In this work we fit an epidemiological model SEIAQR(Susceptible-Exposed-Infectious-Asymptomatic-Quarantined-Removed)to the data of the first COVID-19 outbreak in Rio de Janeiro,Brazil.Particular emphasis is given to t...In this work we fit an epidemiological model SEIAQR(Susceptible-Exposed-Infectious-Asymptomatic-Quarantined-Removed)to the data of the first COVID-19 outbreak in Rio de Janeiro,Brazil.Particular emphasis is given to the unreported rate,that is,the proportion of infected individuals that is not detected by the health system.The evaluation of the parameters of the model is based on a combination of error-weighted least squares method and appropriate B-splines.The structural and practical identifiability is analyzed to support the feasibility and robustness of the parameters’estimation.We use the Bootstrap method to quantify the uncertainty of the estimates.For the outbreak of MarcheJuly 2020 in Rio de Janeiro,we estimate about 90%of unreported cases,with a 95%confidence interval(85%,93%).展开更多
基金The first and third authors were supported by FAPERJ and CNPq,Brazil.The second author acknowledges the support of the Natural Sciences and Engineering Research Council of Canada(NSERC),funding reference number RGPIN-2021-02632。
文摘In this work we fit an epidemiological model SEIAQR(Susceptible-Exposed-Infectious-Asymptomatic-Quarantined-Removed)to the data of the first COVID-19 outbreak in Rio de Janeiro,Brazil.Particular emphasis is given to the unreported rate,that is,the proportion of infected individuals that is not detected by the health system.The evaluation of the parameters of the model is based on a combination of error-weighted least squares method and appropriate B-splines.The structural and practical identifiability is analyzed to support the feasibility and robustness of the parameters’estimation.We use the Bootstrap method to quantify the uncertainty of the estimates.For the outbreak of MarcheJuly 2020 in Rio de Janeiro,we estimate about 90%of unreported cases,with a 95%confidence interval(85%,93%).
