title: Impact of meteorological factors on the prevalence of porcine pasteurellosis in the southcentral of Mainland China.
abstract: Using data collected from 2006 to 2014, we applied geographic information system (GIS) mapping and spatial clustering analysis to evaluate prevalence of porcine pasteurellosis in all 31 provinces of Mainland China. All provinces have been affected, but our results show that there is a very high incidence in provinces of the southcentral of Mainland China. Six provinces comprise the area and account for 14082 outbreaks or 74.66% of the total 18862 number: Guangxi (4574), Sichuan (3493), Chongqing (2443), Guangdong (1584), Guizou (1041) and Yunnan (947). This study aims to evaluate the relation between meteorological factors and number of cases of porcine pasteurellosis in the southcentral of Mainland China. Local meteorological variables and case data of porcine pasteurellosis were provided by authorities. Spearman rank correlation analysis and cross-correlation analysis were used to control for collinearity and lag effects. A zero-inflated Poisson model was used to estimate the probability of an impact of meteorological factors in the epidemiology of porcine pasteurellosis. The results of this model indicated that ENSO have a positive effect on the occurrence of the disease. And there is a positive correlation between mean monthly temperature, relative humidity of the current and previous month and the number of cases of the disease. In contrast, average wind speed of the current month negatively correlated to the number of newly reported cases. Our findings indicate that there may exist meteorological conditions in the southcentral of Mainland China that increase the risk for the appearance of porcine pasteurellosis. Moreover, these meteorological variables may be used to estimate the number of disease' cases in this region.
authors.affiliation: Department of Veterinary Surgery, Northeast Agricultural University, Harbin, Heilongjiang, PR China.
authors.forename: Xiang
authors.initials: X
authors.lastname: Gao
authors.affiliation: Department of Veterinary Surgery, Northeast Agricultural University, Harbin, Heilongjiang, PR China.
authors.forename: Jianhua
authors.initials: J
authors.lastname: Xiao
authors.affiliation: Department of Veterinary Surgery, Northeast Agricultural University, Harbin, Heilongjiang, PR China.
authors.forename: Hongyu
authors.initials: H
authors.lastname: Qin
authors.affiliation: Department of Veterinary Surgery, Northeast Agricultural University, Harbin, Heilongjiang, PR China.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Cao
authors.affiliation: Department of Veterinary Surgery, Northeast Agricultural University, Harbin, Heilongjiang, PR China. Electronic address: hbwang1940@163.com.
authors.forename: Hongbin
authors.initials: H
authors.lastname: Wang
mesh_terms: D000818:Animals; D002681:China / Q000453:epidemiology; D002980:Climate; D016000:Cluster Analysis; D004196:Disease Outbreaks / Q000662:veterinary*; D040362:Geographic Information Systems; D010325:Pasteurella / Q000502:physiology*; D010326:Pasteurella Infections / Q000453:epidemiology / Q000382:microbiology / Q000662:veterinary*; D015995:Prevalence; D013552:Swine; D013553:Swine Diseases / Q000453:epidemiology* / Q000382:microbiology; D014887:Weather
keywords: Interclass Correlation Coefficient; Local Moran's index; Meteorological factor; Porcine pasteurellosis; Southcentral of Mainland China; Spatial analysis; Spearman rank correlation analysis; Zero-inflated Poisson