IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i8p4081-d534952.html
   My bibliography  Save this article

Effects of Spatial Characteristics on the Spread of the Highly Pathogenic Avian Influenza (HPAI) in Korea

Author

Listed:
  • Meilan An

    (Department of Food Industrial Management, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 04620, Korea)

  • Jeffrey Vitale

    (Department of Agricultural Economics, Oklahoma State University, 418 Ag Hall, Stillwater, OK 74078, USA)

  • Kwideok Han

    (Department of Institutional Research and Analytics, Oklahoma State University, 203 PIO Building, Stillwater, OK 74078, USA)

  • John N. Ng’ombe

    (Department of Agricultural Economics and Extension, University of Zambia, Lusaka 10101, Zambia)

  • Inbae Ji

    (Department of Food Industrial Management, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 04620, Korea)

Abstract

This paper examines the effects of regional characteristics on the spread of the highly pathogenic avian influenza (HPAI) during Korea’s 2016–2017 outbreak. A spatial econometric model is used to determine the effects of regional characteristics on HPAI dispersion using data from 162 counties in Korea. Results indicate the existence of spatial dependence, suggesting that the occurrence of HPAI in a county is significantly influenced by neighboring counties. We found that larger size poultry, including laying hens, breeders, and ducks are significantly associated with a greater incidence of HPAI. Among poultry, we found ducks as the greatest source of the spread of HPAI. Our findings suggest that those regions that are spatially dependent with respect to the spread of HPAI, such as counties that intensively breed ducks, should be the focus of surveillance to prevent future epidemics of HPAI.

Suggested Citation

  • Meilan An & Jeffrey Vitale & Kwideok Han & John N. Ng’ombe & Inbae Ji, 2021. "Effects of Spatial Characteristics on the Spread of the Highly Pathogenic Avian Influenza (HPAI) in Korea," IJERPH, MDPI, vol. 18(8), pages 1-13, April.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:8:p:4081-:d:534952
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/8/4081/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/8/4081/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    2. An, Meilan, 2020. "Analysis of HPAI Incidence Factors in Duck Farms Using a Negative Binomial Regression Model," Journal of Rural Development/Nongchon-Gyeongje, Korea Rural Economic Institute, vol. 43(4), December.
    3. Jun Ho Seok & Hanpil Moon & GwanSeon Kim & Michael R. Reed, 2018. "Is Aging the Important Factor for Sustainable Agricultural Development in Korea? Evidence from the Relationship between Aging and Farm Technical Efficiency," Sustainability, MDPI, vol. 10(7), pages 1-15, June.
    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. Kwideok Han & Meilan An & Inbae Ji, 2021. "Analyzing Spatial Dependency of the 2016–2017 Korean HPAI Outbreak to Determine the Effective Culling Radius," IJERPH, MDPI, vol. 18(18), pages 1-12, September.

    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. Guohuan Su & Adam Mertel & Sébastien Brosse & Justin M. Calabrese, 2023. "Species invasiveness and community invasibility of North American freshwater fish fauna revealed via trait-based analysis," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    2. Chakir, Raja & Lungarska, Anna, 2015. "Agricultural land rents in land use models: a spatial econometric analysis," 150th Seminar, October 22-23, 2015, Edinburgh, Scotland 212641, European Association of Agricultural Economists.
    3. Demidova, Olga, 2021. "Methods of spatial econometrics and evaluation of government programs effectiveness," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 107-134.
    4. Iacopo Odoardi & Donatella Furia & Piera Cascioli, 2021. "Can social support compensate for missing family support? An examination of dropout rates in Italy," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 121-139, February.
    5. Ozgun, Burcu & Broekel, Tom, 2021. "The geography of innovation and technology news - An empirical study of the German news media," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    6. Pinto, Allan & Griffin, Terry W., 2022. "Detecting bubbles via single time-series variable: applying spatial specification tests to farmland values," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322534, Agricultural and Applied Economics Association.
    7. Gianfranco Piras & Mauricio Sarrias, 2023. "Heterogeneous spatial models in R: spatial regimes models," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-32, December.
    8. Kandt, Jens & Leak, Alistair, 2019. "Examining inclusive mobility through smartcard data: What shall we make of senior citizens' declining bus patronage in the West Midlands?," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    9. Fernando López & Konstatin Kholodilin, 2023. "Putting MARS into space. Non‐linearities and spatial effects in hedonic models," Papers in Regional Science, Wiley Blackwell, vol. 102(4), pages 871-896, August.
    10. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    11. Paul Feichtinger & Klaus Salhofer, 2016. "The Fischler Reform of the Common Agricultural Policy and Agricultural Land Prices," Land Economics, University of Wisconsin Press, vol. 92(3), pages 411-432.
    12. Anastasiya Penska, 2015. "Determinants of Corruption in Ukrainian Regions: Spatial Analysis," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 42.
    13. Michael Lebacher & Paul W. Thurner & Göran Kauermann, 2021. "Censored regression for modelling small arms trade volumes and its ‘Forensic’ use for exploring unreported trades," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 909-933, August.
    14. Gianfranco Piras, 2014. "Impact estimates for static spatial panel data models in R," Letters in Spatial and Resource Sciences, Springer, vol. 7(3), pages 213-223, October.
    15. Minjie Li & Jian Wang & Yihui Chen, 2019. "Evaluation and Influencing Factors of Sustainable Development Capability of Agriculture in Countries along the Belt and Road Route," Sustainability, MDPI, vol. 11(7), pages 1-28, April.
    16. Joohun Han & Chanjin Chung, 2021. "Impact of Aging and Underemployment on Income Disparity between Agricultural and Non-Agricultural Households," Sustainability, MDPI, vol. 13(21), pages 1-15, October.
    17. Kolawole Valère Salako & Akoeugnigan Idelphonse Sode & Aliou Dicko & Eustache Ayédèguè Alaye & Martin Wolkewitz & Romain Glèlè Kakaï, 2024. "Cross-Country Assessment of Socio-Ecological Drivers of COVID-19 Dynamics in Africa: A Spatial Modelling Approach," Stats, MDPI, vol. 7(4), pages 1-15, October.
    18. Ay, Jean-Sauveur & Ayouba, Kassoum & Le Gallo, Julie, 2018. "Nonlinear impact estimation in spatial autoregressive models," Economics Letters, Elsevier, vol. 163(C), pages 59-64.
    19. Tibor Sipos & Anteneh Afework Mekonnen & Zsombor Szabó, 2021. "Spatial Econometric Analysis of Road Traffic Crashes," Sustainability, MDPI, vol. 13(5), pages 1-16, February.
    20. Amarin Siripanich & Taha Hossein Rashidi & Emily Moylan, 2019. "Interaction of Public Transport Accessibility and Residential Property Values Using Smart Card Data," Sustainability, MDPI, vol. 11(9), pages 1-24, May.

    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:18:y:2021:i:8:p:4081-:d:534952. 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.