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• Asymptomatic patients with COVID-19 tend to be younger and may be more socially active. • Laboratory findings in most asymptomatic cases were unremarkable. • Around half of the cases had lung opacities, most frequently ground glass opacities. • Patients with normal CT were younger than patients with abnormal CT. Coronavirus Disease 2019 (COVID-19) is characterized by an unpredictable disease course, ranging from asymptomatic to severe, life-threatening infections. Asymptomatic COVID-19 infections have been described, and the aim of this systematic review was to summarise their presentation forms. We searched PubMed® and Google® (1 December 2019 to 29 March 2020) and extracted age, laboratory findings, and computed tomography (CT) scans. Pooled incidence rates of clinical characteristics were analyzed using random-effect models. In total, 506 patients from 34 studies (68 single cases and 438 from case-series) with an asymptomatic course were identified. Patients with normal radiology were younger (19.59 ± 17.17 years) than patients with abnormal radiology (39.14 ± 26.70 years) (p -value = 0.013). Despite being asymptomatic, CT investigations revealed abnormalities in 62.2% of the cases; ground-glass opacities were most frequently observed (43.09% by meta-analysis). Most studies reported normal laboratory findings (61.74% by meta-analysis). More than half of the patients without any symptoms present with CT abnormalities. Asymptomatic patients may be contagious and thus a potential source of transmission of COVID-19. [ABSTRACT FROM AUTHOR]

• Worldwide public interest in COVID-19 increased when numbers of newly infected patients started to increase exponentially in China. • The peak of worldwide interest was mid of March 2020 shortly after COVID-19 was declared a pandemic. • Public interest in COVID-19 correlates with the number of newly reported COVID-19 cases, with highest interest observed on average 11.5 days before the peak of newly reported COVID-19 cases. To assess the association of public interest in coronavirus infections with the actual number of infected cases for selected countries across the globe. We performed a Google TrendsTM search for "Coronavirus" and compared Relative Search Volumes (RSV) indices to the number of reported COVID-19 cases by the European Center for Disease Control (ECDC) using time-lag correlation analysis. Worldwide public interest in Coronavirus reached its first peak end of January when numbers of newly infected patients started to increase exponentially in China. The worldwide Google TrendsTM index reached its peak on the 12th of March 2020 at a time when numbers of infected patients started to increase in Europe and COVID-19 was declared a pandemic. At this time the general interest in China but also the Republic of Korea has already been significantly decreased as compared to end of January. Correlations between RSV indices and number of new COVID-19 cases were observed across all investigated countries with highest correlations observed with a time lag of −11.5 days, i.e. highest interest in coronavirus observed 11.5 days before the peak of newly infected cases. This pattern was very consistent across European countries but also holds true for the US. In Brazil and Australia, highest correlations were observed with a time lag of −7 days. In Egypt the highest correlation is given with a time lag of 0, potentially indicating that in this country, numbers of newly infected patients will increase exponentially within the course of April. Public interest indicated by RSV indices can help to monitor the progression of an outbreak such as the current COVID-19 pandemic. Public interest is on average highest 11.5 days before the peak of newly infected cases. [ABSTRACT FROM AUTHOR]

• Estimating the coronavirus disease 2019 (COVID-19) pandemic's case fatality rate (CFR) has been the focus and interest of many stakeholders as it plays a key role in understanding this pandemic and guides appropriate responses and efficient mitigation strategies. • The traditional cumulative CFR estimation is static; however, it is a dynamic value. Moreover, the estimation of the global CFR of COVID-19 according to either the calendar date or the days since the outbreak of the first confirmed case, is different. • We propose that the estimated kinetics of CFR according to days since the outbreak of the first confirmed case could be a useful predictor to design COVID-19 mitigation strategies. Since the outbreak of the coronavirus disease 2019 (COVID-19) in December of 2019 in China, estimating the pandemic's case fatality rate (CFR) has been the focus and interest of many stakeholders. In this manuscript, we prove that the method of using the cumulative CFR is static and does not reflect the trend according to the daily change per unit of time. A proportion meta-analysis was carried out on the CFR in every country reporting COVID-19 cases. Based on these results, we performed a meta-analysis for a global COVID-19 CFR. Each analysis was performed using two different calculations of CFR: according to the calendar date and according to the days since the outbreak of the first confirmed case. We thus explored an innovative and original calculation of CFR, concurrently based on the date of the first confirmed case as well as on a daily basis. For the first time, we showed that using meta-analyses according to the calendar date and days since the outbreak of the first confirmed case, were different. We propose that a CFR according to days since the outbreak of the first confirmed case might be a better predictor of the current CFR of COVID-19 and its kinetics. [ABSTRACT FROM AUTHOR]