Biostatistics to better detect fishy findings
Authors: Arnaud Tarantola, Laurent Gautier
Journal: The Lancet Infectious Diseases (2020)

We commend Srinivas Mantha1Mantha S Ratio, rate, or risk?.Lancet Infect Dis. 2020; (published online May 27.)https://doi.org/10.1016/S1473-3099(20)30439-4Summary Full Text Full Text PDF PubMed Scopus (2) Google Scholar for the much needed clarification of the differences between risks, ratios, and rates, and of the latter's underlying notion of time. There is, however, an additional and important difference. The main scientific basis for epidemiology is biostatistics,2Goldstein ND LeVasseur MT McClure LA On the convergence of epidemiology, biostatistics, and data science.Harv Data Sci Rev. 2020; (published online April 30.)DOI:10.1162/99608f92.9f0215e6Google Scholar which applies rigorous mathematical laws of probability and statistics to the fascinating but unpredictable diversity of living organisms. This is done by accepting some measure of uncertainty. If the sample in which we document data is large enough and representative of the population from which the sample is selected, then we can be confident—at a usually chosen 5% risk of being wrong—that the measure in the population is close to that found in the sample and situated within a range of values called the confidence interval (CI). The CI is a fundamental statistical tool for estimating values and comparing them between groups. Upper and lower bounds of the CI of a risk or ratio computed using a normal or a binomial distribution are equally distant from the estimated value. Unlike risks and ratios, however, rates are usually very small numbers: their numerator can vary but their denominator is usually much larger, especially when composed of a number of people exposed multiplied by a number of days, weeks, or months of exposure.3Ponsich A Goutard F Sorn S Tarantola A A 6-months descriptive study of dog bites in rural Cambodia.Acta Tropica. 2016; 160: 62-67Crossref PubMed Scopus (21) Google Scholar CIs for rates, especially for rates of repeatable events, are computed using a Poisson distribution and can be substantially skewed towards the upper bound. This skew has important consequences: when calculating incidence rates of COVID-19 endpoints to compare them between different populations or groups (especially repeatable events such as hospital admissions or repeat clusters over a time period), computing their CIs using a normal instead of a Poisson distribution would wrongly cut them short on the right. This might result in a statistically significant difference between groups' incidence rates when there would not be any under a Poisson distribution. This also has consequences when estimating the sample size needed to achieve desired power before comparing incidence rates between samples.4Gail M Power computations for designing comparative Poisson trials.Biometrics. 1974; 30: 231-237Crossref Scopus (57) Google Scholar The emergence and rapid global expansion of COVID-19 within weeks and implementation of lockdowns worldwide have made epidemiology a household word.5First Dog On The MoonSomeone had a worse response to coronavirus than Boris Johnson?!.https://firstdogonthemoon.com.au/cartoons/2020/04/21/someone-had-a-worse-response-to-coronavirus-than-boris-johnson/Date accessed: June 3, 2020Google Scholar We enthusiastically welcome increased awareness among clinicians, researchers, and indeed the general public of the importance of epidemiology and biostatistics. As we progress from computing percentages in observational studies to comparing rates and CIs within or among groups, clinicians and researchers must be aware that—unlike risks or ratios—incidence rates follow a Poisson distribution. We declare no competing interests. Ratio, rate, or risk?In epidemiology, the terms ratio, rate, and risk have clear definitions.1 In the emerging publications related to coronavirus disease 2019 (COVID-19), the phrase case fatality rate is being used instead of case fatality ratio.2,3 A ratio is a comparison of two similar quantities. Ratios have no dimensions and can take any value; a ratio of 1 means the two quantities being compared are equal to each other. The case fatality ratio is the ratio of deaths (numerator) to identified cases (denominator), and is usually expressed as percentage. Full-Text PDF