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OBJECTIVE@#To investigate the incidence trend and spatial clustering characteristics of scarlet fever in China from 2016 to 2020 to provide evidence for development of regional disease prevention and control strategies.@*METHODS@#The incidence data of scarlet fever in 31 provinces and municipalities in mainland China from 2016 to 2020 were obtained from the Chinese Health Statistics Yearbook and the Public Health Science Data Center led by the Chinese Center for Disease Control and Prevention.The three-dimensional spatial trend map of scarlet fever incidence in China was drawn using ArcGIS to determine the regional trend of scarlet fever incidence.GeoDa spatial autocorrelation analysis was used to explore the spatial aggregation of scarlet fever in China in recent years.@*RESULTS@#From 2016 to 2020, a total of 310 816 cases of scarlet fever were reported in 31 provinces, municipalities directly under the central government and autonomous regions, with an average annual incidence of 4.48/100 000.The reported incidence decreased from 4.32/100 000 in 2016 to 1.18/100 000 in 2020(Z=103.47, P < 0.001).The incidence of scarlet fever in China showed an obvious regional clustering from 2016 to 2019(Moran's I>0, P < 0.05), but was randomly distributed in 2020(Moran's I>0, P=0.16).The incidence of scarlet fever showed a U-shaped distribution in eastern and western regions of China, and increased gradually from the southern to northern regions.Inner Mongolia Autonomous Region and Hebei and Gansu provinces had the High-high (H-H) clusters of scarlet fever in China.@*CONCLUSION@#Scarlet fever still has a high incidence in China with an obvious spatial clustering.For the northern regions of China with H-H clusters of scarlet fever, the allocation of health resources and public health education dynamics should be strengthened, and local scarlet fever prevention and control policies should be made to contain the hotspots of scarlet fever.
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Humans , Incidence , Scarlet Fever/epidemiology , China/epidemiology , Spatial Analysis , Cluster Analysis , Spatio-Temporal AnalysisABSTRACT
Objective To explore the spatial epidemiological characteristics of mortality and probability of premature death caused by chronic obstructive pulmonary disease (COPD) among residents in Pudong New Area of Shanghai from 2010 to 2020, and to provide reference for the formulation of chronic obstructive pulmonary disease prevention and control strategies according to local conditions. Methods The death data of chronic obstructive pulmonary disease were obtained from the local death surveillance system of Pudong New Area. Crude mortality, age-standardized mortality, and probability of premature death caused by COPD in each subdistricts and towns of Pudong New Area were calculated. The geographical information system (GIS) was used to plot the spatial distribution maps of chronic obstructive pulmonary disease death. The trend surface analysis and the spatial autocorrelation analysis were performed to analyze the spatial distribution of chronic obstructive pulmonary disease death. Results The crude mortality, age-standardized mortality and probability of premature death caused by COPD among residents in Pudong New Area between 2010 and 2020 were 58.40/100,000, 22.35/100,000, and 0.26%, respectively. The results of trend surface analysis showed that the crude mortality, age-standardized mortality and probability of premature death caused by COPD gradually increased from north to south. In the east-west direction, the crude mortality, age-standardized mortality, and probability of premature death showed an upward trend from west to east. The global autocorrelation analysis suggested that there existed a positive spatial autocorrelation for the crude mortality, age-standardized mortality, and probability of premature death. The local spatial autocorrelation analysis showed that the high-high clustering areas of COPD crude mortality, standardized mortality and premature mortality were all located in the rural areas of the southeast of Pudong New Area. Conclusion There are urban and rural differences in the mortality of chronic obstructive pulmonary disease among residents in Pudong New Area from 2010 to 2020. The residents living in rural southeast coast of Pudong New Area are more seriously affected by chronic obstructive pulmonary disease and should be paid more attention.
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Background & objectives: Scrub typhus caused by Orientia tsutsugamushi presents as acute undifferentiated fever and can be confused with other infectious causes of fever. We studied scrub typhus as part of a study on hospital-based surveillance of zoonotic and vector-borne zoonotic diseases at a tertiary care hospital located in the Wardha district, Maharashtra, India. We report here descriptive epidemiology and climatic factors affecting scrub typhus. Methods: Patients of any age and sex with fever of ?5 days were enrolled for this study. Data on sociodemographic variables were collected by personal interviews. Blood samples were tested by IgM ELISA to diagnose scrub typhus. Confirmation of scrub typhus was done by indirect immunofluorescence assay for IgM (IgM IFA). The climatic determinants were determined using time-series Poisson regression analysis. Results: It was found that 15.9 per cent of the study participants were positive for scrub typhus by IgM ELISA and IgM IFA, both. Positivity was maximum (23.0%) in 41-60 yr of age and more females were affected than males (16.6 vs. 15.5%). Farmworkers were affected more (23.6%) than non-farm workers (12.9%). The disease positivity was found to be high in monsoon and post-monsoon seasons (22.9 and 19.4%) than in summer and winter. Interpretation & conclusions: There were three hot spots of scrub typhus in urban areas of Wardha district. Rainfall and relative humidity in the previous month were the significant determinants of the disease
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Objective:To investigate the spatial distribution characteristics of Keshan disease in Shandong Province, and to provide evidence for prevention and control of Keshan disease.Methods:The incidence data of Keshan disease in Shandong Province from 1960 to 2018 were collected from Shandong Provincial Institute for Endemic Disease Control and Prevention, and a spatial database was built. Global and local spatial autocorrelation (Moran's I) were analyzed by ArcGIS 10.2 and GeoDa 1.14 softwares, respectively. Local indicators on spatial association (LISA) aggregation graph was drawn. This allowed us to investigate the spatial autocorrelation and cluster range of the distribution of Keshan disease in Shandong Province. Results:A total of 4 172 cases of Keshan disease were reported in Shandong Province with an annual incidence rate of 0 to 51.4/10 000 of the population at the township-level from 1960 to 2018. Global spatial autocorrelation analysis on the incidence of Keshan disease at the township-level showed that global Moran's I values ranged from 0.020 to 0.429 in 1962 - 1964, 1969 - 1985, 1989, 1995, 1998 - 2001 and 2004 - 2016 ( P < 0.05), thus indicating significant spatial autocorrelation overall. LISA analysis further revealed that high-high clusters of Keshan disease existed in 1960, 1962 - 1964, 1969 - 1985, 1989, 1998 - 2000 and 2002 - 2016. These clusters were predominantly distributed in three areas: Zoucheng City, Pingyi County and Sishui County in the southwest of Shandong Province; Wulian County and Ju County in the southeast of Shandong Province; and Qingzhou City, Linqu County and Yishui County in the central and middle-south of Shandong Province. Conclusions:Keshan disease exhibits significant spatial autocorrelation in Shandong Province. High-high clusters are mainly located in certain townships in the southwest, southeast, central and middle-south of Shandong Province.
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Abstract Geographical variation on hip fractures (HF) may be related to the geographical variation of drinking water composition (DWC); minerals in drinking water may contribute to its fragility. We aim to investigate the effects of DWC on HF risk in Portugal (2000-2010). From National Hospital Discharge Register we selected admissions of patients aged ≥50 years, diagnosed with HF caused by low/moderate energy traumas. Water components and characteristics were selected at the municipality level. A spatial generalized additive model with a negative binomial distribution as a link function was used to estimate the association of HF with variations in DWC. There were 96,905HF (77.3% in women). The spatial pattern of HF risk was attenuated after being adjusted for water parameters. Results show an indirect association between calcium, magnesium, and iron and HF risk but no clear relation between aluminum, cadmium, fluoride, manganese, or color and HF risk. Regarding pH, the 6.7pH and 7pH interval seems to pose a lower risk. Different dose-response relationships were identified. The increase of calcium, magnesium, and iron values in DWC seems to reduce regional HF risk. Long-term exposure to water parameters, even within the regulatory limits, might increase the regional HF risk.
Resumo A variabilidade espacial existente na fratura do colo do fêmur (FCF) pode estar relacionada com a variabilidade geográfica da composição da água para consumo (CAC), devido à ação dos minerais na fragilidade óssea. O objetivo do artigo foi investigar o efeito da CAC no risco de FCF em Portugal (2000-2010). Do registo nacional de altas hospitalares, foram selecionadas todas as admissões em indivíduos ≥50, com diagnóstico de FCF causado por trauma de baixo/moderado impacto. Os componentes e características da água foram usados ao nível do município. Um modelo espacial aditivo generalizado, com a distribuição binomial negativa como função de ligação, foi usado para estimar a associação de FCF e as variações da CAC. Foram selecionadas 96.905 FCF (77,3% em mulheres). O padrão espacial de risco de FCF foi atenuado após ser ajustado pelos parâmetros da CAC. Os resultados mostraram uma associação indireta com cálcio, magnésio e ferro. No entanto, com alumínio, cádmio, fluoreto, manganês e cor, a associação com o risco não foi clara. O intervalo de pH de 6,7 a 7 parece apresentar um menor risco. Foram identificadas diferentes dose-resposta. O aumento do cálcio, magnésio e ferro na CAC parece reduzir o risco regional de FCF. Uma exposição a longo prazo, mesmo obedecendo aos limites impostos por lei, parece aumentar o risco regional de FCF.
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Humans , Male , Female , Osteogenesis Imperfecta , Drinking Water , Water Quality , Femoral Fractures , MineralsABSTRACT
Introduction@#There is a high burden of tuberculosis (TB) in the Western Province, Papua New Guinea. This study aims to describe the spatial distribution of TB in the Balimo District Hospital (BDH) catchment area to identify TB patient clusters and factors associated with high rates of TB.@*Methods@#Information about TB patients was obtained from the BDH TB patient register for the period 26 April 2013 to 25 February 2017. The locations of TB patients were mapped, and the spatial scan statistic was used to identify high- and low-rate TB clusters in the BDH catchment area.@*Results@#A total of 1568 patients were mapped with most being from the Balimo Urban (n = 252), Gogodala Rural (n = 1010) and Bamu Rural (n = 295) local level government (LLG) areas. In the Gogodala region (Balimo Urban and Gogodala Rural LLGs), high-rate clusters occurred closer to the town of Balimo, while low-rate clusters were located in more remote regions. In addition, closer proximity to Balimo was a predictor of high-rate clustering.@*Discussion@#There is heterogeneity in the distribution of TB in the Balimo region. Active case-finding activities indicated potential underdiagnosis of TB and the possibility of associated missed diagnoses of TB. The large BDH catchment area emphasizes the importance of the hospital in managing TB in this rural region.
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Objective: To analyze the spatial epidemiological characteristics of bacillary dysentery and its correlation with meteorological elements in Chongqing, and to construct its incidence prediction model, thus providing scientific basis for the prevention and control of bacterial dysentery. Methods: The data of bacterial dysentery cases and meteorological factors from 2009 to 2016 in Chongqing was collected in this study. Descriptive methods were employed to investigate the epidemiological distribution of bacillary dysentery. Spatiotemporal scanning statistics was used to analyze spatiotemporal characteristics of bacillary dysentery. DCCA coefficient method was used to quantify the correlation between the incidence of bacillary dysentery and meteorological elements. Both Boruta algorithm and particle swarm optimization algorithm (PSO) combined with support vector machine for regression model (SVR) were used to establish the prediction model for the incidence of bacterial dysentery. Results: ①The mean annual reported incidence of bacillary dysentery in Chongqing from 2009 to 2016 was 29.394/100 000. Children <5 years old had the highest incidence (295.892/100 000) among all age categories and scattered children had the highest proportion (50.335%) among all occupation categories. The seasonal incidence peak was from May to October. Bacterial dysentery showed a significant spatial-temporal aggregation that the most likely clusters for disease was found mainly in the main urban areas and main gathering time was from June to October. ②The most important meteorological elements associated with the incidence of bacterial dysentery were monthly mean atmospheric pressure (ρDCCA=-0.918), monthly mean maximum temperature (ρDCCA=0.875) and monthly mean temperature (ρDCCA=0.870). ③The mean squared error (MSE), mean absolute percentage error (MAPE) and square correlation coefficient (R2) of PSO_SVR model constructed based on meteorological elements were 0.055, 0.101 and 0.909, respectively. Conclusion: The main urban areas of Chongqing and the northeast of Chongqing should be regarded as the key areas for the prevention and control of bacillary dysentery. At the same time, according to the characteristics of bacillary dysentery, relevant health departments should take targeted measures to control the spread and prevalence of bacillary dysentery among children <5 years old, scattered children and farmers. The PSO_SVR model constructed based on meteorological elements has good predictive performance and can provide scientific theoretical support for the prevention and control of bacterial dysentery.
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Spatial epidemiology is a new branch of epidemiology, and is a subject that mainly analyzes the geographical distribution and changes of population health or diseases and its related impact factors. Recently, spatial epidemiology has been extensively applied in the prevention and control of parasitic diseases in China, and delightful results have been achieved. However, the research and application of theories and methods of spatial epidemiology are still needed to protect the people’s health in China.
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Spatial epidemiology is a new branch of epidemiology, and is a subject that mainly analyzes the geographical distribution and changes of population health or diseases and its related impact factors. Recently, spatial epidemiology has been extensively applied in the prevention and control of parasitic diseases in China, and delightful results have been achieved. However, the research and application of theories and methods of spatial epidemiology are still needed to protect the people’s health in China.
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Schistosomiasis is one of the key diseases of surveillance and prevention in China. The elimination of schistosomiasis is of great significance to people’s health and social economy. With the development of spatial epidemiology, progress has been made in the spatial distribution of schistosomiasis, the prediction of spatial and temporal trends, and analysis of the environmental factors. This paper reviews the application of spatial epidemiology in the control and prevention of schistosomiasis and introduces the spatio-temporal distribution methods, spatial model, and application of remote sensing technology.
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Spatial epidemiology is a new branch of epidemiology that aims to map the spatial distribution and characteristics as well as to explore the associated influencing factors of diseases by using the geographic information system and other spatial technologies.In recent years,with the rapid development of information-related modern technology,improvement of accessibility on healthrelated services,natural environment,social and economic big data etc.,spatial epidemiology has made considerable progress in both theory and practice and played more important roles in the public health area of China.
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Spatial epidemiology is a new branch of epidemiology that aims to map the spatial distribution and characteristics as well as to explore the associated influencing factors of diseases by using the geographic information system and other spatial technologies.In recent years,with the rapid development of information-related modern technology,improvement of accessibility on healthrelated services,natural environment,social and economic big data etc.,spatial epidemiology has made considerable progress in both theory and practice and played more important roles in the public health area of China.
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Objective To explore the spatial description of Keshan disease(KD)and to provide a basis for reasonable allocation of health resources and for making precision prevention and control strategies. Methods In 2013 and 2014, the KD's condition, prevention and control measures and their effects were investigated in the diseased affected counties in the provinces through combination of case search and key survey. Results A total of 16(100.0%,16/16)diseased provinces,315(96.0%,315/328)diseased counties were surveyed,and 1 562 people with KD were detected in 281 000 residents, the detection rate was 55.6/10 000. Chronic and latent KD detection rates were 8.9/10 000(250)and 46.7/10 000(1 312),respectively.There were 261(82.9%)diseased counties that had reached the control standards of KD,and 54(17.1%)did not meet the control standards,which mainly distributed in the provinces of Henan, Inner Mongolia, Gansu and Shanxi. Conclusions The detection rate of KD has been at a low level, but in Henan, Inner Mongolia, Gansu, and Shanxi, there are prevalent KD areas that have not yet reached the control level.This part of the areas should be treated as key prevention and control areas of KD.
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The monitoring and control of malaria depends largely on the spatial analysis technology and mathematical models. Visualization of malaria situation is the most popular way to present how malaria transmits. In this paper ,the malaria epidemic situation and the application of spatial epidemiology of malaria in China are summarized,so as to provide the systematic epidemi-ological information for malaria elimination in China.
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The implementation of geospatial technologies and methods for improving health has become widespread in many nations, but India's adoption of these approaches has been fairly slow. With a large population, ongoing public health challenges, and a growing economy with an emphasis on innovative technologies, the adoption of spatial approaches to disease surveillance, spatial epidemiology, and implementation of health policies in India has great potential for both success and efficacy. Through our evaluation of scientific papers selected through a structured key phrase review of the National Center for Biotechnology Information on the database PubMed, we found that current spatial approaches to health research in India are fairly descriptive in nature, but the use of more complex models and statistics is increasing. The institutional home of the authors is skewed regionally, with Delhi and South India more likely to show evidence of use. The need for scientists engaged in spatial health analysis to first digitize basic data, such as maps of road networks, hydrological features, and land use, is a strong impediment to efficiency, and their work would certainly advance more quickly without this requirement.
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Spatial epidemiology and molecular epidemiology have been widely used in the studies of tuberculosis (TB),but each with limitations.Integration of the two methods provides new ideas and methods in TB research.All referenced articles are from CNKI,Wan Fang database,PubMed database and Web of Science database.Method of combining spatial epidemiology and molecular epidemiology has been widely used in determining the local epidemic strains of TB genotype,the transmission mechanism,risk factors of TB,drug-resistant TB,as well as evaluating the effectiveness of TB prevention and control measures.Application of the combined methods is of important significance in the studies of TB,thus worthy to be further introduced to researchers and disease prevention and control workers in this country.
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Objective To discuss the spatial-temporal distribution and epidemic trends of autumn-winter type scrub typhus in Shandong province,and provide scientific evidence for further study for the prevention and control of the disease.Methods The scrub typhus surveillance data during 2006-2014 were collected from Shandong Disease Reporting Information System.The data was analyzed by using software ArcGIS 9.3 (ESRI Inc.,Redlands,CA,USA),GeoDa 0.9.5-i and SatScan 9.1.1.The Moran' s I,log-likelihood ratio (LLR),relative risk (RR) were calculated and the incidence choropleth maps,local indicators of spatial autocorrelation cluster maps and space scaning cluster maps were drawn.Results A total of 4 453 scrub typhus cases were reported during 2006-2014,and the annual incidence increased with year.Among the 17 prefectures (municipality) in Shandong,13 were affected by scrub typhus.The global Moran' s I index was 0.501 5 (P＜0.01).The differences in local Moran' s I index among 16 prefectures were significant (P＜0.01).The "high-high" clustering areas were mainly Wulian county,Lanshan district and Juxian county of Rizhao,Xintai county of Tai' an,Gangcheng and Laicheng districts of Laiwu,Yiyuan county of Zibo and Mengyin county of Linyi.Spatial scan analysis showed that an eastward moving trend of high-risk clusters and two new high-risk clusters were found in Zaozhuang in 2014.The centers of the most likely clusters were in the south central mountainous areas during 2006-2010 and in 2012,eastem hilly areas in 2011,2013 and 2014,and the size of the clusters expanded in 2008,2011,2013 and 2014.One spatial-temporal cluster was detected from October 1,2014 to November 30,2014,the center of the cluster was in Rizhao and the radius was 222.34 kilometers.Conclusion A positive spatial correlation and spatial agglomerations were found in the distribution of autumn-winter type scrub typhus in Shandong.Since 2006,the epidemic area of the disease has expanded and the number of high-risk areas has increased.Moreover,the eastward moving and periodically expanding trends of high-risk clusters were detected.
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Spatial epidemiology and molecular epidemiology have been widely used in the studies of tuberculosis (TB),but each with limitations.Integration of the two methods provides new ideas and methods in TB research.All referenced articles are from CNKI,Wan Fang database,PubMed database and Web of Science database.Method of combining spatial epidemiology and molecular epidemiology has been widely used in determining the local epidemic strains of TB genotype,the transmission mechanism,risk factors of TB,drug-resistant TB,as well as evaluating the effectiveness of TB prevention and control measures.Application of the combined methods is of important significance in the studies of TB,thus worthy to be further introduced to researchers and disease prevention and control workers in this country.
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Objective To discuss the spatial-temporal distribution and epidemic trends of autumn-winter type scrub typhus in Shandong province,and provide scientific evidence for further study for the prevention and control of the disease.Methods The scrub typhus surveillance data during 2006-2014 were collected from Shandong Disease Reporting Information System.The data was analyzed by using software ArcGIS 9.3 (ESRI Inc.,Redlands,CA,USA),GeoDa 0.9.5-i and SatScan 9.1.1.The Moran' s I,log-likelihood ratio (LLR),relative risk (RR) were calculated and the incidence choropleth maps,local indicators of spatial autocorrelation cluster maps and space scaning cluster maps were drawn.Results A total of 4 453 scrub typhus cases were reported during 2006-2014,and the annual incidence increased with year.Among the 17 prefectures (municipality) in Shandong,13 were affected by scrub typhus.The global Moran' s I index was 0.501 5 (P＜0.01).The differences in local Moran' s I index among 16 prefectures were significant (P＜0.01).The "high-high" clustering areas were mainly Wulian county,Lanshan district and Juxian county of Rizhao,Xintai county of Tai' an,Gangcheng and Laicheng districts of Laiwu,Yiyuan county of Zibo and Mengyin county of Linyi.Spatial scan analysis showed that an eastward moving trend of high-risk clusters and two new high-risk clusters were found in Zaozhuang in 2014.The centers of the most likely clusters were in the south central mountainous areas during 2006-2010 and in 2012,eastem hilly areas in 2011,2013 and 2014,and the size of the clusters expanded in 2008,2011,2013 and 2014.One spatial-temporal cluster was detected from October 1,2014 to November 30,2014,the center of the cluster was in Rizhao and the radius was 222.34 kilometers.Conclusion A positive spatial correlation and spatial agglomerations were found in the distribution of autumn-winter type scrub typhus in Shandong.Since 2006,the epidemic area of the disease has expanded and the number of high-risk areas has increased.Moreover,the eastward moving and periodically expanding trends of high-risk clusters were detected.
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Spatial statistics plays an important role in spatial epidemiology studies of echinococcosis .Spatial statistics can be used to describe the spatial distribution ,predict the prevalence ,identify disease clusters ,and analyze the influencing factors of echinococcosis .To describe spatial distribution and predict the prevalence ,we can use spatial interpolation ,empirical bayes smoothing and ellipsoidal gradient .Spatial autocorrelation always used to identify disease clusters .Moran's I value ,Getis'G val‐ue and spatial scan statistics are used to judge spatial autocorrelation .Molding plays an important role on analyzing risk factors of echinococcosis .Generalised linear mixed models and Bayesian model are always performed with both spatial factors ,such as geomorphologic features ,climatic characteristics ,vegetation index and factors which make great effect on disease transmission . To figure out the spatial distribution of echinococcosis is significant for echinococcosis control and prevention .