Bayesian modeling of COVID-19 cases with a correction to account for under-reported cases.
Bayesian modeling of COVID-19 cases with a correction to account for under-reported cases.
复制标题
DOI：
10.1016/j.idm.2020.09.005
复制
发表时间：
2020
影响因子：
8.8
通讯作者：
Granzotto DCT
中科院分区：
文献类型：
--
作者：
de Oliveira ACS;Morita LHM;da Silva EB;Zardo LAR;Fontes CJF;Granzotto DCT
新型冠状病毒病始于2019年底，使世界各国政府遇到了大量危重病例和死亡病例，而不仅仅是对其卫生系统崩溃的持续担忧。自大流行开始以来，研究人员和当局主要关注的是开展定量研究（建模和预测），以克服检测匮乏导致病例少报的问题。为了解决这些问题，我们在SIR模型中引入了贝叶斯方法，并对巴西COVID-19病例分析中的漏报进行了修正。实施拟议的模型是为了获得对重要数量的估计，例如繁殖率和平均感染期，以及更有可能出现大流行高峰的日期。模拟研究中考虑了几个报告不足的场景，显示了建模中信息缺乏的影响。
The novel of COVID-19 disease started in late 2019 making the worldwide governments came across a high number of critical and death cases, beyond constant fear of the collapse in their health systems. Since the beginning of the pandemic, researchers and authorities are mainly concerned with carrying out quantitative studies (modeling and predictions) overcoming the scarcity of tests that lead us to under-reporting cases. To address these issues, we introduce a Bayesian approach to the SIR model with correction for under-reporting in the analysis of COVID-19 cases in Brazil. The proposed model was enforced to obtain estimates of important quantities such as the reproductive rate and the average infection period, along with the more likely date when the pandemic peak may occur. Several under-reporting scenarios were considered in the simulation study, showing how impacting is the lack of information in the modeling.
登录
查看更多内容
影响因子：
--
作者：
Prado, Marcelo Freitas do;Antunes, Bianca Brandão de Paula;Bozza, Fernando Augusto
通讯作者：
Bozza, Fernando Augusto
影响因子：
2
作者：
de Oliveira, Guilherme Lopes;Loschi, Rosangela Helena;Assuncao, Renato Martins
通讯作者：
Assuncao, Renato Martins
影响因子：
3.7
作者：
Nishiura H;Klinkenberg D;Roberts M;Heesterbeek JA
通讯作者：
Heesterbeek JA
DOI：
10.1098/rspa.1927.0118
发表时间：
1927-08-01
期刊：
PROCEEDINGS OF THE ROYAL SOCIETY OF LONDON SERIES A-CONTAINING PAPERS OF A MATHEMATICAL AND PHYSICAL CHARACTER
影响因子：
--
作者：
Kermack, WO;McKendrick, AG
通讯作者：
McKendrick, AG
影响因子：
2.7
作者：
HEIDELBERGER, P;WELCH, PD
通讯作者：
WELCH, PD