This is a special post for quick takes by Axby. Only they can create top-level comments. Comments here also appear on the Quick Takes page and All Posts page.
Personal take on the topbiosecurity interventions, after 7 weeks of participation in Bluedot Impact's Biosecurity Fundamentals reading group.
I have shortlisted these four interventions based on what I think are most impactful for preventing extreme pandemics, and tractable (based on my vague sense of public trust and political will in most countries).
Epidemic intelligence - specifically to estimate how likely an outbreak is going to become a pandemic based on pathogen properties → crucial for informing non-pharmaceutical interventions
Targeted and clinical and metagenomic sequencing could help to collect data points
Digital detection tools as well
Enabling non-pharmaceutical interventions such as contact tracing, quarantines and lockdowns (took many months to be implemented in most countries, if at all)
Vaccine delivery - took almost 2 years for Global South (e.g. African countries, India and Indonesia) to be able to vaccinate 60% of their population
Governing benchtop synthesis machines above a certain number of base pairs, since allowing malicious actors to have access to such machines would pose an irreversible risk.
Reflecting on our COVID-19 experience, there were five key problems that would undermine humanity's ability to survive extreme pandemics.
Firstly, it took us about two months from the detection of a novel viral pneumonia to the lockdown of Wuhan. Two months is too long a duration to try to contain the virus within the region. By then, cases of COVID-19 were already reported in Thailand and the United States. This seems quite tractable because central governments have an incentive to contain the spread of viruses within one local region before it spreads to other regions.
Relatedly, the second bottleneck is the time it took for each country to implement contact tracine regimes and lockdowns. The United States did not impose any lockdowns, whereas other countries seem to have taken a couple of months after the first local case before lockdowns were imposed.
A key reason for why governments took such a long time to impose adequate movement control measures is that the epidemiological properties of the virus too unclear. As such, there wasn't enough political will to impose such costly disease control measures. Better epidemic intelligence -- specifically, to provide estimates on how fast the disease can spread, and its lethality -- is crucial to enable governments to implement non-pharmaceutical interventions as quickly as possible.
The fourth bottleneck was the time it took for clinical trials of the vaccines. The design of the vaccine took just slightly over two months from when the COVID-19 genome sequence was published (on 16 Mar 2020). However, it took another nine months for Moderna's coronavirus vaccine to be approved for emergency use on December 18, 2020. Much of the time was spent on clinical trials. By then, the peak of the outbreak had passed in most countries, which means that vaccines were not as effective.
The fourth bottleneck is the time it takes for vaccines to be delivered globally. After Moderna's vaccine was developed and approved on December 18, it is estimated that another two years were needed for the vaccine to be delivered in very populous parts of the world, including Indonesia, India, and the entire African continent. No country would be able to impose lockdowns and disease control measures for such a long time. Part of the reason for why vaccine delivery took such a long time was vaccine nationalism.
From this analysis of the bottlenecks that we face during COVID-19, we can identify the key interventions that would prevent extreme pandemics.
Firstly, and quite uncontroversially, we need better epidemic intelligence. We need to go beyond identifying the genome of novel pathogens to estimating their epidemiological properties such as R0 as quickly as possible. This will help to inform and legitimize non-pharmaceutical interventions such as contract tracing, quarantines and lockdowns. Beyond DNA sequencing methods (including metagenomic sequencing), digital methods could also help to inform epidemiological estimates.
Secondly, governments need to impose non-pharmaceutical interventions such as quarantines and lockdowns more quickly in order to contain novel epidemics within regions. In support of such non-pharmaceutical interventions, digital detection could also enable more effective contact tracing and more targeted interventions.
Thirdly, vaccine equity is crucial for humanity to recover from extreme pandemics; no one is safe until everybody is safe. Speeding up clinical trials is also important, but I would think that pharmaceutical companies already have a strong incentive to speed this up as much as possible. As such, more advocacy and government funding is not as crucial.
Other preventive measures like DNA synthesis screening and governing do use research of concern are also important. However, I think that are less likely to receive public support as there haven't been any cases of successful bioterror attacks using pandemic-capable viruses. Nevertheless, governing access to benchtop synthesis machines (and hardwiring screening measures into their design) is still important to deny potentially malicious actors the capability to develop pandemic-capable viruses as bioweapons. The proliferation of such capabilities -- like the proliferation of fissile material -- would be quite irreversible.
(Not quite sure how to evaluate clean-air interventions like far-UVC or air filtration. My view would probably depend most on whether they are effective enough to prevent even the worst pandemics, second would be whether they would be cost effective enough to be deployed widely)
I'm currently trying to develop an estimation of the effectiveness of pursuing a career in mitigating Global Catastrophic Biological Risks (GCBRs). As part of the EA Global in-depth reading group, I read "Existential Risk and Cost-Effective Biosecurity" by Piers Millett and Andrew Snyder-Beattie (2017). The authors' estimates of the probability of GCBRs over the next century seemed very low (from 1.6 x 10^-6 to 0.02 over the next century, depending on which of the three methodologies used by the authors gives a better estimate)[1].
I could not seem to find any other sources that try to rigorously estimate the risks of GCBRs. Would forum users would be able to point me to some, please? [2] Thanks all in advance!
[1] Even with the highest estimate of 0.02 of GCB events per century, longtermist assumptions (of 10^16 potential lives lost, as indicated by the author) are needed for GCBR-mitigation to be more cost-effective than Givewell's top charities (taken as $4500/life saved). I would prefer not to make longtermist assumptions, in line with Neel Nanda's (2021) call to "Simplify EA Pitches to 'Holy Shit, X-Risk'".
[2] With this input, I hope to write a more extensive post clarifying the priority areas in mitigating GCBRs (possibly pointing to risks of GCBRs from emerging biotech that enable bioterrorism as a priority area; in contrast with a focus on state-led biowarfare). If we are focusing on emerging biotech rather than existing biotech, estimates of whether these technologies would even materialise would be an important consideration as well.
Hey, this is a great question with good context for potential answers too. If you don’t get any substantive responses here, I’d suggest posting as a question on the frontpage — the shortforms really don’t get much visibility.
Personal take on the top biosecurity interventions, after 7 weeks of participation in Bluedot Impact's Biosecurity Fundamentals reading group.
I have shortlisted these four interventions based on what I think are most impactful for preventing extreme pandemics, and tractable (based on my vague sense of public trust and political will in most countries).
Reflecting on our COVID-19 experience, there were five key problems that would undermine humanity's ability to survive extreme pandemics.
Firstly, it took us about two months from the detection of a novel viral pneumonia to the lockdown of Wuhan. Two months is too long a duration to try to contain the virus within the region. By then, cases of COVID-19 were already reported in Thailand and the United States. This seems quite tractable because central governments have an incentive to contain the spread of viruses within one local region before it spreads to other regions.
Relatedly, the second bottleneck is the time it took for each country to implement contact tracine regimes and lockdowns. The United States did not impose any lockdowns, whereas other countries seem to have taken a couple of months after the first local case before lockdowns were imposed.
A key reason for why governments took such a long time to impose adequate movement control measures is that the epidemiological properties of the virus too unclear. As such, there wasn't enough political will to impose such costly disease control measures. Better epidemic intelligence -- specifically, to provide estimates on how fast the disease can spread, and its lethality -- is crucial to enable governments to implement non-pharmaceutical interventions as quickly as possible.
The fourth bottleneck was the time it took for clinical trials of the vaccines. The design of the vaccine took just slightly over two months from when the COVID-19 genome sequence was published (on 16 Mar 2020). However, it took another nine months for Moderna's coronavirus vaccine to be approved for emergency use on December 18, 2020. Much of the time was spent on clinical trials. By then, the peak of the outbreak had passed in most countries, which means that vaccines were not as effective.
The fourth bottleneck is the time it takes for vaccines to be delivered globally. After Moderna's vaccine was developed and approved on December 18, it is estimated that another two years were needed for the vaccine to be delivered in very populous parts of the world, including Indonesia, India, and the entire African continent. No country would be able to impose lockdowns and disease control measures for such a long time. Part of the reason for why vaccine delivery took such a long time was vaccine nationalism.
From this analysis of the bottlenecks that we face during COVID-19, we can identify the key interventions that would prevent extreme pandemics.
Firstly, and quite uncontroversially, we need better epidemic intelligence. We need to go beyond identifying the genome of novel pathogens to estimating their epidemiological properties such as R0 as quickly as possible. This will help to inform and legitimize non-pharmaceutical interventions such as contract tracing, quarantines and lockdowns. Beyond DNA sequencing methods (including metagenomic sequencing), digital methods could also help to inform epidemiological estimates.
Secondly, governments need to impose non-pharmaceutical interventions such as quarantines and lockdowns more quickly in order to contain novel epidemics within regions. In support of such non-pharmaceutical interventions, digital detection could also enable more effective contact tracing and more targeted interventions.
Thirdly, vaccine equity is crucial for humanity to recover from extreme pandemics; no one is safe until everybody is safe. Speeding up clinical trials is also important, but I would think that pharmaceutical companies already have a strong incentive to speed this up as much as possible. As such, more advocacy and government funding is not as crucial.
Other preventive measures like DNA synthesis screening and governing do use research of concern are also important. However, I think that are less likely to receive public support as there haven't been any cases of successful bioterror attacks using pandemic-capable viruses. Nevertheless, governing access to benchtop synthesis machines (and hardwiring screening measures into their design) is still important to deny potentially malicious actors the capability to develop pandemic-capable viruses as bioweapons. The proliferation of such capabilities -- like the proliferation of fissile material -- would be quite irreversible.
(Not quite sure how to evaluate clean-air interventions like far-UVC or air filtration. My view would probably depend most on whether they are effective enough to prevent even the worst pandemics, second would be whether they would be cost effective enough to be deployed widely)
I'm currently trying to develop an estimation of the effectiveness of pursuing a career in mitigating Global Catastrophic Biological Risks (GCBRs). As part of the EA Global in-depth reading group, I read "Existential Risk and Cost-Effective Biosecurity" by Piers Millett and Andrew Snyder-Beattie (2017). The authors' estimates of the probability of GCBRs over the next century seemed very low (from 1.6 x 10^-6 to 0.02 over the next century, depending on which of the three methodologies used by the authors gives a better estimate)[1].
I could not seem to find any other sources that try to rigorously estimate the risks of GCBRs. Would forum users would be able to point me to some, please? [2] Thanks all in advance!
[1] Even with the highest estimate of 0.02 of GCB events per century, longtermist assumptions (of 10^16 potential lives lost, as indicated by the author) are needed for GCBR-mitigation to be more cost-effective than Givewell's top charities (taken as $4500/life saved). I would prefer not to make longtermist assumptions, in line with Neel Nanda's (2021) call to "Simplify EA
Pitches to 'Holy Shit, X-Risk'".
[2] With this input, I hope to write a more extensive post clarifying the priority areas in mitigating GCBRs (possibly pointing to risks of GCBRs from emerging biotech that enable bioterrorism as a priority area; in contrast with a focus on state-led biowarfare). If we are focusing on emerging biotech rather than existing biotech, estimates of whether these technologies would even materialise would be an important consideration as well.
Hey, this is a great question with good context for potential answers too. If you don’t get any substantive responses here, I’d suggest posting as a question on the frontpage — the shortforms really don’t get much visibility.