Spatial and Spatio-temporal Epidemiology This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

A Bayesian latent process spatiotemporal regression model for areal count data
Publication date: June 2018 Source:Spatial and Spatio-temporal Epidemiology, Volume 25 Author(s): C. Edson Utazi, Emmanuel O. Afuecheta, C. Christopher Nnanatu Model-based approaches for the analysis of areal count data are commonplace in spatiotemporal analysis. In Bayesian hierarchical models, a latent process is incorporated in the mean function to account for dependence in space and time. Typically, the latent process is modelled using a conditional autoregressive (CAR) prior. The aim of this paper is to offer an alternative approach to CAR-based priors for modelling the latent process. The proposed approach is ba...
Source: Spatial and Spatio-temporal Epidemiology - February 14, 2018 Category: Epidemiology Source Type: research

Gender and geographical inequalities in fatal drug overdose in Iran: A province-level study in 2006 and 2011
Conclusion Rates of fatal drug overdose were higher among Iranian men and in both younger and older age groups which call for scaling up harm reduction and increasing access to gender- and age-specific substance use treatment services. (Source: Spatial and Spatio-temporal Epidemiology)
Source: Spatial and Spatio-temporal Epidemiology - February 14, 2018 Category: Epidemiology Source Type: research

Gaining relevance from the random: Interpreting observed spatial heterogeneity
Publication date: June 2018 Source:Spatial and Spatio-temporal Epidemiology, Volume 25 Author(s): Rachel Carroll, Shanshan Zhao In Bayesian disease mapping, spatial random effects are used to account for confounding in the data so that reasonable estimates for the fixed effects can be obtained. Typically, the spatial random effects are mapped and qualitative comments are made related to an increase or decrease in risk for certain areas. The approach outlined here illustrates how a quantitative secondary assessment can be applied to make more useful and applicable inference related to these spatial random effects. We ar...
Source: Spatial and Spatio-temporal Epidemiology - February 14, 2018 Category: Epidemiology Source Type: research

Integrating activity spaces in health research: Comparing the VERITAS activity space questionnaire with 7-day GPS tracking and prompted recall
Conclusions : There is a spatial correspondence between destinations collected through VERITAS and 7-day GPS tracking. Both collection methods offer complementary ways to assess daily mobilities, useful to study environmental determinants of health and health inequities. (Source: Spatial and Spatio-temporal Epidemiology)
Source: Spatial and Spatio-temporal Epidemiology - January 8, 2018 Category: Epidemiology Source Type: research

Evaluation of spatio-temporal Bayesian models for the spread of infectious diseases in oil palm
Publication date: Available online 6 January 2018 Source:Spatial and Spatio-temporal Epidemiology Author(s): Marie Denis, Benoît Cochard, Indra Syahputra, Hubert de Franqueville, Sébastien Tisné In the field of epidemiology, studies are often focused on mapping diseases in relation to time and space. Hierarchical modeling is a common flexible and effective tool for modeling problems related to disease spread. In the context of oil palm plantations infected by the fungal pathogen Ganoderma boninense, we propose and compare two spatio-temporal hierarchical Bayesian models addressing the lack of information on propa...
Source: Spatial and Spatio-temporal Epidemiology - January 7, 2018 Category: Epidemiology Source Type: research

Assessing the Association of Diabetes Self-Management Education Centers with Age-adjusted Diabetes Rates Across U.S.: A Spatial Cluster Analysis Approach
In this study, we focus on demographic patterns and geographic regionalization of the disease by including accessibility and availability of diabetes education resources as a critical component in understanding and confronting differences in diabetes prevalence, as well as addressing regional or sub-regional differences in awareness, treatment and control. We conducted an ecological county-level study utilizing publicly available secondary data on 3,109 counties in the continental U.S. We used a Bayesian spatial cluster model that enabled spatial heterogeneities across the continental U.S. to be addressed. We used the Amer...
Source: Spatial and Spatio-temporal Epidemiology - December 19, 2017 Category: Epidemiology Source Type: research

Diving into the consumer nutrition environment: a Bayesian spatial factor analysis of neighborhood restaurant environment
Publication date: Available online 18 December 2017 Source:Spatial and Spatio-temporal Epidemiology Author(s): Hui Luan, Jane Law, Martin Lysy Neighborhood restaurant environment (NRE) plays a vital role in shaping residents’ eating behaviors. While NRE ‘healthfulness’ is a multi-facet concept, most studies evaluate it based only on restaurant type, thus largely ignoring variations of in-restaurant features. In the few studies that do account for such features, healthfulness scores are simply averaged over accessible restaurants, thereby concealing any uncertainty that attributed to neighborhoods’ size or spat...
Source: Spatial and Spatio-temporal Epidemiology - December 18, 2017 Category: Epidemiology Source Type: research

Approximate Bayesian Computation for Spatial SEIR(S) Epidemic Models
Publication date: Available online 22 November 2017 Source:Spatial and Spatio-temporal Epidemiology Author(s): Grant D. Brown, Aaron T. Porter, Jacob J. Oleson, Jessica A. Hinman Approximate Bayesian Computation (ABC) provides an attractive approach to estimation in complex Bayesian inferential problems for which evaluation of the kernel of the posterior distribution is impossible or computationally expensive. These highly parallelizable techniques have been successfully applied to many fields, particularly in cases where more traditional approaches such as Markov chain Monte Carlo (MCMC) are impractical. In this wor...
Source: Spatial and Spatio-temporal Epidemiology - November 29, 2017 Category: Epidemiology Source Type: research

Bayesian hierarchical model of ceftriaxone resistance proportions among Salmonella serotype Heidelberg infections
Publication date: February 2018 Source:Spatial and Spatio-temporal Epidemiology, Volume 24 Author(s): Weidong Gu, Felicita Medalla, Robert M. Hoekstra The National Antimicrobial Resistance Monitoring System (NARMS) at the Centers for Disease Control and Prevention tracks resistance among Salmonella infections. The annual number of Salmonella isolates of a particular serotype from states may be small, making direct estimation of resistance proportions unreliable. We developed a Bayesian hierarchical model to improve estimation by borrowing strength from relevant sampling units. We illustrate the models with different s...
Source: Spatial and Spatio-temporal Epidemiology - November 29, 2017 Category: Epidemiology Source Type: research

Adult obesity prevalence at the county level in the United States, 2000 –2010: Downscaling public health survey data using a spatial microsimulation approach
This study therefore, uses a spatial microsimulation approach to estimate obesity prevalence rates at the county level across the United States to visualize temporal, spatial and spatio-temporal changes from 2000 to 2010 for use in the monitoring of obesity prevalence. This method iteratively replicates the demographic characteristics of public health survey respondents with census data for those areas. Following, Local Moran's I was used to identify clusters of high and low obesity prevalence. The findings showed that obesity prevalence rose dramatically over the last decade with substantial variation across counties and ...
Source: Spatial and Spatio-temporal Epidemiology - November 19, 2017 Category: Epidemiology Source Type: research

Bayesian hierarchical model of ceftriaxone resistance proportions of Salmonella Heidelberg
Publication date: Available online 1 November 2017 Source:Spatial and Spatio-temporal Epidemiology Author(s): Weidong Gu, Felicita Medalla, Robert M. Hoekstra The National Antimicrobial Resistance Monitoring System (NARMS) at the Centers for Disease Control and Prevention tracks resistance among Salmonella infections. The annual number of Salmonella isolates of a particular serotype from states may be small, making direct estimation of resistance proportions unreliable. We developed a Bayesian hierarchical model to improve estimation by borrowing strength from relevant sampling units. We illustrate the models with dif...
Source: Spatial and Spatio-temporal Epidemiology - November 19, 2017 Category: Epidemiology Source Type: research

Spatial variation in cancer incidence and survival over time across Queensland, Australia
Publication date: November 2017 Source:Spatial and Spatio-temporal Epidemiology, Volume 23 Author(s): Susanna M. Cramb, Paula Moraga, Kerrie L. Mengersen, Peter D. Baade Interpreting changes over time in small-area variation in cancer survival, in light of changes in cancer incidence, aids understanding progress in cancer control, yet few space–time analyses have considered both measures. Bayesian space–time hierarchical models were applied to Queensland Cancer Registry data to examine geographical changes in cancer incidence and relative survival over time for the five most common cancers (colorectal, melanoma, ...
Source: Spatial and Spatio-temporal Epidemiology - November 19, 2017 Category: Epidemiology Source Type: research

A Bayesian spatio-temporal framework to identify outbreaks and examine environmental and social risk factors for infectious diseases monitored by routine surveillance
Publication date: Available online 2 November 2017 Source:Spatial and Spatio-temporal Epidemiology Author(s): Aparna Lal, Jonathan Marshall, Jackie Benschop, Aleisha Brock, Simon Hales, Michael G Baker, Nigel P French Spatio-temporal disease patterns can provide clues to etiological pathways, but can be complex to model. Using a flexible Bayesian hierarchical framework, we identify previously undetected space-time clusters and environmental and socio-demographic risk factors for reported giardiasis and cryptosporidiosis at the New Zealand small area level. For giardiasis, there was no seasonal pattern in outbreak ...
Source: Spatial and Spatio-temporal Epidemiology - November 19, 2017 Category: Epidemiology Source Type: research

Spatial and population drivers of persistent cholera transmission in rural Bangladesh: Implications for vaccine and intervention targeting
Publication date: February 2018 Source:Spatial and Spatio-temporal Epidemiology, Volume 24 Author(s): Nushrat Nazia, Mohammad Ali, Md. Jakariya, Quamrun Nahar, Mohammad Yunus, Michael Emch We identify high risk clusters and measure their persistence in time and analyze spatial and population drivers of small area incidence over time. The geographically linked population and cholera surveillance data in Matlab, Bangladesh for a 10-year period were used. Individual level data were aggregated by local 250 × 250 m communities. A retrospective space-time scan statistic was applied to detect high risk clusters. Ge...
Source: Spatial and Spatio-temporal Epidemiology - November 19, 2017 Category: Epidemiology Source Type: research

Comparing the Geographic Distribution and Location Characteristics of HIV-Seropositive and HIV-Seronegative Individuals with a Diagnosis of Cancer Living in the Southeast US
Publication date: Available online 12 October 2017 Source:Spatial and Spatio-temporal Epidemiology Author(s): Benjamin D. Hallowell, Sara W. Robb, Kristina W. Kintziger As HIV-seropositive individuals live longer, they are more likely to acquire conditions seen in the general population. Excluding AIDS-defining malignancies, HIV-seropositive individuals are more likely to develop cancer than individuals in the general population. In order to better inform future screening and prevention efforts in this population, we compared the geographic distribution and location characteristics of HIV-seropositive and HIV-seronega...
Source: Spatial and Spatio-temporal Epidemiology - October 13, 2017 Category: Epidemiology Source Type: research