Would You Lie to Airport Screeners?
The terrible, “lesser evil” choice facing travelers asked about Ebola

Slate Magazine, October 14, 2014
by Benjamin Hale

After the Dallas Ebola patient Thomas Eric Duncan died last week, public comments ranged from expressions of sadness and condolences to his family to vitriolic condemnations of his behavior for lying to airport screeners. It may be helpful to revisit the rationale that likely brought him here, especially in light of the Centers for Disease Control and Prevention’s new airport screening procedures, as well as Liberia’s and Texas’ earlier proposals to prosecute Duncan for evading airport checkpoints. Thinking carefully about his mindset can help us understand how better to address this outbreak and keep it from spreading further.

Ebola is a disease that is terrifying for many reasons, not the least of which is that it kills gruesomely and is easily transmitted. It is also terrifying in part because it preys on caregivers and loved ones, parasitizing the humanity of those who care for and come into close contact with the ill. Duncan himself was a firsthand witness to the horrors of this disease. He briefly assisted his neighbor, a 19-year-old Ebola-infected pregnant woman, as she climbed into a taxi.

It is hard to blame someone for such a brief and noble encounter. Here is a sick young woman who needs help getting to a hospital, but who is too weak to climb into a cab on her own. There he is, standing nearby. Who would not help? Who would recoil and refuse to assist an ailing friend?

And besides, it was just a brief encounter. The opening of a door. The holding of an arm. The making comfortable.

There was little reason for Duncan to suspect, from this one minor interaction, that he would become ill. It is unfathomable, but true, that a single, fleeting touch is enough to pass the disease from one person to another. Duncan probably found this fact similarly unfathomable. He may not have known for certain that his neighbor was infected with Ebola rather than some other illness. He knew that she was sick, that much is clear. He apparently did not believe himself to be infected with Ebola, and certainly did not want to bring the disease to the United States. Indeed, before his passing, Duncan expressed remorse for having brought the disease to the “love of my life.” It is most certainly not true that Duncan brought Ebola here maliciously or intentionally.

Nevertheless, some have suggested that Duncan ought to be prosecuted for lying to airport screeners about this brief contact with his sick neighbor. The logic is that lying in these circumstances puts other lives at risk, and also that lying is wrong. In most circumstances, we punish wrongdoers partly for justice reasons, but also partly for deterrence reasons: It would be very bad for the world if individual travelers could get away with lying to airport screeners. The screeners are in place to contain the outbreak, and if they do not have good information, containment grows that much harder.

This much is true. You should not lie to airport screeners.

But what is not true is that this is always such an easy decision. It is also not true that Duncan is guilty of putting more lives at risk because of this decision.

The fact is, Duncan probably put fewer lives at risk by coming to the United States, and he certainly stood a greater chance of surviving this terrible disease by coming to a Western medical hospital. If he had stayed in Liberia, there is very high likelihood that he would’ve transmitted Ebola to more people than he did. Read more …

Science Advice to Governments
Bridges, Volume 41
October 2014

by Roger Pielke, Jr.

Globally, governments have incredible access to expertise. Some of these experts work directly for governments, while others are found in academia, in business, and in civil society. How can governments best tap into this wide array of expertise in making policy?

This important question was the backdrop for the first global conference on science advice to governments, held in Auckland, New Zealand, in August 2014. The conference focused on government science advisory mechanisms, which includes (especially in some Commonwealth nations) a Chief Scientific Advisor whose role is to support a prime minister or departmental chief.

The conference was remarkable for the participation of sitting governmental officials. Chief scientific advisors from the UK, Cuba, India, Australia, Ireland, the European Union, and Malaysia were among the participants. The meeting was hosted by Sir Peter Gluckman, chief scientific advisor to the New Zealand government, along with the International Council for Science. I also attended, and will share below some of my observations from the conference.

The meeting was important for the conversations and the network facilitated by the conference. Governance takes many different forms around the world, but one constant everywhere is the need to integrate expertise with decision making. Comparing and contrasting experiences, what works and what doesn’t, can help to make science advisory processes more effective.

For instance, in the United States the President’s science advisor is a political appointee who is also accountable to the Congress. This gives the science advisor an explicit role in helping to advance the political agenda of the president. Whether or not the president calls on the science advisor is another matter. In contrast, the UK government’s chief scientific advisor is not a political appointee and serves a term appointment that may span multiple governments. Clearly there are strengths and weaknesses to each approach, although they represent different approaches to democratic governance.

One point discussed at the conference involved the desirability of having a centralized science advisory mechanism at the highest levels of government. For instance, the UK has a chief scientific advisor, but Germany does not. Yet, the German government has an impressive track record of using science in policy. I often point to the German Federal Institute for Risk Assessment as a good example of an agency that has successfully navigated the choppy waters of scientific advice.

The question about the desirability of a centralized advisory mechanism took on greater meaning at the conference when Anne Glover, CSA for the European Commission, gave a candid and heartfelt speech on her experiences as the first person in that role. Glover explained that a number of environmental NGOs had not only called for her to be fired, but also asked the Commission to scrap the CSA position altogether. Their motivation was apparently their dislike of Glover’s views on the science of genetic modification. Glover’s position, and indeed that of a European Commission’s CSA, hangs in the balance as Jean Claude Juncker assumes the EC presidency in November.

Glover’s experiences highlight a common challenge facing scientific advisors and advisory processes – a lack of clarity about their formal role in policy making. The EC CSA is new and working this out; however, other institutions don’t have that excuse. Both Dr. Raja Chidambaram, principal scientific advisor to the Government of India, and chairman of the Scientific Advisory Committee to the Cabinet, India, and Sir Mark Walport, government chief scientific advisor in the UK, presented very detailed descriptions of their roles in government. However, having a well-defined role did not prevent Walport from being criticized for his views on bees and pesticides very soon after assuming the position. Read more …

New CSTPR Publication by Jessica Weinkle:

An Average Perspective on Insurance Profitability Cycles
Insurance Journal
October 6, 2014

by Jessica Weinkle

Dr. Robert Hartwig, president of the Insurance Information Institute (III), is well known for his plentiful data on the insurance industry and chartist presentation style. His identification and aggregation of data is quite commendable.

On several occasions, I have come across Dr. Hartwig’s chart on Property/Casualty Insurance Profitability (See above). The image shows annual first quarter return-on-equity (ROE) for the property/casualty industry from 1975 onward. Arrows overlaying the data demarcate an approximate 10-year period between points of peak profitability.

I don’t find the suggested decadal cycle of P/C industry profitability all that convincing. However, I do think the data is interesting.

I’ve extracted the data from Dr. Hartwig’s “P/C Insurance Profitability” chart above and created the two charts below. The first chart shows the five-year moving average of the data. Read more …

A Lack of Reliable Doping Data Puts the Spirit of Sport in Peril
Sporting Intelligence
September 30, 2014

by Roger Pielke, Jr.

Sport is in the news for a lot of the wrong reasons, from the scandal over the NFL’s response to cases of alleged domestic abuse to FIFA’s latest farce – the global football body ordering executives to return $27,000 watches given as gifts during this year’s World Cup by a grateful Brazilian FA in the same week FIFA sponsored a meeting on ethics.

One area where sport would seem to have its act together is in the area of anti-doping, or in clamping down on the use of prohibited performance-enhancing drugs. The biggest ‘catch’ in recent times could hardly have been more exemplary, in the shape of Lance Armstrong, who finally admitted to years of doping and was stripped of his seven Tour de France titles.

But all is not well with anti-doping efforts. Current policies are unaccountable, threaten athletes’ rights and risk the integrity of very sports that they are supposed to protect.

Anti-doping policies for the Olympic sports are implemented by the World Anti-Doping Agency, which oversees and coordinates the work of almost 200 national anti-doping organisations. WADA is overseen by governments, sports organisations and stakeholders under the provisions of a United Nations treaty. It is responsible for developing a list of prohibited substances and implementing a corresponding testing regime to identify and sanction those who break the rules.

I asked WADA some simple questions. How many athletes fall under testing regimes globally? How many athletes were tested in 2013? How many associated sanctions resulted?

The answers I received were shocking. WADA told me that they do not know the answers to these questions, explaining that the tests are administered by 655 different agencies which have signed on to the WADA Code and not all agencies share their results, even for elite athletes.

This means that important questions, at the core of any evidence-based anti-doping policy, cannot be answered. How many athletes dope? We don’t know. Is that number increasing or decreasing? We don’t know. How well does testing serve as a deterrent? We don’t know. And most importantly: Are anti-doping policies working?

Anti-doping officials tell me that the true purpose of testing is deterrence not detection. However, it is hard to know how well an emphasis on deterrence is actually performing without solid data.

The data that is available clearly suggests a problem. Current testing around the world detects evidence of doping in less than one per cent of samples, a number that hasn’t changed since 1985. Many – most? – of those are for recreational drugs, mainly marijuana, and approved medical usage.

By comparison, an anonymous survey of more than 2,000 elite track and field athletes conducted by WADA at the 2011 World Championships and Pan-Arab games found that 29 per cent and 45 per cent of respondents, respectively, admitted to the use of prohibited performance-enhancing drugs. Read more …

Understanding and managing model risk for reinsurance and ILS

Artemis, September 25, 2014
by Jessica Weinkle

In recent years, insurers and regulators have sought improved transparency of risk modeling practices. For example, recent changes to insurer capital requirements outlined by Solvency II explicitly promote goals of transparency and risk model assessment.

Catastrophe model vendors supply clients and regulators with extensive documentation on methodology. Yet, risk managers are increasingly interested in the uncertainty inherent in model methodology.

This type of uncertainty comes from the theoretical underpinnings of the model construction. In the sciences this type of uncertainty often goes by the term epistemic uncertainty. In insurance, it is often regarded as model risk and generally defined as, “the uncertainty that arises from having the wrong models to start with.”

In response to client demand, catastrophe modelers are offering improved access to model components and ease of model blending, morphing, fusing, etc. Most notable of efforts are those of RMS, Karen Clark and Company (KCC) and Lloyd’s. RMS(one) promises to provide users with access to over 300 probabilistic models, whereas KCC’s RiskInsight enables users access to internal assumptions. Lloyd’s Oasis offers users choice in “a set of plug-and-play components.”

These efforts are aimed at resolving concerns about model risk but do not actually help to reduce or control model risk. Improved ability to manipulate vendors’ models may buffer companies from volatility produced by model updates. But that volatility is produced by changes in the decision making by the model vendors and their judgments about how best to create a model.

The ability to create one’s own theory on how best to estimate a given risk does not make that theory an accurate representation of reality.

By chance alone, some views of risk will demonstrate better skill than others. However, model risk remains persistent because, as Karen Clark long ago explained, “[m]odel validation is also problematic.” Read more …