A Timely Agent Based Model

I’m going to play economic imperialist and declare that epidemiology is partly within the domain of economics. I’m not sure how big the overlap is, but certainly there are economic questions that bear epidemiological type modeling. The movement of ideas is, in the long run, as important as the movement of a virus is in the short run. In any event, economists should be using this sort of methodology more often.

Crisis, governments and the micro-macro conundrum

Layoffs and salary cuts are individual firm responses to a crisis that may make sense from a micro perspective- it is about saving money – but they will have dire consequences on the macro level.

I lived through this in Greece. Ten years ago, every firm was expecting the worst to come from the memorandum. They started making people redundant, pulling out from planned investment and cutting salaries. Unemployment went up, demand collapsed, public revenue went down, more austerity measures were needed and the downward spiral deepened. The country ended up losing one third of its economy in just four years.

Will it now be Greece on steroids everywhere?

The side effects of myriads of micro adaptations appear on the macro level. This is a key problem for economics and is particularly challenging for Austrian economics. Entrepreneurs creatively respond to a crisis by adopting a cautious and defensive approach long before some of them could spot new opportunities for investment and take positive action to exploit them. But if they all choose to first play ‘defense’, they shape the macro-environment in patterns that keeps telling most of them “keep on protecting yourself”, “there are more risks than opportunities out there”. Both supply and demand are on a continuous downward spiral. While some discerning entrepreneurs will spot some opportunities even in the direst of the circumstances, their plans need time to materialise and some may never come to fruition. In the meantime, most economic actors are not well positioned to start what they know to do well, and many have already lost their money in activities that went downhill.

On the other hand, the side effects of a large top down intervention such as the global lock down confirms the Austrian critique that central planning is also a risky endeavour. In an effort to control a complex reality, radical top-down interventions can divert investment to the specific activities they prop up, which appear sustainable for as long as this diversion lasts. Restrictive measures can also backfire, such as Greece’s shock austerity that was intended to balance the budget in Greece, or can prolong a precarious environment, such as the debt-fuelled bailouts elsewhere to save the banking system.

The problem is that policymakers do not have the tools to gain a full grasp of any potential unintended or undesired consequences from their actions. When they focus on one range of analysis, such as preventing a spike of deaths during the epidemic, the measures they take can generate a cascade of negative side effects in areas off their alarmed radar which they may have no idea how to arrest or fix.

I don’t see this micro-macro antithesis as an automatic validation of post Keynesianism in the sense that capitalism is always inherently unstable. It is unstable in periods of crisis when the micro and the macro can become a contradiction.

Exogenous shocks periodically happen. But it is worth studying what post Keynesians state: a crisis can emerge endogenously as in the financial markets.

The way out may be to think in terms of resilience rather than stability. I am inspired by Hilton Root’s forthcoming book Network Origins of the Global Economy. Resilience is the capacity of a system to accommodate turbulences and absorb shocks in recurrent episodes of instability. The system is unstable but can withstand the stresses.

Are multiple adjustments by adaptive agents able to bring about resilience in a system? Or do we need a central node to gain control and bring about order? Is a centrally-induced order a structure of relations that can be resilient over time, given that it depends on the health of the central node and knowing that the capacity of governments to understand and predict is limited?

Life

Screenshot 2020-03-26 at 12.15.15

No matter how old, frail or vulnerable it may be, a life isn’t something to take or risk at another’s discretion. Nor does it undermine culpability when someone dies as a result of negligence. The common law ‘eggshell skull’ rule reflects this moral principle.

During the Coronavirus pandemic, some erstwhile defenders of the famous Non-Aggression Principle (NAP) appear to have forgotten that natural rights are conceived to protect life as well as liberty and property. They seem to think that the liberties we ordinarily enjoy have priority over the right to life of others. The environment has changed and, for the time being, many activities that we previously knew to be safe for others are not. They are not part of our set of liberties until a reformed set of rules, norms and habits establishes a sufficiently hygienic public environment. To say that bans on public gatherings violate natural rights a priori is as untenable as G.A. Cohen’s claim that a prohibition on walking onto a train without a valid ticket is a violation of one’s freedom.

The clue for anarcho-capitalist state-sceptics that this is a genuine shift in social priorities is that even organized criminal gangs are willing to enforce social distancing. You do not have to believe that the state itself is legitimate to see that the need for social distancing is sufficiently morally compelling that it can be enforced absent free agreement, just as one does not need free agreement to exercise a right to self-defense.

Not every restriction is going to be justified, although erring on the restrictive side makes sense while uncertainty about the spread of infection persists. Ultimately, restrictions have to balance genuine costs with plausible benefits. But rejecting restrictions on a priori grounds does not cohere with libertarian principles. Right now, our absolute liberties extend to the right to be alone. Everything else must be negotiated under uncertainty. Someone else’s life, even two-weeks or so in the future, is a valid side-constraint on liberty. People can rightfully be made to stay at home if they are fortunate enough to have one. When people have to travel out of necessity, they can be temporarily exempted, compensated or offered an alternative reasonable means of satisfying their immediate needs.

The Vexing Libertarian Issue of Transition

I have appointed myself an old sage to the world. When your knees are creaky and every snotty eighteen-year-old treats you patronizingly, the least you can do to compensate is award yourself wisdom. Anyway, long story short, it’s a good excuse to spend much time on Facebook. I feel I am rendering a public service. I am continuing my teaching career there. It’s unpaid but the conditions are much better and all the students actually want to be in class.

Of course, it’s also true that Facebook is addictive. It’s not a bad addiction. For this old guy, it’s almost incredible to have frequent conversations with an MD in Pakistan, my niece in India, an old girlfriend in Panama, a young friend’s wife in Japan, and of course, many different kinds of French people. I even have a Facebook friend who lives in the mountains of Algeria; we have lively talks in French. Recently, a young woman who described herself as a Myanmar village girl reached out. (I know what you are thinking but if she is really one of those internet sex trolls, I salute the originality of her marketing strategy.) At all times a day and night, I have at least one Facebook friend who is not asleep. It’s pleasant in these days of confinement.

The same confinement, perhaps, slows me down and makes me more likely to tally up everything. As a result, a new impression has pierced my consciousness. Expressing contempt for democracy seems to be in vogue among people who identify as libertarians (with a small “l,” big “L” Libertarians have nearly vanished from my world. It could just be me.) This contempt reminds me that I have been asking the same question of libertarianism for now about fifty years, all with not much success.

I refer to the question of transition. I mean, what is it supposed to look like moving from wherever we are, in terms of governance, to a society with a drastically diminished government interference in individual lives? I have been receiving evasive answers, answers that don’t make even superficial sense, and swift escapes effected by changing the subject.

Let me say right away that I am not looking for a crushing reading assignment (a common punitive, passive-aggressive maneuver among intellectuals). Mine is a simple question. One should be able to sketch a rudimentary answer to it. Then, it would be up to me to follow through. Then, no excuse!

To my mind, there are only two extreme transition scenarios. One is the Somali scenario. The state falls apart under its own incapacity to limit internal aggression. It disappears or nearly so. When the point is reached where government authority extends only three blocks from the presidential palace to the north and east, and one block from the south and east, you pretty much have a stateless society. Goal reached!

The second scenario is a gradual change from the current “democratic” arrangements. I mean by this fair and reasonably honest elections followed by a peaceful transfer of power. I mean freedom of expression. And, disturbingly, this also includes courts of law. This is disturbing because courts without enforcement of their decisions are not really courts. This fact implies the threat of coercion, of course.

Now, I can imagine a situation like right now with the Corona Virus epidemic when governments (plural) demonstrate on a large scale their inability to do the obvious. The citizens often react to this sort of demonstration by asking for better and more government. However, it does not have to be that way. The combination of wide communication through the internet and – like now – of enforced leisure – may switch the dial. It’s conceivable that large numbers will get the idea that government that is at once heavy-handed, expensive, and incapable is not a good answer to much of anything. With that scenario one can imagine a collective demand for less government.

Strangely, this sort of scenario may be on display in France now, as I write. Well, this is not so strange after all. A deeply statist society where govt absorbs 55% of GDP and up may be exactly the best place to figure out that more government is not the answer. From this thought to the idea that less government may be the answer there is but one step. My intuition though is that it’s a big step. That’s because few people understand markets. No one but a handful of college professors seems to have read the moral philosopher Adam Smith. (Tell me that I am wrong.)

So, I would like for those who are more advanced than I am on this issue of transition (a low bar) to engage me. I am not interested in the same old ethical demonstrations though. Yes, the state is an instrument of coercion and therefore, evil. I already know this. In the meantime, the First Amendment to the Constitution of the United States does a fair job of protecting my freedom of speech, my freedom, of thought, my freedom of religion. I am not eager to leave this behind for the complete unknown. Are you? Why? How?

A History of Plagues

As COVID-19 continues to spread, fears and extraordinary predictions have also gone viral. While facing a new infectious threat, the unknowns of how new traits of our societies worldwide or of this novel coronavirus impact its spread. Though no two pandemics are equivalent, I thought it best to face this new threat armed with knowledge from past infectious episodes. The best inoculation against a plague of panic is to use evidence gained through billions of deaths, thousands of years, and a few vital breakthroughs to prepare our knowledge of today’s biological crises, social prognosis, and choices.

Below, I address three key questions: First, what precedents do we have for infections with catastrophic potential across societies? Second, what are the greatest killers and how do pandemics compare? Lastly, what are our greatest accomplishments in fighting infectious diseases?

As foundation for understanding how threats like COVID-19 come about and how their hosts fight back, I recommend reading The Red Queen concerning the evolutionary impact and mechanisms of host-disease competition and listening to Sam Harris’ “The Plague Years” podcast with Matt McCarthy from August 2019, which predated COVID-19 but had a strangely prophetic discussion of in-hospital strategies to mitigate drug resistance and their direct relation to evolutionary competition.

  • The Biggest Killers:

Infectious diseases plagued humanity throughout prehistory and history, with a dramatic decrease in the number of infectious disease deaths coming in the past 200 years. In 1900, the leading killers of people were (1) Influenza, (2) Tuberculosis, and (3) Intestinal diseases, whereas now we die from (1) Heart disease, (2) Cancer, and (3) Stroke, all chronic conditions. This graph shows not that humans have vanquished infectious disease as a threat, but that in the never-ending war of evolutionary one-upmanship, we have won battles consistently since 1920 forward. When paired with Jonathan Haidt’s Most Important Graph in the World, this vindicates humanity’s methods of scientific and economic progress toward human flourishing.Death rates

However, if the CDC had earlier data, it would show a huge range of diseases that dwarf wars and famines and dictators as causes of death in the premodern world. If we look to the history of plagues, we are really looking at the history of humanity’s greatest killers.

The sources on the history of pandemics are astonishingly sparse/non-comprehensive. I created the following graphs only by combining evidence and estimates from the WHO, CDC, Wikipedia, Our World in Data, VisualCapitalist, and others (lowest estimates shown where ranges were presented) for both major historic pandemics and for ongoing communicable disease threats. This is not a complete dataset, and I will continue to add to it, but it shows representative death counts from across major infectious disease episodes, as well as the death rate per year based on world population estimates. See the end of this post for the full underlying data. First, the top 12 “plagues” in history:

Capture disease top 12

 

Note: blue=min, orange=max across the sources I examined. For ongoing diseases with year-by-year WHO evidence, like tuberculosis, measles, and cholera, I grouped mortality in 5-year spans (except AIDS, which does not have good estimates from the 1980s-90s, so I reported based on total estimated deaths).

Now, let’s look at the plagues that were lowest on my list (number 55-66). Again, my list was not comprehensive, but this should provide context for COVID-19:

Capture covid

As we can see, the 11,400 people who have died from COVID-19 recently passed Ebola to take the 61st (out of 66) place on our list of plagues. Note again that several ongoing diseases were recorded in 5-year increments, and COVID-19 still comes in under the death rates for cholera. Even more notably, it has 0.015% as many victims as the plague in the 14th Century,

  • In Context of Current Infectious Diseases:

For recent/ongoing diseases, it is easier to compare year-by-year data. Adding UNAIDS to our sources, we found the following rates of death across some of the leading infectious causes of death. Again, this is not comprehensive, but helps put COVID-19 (the small red dot, so far in the first 3 months of 2020) in context:

Capture diseases by year

Note: darker segments of lines are my own estimates; full data at bottom of the post. I did not include influenza due to the lack of good sources on a year-by-year basis, but a Lancet article found that 291,000-645,000 deaths from influenza in a year is predictable based on data from 1999-2015.

None of this is to say that COVID-19 is not a major threat to human health globally–it is, and precautions could save lives. However, it should show us that there are major threats to human health globally all the time, that we must continue to fight. These trendlines tend to be going the right direction, but our war for survival has many foes, and will have more emerge in the future, and we should expend our resources in fighting them rationally based on the benefits to human health, not panic or headlines.

  • The Eradication List:

As we think about the way to address COVID-19, we should keep in mind that this fight against infectious disease builds upon work so amazing that most internet junkies approach new infectious diseases with fear of the unknown, rather than tired acceptance that most humans succumb to them. That is a recent innovation in the human experience, and the strategies used to fight other diseases can inform our work now to reduce human suffering.

While influenzas may be impossible to eradicate (in part due to an evolved strategy of constantly changing antigens), I wanted to direct everyone to an ever-growing monument to human achievement, the Eradication List. While humans have eradicated only a few infectious diseases, the amazing thing is that we can discuss which diseases may in fact disappear as threats through the work of scientists.

On that happy note, I leave you here. More History of Plagues to come, in Volume 2: Vectors, Vaccines, and Virulence!

Disease Start Year End Year Death Toll (low) Death Toll (high) Deaths per 100,000 people per year (global)
Antonine Plague 165 180 5,000,000 5,000,000 164.5
Plague of Justinian 541 542 25,000,000 100,000,000 6,250.0
Japanese Smallpox Epidemic 735 737 1,000,000 1,000,000 158.7
Bubonic Plague 1347 1351 75,000,000 200,000,000 4,166.7
Smallpox (Central and South America) 1520 1591 56,000,000 56,000,000 172.8
Cocoliztli (Mexico) 1545 1545 12,000,000 15,000,000 2,666.7
Cocoliztli resurgence (Mexico) 1576 1576 2,000,000 2,000,000 444.4
17th Century Plagues 1600 1699 3,000,000 3,000,000 6.0
18th Century Plagues 1700 1799 600,000 600,000 1.0
New World Measles 1700 1799 2,000,000 2,000,000 3.3
Smallpox (North America) 1763 1782 400,000 500,000 2.6
Cholera Pandemic (India, 1817-60) 1817 1860 15,000,000 15,000,000 34.1
Cholera Pandemic (International, 1824-37) 1824 1837 305,000 305,000 2.2
Great Plains Smallpox 1837 1837 17,200 17,200 1.7
Cholera Pandemic (International, 1846-60) 1846 1860 1,488,000 1,488,000 8.3
Hawaiian Plagues 1848 1849 40,000 40,000 1.7
Yellow Fever 1850 1899 100,000 150,000 0.2
The Third Plague (Bubonic) 1855 1855 12,000,000 12,000,000 1,000.0
Cholera Pandemic (International, 1863-75) 1863 1875 170,000 170,000 1.1
Indian Smallpox 1868 1907 4,700,000 4,700,000 9.8
Franco-Prussian Smallpox 1870 1875 500,000 500,000 6.9
Cholera Pandemic (International, 1881-96) 1881 1896 846,000 846,000 4.4
Russian Flu 1889 1890 1,000,000 1,000,000 41.7
Cholera Pandemic (India and Russia) 1899 1923 1,300,000 1,300,000 3.3
Cholera Pandemic (Philippenes) 1902 1904 200,000 200,000 4.2
Spanish Flu 1918 1919 40,000,000 100,000,000 1,250.0
Cholera (International, 1950-54) 1950 1954 316,201 316,201 2.4
Cholera (International, 1955-59) 1955 1959 186,055 186,055 1.3
Asian Flu 1957 1958 1,100,000 1,100,000 19.1
Cholera (International, 1960-64) 1960 1964 110,449 110,449 0.7
Cholera (International, 1965-69) 1965 1969 22,244 22,244 0.1
Hong Kong Flu 1968 1970 1,000,000 1,000,000 9.4
Cholera (International, 1970-75) 1970 1974 62,053 62,053 0.3
Cholera (International, 1975-79) 1975 1979 20,038 20,038 0.1
Cholera (International, 1980-84) 1980 1984 12,714 12,714 0.1
AIDS 1981 2020 25,000,000 35,000,000 13.8
Measles (International, 1985) 1985 1989 4,800,000 4,800,000 19.7
Cholera (International, 1985-89) 1985 1989 15,655 15,655 0.1
Measles (International, 1990-94) 1990 1994 2,900,000 2,900,000 10.9
Cholera (International, 1990-94) 1990 1994 47,829 47,829 0.2
Malaria (International, 1990-94) 1990 1994 3,549,921 3,549,921 13.3
Measles (International, 1995-99) 1995 1999 2,400,000 2,400,000 8.4
Cholera (International, 1995-99) 1995 1999 37,887 37,887 0.1
Malaria (International, 1995-99) 1995 1999 3,987,145 3,987,145 13.9
Measles (International, 2000-04) 2000 2004 2,300,000 2,300,000 7.5
Malaria (International, 2000-04) 2000 2004 4,516,664 4,516,664 14.7
Tuberculosis (International, 2000-04) 2000 2004 7,890,000 8,890,000 25.7
Cholera (International, 2000-04) 2000 2004 16,969 16,969 0.1
SARS 2002 2003 770 770 0.0
Measles (International, 2005-09) 2005 2009 1,300,000 1,300,000 4.0
Malaria (International, 2005-09) 2005 2009 4,438,106 4,438,106 13.6
Tuberculosis (International, 2005-09) 2005 2009 7,210,000 8,010,000 22.0
Cholera (International, 2005-09) 2005 2009 22,694 22,694 0.1
Swine Flu 2009 2010 200,000 500,000 1.5
Measles (International, 2010-14) 2010 2014 700,000 700,000 2.0
Malaria (International, 2010-14) 2010 2014 3,674,781 3,674,781 10.6
Tuberculosis (International, 2010-14) 2010 2014 6,480,000 7,250,000 18.6
Cholera (International, 2010-14) 2010 2014 22,691 22,691 0.1
MERS 2012 2020 850 850 0.0
Ebola 2014 2016 11,300 11,300 0.1
Malaria (International, 2015-17) 2015 2017 1,907,872 1,907,872 8.6
Tuberculosis (International, 2015-18) 2015 2018 4,800,000 5,440,000 16.3
Cholera (International, 2015-16) 2015 2016 3,724 3,724 0.0
Measles (International, 2019) 2019 2019 140,000 140,000 1.8
COVID-19 2019 2020 11,400 11,400 0.1

 

Year Malaria Cholera Measles Tuberculosis Meningitis HIV/AIDS COVID-19
1990 672,518 2,487 670,000 1,903 310,000
1991 692,990 19,302 550,000 1,777 360,000
1992 711,535 8,214 700,000 2,482 440,000
1993 729,735 6,761 540,000 1,986 540,000
1994 743,143 10,750 540,000 3,335 620,000
1995 761,617 5,045 400,000 4,787 720,000
1996 777,012 6,418 510,000 3,325 870,000
1997 797,091 6,371 420,000 5,254 1,060,000
1998 816,733 10,832 560,000 4,929 1,210,000
1999 834,692 9,221 550,000 2,705 1,390,000
2000 851,785 5,269 555,000 1,700,000 4,298 1,540,000
2001 885,057 2,897 550,000 1,680,000 6,398 1,680,000
2002 911,230 4,564 415,000 1,710,000 6,122 1,820,000
2003 934,048 1,894 490,000 1,670,000 7,441 1,965,000
2004 934,544 2,345 370,000 1,610,000 6,428 2,003,000
2005 927,109 2,272 375,000 1,590,000 6,671 2,000,000
2006 909,899 6,300 240,000 1,550,000 4,720 1,880,000
2007 895,528 4,033 170,000 1,520,000 7,028 1,740,000
2008 874,087 5,143 180,000 1,480,000 4,363 1,630,000
2009 831,483 4,946 190,000 1,450,000 3,187 1,530,000
2010 788,442 7,543 170,000 1,420,000 2,198 1,460,000
2011 755,544 7,781 200,000 1,400,000 3,726 1,400,000
2012 725,676 3,034 150,000 1,370,000 3,926 1,340,000
2013 710,114 2,102 160,000 1,350,000 3,453 1,290,000
2014 695,005 2,231 120,000 1,340,000 2,992 1,240,000
2015 662,164 1,304 150,000 1,310,000 1,190,000
2016 625,883 2,420 90,000 1,290,000 1,170,000
2017 619,825 100,000 1,270,000 1,150,000
2018 1,240,000
2019
2020 16,514

Pandemic responses are beyond Evidence-based Medicine

critical-appraisal-of-randomized-clinical-trials-14-638

John Ioannidis, a professor of medicine at Stanford University, fears that the draconian measures to enforce social distancing across Europe and United States could end up causing more harm than the pandemic itself. He believes that governments are acting on exaggerated claims and incomplete data and that a priority must be getting a more representative sample of populations currently suffering corona infections. I agree additional data would be enormously valuable but, following Saloni Dattani, I think we have more warrant for strong measures than Ioannidis implies.

Like Ioannidis’ Stanford colleague Richard Epstein, I agree that estimates of a relatively small overall fatality rate are plausible projections for most of the developed world and especially the United States. Unlike Epstein, I think those estimates are conditional on the radical social distancing (and self-isolation) measures that are currently being pushed rather than something that can be assumed. I am not in a position to challenge Ioannidis’ understanding of epidemiology. Others have used his piece as an opportunity to test and defend the assumptions of the worst-case scenarios.

Nevertheless, I can highlight the epistemic assumptions underlying Ioannidis’ pessimism about social distancing interventions. Ioannidis is a famous proponent (occasionally critic) of Evidence-based Medicine (EBM). Although open to refinement, at its core EBM argues that strict experimental methods (especially randomized controlled trials) and systematic reviews of published experimental studies with sound protocols are required to provide firm evidence for the success of a medical intervention.

The EBM movement was born out of a deep concern of its founder, Archie Cochrane, that clinicians wasted scarce resources on treatments that were often actively harmful for patients. Cochrane was particularly concerned that doctors could be dazzled or manipulated into using a treatment based on some theorized mechanism that had not been subject to rigorous testing. Only randomized controlled trials supposedly prove that an intervention works because only they minimize the possibility of a biased result (where characteristics of a patient or treatment path other than the intervention itself have influenced the result).

Picture4

So when Ioannidis looks for evidence that social distancing interventions work, he reaches for a Cochrane Review that emphasizes experimental studies over other research designs. As is often the case for a Cochrane review, many of the results point to uncertainty or relatively small effects from the existing literature. But is this because social distancing doesn’t work, or because RCTs are bad at measuring their effectiveness under pandemic circumstances (the circumstances where they might actually count)? The classic rejoinder to EBM proponents is that we know that parachutes can save lives but we can never subject them to RCT. Effective pandemic interventions could suffer similar problems.

Nancy Cartwright and I have argued that there are flaws in the methodology underlying EBM. A positive result for treatment against control in a randomized controlled trial shows you that an intervention worked in one place, at one time for one set of patients but not why and whether to expect it to work again in a different context. EBM proponents try to solve this problem by synthesizing the results of RCTs from many different contexts, often to derive some average effect size that makes a treatment expected to work overall or typically. The problem is that, without background knowledge of what determined the effect of an intervention, there is little warrant to be confident that this average effect will apply in new circumstances. Without understanding the mechanism of action, or what we call a theory of change, such inferences rely purely on induction.

The opposite problem is also present. An intervention that works for some specific people or in some specific circumstances might look unpromising when it is tested in a variety of cases where it does not work. It might not work ‘on average’. But that does not mean it is ineffective when the mechanism is fit to solve a particular problem such as a pandemic situation. Insistence on a narrow notion of evidence will mean missing these interventions in favor of ones that work marginally in a broad range of cases where the answer is not as important or relevant.

Thus even high-quality experimental evidence needs to be combined with strong background scientific and social scientific knowledge established using a variety of research approaches. Sometimes an RCT is useful to clinch the case for a particular intervention. But sometimes, other sources of information (especially when time is of the essence), can make the case more strongly than a putative RCT can.

In the case of pandemics, there are several reasons to hold back from making RCTs (and study designs that try to imitate them) decisive or required for testing social policy:

  1. There is no clear boundary between treatment and control groups since, by definition, an infectious disease can spread between and influence groups unless they are artificially segregated (rendering the experiment less useful for making broader inferences).
  2. The outcome of interest is not for an individual patient but the communal spread of a disease that is fatal to some. The worst-case outcome is not one death, but potentially very many deaths caused by the chain of infection. A marginal intervention at the individual level might be dramatically effective in terms of community outcomes.
  3. At least some people will behave differently, and be more willing to alter their conduct, during a widely publicized pandemic compared to hygienic interventions during ordinary times. Although this principle might be testable in different circumstances, the actual intervention won’t be known until it is tried in the reality of pandemic.

This means that rather than narrowly focusing on evidence from EBM and behavioral psychologists (or ‘nudge’), policymakers responding to pandemics must look to insights from political economy and social psychology, especially how to shift norms towards greater hygiene and social distancing. Without any bright ideas, traditional public health methods of clear guidance and occasionally enforced sanctions are having some effect.

Screenshot 2020-03-23 at 23.57.13

What evidence do we have at the moment? Right now, there is an increasing body of defeasible knowledge of the mechanisms with which the Coronavirus spreads. Our knowledge of existing viruses with comparable characteristics indicates that effectively implemented social distancing is expected to slow its spread and that things like face masks might slow the spread when physical distancing isn’t possible.

We also have some country and city-level policy studies. We saw an exponential growth of cases in China before extreme measures brought the virus under control. We saw immediate quarantine and contact tracing of cases in Singapore and South Korea that was effective without further draconian measures but required excellent public health infrastructure.

We have now also seen what looks like exponential growth in Italy, followed by a lockdown that appears to have slowed the growth of cases though not yet deaths. Some commentators do not believe that Italy is a relevant case for forecasting other countries. Was exponential growth a normal feature of the virus, or something specific to Italy and its aging population that might not be repeated in other parts of Europe? This seems like an odd claim at this stage given China’s similar experience. The nature of case studies is that we do not know with certainty what all the factors are while they are in progress. We are about to learn more as some countries have chosen a more relaxed policy.

Is there an ‘evidence-based’ approach to fighting the Coronavirus? As it is so new: no. This means policymakers must rely on epistemic practices that are more defeasible than the scientific evidence that we are used to hearing. But that does not mean a default to light-touch intervention is prudent during a pandemic response. Instead, the approaches that use models with reasonable assumptions based on evidence from unfolding case-studies are the best we can do. Right now, I think, given my moral commitments, this suggests policymakers should err on the side of caution, physical distancing, and isolation while medical treatments are tested.

[slightly edited to distinguish my personal position from my epistemic standpoint]

Coronavirus and the BRI

The Corona Virus epidemic has shaken the world in numerous ways. The virus, which first emerged in the Chinese city of Wuhan (Hubei province), has led to the loss of over 12,000 lives globally. The three countries most impacted so far have been Italy (4,825 lives lost), China (3,287 lives lost), and Iran (1,500 lives lost) as of Saturday, March 21, 2020.

While there are reports that China is limping back to normalcy, the overall outlook for the economy is grim, to say the least, with some forecasts clearly predicting that even with aggressive stimulus measures China may not be able to attain 3% growth this year.

The Chinese slow down could have an impact on the country’s ambitious Belt and Road Initiative (BRI). While China has been trying to send out a message that BRI will not be impacted excessively, the ground realities could be different given a number of factors.

One of the important, and more controversial, components of the BRI has been the $62 billion China Pakistan Economic Corridor (CPEC), which has often been cited as a clear indicator of ‘Debt Trap Diplomacy’ (this, some analysts argue, is China’s way of increasing other country’s dependency on it, by providing loans for big ticket infrastructural projects, which ultimately lead to a rise in debts).

The US and multilateral organizations like the International Monetary Fund (IMF) have predictably questioned the project, but even in Pakistan many have questioned CPEC, including politicians, with most concerns revolving around its transparency and long-term economic implications. Yet the Imran Khan-led Pakistan Tehreek-E-Insaaf (PTI) government, and the previous Pakistan Muslim League (Nawaz) (PML-N) government, have given the project immense importance, arguing that it would be a game changer for the South Asian nation.

On more than one occasion, Beijing has assured Pakistan that CPEC will go ahead as planned with China’s Ambassador to Pakistan, Yao Jing, stating on numerous occasions that the project will not be hit in spite of the Corona Virus. Senior officials in the Imran Khan government, including the Railway Minister Sheikh Rashid Ahmed and Foreign Minister Shah Mehmood Qureshi, in an interview with the Global Times, stated that while in the short run Corona may have an impact on CPEC, in the long run there would be no significant impact.

Analysts in Pakistan however, doubt that there will be no impact, given the fact that a large number of Chinese workers who had left Pakistan are unlikely to return. Since February 2020, a number of reports have been predicting that the CPEC project is likely to be impacted significantly.

Similarly, in the cases of other countries too, there are likely to be significant problems with regard to the resource crunch in China as well as the fact that Chinese workers cannot travel. Not only is Beijing not in a position to send workers, but countries hit by COVID-19 themselves will not be in a position to get the project back on track immediately, as they will first have to deal with the consequences of the outbreak.

Some BRI projects which had begun to slow down even before the outbreak spread globally were in Indonesia and Bangladesh. In Indonesia, a high speed rail project connecting Jakarta with Bandung (estimated at $6 billion) has slowed down since the beginning of the year, and ever since the onset of the Corona Virus, skilled Chinese personnel have been prevented from going back to Indonesia. Bangladesh too has announced delays on the Payra Coal power plant in February 2020. As casualties arising out of the virus increase in Indonesia and other parts of Asia and Africa, the first priority for countries is to prevent the spread of the virus.

While it is true that Beijing would want to send a clear message of keeping its commitments, matching up to its earlier targets is not likely to be a mean task. Even before the outbreak, there were issues due to the terms and conditions of the project and a number of projects had to be renegotiated due to pressure from local populations.

What China has managed to do successfully is provide assistance for dealing with COVID-19. In response to a request for assistance from the Italian government, China has sent a group of 300 doctors and corona virus testing kits and ventilators. The founder of Ali Baba and one of Asia’s richest men, Jack Ma, has also taken the lead in providing assistance to countries in need. After announcing that he will send 500,000 coronavirus testing kits and 1 million masks to the United States, Ma pledged to donate more than 1 million kits to Africa on Monday March 17, 2020, and on March 21, 2020, in a tweet, the Chinese billionaire said that he would be donating emergency supplies to a number of South Asian and South East Asian countries — Afghanistan, Bangladesh, Cambodia, Laos, Maldives, Mongolia, Myanmar, Nepal, Pakistan, and Sri Lanka. The emergency supplies include 1.8 million masks, 210,000 test kits, 36,000 protective suits and ventilators, and thermometers.

China is bothered not just about it’s own economic gains from the BRI, but is also concerned about the long term interests of countries which have signed up for BRI.

The Corona Virus has shaken the whole world, not just China, and the immediate priority of most countries is to control the spread of the pandemic and minimize the number of casualties. Countries dependent upon China, especially those which have joined the BRI, are likely to be impacted. What remains to be seen is the degree to which BRI is affected, and how developing countries which have put high stakes on BRI related projects respond.