Modeling COVID-19: Forecasting and analyzing the dynamics of the outbreak in Hubei and Turkey

Journal of Biological Dynamics

Khan

2020

In this study, we estimate the severity of the COVID-19 outbreak in Pakistan prior to and after lockdown restrictions were eased. We also project the epidemic curve considering realistic quarantine, social distancing and possible medication scenarios. The pre-lock down value of R 0 is estimated to be 1.07 and the post lock down value is estimated to be 1.86. Using this analysis, we project the epidemic curve. We note that if no substantial efforts are made to contain the epidemic, it will peak in mid-September, 2020, with the maximum projected active cases being close to 700, 000. In a realistic, best case scenario, we project that the epidemic peaks in early to mid-July, 2020, with the maximum active cases being around 120, 000. We note that social distancing measures and medication will help flatten the curve; however, without the reintroduction of further lock down, it would be very difficult to make R 0 < 1.

Section: Introductionmentioning

confidence: 99%

Analysis and prediction of the COVID-19 outbreak in Pakistan

Journal of Biological Dynamics

Khan

2020

“…Since the outbreak many mathematical models have been proposed to estimate the growth rates and understand the transmission dynamics of COVID-19. These include phenomenological models[16, 17], stochastic models[18], both of which are very useful in the early stages of the outbreak, and mechanistic models[19, 20, 22, 23, 30] that incorporate our understanding of the transmission pathways. Imran et.al [24] and Perkins et.al [31] have used optimal control techniques to propose efficient control strategies.…”

Section: Introductionmentioning

confidence: 99%

Can medication mitigate the need for a strict lock down?: A mathematical study of control strategies for COVID-19 infection

Khan

2020

Preprint

We formulate a deterministic epidemic model to study the effects of medication on the transmission dynamics of Corona Virus Disease (COVID-19). We are especially interested in how the availability of medication could change the necessary quarantine measures for effective control of the disease. We model the transmission by extending the SEIR model to include asymptomatic, quarantined, isolated and medicated population compartments. We calculate the basic reproduction number R_0 and show that for R_0<1 the disease dies out and for R_0>1 the disease is endemic. Using sensitivity analysis we establish that R_0 is most sensitive to the rates of quarantine and medication. We also study how the effectiveness and the rate of medication along with the quarantine rate affect R_0. We devise optimal quarantine, medication and isolation strategies, noting that availability of medication reduces the duration and severity of the lock-down needed for effective disease control. Our study also reinforces the idea that with the availability of medication, while the severity of the lock downs can be eased over time some social distancing protocols need to be observed, at least till a vaccine is found. We also analyze the COVID-109 outbreak data for four different countries, in two of these, India and Pakistan the curve is still rising, and in he other two, Italy and Spain, the epidemic curve is now falling due to effective quarantine measures. We provide estimates of R_0 and the proportion of asymptomatic individuals in the population for these countries.

“…Since the outbreak many mathematical models have been proposed to estimate the growth rates and understand the transmission dynamics of COVID-19. These include phenomenological models [16,17], stochastic models [18], both of which are very useful in the early stages of the outbreak, and mechanistic models [19,20,22,23,30] that incorporate our understanding of the transmission pathways. Imran et.al [24] and Perkins et.al [31] have used optimal control techniques to propose efficient control strategies.…”

Section: Introductionmentioning

confidence: 99%

Can medication mitigate the need for a strict lock down?: A mathematical study of control strategies for COVID-19 infection

Khan³

2020

Preprint

BackgroundCOVID-19 is a pandemic that has swept across the world in 2020. To date the only effective control mechanisms were non-pharmaceutical interventions, however there have been encouraging reports regarding possible medication in the literature, with emergency approval given to some drugs in various countries.MethodsWe formulate a deterministic epidemic model to study the effects of medication on the transmission dynamics of Corona Virus Disease (COVID-19). We are especially interested in how the availability of medication could change the necessary quarantine measures for effective control of the disease. We model the transmission by extending the SEIR model to include asymptomatic, quarantined, isolated and medicated population compartments.ResultsWe calculate the basic reproduction number R0 and show that for R0<1 the disease dies out and for R0>1 the disease is endemic. Using sensitivity analysis we establish that R0 is most sensitive to the rates of quarantine and medication. We also study how the effectiveness and the rate of medication along with the quarantine rate affect R0. We devise optimal quarantine, medication and isolation strategies, noting that availability of medication reduces the duration and severity of the lock-down needed for effective disease control.ConclusionOur study also reinforces the idea that with the availability of medication, while the severity of the lock downs can be eased over time some social distancing protocols need to be observed, at least till a vaccine is found. We also analyze the COVID-19 outbreak data for four different countries, in two of these, India and Pakistan the curve is still rising, and in he other two, Italy and Spain, the epidemic curve is now falling due to effective quarantine measures. We provide estimates of R0 and the proportion of asymptomatic individuals in the population for these countries.