tetano
Editor, Senior Moderator
J Clin Med
. 2020 May 15;9(5):E1492.
doi: 10.3390/jcm9051492.
Forecasting COVID-19-Associated Hospitalizations Under Different Levels of Social Distancing in Lombardy and Emilia-Romagna, Northern Italy: Results From an Extended SEIR Compartmental Model
Chiara Reno[SUP] 1 [/SUP], Jacopo Lenzi[SUP] 1 [/SUP], Antonio Navarra[SUP] 2 [/SUP], Eleonora Barelli[SUP] 3 [/SUP], Davide Gori[SUP] 1 [/SUP], Alessandro Lanza[SUP] 2 4 [/SUP], Riccardo Valentini[SUP] 2 5 [/SUP], Biao Tang[SUP] 6 7 [/SUP], Maria Pia Fantini[SUP] 1 [/SUP]
Affiliations
Abstract
The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of 17 April 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world's centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we used a Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model, which encompasses compartments relevant to public health interventions such as quarantine. A new compartment L was added to the model for isolated infected population, i.e., individuals tested positives that do not need hospital care. We found that in Lombardy restrictive containment measures should be prolonged at least until early July to avoid a resurgence of hospitalizations; on the other hand, in Emilia-Romagna the number of hospitalized cases could be kept under a reasonable amount with a higher contact rate. Our results suggest that territory-specific forecasts under different scenarios are crucial to enhance or take new containment measures during the epidemic.
Keywords: COVID-19; SARS-CoV-2; SEIR model; coronavirus; forecasting; lockdown; mathematical modelling; pandemic; public health intervention; resurgence.
. 2020 May 15;9(5):E1492.
doi: 10.3390/jcm9051492.
Forecasting COVID-19-Associated Hospitalizations Under Different Levels of Social Distancing in Lombardy and Emilia-Romagna, Northern Italy: Results From an Extended SEIR Compartmental Model
Chiara Reno[SUP] 1 [/SUP], Jacopo Lenzi[SUP] 1 [/SUP], Antonio Navarra[SUP] 2 [/SUP], Eleonora Barelli[SUP] 3 [/SUP], Davide Gori[SUP] 1 [/SUP], Alessandro Lanza[SUP] 2 4 [/SUP], Riccardo Valentini[SUP] 2 5 [/SUP], Biao Tang[SUP] 6 7 [/SUP], Maria Pia Fantini[SUP] 1 [/SUP]
Affiliations
- PMID: 32429121
- DOI: 10.3390/jcm9051492
Abstract
The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of 17 April 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world's centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we used a Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model, which encompasses compartments relevant to public health interventions such as quarantine. A new compartment L was added to the model for isolated infected population, i.e., individuals tested positives that do not need hospital care. We found that in Lombardy restrictive containment measures should be prolonged at least until early July to avoid a resurgence of hospitalizations; on the other hand, in Emilia-Romagna the number of hospitalized cases could be kept under a reasonable amount with a higher contact rate. Our results suggest that territory-specific forecasts under different scenarios are crucial to enhance or take new containment measures during the epidemic.
Keywords: COVID-19; SARS-CoV-2; SEIR model; coronavirus; forecasting; lockdown; mathematical modelling; pandemic; public health intervention; resurgence.