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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: Apr 3, 2020
Open Peer Review Period: Apr 3, 2020 - Apr 13, 2020
Date Accepted: May 4, 2020
Date Submitted to PubMed: May 5, 2020
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Estimation of the Probability of Reinfection With COVID-19 by the Susceptible-Exposed-Infectious-Removed-Undetectable-Susceptible Model

Victor AO

Estimation of the Probability of Reinfection With COVID-19 by the Susceptible-Exposed-Infectious-Removed-Undetectable-Susceptible Model

JMIR Public Health Surveill 2020;6(2):e19097

DOI: 10.2196/19097

PMID: 32369029

PMCID: 7223428

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Estimation of the probability of reinfection with COVID-19 coronavirus by the SEIRUS model

  • Alexander Okhuese Victor

ABSTRACT

Background:

With sensitivity of the Polymerase Chain Reaction (PCR) test used to detect the presence of the virus in the human host, the global health community has been able to record a great number of recovered population.

Objective:

Therefore, the objective of this study was evaluate the probability of reinfection in the recovered class and the model equations which exhibits the disease-free equilibrium (E_0 ) state for COVID-19 coronavirus.

Methods:

The model differential equation were evaluated for the disease-free equilibrium for the case of reinfection as well as existence and stability criteria for the disease using the model proportions. This evaluation shows that the criteria for a locally or globally asymptotic stability with a basic reproductive number R_0=0 is satisfied. Hence, there is a chance of no secondary reinfections from the recovered population as the rate of incidence of the recovered population vanishes, that is, B=0.

Results:

With a total of about 900,000 infected cases worldwide, numerical simulations for this study was carried to complement the analytical results in investigating the effect of the implementation of quarantine and observatory procedures has on the projection of the further spread of the virus globally.

Conclusions:

As shown by the results, the proportion of infected population in the absence of curative vaccination will continue to grow globally meanwhile the recovery rate will continue slowly which therefore means that the ratio of infection to recovery rate will determine the death rate that is recorded globally and most significant for this study is the rate of reinfection by the recovered population which will decline to zero over time as the virus is cleared clinically from the system of the recovered class.


 Citation

Please cite as:

Victor AO

Estimation of the Probability of Reinfection With COVID-19 by the Susceptible-Exposed-Infectious-Removed-Undetectable-Susceptible Model

JMIR Public Health Surveill 2020;6(2):e19097

DOI: 10.2196/19097

PMID: 32369029

PMCID: 7223428

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