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Human distribution and spatial-temporal clustering analysis of human brucellosis in China from 2012 to 2016

ABSTRACT: Background Brucellosis is a major public health issue in China, while its temporal and spatial distribution have not been studied in depth. This study aims to better understand the epidemiology of brucellosis in the mainland of China, by investigating the human, temporal and spatial distribution and clustering characteristics of the disease. Methods Human brucellosis data from the mainland of China between 2012 and 2016 were obtained from the China Information System for Disease Control and Prevention. The spatial autocorrelation analysis of ArcGIS10.6 and the spatial-temporal scanning analysis of SaTScan software were used to identify potential changes in the spatial and temporal distribution of human brucellosis in the mainland of China during the study period. Results A total of 244?348 human brucellosis cases were reported during the study period of 2012–2016. The average incidence of human brucellosis was higher in the 40–65 age group. The temporal clustering analysis showed that the high incidence of brucellosis occurred between March and July. The spatial clustering analysis showed that the location of brucellosis clustering in the mainland of China remained relatively fixed, mainly concentrated in most parts of northern China. The results of the spatial-temporal clustering analysis showed that Heilongjiang represents a primary clustering area, and the Tibet, Shanxi and Hubei provinces represent three secondary clustering areas. Conclusions Human brucellosis remains a widespread challenge, particularly in northern China. The clustering analysis highlights potential high-risk human groups, time frames and areas, which may require special plans and resources to monitor and control the disease.

SUBMITTER: Liang P

PROVIDER: S-EPMC7557093 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Despite the considerable efforts made to address the issue of brucellosis worldwide, its prevalence in dairy products continues to be difficult to estimate and represents a key public health issue around the world today. The aim of the present study was to better understand the epidemiology of this disease in mainland China. We set out to investigate the yearly spatial distribution and possible hotspots of the disease. METHODS:Human brucellosis data from mainland China between 2007 and 2016 were collected from the China Information System for Disease Control and Prevention. A geographic information system ArcGIS10.3 (ESRI, Redlands) was used to identify potential changes in the spatial and temporal distribution of human brucellosis in mainland China during the study period. These distributions were evaluated using three-dimensional trend analysis and spatial autocorrelation analyse. A gravity-center was used to analyse the migration track of human brucellosis. RESULTS:A total of 399,578 cases of human brucellosis were reported during the 10-year study period. The monthly incidence of brucellosis in China demonstrates clear seasonality. Spring and summer are the peak seasons, while May is the peak month for brucellosis. Three-dimensional trend analysis suggests that brucellosis is on the rise from south to north, and that the epidemic situation in northern China is more severe. Between 2007 and 2016, the overall migration distance of the brucellosis incidence gravity-center was 906.43?km, and the direction was southwest. However, the overall gravity center of brucellosis was still in the northern part of China. In the global autocorrelation analysis, brucellosis in China demonstrated a non-random distribution between 2013 and 2014, with spatial autocorrelation (Z?>?1.96, P?<?0.05) and a clustering trend, while no clustering trend was found from 2007 to 2012 or from 2015 to 2016. In the local autocorrelation analysis, a Low-Low cluster phenomenon was found in the south of China in 2013 and 2014. CONCLUSION:Human brucellosis remains a widespread challenge, particularly in northern China. The hotspots highlight potential high-risk areas which may require special plans and resources for monitoring and controlling the disease.

Project description:BACKGROUND:This study aimed to describe the changing distribution of human brucellosis between 2004 and 2017 in mainland China and seek scientific evidence of the relationship between socio-economic, environmental, and ecological factors and human brucellosis incidence. METHODS:The annual numbers of brucellosis cases and incidence rates from 31 provinces in mainland China between 2004 and 2017 were obtained from the Data-Center for China Public Health Science. The number of monthly brucellosis cases in 2018 was obtained from the Chinese Center for Disease Control and Prevention. The electronic map of the People's Republic of China was downloaded from the National Earth System Science Data Sharing Platform. Human population density, gross domestic product (GDP), and an inventory of cattle and sheep at the end of each year from 2004 to 2017 were obtained from the National Bureau of Statistics of China. Annual rainfall data from 31 provinces in the People's Republic of China from 2004 to 2017 were collected from the China Meteorological Data Service Center. The risk distribution and changing trends of human brucellosis were mapped with ArcGIS. A cluster analysis was employed to identify geographical areas and periods with statistically significant incidence rates. Multivariate linear regression was used to determine possible factors that were significantly correlated with the presence of human brucellosis cases. RESULTS:Human brucellosis cases have spread throughout the whole country. Human brucellosis cases occurred mostly from March to August and were concentrated from April to July. The inventory of sheep, GDP, and climate were significantly correlated with the presence of brucellosis cases in mainland China. CONCLUSIONS:The geographical expansion of human brucellosis in mainland China was observed, so did the high-incidence clusters between 2004 and 2017. Most of the cases were reported during the early spring to early summer (February-August). Results from the multivariate linear regression suggested that the inventory of sheep, GDP, and climate were significantly associated with the incidence of human brucellosis in mainland China.

Project description:Malaria is one of Ethiopia's most targeted communicable diseases for elimination. Malaria transmission varies significantly across space and time; and Ethiopia had space-time disparity in its transmission intensities. Considering heterogeneity and transmission intensity at the district level could play a crucial role in malaria prevention and elimination. This study aimed to explore temporal, spatial, and spatiotemporal clusters of malaria incidence in northwest Ethiopia. The analysis is based on monthly malaria surveillance data of districts and collected from the Amhara public health institute. The Kulldorff's retrospective space-time scan statistics using a discrete Poisson model were used to detect temporal, spatial, and space-time clusters of malaria incidence with and without adjusting the altitude + LLIN arm. Monthly malaria incidence had seasonal variations, and higher seasonal indices occurred in October and November. The temporal cluster occurred in the higher transmission season between September and December annually. The higher malaria incidence risk occurred between July 2012 and December 2013 (LLR = 414,013.41, RR = 2.54, P < 0.05). The purely spatial clustering result revealed that the most likely cluster occurred in the north and northwest parts of the region while secondary clusters varied in years. The space-time clusters were detected with and without considering altitude + LLIN arm. The most likely space-time cluster was concentrated in northwestern and western parts of the region with a high-risk period between July 2012 and December 2013 (LLR = 880,088.3, RR = 5.5, P < 0.001). We found eight significant space-time clusters using the altitude + LLIN arm. The most likely space-time cluster occurred in the western and northwestern parts of the region in July 2012-December 2013 (LLR = 886,097.7, RR = 5.55, P < 0.05). However, secondary clusters were located in eastern, northwestern, western parts of regions, which had different cases and relative risks in each cluster. Malaria transmission had temporal, spatial, and space-time variation in the region at the district level. Hence, considering these variations and factors contributing to malaria stratification would play an indispensable role in preventing and controlling practices that ultimately leads to malaria eliminations.

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Human distribution and spatial-temporal clustering analysis of human brucellosis in China from 2012 to 2016

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