Special Issue "Contemporary Themes in Geographic Epidemiology"

A special issue of J (ISSN 2571-8800). This special issue belongs to the section "Public Health & Healthcare".

Deadline for manuscript submissions: 30 September 2021.

Special Issue Editor

Prof. Dr. Peter Congdon
E-Mail Website
Guest Editor
Department of Geography and Life Sciences Institute, Queen Mary University of London, Mile End Road, London E1 4NS, UK
Interests: chronic disease epidemiology; urban environments and health; spatial epidemiology; health geography; mental ill health; suicidology
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Many current global issues and trends illustrate the contemporary relevance of geographic epidemiology. These include the COVID-19 epidemic and the impact of geographic comparisons of incidence and mortality on policy choices. Effects on health of climate change, pollution, and environmental degradation have been highlighted by international agencies such as the United Nations. Neighbourhood contrasts in healthy life expectancy and access to healthy environments have major importance in achieving spatial health equity. Modern health crises such as the growth of obesity and the drug overdose epidemic also have a clear geospatial context. Geographic epidemiology is also affected by new ways of collecting spatial data and by the availability of big data.

This Special Issue will publish applications and methods papers; critical conceptual review papers; and policy applications using geographic epidemiology. We welcome contributions that highlight the relevance and application of geographic epidemiology to contemporary health problems and to understanding the factors that influence them. Policy applications are relevant, as also are perspectives on, and applications of, the widening range of available analytic methods and data sources. Both international comparisons and lower-scale locality studies are suitable, as are studies of both chronic and infectious diseases. Reviews of conceptual issues such as the context–composition distinction, and the modifiable areal unit problem (in health applications), are also suitable.

Prof. Dr. Peter Congdon
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. J is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • spatial patterns of disease
  • health inequalities
  • geospatial issues in contemporary health crises
  • spatiotemporal models
  • spatial patterns in COVID-19
  • health GIS
  • disease mapping
  • place effects
  • spatial scale for health analysis.

Published Papers (2 papers)

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Research

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Article
COVID-19 Mortality in English Neighborhoods: The Relative Role of Socioeconomic and Environmental Factors
J 2021, 4(2), 131-146; https://0-doi-org.brum.beds.ac.uk/10.3390/j4020011 - 14 May 2021
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Abstract
Factors underlying neighborhood variation in COVID-19 mortality are important to assess in order to prioritize resourcing and policy intervention. As well as characteristics of area populations, such as health status and ethnic mix, it is important to assess the role of more specifically [...] Read more.
Factors underlying neighborhood variation in COVID-19 mortality are important to assess in order to prioritize resourcing and policy intervention. As well as characteristics of area populations, such as health status and ethnic mix, it is important to assess the role of more specifically environmental variables (e.g., air quality, green space access). The analysis of this study focuses on neighborhood mortality variations during the first wave of the COVID-19 epidemic in England against a range of postulated area risk factors, both socio-demographic and environmental. We assess mortality gradients across levels of each risk factor and use regression methods to control for multicollinearity and spatially correlated unobserved risks. An analysis of spatial clustering is based on relative mortality risks estimated from the regression. We find mortality gradients in most risk factors showing appreciable differences in COVID mortality risk between English neighborhoods. A regression analysis shows that after allowing for health deprivation, ethnic mix, and ethnic segregation, environment (especially air quality) is an important influence on COVID mortality. Hence, environmental influences on COVID mortality risk in the UK first wave are substantial, after allowing for socio-demographic factors. Spatial clustering of high mortality shows a pronounced metropolitan-rural contrast, reflecting especially ethnic composition and air quality. Full article
(This article belongs to the Special Issue Contemporary Themes in Geographic Epidemiology)
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Review

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Review
Estimating Health over Space and Time: A Review of Spatial Microsimulation Applied to Public Health
J 2021, 4(2), 182-192; https://0-doi-org.brum.beds.ac.uk/10.3390/j4020015 - 09 Jun 2021
Viewed by 518
Abstract
There is an ongoing demand for data on population health, for reasons of resource allocation, future planning and crucially to address inequalities in health between people and between populations. Although there are regular sources of data at coarse spatial scales, such as countries [...] Read more.
There is an ongoing demand for data on population health, for reasons of resource allocation, future planning and crucially to address inequalities in health between people and between populations. Although there are regular sources of data at coarse spatial scales, such as countries or large sub-national units such as states, there is often a lack of good quality health data at the local level. One method to develop reliable estimates of population health outcomes is spatial microsimulation, an approach that has its roots in economic studies. Here, we share a review of this method for estimating health in populations, explaining the different approaches available and examples where the method is applied successfully for creating both static and dynamic populations. Recent notable advances in the method that allow uncertainty to be represented are highlighted, along with the evolving approaches to validation that are an ongoing challenge in small-area estimation. The summary serves as a primer for academics new to the area of research as well as an overview for non-academic researchers who consider using these models for policy evaluations. Full article
(This article belongs to the Special Issue Contemporary Themes in Geographic Epidemiology)
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