Epidemiological characteristics of COVID-19 cases and estimates of the reproductive numbers 1 month into the epidemic, Italy, 28 January to 31 March 2020

Abstract

Background On 20 February 2020, a locally acquired coronavirus disease (COVID-19) case was detected in Lombardy, Italy. This was the first signal of ongoing transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the country. The number of cases in Italy increased rapidly and the country became the first in Europe to experience a SARS-CoV-2 outbreak. Aim Our aim was to describe the epidemiology and transmission dynamics of the first COVID-19 cases in Italy amid ongoing control measures. Methods We analysed all RT-PCR-confirmed COVID-19 cases reported to the national integrated surveillance system until 31 March 2020. We provide a descriptive epidemiological summary and estimate the basic and net reproductive numbers by region. Results Of the 98,716 cases of COVID-19 analysed, 9,512 were healthcare workers. Of the 10,943 reported COVID-19-associated deaths (crude case fatality ratio: 11.1%) 49.5% occurred in cases older than 80 years. Male sex and age were independent risk factors for COVID-19 death. Estimates of R0 varied between 2.50 (95% confidence interval (CI): 2.18–2.83) in Tuscany and 3.00 (95% CI: 2.68–3.33) in Lazio. The net reproduction number Rt in northern regions started decreasing immediately after the first detection. Conclusion The COVID-19 outbreak in Italy showed a clustering onset similar to the one in Wuhan, China. R0 at 2.96 in Lombardy combined with delayed detection explains the high case load and rapid geographical spread. Overall, Rt in Italian regions showed early signs of decrease, with large diversity in incidence, supporting the importance of combined non-pharmacological control measures.

Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection

“…The impact of COVID-19 is heterogeneous across age groups (9)(10)(11)(12)(13). This may be driven by differences in susceptibility (9), differences in clinical manifestation (11,13) or both (10).…”

“…We considered here both effects in agreement with recent modelling estimates (10). Susceptibility by age, A σ , was parametrized from ( 9), while clinical manifestation, A sc p , was parametrized from a large-scale descriptive study of the COVID19 outbreak in Italy (13).…”

“…Younger individuals tend to have more contacts than adults or the elderly. On the other hand, a marked feature of COVID-19 is the strong age imbalance among cases (9)(10)(11)(12)(13), that may be explained by both a reduced susceptibility (9,10) and an increased rate of subclinical infections in children compared to adults (10,11,13). As subclinical cases are harder to detect, this implies that identification of cases and of their contacts Anatomy of digital contact tracing: Role of age, transmission setting, adoption and case detection may be dependent on age.…”

Isolation and genetic characterization of SARS-CoV-2 from Indian patients in a single family without H/O travel abroad

“…On several introductions / transmissions of SARS-CoV-2 in Europe, D614G mutation was identified in Italian patients with no travel history. These sequences formed a separate cluster, clade G [ 23 ] which spread to other countries including India as observed in this study.…”

Bayesian inference across multiple models suggests a strong increase in lethality of COVID-19 in late 2020 in the UK

“…This could be an indication that individuals count as infected for longer in our models than they test positive in a PCR test. Also, the fixed estimate we use for the age-dependent fraction of asymptomatic infections may be incorrect (based on early data [22], as described in our paper [8]). We note that differences in the conditional numbers of infections between models BC0 and BC1 mainly show up in the first wave.…”