areas while the incidence of human brucellosis also became more 204 intense in half pastoral areas and agricultural areas, which coincided with the 205 conclusion of Zhang et al [19]. As for the cluster analysis, the result indicated that these 31 provinces could be 209 classified into three clusters according to their incidence level and epidemic trend.…”

Spatial Clustering of Severe Hand-Foot-Mouth Disease Cases on Hainan Island, China

“…Anselin's Local Moran I shows the extent of spatial autocorrelation (20,(24)(25)(26): significantly positive values indicate that the township and neighboring townships were similarly high or similarly low (high-high or lowlow), whereas significantly negative values indicate that a township and the neighboring townships were dissimilar (high-low or low-high). In this study, we defined high-high and high-low townships as high-risk clusters for incidence of severe HFMD and proportion of severe HFMD cases; low-low and low-high townships were defined as low-risk clusters.…”