tetano
Editor, Senior Moderator
Medwave. 2020 Mar 27;20(2):e7861. doi: 10.5867/medwave.2020.02.7861.
Number of COVID-19 cases in Chile at 120 days with data at 21/03/2020 and threshold of daily effort to flatten the epi-curve.
[Article in English, Spanish; Abstract available in Spanish from the publisher]
C?rdova-Lepe F[SUP]1[/SUP], Guti?rrez-Aguilar R[SUP]2[/SUP], Guti?rrez-Jara JP[SUP]3[/SUP].
Author information
Abstract
in English, Spanish
We present a straightforward projection with data up to 21/03/2020 of the evolution of the number of COVID-19 cases per day in Chile using data from the Ministry of Health. Assuming an arithmetical growth in the second variation of the data, we present a cubic adjustment model in which we estimate over 100 000 cases at 120 days consistent with the data recorded to date. Furthermore, we use an exponential total case model to represent (using a parameter) the daily effort to reduce a high initial daily growth rate. We simulate this model with different numerical scenarios of feasibility and desired future prevalence.
KEYWORDS:
epidemiology; mathematical models; coronavirus
PMID:32225133DOI:10.5867/medwave.2020.02.7861
Number of COVID-19 cases in Chile at 120 days with data at 21/03/2020 and threshold of daily effort to flatten the epi-curve.
[Article in English, Spanish; Abstract available in Spanish from the publisher]
C?rdova-Lepe F[SUP]1[/SUP], Guti?rrez-Aguilar R[SUP]2[/SUP], Guti?rrez-Jara JP[SUP]3[/SUP].
Author information
Abstract
in English, Spanish
We present a straightforward projection with data up to 21/03/2020 of the evolution of the number of COVID-19 cases per day in Chile using data from the Ministry of Health. Assuming an arithmetical growth in the second variation of the data, we present a cubic adjustment model in which we estimate over 100 000 cases at 120 days consistent with the data recorded to date. Furthermore, we use an exponential total case model to represent (using a parameter) the daily effort to reduce a high initial daily growth rate. We simulate this model with different numerical scenarios of feasibility and desired future prevalence.
KEYWORDS:
epidemiology; mathematical models; coronavirus
PMID:32225133DOI:10.5867/medwave.2020.02.7861