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ORIGINAL RESEARCH article

Front. Cell. Infect. Microbiol.
Sec. Clinical Infectious Diseases
Volume 14 - 2024 | doi: 10.3389/fcimb.2024.1496991
This article is part of the Research Topic Recent Advancements in the Research Models of Infectious Diseases View all articles

Based on the MaxEnt model the analysis of influencing factors and simulation of potential risk areas of human infection with H7N9 avian influenza in China

Provisionally accepted
Zhao Yang Zhao Yang 1,2*Jie Wang Jie Wang 3*Wen Dong Wen Dong 1,2*Zhong Da Ren Zhong Da Ren 4,5*
  • 1 Yunnan Normal University, Kunming, China
  • 2 GIS Technology Engineering Research Centre for West-China Resources and Environment of Educational Ministry., Kunming, China
  • 3 Chongqing City Management College, Chongqing 401331, China
  • 4 State Key Laboratory of Estuarine and Coastal Research, East China Normal University., Shanghai, China
  • 5 Department of Geography, University College Cork, Cork, Ireland

The final, formatted version of the article will be published soon.

    Exposure to infected animals and their contaminated environments may be the primary cause of human infection with the H7N9 avian influenza virus. However, the transmission characteristics and specific role of various influencing factors in the spread of the epidemic are not clearly understood. Therefore, it is of great significance for scientific research and practical application to explore the influencing factors related to the epidemic. Based on the data of relevant influencing factors and case sample points, this study used the MaxEnt model to test the correlation between human infection with H7N9 avian influenza and influencing factors in China from 2013 to 2017, and scientifically simulated and evaluated the potential risk areas of human infection with H7N9 avian influenza in China. The simulation results show that the epidemic risk is increasing year by year, and the eastern and southeastern coasts have always been high-risk areas. After verification, the model simulation results are generally consistent with the actual outbreak of the epidemic. Population density was the main influencing factor of the epidemic, and the secondary influencing factors included vegetation coverage, precipitation, altitude, poultry slaughter, production value, and temperature. The study revealed the spatial distribution and diffusion rules of the H7N9 epidemic and clarified the key influencing factors. In the future, more variables need to be included to improve the model and provide more accurate support for prevention and control strategies.

    Keywords: H7N9, MAXENT model, Influencing factors, Risk simulation, China

    Received: 16 Sep 2024; Accepted: 29 Nov 2024.

    Copyright: © 2024 Yang, Wang, Dong and Ren. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Zhao Yang, Yunnan Normal University, Kunming, China
    Jie Wang, Chongqing City Management College, Chongqing 401331, China
    Wen Dong, Yunnan Normal University, Kunming, China
    Zhong Da Ren, State Key Laboratory of Estuarine and Coastal Research, East China Normal University., Shanghai, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.