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Spatial and Spatio-temporal Epidemiology

S Shekhar, E-H Yoo, S A Ahmed, R Haining, S Kadannolly
Spatial decision support systems have already proved their value in helping to reduce infectious diseases but to be effective they need to be designed to reflect local circumstances and local data availability. We report the first stage of a project to develop a spatial decision support system for infectious diseases for Karnataka State in India. The focus of this paper is on malaria incidence and we draw on small area data on new cases of malaria analysed in two-monthly time intervals over the period February 2012 to January 2016 for Kalaburagi taluk, a small area in Karnataka...
February 2017: Spatial and Spatio-temporal Epidemiology
Brian Hendricks, Miguella Mark-Carew
Lyme disease is the most commonly reported vectorborne disease in the United States. The objective of our study was to identify patterns of Lyme disease reporting after multistate inclusion to mitigate potential border effects. County-level human Lyme disease surveillance data were obtained from Kentucky, Maryland, Ohio, Pennsylvania, Virginia, and West Virginia state health departments. Rate smoothing and Local Moran's I was performed to identify clusters of reporting activity and identify spatial outliers...
February 2017: Spatial and Spatio-temporal Epidemiology
Chandrasekaran Kandhasamy, Kaushik Ghosh
Indian states are currently classified into HIV-risk categories based on the observed prevalence counts, percentage of infected attendees in antenatal clinics, and percentage of infected high-risk individuals. This method, however, does not account for the spatial dependence among the states nor does it provide any measure of statistical uncertainty. We provide an alternative model-based approach to address these issues. Our method uses Poisson log-normal models having various conditional autoregressive structures with neighborhood-based and distance-based weight matrices and incorporates all available covariate information...
February 2017: Spatial and Spatio-temporal Epidemiology
Holly Thurston, Bridget Freisthler, Janice Bell, Daniel Tancredi, Patrick S Romano, Sheridan Miyamoto, Jill G Joseph
This descriptive study utilized Bernoulli and Poisson spatial scan statistical models in SatScan v.9.4 to examine the distribution in space and time of residence of maltreatment cases-operationalized as families with serious maltreatment (resulting in death or hospitalization) of children under 6 years-for the presence of clusters ("hot spots"). In the Poisson model, a population dataset of serious maltreatment cases were non-randomly dispersed in four major areas, with these "hot spots" moving over time and space...
February 2017: Spatial and Spatio-temporal Epidemiology
Annette Kjær Ersbøll, Ulf Strömberg
No abstract text is available yet for this article.
November 2016: Spatial and Spatio-temporal Epidemiology
Daniel Hogg, Simon Kingham, Thomas M Wilson, Michael Ardagh
This article explores the spatio-temporal variation of mood and anxiety treatments in the context of a severe earthquake sequence. The aim was to examine a possible earthquake exposure effect, identify populations at risk and areas with particularly large mood and anxiety treatment rate increases or decreases in the affected Christchurch urban area. A significantly stronger increase of mood and anxiety treatments among residents in Christchurch compared to others in New Zealand have been found, as well as children and elderly identified as especially vulnerable...
November 2016: Spatial and Spatio-temporal Epidemiology
Silvia Bermedo-Carrasco, Cheryl Waldner, Juan Nicolás Peña-Sánchez, Michael Szafron
We examined spatial variations in the frequencies of women who had not heard of human papillomavirus vaccination (NHrd-Vac) and who had not had Pap testing (NHd-Pap) among Colombian administrative divisions (departments), before and after considering differences in socio-demographic factors. Following global and local tests for clustering, Bayesian Poisson hierarchical models identified department factors associated with NHrd-Vac and NHd-Pap, as well as the extent of the spatially structured and unstructured heterogeneity...
November 2016: Spatial and Spatio-temporal Epidemiology
Timothée Vergne, Fedor Korennoy, Lisa Combelles, Andrey Gogin, Dirk U Pfeiffer
African swine fever (ASF) is a viral disease of swine that has been present in the Russian Federation since 2007. Counts of ASF outbreaks reported in the Southern regions of the country (2007-2014) were aggregated to a grid of hexagons, and a zero-inflated Poisson model accounting for spatial dependence between hexagons was used to identify factors associated with the presence of ASF outbreaks and factors associated with the number of ASF reports in affected hexagons. Increasing density of pigs raised on low biosecurity farms was found to be positively associated with the probability of occurrence of at least one ASF outbreak in a hexagon and with the average number of reported ASF outbreaks amongst affected hexagons...
November 2016: Spatial and Spatio-temporal Epidemiology
Annette Kjær Ersbøll, Thora Majlund Kjærulff, Kristine Bihrmann, Jasper Schipperijn, Gunnar Gislason, Mogens Lytken Larsen
BACKGROUND: Geographical variation in incidence and mortality of acute myocardial infarction (AMI) is present in Denmark. We aimed at examining the association between contact to a general practitioner (GP) the year before AMI and a fatal outcome of AMI. METHODS: Register-based data and individual-level addresses including 69,608 individuals with AMI in 2006-2011. A Bayesian hierarchical logistic regression model was used to examine the association. RESULTS: A fatal outcome of AMI was seen among 12...
November 2016: Spatial and Spatio-temporal Epidemiology
Thora Majlund Kjærulff, Annette Kjær Ersbøll, Gunnar Gislason, Jasper Schipperijn
OBJECTIVES: To examine the geographical patterns in AMI and characterize individual and neighborhood sociodemographic factors for persons living inside versus outside AMI clusters. METHODS: The study population comprised 3,515,670 adults out of whom 74,126 persons experienced an incident AMI (2005-2011). Kernel density estimation and global and local clustering methods were used to examine the geographical patterns in AMI. Median differences and frequency distributions of sociodemographic factors were calculated for persons living inside versus outside AMI clusters...
November 2016: Spatial and Spatio-temporal Epidemiology
Michela Cameletti, Francesco Finazzi
In this paper, the Italian hospitalization database provided by the Ministry of Health is analyzed in terms of the temporal and spatial patterns of the hospitalization rates. The database covers the period 2010-2012 and the rates are evaluated for 110 Italian provinces and 18 diagnosis groups as defined by the ICD-9 classification. The analysis is based on a novel model-based clustering approach which enables clustering of spatially registered time series with respect to latent temporal patterns. The clustering result is analyzed to study the spatial distribution of the latent temporal patterns and their trend in order to identify possible critical areas in terms of increasing rates...
November 2016: Spatial and Spatio-temporal Epidemiology
Areti Boulieri, Anna Hansell, Marta Blangiardo
This paper investigates trends in asthma and COPD by using multiple data sources to help understanding the relationships between disease prevalence, morbidity and mortality. GP drug prescriptions, hospital admissions, and deaths are analysed at clinical commissioning group (CCG) level in England from August 2010 to March 2011. A Bayesian hierarchical model is used for the analysis, which takes into account the complex space and time dependencies of asthma and COPD, while it is also able to detect unusual areas...
November 2016: Spatial and Spatio-temporal Epidemiology
Ulf Strömberg, Anders Holmén, Stefan Peterson
Screening strategies need to consider differences in late-stage disease detection linked to socio-demographic and geographic factors. We specifically addressed disparity in melanoma stage at diagnosis linked to residential municipality, gender and marital status within the middle- and old-age population of southern and western Sweden. Population-based registers were used to identify the melanoma cases diagnosed in 2004-2013 (n=7,417). Disease mapping for each population group based on gender and marital status showed marked spatial disparities in melanoma incidences and the overall patterns differed by stage at diagnosis...
November 2016: Spatial and Spatio-temporal Epidemiology
Emanuele Giorgi, Katharina Kreppel, Peter J Diggle, Cyril Caminade, Maherisoa Ratsitorahina, Minoarisoa Rajerison, Matthew Baylis
Plague is an infectious disease caused by the bacterium Yersinia pestis, which, during the fourteenth century, caused the deaths of an estimated 75-200 million people in Europe. Plague epidemics still occur in Africa, Asia and South America. Madagascar is today one of the most endemic countries, reporting nearly one third of the human cases worldwide from 2004 to 2009. The persistence of plague in Madagascar is associated with environmental and climatic conditions. In this paper we present a case study of the spatio-temporal analysis of plague incidence in Madagascar from 1980 to 2007...
November 2016: Spatial and Spatio-temporal Epidemiology
Loni Philip Tabb, Lance Ballester, Tony H Grubesic
Alcohol-related violence is a well-documented public health concern, where various individual and community-level factors contribute to this relationship. The purpose of this study is to examine the impact of a significant policy change at the local level, which privatized liquor sales and distribution. Specifically, we explored the relationship between alcohol and violence in Seattle, WA, 2010-2013, via hierarchical spatio-temporal disease mapping models. To measure and map this complex spatio-temporal relationship at the census block group level (n=567), we examined a variety of models using integrated nested Laplace approximations and used the deviance information criterion to gauge model complexity and fit...
November 2016: Spatial and Spatio-temporal Epidemiology
Susanna M Cramb, Kerrie L Mengersen, Peter D Baade
Despite improvements in cancer survival across many developed countries, it is unclear how survival is changing over time in small areas. This study investigated changes in breast and colorectal cancer survival across 478 areas over 11 years (2001-2011), and the influence of early diagnosis on changes. Queensland Cancer Registry data were analysed using an introduced Bayesian spatio-temporal flexible parametric relative survival model. All areas showed survival improvements between 2001-2003 and 2008-2011. The median absolute 5-year survival improvement for localised breast cancer was small (1...
November 2016: Spatial and Spatio-temporal Epidemiology
Alexander Hohl, Eric Delmelle, Wenwu Tang, Irene Casas
Infectious diseases have complex transmission cycles, and effective public health responses require the ability to monitor outbreaks in a timely manner. Space-time statistics facilitate the discovery of disease dynamics including rate of spread and seasonal cyclic patterns, but are computationally demanding, especially for datasets of increasing size, diversity and availability. High-performance computing reduces the effort required to identify these patterns, however heterogeneity in the data must be accounted for...
November 2016: Spatial and Spatio-temporal Epidemiology
Toni Patama, Eero Pukkala
Lay people and health professionals are increasingly interested in health issues in their region. The high-quality cancer and population registries in the Nordic countries allow fine spatial and temporal visualization of mapped data. This article describes - with real-data examples - a mapping method developed in Finland for such visualization but also utilized for data from numerous other countries and non-cancer outcomes. The Finnish smoothing is based on weighting small-area specific observations with population sizes and distance without losing the interpretability of the values...
November 2016: Spatial and Spatio-temporal Epidemiology
Duncan Lee, Sujit Sahu, Gavin Shaddick
No abstract text is available yet for this article.
August 2016: Spatial and Spatio-temporal Epidemiology
Ravi Maheswaran
Air pollution is being increasingly recognized as a significant risk factor for stroke. There are numerous sources of air pollution including industry, road transport and domestic use of biomass and solid fuels. Early reports of the association between air pollution and stroke come from studies investigating health effects of severe pollution episodes. Several daily time series and case-crossover studies have reported associations with stroke. There is also evidence linking chronic air pollution exposure with stroke and with reduced survival after stroke...
August 2016: Spatial and Spatio-temporal Epidemiology
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