COVID-19 Pandemic in South America
View the Project on GitHub bgonzalezbustamante/COVID-19-South-America
This online tracker was deprecated in mid-May 2020 to focus on a paper which evaluates early projections and governmental responses to COVID-19 epidemic in South America. This paper was published in World Development journal (DOI: 10.1016/j.worlddev.2020.105180). See its demonstration for R.
Source: Compiled using data from the Johns Hopkins University CSSE COVID-19 Dataset.
Note: The estimations have been calculated with a parametric serial interval based on a Gamma distribution with mean μ = 7.5 and standard deviation σ = 3.4 following to Li et al. (2020). The epicurve shows new infections over the period. On the other hand, estimated R illustrates the number of infections that a single case generates: when the value is lower than one, the outbreak is under control (see figure in detail). R is specifically the effective reproduction number (Re), which is calculated on a daily incidence basis. Therefore, it allows us to measure the public health systems response (see Cori et al., 2013; see also Thomson et al., 2019). Finally, the explored serial interval (SI) distribution shows the time interval between the symptoms in each case and the onset of them in secondary cases because of transmission. It is relevant to note that these estimations are too early in this epidemic to obtain a reliable posterior coefficient of variation of the R indicator.
Source: Compiled using data from the Johns Hopkins University CSSE COVID-19 Dataset.
Note: The average of secondary cases is calculated based on the R indicator and its posterior coefficient of variation. The R daily decay rate, on the one hand, is obtained from the second component of a log-incidence regression over the period, while the first component is used to fit the growth-phase. On the other hand, the posterior coefficient of variation of the R indicator is elaborated with a parametric serial interval based the Li et al. (2020) values. After that, 1,000 futures epicurves are simulated from the five days after the current peak to the next two weeks in order to compare observed and predicted values (see figure).
Source: Compiled using data from the Johns Hopkins University CSSE COVID-19 Dataset.
Note: The predicted cumulative incidence of new cases is estimated from the current peak to the following 30-days with 1,000 simulated epicurves per day based on the previous estimation. For further details, see the technical note.
See the Visualisation COVID-19 component of the OSF-Project (DOI: 10.17605/OSF.IO/Y6C7Z)