Dynamic transmission modeling of COVID-19 to support decision-making in Brazil: A scoping review in the pre-vaccine era.
Brazil was one of the countries most affected during the first year of the COVID-19 pandemic, in a pre-vaccine era, and mathematical and statistical models were used in decision-making and public policies to mitigate and suppress SARS-CoV-2 dispersion. In this article, we intend to overview the mode...
Saved in:
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2023-01-01
|
| Series: | PLOS Global Public Health |
| Online Access: | https://doi.org/10.1371/journal.pgph.0002679 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832539973142708224 |
|---|---|
| author | Gabriel Berg de Almeida Lorena Mendes Simon Ângela Maria Bagattini Michelle Quarti Machado da Rosa Marcelo Eduardo Borges José Alexandre Felizola Diniz Filho Ricardo de Souza Kuchenbecker Roberto André Kraenkel Cláudia Pio Ferreira Suzi Alves Camey Carlos Magno Castelo Branco Fortaleza Cristiana Maria Toscano |
| author_facet | Gabriel Berg de Almeida Lorena Mendes Simon Ângela Maria Bagattini Michelle Quarti Machado da Rosa Marcelo Eduardo Borges José Alexandre Felizola Diniz Filho Ricardo de Souza Kuchenbecker Roberto André Kraenkel Cláudia Pio Ferreira Suzi Alves Camey Carlos Magno Castelo Branco Fortaleza Cristiana Maria Toscano |
| author_sort | Gabriel Berg de Almeida |
| collection | DOAJ |
| description | Brazil was one of the countries most affected during the first year of the COVID-19 pandemic, in a pre-vaccine era, and mathematical and statistical models were used in decision-making and public policies to mitigate and suppress SARS-CoV-2 dispersion. In this article, we intend to overview the modeling for COVID-19 in Brazil, focusing on the first 18 months of the pandemic. We conducted a scoping review and searched for studies on infectious disease modeling methods in peer-reviewed journals and gray literature, published between January 01, 2020, and June 2, 2021, reporting real-world or scenario-based COVID-19 modeling for Brazil. We included 81 studies, most corresponding to published articles produced in Brazilian institutions. The models were dynamic and deterministic in the majority. The predominant model type was compartmental, but other models were also found. The main modeling objectives were to analyze epidemiological scenarios (testing interventions' effectiveness) and to project short and long-term predictions, while few articles performed economic impact analysis. Estimations of the R0 and transmission rates or projections regarding the course of the epidemic figured as major, especially at the beginning of the crisis. However, several other outputs were forecasted, such as the isolation/quarantine effect on transmission, hospital facilities required, secondary cases caused by infected children, and the economic effects of the pandemic. This study reveals numerous articles with shared objectives and similar methods and data sources. We observed a deficiency in addressing social inequities in the Brazilian context within the utilized models, which may also be expected in several low- and middle-income countries with significant social disparities. We conclude that the models were of great relevance in the pandemic scenario of COVID-19. Nevertheless, efforts could be better planned and executed with improved institutional organization, dialogue among research groups, increased interaction between modelers and epidemiologists, and establishment of a sustainable cooperation network. |
| format | Article |
| id | doaj-art-74fe84bb8ce945119ae4da14f741bd1a |
| institution | Kabale University |
| issn | 2767-3375 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLOS Global Public Health |
| spelling | doaj-art-74fe84bb8ce945119ae4da14f741bd1a2025-02-05T05:50:32ZengPublic Library of Science (PLoS)PLOS Global Public Health2767-33752023-01-01312e000267910.1371/journal.pgph.0002679Dynamic transmission modeling of COVID-19 to support decision-making in Brazil: A scoping review in the pre-vaccine era.Gabriel Berg de AlmeidaLorena Mendes SimonÂngela Maria BagattiniMichelle Quarti Machado da RosaMarcelo Eduardo BorgesJosé Alexandre Felizola Diniz FilhoRicardo de Souza KuchenbeckerRoberto André KraenkelCláudia Pio FerreiraSuzi Alves CameyCarlos Magno Castelo Branco FortalezaCristiana Maria ToscanoBrazil was one of the countries most affected during the first year of the COVID-19 pandemic, in a pre-vaccine era, and mathematical and statistical models were used in decision-making and public policies to mitigate and suppress SARS-CoV-2 dispersion. In this article, we intend to overview the modeling for COVID-19 in Brazil, focusing on the first 18 months of the pandemic. We conducted a scoping review and searched for studies on infectious disease modeling methods in peer-reviewed journals and gray literature, published between January 01, 2020, and June 2, 2021, reporting real-world or scenario-based COVID-19 modeling for Brazil. We included 81 studies, most corresponding to published articles produced in Brazilian institutions. The models were dynamic and deterministic in the majority. The predominant model type was compartmental, but other models were also found. The main modeling objectives were to analyze epidemiological scenarios (testing interventions' effectiveness) and to project short and long-term predictions, while few articles performed economic impact analysis. Estimations of the R0 and transmission rates or projections regarding the course of the epidemic figured as major, especially at the beginning of the crisis. However, several other outputs were forecasted, such as the isolation/quarantine effect on transmission, hospital facilities required, secondary cases caused by infected children, and the economic effects of the pandemic. This study reveals numerous articles with shared objectives and similar methods and data sources. We observed a deficiency in addressing social inequities in the Brazilian context within the utilized models, which may also be expected in several low- and middle-income countries with significant social disparities. We conclude that the models were of great relevance in the pandemic scenario of COVID-19. Nevertheless, efforts could be better planned and executed with improved institutional organization, dialogue among research groups, increased interaction between modelers and epidemiologists, and establishment of a sustainable cooperation network.https://doi.org/10.1371/journal.pgph.0002679 |
| spellingShingle | Gabriel Berg de Almeida Lorena Mendes Simon Ângela Maria Bagattini Michelle Quarti Machado da Rosa Marcelo Eduardo Borges José Alexandre Felizola Diniz Filho Ricardo de Souza Kuchenbecker Roberto André Kraenkel Cláudia Pio Ferreira Suzi Alves Camey Carlos Magno Castelo Branco Fortaleza Cristiana Maria Toscano Dynamic transmission modeling of COVID-19 to support decision-making in Brazil: A scoping review in the pre-vaccine era. PLOS Global Public Health |
| title | Dynamic transmission modeling of COVID-19 to support decision-making in Brazil: A scoping review in the pre-vaccine era. |
| title_full | Dynamic transmission modeling of COVID-19 to support decision-making in Brazil: A scoping review in the pre-vaccine era. |
| title_fullStr | Dynamic transmission modeling of COVID-19 to support decision-making in Brazil: A scoping review in the pre-vaccine era. |
| title_full_unstemmed | Dynamic transmission modeling of COVID-19 to support decision-making in Brazil: A scoping review in the pre-vaccine era. |
| title_short | Dynamic transmission modeling of COVID-19 to support decision-making in Brazil: A scoping review in the pre-vaccine era. |
| title_sort | dynamic transmission modeling of covid 19 to support decision making in brazil a scoping review in the pre vaccine era |
| url | https://doi.org/10.1371/journal.pgph.0002679 |
| work_keys_str_mv | AT gabrielbergdealmeida dynamictransmissionmodelingofcovid19tosupportdecisionmakinginbrazilascopingreviewintheprevaccineera AT lorenamendessimon dynamictransmissionmodelingofcovid19tosupportdecisionmakinginbrazilascopingreviewintheprevaccineera AT angelamariabagattini dynamictransmissionmodelingofcovid19tosupportdecisionmakinginbrazilascopingreviewintheprevaccineera AT michellequartimachadodarosa dynamictransmissionmodelingofcovid19tosupportdecisionmakinginbrazilascopingreviewintheprevaccineera AT marceloeduardoborges dynamictransmissionmodelingofcovid19tosupportdecisionmakinginbrazilascopingreviewintheprevaccineera AT josealexandrefelizoladinizfilho dynamictransmissionmodelingofcovid19tosupportdecisionmakinginbrazilascopingreviewintheprevaccineera AT ricardodesouzakuchenbecker dynamictransmissionmodelingofcovid19tosupportdecisionmakinginbrazilascopingreviewintheprevaccineera AT robertoandrekraenkel dynamictransmissionmodelingofcovid19tosupportdecisionmakinginbrazilascopingreviewintheprevaccineera AT claudiapioferreira dynamictransmissionmodelingofcovid19tosupportdecisionmakinginbrazilascopingreviewintheprevaccineera AT suzialvescamey dynamictransmissionmodelingofcovid19tosupportdecisionmakinginbrazilascopingreviewintheprevaccineera AT carlosmagnocastelobrancofortaleza dynamictransmissionmodelingofcovid19tosupportdecisionmakinginbrazilascopingreviewintheprevaccineera AT cristianamariatoscano dynamictransmissionmodelingofcovid19tosupportdecisionmakinginbrazilascopingreviewintheprevaccineera |