Abstract
The ongoing COVID-19 pandemic has caused worldwide socioeconomic unrest, forcing governments to introduce extreme measures to reduce its spread. Being able to accurately forecast when the outbreak will hit its peak would significantly diminish the impact of the disease, as it would allow governments to alter their policy accordingly and plan ahead for the preventive steps needed such as public health messaging, raising awareness of citizens and increasing the capacity of the health system. This study investigated the accuracy of a variety of time series modeling approaches for coronavirus outbreak detection in ten different countries with the highest number of confirmed cases as of 4 May 2020. For each of these countries, six different time series approaches were developed and compared using two publicly available datasets regarding the progression of the virus in each country and the population of each country, respectively. The results demonstrate that, given data produced using actual testing for a small portion of the population, machine learning time series methods can learn and scale to accurately estimate the percentage of the total population that will become affected in the future.
Highlights
Coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has developed into a global pandemic that, as of 4 May 2020, is still in progress [1,2]
Many countries have implemented measures such as self-isolation and social distancing in order to prevent further spread [6], flattening the epidemic curve, which could prove crucial in maintaining health services to patients most in need of care either for COVID-19 or for other serious conditions [7]
104 instances were created, each representing the percentage of active coronavirus cases as a fraction of the total population for a single day in the corresponding country
Summary
Coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has developed into a global pandemic that, as of 4 May 2020, is still in progress [1,2]. Many countries have implemented measures such as self-isolation and social distancing in order to prevent further spread [6], flattening the epidemic curve, which could prove crucial in maintaining health services to patients most in need of care either for COVID-19 or for other serious conditions [7]. The ability to identify the rate at which the disease is spreading is crucial in the fight against the pandemic. Antibody tests, in development as of 6 April
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