Estimation of Undetected Symptomatic and Asymptomatic cases of COVID-19 Infection and prediction of its spread in USA

Abstract

The reported COVID-19 cases in the USA have crossed over 2 million, and a large number of infected cases are undetected whose estimation can be done if country-wide antibody testing is performed. In this work, we estimate this undetected fraction of the population by modeling and simulation approach. We propose a new epidemic model SIPHERD in which three categories of infection carriers Symptomatic, Purely Asymptomatic, and Exposed are considered with different transmission rates that are taken dependent on the lockdown conditions, and the detection rate of the infected carriers is taken dependent on the tests done per day. The model is first validated for Germany and South Korea and then applied for prediction of total number of confirmed, active and death, and daily new positive cases in the United States. Our study also demonstrates the possibility of a second wave of the infection if social distancing regulations are relaxed to a large extent. We estimate that around 12.7 million people are already infected, and in the absence of any vaccine, 17.7 million (range: 16.3-19.2) people, or 5.3% (range: 4.9-5.8) of the population will be infected by when the disease spread ends in the USA. We find the Infection to Fatality Ratio to be 0.93% (range: 0.85-1.01).

An epidemic model SIPHERD and its application for prediction of the spread of COVID-19 infection in India

“…S6. The parameter values related to the characteristics of the disease are discussed in more detail in [19] .…”

“…We model the evolution of the COVID-19 disease by dividing the population into different categories as listed below which is described in detail in [19] , [20] . The SIPHERD model equations for the defined entities (S,I,P,H,E,R,D) are a set of coupled ordinary differential Eqs.…”

“…In this paper, we bring out different possible ways for better control of the infection spread. We employ an improved mathematical model SIPHERD [19] for the COVID-19 pandemic embedding the purely asymptomatic infected cases and the transmission of the disease from them. The model simulations bring out the efficacy of different ways for the containment, by predicting the total number of active and confirmed cases, total deaths, and daily new positive cases considering various social distancing/lockdown conditions and the number of tests done per day.…”

Cost and social distancing dynamics in a mathematical model of COVID-19 with application to Ontario, Canada

“…The copyright holder for this this version posted October 25, 2020. ; https://doi.org/10.1101/2020.10.21.20217158 doi: medRxiv preprint [18,26]). To help restrict the model we take ρ S = 4ρ A which is a similar value as observed in [18] who compared data to Germany, South Korea, and the USA. (v) we assume that only people in the P , I S or I A classes will test positive if a test is administered.…”

“…(i) the parameters δ, σ, φ, γ, and q i are constant and the same for each social distancing class as the disease progression characteristics are unaffected by social distancing. [18,26]). To help restrict the model we take ρ S = 4ρ A which is a similar value as observed in [18] who compared data to Germany, South Korea, and the USA.…”