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1 | Country | Philippines | Bangladesh | Nigeria | Rationale | References | |||||||||||||||||||||
2 | Demographics | ||||||||||||||||||||||||||
3 | % of population living rurally | 52.59% | 61.82% | 48.04% | The number of children of interest are the number born each year, times by the fraction living rurally. This is a conservative assumption, since there is evidence of significant organophosphate exposure in urban pregnant women (e.g. Balalian et al. 2021, Sinai cohort summarised in Engel et al. 2016). | https://www.statista.com/statistics/760934/bangladesh-share-of-rural-population/#:~:text=In%202020%2C%20approximately%2061.82%20percent,were%20residing%20in%20rural%20areas. https://tradingeconomics.com/nigeria/rural-population-percent-of-total-population-wb-data.html#:~:text=Rural%20population%20(%25%20of%20total,compiled%20from%20officially%20recognized%20sources. https://tradingeconomics.com/philippines/rural-population-percent-of-total-population-wb-data.html#:~:text=Rural%20population%20(%25%20of%20total,compiled%20from%20officially%20recognized%20sources. | |||||||||||||||||||||
4 | Number of children born each year (2020) | 2,182,500 | 2,889,960 | 7,639,490 | https://knoema.com/atlas/Nigeria/topics/Demographics/Fertility/Number-of-births#:~:text=Number%20of%20births%20of%20Nigeria,by%20our%20digital%20data%20assistant. https://knoema.com/atlas/Bangladesh/topics/Demographics/Fertility/Number-of-births https://knoema.com/atlas/Philippines/topics/Demographics/Fertility/Number-of-births#:~:text=Number%20of%20births%20of%20Philippines,slipped%20by%200.39%20%25%20in%202020. | ||||||||||||||||||||||
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6 | Organophosphate burden | Explanation in Forum post. | |||||||||||||||||||||||||
7 | Median DAP conc. for 50-75th % (nmol/L) | 90 | 90 | 90 | |||||||||||||||||||||||
8 | Median DAP conc. for 75-90th % (nmol/L) | 167 | 167 | 167 | |||||||||||||||||||||||
9 | Median DAP conc. for 90-100th % (nmol/L) | 365 | 365 | 365 | |||||||||||||||||||||||
10 | Proportion of population above 60 nmol/L | 70% | 70% | 70% | |||||||||||||||||||||||
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12 | Organophosphate effect | ||||||||||||||||||||||||||
13 | Uncertainty of effect | 75% | 75% | 75% | I use Bellinger et al.’s (2012) estimate that a ten-fold increase in DAPs causes a loss of 4.25 FSIQ points. I adjust the effect size by 75% (in line with Givewell practice). I make a further adjustment of 75% for the uncertainty of the effect existing, given it is less convincing than the evidence for lead’s DNT. I use Givewell’s figure of 0.22 ‘units of value’ per IQ point gained. | ||||||||||||||||||||||
14 | Effect size adjustment | 75% | 75% | 75% | |||||||||||||||||||||||
15 | IQ points increase per 10-fold decrease in maternal urinary DAP | 4.25 | 4.25 | 4.25 | |||||||||||||||||||||||
16 | Units of value from increasing IQ by 1 point | 0.22 | 0.22 | 0.22 | |||||||||||||||||||||||
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18 | Probability of regulatory outcomes | ||||||||||||||||||||||||||
19 | No effect | 50% | 40% | 75.0% | I make probability estimates of different regulatory outcomes for each case. These are particularly arbitrary, but are slightly more pessimistic than Givewell’s estimates of CPSP’s success. I assume an upper limit of reduction at 20%, although bans in other countries have resulted in decreases of specific metabolites up to 50%. I used relative rather than absolute reductions in exposure because longitudinal U.S. data suggest declines due to regulation of organophosphates are proportional at different exposure levels (Gillezeau et al. 2019). | ||||||||||||||||||||||
20 | 5% reduction in exposure | 30% | 35% | 15.0% | |||||||||||||||||||||||
21 | 10% reduction in exposure | 15% | 20% | 8.0% | |||||||||||||||||||||||
22 | 20% reduction in exposure | 5% | 5% | 2.0% | |||||||||||||||||||||||
23 | Sum reduction in exposure | 0.04 | 0.0475 | 0.0195 | |||||||||||||||||||||||
24 | |||||||||||||||||||||||||||
25 | Effect of regulation | ||||||||||||||||||||||||||
26 | Number of years regulation brought forward | 9 | 9 | 9 | I use the same number of years that regulation is brought forward as Givewell does for CPSP. | ||||||||||||||||||||||
27 | Expected IQ points gained per child | 0.074375 | 0.0883203125 | 0.0362578125 | |||||||||||||||||||||||
28 | Sum of expected IQ points gained each year | 85366 | 157791 | 133067 | |||||||||||||||||||||||
29 | Sum of expected IQ points gained due to regulation | 768293 | 1420116 | 1197599 | |||||||||||||||||||||||
30 | Sum of units of value gained due to regulation | 169024 | 312426 | 263472 | |||||||||||||||||||||||
31 | |||||||||||||||||||||||||||
32 | Cost | ||||||||||||||||||||||||||
33 | Cost of program ($) | 450000 | 390000 | 450000 | Givewell’s estimate of the CPSP budget says adding 3 years of work in Guyana and Tanzania would cost $219,717 each. I make the generous assumption that it costs more than twice as much to perform such work for an expanded list of pesticides that include organophosphates with a high DNT burden. Rounding up, total costs would be $450K per country. I assume Bangladesh is ‘only’ $390,000 total, due to pre-existing activities, networks, and government precedent. | ||||||||||||||||||||||
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35 | Other adjustments | I used the same adjustments for government/monitoring costs as the Givewell CPSP BOTEC. Because the number of pesticides banned for DNT is larger than CPSP’s usual work, the adjustment for agricultural harm is 40% rather than 70%, even though effective alternatives for organophosphates are likely available (Hertz-Picciotto et al. 2018). | |||||||||||||||||||||||||
36 | Government cost of enforcing regulation | 95% | 95% | 95% | |||||||||||||||||||||||
37 | Additional monitoring costs | 90% | 90% | 90% | |||||||||||||||||||||||
38 | Risk of agricultural harm | 40% | 40% | 40% | |||||||||||||||||||||||
39 | Reduced ADHD, ASD | 102% | 102% | 102% | Organophosphates do have convincing links to ADHD and other neurodevelopmental disorders, but I keep the adjustment to 102%. Gaylord et al. (2020) estimates that intellectual disability adds an additional 24% of costs to that from IQ losses, but I use only a 110% adjustment. | ||||||||||||||||||||||
40 | Reduced intellectual disability | 110% | 110% | 110% | |||||||||||||||||||||||
41 | Total adjustments | 0.383724 | 0.383724 | 0.383724 | |||||||||||||||||||||||
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43 | Cost-effectiveness | ||||||||||||||||||||||||||
44 | Units of value per $1,000 (before qualitative adjustments) | 375.6099414 | 801.0912953 | 585.4929105 | |||||||||||||||||||||||
45 | Units of value per $1,000 for GiveDirectly's cash transfer program | 3.4 | 3.4 | 3.4 | |||||||||||||||||||||||
46 | Cost-effectiveness in multiples of cash transfers (before qualitative adjustments) | 110.4735122 | 235.6150869 | 172.2037972 | |||||||||||||||||||||||
47 | Cost-effectiveness in multiples of cash transfers (after qualitative adjustments) | 42.39133799 | 90.41116359 | 66.07872988 | |||||||||||||||||||||||
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