Dataset Information

Epidemiology and spatial distribution of bluetongue virus in Xinjiang, China.

ABSTRACT: Bluetongue (BT) is a non-contagious disease affecting domestic and wild ruminants. Outbreaks of BT can cause serious economic losses. To investigate the distribution characteristics of bluetongue virus (BTV), two large-scale censuses of BTV prevalence in Xinjiang, China were collected. Spatial autocorrelation analysis, including global spatial autocorrelation and local spatial autocorrelation, was performed. Risk areas for BTV occurrence in Xinjiang were detected using the presence-only maximum entropy model. The global spatial autocorrelation of BTV distribution in Xinjiang in 2012 showed a random pattern. In contrast, the spatial distribution of BTV from 2014 to 2015 was significantly clustered. The hotspot areas for BTV infection included Balikun County (p < 0.05), Yiwu County (p < 0.05) and Hami City (p < 0.05) in 2012. These three regions were also hotspot areas during 2014 and 2015. Sheep distribution (25.6% contribution), precipitation seasonality (22.1% contribution) and mean diurnal range (16.2% contribution) were identified as the most important predictors for BTV occurrence in Xinjiang. This study demonstrated the presence of high-risk areas for BTV infection in Xinjiang, which can serve as a tool to aid in the development of preventative countermeasures of BT outbreaks.

SUBMITTER: Ma J

PROVIDER: S-EPMC6388665 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Epidemiology and spatial distribution of bluetongue virus in Xinjiang, China.

Ma Jun J Gao Xiang X Liu Boyang B Chen Hao H Xiao Jianhua J Wang Hongbin H

PeerJ 20190222

Bluetongue (BT) is a non-contagious disease affecting domestic and wild ruminants. Outbreaks of BT can cause serious economic losses. To investigate the distribution characteristics of bluetongue virus (BTV), two large-scale censuses of BTV prevalence in Xinjiang, China were collected. Spatial autocorrelation analysis, including global spatial autocorrelation and local spatial autocorrelation, was performed. Risk areas for BTV occurrence in Xinjiang were detected using the presence-only maximum ...[more]

PMID: 30809462

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Project description:ObjectivesXinjiang is one of the high TB burden provinces of China. A spatial analysis was conducted using geographical information system (GIS) technology to improve the understanding of geographic variation of the pulmonary TB occurrence in Xinjiang, its predictors, and to search for targeted interventions.MethodsNumbers of reported pulmonary TB cases were collected at county/district level from TB surveillance system database. Population data were extracted from Xinjiang Statistical Yearbook (2006~2014). Spatial autocorrelation (or dependency) was assessed using global Moran's I statistic. Anselin's local Moran's I and local Getis-Ord statistics were used to detect local spatial clusters. Ordinary least squares (OLS) regression, spatial lag model (SLM) and geographically-weighted regression (GWR) models were used to explore the socio-demographic predictors of pulmonary TB incidence from global and local perspectives. SPSS17.0, ArcGIS10.2.2, and GeoDA software were used for data analysis.ResultsIncidence of sputum smear positive (SS+) TB and new SS+TB showed a declining trend from 2005 to 2013. Pulmonary TB incidence showed a declining trend from 2005 to 2010 and a rising trend since 2011 mainly caused by the rising trend of sputum smear negative (SS-) TB incidence (p<0.0001). Spatial autocorrelation analysis showed the presence of positive spatial autocorrelation for pulmonary TB incidence, SS+TB incidence and SS-TB incidence from 2005 to 2013 (P <0.0001). The Anselin's Local Moran's I identified the "hotspots" which were consistently located in the southwest regions composed of 20 to 28 districts, and the "coldspots" which were consistently located in the north central regions consisting of 21 to 27 districts. Analysis with the Getis-Ord Gi* statistic expanded the scope of "hotspots" and "coldspots" with different intensity; 30 county/districts clustered as "hotspots", while 47 county/districts clustered as "coldspots". OLS regression model included the "proportion of minorities" and the "per capita GDP" as explanatory variables that explained 64% the variation in pulmonary TB incidence (adjR2 = 0.64). The SLM model improved the fit of the OLS model with a decrease in AIC value from 883 to 864, suggesting "proportion of minorities" to be the only statistically significant predictor. GWR model also improved the fitness of regression (adj R2 = 0.68, AIC = 871), which revealed that "proportion of minorities" was a strong predictor in the south central regions while "per capita GDP" was a strong predictor for the southwest regions.ConclusionThe SS+TB incidence of Xinjiang had a decreasing trend during 2005-2013, but it still remained higher than the national average in China. Spatial analysis showed significant spatial autocorrelation in pulmonary TB incidence. Cluster analysis detected two clusters-the "hotspots", which were consistently located in the southwest regions, and the "coldspots", which were consistently located in the north central regions. The exploration of socio-demographic predictors identified the "proportion of minorities" and the "per capita GDP" as predictors and may help to guide TB control programs and targeting intervention.

Project description:Shigella represents one of the major diarrhea-inducing pathogens threatening public health, but its prevalence and antimicrobial resistance profile in Xinjiang Uygur Autonomous region, China, remains unclear. We conducted comprehensive investigation of Shigella serotype distribution and antimicrobial resistance pattern in Xinjiang, identifying 458 Shigella isolates between 2008 to 2014. Shigella flexneri was identified as predominant species, and several S. flexneri serotypes were isolated, including atypical serotypes 1c, 2c, and 4s. Dominant S. flexneri serotypes were 2a, 1b, 2b, and Xv, different from those generally dominant in China. A hybrid serotype pattern was observed, which included the major Chinese serotypes (2a, Xv) and those predominant in Pakistan (1b, 2b). Shigella sonnei was shown to have a lower frequency compared with that generally observed in China, but an increasing trend of infections associated with this pathogen was observed. Furthermore, a high frequency of drug resistance and different Shigella antimicrobial resistance patterns were demonstrated as well, including very severe resistance phenotypes, such as multidrug resistance and resistance to frontline antibiotics. Seventy-five cephalosporin-resistant Shigella isolates were frequently identified with the resistance determinants that can undergo horizontal transfer, such as blaOXA, blaTEM, blaCTX-M, and integrons, facilitating the development of cephalosporin resistance among Shigella subtypes. Additionally, genetic analyses demonstrated that all 86 quinolone-resistant S. flexneri isolates possess 3-4 mutation sites in quinolone resistance-determining regions, primarily contributing to their resistance to quinolone. However, S. sonnei isolates were not shown to be quinolone resistant. Co-resistance to cephalosporins and quinolones was detected in 17 S. flexneri isolates, and these isolates were additionally multidrug resistant and carried ?-lactamase genes and quinolone-resistance determinants. As is demonstrated in this study, dominant serotypes of Shigella were distributed in unique trend with dangerous drug resistance patterns. Novel strategies are urgently required to prevent the development of drug resistance among diarrhea-inducing pathogens.

Dataset Information

Epidemiology and spatial distribution of bluetongue virus in Xinjiang, China.

Publications

Epidemiology and spatial distribution of bluetongue virus in Xinjiang, China.

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