I appreciate the call for more scrutiny of cost-effectiveness in HSS. Given the EA community’s focus on measurable impact, do you think there’s room to shift some methodological attention toward capturing system-level resilience, which is harder to quantify but critical for long-term outcomes (especially during shocks like pandemics or conflicts)? For example, Rwanda’s long-term investment in community health workers and data systems didn’t show immediate returns, but it was credited with enabling a rapid and coordinated pandemic response – suggesting that some HSS benefits may only become visible during moments of acute stress.
Thanksd @Dee Tomic. I’m interested in what you mean by “resilience” exactly, I’m guessing you mean a Health system which continues to perform at a high standard when put under some stress? I think this is unfortunately really hard to test—how can we know what to attribute any reslience to? Its an important part of a health system, but hard to test. Community Health workers though should show other major effects which are testable besides reslience.
if you’re talking the covid pandemic, then the narrative around a strong “Pandemic response” in East Africa was largely a myth—at least measured by outocomes. Covid spread was hardly prevented at all by the seemingly harsh control measures taken. Most people in East Africa caught Delta within 3 months of it being in the country, and most Omicron within 2 months. The epi curves are insane, they are straight out of a textbook showing uncontrolled spread of a disease. While the virus ripped through the population It was just good fortune that the population was young and didn’t have many cardiovascular comorbidities, so while most people cught covid the mortality rate was super low. We wrote a small piece on this situation in Uganda which is interesting (the epi curves are nuts), and I remember when I checked at the time the Epi curves were almost exactly the same in Rwanda and Kenya.
I’m also interested that you think Rwanda’s investment in community health workers didn’t show immediate returns. This is an area I dont know about, but I was under the impression that community healthworkers did help the country reduce malaria mortality and improve access to care overall in a relatively short time after they were implemented. Again I’m not an expert at all here
You’re right that the effect of data systems are hard to measure in an RCT, that’s certainly one of the exceptions to the rule.
Hi Nick, I really appreciate the thoughtful and detailed reply. You’re absolutely right that “resilience” is a broad and slippery concept, and I agree that attributing outcomes to specific components like CHWs is tricky, especially in crises with many moving parts.
By resilience, I meant something like maintained or recoverable delivery of essential services under stress – not necessarily stopping viral spread, but preserving routine care, adapting quickly (e.g., home-based care), and using real-time data for coordination. I take your point about the COVID epi curves – and agree that the mortality patterns owe much to demographic structure – but I’d argue that Rwanda’s capacity to maintain service delivery (e.g., immunisations, maternal health) and implement decentralised home-based care was in part enabled by their CHW and data infrastructure. That doesn’t negate the limitations of their COVID containment, but points to other dimensions of system functioning.
And yes, you’re absolutely right that Rwanda saw early gains from its CHW programs in areas like malaria and maternal health – I didn’t mean to suggest otherwise, only that some system-wide or crisis-response benefits can be delayed or harder to isolate. I’ll have a read of your Uganda piece – thanks for sharing!
Great insights there, hope to hear from you more on the forum!
Yes thanks to much I understand better now. I agree that Rwanda’s structure is resilient and enabled them to maintain service delivery during the pandemic. Uganda was terrible in this front, for a number of reasons. During the early lockdowns people died because of poor access—this is an article about a kid dying after we couldn’t refer them from one of our OneDay health centers
I think resilience is important but I’m struggling to see how we can test for it in solid ways. In this case I think we have to really on case studies like Rwanda during covid like you say. As a side note like I mentioned in the article, over a 10 year period almost every development thing in Rwanda seemed to work well and bore fruit, and I consider them a success story more than necessarily a model for other countries. Takes a pretty savage dictator to stay on that tight path!
I would hope that many of the same interventions that bring resilience also bring more immediate benefits that would be measurable, but you’re right that won’t always be the case.
I appreciate the call for more scrutiny of cost-effectiveness in HSS. Given the EA community’s focus on measurable impact, do you think there’s room to shift some methodological attention toward capturing system-level resilience, which is harder to quantify but critical for long-term outcomes (especially during shocks like pandemics or conflicts)? For example, Rwanda’s long-term investment in community health workers and data systems didn’t show immediate returns, but it was credited with enabling a rapid and coordinated pandemic response – suggesting that some HSS benefits may only become visible during moments of acute stress.
Thanksd @Dee Tomic. I’m interested in what you mean by “resilience” exactly, I’m guessing you mean a Health system which continues to perform at a high standard when put under some stress? I think this is unfortunately really hard to test—how can we know what to attribute any reslience to? Its an important part of a health system, but hard to test. Community Health workers though should show other major effects which are testable besides reslience.
if you’re talking the covid pandemic, then the narrative around a strong “Pandemic response” in East Africa was largely a myth—at least measured by outocomes. Covid spread was hardly prevented at all by the seemingly harsh control measures taken. Most people in East Africa caught Delta within 3 months of it being in the country, and most Omicron within 2 months. The epi curves are insane, they are straight out of a textbook showing uncontrolled spread of a disease. While the virus ripped through the population It was just good fortune that the population was young and didn’t have many cardiovascular comorbidities, so while most people cught covid the mortality rate was super low. We wrote a small piece on this situation in Uganda which is interesting (the epi curves are nuts), and I remember when I checked at the time the Epi curves were almost exactly the same in Rwanda and Kenya.
https://www.researchgate.net/publication/378869273_Does_epidemiological_evidence_support_the_success_story_of_Uganda’s_response_to_COVID-19
I’m also interested that you think Rwanda’s investment in community health workers didn’t show immediate returns. This is an area I dont know about, but I was under the impression that community healthworkers did help the country reduce malaria mortality and improve access to care overall in a relatively short time after they were implemented. Again I’m not an expert at all here
You’re right that the effect of data systems are hard to measure in an RCT, that’s certainly one of the exceptions to the rule.
Hi Nick, I really appreciate the thoughtful and detailed reply. You’re absolutely right that “resilience” is a broad and slippery concept, and I agree that attributing outcomes to specific components like CHWs is tricky, especially in crises with many moving parts.
By resilience, I meant something like maintained or recoverable delivery of essential services under stress – not necessarily stopping viral spread, but preserving routine care, adapting quickly (e.g., home-based care), and using real-time data for coordination. I take your point about the COVID epi curves – and agree that the mortality patterns owe much to demographic structure – but I’d argue that Rwanda’s capacity to maintain service delivery (e.g., immunisations, maternal health) and implement decentralised home-based care was in part enabled by their CHW and data infrastructure. That doesn’t negate the limitations of their COVID containment, but points to other dimensions of system functioning.
And yes, you’re absolutely right that Rwanda saw early gains from its CHW programs in areas like malaria and maternal health – I didn’t mean to suggest otherwise, only that some system-wide or crisis-response benefits can be delayed or harder to isolate. I’ll have a read of your Uganda piece – thanks for sharing!
Great insights there, hope to hear from you more on the forum!
Yes thanks to much I understand better now. I agree that Rwanda’s structure is resilient and enabled them to maintain service delivery during the pandemic. Uganda was terrible in this front, for a number of reasons. During the early lockdowns people died because of poor access—this is an article about a kid dying after we couldn’t refer them from one of our OneDay health centers
https://www.google.com/amp/s/www.aljazeera.com/amp/features/2020/4/21/children-women-casualties-of-ugandas-coronavirus-transport-ban
I think resilience is important but I’m struggling to see how we can test for it in solid ways. In this case I think we have to really on case studies like Rwanda during covid like you say. As a side note like I mentioned in the article, over a 10 year period almost every development thing in Rwanda seemed to work well and bore fruit, and I consider them a success story more than necessarily a model for other countries. Takes a pretty savage dictator to stay on that tight path!
I would hope that many of the same interventions that bring resilience also bring more immediate benefits that would be measurable, but you’re right that won’t always be the case.