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Global Health and Epidemiology: Methodological Innovations, Applications, and Perspectives
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Global Health and Epidemiology: Methodological Innovations, Applications, and Perspectives

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

Deadline for manuscript submissions: closed (4 April 2023) | Viewed by 5684

Special Issue Editors

Dr. Ali Arab

E-Mail Website
Guest Editor
Department of Mathematics and Statistics, Georgetown University, 305 St. Mary's37th and O Streets, N.W., Washington, DC 20057, USA
Interests: statistical modeling for epidemiological and environmental applications; spatial and spatio-temporal models; hierarchical Bayesian models; modeling the impact of environmental factors on spread of infectious diseases and in particular; vector-borne diseases
Dr. David C. Wheeler

E-Mail Website
Guest Editor
Department of Biostatistics, School of Medicine, Virginia Commonwealth University, 830 East Main Street, PO Box 980032, Richmond, VA 23298, USA
Interests: spatial epidemiology; environmental epidemiology; cancer epidemiology; spatial statistics; machine learning; geographic information systems
Dr. Erik Nelson

E-Mail Website
Guest Editor
Department of Epidemiology and Biostatistics, IU School of Public Health-Bloomington, Indiana University-Bloomington, 1025 E. Seventh Street Room C033, Bloomington, IN 47405, USA
Interests: Spatial epidemiology; Bayesian hierarchical modeling; sexual and reproductive health; environmental pollution; data visualizatio
Prof. Dr. James Stamey

E-Mail Website
Guest Editor
Department of Statistical Science, Baylor University, Department of Statistical Science, Baylor University, 97140 One Bear Place, Waco, TX 76798, USA
Interests: Bayesian modeling; measurement error and misclassification; sample size determination
Dr. Marie Ozanne

E-Mail Website
Guest Editor
Department of Mathematics & Statistics, Mount Holyoke College, 50 College St., South Hadley, MA 01075, USA
Interests: Bayesian hierarchical modeling; compartmental models for infectious diseases with a focus on vector-borne and zoonotic diseases; longitudinal modeling; statistical modeling for health disparities
Dr. Mark J. Meyer

E-Mail Website
Guest Editor
Department of Mathematics & Statistics, Georgetown University, Washington, D.C. 20057, USA
Interests: Functional data analysis; wavelet and spline-based regression; categorical data analysis; longitudinal data analysis; Bayesian statistics; environmental health; and global health science and security

Special Issue Information

Dear Colleagues,

The main goal of the current Special Issue is to advance mathematical and statistical methodological innovations for global health and epidemiology. We strive to create a space to cultivate and stimulate creativity, reflection, and innovation. We expect this Special Issue to provide opportunities for scholarly exchange of innovative ideas as well as new perspectives and reflections on ideas and concepts that, in and of themselves, may not be new to some fields (e.g., statistics or economics) but are unknown or underappreciated in public health research. We also strive to provide an environment for articles that may be considered to be too simple for the theoretical journals and, yet, too complex for the applied journals. To this effect, we intend to make editorial decisions that will reflect the soundness of the argument rather than the implications of their conclusions. In addition, elegant mathematical arguments and logical interpretations that challenge the current methodology are highly encouraged. We welcome new research papers, reviews, and case reports. We will accept manuscripts from different disciplines including global health, epidemiology, health disparities including but not limited to disparities in access to healthcare, exposure assessment, intervention studies, risk, and health impact assessment.

Dr. Ali Arab
Dr. David C. Wheeler
Dr. Erik Nelson
Prof. Dr. James Stamey
Dr. Marie Ozanne
Dr. Mark J. Meyer
Guest Editors

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 submissions that pass pre-check are 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. 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

  • infectious diseases
  • public health
  • emerging epidemics
  • surveillance
  • health disparities
  • environmental exposures
  • social determinants of health
  • One Health
  • modeling
  • spatial modeling
  • longitudinal modeling

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

15 pages, 702 KiB  
Article
A Bayesian Hierarchical Spatial Model to Correct for Misreporting in Count Data: Application to State-Level COVID-19 Data in the United States
by Jinjie Chen, Joon Jin Song and James D. Stamey
Int. J. Environ. Res. Public Health 2022, 19(6), 3327; https://doi.org/10.3390/ijerph19063327 - 11 Mar 2022
Cited by 6 | Viewed by 2498
Abstract
The COVID-19 pandemic that began at the end of 2019 has caused hundreds of millions of infections and millions of deaths worldwide. COVID-19 posed a threat to human health and profoundly impacted the global economy and people’s lifestyles. The United States is one [...] Read more.
The COVID-19 pandemic that began at the end of 2019 has caused hundreds of millions of infections and millions of deaths worldwide. COVID-19 posed a threat to human health and profoundly impacted the global economy and people’s lifestyles. The United States is one of the countries severely affected by the disease. Evidence shows that the spread of COVID-19 was significantly underestimated in the early stages, which prevented governments from adopting effective interventions promptly to curb the spread of the disease. This paper adopts a Bayesian hierarchical model to study the under-reporting of COVID-19 at the state level in the United States as of the end of April 2020. The model examines the effects of different covariates on the under-reporting and accurate incidence rates and considers spatial dependency. In addition to under-reporting (false negatives), we also explore the impact of over-reporting (false positives). Adjusting for misclassification requires adding additional parameters that are not directly identified by the observed data. Informative priors are required. We discuss prior elicitation and include R functions that convert expert information into the appropriate prior distribution. Full article
(This article belongs to the Special Issue Global Health and Epidemiology: Methodological Innovations, Applications, and Perspectives)
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26 pages, 34903 KiB  
Article
On the Supervision of a Saturated SIR Epidemic Model with Four Joint Control Actions for a Drastic Reduction in the Infection and the Susceptibility through Time
by Manuel De la Sen, Asier Ibeas and Santiago Alonso-Quesada
Int. J. Environ. Res. Public Health 2022, 19(3), 1512; https://doi.org/10.3390/ijerph19031512 - 28 Jan 2022
Cited by 2 | Viewed by 2271
Abstract
This paper presents and studies a new epidemic SIR (Susceptible–Infectious–Recovered) model with susceptible recruitment and eventual joint vaccination efforts for both newborn and susceptible individuals. Furthermore, saturation effects in the infection incidence terms are eventually assumed for both the infectious and the susceptible [...] Read more.
This paper presents and studies a new epidemic SIR (Susceptible–Infectious–Recovered) model with susceptible recruitment and eventual joint vaccination efforts for both newborn and susceptible individuals. Furthermore, saturation effects in the infection incidence terms are eventually assumed for both the infectious and the susceptible subpopulations. The vaccination action on newborn individuals is assumed to be applied to a fraction of them while that on the susceptible general population is of linear feedback type reinforced with impulsive vaccination actions (in practice, very strong and massive vaccination controls) at certain time points, based on information on the current levels of the susceptible subpopulation. Apart from the above vaccination controls, it is also assumed that the average of contagion contacts can be controlled via intervention measures, such as confinements or isolation measures, social distance rules, use of masks, mobility constraints, etc. The main objectives of the paper are the achievement of a strictly decreasing infection for all time periods and that of the susceptible individuals over the initial period if they exceed the disease-free equilibrium value. The monitoring mechanism is the combined activation of intervention measures to reduce the contagion contacts together with the impulsive vaccination to reduce susceptibility. The susceptibility and recovery levels of the disease-free equilibrium point are suitably prefixed by the design of the regular feedback vaccination on the susceptible subpopulation. Full article
(This article belongs to the Special Issue Global Health and Epidemiology: Methodological Innovations, Applications, and Perspectives)
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