Modeling neutral viral mutations in the spread of SARS-CoV-2 epidemics

Autor(es)

Marquioni, Vitor M. ^[1] ; de Aguiar, Marcus A. M. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Estadual Campinas UNICAMP, Inst Fis Gleb Wataghin, Campinas, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: PLoS One; v. 16, n. 7 JUL 29 2021.
• Citações Web of Science: 2

Resumo

Although traditional models of epidemic spreading focus on the number of infected, susceptible and recovered individuals, a lot of attention has been devoted to integrate epidemic models with population genetics. Here we develop an individual-based model for epidemic spreading on networks in which viruses are explicitly represented by finite chains of nucleotides that can mutate inside the host. Under the hypothesis of neutral evolution we compute analytically the average pairwise genetic distance between all infecting viruses over time. We also derive a mean-field version of this equation that can be added directly to compartmental models such as SIR or SEIR to estimate the genetic evolution. We compare our results with the inferred genetic evolution of SARS-CoV-2 at the beginning of the epidemic in China and found good agreement with the analytical solution of our model. Finally, using genetic distance as a proxy for different strains, we use numerical simulations to show that the lower the connectivity between communities, e.g., cities, the higher the probability of reinfection. (AU)

• Processo FAPESP: 16/01343-7 - ICTP Instituto Sul-Americano para Física Fundamental: um centro regional para física teórica
• Beneficiário: Nathan Jacob Berkovits
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 19/13341-7 - Transições de fase em modelos Derrida-Higgs finitos
• Beneficiário: Vitor Marquioni Monteiro
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 19/20271-5 - Modelos evolutivos em dinâmica de populações
• Beneficiário: Marcus Aloizio Martinez de Aguiar
• Modalidade de apoio: Auxílio à Pesquisa - Regular