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Advances in Spatial and Temporal Analysis of Respiratory Tract Infection Epidemics

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Public Health Statistics and Risk Assessment".

Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 4927

Special Issue Editors


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Guest Editor
Department of Geography, University of Cincinnati, Cincinnati, OH 45221,USA
Interests: spatial epidemiology; disease mapping; mathematical modeling; global health
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
1. Infectious Disease Epidemiology Group, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation - Education City, P.O. Box 24144 Doha, Qatar
2. Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY 14850, USA
Interests: epidemiology; risk factors; mathematical modeling; data analysis; scientific computing

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Guest Editor
Urban Health Collaborative, Dornsife School of Public Heath, Drexel University, Philadelphia, PA 19104,USA
Interests: health impacts of built environments; spatial scale effects; spatial analysis

Special Issue Information

Dear Colleagues,

Major epidemics, including some that qualify as pandemics, including severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), influenza A, and the novel COVID-19, affect the respiratory tract in humans. These epidemics remain as one of the top global causes of death, and the emergence of novel diseases continues to be a major concern. Geographic analysis of infectious diseases may serve to shed important insights on the etiology and transmission dynamics of these diseases. The identification of spatial and temporal factors associated with disease incidence and dispersion may identify target risk factors or environmental conditions that can be used for the development and implementation of efficient and cost-effective intervention programs, including vaccines. Spatial and temporal statistical and mathematical models may be of great value for the design of geographically targeted program interventions. The focus of this Special Issue is to present novelties in the domain of spatial and temporal analysis that are relevant to modeling respiratory tract infections, including COVID-19.

This Special Issue is calling for high-quality original research articles and reviews on subjects including, but not limited to:

Developing and evaluating novel methods for using spatial analysis or geographical linkage to measure health-relevant population exposures and disease outcomes.

Applications of epidemiologic research using geospatial data or methods that exemplify close integration of theory, spatial methods, and inference to study the epidemiology of respiratory tract infections.

Implementation of spatial and temporal statistical models to identify, quantify and predict variables of interest in the epidemiology of respiratory tract infections.

Identification of spatial and temporal trends.

Identification of spatial and temporal clustering of respiratory tract infections.

Prediction methods to reveal correlation and patterns of respiratory tract infection outbreaks.

Spatial composite indicators for monitoring the spread of respiratory tract infections.

Dr. Diego Fernando Cuadros
Dr. Susanne Awad
Dr. Jingjing Li
Guest Editors

Manuscript Submission Information

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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. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly 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 2500 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

  • respiratory tract infections
  • spatial analysis
  • spatial epidemiology
  • mathematical modeling
  • disease outbreaks
  • spatial clustering
  • spatial risk factors

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Published Papers (1 paper)

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Research

13 pages, 1762 KiB  
Article
Identification of Vulnerable Populations and Areas at Higher Risk of COVID-19-Related Mortality during the Early Stage of the Epidemic in the United States
by Esteban Correa-Agudelo, Tesfaye B. Mersha, Adam J. Branscum, Neil J. MacKinnon and Diego F. Cuadros
Int. J. Environ. Res. Public Health 2021, 18(8), 4021; https://doi.org/10.3390/ijerph18084021 - 12 Apr 2021
Cited by 23 | Viewed by 4231
Abstract
We characterized vulnerable populations located in areas at higher risk of COVID-19-related mortality and low critical healthcare capacity during the early stage of the epidemic in the United States. We analyze data obtained from a Johns Hopkins University COVID-19 database to assess the [...] Read more.
We characterized vulnerable populations located in areas at higher risk of COVID-19-related mortality and low critical healthcare capacity during the early stage of the epidemic in the United States. We analyze data obtained from a Johns Hopkins University COVID-19 database to assess the county-level spatial variation of COVID-19-related mortality risk during the early stage of the epidemic in relation to health determinants and health infrastructure. Overall, we identified highly populated and polluted areas, regional air hub areas, race minorities (non-white population), and Hispanic or Latino population with an increased risk of COVID-19-related death during the first phase of the epidemic. The 10 highest COVID-19 mortality risk areas in highly populated counties had on average a lower proportion of white population (48.0%) and higher proportions of black population (18.7%) and other races (33.3%) compared to the national averages of 83.0%, 9.1%, and 7.9%, respectively. The Hispanic and Latino population proportion was higher in these 10 counties (29.3%, compared to the national average of 9.3%). Counties with major air hubs had a 31% increase in mortality risk compared to counties with no airport connectivity. Sixty-eight percent of the counties with high COVID-19-related mortality risk also had lower critical care capacity than the national average. The disparity in health and environmental risk factors might have exacerbated the COVID-19-related mortality risk in vulnerable groups during the early stage of the epidemic. Full article
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