GW's analysis of the indirect effects of Malaria Consortium's SMC programs relative to Cisse et al. 2016 (public)

	A	B	D
1		Value	Notes
2
3	Increase in indirect effects from treating 5-10 year olds as well as treating 3 month to 5 year olds	3	Our understanding is that treating a greater proportion of the infected population is likely to have a more than proportional effect on the indirect effects on the untreated population due to disease transmission dynamics. We have not found relevant published academic literature on this topic, but assume that treating 5-10 year olds results in a ~3x increase in indirect effects based on seeing the early unpublished results of a modelling study shared with us by Professor Matthew Cairns, a researcher at London School of Hygiene and Tropical Medicine. The model used the Imperial College malaria model (https://www.imperial.ac.uk/malaria-modelling/tools-and-data/) to simulate 4 monthly cycles of SMC targeted at different age ranges with 80% coverage, fitting efficacy over time with Zongo et al. 2015 (https://aac.asm.org/content/59/8/4387). It suggests treating 5-10 year olds would result in ~3x the indirect effects of treating 3 month to 4 year olds in the countries in which Malaria Consortium works. Professor Cairns noted that the indirect effects are likely to be lower in areas of high transmission, but we have not yet taken this into account in our model. We have not vetted this model in depth but use it for our best guess in the absence of further information.
4
5	Proportion of population covered in ACCESS-SMC relative to Cisse et al. 2016	63%	Based on Malaria Consortium monitoring data. Mistaken treatment of 6-7 year olds increased the proportion of prevalent cases that were treated by ~19% (vs only treating under 5s). This implies that ~63% of the population covered in Cisse et al. 2016 is covered in a typical ACCESS-SMC program (See "Population treated" sheet)
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7	Effect size relative to Cisse et al. 2016 due to a lower proportion of the population covered	47%	Based on the heuristic that ~doubling the proportion of the population covered increases the indirect effects by ~3x, we assume that the indirect effects scale according to raising the proportion of the population covered to the power of log, base 2 (3)
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9	Adjustment to account for higher transmission rates in Malaria Consortium areas than Cisse et al. 2016	65%	We have seen early unpublished results of a modelling study shared with us by Professor Matthew Cairns, a researcher at London School of Hygiene and Tropical Medicine, which suggests that indirect effects would be ~35% lower in the typical area covered by Malaria Consortium, than in Cisse et al. 2016 due to higher transmission rates in areas covered by Malaria Consortium. (Professor Matthew Cairns, email to GiveWell, September 19, 2018) (unpublished). The model used the Imperial College malaria model, which we have not vetted in detail, to simulate 4 monthly cycles of SMC targeted at different age ranges with 80% coverage, fitting protective efficacy over time with Zongo et al. 2015, an RCT of SMC using a different drug regimen from the one used in the typical Malaria Consortium trials. We have not vetted this model in depth but use it for our best guess in the absence of further information.
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11	Effect size relative to Cisse et al. 2016	31%
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13	Overall adjustment for differences in program coverage and transmission intensity	-69%
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