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ARBO: Arbovirus modeling and uncertainty quantification toolbox.
Tosin, Michel; Dantas, Eber; Cunha, Americo; Morrison, Rebecca E.
  • Tosin M; Rio de Janeiro State University, Rio de Janeiro, Brazil.
  • Dantas E; Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
  • Cunha A; Rio de Janeiro State University, Rio de Janeiro, Brazil.
  • Morrison RE; University of Colorado Boulder, Boulder, USA.
Softw Impacts ; 12: 100252, 2022 May.
Article in English | MEDLINE | ID: covidwho-1692884
ABSTRACT
The ongoing pandemic of COVID-19 has highlighted the importance of mathematical tools to understand and predict outbreaks of severe infectious diseases, including arboviruses such as Zika. To this end, we introduce ARBO, a package for simulation and analysis of arbovirus nonlinear dynamics. The implementation follows a minimalist style, and is intuitive and extensible to many settings of vector-borne disease outbreaks. This paper outlines the main tools that compose ARBO, discusses how recent research works about the Brazilian Zika outbreak have explored the package's capabilities, and describes its potential impact for future works on mathematical epidemiology.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Softw Impacts Year: 2022 Document Type: Article Affiliation country: J.simpa.2022.100252

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Softw Impacts Year: 2022 Document Type: Article Affiliation country: J.simpa.2022.100252