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Correspondence: Author Response
Social and Policy Determinants of COVID-19 Infection Across 23 Countries: An Ecological Study
Kyungsik Kim1,2,3orcid, Sue K. Park1,2,4orcid
Journal of Preventive Medicine and Public Health 2022;55(3):308-309.
Published online: May 31, 2022
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1Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea

2Cancer Research Institute, Seoul National University, Seoul, Korea

3Department of Biomedical Science, Seoul National University Graduate School, Seoul, Korea

4Integrated Major in Innovative Medical Science, Seoul National University College of Medicine, Seoul, Korea

Corresponding author: Sue K. Park, Department of Preventive Medicine, Seoul National University College of Medicine, 103 Daehak-ro, Jongro-gu, Seoul 03080, Korea, E-mail:

Copyright © 2022 The Korean Society for Preventive Medicine

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

See the Original "Social and Policy Determinants of COVID-19 Infection Across 23 Countries: An Ecological Study" on page 144.
Dear Editor,
We appreciate Dr. Mungmunpuntipantip and Wiwanitkit’ letter and their interest in our paper entitled “Social and Policy Determinants of COVID-19 Infection Across 23 Countries: An Ecological Study” [1]. We used coronavirus disease 2019 (COVID-19) indicators, such as incidence, mortality, and fatality rates, as well as data on various social and policy determinants as of September 2020. Based on the results of our ecological study, we hypothesized that the transmission rates of COVID-19 may change depending on the state of society and policy-making factors.
In a letter to the editor, the authors suggested that an update of our study was necessary because many circumstances had changed since the initial pandemic. We fully agree with this suggestion. However, our hypothesis would be more challenging to evaluate after the initial pandemic, since unlike the early days of the pandemic, social distancing and quarantine policies have been recently changing very rapidly in country-specific ways. Even when the same policy continues, it is now more difficult to compare the effect in each country. Unlike the beginning of the pandemic, social and national quarantine measures are changing due to increases or decreases in COVID-19 transmission rates or severity. Moreover, national quarantine policies (e.g., district lockdowns and others) after vaccination have been implemented only in some countries, such as China, but most countries have not implemented national quarantine policies for all citizens. Therefore, social and national policies cannot be determinants of COVID-19 rates in this situation.
As of April 22, 2022, there were 507 912 123 COVID-19 infection cases worldwide, and 6 236 644 deaths. In the last 7 days, the most active COVID-19 outbreaks were found in Germany, Korea, and France, and the most deaths occurred in the United States, the United Kingdom, and Russia. In Korea, social distancing and restrictions on gatherings are no longer mandatory as of April 18.
In further analyses, it would be more reasonable to consider specific social or policy determinants in each country than in multiple countries. As references, some studies have investigated infection-related factors in relation to national policies and regional, interpersonal, and independent factors [2,3], and a community-based big data modeling study on COVID-19 policy was conducted [4].
Considering the temporal relationship of causality, further research could consider the correlation between mortality and vaccination. Thus, we performed linear regression for the mortality rates of 228 countries using detailed information on vaccination from the World Health Organization as of April 18, 2022 [5]. As a result, we found that the number of total COVID-19 vaccinations, the number of vaccination types, and the first vaccination date were negatively correlated with the number of total deaths in 228 countries (Table 1). However, the number of deaths in the last week was rather positively correlated with the number of vaccinations, and it was not correlated with the date of the first vaccination type used. A simple analysis of this type could measure the effect of vaccination policies on deaths over time.


The authors have no conflicts of interest associated with the material presented in this paper.

Table 1
Linear regression analysis for the number of COVID-19 deaths by the status of COVID-19 vaccinations in 228 countries
Models1 Beta (standardized) T-value p-value
Model 1
 Outcome: cumulative no. of deaths
  Intercept 0 8.863 <0.001
  Cumulative no. of cases 0.149 2.357 0.019
  First vaccination date −0.568 −8.858 <0.001
  No. of vaccination types used −0.145 −2.353 0.020
  No. of total vaccinations2 −0.284 −4.331 <0.001

Model 2
 Outcome: newly reported deaths in the last 7 day
  Intercept 0 1.421 0.157
  Cumulative no. of cases 0.613 11.557 <0.001
  First vaccination date −0.081 −1.420 0.157
  No. of vaccination types used −0.025 −0.456 0.649
  No. of total vaccinations2 0.170 3.048 0.003

COVID-19, coronavirus disease 2019.

1 The explanatory power (R2) of model 1 and model 2 was 0.827 and 0.458, respectively.

2 Cumulative total vaccine doses administered per 100 population.

Data from World Health Organization. WHO coronavirus (COVID-19) dashboard; 2022 Apr 18 [5].

  • 1. Kim K, Jeung YD, Choi J, Park SK. Social and policy determinants of COVID-19 infection across 23 countries: an ecological study. J Prev Med Public Health 2022;55(2):144-152ArticlePubMedPMCPDF
  • 2. Jang SH. Social-ecological factors related to preventive behaviors during the COVID-19 pandemic in South Korea. PLoS One 2022;17(3):e0266264ArticlePubMedPMC
  • 3. Souza RC, Almeida ER, Fortaleza CM, Miot HA. Factors associated with COVID-19 mortality in municipalities in the state of São Paulo (Brazil): an ecological study. Rev Soc Bras Med Trop 2022;55: e04472021ArticlePubMedPMC
  • 4. Mahmoudi J, Xiong C. How social distancing, mobility, and preventive policies affect COVID-19 outcomes: big data-driven evidence from the District of Columbia-Maryland-Virginia (DMV) megaregion. PLoS One 2022;17(2):e0263820ArticlePubMedPMC
  • 5. World Health Organization. WHO coronavirus (COVID-19) dashboard; 2022 Apr. 18. [cited 2022 May 10]. Available from:

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