Epidemic Surveillance of Covid-19: Considering Uncertainty and Under-Ascertainment
Open Access
- 9 April 2020
- journal article
- Published by S. Karger AG in Portuguese Journal of Public Health
- Vol. 38 (1), 23-29
- https://doi.org/10.1159/000507587
Abstract
Epidemic surveillance is a fundamental part of public health practice. Addressing under-ascertainment of cases is relevant in most surveillance systems, especially in pandemics of new diseases with a large spectrum of clinical presentations as it may influence timings of policy implementation and public risk perception. From this perspective, this article presents and discusses early evidence on under-ascertainment of COVID-19 and its motifs, options for surveillance, and reflections around their importance to tailor public health measures. In the case of COVID-19, systematically addressing and estimating under-ascertainment of cases is essential to tailor timely public health measures, and communicating these findings is of the utmost importance for policy making and public perception.Keywords
This publication has 10 references indexed in Scilit:
- Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2)Science, 2020
- Transmission potential and severity of COVID-19 in South KoreaInternational Journal of Infectious Diseases, 2020
- Early dynamics of transmission and control of COVID-19: a mathematical modelling studyThe Lancet Infectious Diseases, 2020
- Effect of non-pharmaceutical interventions for containing the COVID-19 outbreak in ChinaPublished by Cold Spring Harbor Laboratory ,2020
- Estimation of COVID-19 outbreak size in Italy based on international case exportationsPublished by Cold Spring Harbor Laboratory ,2020
- Preliminary estimation of the novel coronavirus disease (COVID-19) cases in Iran: a modelling analysis based on overseas cases and air travel dataPublished by Cold Spring Harbor Laboratory ,2020
- Feasibility of controlling COVID-19 outbreaks by isolation of cases and contactsThe Lancet. Global Health, 2020
- A Novel Coronavirus Emerging in China — Key Questions for Impact AssessmentThe New England Journal of Medicine, 2020
- Quantifying bias of COVID-19 prevalence and severity estimates in Wuhan, China that depend on reported cases in international travelersPublished by Cold Spring Harbor Laboratory ,2020
- Data-Based Analysis, Modelling and Forecasting of the COVID-19 outbreakPublished by Cold Spring Harbor Laboratory ,2020