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Real-Time Analysis of Predictors of COVID-19 Infection Spread in Countries in the European Union Through a New Tool.
Balogh, Aniko; Harman, Anna; Kreuter, Frauke.
  • Balogh A; School of Social Sciences and Mannheim Business School, University of Mannheim, Mannheim, Germany.
  • Harman A; TÁRKI Social Research Institute, Budapest, Hungary.
  • Kreuter F; School of Social Sciences and Mannheim Business School, University of Mannheim, Mannheim, Germany.
Int J Public Health ; 67: 1604974, 2022.
Article in English | MEDLINE | ID: covidwho-2080314
ABSTRACT

Objectives:

Real-time data analysis during a pandemic is crucial. This paper aims to introduce a novel interactive tool called Covid-Predictor-Tracker using several sources of COVID-19 data, which allows examining developments over time and across countries. Exemplified here by investigating relative effects of vaccination to non-pharmaceutical interventions on COVID-19 spread.

Methods:

We combine >100 indicators from the Global COVID-19 Trends and Impact Survey, Johns Hopkins University, Our World in Data, European Centre for Disease Prevention and Control, National Centers for Environmental Information, and Eurostat using random forests, hierarchical clustering, and rank correlation to predict COVID-19 cases.

Results:

Between 2/2020 and 1/2022, we found among the non-pharmaceutical interventions "mask usage" to have strong effects after the percentage of people vaccinated at least once, followed by country-specific measures such as lock-downs. Countries with similar characteristics share ranks of infection predictors. Gender and age distribution, healthcare expenditures and cultural participation interact with restriction measures.

Conclusion:

Including time-aware machine learning models in COVID-19 infection dashboards allows to disentangle and rank predictors of COVID-19 cases per country to support policy evaluation. Our open-source tool can be updated daily with continuous data streams, and expanded as the pandemic evolves.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines Limits: Humans Language: English Journal: Int J Public Health Journal subject: Public Health Year: 2022 Document Type: Article Affiliation country: Ijph.2022.1604974

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines Limits: Humans Language: English Journal: Int J Public Health Journal subject: Public Health Year: 2022 Document Type: Article Affiliation country: Ijph.2022.1604974