Special Issue "Predictive Models That Can Impact Public Health"

Special Issue Editor

Prof. Dr. Antonio Palazón-Bru
E-Mail Website
Guest Editor
Department of Clinical Medicine, Miguel Hernández University, 03005 San Juan de Alicante, Spain
Interests: predictive models; systematic reviews; meta-analysis; screening; cardiovascular diseases; cancer

Special Issue Information

Dear Colleagues,

We are organizing a Special Issue on the use of predictive models to benefit public health for the International Journal of Environmental Research and Public Health. This journal is peer-reviewed and publishes articles in the interdisciplinary area of environmental health sciences and public health. Predictive models estimate probability of an event through the use of information on certain risk factors for that event. They are being increasingly used to assist healthcare professionals in making decisions that are more likely to avoid a specific event, with the consequent positive impact on public health. This Special Issue is focused on the construction and validation of predictive models with original data. Some possible topics are listed below, though other topics are also welcome:

  • COVID-19 research
  • Cardiovascular diseases and their risk factors
  • Infectious diseases
  • Environmental research
  • Screening tests
  • Hospital emergencies
  • Health promotion
  • Forecasting

Prof. Dr. Antonio Palazón-Bru
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. International Journal of Environmental Research and Public Health is an international peer-reviewed open access semimonthly 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 2300 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

  • predictive models
  • forecasting
  • public health
  • environment
  • screening
  • prognosis
  • risk assessment

Published Papers (2 papers)

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Research

Article
Importance of Geospatial Heterogeneity in Chronic Disease Burden for Policy Planning in an Urban Setting Using a Case Study of Singapore
Int. J. Environ. Res. Public Health 2021, 18(9), 4406; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph18094406 - 21 Apr 2021
Viewed by 570
Abstract
Chronic disease burdens continue to rise in highly dense urban environments where clustering of type II diabetes mellitus, acute myocardial infarction, stroke, or any combination of these three conditions is occurring. Many individuals suffering from these conditions will require longer-term care and access [...] Read more.
Chronic disease burdens continue to rise in highly dense urban environments where clustering of type II diabetes mellitus, acute myocardial infarction, stroke, or any combination of these three conditions is occurring. Many individuals suffering from these conditions will require longer-term care and access to clinics which specialize in managing their illness. With Singapore as a case study, we utilized census data in an agent-modeling approach at an individual level to estimate prevalence in 2020 and found high-risk clusters with >14,000 type II diabetes mellitus cases and 2000–2500 estimated stroke cases. For comorbidities, 10% of those with type II diabetes mellitus had a past acute myocardial infarction episode, while 6% had a past stroke. The western region of Singapore had the highest number of high-risk individuals at 173,000 with at least one chronic condition, followed by the east at 169,000 and the north with the least at 137,000. Such estimates can assist in healthcare resource planning, which requires these spatial distributions for evidence-based policymaking and to investigate why such heterogeneities exist. The methodologies presented can be utilized within any urban setting where census data exists. Full article
(This article belongs to the Special Issue Predictive Models That Can Impact Public Health)
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Article
Development, and Internal, and External Validation of a Scoring System to Predict 30-Day Mortality after Having a Traffic Accident Traveling by Private Car or Van: An Analysis of 164,790 Subjects and 79,664 Accidents
Int. J. Environ. Res. Public Health 2020, 17(24), 9518; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph17249518 - 18 Dec 2020
Cited by 1 | Viewed by 566
Abstract
Predictive factors for fatal traffic accidents have been determined, but not addressed collectively through a predictive model to help determine the probability of mortality and thereby ascertain key points for intervening and decreasing that probability. Data on all road traffic accidents with victims [...] Read more.
Predictive factors for fatal traffic accidents have been determined, but not addressed collectively through a predictive model to help determine the probability of mortality and thereby ascertain key points for intervening and decreasing that probability. Data on all road traffic accidents with victims involving a private car or van occurring in Spain in 2015 (164,790 subjects and 79,664 accidents) were analyzed, evaluating 30-day mortality following the accident. As candidate predictors of mortality, variables associated with the accident (weekend, time, number of vehicles, road, brightness, and weather) associated with the vehicle (type and age of vehicle, and other types of vehicles in the accident) and associated with individuals (gender, age, seat belt, and position in the vehicle) were examined. The sample was divided into two groups. In one group, a logistic regression model adapted to a points system was constructed and internally validated, and in the other group the model was externally validated. The points system obtained good discrimination and calibration in both the internal and the external validation. Consequently, a simple tool is available to determine the risk of mortality following a traffic accident, which could be validated in other countries. Full article
(This article belongs to the Special Issue Predictive Models That Can Impact Public Health)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Development, and internal and external validation of a scoring system to predict 30-day mortality after having a traffic accident traveling by private car or van: an analysis of 164,790 subjects and 79,664 accidents
Authors: Antonio Palazón-Bru
Affiliation: Department of Clinical Medicine, Miguel Hernández University, 03005 San Juan de Alicante, Spain

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