City Research Online

Abstract

Test, trace and isolate are the main pillars of the containment strategies promoted by epidemiologists in the COVID-19 pandemic. Equipment, material and labour required for testing is, however, limited, making it a challenge to adopt testing at a large scale. Pooling of samples has the potential to reduce the number of tests required for screening a population with a low infection prevalence. We provide a detailed analysis of a well-known pooling strategy called two-stage pooling which involves testing pools of a fixed size. We show that, while this approach can potentially reduce the number of tests, evaluating its cost effectiveness and configuring it optimally require existence of a reliable estimate of prevalence in the population. In the absence of such information, we propose inferring a prior distribution of the underlying prevalence using a combination of expert opinion and a limited exploratory testing of the population, and applying it with either a two-stage fixed pooling strategy, or a multi-stage adaptive pooling strategy. We explain how each of these strategies can be applied, propose algorithms for finding their corresponding optimal pool size, and identify the situations under which each of these strategies is preferred.

Publication Type:	Monograph (Working Paper)
Additional Information:	© The Author.
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management R Medicine > RA Public aspects of medicine R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Departments:	Bayes Business School > Management

Export

Downloads