Published on in Vol 6, No 4 (2020): Oct-Dec

Preprints (earlier versions) of this paper are available at https://www.medrxiv.org/content/10.1101/2020.06.03.20120113v1, first published .
Reinfection with SARS-CoV-2: Discrete SIR (Susceptible, Infected, Recovered) Modeling Using Empirical Infection Data

Reinfection with SARS-CoV-2: Discrete SIR (Susceptible, Infected, Recovered) Modeling Using Empirical Infection Data

Reinfection with SARS-CoV-2: Discrete SIR (Susceptible, Infected, Recovered) Modeling Using Empirical Infection Data

Authors of this article:

Andrew McMahon1 Author Orcid Image ;   Nicole C Robb1, 2 Author Orcid Image

Journals

  1. Shapiro M, Karim F, Muscioni G, Augustine A. Adaptive Susceptible-Infectious-Removed Model for Continuous Estimation of the COVID-19 Infection Rate and Reproduction Number in the United States: Modeling Study. Journal of Medical Internet Research 2021;23(4):e24389 View
  2. Kröger M, Turkyilmazoglu M, Schlickeiser R. Explicit formulae for the peak time of an epidemic from the SIR model. Which approximant to use?. Physica D: Nonlinear Phenomena 2021;425:132981 View
  3. Nitipir C, Parosanu A, Olaru M, Popa A, Pirlog C, Iaciu C, Vrabie R, Stanciu M, Oprescu‑Macovei A, Bumbacea D, Negrei C, Orlov‑Slavu C. Infection and reinfection with SARS‑CoV‑2 in cancer patients: A cohort study. Experimental and Therapeutic Medicine 2022;23(6) View
  4. Hawkes M, Lee B, Kanji J, Zelyas N, Wong K, Barton M, Mukhi S, Robinson J. Seasonality of Respiratory Viruses at Northern Latitudes. JAMA Network Open 2021;4(9):e2124650 View
  5. Boaventura V, Grave M, Cerqueira-Silva T, Carreiro R, Pinheiro A, Coutinho A, Barral Netto M. Syndromic Surveillance Using Structured Telehealth Data: Case Study of the First Wave of COVID-19 in Brazil. JMIR Public Health and Surveillance 2023;9:e40036 View
  6. Deng B, Niu Y, Xu J, Rui J, Lin S, Zhao Z, Yu S, Guo Y, Luo L, Chen T, Li Q. Mathematical Models Supporting Control of COVID-19. China CDC Weekly 2022;4(40):895 View
  7. Giacopelli G. A Full-Scale Agent-Based Model to Hypothetically Explore the Impact of Lockdown, Social Distancing, and Vaccination During the COVID-19 Pandemic in Lombardy, Italy: Model Development. JMIRx Med 2021;2(3):e24630 View
  8. Arruda E, Das S, Dias C, Pastore D, Khudyakov Y. Modelling and optimal control of multi strain epidemics, with application to COVID-19. PLOS ONE 2021;16(9):e0257512 View
  9. Guan J, Zhao Y, Wei Y, Shen S, You D, Zhang R, Lange T, Chen F. Transmission dynamics model and the coronavirus disease 2019 epidemic: applications and challenges. Medical Review 2022;2(1):89 View
  10. Mundagowa P, Tozivepi S, Chiyaka E, Mukora-Mutseyekwa F, Makurumidze R, Sobh E. Assessment of COVID-19 vaccine hesitancy among Zimbabweans: A rapid national survey. PLOS ONE 2022;17(4):e0266724 View
  11. Yortsos Y, Chang J. A Model for Reinfections and the Transition of Epidemics. Viruses 2023;15(6):1340 View
  12. Tamilalagan P, Krithika B, Manivannan P, Karthiga S. Is reinfection negligible effect in COVID‐19? A mathematical study on the effects of reinfection in COVID‐19. Mathematical Methods in the Applied Sciences 2023;46(18):19115 View
  13. Thomopoulos V, Tsichlas K. An Agent-Based Model for Disease Epidemics in Greece. Information 2024;15(3):150 View
  14. Massard M, Saussereau B, Chirouze C, Lepiller Q, Eftimie R, Perasso A. Modelling and investigating memory immune responses in infectious disease. Application to influenza a virus and sars-cov-2 reinfections. Infectious Disease Modelling 2025;10(1):163 View