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Statistical data driven approach of COVID-19 in Ecuador: R_(0) and R_(t) estimation via new method

Infectious Disease Modelling 2021年第1期6卷 232-243页

作者： Raúl Patricio Fernandez-Naranjo MSc Eduardo Vasconez-Gonzalez MD Katherine Simbana-RiveraMD,MSc Lenin Gomez-Barreno MD Juan S.Izquierdo-Condoy MD Domenica Cevallos-RobalinoMD,MPH(c) Esteban Ortiz-Prado MD,MSc,MPH One Health Research Group Faculty of MedicineUniversidad de las AmericasQuitoEcuador Resident of Intensive Care Unit Hospital Quito Sur IESSQuitoEcuador

The growth of COVID-19 pandemic throughout more than 213 countries around the world have put a lot of pressures on governments and health services to try to stop the rapid expansion of the *** 2009,H1N1 Influenza pandemic,statistical and mathematical methods were used to track how the virus spreads around *** of these models that were developed at the beginning of the XXI century are based on the classical susceptible-infected-recovered(SIR)model developed almost a hundred years *** evolution of this model allows us to forecast and compute basic and effective reproduction numbers(R_(t) and R_(0)),measures that quantify the epidemic potential of a pathogen and estimates different *** this study,we present a traditional estimation technique for R_(0) with statistical distributions by best fitting and a Bayesian approach based on continuous feed of prior distributions to obtain posterior distributions and computing real time R_(t).We use data from COVID-19 officially reported cases in Ecuador since the first confirmed case on February *** of the lack of data,in the case of R_(0) we compare two methods for the estimation of these parameters below exponential growth and maximum likelihood *** do not make any assumption about the evolution of cases due to limited information and we use previous methods to compare scenarios about R_(0) and in the case of R_(t) we used Bayesian inference to model uncertainty in contagious proposing a new modification to the well-known model of Bettencourt and Ribeiro based on a time window of m days to improve *** R_(0) with exponential growth criteria was 3.45 and with the maximum likelihood estimation method was *** results show that Guayas,Pichincha and Manabíwere the provinces with the highest number of cases due to *** reasons explain the increased transmissibility in these localities:massive events,population density,cities dispersion patterns,and

关键词： Bayesian inference R0 COVID-19 Real time reproduction factor basic reproduction factor Ecuador

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