It is unclear to me whether the ripple effects (indirect longterm effects) of life saving interventions are beneficial or harmful. From Wilde et. al (2020), whose abstract is below (emphasis mine), bednets increase fertility 1 to 3 years after their distribution, but decrease it afterwards, so population initially increases[1], but may decrease soon after the distribution.
We examine the extent to which recent declines in child mortality and fertility in SubSaharan Africa can be attributed to insecticide-treated bed nets (ITNs). Exploiting the rapid increase in ITNs since the mid-2000s, we employ a difference-in-differences estimation strategy to identify the causal effect of ITNs on mortality and fertility. We show that the ITN distribution campaigns reduced all-cause child mortality, but surprisingly increased total fertility rates in the short run in spite of reduced desire for children and increased contraceptive use. We explain this paradox in two ways. First, we show evidence for an unexpected increase in fecundity and sexual activity due to the better health environment after the ITN distribution. Second, we show evidence that the effect on fertility is positive only temporarily – lasting only 1-3 years after the beginning of the ITN distribution programs – and then becomes negative. Taken together, these results suggest the ITN distribution campaigns may have caused fertility to increase unexpectedly and temporarily, or that these increases may just be a tempo effect – changes in fertility timing which do not lead to increased completed fertility.
So lifesaving interventions may decrease longterm population. Moreover, Eden and Kuruc (2024) suggest decreasing population decreases longterm income per capita, so lifesaving interventions may end decreasing the longterm size of the economy too. If so, the ripple effects would tend to be harmful.
For life-saving to reduce population, it would have to reduce total fertility by more than 1 per child saved, which is extremely implausible on its face. Your authors’ interpretation is that there is no overall effect on fertility rates: “In this case, women simply shifted the same number of births forward, leading to more births today and less in the future.” (Indeed, if you look at their data in Figure 6, there is no evidence of any reduction in total fertility, let alone a reduction as huge as would be required for your claims.) This implies increased population long term as the saved children later go on to reproduce.
For life-saving to reduce population, it would have to reduce total fertility by more than 1 per child saved, which is extremely implausible on its face.
Why? Each bednet costs 5 $, and Against Malararia Foundation (AMF) saves one life per 5.5 k$, so 1.1 k bednets (= 5.5*10^3/5) are distributed per life saved. I think each bednet covers 2 people (for a few years), and I assume half are girls/women, so 1.1 k girls/women (= 1.1*10^3*2*0.5) are affected per life saved. As a result, population will decrease if the number of births per girl/women covered decreases by 9.09*10^-4 (= 1/(1.1*10^3)). The number of births per women in low income countries in 2022 was 4.5, so that is a decrease of 0.0202 % (= 9.09*10^-4/4.5). Does this still seem implausible? Am I missing something?
Your authors’ interpretation is that there is no overall effect on fertility rates: “In this case, women simply shifted the same number of births forward, leading to more births today and less in the future.” (Indeed, if you look at their data in Figure 6, there is no evidence of any reduction in total fertility, let alone a reduction as huge as would be required for your claims.) This implies increased population long term as the saved children later go on to reproduce.
That is one hypothesis advanced by the author, but not the only interpretation of the evidence? I think you omitted crucial context around what you quoted (emphasis mine):
However, the third interpretation is a tempo vs. quantum effect: perhaps the ITN distribution induced women to have more births now, but did not change the number of overall births they intended to have. In this case, women simply shifted the same number of births forward, leading to more births today and less in the future [this is the only sentence you quoted]. Therefore, it is important to view our positive fertility results as short run, one year effects, rather than the effect on completed fertility.
My interpretation is that the author thinks the effect on total fertility is unclear. I was not clear in my past comment. However, by “lifesaving interventions may decrease longterm population”, I meant this is one possibility, not the only possibility. I agree lifesaving interventions may increase population too. One would need to track fertility for longer to figure out which is correct.
Indeed, if you look at their data in Figure 6, there is no evidence of any reduction in total fertility, let alone a reduction as huge as would be required for your claims.
From Figure 6 below, there is a statistically significant increase in fertility in year 0 (relative to year −1), and a statistically significant decrease in year 3. Eyeballing the area under the black line, I agree it is unclear whether total fertility increased. However, it is also possible fertility would remain lower after year 3 such that total fertility decreases. Moreover, the magnitude of the decrease in fertility in year 3 is like 3 % or 4 %, which is much larger than the minimum decrease of 0.0202 % I estimated above for population decreasing. Am I missing something? Maybe the effect size is being expressed as a fraction of the standard deviation of fertility in year −1 (instead of the fertility in year −1), but I would expect the standard deviation to be at least 10 % of the mean, such that my point would hold.
Why would being under a bednet reduce fertility? Two things that could make sense:
(1) The authors’ hypothesis of a mere timing shift, as fertility temporarily increases as a result of better health, followed by a (presumably similarly temporary) compensatory reduction in the immediately subsequent years, perhaps from the new parents stabilizing on their preferred family size. As noted, this hypothesis does not imply reduced total fertility.
(2) If some families stabilize on their preferred family size by (eventually) having an extra baby in the event that a previous one dies tragically early, then fertility (total births) could be expected to drop slightly as a result of life-saving interventions, but not to the point of exceeding the number of lives saved (or reducing total population).
In the absence of a plausible explanation that should lead us to view the outcome in question as especially likely, randomly positing a systematic negative population effect seems unreasonable to me. Anything is possible, of course. But selectively raising unsupported possibilities to salience just to challenge others to rule them out is a bad way to approach longtermist analysis, in my view. (Basically, the slight risk of negative fertility effects is outweighed by the expected gain in population, but common habits of thought overweight salient “risks” in a way that makes this dialectical method especially distorting.) See also: It’s Not Wise to be Clueless.
In places where lifetime births/woman has been converging to 2 or lower, saving one child’s life should lead parents to avert a birth they would otherwise have. The impact of mortality drops on fertility will be nearly 1:1, so population growth will hardly change. In the increasingly exceptional locales where couples appear not to limit fertility much, such as Niger and Mali, the impact of saving a life on total births will be smaller, and may come about mainly through the biological channel of lactational amenorrhea. Here, mortality-drop-fertility-drop ratios of 1:0.5 and 1:0.33 appear more plausible.
So it looks like saving lives in low income countries decreases fertility, but still increases population size. Because of the decrease in fertility, it may be good to downgrade the cost-effectiveness. The above would suggest multiplying it by around 0.5 (= 1 − 0.5) to 0.7 (= 1 − 0.33).
Yeah, that’s more in line with what I would expect. (Except the first sentence may be a bit hasty. Many first-world couples delay parenting until their 30s. If a child dies, they may not be able to have another—esp. since a significant period of grieving may be necessary before they were even willing to.)
Hi Richard,
It is unclear to me whether the ripple effects (indirect longterm effects) of life saving interventions are beneficial or harmful. From Wilde et. al (2020), whose abstract is below (emphasis mine), bednets increase fertility 1 to 3 years after their distribution, but decrease it afterwards, so population initially increases[1], but may decrease soon after the distribution.
So lifesaving interventions may decrease longterm population. Moreover, Eden and Kuruc (2024) suggest decreasing population decreases longterm income per capita, so lifesaving interventions may end decreasing the longterm size of the economy too. If so, the ripple effects would tend to be harmful.
Because bednets also decrease nearterm mortality, which is why Against Malaria Foundation is one of GiveWell’s top charities
For life-saving to reduce population, it would have to reduce total fertility by more than 1 per child saved, which is extremely implausible on its face. Your authors’ interpretation is that there is no overall effect on fertility rates: “In this case, women simply shifted the same number of births forward, leading to more births today and less in the future.” (Indeed, if you look at their data in Figure 6, there is no evidence of any reduction in total fertility, let alone a reduction as huge as would be required for your claims.) This implies increased population long term as the saved children later go on to reproduce.
Why? Each bednet costs 5 $, and Against Malararia Foundation (AMF) saves one life per 5.5 k$, so 1.1 k bednets (= 5.5*10^3/5) are distributed per life saved. I think each bednet covers 2 people (for a few years), and I assume half are girls/women, so 1.1 k girls/women (= 1.1*10^3*2*0.5) are affected per life saved. As a result, population will decrease if the number of births per girl/women covered decreases by 9.09*10^-4 (= 1/(1.1*10^3)). The number of births per women in low income countries in 2022 was 4.5, so that is a decrease of 0.0202 % (= 9.09*10^-4/4.5). Does this still seem implausible? Am I missing something?
That is one hypothesis advanced by the author, but not the only interpretation of the evidence? I think you omitted crucial context around what you quoted (emphasis mine):
My interpretation is that the author thinks the effect on total fertility is unclear. I was not clear in my past comment. However, by “lifesaving interventions may decrease longterm population”, I meant this is one possibility, not the only possibility. I agree lifesaving interventions may increase population too. One would need to track fertility for longer to figure out which is correct.
From Figure 6 below, there is a statistically significant increase in fertility in year 0 (relative to year −1), and a statistically significant decrease in year 3. Eyeballing the area under the black line, I agree it is unclear whether total fertility increased. However, it is also possible fertility would remain lower after year 3 such that total fertility decreases. Moreover, the magnitude of the decrease in fertility in year 3 is like 3 % or 4 %, which is much larger than the minimum decrease of 0.0202 % I estimated above for population decreasing. Am I missing something? Maybe the effect size is being expressed as a fraction of the standard deviation of fertility in year −1 (instead of the fertility in year −1), but I would expect the standard deviation to be at least 10 % of the mean, such that my point would hold.
Why would being under a bednet reduce fertility? Two things that could make sense:
(1) The authors’ hypothesis of a mere timing shift, as fertility temporarily increases as a result of better health, followed by a (presumably similarly temporary) compensatory reduction in the immediately subsequent years, perhaps from the new parents stabilizing on their preferred family size. As noted, this hypothesis does not imply reduced total fertility.
(2) If some families stabilize on their preferred family size by (eventually) having an extra baby in the event that a previous one dies tragically early, then fertility (total births) could be expected to drop slightly as a result of life-saving interventions, but not to the point of exceeding the number of lives saved (or reducing total population).
In the absence of a plausible explanation that should lead us to view the outcome in question as especially likely, randomly positing a systematic negative population effect seems unreasonable to me. Anything is possible, of course. But selectively raising unsupported possibilities to salience just to challenge others to rule them out is a bad way to approach longtermist analysis, in my view. (Basically, the slight risk of negative fertility effects is outweighed by the expected gain in population, but common habits of thought overweight salient “risks” in a way that makes this dialectical method especially distorting.) See also: It’s Not Wise to be Clueless.
From the abstract of David Roodman’s paper on The Impact of Life-Saving Interventions on Fertility:
So it looks like saving lives in low income countries decreases fertility, but still increases population size. Because of the decrease in fertility, it may be good to downgrade the cost-effectiveness. The above would suggest multiplying it by around 0.5 (= 1 − 0.5) to 0.7 (= 1 − 0.33).
Yeah, that’s more in line with what I would expect. (Except the first sentence may be a bit hasty. Many first-world couples delay parenting until their 30s. If a child dies, they may not be able to have another—esp. since a significant period of grieving may be necessary before they were even willing to.)