Very nice -- Thanks!
For everybody, the latest Economist has an interesting piece:
Why a study showing that covid-19 is everywhere is good news
If millions of people were infected weeks ago without dying, the virus must be less deadly than official data suggest
Here is the study
they refer to, which can be downloaded. For the modelers, it has a calibrated SEIR model. From the paper:
The ongoing SARS-CoV-2 pandemic continues to cause tremendous morbidity and mortality around the world [1, 2]. Regional preparation for the pandemic requires forecasting the growth rate of the epidemic, the timing of the peak, the demand for hospital resources, and the degree to which current policies may curtail the epidemic, all of which beneﬁt from accurate estimates of the true prevalence of the virus within a population . Conﬁrmed cases are thought to be underestimates of true prevalence due to some unknown combination of patients not reporting for testing, testing not being conducted, and false-negative test results. Estimating the true prevalence informs the scale of upcoming hospital, ICU and ventilator surges, the proportion of individuals who are susceptible to contracting the disease, and estimates of key epidemiological parameters such as the epidemic growth rate and the fraction of infections which are sub-clinical.
The current literature suggests that the predominant symptoms associated with COVID are fever, cough and sore-throat; that is, patients often present with an inﬂuenza-like illness (ILI) yet test negative for inﬂuenza [4, 5]. With many COVID patients having a similar presentation as patients with inﬂuenza, existing surveillance networks in place for tracking inﬂuenza could be used to help track COVID.
Here, we quantify background levels of non-inﬂuenza ILI over the past 10 years and identify a recent surge of non-inﬂuenza ILI starting the ﬁrst week of March, 2020. This surge of excess ILI correlates with known patterns of SARS-CoV-2 spread across states within the US, suggesting the surge is unlikely to be due to other endemic respiratory pathogens, yet is orders of magnitude larger than the number of conﬁrmed COVID cases reported. Together this suggests that the true prevalence of SARS-CoV-2 within the US is much larger than currently appreciated and that even the highest symptomatic case detection rates are likely lower than 3% corresponding to approximately 9 million new ILI cases due to SARS-CoV-2. Our analysis provides empirical corroboration of previous hypotheses of substantial undocumented cases yet places the estimated undocumented case rate an order of magnitude higher than prior reports . Moreover, these updated prevalence estimates predict that epidemic doubling times greater than 3.5 days [7, 8] would be unable to account for the magnitude of the ILI surge. We test our hypothesis of sub 3-day doubling times in the US by analyzing both state and national COVID surveillance data, ﬁnding a broad agreement of doubling time less than 3.5 days in both conﬁrmed COVID case counts and documented COVID deaths. Our ﬁndings highlight probable trajectories of the US epidemic and provide evidence for a conceptual model for COVID spread in the US in which more rapid spread than previously reported is coupled with a larger undiagnosed population to give rise to currently observed trends.