Mese: Ottobre 2020

The first wave of the SARS-CoV-2 epidemic in Tuscany (Italy): a SI²R²D compartmental model with uncertainty evaluation

Publication date: 29/10/2020 – E&P Code:
Authors: Michela Baccini1, Giulia Cereda1, Cecilia Viscardi1

Abstract: With the aim of studying the spread of the SARS-CoV-2 infection in the Tuscany region of Italy during the first epidemic wave (from February to June 2020), we define a compartmental model which accounts for both detected and undetected infections and assumes that only notified cases can die. We estimate the initial infection and case fatality rates and the basic reproduction number, modeled as a time-varying function, by calibrating on the cumulative daily number of observed deaths and notified infected, after fixing to plausible values the other model parameters to assure identifiability. The uncertainty of the estimates is quantified by a parametric bootstrap procedure and a Global Sensitivity Analysis (GSA) based on the Sobol’s variance decomposition is performed to assess the sensitivity of the estimates to changes in the values of the fixed parameters. According to our results, the basic reproduction number drops from an initial value of 6.055 to 0 at the end of the national lockdown, then it grows again, but remaining under 1. At the beginning of the epidemic, the case and the infection fatality rates are estimated to be 13.1% and 2.3%, respectively. Among the parameters considered as fixed, the average time from infection to recovery for the not notified infected appears to be the most impacting one on the model estimates. The probability for an infected to be notified has a relevant impact on the infection fatality rate and on the shape of the epidemic curve. This stresses the need of collecting information on these parameters to better understand the phenomenon and get reliable predictions.

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Pool testing on random and natural clusters of individuals: optimisation of SARS-CoV-2 surveillance in the presence of low viral load samples

Publication date: 23/10/2020 – E&P Code:
Authors: Michela Baccini1,2, Alessandra Mattei1,2, Irene Paganini3, Emilia Rocco1,2, Cristina Sani3, Giulia Vannucci1,2, Simonetta Bisanzi3, Elena Burroni3, Marco Peluso3, Armelle Munnia3, Filippo Cellai3, Giampaolo Pompeo3, Laura Micio3, Jessica Viti3, Fabrizia Mealli1,2, Francesca Carozzi3Sottomesso alla peer review sulla rivista Epidemiologia&Prevenzione

Abstract: Facing the SARS-CoV-2 epidemic requires intensive testing on the population to early identify and isolate infected subjects. During the emergency phase of the epidemic, RT-qPCR on nasopharyngeal (NP) swabs, which is the most reliable technique to detect ongoing infections, exhibited limitations due to availability of reagents and budget constraints. This stressed the need to develop screening procedures requiring fewer resources and suitable to be extended to larger proportions of the population. RT-qPCR on pooled samples from individual NP swabs seems to be a promising technique to improve surveillance.
We performed preliminary experimental analyses aimed to investigate the performance of pool testing on samples with low viral load and we evaluated through Monte Carlo (MC) simulations alternative screening protocols based on sample pooling, tailored to contexts characterized by different infection prevalence. We focused on the role of pool size and the opportunity to take advantage of natural clustering structure in the population, e.g. families, school classes, hospital rooms.
Despite the use of a limited number of specimens, our results suggest that, while high viral load samples seem to be detectable even in a pool with 29 negative samples, positive specimens with low viral load may be masked by the negative samples, unless smaller pools are used. The results of MC simulations confirm that pool testing is useful in contexts where the infection prevalence is low. The gain of pool testing in saving resources can be very high, and can be optimized by selecting appropriate group sizes. Exploiting natural groups makes it convenient the definition of larger pools and potentially overcomes the issue of low viral load samples by increasing the probability of identifying more than one positive in the same pool.

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Effect of timing of implementation of the lockdown on the number of deaths for COVID-19 in four European countries

Publication date: 20/10/2020 – E&P Code:
Authors: Raffaele Palladino1,2,3, Jordy Bollon4, Luca Ragazzoni4,5, Francesco Barone-Adesi4,5

Abstract: Background: Lockdown in France, Italy, Spain and United Kingdom, the four European countries which have been impacted the most by the COVID-19 emergency, was enforced 13 to 16 days after the one in Hubei, when normalizing for the time when the outbreak hit 50 cases in all countries. This prompts the question on how many deaths for COVID-19 could have been avoided during the early phase of the pandemic, had containment measures in European countries aligned in timing with those adopted in China.
Methods: We modeled the daily number of COVID-19 deaths in France, Italy, Spain, United Kingdom and we estimated the effect of the national lockdown implementing an interrupted time series analysis. Then, we created four separate counterfactual scenario by predicting the daily number of deaths that would have been observed in the four countries if the lockdown had been implemented at the same time as in Hubei. Finally, we estimated the relative change in the number of total deaths in the counterfactual scenario, compared to the observed one.
Results: If an early lockdown had been implemented, the death toll would have been 2461, 6769, 6792 and 4071, corresponding to a 92% (95%CI: 86% to 95%), 81% (95%CI: 77% to 84%), 78% (95%CI: 62% to 86%) and 90% (95%CI: 88% to 92%) relative reduction, as compared with observed data.
Conclusions: We found that a more rapid and homogeneous response would have avoided a substantial number of deaths. Our results underline the need of strengthening public health emergency preparedness at national and global level.

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