Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys

Daniel B Larremore; Bailey K Fosdick; Kate M Bubar; Sam Zhang; Stephen M Kissler; C. Jessica E. Metcalf; Caroline Buckee; Yonatan Grad

In the absence of baseline estimates of seroprevalence, an initial survey will provide a preliminary estimate of population prevalence (Fig. 2 ). Our framework updates the 'rule of 3' approach (16) by incorporating uncertainty in test characteristics and can further address uncertainty from biased sampling schemes (see Supplementary Text). As a result, convenience samples, such as newborn heel stick dried blood spots or samples from blood donors, can be used to estimate population seroprevalence. However, it is important to note that in the absence of reliable assessment of correlations in seroprevalence across age groups, extrapolations from these convenience samples may be misleading as sample size increases (Supplementary Figs. S4 and S6). Uniform or model and demographic informed samples, while more challenging logistically to implement, give the most reliable estimates. The results of a one-time study could be used to update the priors of our Bayesian hierarchical model and improve the inferences from convenience samples. In this context, we note that our mathematical framework naturally allows the integration of samples from multiple test kits and protocols, provided that their sensitivities and specificities can be estimated, which will become useful as serological 10 . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.