There's also the option of scientific or mathematical competence, instead of pandemic theater.
Contact tracing was historically used at the start of a disease outbreak where it can be 100% successful. It's nearly useless later, with only partial visibility due to widespread dispersion. Even a 7x24 Person of Interest panopticon could not trace every contact across urban populations.
> Contact tracing was historically used at the start of a disease outbreak
Correct me if I'm wrong - but that's only true due to the historical turnaround time of contact tracing. Even with many cases, contact tracing at the margin can reduce $R_t$. Even in the UK, until the last 2 weeks or so, there were very few cases relative to how many there are now. Especially since covid appears to spread through a disproportionate number of super-spreading incidents compared to say the flu (ie. very right-tailed distribution in the number of people you infect with covid) means that contact tracing can be particularly effective.
If contact tracing is relying on flawed input data (PCR "positive" for people without symptoms), how can we avoid societal DoS of medical resources, income, and school from unnecessary contact tracing?
Are there any theories on the root cause of specific people being "super spreaders"? Were those people symptomatic at the time of transmission? If not, how long was the asymptomatic transmission window when they were super-spreading, based on their traced contacts?
Historically, we quarantine the sick. Covid responses have quarantined the healthy, based on claims of pre-symptomatic transmission. If we can quantify an observed transmission window (2h? 1d?) in pre-symptomatic super spreaders, before viral load reaches a threshold that causes symptoms, then we can better estimate transmission risk.
Most of the evidence suggests that PCR specificity is very high - there are not many false positives. [0] Even if there were lots of false positives, the recent spike in cases in the UK can't be attributed to that because there is no reason the errors would be temporally correlated.
The concern over PCR cycle is that you will detect people who are not spreading the disease, but those people had the virus at some point. I'd like more evidence about this societal DoS - contact tracing doesn't take medical resources and unmitigated spread consumes more medical resources, mean discretionary income (in the US at least) is higher than before the pandemic.
> Are there any theories on the root cause of specific people being "super spreaders"?
Yes, there are quite a few papers on the fact that the large majority of Covid-19 spread is by a very small percentage of the people who are infected, moreso than other diseases.
> To summarise, false-positive COVID-19 swab test results might be increasingly likely in the current epidemiological climate in the UK, with substantial consequences at the personal, health system, and societal levels.
Some examples from the article:
- Unnecessary treatment cancellation or postponement
- Potential exposure to infection following a wrong pathway in hospital settings as an in-patient
- Financial losses related to self-isolation, income losses, and cancelled travel
- Psychological damage due to misdiagnosis or fear of infecting others, isolation, or stigmatisation
- Misspent funding (often originating from taxpayers) and human resources for test and trace
- Funding replacements in the workplace
- Increased depression and domestic violence
- Misdirection of policies regarding lockdowns and school closures
There are tried and true historical responses to the incompetence of a few affecting the lives of millions. Even when forgotten, history shows that populations have repeatedly reinvented those responses.
Contact tracing was historically used at the start of a disease outbreak where it can be 100% successful. It's nearly useless later, with only partial visibility due to widespread dispersion. Even a 7x24 Person of Interest panopticon could not trace every contact across urban populations.