tetano
Editor, Senior Moderator
Sci Rep
. 2024 May 22;14(1):11728.
doi: 10.1038/s41598-024-62300-y. Assessing eco-geographic influences on COVID-19 transmission: a global analysis
Jing Pan[SUP] 1 2 [/SUP], Arivizhivendhan Kannan Villalan[SUP] 1 2 [/SUP], Guanying Ni[SUP] 3 [/SUP], Renna Wu[SUP] 3 [/SUP], ShiFeng Sui[SUP] 4 [/SUP], Xiaodong Wu[SUP] 5 [/SUP], XiaoLong Wang[SUP] 6 7 [/SUP]
Affiliations
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.
Keywords: COVID-19; Epidemiological characteristics analysis; Maximum entropy; Population-based studies; Risk assessment; Spatial modeling.
. 2024 May 22;14(1):11728.
doi: 10.1038/s41598-024-62300-y. Assessing eco-geographic influences on COVID-19 transmission: a global analysis
Jing Pan[SUP] 1 2 [/SUP], Arivizhivendhan Kannan Villalan[SUP] 1 2 [/SUP], Guanying Ni[SUP] 3 [/SUP], Renna Wu[SUP] 3 [/SUP], ShiFeng Sui[SUP] 4 [/SUP], Xiaodong Wu[SUP] 5 [/SUP], XiaoLong Wang[SUP] 6 7 [/SUP]
Affiliations
- PMID: 38777817
- DOI: 10.1038/s41598-024-62300-y
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.
Keywords: COVID-19; Epidemiological characteristics analysis; Maximum entropy; Population-based studies; Risk assessment; Spatial modeling.