COVID-19, flattening the curve: recommendations towards control and managing a second wave
Open accessAbstract
Flattening the coronavirus disease (COVID-19) curve has been one of the most important public health targets since the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide. In this review, we examined measures that were key to flattening the curve in countries that have succeeded in achieving this against other countries. The most consistent factors seen from studies were aggressive testing, contact tracing, social distancing, quarantine measures, and innovative technology. These factors were reported to have helped achieve drop in the number of daily new cases reported. Countries like South Korea and Australia employed extensive testing of their residents as a means of curbing the pandemic and limiting its spread. China and Spain employed tracking software and artificial intelligence (AI) in ensuring that infected individuals remained isolated for the recommended number of days and that close contacts of positive cases were tested and quarantined as well. While efforts towards developing a vaccine are still ongoing, and the possibility of a second wave in many countries, we discussed pertinent public health measures and recommendations.
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A research group in Spain developed a blockchain and AI-based app that can predict the evolution of the COVID-19 pandemic.
“For example, a research group in Spain leverages these two technologies to develop a blockchain and AI-based app that is able to predict the evolution of the COVID-19 pandemic [151].”
From Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-Like Epidemics: A Survey (2021) · cites this paper as [151]
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- Authors
- Fenemigho, I., Ukponmwan, E., Nnakwue, E. C., Udoete, I., Asuzu, C., Adaralegbe, A., & Effiong, U.
- Affiliations
- University of South Wales (GB)
- University of Benin (NG)
- University of Ibadan (NG)
- All Saints University School of Medicine (DM)
- Rutgers, The State University of New Jersey (US)
- University of Connecticut (US)
- Central Michigan University (US)
- Venue
- Journal of Global Health Reports
- Published
- 2020-08-10
- Volume
- 4
- ISSN
- 2399-1623 (ISSN-L)
- OpenAlex
- W3048428145
- Cited by
- 5
- References
- 16
- Citations by year
- 2024: 1 · 2023: 1 · 2022: 1 · 2021: 2
- FWCI
- 0.16
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Journal of Global Health Reports (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Physical Sciences › Computer Science › Information Systems › COVID-19 Digital Contact Tracing
- Social Sciences › Sociology and Political Science › COVID-19 Prevention and Impact
- Keywords
- COVID-19 pandemic, SARS-CoV-2, flattening the curve, second wave, public health measures, large-scale testing, contact tracing, social distancing, quarantine, artificial intelligence, pandemic response
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