Por favor, use este identificador para citar o enlazar este ítem:
http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/130| Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: a modelling study in Hubei, China and northern Italy | |
| Anthony Hauser Michel J Counotte Charles C Margossian Garyfallos Konstantinoudis Nicola Low Christian L Althaus Julien Riou | |
| Novel Coronavirus | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| 10.1101/2020.03.04.20031104 | |
| Background. The epidemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that originated in Wuhan, China in late 2019 is now pandemic. Reliable estimates of death from coronavirus disease 2019 (COVID-19) are essential to guide control efforts and to plan health care system requirements. The objectives of this study are to: 1) simulate the transmission dynamics of SARS-CoV-2 using publicly available surveillance data; 2) give estimates of SARS-CoV-2 mortality adjusted for bias in the two regions with the world's highest numbers of confirmed Covid-19 deaths: Hubei province, China and northern Italy. Method and Findings. We developed an age-stratified susceptible-exposed-infected-removed (SEIR) compartmental model describing the dynamics of transmission and mortality during the SARS-CoV-2 epidemic. Our model accounts for two biases; preferential ascertainment of severe cases and delayed mortality (right-censoring). We fitted our transmission model to surveillance data from Hubei province (1 January to 11 February 2020) and northern Italy (8 February to 3 March 2020). Overall mortality among all symptomatic and asymptomatic infections was estimated to be 3.0% (95% credible interval: 2.6-3.4%) in Hubei province and 3.3% (2.0-4.7%) in northern Italy. Mortality increased with age; we estimate that among 80+ year olds, 39.0% (95%CrI: 31.1-48.9%) in Hubei province and 89.0% (95%CrI: 56.2-99.6%) in northern Italy dies or will die. Limitations are that the model requires data recorded by date of onset and that sex-disaggregated mortality was not available. Conclusions. We developed a mechanistic approach to correct the crude CFR for bias due to right-censoring and preferential ascertainment and provide adjusted estimates of mortality due to SARS-CoV-2 infection by age group. While specific to the situation in Hubei, China and northern Italy during these periods, these findings will help the mitigation efforts and planning of resources as other regions prepare for SARS-CoV-2 epidemics. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement JR is funded by the Swiss National Science Foundation (grant 174281). MC is funded by the Swiss National Science Foundation (grant 176233). ### Author Declarations All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript. Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All code and data are available from https://github.com/jriou/covid_adjusted_cfr | |
| Cold Spring Harbor Laboratory Press | |
| 2020 | |
| Preimpreso | |
| https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v2 | |
| Inglés | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Artículos científicos |
Cargar archivos:
| Fichero | Tamaño | Formato | |
|---|---|---|---|
| estimation of SARS.pdf | 479.79 kB | Adobe PDF | Visualizar/Abrir |