GiveWell's CEA for vitamin A supplementation (VAS) for codelivery grant to Malaria Consortium (public)

	A	C	E	F
1	Guide to interpreting this cost-effectiveness analysis

2	Sheet descriptions
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4			Simple CEA	This sheet contains a simplified version of the CEA that is designed to be comparable to our CEAs of other programs.
5			Main CEA	This sheet contains the primary calculations that result in final cost-effectiveness estimates. This sheet draws on inputs from the "Inputs" sheet and inputs calculated in the other supplemental sheets listed below.
6			Counterfactual mortality	This sheet contains our calculations of how high mortality rates would be in the absence of VAS campaigns.
7			External validity	This sheet contains our calculations of the external validity adjustments we apply to the effect of VAS on mortality, based on differences between the populations treated in studies and the populations treated by grantee programs.
8			Leverage/Funging	This sheet contains our calculations of the impact that crowding in and crowding out funding by other contributors has on the benefits of the program.
9			Inputs	This sheet contains all of the manually entered input values informing the CEA, along with the sources and reasoning supporting them. This sheet also contains inputs sourced from the "GBD estimates" sheet.
10			GBD estimates	This sheet contains disease burden and population datasets downloaded from the Institute of Health Metrics (IHME)'s Global Burden of Disease (GBD) project.
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12	Terminology key
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14		Terms specific to this CEA
15			VAS	Stands for vitamin A supplementation; describes an intervention in which vitamin A supplements are delivered to a population in an effort to reduce rates of vitamin A deficiency.
16			VAD	Stands for vitamin A deficiency; describes a condition resulting from insufficient dietary intake of vitamin A that is associated with increased morbidity and mortality.
17			Stunting	Describes a condition in which a child has a height-for-age measurement more than two standard deviations below average. We use rates of stunting as one of several proxies for rates of vitamin A deficiency.
18			Wasting	Describes a condition in which a child has a weight-for-age measurement more than two standard deviations below average. We use rates of wasting as one of several proxies for rates of vitamin A deficiency.
19			Anemia	Describes a condition in which a person does not have enough healthy red blood cells or hemoglobin in their blood to transport oxygen through their body. We use anemia rates as one of several proxies for rates of vitamin A deficiency.
20			Poverty headcount	Refers to the percentage of a population that has income or consumption levels lower than a given poverty benchmark.
21			Fixed-effects	A fixed-effect meta-analysis assumes that the true impact of the intervention is consistent in every study in the analysis. Differences between study results are assumed to be solely down to chance. The main estimate from the analysis can be interpreted as the typical intervention effect.
22			Random-effects	A random-effects meta-analysis assumes that the true impact of the intervention varies and follows some distribution. The main estimate from the analysis can be interpreted as the average impact of the intervention across heterogenous studies with different findings.
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24		Terms used across GiveWell's CEAs
25			Internal validity	Describes an adjustment we make to the treatment effect of an intervention to account for the possibility that the treatment effects found in studies may not represent the true effect the intervention had on the populations studied.
26			External validity	Describes an adjustment we make to the treatment effect of an intervention to account for differences in the program implementation or populations treated in studies from the program implementation or populations treated by grantee programs.
27			Leverage	Describes a situation where a grantee's spending on a program causes other organizations or governments to contribute more to the program than they otherwise would have. In most cases, accounting for leverage increases cost-effectiveness
28			Funging	Describes a situation where a grantee's spending on a program causes other organizations or governments to contribute less to the program than they otherwise would have. In most cases, accounting for funging decreases cost-effectiveness.
29			In-kind contributions	Describes non-financial (e.g., staff time, office space) contributed to a program that might otherwise have been used for other activities or programs.
30			Counterfactual	In most cases, describes the state of the world that would exist if we did not provide funding to a grantee for a program. When discussing the "counterfactual value of other actors' spending," we are referring to how much benefit another organization's or government's spending would generate if it were spent on something other than the grantee program.
31			Moral weights	To compare cost-effectiveness across different programs, we use ‘moral weights’ to quantify the benefits of different program impacts (e.g. increased income vs reduced deaths). We benchmark the value of each benefit to a value of 1, which we define as the value of doubling someone’s consumption for one year.
32			Philanthropic actors	Non-governmental organizations (NGOs) providing funding to philanthropic programs.
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34	Unit and source key
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36		Unit labels used in the CEA
37			#	Number
38			per 1k	Rate per 1,000
39			per 100k	Rate per 100,000
40			$	U.S. dollars
41			ln($)	The natural logarithm of a monetary value in U.S. dollars
42			%	Percentage
43			ppt	Percentage points
44			UoV	Units of value: an arbitrary unit GiveWell uses to compare the moral value of different types of outcomes, such as saving lives or increasing income
45			xcash	Cost-effectiveness in terms of multiples of GiveDirectly's unconditional cash transfer program
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47		Source labels used in the CEA
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49			Input	A value pulled from the "Inputs" sheet
50			Calc	A value calculating using other values in the same sheet
51			Supp	A value pulled from one of the sheets hosting supplemental calculations
52			Main	A value pulled form the "Main CEA" sheet
53			Feed	A value pulled from an earlier section within the same sheet
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55	GiveWell analyses informing this model
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57		Analyses specific to this CEA
58			GiveWell's analysis of coverage estimates from RCTs of VAS from Imdad et al. 2017
59			GiveWell's development effects estimation model for VAS
60			GW's analysis of baseline mortality for Imdad et al. 2017
61			GiveWell's analysis of the internal validity adjustment for VAS
62			GiveWell's analysis of the effect size of 1 round of VAS
63			GiveWell's analysis of counterfactual VAS coverage
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65		Analyses referenced across GiveWell's CEAs
66			GW's moral weights and discount rate
67			GW's supplemental intervention-level adjustments
68			GW's analysis of the counterfactual value of Global Fund spending
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