Estimation of Infection Rate and Predictions of Disease Spreading Based on Initial Individuals Infected With COVID-19

Abstract

We consider the pandemic spread of COVID-19 in selected countries after the outbreak of the SARS-CoV-2 coronavirus in Wuhan City, China. We estimated the infection rate and the initial individuals infected with COVID-19 by using officially reported data from the early stages of the epidemic for a model of susceptible (S), infectible (I), quarantined (Q), and officially confirmed recovered (R k) populations (the so-called SIQR k model). In the officially reported data, we know the number of quarantined cases and the officially reported number of recovered cases. We cannot know about recovered cases from asymptomatic patients. In the SIQR k model, we can estimate the parameters and the initial infections (confirmed cases + asymptomatic cases) from fitted values. We obtained an infection rate in the range β = 0.233 ∼ 0.462, a basic reproduction number of R o = 1.8 ∼ 3.5, and the initial number of infected individuals, I (0) = 10 ∼ 8409, for selected countries. By using fitting parameters, we estimated that the maximum time span of the infection was around 50 days in Germany when the government invoked the quarantine policy. The disease is expected to subside about 6 months after the first patients are found.

Towards predicting COVID-19 infection waves: A random-walk Monte Carlo simulation approach

“…The incubation period of the coronavirus disease (after which symptoms develop) for infected individuals is found to be in the range of 8.2–15.6 days at the percentile level [30] . Furthermore, recent studies have shown that COVID-19 recovery times have an average value of about 25–28 days [31] , [32] . Given that these recovery times are evaluated after symptoms develop, a total of 35 days after infection is a reasonably accurate estimate.…”

Comprehensive Survey of Using Machine Learning in the COVID-19 Pandemic

“…Since the first confirmed case in 2019, the confirmed COVID-19 cases in all world were rapidly increased, which reached 86.7 million cases, including 1.87 million deaths by January 2021. Determining the future severity of the outbreak is considered one of the main keys to plan against this pandemic [ 85 , 86 ]. In this subsection, we survey the studies that are concerned with analyzing the epidemic status, measure the reproduction number and exponential growth using statistical and DL models.…”

Stability analysis of SEIR model related to efficiency of vaccines for COVID-19 situation

“…The recovered rate is based on 14 days recovery with 96% recovered; i.e., . Initial/Parameter Case I/Reference Case II/Reference S(0) 0.97286 [12] 0.994 [12] E(0)+I(0) 0.00905 [41] 3.813 × 10 −4 [41] R(0) 0.01809 [41] 5.569 × 10 −3 [41] β 0.462 [42] 0.32 [43] α 1/11.5 per day [22] 1/11.5 per day [22] γ 0.0686 per day [12] 0.0686 per day [12] b 0 3.178 × 10 −5 per day [44] 4.893 × 10 −5 per day [45] d 0 2.377 × 10 −5 per day [46] 1.992 × 10 −5 per day [47] d 1 2.585 × 10 −5 per day [12] 2.021 × 10 −5 per day [41] d 2 2.585 × 10 −5 per day [12] 2.021 × 10 −5 per day [41] …”