In December 2019, a group of patients presented a diagnosis of pneumonia of unknown etiology in Hubei Province, Wuhan, China. By January 2020, authorities around the world faced a new coronavirus (SARS-CoV-2). By August 2020, the two countries with the highest number of SARS-CoV-2 infections are the USA and Brazil. The transmission rate of a virus is studied from the basic reproduction number (R0). The SIR model is the simplest compartmental epidemiological model (Susceptible, Infectious and Recovered). The SIR model can be used to estimate R0 by fitting the curve of the infected compartment to the experimental curve of infected subjects per day. The aim of this work is to study the projection of the R0 of SARS-CoV-2 in the USA and Brazil. For this purpose, five experiments were performed by adjusting the SIR model curve of infected compartment to experimental data at five time intervals (the first 14, 28, 42, 56 and 187 days for the USA data, and 177 days for Brazil data). In the first two time intervals the R0 varied between 5.46 and 7.75 for the USA data and 1.84 and 4.29 for Brazil data, and in the last three time intervals the R0 decreased to 1.05 for the USA data and 1.01 for Brazil data, suggesting that the social distancing measures implemented in both countries were able to decrease the infection spreading. The differences in the R0 values of the five experiments imply that R0 also depends on the preventive measures implemented to face the pandemic.
|Title of host publication||2020 IEEE ANDESCON, ANDESCON 2020|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|State||Published - 13 Oct 2020|
|Event||2020 IEEE ANDESCON, ANDESCON 2020 - Quito, Ecuador|
Duration: 13 Oct 2020 → 16 Oct 2020
|Name||2020 IEEE ANDESCON, ANDESCON 2020|
|Conference||2020 IEEE ANDESCON, ANDESCON 2020|
|Period||13/10/20 → 16/10/20|
Bibliographical noteFunding Information:
ACKNOWLEDGMENTS This work was funded by the Research and Development Deanery of Salesian Polytechnic University and the Research and Development Deanery of the Simón Bolívar University (DID).
© 2020 IEEE.
- Mathematical Epidemiologic Model
- Parametric Fitting