Kulldorff's Scan Statistic Research Articles

Epidemic Characteristics, Spatiotemporal Pattern, and Risk Factors of Other Infectious Diarrhea in Fujian Province From 2005 to 2021: Retrospective Analysis.

Other infectious diarrhea (OID) continues to pose a significant public health threat to all age groups in Fujian Province. There is a need for an in-depth analysis to understand the epidemiological pattern of OID and its associated risk factors in the region. In this study, we aimed to describe the overall epidemic characteristics and spatiotemporal pattern of OID in Fujian Province from 2005 to 2021 and explore the linkage between sociodemographic and environmental factors and the occurrence of OID within the study area. Notification data for OID in Fujian were extracted from the China Information System for Disease Control and Prevention. The spatiotemporal pattern of OID was analyzed using Moran index and Kulldorff scan statistics. The seasonality of and short-term impact of meteorological factors on OID were examined using an additive decomposition model and a generalized additive model. Geographical weighted regression and generalized linear mixed model were used to identify potential risk factors. A total of 388,636 OID cases were recorded in Fujian Province from January 2005 to December 2021, with an average annual incidence of 60.3 (SD 16.7) per 100,000 population. Children aged <2 years accounted for 50.7% (196,905/388,636) of all cases. There was a steady increase in OID from 2005 to 2017 and a clear seasonal shift in OID cases from autumn to winter and spring between 2005 and 2020. Higher maximum temperature, atmospheric pressure, humidity, and precipitation were linked to a higher number of deseasonalized OID cases. The spatial and temporal aggregations were concentrated in Zhangzhou City and Xiamen City for 17 study years. Furthermore, the clustered areas exhibited a dynamic spreading trend, expanding from the southernmost Fujian to the southeast and then southward over time. Factors such as densely populated areas with a large <1-year-old population, less economically developed areas, and higher pollution levels contributed to OID cases in Fujian Province. This study revealed a distinct distribution of OID incidence across different population groups, seasons, and regions in Fujian Province. Zhangzhou City and Xiamen City were identified as the major hot spots for OID. Therefore, prevention and control efforts should prioritize these specific hot spots and highly susceptible groups.

Mapping, trends, and factors associated with anemia among children aged under 5 y in East Africa

Child anemia is a severe public health concern in low- and middle-income countries. Identifying anemia change over time, its spatial heterogeneity, and the influencing factors is critical to monitoring and prioritizing successful interventions.This analysis uses nationally representative Demographic and Health Surveys administrated in 11 East African countries, which included 149 864 children. Trend analysis, interpolation, and Kulldorff scan statistics were used. Trend and hotspot areas were identified and multilevel (three-level) ordinal logistic regression analyzed.More than half of the children in East Africa suffer from anemia. In all but two countries, the prevalence of child anemia was considered a severe public health problem; no country had an anemia prevalence < 35%. Anemia reduction efforts and the prevalence of anemia exhibit fluctuations over time in East African countries. Zimbabwe has shown a more consistent reduction in all forms of anemia. Most countries have experienced a significant reduction in the severe form of anemia in recent years. Community-based spatial analysis indicates that child anemia is heterogeneous within and between countries. Many communities are experiencing a high prevalence of anemia among children, with a maximum of four of five and a minimum one of five of their children infected by any anemia. Nutrition, genetic hemoglobin disorders, physical environment, poverty, and maternal and community characteristics influence child anemia.Multisectorial interventions that improve maternal and child nutrition are needed. These analyses support the design and prioritization of interventions in high-risk areas and communities.

Privacy Preservation in Multi-Cloud Secure Data Fusion for Infectious-Disease Analysis

It is often observed that people's data are scattered across various organizations and these data can be used to generate usable insights when integrated. However, data fusion from multiple data hosting sites could put user privacy at risk albeit with some security mechanisms. This paper studies a data-analytic platform that adopts the Kulldorff scan statistic to determine infectious-disease spatial hotspots by integrating and analyzing users' health and location data that are respectively stored in two clouds. We examine the privacy threats to this platform which has a key-oblivious inner product encryption (KOIPE) mechanism in place to ensure that only coarse-grained statistical data is revealed to the honest-but-curious (HbC) entity. To protect user privacy from the designed inference attack, we exploit a game-theoretic approach to incentivize users to form anonymous clusters with a quantitative privacy guarantee. We conduct extensive simulations based on real-life datasets to demonstrate the performance of our scheme in terms of design overhead and privacy level.

A spatial analysis of co-circulating dengue and chikungunya virus infections during an epidemic in a region of Northeastern Brazil

The aim of this study was to describe, through spatial analysis, the cases of arboviruses (dengue and chikungunya), including deaths, during the first epidemic after the circulation of the chikungunya virus (CHIKV) in the state of Pernambuco, Northeastern Brazil. This was an ecological study in both Pernambuco and the state capital, Recife, from 2015 to 2018. The odds ratios (OR) were estimated, and the statistical significance was considered p≤0.05. For the spatial analysis, Kulldorff's space-time scan statistics method was adopted to identify spatial clusters and to provide the relative risk (RR). In order to assess the significance at a level of p < 0.01 of the model, the number of Monte Carlo replications was 999 times. To perform the scan statistics we used the Poisson probability model, with a circular scanning window; annual temporal precision and retrospective analysis. A total of 227 deaths and 158,728 survivors from arboviruses was reported during the study period, with 100 deaths from dengue and 127 from CHIKV. The proportion of deaths from dengue was 0.08% and from chikungunya was 0.35%. The proportion of all those infected (deaths plus survivors) with dengue was 77.42% and with chikungunya was 22.58%. Children aged 0 to 9 years were around 3 times more likely to die than the reference group (OR 2.84; CI95% 1.16–5.00). From the age of 40, the chances of death increased significantly: 40–49 (OR 2.52; CI95% 1.19–5.29), 50–59 (OR 5.55; CI95% 2.76–11.17) and 60 or more (OR 14.90; CI95% 7.79–28.49). Males were approximately twice as likely to die as females (OR 1.77; CI95% 1.36–2.30). White-skinned people were less likely to die compared to non-white (OR 0.60; CI95% 0.41–0.87). The space-time analysis of prevalence in the state of Pernambuco revealed the presence of four clusters in the years 2015 and 2016, highlighting the Metropolitan Macro-region with a relative risk=4 and the Agreste and Hinterland macro-regions with a relative risk=3.3. The spatial distribution of the death rate in the municipality of Recife smoothed by the local empirical Bayesian estimator enabled a special pattern to be identified in the southwest and northeast of the municipality. The spatiotemporal analysis of the death rate revealed the presence of two clusters in the year 2015. In the primary cluster, it may be noted that the aforementioned aggregate presented a RR=7.2, and the secondary cluster presented a RR=6.0. The spatiotemporal analysis with Kulldorff's space-time scan statistics method, proved viable in identifying the risk areas for the occurrence of arboviruses, and could be included in surveillance routines so as to optimize prevention strategies during future epidemics.

Use of spatial analytics and geographic information systems in childhood diarrhoea in rural areas of India: A protocol paper

Introduction and Aim: The most recent advancement in epidemiology is using Geographic Information Systems (GIS) to comprehend illness based on clustering and spatial analysis. Using spatial analysis has shown positive changes in sanitation, reducing diarrhoea's burden. This study put forwards the methodology used to analyze spatiotemporal clustering and hotspot areas of childhood diarrhea in Karkala taluk, Udupi during 2015 to 2018. Materials and Methods: This study describes the methods used to analyze the space-time clustering and local indicators of spatial association (LISA) of childhood diarrhoea using the GeoDa and SaTScan programmes. At the Karkala taluk, data on under-five diarrhoea was gathered throughout time and space to develop the geospatial models. While the timing of the onset of the diarrhoea impacts the temporal characteristics, the child's position at the time of the event determines the spatial characteristics. The child's location and time of diarrheal episode was considered for the geospatial analysis. Results: The Kulldorff scan statistic (SaTScan v10.1) was employed for geographical analysis, and GeoDa software used for LISA and hotspot analysis. The randomness distribution of childhood diarrhoea over time and space was determined using the Kulldorff scan statistic software. The SaTScan locates and evaluates the statistical significance of geographical clusters based on the number of cases inside and outside the cylinder window. The scanning window in the software uses a cylinder with an elliptical or circular base to study intervals for time, space, and space-time. The different combinations of High and Low categories of the spatial association are covered by the hotspot analysis utilizing the GeoDa software. Conclusion: To build data-driven public health decision-making, it is required to link spatial and temporal patterns of diarrheal incidence among under-five children with predictive variables derived from routine data.

Epidemiological patterns related to deaths caused by visceral leishmaniasis in the southern Amazon region of Brazil.

We analysed the spatial and spatiotemporal patterns of visceral leishmaniasis (VL) mortality at the municipality level in an endemic state in the southern Amazon region of Brazil. Individual-level factors associated with death due to VL were also investigated. All VL cases and deaths reported between 2007 and 2018 were included. The global and local bivariate Moran's index assessed the space-time autocorrelation of smoothed triennial VL mortality. Kulldorff's scan statistics investigated spatial and spatiotemporal clusters. A multivariable logistic regression explored sociodemographic, diagnostic and clinical variables associated with death due to VL. We observed an overall VL mortality and lethality of 0.14 cases/100 000 inhabitants and 11.2%, respectively. A total of 14% of the municipalities registered at least one VL-related death. In the southeastern mesoregion of the state, we detected high-risk spatial (relative risk [RR] 14.14; p<0.001) and spatiotemporal (RR 15.91; p<0.001) clusters for VL mortality. Bivariate Moran's analysis suggested a high space-time autocorrelation of VL mortality. Death by VL was associated with age ≥48y (odds ratio [OR] 7.2 [95% confidence interval {CI} 3.4 to 15.3]), displacement for notification (OR 3.3 [95% CI 1.5 to 7.2]) and occurrence of oedema (OR 2.8 [95% CI 1.3 to 6.1]) and bleeding (OR 5.8 [95% CI 2.6 to 12.8]). VL mortality has a heterogeneous spatiotemporal distribution. The death-related factors suggest late diagnosis as an underlying cause of mortality.

Spatiotemporal variation of malaria incidence in parasite clearance interventions and non-intervention areas in the Amhara Regional State, Ethiopia.

In Ethiopia, malaria remains a major public health problem. To eliminate malaria, parasite clearance interventions were implemented in six kebeles (the lowest administrative unit) in the Amhara region. Understanding the spatiotemporal distribution of malaria is essential for targeting appropriate parasite clearance interventions to achieve the elimination goal. However, little is known about the spatiotemporal distribution of malaria incidence in the intervention and non-intervention areas. This study aimed to investigate the spatiotemporal distribution of community-based malaria in the intervention and non-intervention kebeles between 2013 and 2018 in the Amhara Regional State, Ethiopia. Malaria data from 212 kebeles in eight districts were downloaded from the District Health Information System2 (DHIS2) database. We used Autoregressive integrated moving average (ARIMA) model to investigate seasonal variations; Anselin Local Moran's I statistical analysis to detect hotspot and cold spot clusters of malaria cases; and a discrete Poisson model using Kulldorff scan statistics to identify statistically significant clusters of malaria cases. The result showed that the reduction in the trend of malaria incidence was higher in the intervention areas compared to the non-intervention areas during the study period with a slope of -0.044 (-0.064, -0.023) and -0.038 (-0.051, -0.024), respectively. However, the difference was not statistically significant. The Global Moran's I statistics detected the presence of malaria clusters (z-score = 12.05; p<0.001); the Anselin Local Moran's I statistics identified hotspot malaria clusters at 21 locations in Gendawuha and Metema districts. A statistically significant spatial, temporal, and space-time cluster of malaria cases were detected. Most likely type of spatial clusters of malaria cases (LLR = 195501.5; p <0.001) were detected in all kebeles of Gendawuha and Metema districts. The temporal scan statistic identified three peak periods between September 2013 and November 2015 (LLR = 8727.5; p<0.001). Statistically significant most-likely type of space-time clusters of malaria cases (LLR = 97494.3; p<0.001) were detected at 22 locations from June 2014 to November 2016 in Metema district. There was a significant decline in malaria incidence in the intervention areas. There were statistically significant spatiotemporal variations of malaria in the study areas. Applying appropriate parasite clearance interventions is highly recommended for the better achievement of the elimination goal. A more rigorous evaluation of the impact of parasite clearance interventions is recommended.

Spatio-temporal clusters and patterns of spread of dengue, chikungunya, and Zika in Colombia.

Colombia has one of the highest burdens of arboviruses in South America. The country was in a state of hyperendemicity between 2014 and 2016, with co-circulation of several Aedes-borne viruses, including a syndemic of dengue, chikungunya, and Zika in 2015. We analyzed the cases of dengue, chikungunya, and Zika notified in Colombia from January 2014 to December 2018 by municipality and week. The trajectory and velocity of spread was studied using trend surface analysis, and spatio-temporal high-risk clusters for each disease in separate and for the three diseases simultaneously (multivariate) were identified using Kulldorff's scan statistics. During the study period, there were 366,628, 77,345 and 74,793 cases of dengue, chikungunya, and Zika, respectively, in Colombia. The spread patterns for chikungunya and Zika were similar, although Zika's spread was accelerated. Both chikungunya and Zika mainly spread from the regions on the Atlantic coast and the south-west to the rest of the country. We identified 21, 16, and 13 spatio-temporal clusters of dengue, chikungunya and Zika, respectively, and, from the multivariate analysis, 20 spatio-temporal clusters, among which 7 were simultaneous for the three diseases. For all disease-specific analyses and the multivariate analysis, the most-likely cluster was identified in the south-western region of Colombia, including the Valle del Cauca department. The results further our understanding of emerging Aedes-borne diseases in Colombia by providing useful evidence on their potential site of entry and spread trajectory within the country, and identifying spatio-temporal disease-specific and multivariate high-risk clusters of dengue, chikungunya, and Zika, information that can be used to target interventions.

Epidemiological characteristics of mumps from 2004 to 2020 in Jiangsu, China: a flexible spatial and spatiotemporal analysis.

Abstract The mumps resurgence has frequently been reported around the world in recent years, especially in many counties mumps vaccines have been widely used. This study aimed to describe the spatial epidemiological characteristics of mumps in Jiangsu, and provide a scientific basis for the implementation and adjustment of strategies to prevent and control mumps. The epidemiological characteristics were described with ratio or proportion. Spatial autocorrelation, Tango's flexible spatial scan statistics, and Kulldorff's elliptic spatiotemporal scan statistics were applied to identify the spatial autocorrelation, detect hot and cold spots of mumps incidence, and aggregation areas. A total of 172 775 cases were reported from 2004 to 2020 in Jiangsu. The general trend of mumps incidence is declining with a bimodal seasonal distribution identified mainly in summer and winter, respectively. Children aged 5–10 years old are the main risk group. A migration trend of hot spots from southeast to northwest over time was found. Similar high-risk aggregations were detected in the northwestern parts through spatial-temporal analysis with the most likely cluster time frame around 2019. Local medical and health administrations should formulate and implement targeted health care policies and allocate health resources more appropriately corresponding to the epidemiological characteristics of mumps.

Spatio-temporal epidemiology of emergency medical requests in a large urban area. A scan-statistic approach.

Pre-hospital care is provided by emergency medical services (EMS) staff, the initial health care providers at the scene of disaster. This study aimed to describe the characteristics of EMS callers and space-time distribution of emergency requests in a large urban area. Descriptive thematic maps of EMS requests were created using an empirical Bayesian smoothing approach. Spatial, temporal and spatio-temporal clustering techniques were applied to EMS data based on Kulldorff scan statistics technique. Almost 225,000 calls were registered in the EMS dispatch centre during the study period. Approximately two-thirds of these calls were associated with an altered level of patient consciousness, and the median response time for rural and urban EMS dispatches was 12.2 and 10.1 minutes, respectively. Spatio-temporal clusters of EMS requests were mostly located in central parts of the city, particularly near the downtown area. However, high-response time clustered areas had a low overlap with these general, spatial clusters. This low convergence shows that some unknown factors, other than EMS requests, influence the high-response times. The findings of this study can help policymakers to better allocate EMS resources and implement tailored interventions to enhance EMS system in urban areas.

Subnational mapping for targeting anaemia prevention in women of reproductive age in Ethiopia: A coverage-equity paradox.

Anaemia in women of reproductive age (WRA) can be effectively addressed if supported by a better understanding of the spatial variations, magnitude, severity and distribution of anaemia. This study aimed to map the subnational spatial distribution of anaemia (any, moderate and severe forms) among WRA in Ethiopia. We identified and mapped (any, moderate and severe) anaemia hotspots in WRA (n = 14,923) at the subnational level and identified risk factors using multilevel logistic regression. Kulldorff scan statistics were used to identify hotspot regions. Ordinary kringing was used to predict the anaemia prevalence in unmeasured areas. The overall anaemia prevalence increased from 16.6% in 2011 to 23.6% in 2016, a rise that was mostly related to the widening of existing hotspot areas. The primary clusters of (any) anaemia were in Somali and Afar regions. The horn of the Somali region represented a cluster of 330 km where 10% of WRA were severely anaemic. The Oromia-Somali border represented a significant cluster covering 247 km, with 9% severe anaemia. Population-dense areas with low anaemia prevalence had high absolute number of cases. Women education, taking iron-folic-acid tablets during pregnancy and birth-delivery in health facilities reduced the risk of any anaemia (P < 0.05). The local-level mapping of anaemia helped identify clusters that require attention but also highlighted the urgent need to study the aetiology of anaemia to improve the effectiveness and safety of interventions. Both relative and absolute anaemia estimates are critical to determine where additional attention is needed.

Spatial distribution of foot-and-mouth disease (FMD) outbreaks in South Africa (2005-2016).

Foot-and-mouth disease (FMD) is a transboundary animal disease that has negative socioeconomic consequences including impacts on food security. In South Africa, FMD outbreaks in communal farming communities cause major livestock and human livelihood concerns; they raise apprehensions about the effectiveness of FMD control measures within the FMD protection areas. This study aimed to identify high-risk areas for FMD outbreaks at the human/domestic animal/wildlife interface of South Africa. Cuzick-Edwards tests and Kulldorff scan statistics were used to detect spatial autocorrelation and spatial-temporal clusters of FMD outbreaks for the years 2005-2016.Four high-risk clusters were identified and the spatial distribution of outbreaks in cattle were closer to game reserve fences and consistent with wildlife contacts as a main contributor of FMD occurrence. Strategic allocation of resources, focused control measures, and cooperation between the affected provinces are recommended to reduce future outbreaks. Further research is necessary to design cost-effective control strategies for FMD.

The spatial clustering analysis of COVID-19 and its associated factors in mainland China at the prefecture level

Coronavirus disease 2019 (COVID-19) has become a worldwide public health threat. Many associated factors including population movement, meteorological parameters, air quality and socioeconomic conditions can affect COVID-19 transmission. However, no study has combined these various factors in a comprehensive analysis. We collected data on COVID-19 cases and the factors of interest in 340 prefectures of mainland China from 1 December 2019 to 30 April 2020. Moran's I statistic, Getis-Ord Gi⁎ statistic and Kulldorff's space-time scan statistics were used to identify spatial clusters of COVID-19, and the geographically weighted regression (GWR) model was applied to investigate the effects of the associated factors on COVID-19 incidence. A total of 67,449 laboratory-confirmed cases were reported during the study period. Wuhan city as well as its surrounding areas were the cluster areas, and January 25 to February 21, 2020, was the clustering time of COVID-19. The population outflow from Wuhan played a significant role in COVID-19 transmission, with the local coefficients varying from 14.87 to 15.02 in the 340 prefectures. Among the meteorological parameters, relative humidity and precipitation were positively associated with COVID-19 incidence, while the average wind speed showed a negative correlation, but the relationship of average temperature with COVID-19 incidence inconsistent between northern and southern China. NO2 was positively associated, and O3 was negatively associated, with COVID-19 incidence. Environment with high levels of inbound migration or travel, poor ventilation, high humidity or heavy rainfall, low temperature, and high air pollution may be favorable for the growth, reproduction and spread of SARS-CoV-2. Therefore, applying appropriate lockdown measures and travel restrictions, strengthening the ventilation of living and working environments, controlling air pollution and making sufficient preparations for a possible second wave in the relatively cold autumn and winter months may be helpful for the control and prevention of COVID-19.

High-risk clusters and temporal trends in congenital syphilis infection in Brazil

RESUMOObjetivo.Determinar a existência de aglomerados de municípios (clusters) com alto risco para sífilis congênita (SC) no Brasil e descrever a tendência temporal da doença no país, comparando a população de crianças cujas mães realizaram o pré-natal com aquelas cujas mães não realizaram esse controle.Métodos.Este estudo ecológico utilizou dados do Sistema de Informação de Agravos de Notificação (SINAN) e do Sistema de Informações sobre Nascidos Vivos (SINASC). Para a análise de aglomerados, a estatística de varredura Kulldorff foi aplicada à população de risco. A significância estatística foi determinada pelo logaritmo da razão de verossimilhança utilizando a distribuição discreta de Poisson. Para a análise das tendências das taxas de detecção do agravo, utilizou-se a regressão de Prais-Winsten. A análise foi realizada com os programas SatScan 9.4 e Stata 14.0.Resultados.Clusters com taxas de detecção de 41,3, 44,4 e 188,1 casos/10 000 nascidos vivos foram identificados em 2001, 2009 e 2017, respectivamente. Em 2001, as taxas foram 8 vezes maiores nos clusters do que no restante do país; em 2009, foram 3,3 vezes maiores; e, em 2017, 2,5. Detectou-se uma tendência crescente na infecção por SC em todas as regiões e unidades da federação. As taxas foram 8,53 vezes maiores nos neonatos cujas mães não realizaram pré-natal (243,3 casos/1 000 nascidos vivos vs. 28,4 casos/1 000 nascidos vivos em mães com pré-natal).Conclusões.A identificação de aglomerados de municípios com alto risco para SC e de tendências crescentes de infecção por SC em todo o país, mesmo na presença de pré-natal, indicam a necessidade de melhoria nas ações de saúde pública para o combate dessa doença.

Spatial distribution of Leishmania seropositive dogs in the Angelim neighborhood, Teresina, Piauí, Brazil: appraisal of three spatial clustering methods

The detection of spatial clusters has been suggested as a potential tool for guiding the delivery of interventions against visceral leishmaniasis; however, little attention has been given to the consistency of results by using different spatial clustering methods. The present study aimed to assess the performance of three different techniques for identifying patterns in the spatial distribution of canine leishmaniasis in the city of Teresina, Brazil. This cross-sectional study was based on a serological survey for canine leishmaniasis in which each dog domicile was georeferenced to the exact location of each animal in space. The spatial analysis was performed using three methods: the Cuzick-Edwards statistic, the Hierarchical Nearest Neighbour analysis, and the Kulldorff Scan statistic. All techniques were able to identify clusters of high prevalences of canine leishmaniasis, but results were not consistent among techniques. The feasibility of the identification and location of clusters of cases in a restricted number of villages in neighborhoods might contribute to the optimization of control measures against visceral leishmaniasis. However, given the relative inconsistency of the results provided by the different methods, protocols for assessing clusters of diseases should always include more than one method of evaluation.

Can local risk of West Nile virus infection be predicted from previous cases? A descriptive study in Quebec, 2011-2016.

This study aimed at (1) describing the local risk of West Nile virus (WNV) infection in humans based on previous case reports and (2) investigating the spatial clustering of cases in the five most affected administrative regions of Quebec, Canada, for the 2011-2016 period. Human WNV cases declared to the Ministry of Health and Social Services of Quebec(Ministère de la santé et des services sociaux, MSSS) were retrieved. Incidence risk by age and sex was calculated for the study period. The yearly and monthly occurrence of cases in geographical units (GUs) was described and the probability of observing cases in a GU with cases reported in the previous year or month was assessed. Moran's I was used to assess global clustering across the study area. Spatial clusters were identified by the Kulldorff scan statistic. A total of 261 WNV cases were declared to the MSSS between 2011 and 2016 in the study area. Overall, a low percentage of GU with cases reported had additional cases reported over the next month or year. Global spatial clustering was weak but statistically significant (p < 0.05) for 2012 and 2015. For these two years, spatial clusters of high-risk GUs were identified. Results underline the challenge of predicting the distribution of WNV incidence risk in Quebec based on previous occurrence of human cases. Ongoing research with high spatial resolution entomological data is still necessary to understand the spatial distribution of risk at a local scale.

Identifying high-risk areas for nonfatal opioid overdose: a spatial case-control study using EMS run data

PurposeThe objective of our study was to incorporate stricter probable nonfatal opioid overdose case criteria, and advanced epidemiologic approaches to more reliably detect local clustering in nonfatal opioid overdose activity in EMS runs data. MethodsData were obtained using emsCharts for our study area in southwestern Pennsylvania from 2007 to 2018. Cases were identified as emergency medical service (EMS) responses where naloxone was administered, and improvement was noted in patient records between initial and final Glasgow Coma Score. A subsample of all-cause EMS responses sites were used as controls and exact matched to cases on sex and 10-year-age category. Clustering was assessed using difference in Ripley's K function for cases and controls and Kulldorff scan statistics. ResultsDifference in K functions indicated no significant difference in probable nonfatal overdose EMS runs across the study area compared to all-cause EMS runs. However, scan statistics did identify significant local clustering of probable nonfatal overdose EMS runs (maximum likelihood = 16.40, P = 0.0003). ConclusionsResults highlight relevance of EMS data to detect community-level overdose activity and promote reliable use through stricter case definition criteria and advanced methodological approaches. Techniques examined have the potential to improve targeted delivery of neighborhood-level public health response activities using a near real-time data source.

Spatial-temporal analysis on pulmonary tuberculosis in Beijing during 2005-2015

Objective: To analyze the spatial distribution and identify the high risk areas of pulmonary tuberculosis at the township level in Beijing during 2005-2015. Methods: Data on pulmonary tuberculosis cases was collected from the tuberculosis information management system. Global autocorrelation analysis, local indicators of spatial association and Kulldorff's Scan Statistics were applied to map the spatial distribution and detect the space-time clusters of the pulmonary tuberculosis cases during 2005-2015. Results: Spatial analysis on the incidence of pulmonary tuberculosis at the township level demonstrated that the spatial autocorrelation was positive during the study period. The values of Moran's I ranged from 0.224 3 to 0.291 8 with all the P values less than 0.05. Hotspots were primarily distributed in 8 towns/streets as follows: Junzhuang, Wangping, Yongding and Tanzhesi in Mentougou district, Yancun in Fangshan district, Wangzuo town in Fengtai district, Tianqiao street in Xicheng district and Tianzhu town in Shunyi district. Spatiotemporal clusters across the entire study period were identified by using Kulldorff's spatiotemporal scan statistic. The primary cluster was located in Chaoyang and Shunyi districts, including 17 towns/streets, as follows: Cuigezhuang, Maizidian, Dongfeng, Taiyanggong, Zuojiazhuang, Hepingjie, Xiaoguan, Xiangheyuan, Dongba, Jiangtai, Wangjing, Jinzhan, Jiuxianqiao, Laiguangying, Sunhe towns/streets in Chaoyang district, Houshayu and Tianzhu town in Shunyi district, during January to December 2005. Conclusion: Incidence rates of pulmonary tuberculosis displayed spatial and temporal clusterings at the township level in Beijing during 2005-2015, with high risk areas relatively concentrated in the central and southern parts of Beijing.

Visual-spatial and temporal characteristics related to infectious Tuberculosis epidemics in Guangxi Zhuang Autonomous Region, 2012-2015

Objective: To study the spatial and temporal mode of infectious TB transmission in Guangxi Zhuang Autonomous Region (Guangxi). Methods: Data related to infectious TB case (Include smear and/or culture positive patients) in Guangxi were collected from the National Notifiable Disease Reported System (NNDRS) from 2010 to 2015. Spatial-temporal analysis and prediction were performed by SaTScan 7.0.2, GeoDa 1.8.12, R program v 3.3.1 and SPSS 19.0 software, using the time series model, Moran's I global and local spatial autocorrelation (Empirical Bayes adjustment). Kulldorff 's space-time scan statistics displayed by R software was used to identify the temporal and spatial trend of TB. Results: The total number of infectious TB cases, collected from NNDRS was 76 151, and showing a decreasing trend on annual incidence (value of Chi-square for Linear trend=3 464.53, P-value=0.000). The forecast value of TB cases in 2016 was 7 764 (4 971-10 557), with peak in March, analyzed through the Winters'multiplicative model. The Moran's I global Statistics was greater than 0 (0.257-0.390). TB cluster seemed to have been existed for several years. The most significant hot spots seemed to be mainly located in the central and western parts of Guangxi, shown by local spatial autocorrelation statistics and the result from space-time scanning.Counties or districts that located in the east parts of Guangxi presented the low-low relation (significant cold spots). The situation of infectious TB seemed migratory. Conclusions: Our data showed an annual decreasing trend of incidence on infectious TB with temporal concentration in spring and summer. Main clusters (hot spots) were found to be located in the central and western parts of Guangxi. Hopefully, our findings can provide clues to uncover the real mode of TB transmission at the molecular-biological level.

High prevalence of epilepsy in onchocerciasis endemic regions in the Democratic Republic of the Congo.

BackgroundAn increased prevalence of epilepsy has been reported in many onchocerciasis endemic areas. The objective of this study was to determine the prevalence of epilepsy in onchocerciasis endemic areas in the Democratic Republic of the Congo (DRC) and investigate whether a higher annual intake of Ivermectin was associated with a lower prevalence of epilepsy.Methodology/Principle findingsBetween July 2014 and February 2016, house-to-house epilepsy prevalence surveys were carried out in areas with a high level of onchocerciasis endemicity: 3 localities in the Bas-Uele, 24 in the Tshopo and 21 in the Ituri province. Ivermectin uptake was recorded for every household member. This database allowed a matched case-control pair subset to be created that enabled putative risk factors for epilepsy to be tested using univariate logistic regression models. Risk factors relating to onchocerciasis were tested using a multivariate random effects model. To identify presence of clusters of epilepsy cases, the Kulldorff's scan statistic was used. Of 12, 408 people examined in the different health areas 407 (3.3%) were found to have a history of epilepsy. A high prevalence of epilepsy was observed in health areas in the 3 provinces: 6.8–8.5% in Bas-Uele, 0.8–7.4% in Tshopo and 3.6–6.2% in Ituri. Median age of epilepsy onset was 9 years, and the modal age 12 years. The case control analysis demonstrated that before the appearance of epilepsy, compared to the same life period in controls, persons with epilepsy were around two times less likely (OR: 0.52; 95%CI: (0.28, 0.98)) to have taken Ivermectin than controls. After the appearance of epilepsy, there was no difference of Ivermectin intake between cases and controls. Only in Ituri, a significant cluster (p-value = 0.0001) was identified located around the Draju sample site area.ConclusionsThe prevalence of epilepsy in health areas in onchocerciasis endemic regions in the DRC was 2–10 times higher than in non-onchocerciasis endemic regions in Africa. Our data suggests that Ivermectin protects against epilepsy in an onchocerciasis endemic region. However, a prospective population based intervention study is needed to confirm this.