IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i8p4859-d795539.html
   My bibliography  Save this article

Integrated Analysis of Behavioural and Health COVID-19 Data Combining Bayesian Networks and Structural Equation Models

Author

Listed:
  • Ron S. Kenett

    (KPA Group and Samuel Neaman Institute, Raanana 43100, Israel)

  • Giancarlo Manzi

    (Data Science Research Centre, Department of Economics, Management and Quantitative Methods, University of Milan, 20122 Milan, Italy)

  • Carmit Rapaport

    (Department of Geography and Environmental Studies, University of Haifa, Haifa 3498838, Israel
    NIRED—National Institute for Regulation of Emergency and Disaster, College of Law and Business, Ramat Gan 5110801, Israel)

  • Silvia Salini

    (Data Science Research Centre, Department of Economics, Management and Quantitative Methods, University of Milan, 20122 Milan, Italy)

Abstract

The response to the COVID-19 pandemic has been highly variable. Governments have applied different mitigation policies with varying effect on social and economic measures, over time. This article presents a methodology for examining the effect of mobility restriction measures and the association between health and population activity data. As case studies, we refer to the pre-vaccination experience in Italy and Israel. Facing the pandemic, Israel and Italy implemented different policy measures and experienced different population behavioral patterns. Data from these countries are used to demonstrate the proposed methodology. The analysis we introduce in this paper is a staged approach using Bayesian Networks and Structural Equations Models. The goal is to assess the impact of pandemic management and mitigation policies on pandemic spread and population activity. The proposed methodology models data from health registries and Google mobility data and then shows how decision makers can conduct scenario analyses to help design adequate pandemic management policies.

Suggested Citation

  • Ron S. Kenett & Giancarlo Manzi & Carmit Rapaport & Silvia Salini, 2022. "Integrated Analysis of Behavioural and Health COVID-19 Data Combining Bayesian Networks and Structural Equation Models," IJERPH, MDPI, vol. 19(8), pages 1-26, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:8:p:4859-:d:795539
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/8/4859/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/8/4859/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sarah Dryhurst & Claudia R. Schneider & John Kerr & Alexandra L. J. Freeman & Gabriel Recchia & Anne Marthe van der Bles & David Spiegelhalter & Sander van der Linden, 2020. "Risk perceptions of COVID-19 around the world," Journal of Risk Research, Taylor & Francis Journals, vol. 23(7-8), pages 994-1006, August.
    2. Bargain, Olivier & Aminjonov, Ulugbek, 2020. "Trust and compliance to public health policies in times of COVID-19," Journal of Public Economics, Elsevier, vol. 192(C).
    3. Ron S. Kenett & Silvia Salini, 2011. "Rejoinder to ‘Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis’," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(5), pages 484-486, September.
    4. Chernozhukov, Victor & Kasahara, Hiroyuki & Schrimpf, Paul, 2021. "Causal impact of masks, policies, behavior on early covid-19 pandemic in the U.S," Journal of Econometrics, Elsevier, vol. 220(1), pages 23-62.
    5. Per Block & Marion Hoffman & Isabel J. Raabe & Jennifer Beam Dowd & Charles Rahal & Ridhi Kashyap & Melinda C. Mills, 2020. "Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world," Nature Human Behaviour, Nature, vol. 4(6), pages 588-596, June.
    6. Ron S. Kenett & Silvia Salini, 2011. "Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(5), pages 465-475, September.
    7. Gupta, Sumeet & Kim, Hee W., 2008. "Linking structural equation modeling to Bayesian networks: Decision support for customer retention in virtual communities," European Journal of Operational Research, Elsevier, vol. 190(3), pages 818-833, November.
    8. Painter, Marcus & Qiu, Tian, 2021. "Political beliefs affect compliance with government mandates," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 688-701.
    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. Chien-Lung Chan & Chi-Chang Chang, 2022. "Big Data, Decision Models, and Public Health," IJERPH, MDPI, vol. 19(14), pages 1-9, July.

    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. Grimalda, Gianluca & Murtin, Fabrice & Pipke, David & Putterman, Louis & Sutter, Matthias, 2023. "The politicized pandemic: Ideological polarization and the behavioral response to COVID-19," European Economic Review, Elsevier, vol. 156(C).
    2. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    3. Mauro Caselli & Andrea Fracasso & Sergio Scicchitano, 2022. "From the lockdown to the new normal: individual mobility and local labor market characteristics following the COVID-19 pandemic in Italy," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(4), pages 1517-1550, October.
    4. Bartscher, Alina Kristin & Seitz, Sebastian & Siegloch, Sebastian & Slotwinski, Michaela & Wehrhöfer, Nils, 2021. "Social capital and the spread of covid-19: Insights from european countries," Journal of Health Economics, Elsevier, vol. 80(C).
    5. Shuguang Jiang & Qian Wei & Luyao Zhang, 2022. "Individualism Versus Collectivism and the Early-Stage Transmission of COVID-19," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(2), pages 791-821, November.
    6. Deiana, Claudio & Geraci, Andrea & Mazzarella, Gianluca & Sabatini, Fabio, 2022. "Can relief measures nudge compliance in a public health crisis? Evidence from a kinked fiscal policy rule," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 407-428.
    7. Paolo Castelnovo & Martina Dal Molin, 2021. "The learning mechanisms through public procurement for innovation: The case of government‐funded basic research organizations," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 92(3), pages 411-446, September.
    8. Hernando Santamaría-García & Miguel Burgaleta & Agustina Legaz & Daniel Flichtentrei & Mateo Córdoba-Delgado & Juliana Molina-Paredes & Juliana Linares-Puerta & Juan Montealegre-Gómez & Sandra Castelb, 2022. "The price of prosociality in pandemic times," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    9. Pan Zhang & Zhouling Bai, 2024. "Leaving messages as coproduction: impact of government COVID-19 non-pharmaceutical interventions on citizens’ online participation in China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    10. Pedro Costa & Helena Rodrigues, 2024. "The ever-changing business of e-commerce-net benefits while designing a new platform for small companies," Review of Managerial Science, Springer, vol. 18(9), pages 2507-2545, September.
    11. Bird, Matthew D. & Arispe, Samuel & Muñoz, Paula & Freier, Luisa Feline, 2023. "Trust, social protection, and compliance: Moral hazard in Latin America during the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 206(C), pages 279-295.
    12. Anna Petherick & Rafael Goldszmidt & Eduardo B. Andrade & Rodrigo Furst & Thomas Hale & Annalena Pott & Andrew Wood, 2021. "A worldwide assessment of changes in adherence to COVID-19 protective behaviours and hypothesized pandemic fatigue," Nature Human Behaviour, Nature, vol. 5(9), pages 1145-1160, September.
    13. Hamed Taherdoost & Mitra Madanchian, 2021. "Empirical Modeling of Customer Satisfaction for E-Services in Cross-Border E-Commerce," Post-Print hal-03741849, HAL.
    14. Lau Lilleholt & Ingo Zettler & Cornelia Betsch & Robert Böhm, 2023. "Development and validation of the pandemic fatigue scale," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    15. Pan, Jing Yu & Liu, Dahai, 2022. "Mask-wearing intentions on airplanes during COVID-19 – Application of theory of planned behavior model," Transport Policy, Elsevier, vol. 119(C), pages 32-44.
    16. Foliano, Francesca & Tonei, Valentina & Sevilla, Almudena, 2024. "Social restrictions, leisure and well-being," Labour Economics, Elsevier, vol. 87(C).
    17. Ali Zackery & Joseph Amankwah-Amoah & Zahra Heidari Darani & Shiva Ghasemi, 2022. "COVID-19 Research in Business and Management: A Review and Future Research Agenda," Sustainability, MDPI, vol. 14(16), pages 1-32, August.
    18. Olga Khokhlova & Nishtha Lamba & Aditi Bhatia & Marina Vinogradova, 2021. "Biowarfare conspiracy, faith in government, and compliance with safety guidelines during COVID-19: an international study," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 20(2), pages 235-251, November.
    19. Niculaescu, Corina E. & Sangiorgi, Ivan & Bell, Adrian R., 2023. "Does personal experience with COVID-19 impact investment decisions? Evidence from a survey of US retail investors," International Review of Financial Analysis, Elsevier, vol. 88(C).
    20. Garaus, Marion & Hudáková, Melánia, 2022. "The impact of the COVID-19 pandemic on tourists’ air travel intentions: The role of perceived health risk and trust in the airline," Journal of Air Transport Management, Elsevier, vol. 103(C).

    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:19:y:2022:i:8:p:4859-:d:795539. 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.