Determination of daily reproduction numbers of SARS-CoV2 based on death cases suggests more rapid initial spread in Italy and the United States

ABSTRACT

Population density, behaviour and cultural habits strongly influence the spread of pathogens. Consequently, key epidemiological parameters may vary from country to country. Confirmed COVID-19 cases in in China have been used to estimate those parameters, that vary largely (reviewed in 1). The estimates also depend on testing frequency and case definitions that are prone to change during ongoing epidemics, providing additional uncertainties. The rise in fatal cases due to SARS-CoV2 could be a more reliable parameter, since missing of deaths is less likely. In the absence of changes in the management of severe COVID-19 cases, the rise in death cases should be proportional to the rise in virus infections. Although the fluctuating low numbers of fatal cases very early in the epidemic may lead to some uncertainty, more than 100 deaths per day are reported since 10.03.2020 in Italy and since 21.03.2020 in the US. Therefore, the dynamics of deaths were analysed to estimate the daily reproduction numbers (Rt) and the effectiveness of control measures. Thus, our analysis provides evidence that basic epidemiological parameters differ between countries to an extent compromising epidemiological predictions of the pandemic. It also suggests that suppression of spread in Italy and the US may be more difficult to achieve. Although we assume that variations in social behaviour are responsible for the different estimates of R0, selection of more rapidly spreading variants of SARS-CoV-2 cannot be excluded. Despite uncertainty in the reliability of the data used and lack of information on possible changes in the effectiveness of registration of COVID-19 deaths during the observation period, our findings should be considered as a working hypothesis demanding further investigations. As the number of deaths rapidly increases worldwide, we encourage more sophisticated modelling of the epidemic based on the dynamics of death cases by experts in the field.