Global Determinants of Covid-19 Deaths: Lockdown Dates and Social Distancing Measures Mattered
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Abstract
Objectives
The objective of this paper is to examine the influence that various contextual variables have upon the number of deaths due to covid-19, across the world.
Setting Level
This study utilizes data for 125 countries for contextual variables from 1st January 2020 until the 15th June 2020.
Participants
This study considers deaths from covid-19.
Interventions
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Primary and secondary outcome measures
The contextual variables considered in this study are stringency index, stringency variability, lockdown date, population density, level of airline passengers and country health security index.
Results
It is shown there is a very strong association between the level of airline passengers and covid-19 deaths. The results from regression analysis conducted in this study show significant positive relationships at the 5% level of statistical significance between Deaths from covid-19 and airline passenger levels and stringency variability; significant negative relationships are revealed for stringency index and lockdown date supporting the notion that lock down and social distancing measures mattered and were effective. The Global health security index and population density did not significantly affect deaths.
Conclusion
This study highlights the strong link between a country’s airline passengers and covid-19 deaths and found that the lockdown date and stringency measures had a significant effect upon deaths. The implications of the research is that lockdown and stringency measures implemented by governments around the world worked and mattered. Further, the fact that global health security did not affect deaths may indicate better preparedness required to confront future pandemics.
Trial Registration
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FUNDING: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Article Summary: Strengths and Limitations of Study
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It is discovered in this paper, for a sample of 125 countries that lockdown and social distancing measures had a very significant positive effect upon reducing covid-19 deaths across the world. Countries deaths were very significantly positively related to the level of annual airline passengers. A combination of 18 countries with a share of 84% of global annual air passengers accounted for 80% of total deaths recorded from covid-19, worldwide.
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The quality of a country’s health system as measured by a new measure GHI Global Health Security Index did not significantly reduce the number of covid-19 deaths, supporting the fact that both developed and developing countries were lacking in essential equipment, as well as track and trace mechanisms.
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The strengths of the study are that it is very timely and judgement needs to be made at the national and international level whether the lockdown was effective given the likelihood of a 2 nd wave to the pandemic. Countries need to better prepare themselves for future pandemics in terms of rapid data sharing and analysis to ensure that outbreaks are contained more effectively and efficiently through stringent lockdown and social distancing measures.
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A limitation of the study is the quality of data relating to the deaths actually caused by the covid-19 virus. Despite this the methodology and results of the paper are very sound and robust.
Article activity feed
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SciScore for 10.1101/2020.07.28.20163394: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar …
SciScore for 10.1101/2020.07.28.20163394: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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SciScore for 10.1101/2020.07.28.20163394: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement Data was from reliable and collected ethically by the providers and this study did not need the consent of patients directly, and is publicly available. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Data from additional tools added to each annotation on a weekly basis.
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and …
SciScore for 10.1101/2020.07.28.20163394: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement Data was from reliable and collected ethically by the providers and this study did not need the consent of patients directly, and is publicly available. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Data from additional tools added to each annotation on a weekly basis.
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.
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