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

Reno, Chiara; Lenzi, Jacopo; Navarra, Antonio; Barelli, Eleonora; Gori, Davide; Lanza, Alessandro; Валентини, Р.; Tang, Biao; Fantini, Maria Pia

doi:10.20944/preprints202004.0397.v1

Cited by 25 publications

(19 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Continuous time Markov chain models are regularly used to model transmission of diseases. To date most of the work done to model COVID-19 has used deterministic modelling which gives an approximation of the mean of the stochastic epidemic curves [12,[21][22][23]. However, the deterministic curves will miss the likely timing of the peak of incidence since averaging over values does not imply averaging over time.…”

Section: Discussionmentioning

confidence: 99%

Modeling the Effect of Lockdown Timing as a COVID-19 Control Measure in Countries with Differing Social Contacts

Oraby

Tyshenko

Maldonado

et al. 2020

Preprint

View full text Add to dashboard Cite

The application, timing, and duration of lockdown strategies during a pandemic remain poorly quantified with regards to expected public health outcomes. Previous projection models have reached conflicting conclusions about the effect of complete lockdowns on COVID-19 outcomes. We developed a stochastic continuous-time Markov chain (CTMC) model with eight states including the environment (SEAMHQRD-V), and derived a formula for the basic reproduction number, R0, for that model. Applying the R0 formula as a function in previously-published social contact matrices from 152 countries, we produced the distribution and four categories of possible R0 for the 152 countries and chose one country from each quarter as a representative for four social contact categories (Canada, China, Mexico, and Niger). The model was then used to predict the effects of lockdown timing in those four categories through the representative countries. The analysis for the effect of a lockdown was performed without the influence of the other control measures, like social distancing and mask wearing, to quantify its absolute effect. Hypothetical lockdown timing was shown to be the critical parameter in ameliorating pandemic peak incidence. More importantly, we found that well-timed lockdowns can split the peak of hospitalizations into two smaller distant peaks while extending the overall pandemic duration. The timing of lockdowns reveals that a “tunneling” effect on incidence can be achieved to bypass the peak and prevent pandemic caseloads from exceeding hospital capacity.

show abstract

Section: Discussionmentioning

confidence: 99%

Modeling the Effect of Lockdown Timing as a COVID-19 Control Measure in Countries with Differing Social Contacts

Oraby

Tyshenko

Maldonado

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Finally, further works have been trying to predict the behavior of some COVID-19 related variables through the use of exponential models as well as dynamic SIR-based models ( Chen et al., 2020 ; Fanelli and Piazza, 2020 ; Remuzzi and Remuzzi, 2020 ; Reno et al., 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Assessing correlations between short-term exposure to atmospheric pollutants and COVID-19 spread in all Italian territorial areas

Accarino

Lorenzetti

Aloisio

2021

Environmental Pollution

View full text Add to dashboard Cite

The spread of SARS-CoV-2, the beta coronavirus responsible for the current pneumonia pandemic outbreak, has been speculated to be linked to short-term and long-term atmospheric pollutants exposure. The present work has been aimed at analyzing the atmospheric pollutants concentrations ( PM 10 , PM 2.5 , NO 2 ) and spatio-temporal distribution of cases and deaths (specifically incidence, mortality and lethality rates) across the whole Italian national territory, down to the level of each individual territorial area, with the goal of checking any potential short-term correlation between these two phenomena. The data analysis has been limited to the first quarter of 2020 to reduce the lockdown-dependent biased effects on the atmospheric pollutant levels as much as possible. The analysis looked at non-linear, monotonic correlations using the Spearman non-parametric correlation index. The statistical significance of the Spearman correlations has also been evaluated. The results of the statistical analysis suggest the hypothesis of a moderate-to-strong correlation between the number of days exceeding the annual regulatory limits of PM 10 , PM 2.5 and NO 2 atmospheric pollutants and COVID-19 incidence, mortality and lethality rates for all the 107 territorial areas in Italy. A weak-to-moderate correlation seems to exist when considering the 36 territorial areas in four of the most affected regions (Lombardy, Piedmont, Emilia-Romagna and Veneto). Overall, PM 10 and PM 2.5 showed a higher non-linear correlation than NO 2 with incidence, mortality and lethality rates. As to particulate matters, PM 10 profile has been compared with the incidence rate variation that occurred in three of the most affected territorial areas in Northern Italy (i.e., Milan, Brescia, and Bergamo). All areas showed a similar PM 10 time trend but a different incidence rate variation, that was less severe in Milan compared with Brescia and Bergamo.

show abstract

“…We simulate COVID-19 spread with rapid testing and model disease outcomes in three regions in the United States and São José do Rio Preto, Brazil -the site of the clinical validation study -using publicly available data. To date, COVID-19 modeling describes the course of disease spread in response to social distancing and quarantine measures, and a previous simulation study has shown that frequent testing with accuracies less than qRT-PCR, coupled with quarantine process and social distancing, are predicted to significantly decrease infections 12,17,[23][24][25][26][27] . This is the first modeling system using publicly-available data to simulate how potential public health strategies based on testing performance, frequency, and geography impact the course of COVID-19 spread and outcomes.…”

Section: Introductionmentioning

confidence: 99%

Validating and modeling the impact of high-frequency rapid antigen screening on COVID-19 spread and outcomes

Nash¹,

Badea²,

Reddy³

et al. 2020

Preprint

View full text Add to dashboard Cite

High frequency screening of populations has been proposed as a strategy in facilitating control of the COVID-19 pandemic. We use computational modeling, coupled with clinical data from rapid antigen tests, to predict the impact of frequent viral antigen rapid testing on COVID-19 spread and outcomes. Using patient nasal or nasopharyngeal swab specimens, we demonstrate that the sensitivity/specificity of two rapid antigen tests compared to quantitative real-time polymerase chain reaction (qRT-PCR) are 80.0%/91.1% and 84.7%/85.7%, respectively; moreover, sensitivity correlates directly with viral load. Based on COVID-19 data from three regions in the United States and São José do Rio Preto, Brazil, we show that high frequency, strategic population-wide rapid testing, even at varied accuracy levels, diminishes COVID-19 infections, hospitalizations, and deaths at a fraction of the cost of nucleic acid detection via qRT-PCR. We propose large-scale antigen-based surveillance as a viable strategy to control SARS-CoV-2 spread and to enable societal re-opening.

show abstract

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

Cited by 25 publications

References 18 publications

Modeling the Effect of Lockdown Timing as a COVID-19 Control Measure in Countries with Differing Social Contacts

Modeling the Effect of Lockdown Timing as a COVID-19 Control Measure in Countries with Differing Social Contacts

Assessing correlations between short-term exposure to atmospheric pollutants and COVID-19 spread in all Italian territorial areas

Validating and modeling the impact of high-frequency rapid antigen screening on COVID-19 spread and outcomes

Contact Info

Product

Resources

About