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Lessons learned from three Southeast Asian countries during the COVID-19 pandemic

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  • Khairulbahri, Muhamad

Abstract

Several scholars have focused on the COVID-19 case studies in Europe and USA, leaving the people in Southeast Asia with little information about the lesson learned from their own case studies. This study aims to analyses case studies through the SEIR model in three Southeast Asia countries including Singapore, Malaysia, and Indonesia. The SEIR model incorporates two types measures including social behavior and lockdowns as well as hospital preparedness. The SEIR model reveals that Malaysia, despite its relatively low testing capacity but with the application of the national lockdown, can slash the coronavirus transmission while Indonesia has still struggled to contain the COVID-19 flow owing to partial lockdowns. Singapore, at one hand, can successfully contain the coronavirus due to the national lockdowns, and the better healthcare system. With this point in mind, it is not surprising that Singapore has very low fatality rates and significantly low cases after lockdowns. Better preparedness lockdowns, and sufficient testing capacity are keys to controlling the COVID-19 flow, especially if the development of vaccines or distribution of respective vaccines is under progress.

Suggested Citation

  • Khairulbahri, Muhamad, 2021. "Lessons learned from three Southeast Asian countries during the COVID-19 pandemic," Journal of Policy Modeling, Elsevier, vol. 43(6), pages 1354-1364.
  • Handle: RePEc:eee:jpolmo:v:43:y:2021:i:6:p:1354-1364
    DOI: 10.1016/j.jpolmod.2021.09.002
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    References listed on IDEAS

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    1. Mohd, Mohd Hafiz & Sulayman, Fatima, 2020. "Unravelling the myths of R0 in controlling the dynamics of COVID-19 outbreak: A modelling perspective," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    2. Donsimoni Jean Roch & Glawion René & Plachter Bodo & Wälde Klaus, 2020. "Projecting the spread of COVID-19 for Germany," German Economic Review, De Gruyter, vol. 21(2), pages 181-216, June.
    3. Homer, J.B. & Hirsch, G.B., 2006. "System dynamics modeling for public health: Background and opportunities," American Journal of Public Health, American Public Health Association, vol. 96(3), pages 452-458.
    4. Facundo Piguillem & Liyan Shi, 2022. "Optimal Covid-19 Quarantine and Testing Policies," The Economic Journal, Royal Economic Society, vol. 132(647), pages 2534-2562.
    5. Navid Ghaffarzadegan & Hazhir Rahmandad, 2020. "Simulation‐based estimation of the early spread of COVID‐19 in Iran: actual versus confirmed cases," System Dynamics Review, System Dynamics Society, vol. 36(1), pages 101-129, January.
    6. Negar Darabi & Niyousha Hosseinichimeh, 2020. "System dynamics modeling in health and medicine: a systematic literature review," System Dynamics Review, System Dynamics Society, vol. 36(1), pages 29-73, January.
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    Cited by:

    1. Alfano, Vincenzo, 2024. "Unlocking the importance of perceived governance: The impact on COVID-19 in NUTS-2 European regions," Social Science & Medicine, Elsevier, vol. 343(C).
    2. Bonfiglio, Andrea & Coderoni, Silvia & Esposti, Roberto, 2022. "Policy responses to COVID-19 pandemic waves: Cross-region and cross-sector economic impact," Journal of Policy Modeling, Elsevier, vol. 44(2), pages 252-279.
    3. Giammetti, Raffaele & Papi, Luca & Teobaldelli, Désirée & Ticchi, Davide, 2022. "The optimality of age-based lockdown policies," Journal of Policy Modeling, Elsevier, vol. 44(3), pages 722-738.
    4. Alfano, Vincenzo & Guarino, Massimo, 2023. "The effect of self-esteem on the spread of a pandemic. A cross-country analysis of the role played by self-esteem in the spread of the COVID-19 pandemic," Social Science & Medicine, Elsevier, vol. 324(C).
    5. Alfano, Vincenzo & Ercolano, Salvatore & Pinto, Mauro, 2022. "Fighting the COVID pandemic: National policy choices in non-pharmaceutical interventions," Journal of Policy Modeling, Elsevier, vol. 44(1), pages 22-40.

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    More about this item

    Keywords

    Coronavirus; Singapore; Malaysia; Indonesia; Southeast Asia; COVID-19; SEIR model;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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