darshan wrote:Would not there be a trade off of start losing immunity to everyday things if we go in sanitized bubble of killing everything in sight or staying away from it?
For sure protocols and machinations need to be in place moving forward so some country come tomorrow doesn't get any ideas.
Yes there is a big trade-off. Living sanitized with greatly reduced contact with potential pathogens destroys immunity. Limited exposure is the way to go. The alternative is what seems to be the end-goal of allopathic systems - replace the entire immune system with drug cocktails. Neither sustainable nor desirable.
There were some posts on this thread along the lines of - "this virus is the most evolved to date, it will only get worse, viruses will evolve to the point where they have awesome abilities." This virus is neither the most contagious (that would be measles), nor the most deadly (a host of other viruses will beat this one to claim that title), nor the "most evolved" in any sense. Evolution is not linear, that viruses get increasingly better at all aspects like contagiousness, lethality, re-infection, and further accelerated evolution. The viruses need hosts to survive, if they kill off those hosts too quickly, they die out themselves. And mammals (including humans) are also evolving to deal with new threats (although with humans, that process is greatly slowed down by medicine, which aims to keep the status quo and supplement it with drugs).
The initial lockdown was probably inevitable, but it is in no way sustainable in the long term. The need is to evolve a better strategy, keeping the observed characteristics of the virus in mind.
The worst hotspots for this current pandemic, don't show infection rates exceeding 25%. It could be that the virus hasn't done its worst. But the characteristics of the virus seem to be - great inhomogeniety in infectiousness and susceptibility among the target population. It seems (based on the references I linked in my earlier post) that about 9% to 10% of the infected population is responsible for 80% of subsequent infections, and the remaining 90% of the infected population or so only contribute to 20% of subsequent infections. These 9% to 10% or so are the "super spreaders." This was also observed in S. Korea, where the one church caused about 60% of subsequent infections. They had an aggressive tracing program, admittedly. Then there is inhomogeniety in susceptibility. When the most susceptible members get infected and recover (or not), the infection starts petering out. There could be some overlap between infectiousness vs. susceptibility inhomogeniety, which can be accounted for in various ways. For example, infectiousness inhomogeniety could be due to high viral load, which correlates with immune response, and that would overlap with susceptibility inhomogeniety. OTOH, infectiousness could also be determined by the number of contacts which the person has, and above-average social interaction with these contacts - and this would not overlap with susceptibility inhomogeniety.
What all this means, is that the simplistic 1-1/R0 model for the herd immunity threshold doesn't describe the infection dynamics. Accounting for the inhomogenities can be done with more sophisticated models. These models are not new, they seem to have been used with well-recognized (which isn't necessarily the same as - accurately estimated) parameters for malaria, TB, and also the first SARS infection (2002). These diseases also apparently display substantial inhomogenities in infectiousness and susceptibility. With models which account for the inhomogeniety for SARS-2/COVID-19 (10% being super spreaders) the herd immunity threshold with an R0 of 2.4 or so seems to come down to the 10% to 20% range (the simple 1-1/R0 model yields about 58% HIT). References for this statement are in my previous post.
The test of any model being real-world validation - that validation would come from what kind of headway the virus makes when lockdowns are removed. If it continues to advance in former hotspots like NYC, Italy, etc. that would mean that those places are not yet at the end-phase (note - the end state is not herd immunity, infection momentum carries beyond that point, so if the HIT is like 10%, eventually about 20% to 25% would get infected - likewise, with a 60% HI threshold, it seems about 80% to 90% would get infected eventually, with unrestrained spread). Again, references are in my previous post.
If there's not much advance in those former hotspots when lockdowns are lifted, that would imply that there is no point in further lockdowns in those areas, beyond the 20% infection point or so. Blindly repeating the "60% herd immunity threshold, and no part of the world is even close to this" mantra, without keeping in mind the underlying assumptions and (lack of) sophistication of the infection model, does not help.
Spain as a whole shows 5% infected (with a decent sample size of 70,000 or so individuals, >0.1% of the country's population), which is actually a phenomenal number for a country as a whole, especially when it has been under lockdown for a decent while. Individual areas within Spain show infected fractions as high as 15%. Same with France, 4.4% countrywide, much higher in hotspots like Paris. NYC, Italy, Paris, Diamond Princess, etc. being in the 15% to 25% range, might indicate that the simplistic model yielding 60% HIT needs to be reevaluated.
So the need now is to observe what happens as lockdowns are eased, especially in earlier hotspots. That would indicate how to proceed. Of course, there is no need for mathematical models for this, empirical evidence of further disease spread is sufficient, this seems to be the direction India is going in, with R/O/G zones. I only brought up the above, because the "60% infection threshold necessary to stop this disease" mantra keeps getting mindlessly repeated, and it's starting to look like this principle from a naive model might actually drive public policy.