ArticleScientific reports2024
Assessing eco-geographic influences on COVID-19 transmission: a global analysis.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Determinants of COVID-19 prevalence in Central Java, Indonesia: An ecological study of socio-demographic, environmental, and healthcare factors.Dialogues in health · 2026Article
- Understanding the role of international flight networks in disease spread: spatial epidemic prevention zones and hierarchical disease control policies.International journal of health geographics · 2026Article
- Analysing Spatiotemporal Characteristics and Estimating the Spatial Distribution of Peste des Petits Ruminants (PPR) in Africa.Transboundary and emerging diseases · 2026Article
- Marine-Derived Peptides fromMicroorganisms · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
COVID-19 has been massively transmitted for almost 3 years, and its multiple variants have caused serious health problems and an economic crisis. Our goal was to identify the influencing factors that reduce the threshold of disease transmission and to analyze the epidemiological patterns of COVID-19. This study served as an early assessment of the epidemiological characteristics of COVID-19 using the MaxEnt species distribution algorithm using the maximum entropy model. The transmission of COVID-19 was evaluated based on human factors and environmental variables, including climate, terrain and vegetation, along with COVID-19 daily confirmed case location data. The results of the SDM model indicate that population density was the major factor influencing the spread of COVID-19. Altitude, land cover and climatic factor showed low impact. We identified a set of practical, high-resolution, multi-factor-based maximum entropy ecological niche risk prediction systems to assess the transmission risk of the COVID-19 epidemic globally. This study provided a comprehensive analysis of various factors influencing the transmission of COVID-19, incorporating both human and environmental variables. These findings emphasize the role of different types of influencing variables in disease transmission, which could have implications for global health regulations and preparedness strategies for future outbreaks.
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Registered trials
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