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In the present paper, we aimed to determine the influence of various non-pharmaceutical interventions (NPIs) enforced during the first wave of COVID-19 across countries on the spreading rate of COVID-19 during the second wave. For this purpose, we took into account national-level climatic, environmental, clinical, health, economic, pollution, social, and demographic factors. We estimated the growth of the first and second wave across countries by fitting a logistic model to daily-reported case numbers, up to the first and second epidemic peaks. We estimated the basic and effective (second wave) reproduction numbers across countries. Next, we used a random forest algorithm to study the association between the growth rate of the second wave and NPIs as well as pre-existing country-specific characteristics. Lastly, we compared the growth rate of the first and second waves of COVID-19. The top three factors associated with the growth of the second wave were body mass index, the number of days that the government sets restrictions on requiring facial coverings outside the home at all times, and restrictions on gatherings of 10 people or less. Artificial intelligence techniques can help scholars as well as decision and policy-makers estimate the effectiveness of public health policies, and implement "smart" interventions, which are as efficacious as stringent ones. [ABSTRACT FROM AUTHOR]

The coronavirus disease (COVID-19) pandemic caused unprecedented research activity all around the world but publications from Central-Eastern European countries remain scarce. Therefore, our aim was to characterise the features of the pandemic in the intensive care units (ICUs) among members of the SepsEast (Central-Eastern European Sepsis Forum) initiative. We conducted a retrospective, international, multicentre study between March 2020 and February 2021. All adult patients admitted to the ICU with pneumonia caused by COVID-19 were enrolled. Data on baseline and treatment characteristics, organ support and mortality were collected. Eleven centres from six countries provided data from 2139 patients. Patient characteristics were: median 68, [IQR 60–75] years of age; males: 67%; body mass index: 30.1 [27.0–34.7]; and 88% comorbidities. Overall mortality was 55%, which increased from 2020 to 2021 (p = 0.004). The major causes of death were respiratory (37%), cardiovascular (26%) and sepsis with multiorgan failure (21%). 1061 patients received invasive mechanical ventilation (mortality: 66%) without extracorporeal membrane oxygenation (n = 54). The rest of the patients received non-invasive ventilation (n = 129), high flow nasal oxygen (n = 317), conventional oxygen therapy (n = 122), as the highest level of ventilatory support, with mortality of 50%, 39% and 22%, respectively. This is the largest COVID-19 dataset from Central-Eastern European ICUs to date. The high mortality observed especially in those receiving invasive mechanical ventilation renders the need of establishing national–international ICU registries and audits in the region that could provide high quality, transparent data, not only during the pandemic, but also on a regular basis. [ABSTRACT FROM AUTHOR]