| Texto completo | |
| Autor(es): |
Justo Arevalo, Santiago
[1, 2]
;
Zapata Sifuentes, Daniela
[2]
;
Huallpa, Cesar J.
[3]
;
Landa Bianchi, Gianfranco
[2]
;
Castillo Chavez, Adriana
[2]
;
Garavito-Salini Casas, Romina
[2]
;
Uribe Calampa, Carmen Sofia
[2]
;
Uceda-Campos, Guillermo
[1, 4]
;
Pineda Chavarria, Roberto
[2]
Número total de Autores: 9
|
| Afiliação do(s) autor(es): | [1] Univ Sao Paulo, Inst Chem, Dept Biochem, Sao Paulo - Brazil
[2] Univ Ricardo Palma, Fac Ciencias Biol, Lima - Peru
[3] Univ Nacl Agr Molina, Fac Ciencias, Lima - Peru
[4] Univ Nacl Pedro Ruiz Gallo, Fac Ciencias Biol, Lambayeque - Peru
Número total de Afiliações: 4
|
| Tipo de documento: | Artigo Científico |
| Fonte: | SCIENTIFIC REPORTS; v. 11, n. 1 SEP 7 2021. |
| Citações Web of Science: | 0 |
| Resumo | |
Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This disease has spread globally, causing more than 161.5 million cases and 3.3 million deaths to date. Surveillance and monitoring of new mutations in the virus' genome are crucial to our understanding of the adaptation of SARS-CoV-2. Moreover, how the temporal dynamics of these mutations is influenced by control measures and non-pharmaceutical interventions (NPIs) is poorly understood. Using 1,058,020 SARS-CoV-2 from sequenced COVID-19 cases from 98 countries (totaling 714 country-month combinations), we perform a normalization by COVID-19 cases to calculate the relative frequency of SARS-CoV-2 mutations and explore their dynamics over time. We found 115 mutations estimated to be present in more than 3% of global COVID-19 cases and determined three types of mutation dynamics: high-frequency, medium-frequency, and low-frequency. Classification of mutations based on temporal dynamics enable us to examine viral adaptation and evaluate the effects of implemented control measures in virus evolution during the pandemic. We showed that medium-frequency mutations are characterized by high prevalence in specific regions and/or in constant competition with other mutations in several regions. Finally, taking N501Y mutation as representative of high-frequency mutations, we showed that level of control measure stringency negatively correlates with the effective reproduction number of SARS-CoV-2 with high-frequency or not-high-frequency and both follows similar trends in different levels of stringency. (AU) | |
| Processo FAPESP: | 15/13318-4 - Engenharia estrutural do sítio ativo de diguanilato ciclases (domínios GGDEF) para a produção de novos segundos mensageiros |
| Beneficiário: | Santiago Justo Arevalo |
| Modalidade de apoio: | Bolsas no Brasil - Doutorado Direto |