"What I’m sure about is that it does not cause profound, long-term immunodeficiency like that seen with HIV. I am sure about that because we have not seen the hallmarks of such immunodeficiency in recovered COVID-19 patients."
Also, there has been a *lot* of data collected on immunity to SARS-CoV-2 itself in the recovered patients. A lot. And it does show that survivors like yourself have enhanced immunity, not reduced, to that specific virus.
Do you have any thoughts on how the widespread availability of at-home COVID tests should affect how we look at the test positivity rate? On one hand, if people are using at-home tests and then following up with PCR tests to confirm positives, this would increase the test positivity rate, and what used to be considered a "high" rate might no longer be indicative of a lot of cases that are being missed. On the other hand, the availability of at-home tests might mean that PCR tests are being skipped entirely, and we're just missing lots of cases, so we would be missing lots of cases even when the positivity rate was "low".
Good question. This is yet another reason that I think Dr. Natalie Dean's suggestion of random sampling to assess prevalence is a very good one. There are too many situations where the aggregated data reported from testing entities (including doctor's offices) is too self-selected to be really meaningful. It has a lot of problems--people only testing if they are concerned about COVID, people using home tests, people not being able to even *get* tests.
A random sample approach would resolve most of these problems and give us an excellent prevalence estimate, so I'm increasingly in the camp that local public health authorities should switch to this. Counting positive tests in the aggregate as your chief disease-tracking tool makes sense when you have a few hundred cases worldwide, not a few million.
"What I’m sure about is that it does not cause profound, long-term immunodeficiency like that seen with HIV. I am sure about that because we have not seen the hallmarks of such immunodeficiency in recovered COVID-19 patients."
Also, there has been a *lot* of data collected on immunity to SARS-CoV-2 itself in the recovered patients. A lot. And it does show that survivors like yourself have enhanced immunity, not reduced, to that specific virus.
Do you have any thoughts on how the widespread availability of at-home COVID tests should affect how we look at the test positivity rate? On one hand, if people are using at-home tests and then following up with PCR tests to confirm positives, this would increase the test positivity rate, and what used to be considered a "high" rate might no longer be indicative of a lot of cases that are being missed. On the other hand, the availability of at-home tests might mean that PCR tests are being skipped entirely, and we're just missing lots of cases, so we would be missing lots of cases even when the positivity rate was "low".
Good question. This is yet another reason that I think Dr. Natalie Dean's suggestion of random sampling to assess prevalence is a very good one. There are too many situations where the aggregated data reported from testing entities (including doctor's offices) is too self-selected to be really meaningful. It has a lot of problems--people only testing if they are concerned about COVID, people using home tests, people not being able to even *get* tests.
A random sample approach would resolve most of these problems and give us an excellent prevalence estimate, so I'm increasingly in the camp that local public health authorities should switch to this. Counting positive tests in the aggregate as your chief disease-tracking tool makes sense when you have a few hundred cases worldwide, not a few million.