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UCLA - Stanford University study taking a second, more careful look at COVID case statistics

A source for the study itself:

https://www.medrxiv.org/content/10.1101/2020.06.06.20124446v2

 

 

Text from the abstract:

 

"Abstract Objective: Our objective is to demonstrate

a method to estimate the probability of a laboratory

confirmed COVID19 infection, hospitalization, and

death arising from a contact with an individual of

unknown infection status. Methods: We calculate

the probability of a confirmed infection, hospitalization,

and death resulting from a county-level person-contact

using available data on current case incidence,

secondary attack rates, infectious periods, asym-

ptomatic infections, and ratios of confirmed infections

to hospitalizations and fatalities. Results: Among US

counties with populations greater than 500,000 people,

during the week ending June 13,2020, the median

estimate of the county level probability of a confirmed

infection is 1 infection in 40,500 person contacts

(Range: 10,100 to 586,000). For a 50 to 64 year-old

individual, the median estimate of the county level

probability of a hospitalization is 1 in 709,000 person

contacts (Range: 177,000 to 10,200,000) and the

median estimate of the county level probability of a

fatality is 1 in 6,670,000 person contacts

(Range 1,680,000 to 97,600.000).


 

"Conclusions and Relevance: Estimates of the

individual probabilities of COVID19 infection,

hospitalization and death vary widely but may not

align with public risk perceptions. Systematically

collected and publicly reported data on infection

incidence by, for example, the setting of exposure,

type of residence and occupation would allow

more precise estimates of probabilities than

possible with currently available public data.

Calculation of secondary attack rates by setting

and better measures of the prevalence of

seropositivity would further improve those

estimates."


Posted by George Freund on September 14, 2020 at 10:33 AM 54 Views