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Advisor(s)
Abstract(s)
The use of artificial neural networks (ANNs) is a great contribution to medical studies
since the application of forecasting concepts allows for the analysis of future diseases propagation.
In this context, this paper presents a study of the new coronavirus SARS-COV-2 with a focus on
verifying the virus propagation associated with mitigation procedures and massive vaccination
campaigns. There were two proposed methodologies in making predictions 28 days ahead for the
number of new cases, deaths, and ICU patients of five European countries: Portugal, France, Italy,
the United Kingdom, and Germany. A case study of the results of massive immunization in Israel
was also considered. The data input of cases, deaths, and daily ICU patients was normalized to
reduce discrepant numbers due to the countries’ size and the cumulative vaccination values by
the percentage of population immunized (with at least one dose of the vaccine). As a comparative
criterion, the calculation of the mean absolute error (MAE) of all predictions presents the best
methodology, targeting other possibilities of use for the method proposed. The best architecture
achieved a general MAE for the 1-to-28-day ahead forecast, which is lower than 30 cases, 0.6 deaths,
and 2.5 ICU patients per million people.
Description
Keywords
Time series prediction ANN forecasting New coronavirus COVID-19 prediction cases COVID-19 prediction ICU COVID-19 vaccination COVID-19 in Europe COVID-19 in Israel COVID-19 wearing of face mask
Citation
Carvalho, Kathleen; Vicente, João Paulo; Jakovljevic, Mihajlo; Teixeira, João Paulo (2021). Analysis and forecasting incidence, intensive care unit admissions, and projected mortality attributable to COVID-19 in Portugal, the UK, Germany, Italy, and France: predictions for 4 weeks ahead. Bioengineering. ISSN 2306-5354. 8:6, p. 1-19