IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i9p3092-d351832.html
   My bibliography  Save this article

Could Environment Affect the Mutation of H1N1 Influenza Virus?

Author

Listed:
  • Dong Jiang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    Savaid Medical School, University of Chinese Academy of Sciences, Beijing 100049, China
    These authors contributed equally to this work.)

  • Qian Wang

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    Savaid Medical School, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Zhihua Bai

    (Savaid Medical School, University of Chinese Academy of Sciences, Beijing 100049, China
    CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
    These authors contributed equally to this work.)

  • Heyuan Qi

    (CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China)

  • Juncai Ma

    (CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China)

  • Wenjun Liu

    (Savaid Medical School, University of Chinese Academy of Sciences, Beijing 100049, China
    CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
    State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresourses & Laboratory of Animal Infectious Diseases, College of Animal Sciences and Veterinary Medicine, Guangxi University, Nanning 530004, Guangxi, China)

  • Fangyu Ding

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China)

  • Jing Li

    (Savaid Medical School, University of Chinese Academy of Sciences, Beijing 100049, China
    CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China)

Abstract

H1N1 subtype influenza A viruses are the most common type of influenza A virus to infect humans. The two major outbreaks of the virus in 1918 and 2009 had a great impact both on human health and social development. Though data on their complete genome sequences have recently been obtained, the evolution and mutation of A/H1N1 viruses remain unknown to this day. Among many drivers, the impact of environmental factors on mutation is a novel hypothesis worth studying. Here, a geographically disaggregated method was used to explore the relationship between environmental factors and mutation of A/H1N1 viruses from 2000–2019. All of the 11,721 geo-located cases were examined and the data was analysed of six environmental elements according to the time and location (latitude and longitude) of those cases. The main mutation value was obtained by comparing the sequence of the influenza virus strain with the earliest reported sequence. It was found that environmental factors systematically affect the mutation of A/H1N1 viruses. Minimum temperature displayed a nonlinear, rising association with mutation, with a maximum ~15 °C. The effects of precipitation and social development index (nighttime light) were more complex, while population density was linearly and positively correlated with mutation of A/H1N1 viruses. Our results provide novel insight into understanding the complex relationships between mutation of A/H1N1 viruses and environmental factors.

Suggested Citation

  • Dong Jiang & Qian Wang & Zhihua Bai & Heyuan Qi & Juncai Ma & Wenjun Liu & Fangyu Ding & Jing Li, 2020. "Could Environment Affect the Mutation of H1N1 Influenza Virus?," IJERPH, MDPI, vol. 17(9), pages 1-9, April.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:9:p:3092-:d:351832
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/9/3092/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/17/9/3092/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Galam, Serge, 2010. "Public debates driven by incomplete scientific data: The cases of evolution theory, global warming and H1N1 pandemic influenza," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3619-3631.
    2. Raupach, M.R. & Rayner, P.J. & Paget, M., 2010. "Regional variations in spatial structure of nightlights, population density and fossil-fuel CO2 emissions," Energy Policy, Elsevier, vol. 38(9), pages 4756-4764, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Can Chen & Xiaobao Zhang & Daixi Jiang & Danying Yan & Zhou Guan & Yuqing Zhou & Xiaoxiao Liu & Chenyang Huang & Cheng Ding & Lei Lan & Xihui Huang & Lanjuan Li & Shigui Yang, 2021. "Associations between Temperature and Influenza Activity: A National Time Series Study in China," IJERPH, MDPI, vol. 18(20), pages 1-11, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Xueqi & Liu, Gengyuan & Coscieme, Luca & Giannetti, Biagio F. & Hao, Yan & Zhang, Yan & Brown, Mark T., 2019. "Study on the emergy-based thermodynamic geography of the Jing-Jin-Ji region: Combined multivariate statistical data with DMSP-OLS nighttime lights data," Ecological Modelling, Elsevier, vol. 397(C), pages 1-15.
    2. Galam, Serge, 2021. "Will Trump win again in the 2020 election? An answer from a sociophysics model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    3. Su, Yongxian & Chen, Xiuzhi & Li, Yong & Liao, Jishan & Ye, Yuyao & Zhang, Hongou & Huang, Ningsheng & Kuang, Yaoqiu, 2014. "China׳s 19-year city-level carbon emissions of energy consumptions, driving forces and regionalized mitigation guidelines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 231-243.
    4. Gang Xu & Tianyi Zeng & Hong Jin & Cong Xu & Ziqi Zhang, 2023. "Spatio-Temporal Variations and Influencing Factors of Country-Level Carbon Emissions for Northeast China Based on VIIRS Nighttime Lighting Data," IJERPH, MDPI, vol. 20(1), pages 1-17, January.
    5. Kononovicius, Aleksejus, 2021. "Supportive interactions in the noisy voter model," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    6. Juan Jose Miranda & Oscar A. Ishizawa & Hongrui Zhang, 2020. "Understanding the Impact Dynamics of Windstorms on Short-Term Economic Activity from Night Lights in Central America," Economics of Disasters and Climate Change, Springer, vol. 4(3), pages 657-698, October.
    7. Nadiia Charkovska & Mariia Halushchak & Rostyslav Bun & Zbigniew Nahorski & Tomohiro Oda & Matthias Jonas & Petro Topylko, 2019. "A high-definition spatially explicit modelling approach for national greenhouse gas emissions from industrial processes: reducing the errors and uncertainties in global emission modelling," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(6), pages 907-939, August.
    8. Rostyslav Bun & Zbigniew Nahorski & Joanna Horabik-Pyzel & Olha Danylo & Linda See & Nadiia Charkovska & Petro Topylko & Mariia Halushchak & Myroslava Lesiv & Mariia Valakh & Vitaliy Kinakh, 2019. "Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(6), pages 853-880, August.
    9. Mengcheng Li & Haimeng Liu & Shangkun Yu & Jianshi Wang & Yi Miao & Chengxin Wang, 2022. "Estimating the Decoupling between Net Carbon Emissions and Construction Land and Its Driving Factors: Evidence from Shandong Province, China," IJERPH, MDPI, vol. 19(15), pages 1-26, July.
    10. Xiao, Hongwei & Ma, Zhongyu & Mi, Zhifu & Kelsey, John & Zheng, Jiali & Yin, Weihua & Yan, Min, 2018. "Spatio-temporal simulation of energy consumption in China's provinces based on satellite night-time light data," Applied Energy, Elsevier, vol. 231(C), pages 1070-1078.
    11. Cui, Yuanzheng & Zhang, Weishi & Wang, Can & Streets, David G. & Xu, Ying & Du, Mingxi & Lin, Jintai, 2019. "Spatiotemporal dynamics of CO2 emissions from central heating supply in the North China Plain over 2012–2016 due to natural gas usage," Applied Energy, Elsevier, vol. 241(C), pages 245-256.
    12. F. Jacobs & S. Galam, 2019. "Two-Opinions-Dynamics Generated By Inflexibles And Non-Contrarian And Contrarian Floaters," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-30, June.
    13. Paulo Reis Mourao, 2019. "The effectiveness of Green voices in parliaments: Do Green Parties matter in the control of pollution?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(2), pages 985-1011, April.
    14. Naifu Yu & Yingkai Tang & Ying Ma, 2023. "Spatio-Temporal Evolution, Spillover Effects of Land Resource Use Efficiency in Urban Built-Up Area: A Further Analysis Based on Economic Agglomeration," Land, MDPI, vol. 12(3), pages 1-17, February.
    15. Zhao, Bingbing & Deng, Min & Lo, Siuming & Liu, Baoju, 2024. "Estimating built-up area carbon emissions through addressing regional development disparities with population and nighttime light data," Applied Energy, Elsevier, vol. 369(C).
    16. Wang, Shaojian & Zeng, Jingyuan & Liu, Xiaoping, 2019. "Examining the multiple impacts of technological progress on CO2 emissions in China: A panel quantile regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 140-150.
    17. Delanoë, Alexandre & Galam, Serge, 2014. "Modeling a controversy in the press: The case of abnormal bee deaths," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 93-103.
    18. Yang, Di & Luan, Weixin & Qiao, Lu & Pratama, Mahardhika, 2020. "Modeling and spatio-temporal analysis of city-level carbon emissions based on nighttime light satellite imagery," Applied Energy, Elsevier, vol. 268(C).
    19. Ahfeldt, Gabriel M. & Pietrostefani, Elisabetta, 2017. "The compact city in empirical research: A quantitative literature review," LSE Research Online Documents on Economics 83638, London School of Economics and Political Science, LSE Library.
    20. Cheng, Chun & Luo, Yun & Yu, Changbin, 2020. "Dynamic mechanism of social bots interfering with public opinion in network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).

    More about this item

    Keywords

    H1N1 influenza virus; mutation; environment factors;
    All these keywords.

    JEL classification:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:9:p:3092-:d:351832. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.