A Computational Model for Estimating the Progression of COVID-19 Cases in the US West and East Coasts

Yeo, Yao Yu; Yeo, Yao-Rui; Yeo, Wan-Jin

doi:10.1101/2020.03.24.20043026

Cited by 6 publications

(7 citation statements)

References 27 publications

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“…Adding more compartments allows for a refined description of specific epidemics. Such models range from SEIR 6 , 8 , 9 and SUQC 10 models of COVID-19 to models as complex as the SIDARTHE 11 model which considers susceptible, infected, diagnosed, ailing, recognized, threatened, healed and extinct compartments. As an alternative to continuous epidemic models, discrete-time SI and SIR model have also been developed 12 .…”

Section: Introductionmentioning

confidence: 99%

Age-stratified discrete compartment model of the COVID-19 epidemic with application to Switzerland

Balabdaoui

Mohr

2020

Sci Rep

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Compartmental models enable the analysis and prediction of an epidemic including the number of infected, hospitalized and deceased individuals in a population. They allow for computational case studies on non-pharmaceutical interventions thereby providing an important basis for policy makers. While research is ongoing on the transmission dynamics of the SARS-CoV-2 coronavirus, it is important to come up with epidemic models that can describe the main stages of the progression of the associated COVID-19 respiratory disease. We propose an age-stratified discrete compartment model as an alternative to differential equation based S-I-R type of models. The model captures the highly age-dependent progression of COVID-19 and is able to describe the day-by-day advancement of an infected individual in a modern health care system. The fully-identified model for Switzerland not only predicts the overall histories of the number of infected, hospitalized and deceased, but also the corresponding age-distributions. The model-based analysis of the outbreak reveals an average infection fatality ratio of 0.4% with a pronounced maximum of 9.5% for those aged ≥ 80 years. The predictions for different scenarios of relaxing the soft lockdown indicate a low risk of overloading the hospitals through a second wave of infections. However, there is a hidden risk of a significant increase in the total fatalities (by up to 200%) in case schools reopen with insufficient containment measures in place.

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Section: Introductionmentioning

confidence: 99%

Age-stratified discrete compartment model of the COVID-19 epidemic with application to Switzerland

Balabdaoui

Mohr

2020

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Adding more compartments allows for a refined description of specific epidemics. Such models range from SEIR 6,8,9 and SUQC 10 models of COVID-19 to models as complex as the SIDARTHE 11 model which considers susceptible, infected, diagnosed, ailing, recognized, threatened, healed and extinct compartments. An important feature of COVID-19 is its highly non-uniform attack of the different age strata of society.…”

mentioning

confidence: 99%

Age-stratified model of the COVID-19 epidemic to analyze the impact of relaxing lockdown measures: nowcasting and forecasting for Switzerland

Balabdaoui

Mohr

2020

Preprint

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Compartmental models enable the analysis and prediction of an epidemic including the number of infected, hospitalized and deceased individuals in a population. They allow for computational case studies on non-pharmaceutical interventions therebyproviding an important basis for policy makers. While research is ongoing on the transmission dynamics of the SARS-CoV-2 coronavirus, it is important to come up with epidemic models that can describe the main stages of the progression of the associated COVID-19 respiratory disease. We propose an age-stratified discrete compartment model as an alternative to differential equation based S-I-R type of models. The model captures the highly age-dependent progression of COVID-19 and is able to describe the day-by-day advancement of an infected individual in a modern health care system. The fully-identified model for Switzerland not only predicts the overall histories of the number of infected, hospitalized and deceased, but also the corresponding age-distributions. The model-based analysis of the outbreak reveals an average infection fatality ratio of 0.4% with a pronounced maximum of 9.5% for those aged ≥80 years. The predictions for different scenarios of relaxing the soft lockdown indicate a low risk of overloading the hospitals through a second wave of infections. However, there is a hidden risk of a significant increase in the total fatalities (by up to 200%) in case schools reopen with insufficient containment measures in place.

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“…For the modeling carried out in this work, we proposed a modification of the SEIR model (Susceptible-Exposed-Infected-Removed) [4–6]. In the model proposed here, the number of susceptible individuals S decreases according to the rate of effective contacts between the untested infected and the susceptible (β), assuming that the tested infected remain isolated according to the guidelines of the health authorities [7–9].…”

Section: Methodsmentioning

confidence: 99%

“…We estimate the proportion of tested and untested cases at ρ = 0.2 and the mortality rate at c = 0.02, according to official data for Rondônia. To simulate the statistical dispersion of the average periods of incubation (1 /α ) and infection (1/ γ ), the mean values suggested in the literature, 1/ γ = 3 and 1/ α = 5.1, were used in the Erlang distribution with equal to two, obtaining periods greater than or equal to one variable around the suggested means [6,14,15]. The model estimated the rate of effective contacts from the basic reproduction rate and the period of infection ( β = R 0 γ ).…”

Section: Methodsmentioning

confidence: 99%

A Computational Model for Estimating the Evolution of COVID-19 in Rondônia-Brazil

Dias

Machado

2020

Preprint

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In this work, the modified SEIR model was proposed to account separately for the tested and isolated cases, with severe and critical symptoms, from those not tested, with mild and moderate symptoms. Two parameters were estimated and evaluated for the cases registered in Rondônia, Brazil, between March 20 and April 22. The basic reproduction rate did not remain constant during the period, showing eventual variations due to social behavior. The results show that an increase in the proportion of testing to about 56% provided a significant decrease in confirmed cases, for the expansion of tested cases beyond the current testing criterion (20%) would help to identify and isolate also mild and moderate cases, generally referred to as asymptomatic.

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A Computational Model for Estimating the Progression of COVID-19 Cases in the US West and East Coasts

Cited by 6 publications

References 27 publications

Age-stratified discrete compartment model of the COVID-19 epidemic with application to Switzerland

Age-stratified discrete compartment model of the COVID-19 epidemic with application to Switzerland

Age-stratified model of the COVID-19 epidemic to analyze the impact of relaxing lockdown measures: nowcasting and forecasting for Switzerland

A Computational Model for Estimating the Evolution of COVID-19 in Rondônia-Brazil

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