Fear, Access, and the Real-Time Estimation of Etiological Parameters for Outbreaks of Novel Pathogens

Nina H Fefferman; Eric Lofgren; Nianpeng Li; Pieter Blue; David Weber; Abdul-Aziz Yakubu

is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.19.20038729 doi: medRxiv preprint SIR model was fit to obtain those parameters is currently unavailable). We make this 184 assumption to provide a method by which analysis of previously published rates for 185 historical outbreaks could be analyzed without having to reanalyze the original outbreak 186 data (should that data in fact be accessible, the correction can naturally be applied 187 directly to the m i data directly rather than to * i curve described below). We, therefore, 188 begin with an initially reconstructed SIR system (denoted by *) using only our measured 189 identical, we see that asymmetry in error type rates alone can drastically alter our 220 understanding of an ongoing outbreak (Fig. 1a) . Extending this simple case to also 221 include behavioral responses that shift over the course of an outbreak (i.e. non-constant 222 testing rates), while still keeping all else the same, we see also that there can be drastic 223 errors, even in the understood shape of the incidence curve to match the cases observed 224 (Fig. 1b) . (Again, for derivation of predictions for agreement/disagreement with real 225 disease process based on the direction of the inequality between ε A and 1, and the 226 derivation of this example, see ESM Appendix 1). 227 . 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.