I want to use cost per outcome metrics from GiveWell & the Impact Genome Registry to derive benefit-cost ratios for different social interventions.
This will help channel donations to the most impactful programs.
Data Sources:
Impact Genome Registry:
Example: From 2009-2021, Against Malaria Foundation saved 60,900 lives at a cost of $322,984,099 by distributing insecticide treated nets.
Analysis:
If this program was conducted in India, the QALY is $6,100 (PPP adjusted to India). Average age of India is 28.7 years old and life expectancy is 70.42 years .
Benefit of intervention:
number of years saved (life expectancy - average age) x QALY x number of lives saved = 41.3 x 6,100 x 60,900 = $15,342,537,000
Benefit Cost Ratio:
$15,342,537,000 / $322,984,099 = 47.5
Deliverables: At the end of August, I will complete the following for oracular funding:
A table listing the benefit-cost ratio of various interventions
A report detailing the findings & methodology used to arrive at conclusions
Open-source python code that calculates BC ratio & renders a visual representation of the same
Project lead Siddique Patel has been researching, investing and advising clients in alternative financial products since 2013. He has a deep understanding of use cases for public blockchains and is competent in python.
His team has been working on data driven outcome financing since October 2021. The focus has been on replicating social impact bonds and pay-for-performance contracts in a retail based donation model.
We need a total of $4500 as runway until August '23. Funds will be utilized in the following manner
$3000 as a stipend to project lead for 5 months
$1500 for additional software developer resources