The Impact of Non-Pharmaceutical Interventions on the Second Wave of COVID-19: Insights from an Artificial Intelligence-Based, Cross-Country Study

18 Pages Posted: 12 Aug 2021

See all articles by Sile Tao

Sile Tao

University of Alberta

Nicola Luigi Bragazzi

York University

Jianhong Wu

York University - Laboratory for Industrial and Applied Mathematics; Xi'an Jiaotong University (XJTU) - The Interdisplinary Research Center for Mathematics and Life Sciences

Bruce Mellado

University of the Witwatersrand

Jude Dzevela Kong

Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), York University

Date Written: August 1, 2021

Abstract

Objective: To determine the relative influences of various non-pharmaceutical interventions (NPIs) put in place during the first wave of COVID-19 across countries on the spreading rate of COVID-19 during the second wave, taking into account national-level climatic, environmental, clinical, health, economic, pollution, social, and demographic factors. Methods: We first estimate the growth of the first and second wave across countries by fitting a logistic model to reported daily case numbers, up to the first and second epidemic peaks. Using the growth rate, we estimate the basic and effective reproduction number (second wave) Re across countries. Next, we use Random Forest, an “off-the-shelf” machine learning algorithm, to study the association between the growth rate of the second wave of COVID-19 and NPIs as well as pre-existing country characteristics (climatic, environmental, clinical, health, economic, pollution, social, and demographic factors). Lastly, we compare the growth rate of the first and second waves of COVID-19. Findings: Our findings reveal that the mean R0 and Re were respectively 2.02 (S.D 1.09) and 1.07 (S.D. 0.41). R0 has the highest value in Israel (R0 = 6.93) and lowest in Senegal (R0 = 1.13) whereas Re (second wave) had the highest value in Mexico ( Re = 3.08) and lowest in Bangladesh (Re = 1.07). The top three factors associated with the growth of the second wave are body mass index, the number of days that the government sets restrictions on requiring facial coverings outside the home at all times regardless of location or presence of other people in some areas, and restrictions on gatherings of 10 people or less. We found a statistically significant difference between the means of the first and second waves. Conclusion: Artificial intelligence techniques can enable scholars as well as public health decision- and policy-makers to estimate the effectiveness of public health policies and mitigation strategies to counteract the toll of the outbreak in terms of infections and deaths, enforcing and implementing “smart” interventions, which are as efficacious as drastic and stringent ones.

Note: Funding: No specific funding was received. We acknowledge support from Canada’s International Development Research Centre (IDRC) (Grant No. 109559-001).

Declaration of Interests: None to declare

Suggested Citation

Tao, Sile and Bragazzi, Nicola Luigi and Wu, Jianhong and Wu, Jianhong and Mellado, Bruce and Kong, Jude Dzevela, The Impact of Non-Pharmaceutical Interventions on the Second Wave of COVID-19: Insights from an Artificial Intelligence-Based, Cross-Country Study (August 1, 2021). Available at SSRN: https://ssrn.com/abstract=3897382 or http://dx.doi.org/10.2139/ssrn.3897382

Sile Tao

University of Alberta ( email )

Edmonton, Alberta T6G 2R3
Canada

Nicola Luigi Bragazzi (Contact Author)

York University ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

Jianhong Wu

York University - Laboratory for Industrial and Applied Mathematics ( email )

Canada

Xi'an Jiaotong University (XJTU) - The Interdisplinary Research Center for Mathematics and Life Sciences ( email )

China

Bruce Mellado

University of the Witwatersrand ( email )

1 Jan Smuts Avenue
Johannesburg, GA Gauteng 2000
South Africa

Jude Dzevela Kong

Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), York University ( email )

4700 Keele St
Toronto, ON M3J 1P3
Canada

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