里约热内卢首次疫情期间未报告的新冠病例数估计。
Estimate of the rate of unreported COVID-19 cases during the first outbreak in Rio de Janeiro.
作者信息
Aronna M S, Guglielmi R, Moschen L M
机构信息
Escola de Matemática Aplicada - EMAp, FGV, Rio de Janeiro, RJ, Brazil.
Department of Applied Mathematics, University of Waterloo, Waterloo, ON, Canada.
出版信息
Infect Dis Model. 2022 Sep;7(3):317-332. doi: 10.1016/j.idm.2022.06.001. Epub 2022 Jun 22.
In this work we fit an epidemiological model SEIAQR ( - - - - - ) 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 March-July 2020 in Rio de Janeiro, we estimate about 90% of unreported cases, with a 95% confidence interval (85%, 93%).
在这项工作中，我们将一个流行病学模型SEIAQR（ - - - - - ）应用于巴西里约热内卢首次新冠疫情的数据。特别强调了未报告率，即未被卫生系统检测到的感染个体比例。模型参数的评估基于误差加权最小二乘法和适当的B样条曲线的组合。分析了结构和实际可识别性以支持参数估计的可行性和稳健性。我们使用自助法来量化估计值的不确定性。对于2020年3月至7月里约热内卢的疫情，我们估计约90%的病例未被报告，95%置信区间为（85%，93%）。
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