Tag: recovery

Global Hints about Community Resilience

Long is the road to learning by precepts, but short and successful by examples. ~ Seneca the Younger.

I am an unrepentant data geek. One facet of my geek-ness is that I am autodidactic (I actually had a Professor call me that – I had to look it up) – I seldom accept others’ conclusions; I have to see for myself (actually, the Professor said I had to learn from my own mistakes, which I sometimes do). About 10 years ago, I first stumbled over FM’s Resilience Index. Now in its 12th year, it is a composite of 18 different indicators.

I posted about it at the time; lots of graphs, but I didn’t really put them into a useful context. In this post, I want to take a look at hints that they may have for those of us trying to understand a community’s resilience, in particular factors that we should consider in the resilience indices so prevalent in the literature and in use in the US.

The variables. FM is an insurance company. So “resilience” has to do with physical phenomena – natural hazards and climate change, as examples. It bins the 18 variables included in the Index into two categories: Physical factors and Macro factors. The Physical factors, in effect risk factors, rely on FM’s experience in each country, except for the cybersecurity data. The Macro factors might be considered as those attributes related to recovery from a natural disaster, i.e., resilience factors. If you’re interested in the data sources and methodology, follow this link.

Whenever possible, the data are averaged over a five-year period. This is something that is generally not done for most (any?) of the US resilience indices. The advantage of this is that it smooths out some of the inevitable noise in the data while maintaining evidence of a significant trend.

All of the Macro factors that involve money are adjusted for Purchasing Power Parity (PPP). The intent is to remove cost-of-living differences from comparisons. For the most common resilience indicator systems in the US, this has not been done. Thus, California counties (or other units) are indicated as more resilient than they really are because important data such as median household incomes are not adjusted for the very high cost of living (CoL) in CA. Using poverty values not adjusted for CoL, the number of people living below the poverty line in CA is less than the US average. However, once the value is adjusted, California has the highest fraction of its population living in poverty of all the states. In this context, it’s not surprising that it’s taking so long to rebuild Pacific Palisades!

Physical factors

Climate risk exposure – the portion of the country’s economically productive area exposed to climatic risks today.

Climate change exposure – the portion of the country’s economically productive area exposed to climatic risks in 2050.

Climate risk quality – enforcement of building codes for wind (90% of the indicator), and mitigation of flood and wind impacts.

Seismic risk exposure – the portion of the country’s economically productive area exposed to seismic risks.

Cybersecurity – commitment as shown in action (80%), and risk reduction relative to risk.

Fire risk quality – enforcement of fire codes (80%), and risk reduction relative to risk.

I haven’t seen the proportion of economically productive area to determine exposure to hazards used before. In the US, we either don’t include exposure data in our resilience indices, or else use something like the HAZUS code to calculate hazard losses (as is done for FEMA’s Community Resilience / National Risk Index). We certainly don’t include projections of risks in the year 2050. We also don’t include fire risks to the built environment as is done here, nor effectively give credit for mitigating actions.

Macro factors:

Control of corruption – perceived amount of corruption (public resources used for private gain) as well as “capture of state by elites and private interests.”

Education – average of expected years of schooling and the mean of actual schooling.

Energy intensity – energy consumption divided by the adjusted gross domestic product.

Greenhouse gas emissions – emissions divided by the adjusted gross domestic product.

Health expenditure – mean expenditure on health per person, both public and private, adjusted for PPP.

Inflation – annual rate of inflation.

Internet usage – fraction of the population using the internet.

Logistics – how easy it is to export to a target country in terms of the quality of infrastructure, the quality and availability of logistics activities, and public sector bottlenecks; based on survey data.

Political risk – perceived likelihood that the national government will be either destabilized or overthrown, either unlawfully or by violence.

Productivity – GDP (adjusted for PPP) per capita.

Urbanization rate – on an annual basis.

Water stress – freshwater withdrawn as a fraction of available resources.

Each factor was statistically massaged so that they were on a common scale (0-100). The resilience index for each country is then the mean of the 18 values. In contrast, in FEMA ‘s resilience index, the exposure (calculated via HAZUS) is divided into the Macro factors.

I took this data and mapped each factor against the resilience index and against each other. I won’t clutter this too-long post up any further with a bunch of graphs. The results are summarized in the following table where I’ve looked at correlations among the variables. R2 is a measure of how well two variables are linearly correlated. I’ve arbitrarily chosen an R2 value of 0.5 as the threshold indicating a strong relationship. All of the strong relationships are listed in the table below. If anyone wants the complete set of correlation just let me know.

Strong relationships R2 ≥ 0.5
Resilience indexControl of corruption0.76
 Climate mitigation0.74
 Productivity0.70
 Education0.70
 Logistics0.66
 Fire mitigation0.65
 Health expenditure0.57
 Internet usage0.57
Productivity (GDP per capita)Control of corruption0.65
 Logistics0.60
 Climate risk mitigation0.57
 Health expenditure0.53
 Education0.52
 Fire risk mitigation0.51
 Internet usage0.50
Health expendituresClimate mitigation0.56
EducationInternet usage0.68
 Climate mitigation0.57
 Fire mitigation0.52
 Urbanization rate0.51
 Control of corruption0.51
Political riskControl of corruption0.55
Control of corruptionLogistics0.66
 Climate mitigation0.54
Urbanization rateInternet usage0.52
LogisticsFire mitigation0.63
 Climate mitigation0.57
Climate mitigationFire mitigation0.73
Climate risk exposureClimate change exposure0.50

The strongest correlation was between the resilience index and control of corruption. This factor is not considered in any of the commonly used resilience indices. In effect, we are ignoring the community’s governance/institutional capital as a factor in its resilience. The impact of official corruption on recovery from disaster is obvious. The news from Gaza bombards us daily with a reminder of how much corruption hinders recovery. And apparently misuse of $100 M in recovery funding is another factor hampering the Pacific Palisades recovery. The only index that considers this factor is Arup’s resilience index for the 100 Cities initiative. Based on its strong relationship to a country’s resilience, this factor deserves more attention. (As an aside, I compared FM’s “Control of corruption” data with the Corruption Perceptions Index from Transparency International. The two are determined rather differently; however, they are highly correlated R2 = 0.96, i.e., they apparently are reflecting the same thing!).

Logistics, internet usage and fire risk mitigation are all important factors strongly related to both resilience and productivity. None of them are currently included in common resilience indices. I have often said that resilience is a manifestation of a community’s strengths, not its vulnerabilities. Intuitively, the ability to move physical assets where they are needed is an important strength related to recovery. In a similar sense, internet usage facilitates movement of information across the community. More generally, this emphasizes the importance of dispatchable capital.

One surprise: exposure factors weren’t correlated with the corresponding “quality” factors, i.e., mitigation wasn’t related to exposure. While the two climate exposure factors were correlated, none of the exposure factors were correlated with any of the resilience factors. Similarly, greenhouse gas emissions were not correlated with any of the other variables.

This is the first time that FM has included cybersecurity. It doesn’t make any difference to the resilience index, and is not correlated with any of the other factors. It seems to be irrelevant to both resilience and natural hazards and fires.

There is a lot more that can be extracted from this data, but this post is long enough already. FM has provided a rather different window on resilience, pointing out the importance of variables not often considered when we look at our communities. I hope that those working to make their communities more resilient will include all of the community’s capital portfolio in their efforts – its logistics systems (physical capital), its information systems (social capital), and above all, how the community makes and implements decisions (governance/institutional capital).

Looking beyond the flames

One of the reasons people hate politics is that truth is rarely a politician’s objective. Election and power are. ~ Cal Thomas

The ongoing wildfires in California have shone a light on one of the too-seldom recognized flaws of Democracy. The only real form of accountability for poor performance by elected officials is to vote them out. But what if there isn’t a viable opposition? What if the Public is not well-informed?

There should be no question in anyone’s mind that poor governance and incompetence are the root causes of the human tragedies in LA. The first duty of any government is to assure its citizens’ quality of life. At the community level, that means law enforcement, fire protection and support of a viable economic life. It doesn’t mean towing away anyone’s vehicle without appropriate notice for possible violations unrelated to the car (as is being done in Chicago, New York and other big cities). It doesn’t mean ignoring the deaths and destruction caused by black-on-black crime. It doesn’t mean accepting petty crime (so corrosive to community). It doesn’t mean cutting millions from the fire department’s budget while funding less fundamental functions.

There is a sad litany of poor performance by the politicians that led to this. A few examples:

  • Having ~100 emergency vehicles out of commission because they need maintenance – but not having the mechanics to work on them.
  • The Mayor of LA going to Ghana on a boondoggle – in spite of extraordinary warnings from the National Weather Service that a fire disaster was looming – before the fire.
  • Empty reservoirs and not a single new dam – even though the state’s voters had approved a $7.5B ballot initiative for more water storage – in 2014!
  • There is evidence that arson was the cause of at least one fire – caused by a homeless person. In spite of spending billions, the number of homeless continues to rise.
  • Water not being pumped because there was too little pressure – but that’s OK because at least 300 water hydrants had been stolen and not replaced.
  • Not having a scheduled controlled burn – because it might make somebody look bad if it went wrong.
  • Sending supposedly “excess” equipment to Ukraine – and then not replacing it.

There are many, especially on the Right, who blame the “progressive” policies pursued by the Democratic leadership, both locally and at the state level. It is easy – now – to recognize the folly of effectively incentivizing petty crime, for example. But the failure of governance in California ultimately is really not a Red vs Blue issue. It is a corruption issue. Most simply, when one party has been in power for a long time (whether GOP or Dem) and has no real opposition, corruption is the result. As Lord Acton said, Power corrupts, absolute power corrupts absolutely. It is not that Democratic politicians can’t govern, it’s that they have been in power in California so long that governing is immaterial to many of them.

Their dysfunction is an extreme example of Pournelle’s Iron Law. Idealists start movements to right wrongs, to make life better in their communities. Over time the idealists get pushed aside; their places are taken by the bureaucrats and hacks. These may pay lip service to the founders’ visions and ideals but their real aim is to perpetuate their power and the perks that come with it.

In a sense, most of us are a little complicit in their sham. Too many of us accept the hacks’ lip service for intention; or vote for them because, well, we always have. We don’t go beyond the honeyed words to see the toxic acid corroding our communities. We are too caught up in our own day-to-day struggles to actually understand why things seem to be going so wrong. We believe the media’s half truths (“mostly peaceable demonstrations”) because to doubt is to risk being cancelled. Or maybe we take the coward’s way out, soothing ourselves with the “certainty” that we can’t make a difference anyway, can we? Whatever the reason, the corrupt incompetents remain in power, almost certain to be overwhelmed by the next crisis.

But it doesn’t have to be this way. Poor opponent or not, vote the jackals out; don’t reward incompetence! If what you see doesn’t match what you’re being told – by either the politicians or the media – then suspect you’re being lied to. Dig at it until you get at the truth – and then act on it. Most importantly, don’t vote based on loyalty, or to just go along – vote for who is going to do the best job. If they don’t live up to your expectations, vote them out. And if none of that works, then vote with your feet – leave.

It might seem that I’m playing the Blame Game, but actually I’m not. I’m looking forward to how we can best help the devastated rebuild their shattered lives. Those of us thankfully muttering to ourselves “There but for the Grace of God…” are faced with a moral dilemma: how can we best help our friends in California recover?

Do we trust the recovery to the incompetents who contributed to this horrendous human tragedy? Do we find another way to get the funds needed for rebuilding and recovery into the hands that need them? Do we deny the funds so badly needed (no one seriously believes we’ll actually do this) to those who need housing, jobs; because we fear that the incompetents will fritter those funds away? I offer no answers but the questions demand them.

Ecological vs engineering resilience

The goal of resilience is to thrive. – Jamais Cascio

Both Claire Rubin and James Brooke were kind enough to forward to me a short piece from The Conversation, by Prof A A Batabyal of RIT (nice that someone is looking out for me!). Although the short essay started by looking at “sustainability,” it was really focused on “resilience.” In particular, Batabyal contrasts “ecological” resilience against “engineering” resilience.

He uses a lake and a bridge as exemplars: the former for ecological resilience (as defined by Hollings) and the latter for engineering resilience (as defined by Pimm). The bridge has only one stable state; the lake has more than one stable states. As the Prof points out, Hollings’ definition boils down to how much stress an ecosystem can withstand before it restructures. Pimms’ definition of resilience relates to how fast a system can return to equilibrium.

The Prof then points out that most socioeconomic systems – such as communities – “exist” in multiple states. Thus, Hollings’ definition should be favored. I disagree, for several reasons.

First and foremost, Hollings’ definition and the panarchic framework it leads to is not very useful for a community trying to become more resilient. The definition requires us to observe a system under stress and then watch it change. The amount of stress needed to force the system to change is its “resilience.” If I’m a community professional, in essence this implies I have to let the community fail before I can gauge its resilience! Of course this is nonsense – but it does point to the difficulty of predicting a community’s resilience using this approach.

One of the biggest stumbling blocks is knowing whether a community has restructured. Take New Orleans after Katrina as an example. There were several differences in the Before and After:

  • The city’s population dropped by a third.
  • Several new civic organizations were put in place.
  • There were measureable changes in the performance of important community systems (e.g., student performance improved).
  • Much of the sleaze in the French Quarter disappeared.

Did these indicate a change in structure?

Then there’s the “resilience-to” problem.In practical terms, we know that a community generally doesn’t have a single “resilience.” Rather a community’s resilience depends on

  • The stressor. A community may be able to deal with a great deal of economic stress, but fold like a house of cards in the face of a pandemic.
  • The speed of stress. A community may be able to adapt to a high level of stress spread over time but unable to tolerate the same stress experienced as a rapid shock.
  • The amount and type of damage, and the resources available for recovery.

Pimm’s concept of “engineering resilience” has the advantage of seeming more like what people think of as resilience. As the result of a Wild Thing – some sort of extreme event – a community loses capacity or functionality. Over time, the community recovers from the Wild Thing and regains its capacity. The time required to regain its functionality is the community’s resilience. Bruneau et al’s concept of resilience is very consistent with this idea.

From a community’s standpoint, community systems are either functional or failed – they either do or don’t meet the community’s demand for their function. After the damage wrought by a Wild Thing, the community at large doesn’t really care whether the health care system, or the system providing electricity are structured the same as before. They only care whether they can obtain the same (or better) health care as before the Wild Thing. They only care whether they can get light when they flip the switch, or air conditioning when it’s hot outside. Community professionals are most concerned with determining how soon after a Wild Thing the health care system is functional; how soon the lights can come back on after power is lost.

The stress testing approach* that Jennifer Adams and I have developed provides community professionals with a way to gauge this type of resilience. To summarize, community professionals postulate a particular Wild Thing – type, intensity, timing. This leads to a prediction of the damage the Wild Thing will cause. This in turn leads to a prediction of which community systems will fail. The resilience of each system is then determined by the use of dispatchable capital over time. The resilience of the community is inferred to be the resilience (time to recovery) of the last system to recover.

Community professionals and communities themselves want to know how resilient they will be to Wild Things before they occur. Simply put, Hollings’ approach to resilience may be useful in explaing what happened to a community as a result of a Wild Thing after the fact. It’s not very useful to community professionals trying to determine their community’s “recoverability” before a Wild Thing strikes. There is a certain inevitability to the “ecological” resilience approach when applied to communities. If sufficiently stressed, they will fail and restructure. When and how and to what is unanswered. Measuring the “engineering” resilience of communities using stress testing methodology gives community professionals answers they can work with, and is more intuitive. The approach can indicate paths to reduce damage and community system failures. It can also point to which additional resources could speed the community’s recovery from a Wild Thing. Ultimately, it can make recovery surer and more rapid – and communities more resilient.

_______________

* M. J. Plodinec, “Stress Testing of Community Resilience to Extreme Events,” Journal of Homeland Security and Emergency Management, 18(2), 151-176 (2021).

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Beyond sustainability and resilience

Sustainability is here to stay, or we may not be.

Niall Ferguson

As a few of you know, Jennifer Adams and I are writing a book (working title: The Connected Community) on systems thinking for community practitioners. The premise of the book is that systems thinking provides community practitioners – emergency managers, economic developers, city planners – with a rich set of tools to strengthen their communities.

Recently I was asked how sustainability and resilience fit into this. My initial knee-jerk answer was “Ultimately I want people to use these tools to make their communities more resilient.” Then I thought a bit, and said, “Well, actually, maybe more sustainable too.” Not satisfied with that answer, I finally said, “Really, it’s both and neither. What I really hope happens as a result of the book is that communities become more future-fit.” In the next few posts, I’m going to take a deep dive into both sustainability and resilience, and compare and contrast them. I’ll close the series with what I mean by a “future-fit” community and why the distinction is so important.

Fear of the apocalypse seems to be driving much of what’s being done in the names of both sustainability and resilience, as the quote above exemplifies. Fear of a future climate catastrophe seems to be the basis for much of what is called sustainability today. The Transition Town movement and several similar resilience initiatives are based on a presumed death of globalization, and a tumbling down Peak Oil to a valley of unknown depth.  Those John-the-Baptists who are proclaiming the coming apocalypse – whichever it might be – go on to preach from the Book of Sustainability as the Path to Resilience in the face of what’s coming. Thus, much of what is called sustainability or resilience are founded on a profound sense of despair.  

I won’t assess any of the actions suggested by the Prophets of Doom – many I find useful, some I find silly, and some are likely counterproductive – but I do want to examine the relationship between resilience and sustainability.  Is a sustainable community resilient?  Is a resilient community sustainable?  Are resilience and sustainability at opposite ends of a continuum, or at right angles to each other?

Right away, we’re confronted by a huge difficulty – both “sustainability” and “resilience” have become fads; both words have become very imprecise concepts.  The dictionary definitions of sustainability are about maintaining a certain level, or, as Wikipedia says, the capacity to endure.  In essence, this means a type of persistence.  However, if we look at the UN’s Brundtland Commission definition, then sustainability is all about balancing use of resources for current needs vs the resources needed in the future.  In what follows, I’m going consider community sustainability as meaning a wise use of resources,

  • Discriminating between wants and needs so that needs are met first, and
  • Using resources efficiently – the least necessary to meet the maximal amount of needs.

Resilience has been tortured nearly as badly.  To some it’s a process, to some an attribute; to some, it means resisting change, to some reverting to normal after a crisis.  However, resilience has one advantage in that almost all of the faddish definitions have this kernel of bouncing back after an external stress is applied.  In what follows, I’m going to consider community resilience as a community’s ability to

  • Anticipate crises,
  • Take action to reduce their impacts,
  • Respond effectively to them, and
  • Recover rapidly.

If we compare these two, we can begin to see a contrast.  In thermodynamic terms, sustainability is about trying to maintain equilibrium while resilience is a kinetic property.  In philosophic terms, sustainability is ontological, resilience is phenomenological.  Or in my terms, resilience is about time and sustainability is timeless. Resilience is aimed at minimizing the time to recovery from an upset; sustainability is focused on the resources the community uses over its lifetime. Thus, to echo those nasty questions I used to hate on the SAT, resilience is to sustainability as weather is to climate.

In the next post, I’ll use the definition of community to further illuminate the sustainability-resilience relationship.

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Gödel’s Theorem and Economic Resilience

Logic is the anatomy of thought.

John Locke

Kurt Gödel was one of the last century’s preeminent mathematicians and philosophers. He is most famous for proving that for any system of logic, there are meaningful questions that can be asked, but that cannot be answered within that logical system.

It is easy to dismiss this as academic navel-gazing, but there are real-world examples of this. One of the over-riding issues of our times is the quest for social “justice.” But what is justice? Some say that government should take from those who have more and give to those who have less, and that is justice. But others (J D Vance and Wendell Berry) point out that this creates dependence and eventually is destructive. I can ask questions about justice, but can’t definitively answer them.

If I killed a man a thousand years ago in England, justice then would demand that I pay a wergild to the person’s family or lord to recompense them for their loss. Today, I would most likely either languish in prison (essentially a ward of the state) or be executed – the family of my victim would be uncompensated. Which “justice” is more just?

If we pass on to a higher plane, perhaps we’ll know. And, generally, that is one way to answer the unanswerable questions – move to a higher level framework. In the physical sciences, one of the great unresolved questions of the 19th century was – is light a particle or a wave? Newtonian physics said light was particulate, but couldn’t explain why light sometimes acted as a wave. It was only when quantum mechanics was developed (with Newtonian physics as a special case) that the question was finally answered with a resounding “Yes. Light is both particle and wave.” Quantum mechanics became that “higher plane” to explain light’s behavior; a new “logic” that subsumed Newtonian physics as a special case.

In the social sciences we have a similar situation – we can ask if a community or a community system (e.g., its economy) is resilient, but we can’t really answer that a priori within the logic of what we know. We have to develop the logic for that “higher plane” if we are to be able to predict resilience.

Shade Shutters, in a recent article,* has given us a glimpse of what that higher plane might be. He and his co-workers developed a quantitative measure for the economic structures of 938 urban areas. Rather than looking at this as a static property, they looked at the change of the economic structure over the period 2001-2017. Their primary interest was in finding a relationship between the evolution of an area’s economy and the economy’s performance during and after the Great Recession (GR). They chose the area’s per capita GDP as their performance measure.

They identified six clusters that were archetypes of an area’s economic evolution:

  • The economies in Cluster 1 were relatively stable prior to the GR, changed rapidly during the Recession, and then stopped changing, i.e., achieved a stable “New Normal.”
  • The economies in Cluster 6 behaved similarly, except that they had been significantly changing even before the GR.
  • The economies in Cluster 2 significantly changed prior to the Recession, and then essentially were stable.
  • The economies in Cluster 3 changed leading up to and in the early part of the Recession and then slowly evolved back to a prior configuration.
  • The economies in Cluster 4 had an almost constant rate of change in structure; there was little discernible influence of the GR on their makeup. I am tempted to think of them as the continuously adapting economies.
  • The economies in Cluster 5 had virtually no change before, during or after the Recession. In response to my query, Shutters indicated that these all seemed to be “micropolitan” – small urban centers.

Looking at the performance of each cluster, the economies in Cluster 4 (continuously adapting) were the only ones to show a net growth from the start of the GR through its recovery. All of the others lost ground in terms of their net change in per capita GCP. Somewhat surprisingly (to me), Cluster 5 – the unchanging one – did not perform the worst; the worst performing were the economies in Cluster 3, which had drifted back into their pre-Recession makeup.

Like all good research, Shutters’ work leads to lots of questions.

  • Besides the structural evolution of their economies, is there any other common thread that seems to key the best-performing archetype, or any of them? Geography, presence or absence of a dominant employer, prevalence of a certain type of industry, or trends. I would anticipate that communities with an “eds and meds” economy would tend to be more a Cluster 5, for example.
  • Cluster 3 is an anomaly to me – a sort of “Back to the Future” evolution. The figure seems to imply either that the Cluster’s evolution prior to the Great Recession was to an unstable state or that there was growth up to and into the Great Recession which was then chopped off. In a subsequent note, Shutters indicated that the evolution of Cluster 3 economies might reflect a temporary condition due to unemployment changing the apparent structure and then a recovery to the Old Normal.
  • A community’s economy is a more-or-less decentralized system. Its structural evolution reflects decisions made independently by scores of entrepreneurs and business owners. If the Invisible Hand was ever at work, it certainly has to be here.  Are these results applicable to other community systems, especially other decentralized ones (e.g., social systems)?
  • We tend to look at internal factors that cause a system to evolve in a certain way. But, in general, systems evolve in response to changes in their environment (everything that’s not a part of the system). The continuously adapting economies may simply be in an environment that is changing slowly enough that they can “keep up.”

Shutters has not yet reached that higher plane that will allow us to truly understand what makes a community resilient. But I believe his work points us toward that higher plane. Several years ago, I told a parable of foresters looking at fallen trees to try to understand the causes of their fall. I concluded the tale

[the foresters] are standing in the midst of a forest in which the trees are each bending to the wind and the other elements and then straightening when the wind or the rain or the snow dies down. And we as foresters are really most interested in what keeps the trees standing, not what makes them fall. So it should be with community recovery and resilience. Resilience does not arise from demonstrated weakness but rather from the exertion of strength. Thus, we need to know and understand the strengths of each community, how those strengths are exerted, and how we can nurture those strengths so that they become even stronger.

Shutters, as a wise forester, is focusing on recovery, not vulnerability. He is honed in on an economy’s dynamic character, not its static attributes. And by doing that, he is pointing to a path that I believe will lead to a greater understanding of what makes a community resilient. And if we achieve that understanding, the next – greater – challenge will be transform our communities so that they can adapt to their changing environments.

* Shutters, Shade T., S. S. Kandala, F. Wei, and A. P. Kinzig. “Resilience of Urban Economic Structures Following the Great Recession.” Sustainability 13, no. 2374 (2021).

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Rising after the fall

Our greatest glory is not in never falling, but in rising every time we fall.

Confucius

In a November post, I talked about a different way for a community to visualize its resilience. It was a functional approach focusing on three aspects of a community – its common functions, the risks it faces, and the resources it has for recovery. Left hanging was how a community can determine the resources needed for recovery from a disaster – and whether it can recover at all.

Recently, my co-worker Jennifer Adams and I were notified that our paper that provides one approach communities can use has been accepted for publication. The approach is based on the stress testing performed by financial institutions, adapted for the community context. I briefly summarize the approach below; if you are interested in more detail, it will be in the published version (in the Journal of Homeland Security and Emergency Management).

In general, the approach is effectively an extended tabletop exercise, focused on a specific event. It is intended to be scalable – applicable to a neighborhood, a community system, or an entire community. Since the focus is on recovery, the time frame for the scenario extends beyond that usually considered in emergency management exercises.

The approach starts with development of a scenario based on a specific extreme event. The extreme event chosen should correspond to one or more of the risks facing the community. Each scenario should be plausible but need not be tremendously detailed. The type and magnitude of the extreme event, its geographic scope if relevant (e.g., areas of flooding or damage) and the time over which the event will occur should be included.

Perhaps in parallel, the scope of testing is also fixed. Again, this may be a neighborhood, a single community system or an entire community. Since it is assumed that testing is conducted by those who know the neighborhood, system or community, the availability of these “subject matter experts” effectively determines the scope of testing.

An important part of the approach is the establishment of success criteria: this forces the community to think about what recovery is, and how long it should take to reach it. This in turn sets the minimum time horizon for testing – the recovery process should be simulated at least this long (and if recovery has not occurred by this time, the test can be extended). For many physical infrastructure systems, success criteria for recovery may already have been set (e.g., Maximum Allowable Outages); for others (e.g., social support systems), a desired time to resume normal operations may be used.

The next step is focused on the impacts of the extreme event. The community’s anticipated losses – especially in terms of the community’s fixed assets – are determined. This includes both the direct losses, and those indirect ones that result either as a cascade because of interdependencies or because of actions taken in response to the extreme event. So, for example, a weather event triggers physical damage, that in turn challenges the community’s human, economic and social capital. A health crisis may cause loss of life; as we have seen with Covid-19, the response to the pandemic may seriously deplete the community’s social and economic capital as well. Social unrest can lead to loss of life as well as tears in the community’s social and cultural fabrics. As a result of this analysis, metrics for measuring progress toward recovery are also developed.

With recovery – the end state – defined, and the losses identified, the next step is to identify the tasks required to achieve recovery. This is the core of the approach – first identifying the tasks and then the resources needed to accomplish each task. If a community has a long-term recovery plan, this is an opportunity to exercise it. Since most communities do not have such plans, this forces them to think beyond their desired endpoint and to detail how they’re going to get there after the extreme event. In effect, it provides an opportunity to develop a recovery plan for the specific extreme event. Most likely, these plans will represent “brute force” approaches.

In this step, the community also goes one step further – looking at the time necessary to accomplish each task with the resources available. It uses the community capitals approach as a means to systematically look at the assets available for recovery (dispatchable capital) and the time required to deploy them successfully. Depending on the expertise available for the test, rather accurate estimates of task duration and sequencing (serial and parallel) can be achieved.

The final step is to analyze the results. First and foremost is to determine whether the success criteria have been met. In other words, determining whether all of the tasks required for recovery can be completed in the expected/desired time frame. If they cannot, then the testing points to possible actions the community can take to recover in time. These may be mitigating actions to limit losses; investments to increase dispatchable assets; better planning to develop more innovative (and probably more elegant) paths to recovery. In practice, it’s likely that a combination of some or all of these would be chosen. This approach to testing also provides a time to recovery (i.e., when the last task is completed).

Stress testing of this type offers some real positives to a community:
• It is based on the risks the community actually faces.
• It uses the community’s own expertise and knowledge of itself.
• It is scalable – a community can look at only one part or the whole community.
• It provides a time to recover based on the resources actually available to the community.
• It indicates opportunities for community action to reduce the time to recovery.

I have briefly summarized the approach and what it can do for a community. In a followup, I will look at a specific scenario based on a health crisis. I’ll do this in two ways: first, just looking at a community health care system, and then looking at the entire community. I’ll do this with much trepidation – the damage from covid is perhaps too fresh; too many are still falling ill and some dying; and, sadly, too many are still playing the Blame Game. But I’ll still do it, because as Confucius indicates, the glory is in rising again – recovering – and stress testing can speed our rise from disaster.

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Covid-19: Disasters Have Direction

You can be sure of succeeding in your attacks if you only attack places which are undefended. You can ensure the safety of your defense if you only hold positions that cannot be attacked.

Sun Tzu

This is an updating of an old post.  The original did not have any specific examples; I think Covid-19 provides a good one.  I’m sure the concept “Disasters Have Direction” is obvious to many of you, but I’ve never seen it articulated.  As I try to show in the discussion of the pandemic, it can be a useful construct as we think about a community’s resilience.

For a few years, FEMA and DHS have championed the idea of an “All Hazards – Maximum of Maxima” approach to planning.  The basic premise is that if a community plans for the worst of the worst, then it will be prepared for whatever may actually happen. This is a deceptively simple tautology that I think deserves a little more analysis than it usually receives, especially in terms of community resilience.

Let’s start by looking at an idealized community.   A community can be thought of as an ecosystem.  There is a “human layer,” made up of individuals and families.  There is an institutional layer, consisting of private businesses and other economic institutions, and all of the other “human-serving” organizations in the community.  Then there is the physical, environmental, layer – containing the built and natural environment.  All of these are held together by the social capital within the community (some may argue whether the physical layer is bound to the community by its social capital, but that’s a subject for another post!).

Of course, this is an ideal community; real communities may have a strong economy but be weak in the human element.  Some have a decaying infrastructure but a flourishing natural environment.  Thus, we can depict a real community as follows.  This real community would be relatively weak in terms of its community institutions, have a somewhat stressed natural environment, but have a robust built environment.

Now let’s assume the community is hit by a pandemic.  There is no immediate physical damage.  Any that occurs most likely happens because the humans who normally maintain things –infrastructure, for example – are not able to do so.  This disaster has attacked individuals and families, and – because they are closely tied to the human layer – the community organizations that meet social needs.  For a pandemic, hospitals, clinics and the public health department would certainly be included.  Since, in this case, there is relatively little capacity in the community institutions (e.g., a rural community), they will be particularly hard hit – most likely overwhelmed. 

But what happens in a natural disaster?  The initial impact on the community is going to be on the physical layer; buildings are going to be blown down, debris will be strewn about, flooding may occur. The other parts of the community will be impacted because of these physical blows.  In our notional real community depicted above, there would be relatively little damage done to the built environment, but the natural environment would experience much greater damage (at least in relative terms) because it is weaker. 

A severe economic downturn attacks the community from another direction.  Businesses lay off workers; some close.  Many individuals and families experience severe economic hardship.  There is no immediate impact on the other parts of the community ecosystem.  Eventually, however, all will be affected.  In our example community, the economic impacts are less severe than for a community with a weak economy, or already burdened individuals and families.

Thus, disasters have a direction, as shown in the next graphic. It must be stressed that the graphic points out the initial point of attack.  If the magnitude of the initial impact is huge, or other parts of the community are weak, then the disaster is likely to ripple throughout the community with cascading impacts.

This simple concept is consistent with the idea that vulnerability to a threat depends on weakness at the point of attack.  This is shown in the next figure.  Threat X indicates a potential health crisis (e.g., a pandemic), while Threat Y is primarily a threat to the community’s economy.  As depicted, Threat X is more likely to lead to disaster than Threat Y because the greater relative strength of the community to withstand an economic downturn.

This simple picture of a community also has meaning in terms of recovery and community resilience.  If community resilience is measured by how fast – and effectively – resources are deployed to achieve community restoration and recovery, then the social capital within the community plays a crucial role.  Suppose Threat X above actually materializes.  The vulnerable part of the community has few available resources.  It is the community’s social capital – its connectedness – that provides the pathways for resources to be shifted within the community.  It is the community’s social capital that determines whether resources from outside the community are effectively brought to bear.  In a very real sense, it is the community’s social capital that determines whether the community actually recovers from disaster.

If we look at Covid-19 through this lens, clearly the pandemic attacked individuals and families, and community health organizations.  Its magnitude varied from community to community, but – initially – dealing with the pandemic exceeded the resources (e.g., PPE, ventilators) available to most communities, i.e., it was a disaster and it had a direction.  Communities had to rely on their connections (bridging and linking social capital) to others in the region and to the state (and, for the biggest cities, to the federal government) to get the resources they needed.  In a later post, I’ll outline a methodology that, if used, could have reduced the impact of the pandemic at the community level.

Our response to the pandemic triggered an economic disaster.  For those of you who remember my old post “Of Ice Storms, Interdependencies and their Impacts on Running a Bar” I pointed out that the number of businesses which could reopen after a disaster depended on how long they were closed.  In some places, the Covid-19 lockdowns lasted for months – and the economic consequences have been devastating.  I intend to update that post as well and expand upon it a little based on the knowledge we’ve gained from the pandemic.

Dan Alesch once said that we recall a disaster by the name of its triggering event, but remember it because of its impacts.  If that’s the case, Covid-19 will join the Dishonor Roll with Katrina, Deep Water Horizon, the Great Recession and so many others.  Each of these disasters were daggers that first pierced specific parts of the community, i.e., they had a direction.  Their impacts were determined by communities’ strengths at the point of attack and the force of the dagger’s thrust.  A community’s social capital determines how rapidly resources can be brought to bear to heal the wounds.  However, those who are not connected – without significant social capital – have to recover on their own:  resources won’t flow where messages don’t go.  In this way, the community’s social capital plays a crucial role in its recovery – and thus is a key component of the community’s resilience.

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Community Recovery in the Time of Covid

Sometimes things fall apart so that better things can fall together.

Marilyn Monroe

Our communities are going through tough times right now. All have seen disease and death damage their social fabrics. Some are experiencing physical devastation due to nature’s wrath and men’s anger. Sadly, we know that more death and destruction is inevitable. Our response to this has led to economic and educational chaos, and stunted lives.

But we also know that eventually these will ebb and end. We will stand on the rubble and realize that our communities must now recover – must now reach toward a New and, hopefully, Better Normal. We know that for some, recovery will require more resources than they have to give. Communities will look to state and federal governments to provide them the resources they lack. But what resources will our communities actually need?

Unfortunately, there’s no single answer. The damage done to many of our communities covers the spectrum from their physical environments to their social fabrics and their economies. Just as the damage experienced by communities will vary so to will the resources needed for recovery. Some communities will reach for any funding that they can, and sort of haphazardly aim to rebuild what was lost. But for those with the greatest damage, “You Can’t Go Home Again.” This time the magnitude of the damage is too great. For them, trying to rebuild the past has no future.

Other, more resilient, communities will recognize that the changes wrought by Covid and our response are so great that they require almost a reinvention. They will make the tough decisions to rebuild their communities to be “Future Fit,” ready to face whatever adversities the future may bring. They will take responsibility for their own recovery and develop plans to reach a New and Better Normal. And through their planning most will recover more rapidly than those who don’t plan.

While those plans will vary in detail, on another level they will have in common a focus on functionality, infrastructure and assets. In terms of functionality, they will likely start with an assessment of the damage to the community’s infrastructures. They will then look at how the existing infrastructure and assets will be used to achieve recovery. While these plans are likely to differ in the terms they use, I think it’s useful to look at their common focus through the lens of the Seven Capitals.

Social. In the US, our social fabric (our social infrastructure, if you will) has been badly frayed, especially in many of our major cities. Rioting, aided by masking and lockdowns, have prevented our social networks from the message-passing that is so vital for recovery of our communities – as I’ve said before, “Resources won‘t flow where messages don’t go.” And I’m not just talking about PPE and medical supplies. Although we don’t talk about it enough, most people depend on their networks of friends, neighbors and acquaintances to find out about job opportunities.

Unfortunately, while academia has established the importance of social capital, the damage to it is being ignored by many politicians. Recovery will require opening the places we gather as quickly as possible, so that we can reestablish our personal networks. That means churches, libraries, schools, parks and recreational venues. That also means getting rid of masks as soon as we can – they facilitate anti-social behavior. And most importantly, getting rid of those barriers that are keeping families apart.

Human. Even before Covid-19 reared its gnarly snout, our educational system had some serious problems. Educational “attainment,” especially in our de facto segregated inner city schools was so bad that it would have had to improve to be abysmal. Look at Baltimore – proficiency in reading and math hovering just slightly over 10%, but with a 70% graduation rate. And DC bordering on the criminal – a whopping 20% proficiency in reading and math among eighth graders, while spending twice the national average per pupil.

But just getting back to that “Normal” is proving challenging. While the “hybrid” model (part in-person, part online) sort-of, kind-of works for middle class kids, inevitably the disadvantaged (esp. in rural areas) will fall behind. We need to get the schools fully open now. But that will not absolve us of fixing the damage the lockdowns have already caused. If you can’t read and can’t do basic math, you can’t get a job to support yourself, let alone your family. One way to approach this is to task the federal Senior Corps with providing educational mentors for those who are struggling. This may also be a business opportunity for some of those out of work.

At the same time we’re taking care of our kids, we need to take a hard look at the skills of our out-of workers. These folks, in general, have developed the life skills to hold down a job. Most of those eventually will find similar work. But many won’t – a lot of jobs are gone, especially those in small businesses. We need to beef up our infrastructure for coaching, redirecting and retraining these once-and-future assets to our society.

Economic. Overall, the US now has a “90%” economy – about 10% of our labor force is out of work. Our goal should be careers, not simply jobs. That means businesses aimed at today’s and tomorrow’s needs, and workers with skills to match. Local government has a small role to play (as I discuss below) but ultimately economic recovery will be accomplished through the actions of innovators and entrepreneurs creating careers, and workers willing to learn new skills.

But that’s not to say that businesses, especially small businesses, don’t need help – many do. Professional and business associations should play a major role. First and foremost, small business owners need coaching as they make the tough decisions about whether and how to relaunch. Damage assessment is a skill that they seldom need, yet it is crucial to these decisions. It may indicate that the customer base isn’t there, or that a new business model is needed. Small business owners also often need help with the paperwork for SBA loans. Most professional associations already are providing guidelines for protecting the health of customers and employees, but they can do more.

Cultural. Anyone who watches the news has to be worried about the cultural chasm that seems to be widening in our country. We’ve always had the elitists who believe that government can solve all of our problems. We’ve always had the anarchists who believe that the only answer to our problems is the complete destruction of society as we know it. In past decades, the sensible middle – those who recognized our problems and worked to implement practical solutions – was strong enough to hold us together in this ideological tug-of-war. I’m not so sure that’s true any more.

If we are to recover our culture, we must first once more define it for ourselves. That means rediscovering our common values – freedom (and its homely twin, responsibility), family, the rule of law, equality of opportunity. That means regaining confidence in our own ability – that of each one of us – to make a difference in our world. That means recapturing our history – America the Aspirational – and our ability to dream. That means looking clearly and critically at our world, not through red- or blue-tinted glasses, but through the lens of our common values. And when we see situations not consistent with those values, once more working for the common good.

Doing all of this requires time and starts with small steps: opening churches, museums, art galleries, recreational venues and, yes, even bars. Rebuilding our culture will require that we reestablish our social networks, especially our ability to repair and extend those networks. The task of community rebuilding and recovery, if done well, will strengthen the sensible middle, and thus strengthen our cultural bonds.

Institutional. It is clear that many (most?) of our communities are going to need rebuilding (if not reinvention). That effort is going to require planning and resources. Since entire communities have been impacted, the whole of these communities needs to be a part of recovery planning, not just government. Further, all must recognize that while there likely will be more federal and state aid, ultimately recovery of the community will depend on how well the community can mobilize its own resources – financial, human and social.

For some communities, some sort of long-term recovery committee will move the community to a New Normal. Ideally, the committee will include all of those who can mobilize resources to get things done. Its most important job will be to “define victory” – determine what a successful recovery is for the community. It will integrate local (not just government!), state and federal resources. A part of this will be finding “patient capital.” It will act as an information hub, letting the public know what businesses are open, and where there are job openings. It will act as an economic gardener, focusing its attention on new and existing businesses looking to grow. Working with both local business and local government, it will flatten some of the regulatory barriers (e.g., licensing/permitting, unnecessary zoning restrictions, environmental reviews) to the birth of new businesses. The committee will also report on progress to the public. After a disaster of this magnitude, recovery will take years not weeks, so keeping the public informed is essential.

Built. Some locations have experienced significant damage to their infrastructures (e.g., from wildfires in the western US and tropical storms in the southeast). We know the drill for recovery – sort of. But if the New Normal is to be better than the old, then we may need to rethink the physical infrastructure, particularly in our bigger cities. I’m not a big fan of Governor Cuomo, but his ideas for making New York City both more livable and “socially distance-able” make sense. But what the events of the last few months have really highlighted are the infrastructure needs of our rural communities. Many of our responses to the pandemic have greatly stressed our – already fragile – rural health care infrastructure. And as I’ve noted above, we need to expand our internet coverage to include everyone, especially those in our rural areas.

This post is much longer than normal (I apologize!) but I could have written even more for each of these. Recovery from the pandemic will be a long slog. We cannot claim to have recovered until we’ve rebuilt all of our infrastructures (the assets of our community capitals) and have them functioning again. While government has a role to play, our communities’ recoveries won’t depend on government’s actions (although failure to recover may). Ultimately the recovery of my community, or your community, will depend on whether you and I – all of us – work together to achieve a New Normal. Our goal must be “Future Fit” communities, ready to face whatever adversities and to seize whatever opportunities the future may present.

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Economic recovery – sort of

These are the times that try men’s souls.

Thomas Paine

The pandemic and protests and civil disorder continue to assail both the social fabrics and the economies of our cities, states and nation. Over the last few weeks, I’ve been following an interesting set of maps and graphs detailing the ongoing evolution of the US economy.*

The graphs and maps are focused on consumer spending, and based on private sector data (e.g., credit card transactions). Thus, they do not directly reflect business activity (although the team has separately analyzed some data relating to business activity). They also are significantly distorted by government initiatives designed to mitigate the economic impacts (more on that below). The data is broken down into seven economic sectors** – by state and county, and also includes data for 50+ metro areas. Data are also reported on a national level for consumers living in high, medium and low income areas. In the following, let me give you a sort of high-level early-stage summary on the recovery of consumer spending (based on data up 6/26/20).

Total consumer spending is still down by about 7% since the group’s January baseline. However, that total is misleading – spending on Arts, entertainment and recreation and Transportation is still only abut half of the baseline, with a very slow trajectory toward recovery. It may take years for these sectors related to tourism to recover, especially Transportation. Spending on Restaurants and hotels is also still down by a third nation-wide, but with a better trajectory. Health care spending is down 12%, but seems to be recovering well. Spending on Apparel and merchandise has essentially recovered, though the data does not reflect shifts from storefronts to online suppliers. The biggest surprise is Grocery spending – up 12%, probably reflecting eating at home vs dining out. This is highlighted by data from March: Grocery spending spiked at +73%!

Another surprise is in who’s not spending – consumers in affluent areas are spending 12% less than in January. Middle income areas are seeing a drop of only about 6% in spending; while there is a negligible drop in less affluent areas. Other data collected by the group indicate that small businesses in the more affluent areas are also being harder hit than in other areas.

Looking at the data at a state level, mid-America is doing the best, with generally increased consumer spending; Tennessee having the largest increase (5%). West Virginia, New Hampshire, Idaho, Hawaii and Maine are also seeing somewhat increased consumer spending compared to January. Both coasts are doing more poorly, especially the West Coast. Consumer spending in Rhode Island and California has lagged the worst among the states.

Looking at the metro areas, there are two surprises: Jacksonville and Nashville. Jacksonville’s consumer spending is up over 5% compared to January; Nashville’s is off 33%(!). Nashville is particularly surprising given that Tennessee in general is doing rather well. San Francisco is also lagging badly, as are the other California metro areas as well as DC.

A few other observations about the data:

  • Iowa is the only state which has seen a decline on spending for groceries (11%).
  • Nashville saw the biggest drop in Transportation spending – 80%, and it’s staying flat.
  • In terms of Health care spending, the southern tier of states has recovered more than the northern tier; poorest performing is Vermont, off 52%.
  • In general, spending in rural areas is recovering more rapidly than in urban areas; and several rural counties actually saw increased consumer spending.
  • There is one aspect of the data that I find fascinating, but can’t explain: almost everyone one of the curves bottomed out in the period 3/28-4/17. However, in each case, there were two dips – one around 3/30 and another around 4/15, with slightly increased spending in between.

Here’s my takeaways:

  • The data shows great disparities in terms of geography, economic sector and income group. When I add in the data not included here (e.g., unemployment, housing, bankruptcies, small businesses closing) I come to the conclusion that recovery policies are going to have to be carefully crafted if they are to work. One size won’t fit all. Given the continuing dysfunction in Washington, I have to wonder whether my prediction of a four to five year recovery wasn’t overly optimistic. If Congress can’t come together on something as relatively simple as policing reform, how are they going to deal with the knottier (and naughtier!) issues surrounding recovery? As one example, increasing taxes on higher income groups will penalize already suffering small businesses in their areas – is this what we really want to do?
  • These data necessarily paint a much more positive picture than reality. They reflect the positive impacts on spending due to stimulus and unemployment payments (which eventually have to expire), but hide the looming problems associated with housing. Throughout the country, there have effectively been rent and mortgage “holidays” – most often three to six month moratoria on evictions and foreclosures. As these expire, the pressures on the consumer are going to increase. Governments will be forced to choose between landlords and renters, banks and homeowners. In general, my sympathies are always with the underdog, but the choice between landlords and renters is actually between two little guys – over half of the nation’s landlords manage only one or a very few units.
  • The prognosis for many metro areas is not very good. People are leaving NYC, San Francisco (in fact, all of California) and other big cities in droves. Conversely, the suburbs and near-urban rural areas are already seeing signs of growth. If this de-urbanizing trend continues (and I think it will) it will constitute a watershed period in American history, testing urban resilience as never before.
  • Still, the data could have been worse; even with the caveats above, rebounding consumer spending is a necessity for our consumer-driven economy. And recovery is actually happening in some places. We aren’t seeing a V-shaped recovery, but progress is being made.

* Developed by a group consisting of Raj Chetty, John N. Friedman, Nathaniel Hendren, Michael Stepner, and the Opportunity Insights Team.

** Apparel and general merchandise; Arts, entertainment and recreation; Grocery; Health care; Restaurant and hotel; and Transportation.

Finding a Better Path

I’ve learned that the safest path is not always the best path and I’ve learned that the voice of fear is not always to be trusted.

Steve Goodier

If COVID-19 returns in the fall, do we really want to go down the same path we’ve been taking? In the US, we have focused on “flattening the curve” – not reducing the total number of deaths directly due to COVID-19, but rather spacing them out so that “indirect” deaths due to insufficient health care system capacity have been minimized. We took this path because our models initially predicted tens of millions of cases – and millions of deaths – that would have overwhelmed our emergency rooms. In taking this approach, all of us were faced with a situation for which we were unprepared – we had never been faced with this kind of crisis. Our stocks of many critical resources had been depleted but never replenished. The “Triple Header” of hurricanes almost three years ago had hinted at what we now know – our EM doctrines are clearly inadequate to handle disasters that go beyond the regional. We acted largely out of caution and a fear of the unknown.

Things will be different the next time. We know that the approach we’ve taken to the pandemic is fraught with unintended consequences – impacting our economy, our social compact and our mental health. We will have much greater testing capability and probably sufficient PPE, and capable supply chains for each, the next time. With luck, we may also have more effective treatments available for those infected.

The problem we face in crafting a new approach is simply that too much conflicting “information” is being fire-hosed at us; it’s damned difficult to find the nuggets of truth in the rushing torrent so that we can plot a better path for the future. I strongly believe we should empanel a national Board of Inquiry for the coronavirus chartered to develop a better approach for nationwide disasters such as this. It is important that we do this for next fall, but also because this crisis may impact our ability to manage severe weather events starting this summer.

Rather than bipartisan, the Board should be non-partisan – focused on policy and planning rather than personalities and politics; lasered in on developing a better approach rather than playing the Blame Game. Such a Board needs a strong chair, versed in both the strategic and operational aspects of dealing with crises; Craig Fugate, Honore Russell or Thad Allen come to mind. The Board should be independent of both the Executive and Legislative Branches, perhaps under the National Academies. The Board should include expertise in economics; health and health care; law; and federal, state and local decision-making.

Such a Board should pursue lines of inquiry such as:

• Situational awareness. Whatever plan we develop, we can be sure that it will have to be modified once case numbers start to rise. Those changes will be informed by the data at hand. I’m sure I’m not the only one who can’t figure out whether we’re severely undercounting or overcounting cases and deaths (My guess is undercounting cases and overcounting deaths, but who knows?). The federal government should provide useful guidance in terms of how to count and report, esp. considering that both the pub;lic and private sectors are likely to be involved.

• Federal, state, community and private sector roles. There seem to be as many opinions about who should lead and how, who should follow, and who should get out of the way as there are politicians and pundits, i.e., way too many. We need simple efficient processes at all levels, minimizing paperwork, and clear on what they are and how to follow them. We really began to have success when we let the private sector get involved. Our processes need to stop stymieing and start encouraging private sector participation.

• Urban areas. Most importantly, we need to understand why urban areas such as NYC were hit so hard. Less than 3% of US counties – all urban and accounting for half of our nation’s GDP – have had 60% of US cases. If NYC was a separate country, its mortality rate would exceed Italy’s! Over one-third of US deaths occurred within a 30 mile radius of NYC. We have to understand what happened in these urban areas to perform better next time.

• Foreign experience. The Board should consider successful responses from other countries. As of today, Taiwan has had only six deaths and less than 450 cases out of a population of 23+M. They learned some hard lessons from SARS – and acted on what they learned; we apparently haven’t.

• Lockdowns. Singapore, South Korea and Sweden all have approached the “Wu Flu” very differently than we have in the US, with arguably better results. One element these have in common is aggressive contact tracking; it seems that we can learn from what they have done. In these countries, the elderly and those potentially at greatest risk were urged to quarantine, but schools weren’t closed; restaurants weren’t closed; retailers weren’t closed. If we look at the responses across our states, lockdowns don’t seem to have had a quantifiable impact on health outcomes; population density does. Conversely, we will likely pay a terrible price later in deaths of those who didn’t go for their cancer treatments, who couldn’t afford to pay for their medications, who didn’t get the proper exercise. This doesn’t begin to address the incalculable impacts on our kids’ educations and future employability, or the millions of children worldwide who the UN estimates are going to die of starvation.

• Next points of attack. We now know that urban centers were the hardest hit in this first round. We need to determine whether this has resulted in “herd immunity.” The potential vulnerability of more rural populations also needs to be addressed.

There are other issues (e.g., border security and immigration) that also should be considered. What we need most now, however, is the wisdom to find those nuggets of truth, the wisdom to use them as signposts toward a better path, and the courage to follow those signs onto that path. Given our highly partisan polity, wisdom, will and courage will all be needed. The GOP and the Dems have both contributed to the problems; the best ideas from both are needed to solve them.