Weaponizing Covid Data for Max Panic

This post comes from a Florida newspaper who dig into facts rather than amplify fears.  Fortunately Florida has leadership who have taken a balanced and reasoned approach to the contagion, but there are many in that state and around the world who are freaked out and want others to also be alarmed.  An article by Len Cabrera at the Alachua Chronicle (near Gainesville) provides insight into the twisting of data by fear mongers: Increasing percentage of Florida’s COVID data is questionable.  Excerpts in italics with my bolds.

When government-provided data is used to support increasing government power, we should all question its validity. Because we know that all lab tests have false positives and that PCR tests pick up fragments of the virus that may or may not indicate infection, COVID deaths should be certified by physicians, not matched to names in the list of people who previously had a positive test.

48% of the entries in the Florida Department of Health (FDOH) COVID-19 case line data have “UNKNOWN” or blanks in the fields for emergency department visit or hospitalization, indicating that FDOH has not been able to collect information about them. Thus, we don’t know whether they ever had symptoms, much less whether they were hospitalized and/or died because of COVID. The percentage of FDOH-reported COVID deaths that have “UNKNOWN” or blank entries is increasing, suggesting that these recently-reported deaths (many from months ago) may not be valid COVID-19 deaths.

Cases started inexplicably rising in Florida in early June despite mask mandates, business closures, and capacity limits across the state (driven by county commissions and/or mayors, not state-wide policy). When scientists, reporters, or private citizens questioned the validity of the data, they were told to shut up and trust the judgment of government “experts” that these are valid cases, not just positive tests.

Documented studies (summarized here) show that PCR tests are too sensitive to properly identify cases when they use a cycle threshold over 34, and almost all labs in the United States use at least 37, if not 40. The New York Times reported that these tests can produce 40% to 90% false positive results. (If you don’t have a subscription you can read the summary from Apoorva Mandavilli’s Twitter account.)

The push for more and more testing, especially of asymptomatic people returning to work or school, has driven this artificial casedemic. Don’t read something I’m not saying. This does not mean COVID doesn’t exist or isn’t real but that a good portion of the FDOH “cases” are just people with positive tests, not people actively infected (and infectious) with COVID.

To try to get a handle on these suspicious cases, I looked at the case line data to determine the number of “cases” that have “UNKNOWN” or blank entries for both emergency department visit or hospitalization. Contact tracers attempt to get this data when they interview individuals with positive tests, and they enter “NO” if the person has not visited an emergency room or been hospitalized. (This can be changed later if those events occur.) Sometimes the individual is not cooperative, so there can be cases in which a contact tracer enters “UNKNOWN” after an interview, but most of the time, “UNKNOWN” indicates that contact tracing was not successful (i.e., FDOH was not able to interview the person who tested positive).

The number of records with “UNKNOWN” or missing information in both of these fields allows us to estimate the number of questionable “cases.”

Using the most recent (as I write this) FDOH case line file (10/3), there are 714,591 “cases,” but 305,953 (43%) have “UNKNOWN” or blanks for both emergency room visit or hospitalization. Considering records with either category as unknown or blank increases the suspected bad data to 48%.

Breaking it down by case date, the percentage of records missing data in both fields increased dramatically in June, as asymptomatic testing increased. (The 55% in October is probably not meaningful since it’s only 3 days and interviews may not have been completed, but there’s no reason why July should be 52%.)

However, deaths are often reported months after the date of the positive test, and for people who roll around in the data every day, it’s obvious that the percentage of reported deaths with unknown data is getting worse; the most recent reports are much higher than the 24-25% of the last couple months. The table above is categorized on case date (the date the test result was received by FDOH), but looking at the death data by reporting date suggests that officials are farming death certificates for people who died with a positive COVID test rather than adding deaths that were legitimately caused by COVID.

The graph at the top shows that there is clearly an increasing trend in the percentage of deaths that are probably not true COVID cases because of missing or unknown information. While the overall percentage (by case date) was 20%, the percentage of bad data since August 3 (by report date) was 32%; over the last four weeks, it was 40%.

Remember, health officials assure us that these are actual cases of COVID-19, not simply positive tests. They tell us they’re contacting them and interviewing them to weed out false positives. At the very least, when someone who died a few months ago is matched to a positive COVID test and declared a COVID death, we should expect investigators to determine whether they visited an emergency room, were hospitalized, or were ever treated for any COVID-19 complications. The increasing percentage of bad data does not paint a good picture of the FDOH. It is possible that FDOH is overwhelmed and cannot properly complete the data, but it would be better to report correct data more slowly than to rush exaggerated numbers that fuel public panic and overreactions from elected officials.

If breathing into a paper bag doesn’t help, try this prayer at bedtime.