http://www.upmc-biosecurity.org/website/resources/publications/2006/2006-09-15-diseasemitigationcontrolpandemicflu.html
Donald Henderson, arguably most famous Epidemiologist of 20th century - for eradicating smallpox - led a massive research effort in 2006 as part of a bioterrorism planning and readiness project. Lit reviews, recommendations, etc. - where he concluded.... https://twitter.com/KanekoaTheGreat/status/1340357881095319557
Donald Henderson, arguably most famous Epidemiologist of 20th century - for eradicating smallpox - led a massive research effort in 2006 as part of a bioterrorism planning and readiness project. Lit reviews, recommendations, etc. - where he concluded.... https://twitter.com/KanekoaTheGreat/status/1340357881095319557
"Experience has shown that communities faced with epidemics or other adverse events respond best and with the least anxiety when the normal social functioning of the community is least disrupted"
Additionally:
A World Health Organization (WHO) Writing Group, after reviewing the literature and considering contemporary international experience, concluded that “forced isolation and quarantine are ineffective and impractical”.
A World Health Organization (WHO) Writing Group, after reviewing the literature and considering contemporary international experience, concluded that “forced isolation and quarantine are ineffective and impractical”.
Country-level analyses comparing health outcomes b/w countries with extreme heterogeneity in their policies are insightful - each one finds that population age structure and obesity associate with health outcomes/caseloads - not lockdown stringency
https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(20)30208-X/fulltext
https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(20)30208-X/fulltext
https://ideas.repec.org/p/wai/econwp/20-06.html
Similarly on a county by county basis in the U.S. Notice author mentions 'identification' - this refers to whether there are valid counterfactuals, and are able to determine parameter value from observables, or whether there's a different parameterization
Similarly on a county by county basis in the U.S. Notice author mentions 'identification' - this refers to whether there are valid counterfactuals, and are able to determine parameter value from observables, or whether there's a different parameterization
that can generate the same distribution of observations. In other words - there are certain rigors required to model a valid counterfactual and disentangle various confounders if you want to say something about causality, rather than just an association/correlation
Highly suggest anyone interested take a look through the paper above, it is done properly using IV regression to identify lockdown parameter to test whether or not lockdowns had a causal effect by using political drivers of lockdowns as an instrument (to get exogenous variation)
Here's a favorite - NBER paper showing that 4 stylized facts about the virus behavior persist among all countries in study despite heterogeneity in policies / lockdown stringency
https://www.nber.org/system/files/working_papers/w27719/w27719.pdf
https://www.nber.org/system/files/working_papers/w27719/w27719.pdf
It's a reminder that we're dealing with nature, not something you can just POLICY your way out of w/ mask mandates. The implications here are pretty devastating for the mask/lockdown commies once you reflect on these.
https://www.sciencedirect.com/science/article/pii/S0305750X20302977?via%3Dihub
Again confirming how much age structure plays a role in the health outcomes we're observing:
"Population age structures alone may account for four-fold variation in average regional infection-fatality ratios across Europe"
Again confirming how much age structure plays a role in the health outcomes we're observing:
"Population age structures alone may account for four-fold variation in average regional infection-fatality ratios across Europe"