EA - Zzapp Malaria: More effective than bed nets? (Wanted: CTO, COO and Funding) by Yonatan Cale

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Zzapp Malaria: More effective than bed nets? (Wanted: CTO, COO & Funding), published by Yonatan Cale on September 9, 2022 on The Effective Altruism Forum. TL;DR: This post describes Zzapp’s approach and effectiveness from their own perspective, intended as an intro aimed at the Effective Altruism community, as an invitation to investigate further and maybe fund them. They claim to be 2x more cost effective than bed nets in reducing malaria in urban and semi-urban areas (over 70% of Africa’s population). Epistemic status: Based on conversations with Arnon, the CEO of Zzapp Malaria, not cross checked with other info such as Givewell’s review of Against Malaria Foundation. Zzapp’s approach and theoretical reason to think it would work You can skip to their experiment and how it went, if you prefer. TL;DR: Spray water bodies with larvicide to prevent mosquitoes from reproducing, and do it extra well by managing the considerable ops work of finding and spraying the water bodies using satellite imaging and an app for the people on the ground. Spraying water bodies with larvicide - is tried and works, unrelated to Zzapp Sources [link] [link]. Theoretical advantages compared to bed nets In every place that malaria was eliminated (which happened many times), larvicide (the treatment of standing water bodies) was the main component. Bed Nets only help people indoors during the night. Many people don’t use their bed nets. Mosquitos developed resistance to the bes nets’ insecticide in many countries Note I think Givewell already took the problems into account in their analysis, and Arnon emphasizes he thinks bed nets are great, and this is a pitch for using larvicide in urban (and semi urban) areas, not for stopping distributing bed nets. Zzapp think the ideal solution would probably combine many interventions. We are writing this as a comparison with bed nets since EAs already think bed nets are great. Problems in existing larvicide approaches Existing solutions: Problems in theory Coverage is important It’s important [how many water bodies you find] and [how many of those you spray], and the difference between 95% and 50% is really big, similarly to the situation when vaccinating 95% or 50% of the population, because of the effect on R (reproduction number) - less infected people will infect less other people, it snowballs but in a good way (hopefully), and the same is true about reproduction of mosquitos. Existing solutions have bad coverage People miss water bodies in the areas they are assigned to search People miss entire areas Even when water bodies are found, the spray team sometimes may still skip them or forget to treat them according to schedule Small RCT Ref to a (tiny) randomized controlled trial run by Zzapp and AngloGold Ashanti Malaria Control (AGAMal), where two groups scanned the same square kilometer, one group used the app and one didn’t and the group with the app found 28% more water bodies. Scanning an entire town In a different operation, when scanning an entire town with AGAMal, they found 20x more water bodies when using Zzapp’s app. (publication in progress, we’ll add a link when it’s ready). From that they think that on a larger scale the app has an even greater impact.What happened behind the scenes is that without the app - the scanners skipped entire neighborhoods. Not a problem: Poisoning water bodies The larvicide in the relevant quantities (bti) isn’t poisonous to humans, animals, or other insects except for mosquitoes and black flies. Zzapp’s advantages compared to “manual” larvicide Zzapp has an app they give to the people “on the ground”: The app follows “where do the people go go” and lets the people mark “I checked this house’s garden” and “I found a water source here” and “this house didn’t let me in” The control room shows a map with ״Here...