OBJECTIVETo study the quantified indices for describing the distributional status of diseases in the spatial point pattern analysis, and provide the a statistic in disease prevention and control.

METHODSG function, F function, J function and K function were summarized based on the inter-case distances from the view of spatial point pattern analysis. Through the introduction of the basic principles, these were used to analyze the data of acute schistosomiasis in the Guichi District, Chizhou City, Anhui province, with the study distances being from 0 to 3000 meters with 50-meter intervals. The findings were also validated by means of spatial moving scan window performed in SaTScan software.

RESULTSA total of 83 cases of acute schistosomiasis identified in Guichi District, and the point map showed that these cases were mainly distributed around the Yangtze and Qiupu rivers. The computational methods and characteristics of the four quantified indices were obtained. These acute schistosomiasis cases were also explored by using these indices, and the results showed that C and K functions were above 95% confidence interval. While, F and J functions were below 95% confidence interval. Ml these four indices showed that spatial clustering existed in the acute cases, which was consistent with the results of spatial moving scan window method. The latter method also found a most likely cluster, the coordinate of the circle center is (30.65 N, 117.44 E), radius is 2.69 km, and relative risk is 12.78 (DIR = 32. 80, P = 0. 0001).

CONCLUSIONThe quantified indices to describe the distributional status of diseases have not only solved the obstacle that spatial point pattern map which could only be analyzed qualitatively, but also supplied a theoretical foundation to deepen spatial clustering analysis.

OBJECTIVETo study the quantified indices for describing the distributional status of

Epidemiologic Measurements ; Models, Statistical ; Space-Time Clustering

OBJECTIVETo explore the spatial and temporal characteristics of measles patients younger than 1 year old in Shandong province.

METHODSA total of 5309 cases of measles, whose patients were younger than 1 year old in Shandong province between year 1999 and 2008 were collected. The epidemic features of measles were described, and the annual infant incidence was calculated. Software ArcGIS9.3 was applied to draw the spatial map of the disease, and the software GeoDa0.95i-beta was adopted to analyze the spatial autocorrelation.

RESULTSThe incidence among infants younger than 1 year old reported in Shandong province rose from 23.45/100 000 (206 cases) in 1999 to 269.60/100 000 (2791 cases) in 2008.5309 cases covered all month-aged infants under 1 year old, except 12 months old. Most patients (3494 cases) aged between 6 - 9 months old; especially the infants around 8 months old, accounting for 20.7% (1100/5309). The epidemic peak was between March and May, accounting for 45.5% (2414/5309). The spatial and temporal distribution features showed an up and down temporal trend and an increase from east to west in spatial trend. The global Moran's I values of measles incidence among infants in Shandong province were 0.346, 0.150, 0.396, 0.213, 0.477, 0.354 and 0.331 in year 1999, 2001 - 2002, 2005 - 2008 (P < 0.01) and 0.076 in year 2004 (P < 0.05). The local spatial autocorrelation analysis showed that southwest and northwest districts of Shandong were highly clustered districts of measles.

CONCLUSIONIn Shandong, the measles incidence among infants younger than 1 year old rose obviously; especially the infants aged between 6-9 months age. The epidemic peak was between March and May. A positive spatial correlation was found, the disease showed a distinct regional distribution feature, and a cluster district was found.

China ; epidemiology ; Geography ; Humans ; Incidence ; Infant ; Infant, Newborn ; Measles ; epidemiology ; Space-Time Clustering

OBJECTIVETo explore the biases and confoundings in Spatial Epidemiological studies.

METHODSPossible bias and confounding and their impact on study results in Spatial Epidemiology were analyzed in given examples.

RESULTSIn Spatial Epidemiology, biases related to ascertainment/numerator/denominator induced by the choice of the disease induction/latency period and mis-specification of exposure-disease model, exposure inaccuracy, spatial dependency, significance tests etc. were involved, as well as to ecological, socio-economic confoundings factors.

CONCLUSIONThe sources of bias in 'Spatial Epidemiology' were both numerous and complex, that might be overestimated or underestimated on the study results. Hence, careful interpretation of such studies was needed.

Bias ; Confounding Factors (Epidemiology) ; Ecology ; Epidemiology ; Geographic Information Systems ; Geography ; Humans ; Socioeconomic Factors ; Space-Time Clustering

OBJECTIVETo explore the influence of landscape elements on the transmission of hemorrhagic fever with renal syndrome (HFRS) in Changsha.

METHODSA total of 327 cases of HFRS diagnosed between year 2005 - 2009 were recruited in the study. Based on the demographic data, meteorological data and the data of second national land survey during the same period, a GIS landscape elements database of HFRS at the township scale of Changsha was established. Spatial-temporal cluster analysis methods were adopted to explore the influence of landscape elements on the spatial-temporal distribution of HFRS in Changsha during the year of 2005 - 2009.

RESULTSThe annual incidences of HFRS in Changsha between year 2005 - 2009 were 1.16/100 000 (70 cases), 0.95/100 000 (58 cases), 1.40/100 000(87 cases), 0.75/100 000(47 cases) and 1.02/100 000(65 cases) respectively. The results of poisson regression model analysis of principal component showed that the incidence of HFRS was positively correlated with farmland area (M = 29.00 km2) and urban and rural area (M = 6.12 km2; incidence rate ratios (IRR) = 1.34, 95% CI: 1.27 - 1.41); but negatively correlated with forestland area (M = 39.00 km2; IRR = 0.67, 95% CI: 0.55 - 0.81) and garden plot area (M = 0.99 km2; IRR = 0.74, 95% CI: 0.63 - 0.86). A significant cluster of the spatial-temporal distribution of HFRS cases was found in the study. The primary cluster (28.9 N, 113.37 E, radius at 22.22 km, RR = 5.23, log likelihood ratio (LLR) = 51.61, P <0.01, 67 cases of HFRS and incidence at 4.4/100 000) was found between year 2006 and 2007; and the secondary cluster (28.2 N, 113.6 E, RR = 10.77, LLR = 16.01, P < 0.01, 11 cases of HFRS and the incidence at 10.6/100 000) was found between year 2008 and 2009.

CONCLUSIONThe landscape elements were found to be closely related to the prevalence and transmission of HFRS.

China ; epidemiology ; Climate ; Geographic Information Systems ; Hemorrhagic Fever with Renal Syndrome ; epidemiology ; transmission ; Humans ; Regression Analysis ; Space-Time Clustering

Objective: To explore the spatio-temporal epidemic trends and related driving effects of meteorological factors on brucellosis in Datong city, Shanxi province, from 2005 to 2015. Methods: We collected the surveillance data on brucellosis and related meteorological data in Datong city from 2005 to 2015, to describe the epidemic characteristics of the disease. Quasi-Poisson distribution lag non-liner model (DLNM) was built to explore the driving effect of monthly meteorological data on the disease. Results: From 2005 to 2015, Datong city reported a total of 17 311 cases of brucellosis including one death, with the annual average incidence as 47.43 per 100 000 persons. A rising trend was seen during the study period. The monthly incidence of Brucellosis presented an obvious curve with a major peak from March to June, accounted for 48.40% of the total cases. The high incidence areas in the city gradually expanded from the northeast and southeast to the western areas. Results from the DLNM studies suggested that seasonality of brucellosis in Datong was significantly affected by metrological factors such as evaporation, rainfall and temperature. The peak of delayed effect appeared the highest when the monthly cumulative evaporation capacity was 140-260 mm and the monthly cumulative rainfall was 20-60 mm with lag less than 1 month or the monthly temperature was -13 ℃ with lag of 4-5 months. Conclusions: The incidence of human brucellosis in Datong city increased significantly from 2005 to 2015. Meteorological factors such as evaporation, rainfall, temperature all showed significant driving effects on the disease.
Brucellosis/epidemiology* ; China/epidemiology* ; Cities ; Climate ; Humans ; Incidence ; Meteorological Concepts ; Space-Time Clustering ; Spatio-Temporal Analysis ; Temperature

OBJECTIVETo identify spatial distribution and risk factors among tuberculosis (TB) cases in Songjiang district, Shanghai, 2006 - 2009.

METHODSAll active TB cases and all bacteriologically confirmed TB cases diagnosed during the period from 2006 to 2009 were recruited into the study. Spatial scan statistics were used to identify spatial clusters. Using logistic regression, we compared the demographic and clinical characteristics of TB cases in spatial clusters versus TB cases not in spatial clusters.

RESULTSA total of 1815 active TB cases and 730 bacteriologically confirmed TB cases were recruited during 2006 - 2009. Chedun township and Xinqiao township was detected to be a spatial cluste (RR = 1.38, LLR = 16.78, P < 0.01), which was the location of the municipal industrial zone. No spatial cluster was found during 2006 - 2007, while during 2008 - 2009 Chedun township was detected to be a spatial cluster (RR = 1.70, LLR = 15.06, P < 0.01). Among resident population, the spatial cluster of TB cases was located in the southwestern part of Songjiang district, which included five townships Xinbang, Shihudang, Xiaokunshan, Maogang and Yongfeng (RR = 1.49, LLR = 10.52, P < 0.01); while among migrant population, the spatial cluster of TB cases was located in Chedun township (RR = 1.55, LLR = 15.64, P < 0.01). There were higher proportions of resident TB cases who were farmers (AOR = 4.9, 95%CI: 1.9 - 12.3) or had other occupations (AOR = 2.6, 95%CI: 1.1 - 5.9) in the spatial cluster. There were higher proportions of migrant TB cases who lived here for less than 5 years (< 1 year: AOR = 5.9, 95%CI: 1.8 - 19.5; 1 - 5 years: AOR = 3.2, 95%CI: 1.0 - 9.9) or worked at other occupations (AOR = 2.8, 95%CI: 1.5 - 5.1) and lower proportions of migrant TB cases who came from Eastern region (AOR = 0.3, 95%CI: 0.1 - 0.8) or Middle region (AOR = 0.5, 95%CI: 0.3 - 0.9) in the spatial cluster.

CONCLUSIONIn Songjiang district there was a spatial cluster in TB cases, which was Chedun township. Local residents with TB who were farmers or had other occupations were more likely to be in the spatial cluster. Migrants with TB who lived here for less than 5 years or came from Western region were more likely to be in the spatial cluster.

Adult ; Aged ; China ; epidemiology ; Female ; Humans ; Logistic Models ; Male ; Middle Aged ; Risk Factors ; Space-Time Clustering ; Transients and Migrants ; Tuberculosis ; epidemiology ; Tuberculosis, Pulmonary ; epidemiology

OBJECTIVETo identify the epidemiological and clinical features of unexpected sudden cardiac deaths (SUD) in Yunnan.

METHODSChoosing the old SUD cases from Xiangyun, Heqing, Nanjian and Dayao counties and using the standardized verbal autopsy Form, we interviewed the family members of the cases, witnesses and doctors as well as reviewing their medical files to get relative information.

RESULTSWe identified 116 SUDs in 21 villages from 1984 to 2004. The village-specific annually standardized incidence rates were ranged from 0.2/1000 to 8.9/1000 (median = 0.8/1000). 66% and 29% of the SUDs occurred in July and August respectively. The incidence rates of SUD were higher (1.6/1000, chi(2) = 16, P < 0.01) in 10 - 39 year-olds, and higher in females than in males (RR = 1.6, 95% CI: 1.1 - 2.3). Seventy percent of SUD occurred in families having clustering nature and 60% of the additional cases in the family were occurred within 24 hours (median = 20 hours) after the first SUD identified in the family. SUD occurred in 23 families followed the first affected family in a village during the same season. In these 23 families, 61% of the first SUD occurred within 8 days after the first SUD in the first affected family. 68% and 66% of the SUDs did not have any complaints or signs during the last 3 weeks or from 3 weeks to 2 days prior to the onset of the disease. 63% of the SUDs had cardiac symptoms within the last 2 days prior to the onset with major symptoms as dizziness, nausea, faintness, unconsciousness, weakness and palpitation. The median duration from acute onset to death was 2 hours.

CONCLUSIONSThe extreme time-space clustering of SUD in families and in villages suggested that the risk factors occurred in specific time and location. Familial clustered SUD cases had common exposure pattern. Sudden onset of acute cardiac symptoms often followed by sudden death. Epidemiological study on new cases was necessary to identify risk factors and to develop hypothesis for causation. In July 2005, we instituted a special SUD surveillance system for all the affected counties together with 10 counties which had no reported cases.

Adolescent ; Adult ; Age Factors ; Child ; China ; epidemiology ; Death, Sudden, Cardiac ; epidemiology ; Female ; Humans ; Incidence ; Interviews as Topic ; Male ; Retrospective Studies ; Risk Factors ; Sex Factors ; Space-Time Clustering ; Young Adult

OBJECTIVETo analyze the spatial-temporal distribution of Hepatitis E (HEV) in Hunan province from 2006 to 2014.

METHODSData related to HEV cases in Hunan province from 2006 to 2014 were collected from the Infectious Diseases Reporting Information System in the formation System of Disease Prevention and Control of China. Based on ArcGIS (10.2) and SaTScan(version 9.1), spatial autocorrelation analysis and space-time clustering analysis were used to study the prevalence on HEV.

RESULTSA total of 7 124 HEV cases were reported with 3 deaths during this period. The average annual incidence rate was 1.22/10(5). Most of the cases were over 55 years old and the majority of them (54.15%) were farmers. The distribution of HEV showed differences on locations and the regions with high incidence seen in northern and western areas of Hunan. However the regions with low incidence appeared in central or southern parts of Hunan. Data from the global spatial autocorrelation analysis showed that there was space autocorrelation on the HEV incidence rates in counties (cities, districts) (Moran'I was positive,P<0.05). A total of 31 countries were found in the high-high region with most of the clusters located in northern and western Hunan. According to local indication of spatial autocorrelation analysis, 31 countries in high-high region all showed statistically significant differences (P<0.05). RESULTS from the space-time scan showed 7 space-time clustering areas, including those most likely in the western Hunan area (2012-2014); the secondary clusters in northern Hunan areas (2011-2014).

CONCLUSIONSSignificant cluster pattern was found in the distribution of HEV in Hunan province. Clusters found in northern and western of Hunan province were seen more than in other regions.

Adult ; Aged ; China ; epidemiology ; Cities ; Cluster Analysis ; Farmers ; statistics & numerical data ; Hepatitis E ; epidemiology ; Humans ; Incidence ; Middle Aged ; Prevalence ; Seroepidemiologic Studies ; Space-Time Clustering ; Spatial Analysis