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is the (which was not peer-reviewed) The copyright holder for this preprint .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 Note that these calculations presented in Figure 1 are meant to be extremes to highlight 228 the potential for confusion -we show a full range of values for 1 ε , and 2 ε ranging from 229 potentially realistic ( ε A =1) to dramatically inflated (both 1 ε , and 2 ε are greater than 0.5, 230 which would result in a more accurate test by simply negating the result). This is done to 231 highlight the problem, though of course, real-world values are expected to be within a 232 much narrower, more conservative range. from an idealized instructional case, when we incorporate both testing rate dependence 243 on perceived prevalence and the amount of time since surpassing the threshold for 244 increased behavioral demand for testing (e.g. gradual relaxation in public risk perception 245 over time), the differences between the reality of the disease dynamics and the 246 understanding that would be provided by fitting a model to case incidence data is even 247 greater (Fig 2b) . 248 249 . 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. 1958 outbreaks would already have been accurately understood (Fig 3b and 3c) . 270 271 . 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.