COVID-19 data are messy: analytic methods for rigorous impact analyses with imperfect data

COVID-19 data are messy: analytic methods for rigorous impact analyses with imperfect data

Abstract Background The COVID-19 pandemic has led to an avalanche of scientific studies, drawing on many different types of data. However, studies addressing the effectiveness of government actions against COVID-19, especially non-pharmaceutical interventions, often exhibit data problems that threat...

Full description

Bibliographic Details
Main Authors: Michael A. Stoto, Abbey Woolverton, John Kraemer, Pepita Barlow, Michael Clarke
Format: Article
Language:English
Published: BMC 2022-01-01
Series:Globalization and Health
Subjects:
COVID-19
Non-pharmaceutical interventions
Surveillance data
Surveillance biases
Impact analysis
Observational studies
Online Access:https://doi.org/10.1186/s12992-021-00795-0

Internet

https://doi.org/10.1186/s12992-021-00795-0

Similar Items