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Assessing the Socioeconomic Impact of Stringent Containment Policies on COVID-19 Outcomes: A Comparative Analysis of OECD Countries in 2020-2021

Yıl 2024, Cilt: 13 Sayı: 4, 1667 - 1679, 25.12.2024
https://doi.org/10.37989/gumussagbil.1556480

Öz

Stringent containment measures, including business and workplace closures, travel restrictions, mandatory facemask usage, and compulsory vaccinations, have been widely implemented to curb the spread of Coronavirus Disease 2019 (COVID-19). However, the optimal level of strictness in these policies remains contentious, with concerns regarding potential adverse societal and economic impacts of excessively stringent measures. This study explores the effectiveness of varying degrees of containment policies in mitigating COVID-19 cases and fatalities. Using a homogeneous sample of 31 countries with a GDP per capita above $16,000, we conduct a comparative analysis between nations with high and low levels of containment strictness. Our findings indicate that countries with a containment index below 50 (indicating lower strictness) exhibit lower average COVID-19 confirmed cases per population (24.69% vs. 26.06%) and lower fatality rates (74.33% vs. 76.38%) compared to countries with higher containment indices (around 60). These results suggest that excessively stringent containment measures may not be essential for effective COVID-19 mitigation and that less stringent policies could be more sustainable over the long term. This study contributes to the existing literature on the efficacy of containment policies in managing COVID-19 and offers insights for policymakers striving to strike a balance between public health objectives and economic considerations. Our findings advocate for a moderate approach to containment strategies, emphasizing targeted and adaptable measures as potentially more effective in mitigating the impact of COVID-19 while minimizing adverse effects on society and the economy.

Teşekkür

Acknowledgement: I would like to thank Dr. Mario Coccia, who read the draft and pre-submission versions of the study, provided valuable criticism, and contributed to the correction of the article.

Kaynakça

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  • 2. Bontempi, E., Coccia, M., Vergalli, S., and Zanoletti, A. (2021). “Can commercial trade represent the main indicator of the COVID-19 diffusion due to human-to-human interactions? A comparative analysis between Italy, France, and Spain”. Environmental Research, 201, 111529. https://doi.org/10.1016/j.envres.2021.111529
  • 3. Coccia, M. (2020). “Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID”. The Science of the Total Environment, 729, 138474. https://doi.org/10.1016/j.scitotenv.2020.138474
  • 4. Coccia, M. (2022). “COVID-19 pandemic over 2020 (with lockdowns) and 2021 (with vaccinations): similar effects for seasonality and environmental factors”. Environmental Research, 208, 112711. https://doi.org/10.1016/j.envres.2022.112711
  • 5. Nicoll, A., and Coulombier, D. (2009). “Europe’s initial experience with pandemic (H1N1) 2009 - mitigation and delaying policies and practices”. Eurosurveillance, 14(29), 19279. https://doi.org/10.2807/ese.14.29.19279-en
  • 6. Vinceti, M., Filippini, T., Rothman, K.J., Di Federico, S., and Orsini, N. (2021). “SARS-CoV-2 infection incidence during the first and second COVID-19 waves in Italy”. Environmental Research, 197, 111097. https://doi.org/10.1016/j.envres.2021.111097
  • 7. Askitas, N., Tatsiramos, K., and Verheyden, B. (2021). “Estimating worldwide effects of non-pharmaceutical interventions on COVID-19 incidence and population mobility patterns using a multiple-event study”. Scientific Reports, 11(1), 1972. https://doi.org/10.1038/s41598-021-81442-x
  • 8. Flaxman, S., Mishra, S., Gandy, A., Unwin, H. J. T., Mellan, T. A., Coupland, H., ... and Bhatt, S. (2020). “Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe”. Nature, 584(7820), 257- 261. https://doi.org/10.1038/s41586-020-2405-7
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  • 10. Wieland, T. (2020). “A phenomenological approach to assessing the effectiveness of COVID-19 related nonpharmaceutical interventions in Germany”. Safety Science, 131, 104924. https://doi.org/10.1016/j.ssci.2020.104924
  • 11. Hale, T., Angrist, N., Goldszmidt, R., Kira, B., Petherick, A., Phillips, T., ... and Tatlow, H. (2021). “A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)”. Nature Human Behaviour. 5, 529-538. https://doi.org/10.1038/s41562-021-01079-8
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Sıkı Kontrol Politikalarının COVID-19 Sonuçları Üzerindeki Sosyoekonomik Etkisinin Değerlendirilmesi: 2020-2021'de OECD Ülkelerinin Karşılaştırmalı Analizi

Yıl 2024, Cilt: 13 Sayı: 4, 1667 - 1679, 25.12.2024
https://doi.org/10.37989/gumussagbil.1556480

Öz

İşyeri kapatmaları, seyahat kısıtlamaları, zorunlu yüz maskesi kullanımı ve zorunlu aşılamalar gibi katı sınırlama önlemleri, Koronavirüs Hastalığı 2019'un (COVID-19) yayılmasını engellemek için yaygın olarak uygulanmıştır. Ancak, bu politikalardaki en uygun katılık düzeyi, aşırı katı önlemlerin olası olumsuz toplumsal ve ekonomik etkileriyle ilgili endişelerle tartışmalı olmaya devam etmektedir. Bu çalışma, COVID-19 vakalarını ve ölümlerini azaltmada çeşitli sınırlama politikalarının etkinliğini araştırmaktadır. Kişi başına düşen GSYİH'si 16.000 doların üzerinde olan 31 ülkeden oluşan homojen bir örneklem kullanarak, yüksek ve düşük sınırlama katılığı düzeylerine sahip ülkeler arasında karşılaştırmalı bir analiz yürütüyoruz. Bulgularımız, 50'nin altında bir kontrol endeksine sahip ülkelerin (daha düşük sıkılığı gösterir) nüfus başına daha düşük ortalama COVID-19 doğrulanmış vaka (24,69% - 26,06%) ve daha düşük ölüm oranları (74,33% - 76,38%) sergilediğini, daha yüksek kontrol endekslerine sahip ülkelerle (yaklaşık 60) karşılaştırıldığında gösterdiğini göstermektedir. Bu sonuçlar, aşırı sıkı kontrol önlemlerinin etkili COVID-19 azaltımı için gerekli olmayabileceğini ve daha az sıkı politikaların uzun vadede daha sürdürülebilir olabileceğini göstermektedir. Bu çalışma, COVID-19'u yönetmede kontrol politikalarının etkinliği hakkındaki mevcut literatüre katkıda bulunmakta ve halk sağlığı hedefleri ile ekonomik hususlar arasında bir denge kurmaya çalışan politika yapıcılar için içgörüler sunmaktadır. Bulgularımız, hedeflenen ve uyarlanabilir önlemlerin COVID-19'un etkisini azaltmada potansiyel olarak daha etkili olduğunu ve toplum ve ekonomi üzerindeki olumsuz etkileri en aza indirdiğini vurgulayarak, kontrol stratejilerine yönelik ılımlı bir yaklaşımı savunmaktadır.

Kaynakça

  • 1. Anttiroiko, A.V. (2021). “Successful government responses to the pandemic: Contextualizing national and urban responses to the COVID-19 outbreak in East and West”. International Journal of E-Planning Research, 10(2), 1-17. https://doi.org/10.4018/IJEPR.20210401.oa1
  • 2. Bontempi, E., Coccia, M., Vergalli, S., and Zanoletti, A. (2021). “Can commercial trade represent the main indicator of the COVID-19 diffusion due to human-to-human interactions? A comparative analysis between Italy, France, and Spain”. Environmental Research, 201, 111529. https://doi.org/10.1016/j.envres.2021.111529
  • 3. Coccia, M. (2020). “Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID”. The Science of the Total Environment, 729, 138474. https://doi.org/10.1016/j.scitotenv.2020.138474
  • 4. Coccia, M. (2022). “COVID-19 pandemic over 2020 (with lockdowns) and 2021 (with vaccinations): similar effects for seasonality and environmental factors”. Environmental Research, 208, 112711. https://doi.org/10.1016/j.envres.2022.112711
  • 5. Nicoll, A., and Coulombier, D. (2009). “Europe’s initial experience with pandemic (H1N1) 2009 - mitigation and delaying policies and practices”. Eurosurveillance, 14(29), 19279. https://doi.org/10.2807/ese.14.29.19279-en
  • 6. Vinceti, M., Filippini, T., Rothman, K.J., Di Federico, S., and Orsini, N. (2021). “SARS-CoV-2 infection incidence during the first and second COVID-19 waves in Italy”. Environmental Research, 197, 111097. https://doi.org/10.1016/j.envres.2021.111097
  • 7. Askitas, N., Tatsiramos, K., and Verheyden, B. (2021). “Estimating worldwide effects of non-pharmaceutical interventions on COVID-19 incidence and population mobility patterns using a multiple-event study”. Scientific Reports, 11(1), 1972. https://doi.org/10.1038/s41598-021-81442-x
  • 8. Flaxman, S., Mishra, S., Gandy, A., Unwin, H. J. T., Mellan, T. A., Coupland, H., ... and Bhatt, S. (2020). “Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe”. Nature, 584(7820), 257- 261. https://doi.org/10.1038/s41586-020-2405-7
  • 9. Allen, D.W. (2022). “Covid-19 lockdown cost/benefits: A critical assessment of the literature”. International Journal of the Economics of Business, 29(1), 1-32. https://doi.org/10.1080/13571516.2021.1976051
  • 10. Wieland, T. (2020). “A phenomenological approach to assessing the effectiveness of COVID-19 related nonpharmaceutical interventions in Germany”. Safety Science, 131, 104924. https://doi.org/10.1016/j.ssci.2020.104924
  • 11. Hale, T., Angrist, N., Goldszmidt, R., Kira, B., Petherick, A., Phillips, T., ... and Tatlow, H. (2021). “A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)”. Nature Human Behaviour. 5, 529-538. https://doi.org/10.1038/s41562-021-01079-8
  • 12. Stringency Index. (2022). “COVID-19: Stringency Index”. Retrieved from https://ourworldindata.org/covid-stringency-index Accessed: February, 2022.
  • 13. Barro, R.J. (2020). “Non-pharmaceutical interventions and mortality in U.S. cities during the Great Influenza Pandemic, 1918-1919”. NBER Working Paper, No.27049. https://doi.org/10.3386/w27049
  • 14. Wood, S.N. (2021). “Inferring UK COVID-19 fatal infection trajectories from daily mortality data: Were infections already in decline before the UK lockdowns?” Biometrics, https://doi.org/10.1111/biom.13462
  • 15. Kargı, B., and Coccia, M. (2024). “The developmental routes followed by smartphone technology over time (2008-2018 Period).” Bulletin of Economic Theory and Analysis, 9(2), 369-395. doi. https://doi.org/10.25229/beta.1398832
  • 16. Kargı, B., Coccia, M., and Uçkaç, B.C. (2023). “Findings from the first wave of covid-19 on the different impacts of lockdown on public health and economic growth”. International Journal of Economic Sciences, 12(2), 21-39. https://doi.org/10.52950/ES.2023.12.2.002
  • 17. Kargı, B., Coccia, M., and Uçkaç, B. C. (2023). “How does the wealth level of nations affect their COVID19 vaccination plans? Economics.” Management and Sustainability, 8(2), 6-19. https://doi.org/10.14254/jems.2023.8-2.1
  • 18. Hsiang, S., Allen, D., Anna-Phan, S., Bell, K., Bolinger, I., … and Wu, T. (2020). “The effect of large-scale anti-contagion policies on the COVID-19 pandemic”. Nature, 584(7820), 262-267. https://doi.org/10.1038/s41586-020-2404-8
  • 19. Lai, S., Ruktanonchai, N.W., Zhou, L., Prosper, O., … and Tatem, A.J. (2020). “Effect of non-pharmaceutical interventions to contain COVID-19 in China”. Nature, 585(7825), 410-413. https://doi.org/10.1038/s41586-020-2293-x
  • 20. Hale, T., Angrist, N., Hale, A.J., Kira, B., Majumdar, S., … and Zhang, Y. (2021). “Government responses and COVID-19 deaths: Global evidence across multiple pandemic waves”. PLOS One, 16(7), e0253116. https://doi.org/10.1371/journal.pone.0253116 21. Tian, H., Liu, Y., Li, Y., Wu, S.-H., … and Dye, O.G. (2020). “An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China”. Science, 368(6491), 638-642. https://doi.org/10.1126/science.abb6105
  • 22. Alfano, V., & Ercolano, S. (2020). “The efficacy of lockdown against COVID-19: A cross-country panel analysis”. Applied Health Economics and Health Policy, 18(4), 509-517. https://doi.org/10.1007/s40258-020-00596-3
  • 23. Desvars-Larrive, A., Dervic, E., Haug, N., Niederkrotenthaler, T., Chen, J., … and Thurner, S. (2020). “A structured open dataset of government interventions in response to COVID-19”. Scientific Data, 7(1), 1-9. https://doi.org/10.1038/s41597-020-00609-9
  • 24. Bjørnskov, C. (2021). “Did lockdown work? An economist’s cross-country comparison”. Journal of Global Economics, 9(3), 213-229. https://doi.org/10.1080/17487870.2021.1879813
  • 25. Islam, N., Sharp, S.J., Chowell, G., Shabnam, S., … White, M. (2020). “Physical distancing interventions and incidence of coronavirus disease 2019: natural experiment in 149 countries”. BMJ, 370, m2743. https://doi.org/10.1136/bmj.m2743
  • 26. Brauner, J. M., Mindermann, S., Sharma, M., Johnston, D., … and Kulveit, J. (2021). “Inferring the effectiveness of government interventions against COVID-19”. Science, 371(6531). https://doi.org/10.1126/science.abd9338
  • 27. Dehning, J., Zierenberg, J., Spitzner, F.P., Wibral., … and Priesemann, V. (2020). “Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions”. Science, 369(6500), eabb9789. https://doi.org/10.1126/science.abb9789
  • 28. Sebhatu, A., Wennberg, K., Arora-Jonsson, S., Lindberg, S.I. (2020). “Explaining the homogeneous diffusion of COVID-19 nonpharmaceutical interventions across heterogeneous countries”. PNAS, 117(35), 21201-21208. https://doi.org/10.1073/pnas
  • 29. Gourinchas, P. O. (2020). “COVID-19 and the macroeconomic policy response in Europe”. Brookings Papers on Economic Activity, 2020(2), 495-516. https://doi.org/10.1353/eca.2020.0008
  • 30. Moghadas, S. M., Vilches, T.N., Zhang, K., Wells, C.R., Shoukat, A., … and Galvani, A.P. (2021). “The impact of vaccination on COVID-19 outbreaks in the United States”. Nature Medicine, 27(3), 515-522. https://doi.org/10.1101/2020.11.27.20240051
  • 31. Rosen, B., Dine, S., and Davidovitch, N. (2021). “Lessons in COVID-19 vaccination from Israel”. Nature Reviews Immunology, 21(4), 205-211. https://doi.org/10.1377/forefront.20210315.476220
  • 32. The World Bank. (2022). GDP per capita (current US$). Retrieved from https://data.worldbank.org/indicator/NY.GDP.PCAP.CD Accessed: March, 2022.
  • 33. OECD Data, (2022). GDP, volume – annual growth rates in percentage. Retrieved from: https://stats.oecd.org/index.aspx?queryid=60703 Accessed: March, 2022.
  • 34. International Monetary Fund. (2022). World Economic Outlook (October - 2021). Retrieved from: https://www.imf.org/en/Publications/WEO/Issues/2021/10/12/world-economic-outlook-october-2021 Accessed March 2021.
  • 35. Johns Hopkins Center for System Science and Engineering. (2022). Coronavirus COVID-19 Global Cases. Retrieved from: https://www.arcgis.com/apps/dashboards/bda7594740fd40299423467b48e9ecf6 Accessed: March 4, 2022.
  • 36. Lau, H., Khosrawipour, T., Kocbach, P., Ichii, H., Bania, J., and Khosrawipour, V. (2021). “Evaluating the massive underreporting and undertesting of COVID-19 cases in multiple global epicenters”. Pulmonology, 27(2), 110-115. https://doi.org/10.1016/j.pulmoe.2020.05.015
  • 37. Wilson, N., Kvalsvig, A., and Barnard, L. (2020). “Case-fatality risk estimates for COVID-19 calculated by using a lag time for fatality”. Emerging Infectious Diseases, 26(6), 1339-1441. https://doi.org/10.3201/eid2606.200320
  • 38. Coccia, M. (2023a). “Effects of strict containment policies on COVID-19 pandemic crisis: lessons to cope with next pandemic impacts”. Environmental Science and Pollution Research International, 30(1), 2020–2028. https://doi.org/10.1007/s11356-022-22024-w
  • 39. Angelopoulos, A. N., Pathak, R., Varma, R., and Jordan, M. I. (2020). “On identifying and mitigating bias in the estimation of the COVID-19 case fatality rate”. Harvard Data Science Review. https://doi.org/10.1162/99608f92.f01ee285
  • 40. WHO (2020). “Estimating mortality from COVID-19, Scientific Brief”. Retrieved from: https://www.who.int/news-room/commentaries/detail/estimating-mortality-from-covid-19 Accessed: May 6, 2021.
  • 41. Uçkaç, B.C., Coccia, M., and Kargı, B. (2023). “Diffusion of COVID-19 in polluted regions: Main role of wind energy for sustainable and health”. International Journal of Membrane Science and Technology, 10(3), 2755-2767. https://doi.org/10.15379/ijmst.v10i3.2286
  • 42. Uçkaç, B.C., Coccia, M., and Kargı, B. (2023). “Simultaneous encouraging effects of new technologies for socioeconomic and environmental sustainability”. Bulletin Social-Economic and Humanitarian Research, 19(21), 100-120. https://doi.org/10.52270/26585561_2023_19_21_100
  • 43. Atkeson, A. G. (2021). Behavior and the Dynamics of Epidemics. Brookings Papers on Economic Activity, Spring.
  • 44. Yao, L., Li, M., Wan, J.Y., (...), Bailey, J.E., Graff, J.C. (2022). “Democracy and case fatality rate of COVID-19 at early stage of pandemic: a multicountry study”. Environmental Science and Pollution Research, 29(6), 8694-8704. https://doi.org/10.1007/s11356-021-16250-x
  • 45. Homburg, S. (2020). “Effectiveness of corona lockdowns: evidence for a number of countries”. The Economists’ Voice, 17(1), 20200010. https://doi.org/10.1515/ev-2020-0010
  • 46. Goolsbee, A., and Syverson, C. (2021). “Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020”. Journal of Public Economics, 193, 104311. https://doi.org/10.1016/j.jpubeco.2020.104311
  • 47. Ball, P. (2021). “What the COVID-19 pandemic reveals about science, policy and society”. Interface Focus, 11(5), 20210022. https://doi.org/10.1098/rsfs.2021.0022
  • 48. Birch, J. (2021). “Science and policy in extremis: The UK’s initial response to COVID 19”. European Journal of Philosophy of Science, 11, 90. https://doi.org/10.1007/s13194-021-00407-z
  • 49. Gore, A. (2004). “The politics of fear”. Social Research, 71(4), 779-798. https://doi.org/10.1353/sor.2004.0040
  • 50. Kufel, T., Kufel, P., and Błażejowski, M. (2022). “Do COVID-19 lock-downs affect business cycle? Analysis using energy consumption cycle clock for selected European countries”. Energies, 15(1), 340. https://doi.org/10.3390/en15010340
  • 51. Murphy, J., Vallières, F., and Bentall, R.P. (2021). “Psychological characteristics associated with COVID-19 vaccine hesitancy and resistance in Ireland and the United Kingdom”. Nature Communications, 12, 29. https://doi.org/10.1038/s41467-020-20226-9
  • 52. Vergara, R., Sarmiento, P., and Lagman, J. (2021). “Building public trust: a response to COVID-19 vaccine hesitancy predicament”. Journal of Public Health, 43(2), e291–e292. https://doi.org/10.1093/pubmed/fdaa282
  • 53. Raleigh, V.S. (2020). “UK’s record on pandemic deaths”. BMJ, 370, m3348. https://doi.org/10.1136/bmj.m3348
  • 54. Green, D., Filkin, G., and Woods, T. (2021). “Our unhealthy nation”. Lancet Healthy Longev, 2, E8–E9. https://doi.org/10.1016/S2666-7568(20)30062-3
  • 55. Kargı, B., Coccia, M., and Uçkaç, B.C. (2023). “Socioeconomic, demographic and environmental factors and COVID-19 vaccination: Interactions affecting effectiveness”. Bulletin Social-Economic and Humanitarian Research, 19(21), 83-99. http://doi.org/10.52270/26585561_2023_19_21_83
Toplam 54 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Halk Sağlığı (Diğer), Sağlık Yönetimi
Bölüm Makaleler
Yazarlar

Bilal Kargı 0000-0002-7741-8961

Yayımlanma Tarihi 25 Aralık 2024
Gönderilme Tarihi 26 Eylül 2024
Kabul Tarihi 22 Ekim 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 13 Sayı: 4

Kaynak Göster

APA Kargı, B. (2024). Assessing the Socioeconomic Impact of Stringent Containment Policies on COVID-19 Outcomes: A Comparative Analysis of OECD Countries in 2020-2021. Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi, 13(4), 1667-1679. https://doi.org/10.37989/gumussagbil.1556480
AMA Kargı B. Assessing the Socioeconomic Impact of Stringent Containment Policies on COVID-19 Outcomes: A Comparative Analysis of OECD Countries in 2020-2021. Gümüşhane Sağlık Bilimleri Dergisi. Aralık 2024;13(4):1667-1679. doi:10.37989/gumussagbil.1556480
Chicago Kargı, Bilal. “Assessing the Socioeconomic Impact of Stringent Containment Policies on COVID-19 Outcomes: A Comparative Analysis of OECD Countries in 2020-2021”. Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi 13, sy. 4 (Aralık 2024): 1667-79. https://doi.org/10.37989/gumussagbil.1556480.
EndNote Kargı B (01 Aralık 2024) Assessing the Socioeconomic Impact of Stringent Containment Policies on COVID-19 Outcomes: A Comparative Analysis of OECD Countries in 2020-2021. Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi 13 4 1667–1679.
IEEE B. Kargı, “Assessing the Socioeconomic Impact of Stringent Containment Policies on COVID-19 Outcomes: A Comparative Analysis of OECD Countries in 2020-2021”, Gümüşhane Sağlık Bilimleri Dergisi, c. 13, sy. 4, ss. 1667–1679, 2024, doi: 10.37989/gumussagbil.1556480.
ISNAD Kargı, Bilal. “Assessing the Socioeconomic Impact of Stringent Containment Policies on COVID-19 Outcomes: A Comparative Analysis of OECD Countries in 2020-2021”. Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi 13/4 (Aralık 2024), 1667-1679. https://doi.org/10.37989/gumussagbil.1556480.
JAMA Kargı B. Assessing the Socioeconomic Impact of Stringent Containment Policies on COVID-19 Outcomes: A Comparative Analysis of OECD Countries in 2020-2021. Gümüşhane Sağlık Bilimleri Dergisi. 2024;13:1667–1679.
MLA Kargı, Bilal. “Assessing the Socioeconomic Impact of Stringent Containment Policies on COVID-19 Outcomes: A Comparative Analysis of OECD Countries in 2020-2021”. Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi, c. 13, sy. 4, 2024, ss. 1667-79, doi:10.37989/gumussagbil.1556480.
Vancouver Kargı B. Assessing the Socioeconomic Impact of Stringent Containment Policies on COVID-19 Outcomes: A Comparative Analysis of OECD Countries in 2020-2021. Gümüşhane Sağlık Bilimleri Dergisi. 2024;13(4):1667-79.