| Popis: |
The novel Coronavirus SARS-CoV-2 (CoV) has induced a worldwide pandemic, notably in Italy, one of the worst-hit countries in Europe, which witnessed a death toll unseen in the recent past. There are potentially many factors, such as infections from undetected index cases, early vs late testing strategies, limited health care facilities etc., that might have aggravated the COVID-19 situation in Italy. We developed a COVID-19 specific infection epidemic model composed of susceptible (S), exposed (E), carrier (C), infected (I), recovery (R) and dead (D) (SECIRD), specifically parameterized for Italy to disentangle the impact of these factors and their implications on infection dynamics to help planning an effective control strategy for a possible second wave. Our model discriminates between detected infected and undetected individuals who played a crucial role in the disease spreading and is not well addressed by classical SEIR-like transmission models. We first estimated the number of undetected infections through a Bayesian Markov Chain Monte Carlo (MCMC) framework, which ranges from ∼ 7 to ∼ 22 fold higher than reported infections, depending upon regions. We exploited this information to evaluate the impact of the undetected component on the evolution of the pandemic and the benefits of an enhanced testing strategy. In high testing regions like Veneto, 18% of all infections resulted in hospitalization, while for Lombardia and Piemonte, it is 25% and 27%, respectively. We investigated the impact of an overwhelmed health care system upon death toll by applying hospital and intensive care unit (ICU) capacities in the SECIRD model, and we estimated a 10% reduction in death in Lombardia, the worst hit region, if a higher number of hospital facilities had been available since the beginning. Adopting a combined strategy of rapid early and targeted testing (∼ 10 fold) with increased hospital capacity would help in avoiding bottlenecks affecting the health care system. Our results demonstrate that the early testing would have a strong impact on the overall hospital accessibility and, hence, upon death toll (∼20% to 50% reduction) and could have mitigated the lack of facilities at the crucial middle stage of the epidemic. |
