Comparative Reconstruction of SARS-CoV-2 transmission in three African countries using a mathematical model integrating immunity data.

Objectives: Africa has experienced fewer coronavirus disease 2019 (COVID-19) cases and deaths than other regions, with a contrasting epidemiological situation between countries, raising questions regarding the determinants of disease spread in Africa. Method: We built a susceptible-exposed-infected-recovered model including COVID-19 mortality data where recovery class is structured by specific immunization and modeled by a partial differential equation considering the opposed effects of immunity decline and immunization. This model was applied to Tunisia, Senegal, and Madagascar. Finding: Senegal and Tunisia experienced two epidemic phases. Initially, infections emerged in naive individuals and were limited by social distancing. Variants of concern (VOCs) were also introduced. The second phase was characterized by successive epidemic waves driven by new VOCs that escaped host immunity. Meanwhile, Madagascar demonstrated a different profile, characterized by longer intervals between epidemic waves, increasing the pool of susceptible individuals who had lost their protective immunity. The impact of vaccination in Tunisia and Senegal on model parameters was evaluated. Interpretation: Loss of immunity and vaccination-induced immunity have played crucial role in controlling the African pandemic. Severe acute respiratory syndrome coronavirus 2 has become endemic now and will continue to circulate in African populations. However, previous infections provide significant protection against severe diseases, thus providing a basis for future vaccination strategies.

[1]  Reed J. D. Sorensen,et al.  Past SARS-CoV-2 infection protection against re-infection: a systematic review and meta-analysis , 2023, The Lancet.

[2]  Sébastien Bourdin,et al.  Spatio-temporal evolution of the COVID-19 across African countries , 2022, Frontiers in Public Health.

[3]  O. Faye,et al.  First wave COVID-19 pandemic in Senegal: Epidemiological and clinical characteristics , 2022, PloS one.

[4]  M. Hsairi,et al.  Hospital bed capacity across in Tunisia hospital during the first 4 waves of the COVID-19 pandemic: A descriptive analysis , 2022, Infectious Medicine.

[5]  H. Triki,et al.  Molecular Epidemiology of SARS-CoV-2 in Tunisia (North Africa) through Several Successive Waves of COVID-19 , 2022, Viruses.

[6]  Z. Randriamanantany,et al.  Seroprevalence of ancestral and Beta SARS-CoV-2 antibodies in Malagasy blood donors , 2021, The Lancet Global Health.

[7]  A. Fontanet,et al.  Evolution of antibody responses up to 13 months after SARS-CoV-2 infection and risk of reinfection , 2021, EBioMedicine.

[8]  Saúl Pérez-González,et al.  Epidemiological models and COVID-19: a comparative view , 2021, History and Philosophy of the Life Sciences.

[9]  J. Héraud,et al.  SARS-CoV-2 antibody seroprevalence follow-up in Malagasy blood donors during the 2020 COVID-19 Epidemic , 2021, EBioMedicine.

[10]  Hannah Ritchie,et al.  A global database of COVID-19 vaccinations , 2021, Nature Human Behaviour.

[11]  Y. Kawaoka,et al.  Antibody titers against SARS-CoV-2 decline, but do not disappear for several months , 2021, EClinicalMedicine.

[12]  Bjoern Peters,et al.  Immunological memory to SARS-CoV-2 assessed for up to 8 months after infection , 2021, Science.

[13]  S. Jordan,et al.  Innate and adaptive immune responses to SARS‐CoV‐2 in humans: relevance to acquired immunity and vaccine responses , 2020, Clinical and experimental immunology.

[14]  M. Nussenzweig,et al.  Evolution of Antibody Immunity to SARS-CoV-2 , 2020, bioRxiv.

[15]  A. Iafrate,et al.  Persistence and decay of human antibody responses to the receptor binding domain of SARS-CoV-2 spike protein in COVID-19 patients , 2020, Science Immunology.

[16]  J. Scott,et al.  Seroprevalence of anti–SARS-CoV-2 IgG antibodies in Kenyan blood donors , 2020, Science.

[17]  Otto O. Yang,et al.  Rapid Decay of Anti–SARS-CoV-2 Antibodies in Persons with Mild Covid-19 , 2020, The New England journal of medicine.

[18]  M. Hernán,et al.  Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study , 2020, The Lancet.

[19]  Sang Woo Park,et al.  Modeling shield immunity to reduce COVID-19 epidemic spread , 2020, Nature Medicine.

[20]  R. Berisio,et al.  A Structural View of SARS-CoV-2 RNA Replication Machinery: RNA Synthesis, Proofreading and Final Capping , 2020, Cells.

[21]  Gergely Röst,et al.  Temporal evolution of immunity distributions in a population with waning and boosting , 2018, bioRxiv.

[22]  M. Buchmeier,et al.  Coronavirus Spike Proteins in Viral Entry and Pathogenesis , 2001, Virology.

[23]  L. White,et al.  Microparasite population dynamics and continuous immunity , 1998, Proceedings of the Royal Society of London. Series B: Biological Sciences.