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The Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program created standardized sub-county geographies that are comparable over time, place, and outcomes. Expected census tract-level counts were calculated for asthma emergency department visits and lung cancer. Census tracts were aggregated for various total population and sub-population thresholds, then suppression and stability were examined. A total of 5,000 persons was recommended for the more common outcome scheme and a total of 20,000 persons was recommended for the rare outcome scheme. Health outcomes with a median case count of 17.0 cases or higher should produce stable estimates at the census tract level. This project generated recommendations for three sub-county geographies that will be useful for surveillance purposes census tract, a more common outcome aggregation scheme, and a rare outcome aggregation scheme. This methodology can be applied anywhere to aggregate geographic units and produce stable rates at a finer resolution. Published by Elsevier Ltd.Racial disparities in cardiovascular health (CVH) continue to remain a public health concern in the United States. We use unique population-based data from the Multi-Ethnic Study of Atherosclerosis cohort to explore the black-white differences in optimal CVH. Utilizing geographically weighted regression methods, we assess the spatial heterogeneity in black-white differences in optimal CVH and the impact of both individual- and neighborhood-level risk factors. We found evidence of significant spatial heterogeneity in black-white differences that varied within and between the five sites. Initial models showed decreased odds of optimal CVH for blacks that ranged from 60% to 70% reduced odds - with noticeable variation of these decreased odds within each site. Adjusting for risk factors resulted in reductions in the black-white differences in optimal CVH. Further understanding of the reasons for spatial heterogeneities in black-white differences in nationally representative cohorts may provide important clues regarding the drivers of these differences. OBJECTIVE The study aimed to explore the association between area-based coverage of community services and the incidence of self-harm, which will provide an evaluation framework for the support of self-harm. METHODS Enhanced two-Step floating catchment area method was used to estimate the centersto- population ratio and geographical accessibility adjusted by a distance-decay function. Spearman's rank coefficient was used to examine the association between the self-harm rate and adjusted accessibility index. RESULTS There was a significant negative correlation between the accessibility index and selfharm rate in youth (rho = -0.87, P  less then  0.01) and older adults (rho = -0.87, P  less then  0.01). The survival curves showed no relationship between self-harm repetition and service accessibility in youth or older adults. CONCLUSIONS The uneven spatial accessibility of community social service centers and the independence between spatial accessibility and self-harm highlights the need to explore personal barriers to community service utilization. Fine-scale hotspots detection is crucial for optimum delivery of essential health-services for reducing severe malaria in pregnancy (MiP) and death cases in Burkina Faso. This study used hierarchical-Bayesian Spatio-temporal modeling to explore space-time patterns and pinpoint health-districts with an exceedance probability of severe MiP incidence and fatality rate. Study also assessed effect of health-district service delivery (readiness) on severe-MiP outcomes. Severe-MiP fatality rate declined considerably while its incidence rate remained unchanged between January-2013 and December-2018. Severe-MiP cases persisted throughout the year with peaks between August and November. These peaks increased 2.5-fold the fatality rate. Furthermore, severe-MiP fatality was higher in health-districts classified as low-readiness (IRR = 2.469, 95%CrI 1.632-3.738). However, the fatality rate decreased significantly with proper coverage with three doses for intermittent-preventive-treatment with sulphadoxine-pyrimethamine. Severe-MiP burden was heterogeneous spatially and temporally. The study suggested that health-programs should increase health-districts readiness and optimize resource allocation in high burden areas and months. A range of Bayesian models have been used to describe spatial and temporal patterns of disease in areal unit data. In this study, we applied two Bayesian spatio-temporal conditional autoregressive (ST CAR) models, one of which allows discontinuities in risk between neighbouring areas (creating 'groups'), to examine dengue fever patterns. UNC1999 Data on annual (2002-2017) and monthly (January 2013 - December 2017) dengue cases and climatic factors over 14 geographic areas were obtained for Makassar, Indonesia. Combinations of covariates and model formulations were compared considering credible intervals, overall goodness of fit, and the grouping structure. For annual data, an ST CAR localised model incorporating average humidity provided the best fit, while for monthly data, a single-group ST CAR autoregressive model incorporating rainfall and average humidity was preferred. Using appropriate Bayesian spatio-temporal models enables identification of different groups of areas and the impact of climatic covariates which may help inform policy decisions. Crown All rights reserved.In 2012, the United States experienced one of the largest outbreaks of West Nile virus (WNV)-associated deaths, with the majority occurring in Dallas County (Co.), Texas (TX) and surrounding areas. In this study, logistic mixed models were used to identify associations between the landscape, human population, and WNV-infected Culex quinquefasciatus mosquitoes during the 2012 WNV epidemic in Dallas Co. We found increased probabilities for WNV-positive mosquitoes in north and central Dallas Co. The most significant predictors of the presence of WNV in Cx. quinquefasciatus pools were increased urbanization (based on an index composed of greater population density, lower normalized difference vegetation index, higher coverage of urban land types, and more impervious surfaces), older human populations, and lower elevation. These relationships between the landscape, sociodemographics, and risk of enzootic transmission identified regions of Dallas Co., TX with highest risk of spillover to human disease during the 2012 WNV epidemic.

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