11–20 of 73 posts
I seem to be hitting trying to read this. Can someone help summarize the results of this analysis?
> Simulating from 1 January, we obtained 108,689 (95% PPI: 1,023 to 14,182,310) local infections cumulatively in the United States by 12 March (Fig. 1A).
What that means is that they don't really know - that confidence interval is absurd - but they have reason to think there could have been 100k Americans with the coronavirus on March 12.
Interesting. An estimate that infections were multiple orders of magnitude higher than detected in mid-March is higher than I'd heard before, although I suppose it's probably implied by the "basically everyone in New York caught it" theory.
It does not suggest that everyone in new york caught the virus. Just that in the early days of the pandemic, when schools were open and no one knew about the virus, the model for growth was exponential with about a 25% increase in cases per day, the best estimate for the number of infections was 2^(14/3)*(1/1.5%)x deaths. Each death corresponded to about 2000 cases.
Earlier quoted context omitted.
California wasn't hit very hard early. In terms of total reported cases, they're only just now starting to catch up with New York (21 per thousand for the state vs 17 per thousand for California) - and as we catch up we've had a pretty sharp improvement from the peak in July. The theory is that California flattened the curve in the original sense, delaying the peak in order to ensure it's moderately lower and protect…
Louisiana, then?
Interesting. An estimate that infections were multiple orders of magnitude higher than detected in mid-March is higher than I'd heard before, although I suppose it's probably implied by the "basically everyone in New York caught it" theory.
As nice as it would be, seroprevalence studies have ruled out the "basically everyone in New York caught it" theory.
Interesting. An estimate that infections were multiple orders of magnitude higher than detected in mid-March is higher than I'd heard before, although I suppose it's probably implied by the "basically everyone in New York caught it" theory.
As nice as it would be, seroprevalence studies have ruled out the "basically everyone in New York caught it" theory.
Interesting. An estimate that infections were multiple orders of magnitude higher than detected in mid-March is higher than I'd heard before, although I suppose it's probably implied by the "basically everyone in New York caught it" theory.
I would not be surprised if it were much higher.
Interesting. An estimate that infections were multiple orders of magnitude higher than detected in mid-March is higher than I'd heard before, although I suppose it's probably implied by the "basically everyone in New York caught it" theory.
As nice as it would be, seroprevalence studies have ruled out the "basically everyone in New York caught it" theory.
What recent studies have shown is that while the naive herd immunity threshold is perhaps around 60% (working backwards from R0 estimates), after you factor in clustering of populations, baseline hygienic improvements, and moderate social distancing, that NY did reach an effective level of herd immunity.
Interesting. An estimate that infections were multiple orders of magnitude higher than detected in mid-March is higher than I'd heard before, although I suppose it's probably implied by the "basically everyone in New York caught it" theory.
Interesting. An estimate that infections were multiple orders of magnitude higher than detected in mid-March is higher than I'd heard before, although I suppose it's probably implied by the "basically everyone in New York caught it" theory.
It's not that hard to work backward from the observed fatality rate and the death curve to the infection curve two weeks ago. That's basically all they're doing in this paper. It does not suggest that everyone in new york caught the virus. Just that in the early days of the pandemic, when schools were open and no one knew about the virus, the model for growth was exponential with about a 25% increase in cases per day…
Earlier quoted context omitted.
As nice as it would be, seroprevalence studies have ruled out the "basically everyone in New York caught it" theory.
A substantial percentage of infections are believed to not show up in seroprevalence studies. One of the major areas of research right now is determining how large this population is.