Quantifying the Individual Variation in Susceptibility to Endemic Coronavirus and SARS-CoV-2 with Human Challenge Trials

Abstract

Human challenge trials reveal how the infection risk depends on a given infectious dose. We propose a mathematical framework to analyze and interpret the outcomes of human challenge trials by incorporating the variability between individuals in susceptibility to infection. We illustrate the framework for two distinctive diseases; endemic diseases where a fraction of the study population has been exposed to the target pathogen previously and is thus immune, and novel diseases where the study population is fully susceptible. Based on available data from published trials, we estimate the immune proportion and the variation in susceptibility to endemic HCoV-229E and present plausible infection risks with SARS-CoV-2 over multiple orders of magnitude of the infectious dose. The results show that the proposed method captures heterogeneous background susceptibility in the study population, and we suggest ways to improve the design of future trials and to translate their outcomes to the general population.