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Measuring neighbourhood social dimensions using individual responses: an application of multilevel factor analysis and ecometrics
Publication date: Available online 2 December 2019Source: Spatial and Spatio-temporal EpidemiologyAuthor(s): Beatriz Caicedo-Velásquez, Kelvyn Jones (Source: Spatial and Spatio-temporal Epidemiology)
Source: Spatial and Spatio-temporal Epidemiology - December 4, 2019 Category: Epidemiology Source Type: research

Multivariate spatiotemporal modeling of drug- and alcohol-poisoning deaths in New York City, 2009–2014
Publication date: February 2020Source: Spatial and Spatio-temporal Epidemiology, Volume 32Author(s): Yusuf Ransome, S.V. Subramanian, Dustin T. Duncan, Daivid Vlahov, Joshua WarrenAbstractDrug- and alcohol-poisoning deaths remain current public health problems. Studies to date have typically focused on individual-level predictors of drug overdose deaths, and there remains a limited understanding of the spatiotemporal patterns and predictors of the joint outcomes. We use a hierarchical Bayesian spatiotemporal multivariate Poisson regression model on data from (N = 167) ZIP-codes between 2009 and 2014 in New York City to...
Source: Spatial and Spatio-temporal Epidemiology - November 28, 2019 Category: Epidemiology Source Type: research

Environmental factors affecting ecological niche of Coccidioides species and spatial dynamics of valley fever in the western United States
This study's objective was to estimate the impact of climate, soil, elevation and land cover on the Coccidioides species’ ecological niche. This research used maximum entropy ecological niche modeling based on disease case data from 2015 to 2016. Results found mean temperature of the driest quarter, and barren, shrub, and cultivated land covers influential in characterizing the niche. In addition to hotspots in central California and Arizona, the Columbia Plateau ecoregion of Washington and Oregon showed more favorable conditions for fungus presence than surrounding areas. The identification of influential spatial driver...
Source: Spatial and Spatio-temporal Epidemiology - November 20, 2019 Category: Epidemiology Source Type: research

Multivariate spatiotemporal modeling of drug- and alcohol-poisoning deaths in New York City, 2009-2014
Publication date: Available online 11 November 2019Source: Spatial and Spatio-temporal EpidemiologyAuthor(s): Yusuf Ransome, S.V. Subramanian, Dustin T. Duncan, Daivid Vlahov, Joshua WarrenAbstractDrug- and alcohol-poisoning deaths remain current public health problems. Studies to date have typically focused on individual-level predictors of drug overdose deaths, and there remains a limited understanding of the spatiotemporal patterns and predictors of the joint outcomes. We use a hierarchical Bayesian spatiotemporal multivariate Poisson regression model on data from (N=167) ZIP-codes between 2009 and 2014 in New York City...
Source: Spatial and Spatio-temporal Epidemiology - November 13, 2019 Category: Epidemiology Source Type: research

Editorial Board
Publication date: November 2019Source: Spatial and Spatio-temporal Epidemiology, Volume 31Author(s): (Source: Spatial and Spatio-temporal Epidemiology)
Source: Spatial and Spatio-temporal Epidemiology - November 1, 2019 Category: Epidemiology Source Type: research

Examining the role of a retail density ordinance in reducing concentration of tobacco retailers
Publication date: Available online 28 October 2019Source: Spatial and Spatio-temporal EpidemiologyAuthor(s): Priyanka Vyas, Hugh Sturrock, Pamela LingAbstractNeighborhood characteristics and the built environment are important determinants in shaping health inequalities. We evaluate the role of a retail density ordinance in reducing concentration of tobacco stores based on neighborhood characteristics and land use pattern in San Francisco. The study evaluated the spatial distribution of tobacco retailers before and after the ordinance to identify geographic pockets where the most significant reduction had occurred. A gener...
Source: Spatial and Spatio-temporal Epidemiology - October 29, 2019 Category: Epidemiology Source Type: research

Application of kernel smoothing to estimate the spatio-temporal variation in risk of STEC O157 in England
Publication date: Available online 24 October 2019Source: Spatial and Spatio-temporal EpidemiologyAuthor(s): Richard Elson, Tilman M. Davies, Claire Jenkins, Roberto Vivancos, Sarah J. O'Brien, Iain R. Lake (Source: Spatial and Spatio-temporal Epidemiology)
Source: Spatial and Spatio-temporal Epidemiology - October 26, 2019 Category: Epidemiology Source Type: research

Herd and environmental determinants of reproductive performance in Swedish dairy herds, 2001–2009
Publication date: November 2019Source: Spatial and Spatio-temporal Epidemiology, Volume 31Author(s): M.A. Stevenson, E. Löf, M. Söderström, H. Gustafsson, U. EmanuelsonAbstractThis was a retrospective cohort study of Swedish dairy herds. Summary measures of production and reproductive performance, details of soil, moss mineral concentrations, and temperature and rainfall measurements at each herd location were available for the period September 2001 to August 2009. A Bayesian mixed-effects regression model including spatial and non-spatial heterogeneity terms was developed to quantify associations between hypothesised e...
Source: Spatial and Spatio-temporal Epidemiology - September 14, 2019 Category: Epidemiology Source Type: research

Comparison of different software implementations for spatial disease mapping
Publication date: Available online 9 August 2019Source: Spatial and Spatio-temporal EpidemiologyAuthor(s): M. Vranckx, T. Neyens, C. FaesAbstractDisease mapping is a scientific field that aims to understand and predict disease risk based on counts of observed cases within small regions of a study area of interest. Hierarchical model-based approaches that borrow information from neighbouring areas via conditional autoregressive (CAR) random effects on the local disease rates have gained a lot of popularity, thanks to the readily implemented Markov chain Monte Carlo methods. Nowadays, many software implementations to model r...
Source: Spatial and Spatio-temporal Epidemiology - August 23, 2019 Category: Epidemiology Source Type: research

Spatio-Temporal Analysis of Differences in Campylobacteriosis Incidence between Urban and Rural Areas in the Southern District Health Board, New Zealand
The objective of this paper is to investigate differences in campylobacteriosis incidence between urban and rural areas in the Southern District Health Board of New Zealand between 2000-2015. The data were analysed using a Bayesian change-point model to evaluate how campylobacteriosis incidence changed over time and to see whether the dynamics differed between rural and urban areas. A conditional auto regressive error term was introduced to account for any spatial effects. The results of our analysis showed that campylobacteriosis incidence increased between 2000-2005, decreased between 2006-2008 then stabilised from 2009 ...
Source: Spatial and Spatio-temporal Epidemiology - August 17, 2019 Category: Epidemiology Source Type: research

Editorial Board
Publication date: August 2019Source: Spatial and Spatio-temporal Epidemiology, Volume 30Author(s): (Source: Spatial and Spatio-temporal Epidemiology)
Source: Spatial and Spatio-temporal Epidemiology - August 15, 2019 Category: Epidemiology Source Type: research

Bayesian Hierarchical Spatial Models: Implementing the Besag York Mollié Model in Stan
This report presents a new implementation of the Besag-York-Mollié (BYM) model in Stan, a probabilistic programming platform which does full Bayesian inference using Hamiltonian Monte Carlo (HMC). We review the spatial auto-correlation models used for areal data and disease risk mapping, and describe the corresponding Stan implementations. We also present a case study using Stan to fit a BYM model for motor vehicle crashes injuring school-age pedestrians in New York City from 2005-2014 localized to census tracts. Stan efficiently fit our multivariable BYM model having a large number of observations (n=2095 census tracts) ...
Source: Spatial and Spatio-temporal Epidemiology - August 13, 2019 Category: Epidemiology Source Type: research

Model-based small area estimation at two scales using Moran's spatial filtering
Publication date: Available online 8 August 2019Source: Spatial and Spatio-temporal EpidemiologyAuthor(s): Phuong N. Truong, Alfred SteinAbstractIn spatial epidemiology and public health studies, including covariates in small area estimation of spatial binary data remains a challenge. In this paper, Moran's spatial filtering is proposed to model two-scale spatial binary data. Two models are developed: the first uses deterministic estimation of the sample size at small areal level; the second generates a random sample size using the multinomial distribution. The models were applied to estimate the underweight among children...
Source: Spatial and Spatio-temporal Epidemiology - August 10, 2019 Category: Epidemiology Source Type: research

Comparison of different software implementations for spatial disease mapping.
Publication date: Available online 9 August 2019Source: Spatial and Spatio-temporal EpidemiologyAuthor(s): Vranckx M., Neyens T., Faes C.AbstractDisease mapping is a scientific field that aims to understand and predict disease risk based on counts of observed cases within small regions of a study area of interest. Hierarchical model-based approaches that borrow information from neighbouring areas via conditional autoregressive (CAR) random effects on the local disease rates have gained a lot of popularity, thanks to the readily implemented Markov chain Monte Carlo methods. Nowadays, many software implementations to model r...
Source: Spatial and Spatio-temporal Epidemiology - August 10, 2019 Category: Epidemiology Source Type: research

Associations of neighbourhood safety with leisure-time walking and cycling in population subgroups: the HELIUS study
We examined the association of neighbourhood safety with leisure-time walking and cycling in the population at large, as well as in some subgroups in terms of sex, age, ethnicity and socio-economic position. We used data of 19,914 participants (18-70 years) from a study in Amsterdam, the Netherlands. Leisure-time walking and cycling in minutes/week were assessed with standard questionnaire. Geographic Information System techniques were used to examine neighbourhood safety (range=1-10). Multilevel linear regression analyses showed positive associations between safety and walking (B=7.9, 95% CI=-6.2-21.9) and cycling (B=14.8...
Source: Spatial and Spatio-temporal Epidemiology - August 8, 2019 Category: Epidemiology Source Type: research