The use of randomized controlled trials (RCTs) to study the impact of specific interventions, has over the last decade become a dominant methodology in development microeconomics

However, some argue that socioeconomic RCTs do not test hypothesis rooted in theory and ignore mechanisms of causality
For example,

"In 2006, approximately 1,300 men and women were tested for HIV. They were then offered financial incentives of random amounts ranging from zero to values worth approximately four month’s wages if they maintained their HIV status for approximately one year..."
"Throughout the year, respondents were asked about their sexual behavior three times, through interviewer-administered sexual diaries. Respondents were then tested for HIV, and financial incentives were awarded based on whether they had maintained their HIV status..."
"After the second round of testing, the incentives program stopped."

Taken from the article 'Conditional Cash Transfers and HIV/AIDSPrevention: Unconditionally Promising?'
After the study provided no significant effects on the cash transfer on reported sexual behavior, the researchers hypothesize that the monetary reward was too far in the future for the participants
And for a reduction in risky sexual behavior, the participants would need compensation in the present
The World Bank and others have looked to medical, particularly pharmaceutical, research as a model and as a means of seeming legitimate
But, the use of RCTs in development explicitly seeks to remove or downplay the importance of social, political, and cultural contexts

And humans are less controllable than bodily functions
The pursuit of causality comes at the expense of generalizability which is crucial to expanding programming into different contexts
Complex socioeconomic interventions combine multiple interacting components, which interact in a way that their sum is greater than the effects of the individual parts
Socioeconomic RCTs differ from medical RCTs because participants in the latter usually do not know how the treatment will affect them, whereas, in the former, interventions often require individuals to understand effects well enough to evaluate benefits
Double-blinding is common in medical RCTs but fairly impossible in socioeconomic RCTs
Complex interventions interact with socioeconomic and environmental conditions, organizational readiness, policy context, and target population
The socioeconomic RCTs can also create a treatment sample that differs from the general population that may skew results

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Hard agree. And if this is useful, let me share something that often gets omitted (not by @kakape).

Variants always emerge, & are not good or bad, but expected. The challenge is figuring out which variants are bad, and that can't be done with sequence alone.


You can't just look at a sequence and say, "Aha! A mutation in spike. This must be more transmissible or can evade antibody neutralization." Sure, we can use computational models to try and predict the functional consequence of a given mutation, but models are often wrong.

The virus acquires mutations randomly every time it replicates. Many mutations don't change the virus at all. Others may change it in a way that have no consequences for human transmission or disease. But you can't tell just looking at sequence alone.

In order to determine the functional impact of a mutation, you need to actually do experiments. You can look at some effects in cell culture, but to address questions relating to transmission or disease, you have to use animal models.

The reason people were concerned initially about B.1.1.7 is because of epidemiological evidence showing that it rapidly became dominant in one area. More rapidly that could be explained unless it had some kind of advantage that allowed it to outcompete other circulating variants.
I want to share my thoughts, as someone who has been so alarmed by the so-called "dissident" scientists like Gupta, Heneghan, Kuldorff, Bhattacharya, & Ioannidis who consider themselves brave Galileos unfairly treated by "establishment scientists." I will try not to swear. 1/n


I want to talk about 3 things:
‼️Their fringe views are inhumane, unethical junk science that promotes harm
‼️They complain that they've been marginalized but this is simply untrue
‼️I am sick of people telling me we have to "listen to both sides." There aren't 2 sides here 2/n

These 'dissident' scientists have consistently downplayed COVID-19, urging policymakers not to take aggressive control measures. They claim it is not a serious threat. Gupta even went on TV saying people under 65 shouldn't worry about it!

RECEIPTS

They have consistently argued that policymakers should just let the virus rip, in an attempt to reach herd immunity by natural infection. Kuldorff *continues* to argue for this even now that we have many highly effective, safe vaccines.


We've never controlled a deadly, contagious pandemic before by just letting the virus spread, as this approach kills & disables too many people. In Manaus, Brazil, 66% of the city was infected & an astonishing *1 in 500* people died of COVID-19

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