Global Health Epidemiology and Disease Control

A special issue of Epidemiologia (ISSN 2673-3986).

Deadline for manuscript submissions: 30 June 2024 | Viewed by 4545

Special Issue Editor

Special Issue Information

Dear Colleagues,

Global health deals with health issues and determinants that overcome national borders, aiming to improve health with a global perspective and achieve equity for all people. Over the last decades, growing challenges are emerging in this area, and understanding of the complexity of global health issues is crucial for strengthening health systems and informing policies at national and international levels.

This Special Issue of Epidemiologia focuses on the current state of the knowledge surrounding global health epidemiology, its challenges, and its opportunities for improvement. Epidemiologic research with a global focus and relevant studies are welcome. Possible examples include, but are not limited to, major determinants that influence individuals’ and populations’ health, factors that affect the burden of disease, interactions with pollutants and climate change, health assessments in low-resource settings, food and nutritional safety, health in mobile populations, and travel medicine.

We look forward to receiving your contributions, both qualitative and quantitative, on global health epidemiology.

Dr. Pietro Ferrara
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 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. Epidemiologia 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

  • global health
  • population health
  • disease control
  • real-world epidemiology
  • burden of disease
  • determinants of health
  • sustainable development goals

Published Papers (3 papers)

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13 pages, 302 KiB  
Article
Comprehensive Knowledge about HIV/AIDS among Women of Reproductive Age in India
by Aritro Bhattacharyya, Ritankar Chakraborty, Tapasya Raj, Bijaya Kumar Padhi, Jagdish Khubchandani, Prakasini Satapathy, Sarvesh Rustagi and Vijay Kumar Chattu
Epidemiologia 2023, 4(4), 492-504; https://doi.org/10.3390/epidemiologia4040041 - 16 Nov 2023
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Abstract
HIV/AIDS has been a major threat to global public health, with India ranking third when it comes to the global burden of people living with HIV, especially women. It is imperative to assess the level of knowledge women have about transmission and prevention [...] Read more.
HIV/AIDS has been a major threat to global public health, with India ranking third when it comes to the global burden of people living with HIV, especially women. It is imperative to assess the level of knowledge women have about transmission and prevention of this infection. This study sought to delineate the determinants of the comprehensive knowledge of HIV/AIDS among women in the reproductive age groups in India. Data from the fifth round of the National Family Health Survey conducted in India were analyzed. The sample included 95,541 women aged 15–49 years. Multilevel logistic regression was fitted with individual characteristics, household characteristics, and community characteristics to identify determinants of comprehensive knowledge on HIV/AIDS. Nearly a fourth (24.8%) of the women aged 15–49 in India who had ever heard of HIV had comprehensive knowledge of HIV/AIDS. Multilevel logistic regression showed that the likelihood of comprehensive knowledge of HIV/AIDS was higher among women aged 40–44 (AOR = 1.57) and 30–34 (AOR = 1.56). The likelihood of having comprehensive knowledge increased with the increase in the level of education. Women with secondary and higher levels of education were 1.9 times and 3.38 times more likely to have comprehensive knowledge, respectively, than those with no education. Household wealth, access to mass media, and having ever tested for HIV were also significant determinants of comprehensive knowledge of HIV/AIDS among women. The odds of having comprehensive knowledge about HIV/AIDS were higher for women with higher community wealth (AOR = 1.31), higher community education (AOR = 1.09), and higher community employment (AOR = 1.12). Factors at both the individual and community levels were shown to be indicators of comprehensive knowledge of HIV/AIDS. Policymakers and public health practitioners in India should come up with plans to close the information gaps about HIV/AIDS that exist among women and their demographic subgroups. Full article
(This article belongs to the Special Issue Global Health Epidemiology and Disease Control)
34 pages, 3110 KiB  
Article
Data-Driven Deep Learning Neural Networks for Predicting the Number of Individuals Infected by COVID-19 Omicron Variant
by Ebenezer O. Oluwasakin and Abdul Q. M. Khaliq
Epidemiologia 2023, 4(4), 420-453; https://doi.org/10.3390/epidemiologia4040037 - 20 Oct 2023
Cited by 3 | Viewed by 1808
Abstract
Infectious disease epidemics are challenging for medical and public health practitioners. They require prompt treatment, but it is challenging to recognize and define epidemics in real time. Knowing the prediction of an infectious disease epidemic can evaluate and prevent the disease’s impact. Mathematical [...] Read more.
Infectious disease epidemics are challenging for medical and public health practitioners. They require prompt treatment, but it is challenging to recognize and define epidemics in real time. Knowing the prediction of an infectious disease epidemic can evaluate and prevent the disease’s impact. Mathematical models of epidemics that work in real time are important tools for preventing disease, and data-driven deep learning enables practical algorithms for identifying parameters in mathematical models. In this paper, the SIR model was reduced to a logistic differential equation involving a constant parameter and a time-dependent function. The time-dependent function leads to constant, rational, and birational models. These models use several constant parameters from the available data to predict the time and number of people reported to be infected with the COVID-19 Omicron variant. Two out of these three models, rational and birational, provide accurate predictions for countries that practice strict mitigation measures, but fail to provide accurate predictions for countries that practice partial mitigation measures. Therefore, we introduce a time-series model based on neural networks to predict the time and number of people reported to be infected with the COVID-19 Omicron variant in a given country that practices both partial and strict mitigation measures. A logistics-informed neural network algorithm was also introduced. This algorithm takes as input the daily and cumulative number of people who are reported to be infected with the COVID-19 Omicron variant in the given country. The algorithm helps determine the analytical solution involving several constant parameters for each model from the available data. The accuracy of these models is demonstrated using error metrics on Omicron variant data for Portugal, Italy, and China. Our findings demonstrate that the constant model could not accurately predict the daily or cumulative infections of the COVID-19 Omicron variant in the observed country because of the long series of existing data of the epidemics. However, the rational and birational models accurately predicted cumulative infections in countries adopting strict mitigation measures, but they fell short in predicting the daily infections. Furthermore, both models performed poorly in countries with partial mitigation measures. Notably, the time-series model stood out for its versatility, effectively predicting both daily and cumulative infections in countries irrespective of the stringency of their mitigation measures. Full article
(This article belongs to the Special Issue Global Health Epidemiology and Disease Control)
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12 pages, 957 KiB  
Perspective
Myopia, Sodium Chloride, and Vitreous Fluid Imbalance: A Nutritional Epidemiology Perspective
by Ronald B. Brown
Epidemiologia 2024, 5(1), 29-40; https://doi.org/10.3390/epidemiologia5010003 - 29 Jan 2024
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Abstract
Theories of myopia etiology based on near work and lack of outdoor exposure have had inconsistent support and have not prevented the rising prevalence of global myopia. New scientific theories in the cause and prevention of myopia are needed. Myopia prevalence is low [...] Read more.
Theories of myopia etiology based on near work and lack of outdoor exposure have had inconsistent support and have not prevented the rising prevalence of global myopia. New scientific theories in the cause and prevention of myopia are needed. Myopia prevalence is low in native people consuming traditional diets lacking in sodium chloride, and nutritional epidemiological evidence supports the association of rising myopia prevalence with dietary sodium intake. East Asian populations have among the highest rates of myopia associated with high dietary sodium. Similar associations of sodium and rising myopia prevalence were observed in the United States in the late 20th century. The present perspective synthesizes nutritional epidemiology evidence with pathophysiological concepts and proposes that axial myopia occurs from increased fluid retention in the vitreous of the eye, induced by dietary sodium chloride intake. Salt disturbs ionic permeability of retinal membranes, increases the osmotic gradient flow of fluid into the vitreous, and stretches ocular tissue during axial elongation. Based on the present nutritional epidemiology evidence, experimental research should investigate the effect of sodium chloride as the cause of myopia, and clinical research should test a very low-salt diet in myopia correction and prevention. Full article
(This article belongs to the Special Issue Global Health Epidemiology and Disease Control)
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