Citation

Bangdiwala SI, G A, Monsalves MJ, Palmeiro Y. Soc. Health Sci. 2021; 19(1): 52-79.

Copyright

(Copyright © 2021, University of South Africa (UNISA))

DOI

10.10520/ejc-safety1-v19-n1-a4

PMID

unavailable

Abstract

Communicating statistics in health risk communication is a fundamental part of managing public health emergencies. Effective communication requires careful planning and the anticipation of possible information demands from the population. The information should be clear, relevant, easy to understand, timely, accurate and precise, allowing the public to make informed decisions about protective behaviours. COVID-19, being a new disease, with little known about its characteristics and effects, has challenged governments and healthcare systems in all countries. This article discusses the statistical issues involved, and the experiences of risk communication in four countries - Canada, Chile, Ecuador and England. These countries have communicated risks differently, partly because of their different healthcare systems, as well as socioeconomic, cultural and political realities. During a pandemic, health authorities and governments must step up to the challenge of communicating statistical information under pressure and with urgency, when little is known about the disease, the situation is dynamic and evolving, and the general public is gripped with fear and anxiety. This is in addition to the existing challenges relating to the generation of data of different quality by diverse sources, and a public with varying levels of statistical literacy. From a statistical perspective, communiqués about risks and numbers should convey the uncertainty there is about the information, the inherent variabilities in the system, the precision and accuracy of estimates and the assumptions behind projections. Complex technical concepts, such as 'flattening the curve', 'range in risk estimates' and 'projected trends,' should be explained.

Language: en

Keywords

Coronavirus; COVID-19; Flattening the Curve; Health indicators; Lockdown; pandemics; Probability; Risk assessment; SARS-CoV2; Statistical literacy; Uncertainty; vital statistics