Tag Archives: ebola

Fighting Emerging Pandemics With Catastrophe Bonds

By Dr. Gordon Woo, catastrophe risk expert

When a fire breaks out in a city, there needs to be a prompt firefighting response to contain the fire and prevent it from spreading. The outbreak of a major fire is the wrong time to hold discussions on the pay of firefighters, to raise money for the fire service, or to consider fire insurance. It is too late.

Like fire, infectious disease spreads at an exponential rate. On March 21, 2014, an outbreak of Ebola was confirmed in Guinea. In April, it would have cost a modest sum of $5 million to control the disease, according to the World Health Organization (WHO). In July, the cost of control had reached $100 million; by October, it had ballooned to $1 billion. Ebola acts both as a serial killer and loan shark. If money is not made available rapidly to deal with an outbreak, many more will suffer and die, and yet more money will be extorted from reluctant donors.

Photo credits: Flickr/©afreecom/Idrissa Soumaré

An Australian nurse, Brett Adamson, working for Médecins Sans Frontières (MSF), summed up the frustration of medical aid workers in West Africa, “Seeing the continued failure of the world to respond fast enough to the current situation I can only assume I will see worse. And this I truly dread”

One of the greatest financial investments that can be made is for the control of emerging pandemic disease. The return can be enormous: one dollar spent early can save twenty dollars or more later. Yet the Ebola crisis of 2014 was marked by unseemly haggling by governments over the failure of others to contribute their fair share to the Ebola effort. The World Bank has learned the crucial risk management lesson: finance needs to be put in place now for a future emerging pandemic.

At the World Economic Forum held in Davos between January 21-24, 2015, the World Bank president, Jim Yong Kim, himself a physician, outlined a plan to create a global fund that would issue bonds to finance important pandemic-fighting measures, such as training healthcare workers in advance. The involvement of the private sector is a key element in this strategy. Capital markets can force governments and NGOs to be more effective in pandemic preparedness. Already, RMS has had discussions with the START network of NGOs over the issuance of emerging pandemic bonds to fund preparedness. One of their brave volunteers, Pauline Cafferkey, has just recovered from contracting Ebola in Sierra Leone.

The market potential for pandemic bonds is considerable; there is a large volume of socially responsible capital to be invested in these bonds, as well as many companies wishing to hedge pandemic risks.

RMS has unique experience is this area. Our LifeRisks models are the only stochastic excess mortality models to have been used in a 144A transaction, and we have undertaken the risk analyses for all 144A excess mortality capital markets transactions issued since the 2009 (swine) flu pandemic.

Excess mortality (XSM) bonds modeled by RMS  
Vita Capital IV Ltd 2010
Kortis Capital Ltd 2010
Vita Capital IV Ltd. (Series V and VI) 2011
Vita Capital V 2012
Mythen Re Ltd. (Series 2012-2)XSM modeled by RMS 2012
Atlas IX Capital Limited (Series 2013-1) 2013

With this unique experience, RMS is best placed to undertake the risk analysis for this new developing market, which some insiders believe has the potential to grow bigger than the natural catastrophe bond market.

Ebola in the US: How big of problem are we looking at?

As mentioned in my previous blog post, Ebola has the potential to be one of the deadliest epidemics in a century, but the primary area of concern is Western Africa, where the virus is most prevalent. However, as cases pop up in the U.S., concerns are rising, as evidenced by the acute media analysis and discussion around the first case in New York, for example.

Based on RMS modeling, we estimate that there will be between 15 and 130 cases in the U.S. between now and the end of the year—less than 1 case for every 2 million people. Our calculations assume that American medical professionals working with infected people in West Africa will account for the majority of cases. We simulated the number of new U.S. cases based on the existing infection rates among the American medical workers; this technique incorporates our projections for future West African caseloads and medical staff on the ground in the next two months, based on RMS’s epidemic scenario model. We then further modeled the virus’s spread once back in the U.S., taking into account the preparedness and higher quality of treatment facilities here versus the affected countries in West Africa.

The high end of the range is likely a slight overestimate as our calculations exclude automatic quarantining measures that some areas of the US are implementing. These measures can both reduce the number of contacts (people who come into contact with the infected person) for the imported cases, as well as increase the travel burden on U.S. volunteers planning to support the effort in Africa; this in turn could potentially reduce the number of people who actually make it over to the affected region.

The U.S. is prepared to handle the caseload even if it hits the upper range of 130 new cases. At any given time between now and December, specialized Ebola biocontainment facilities will have 11 beds available, which is enough to cope with the maximum weekly caseload in most of (but not all) of our modeled projections. In the more extreme scenarios, we still expect hospitals nationwide that have at least one Ebola treatment bed in place to handle overflow. Even if the reality over the next few months resembles a very pessimistic situation, it will be manageable given the U.S.’s higher capacity for managing cases.

Catastrophe modeling is an art and a science. The interesting, albeit challenging, part about calculating a range for something like this is that so much is contingent on estimates. The very nature of the virus and the exponential way the epidemic spreads means our estimates of the uncertainty in the variables are amplified in the number of cases. Our estimate is largely dependent on when affected regions reach the tipping point, where the number of new daily cases declines rather than increases. Everything is interconnected – the pace at which the epidemic spreads directly affects the tipping point, which then affects the need for treatment and number of professionals, which in turn affects the potential number of cases that can be imported back to the U.S.

As with all catastrophes we model, understanding risk is the first step toward mitigating and managing it.

Are fears of a global Ebola pandemic warranted?

Ebola is a hot topic in the media right now, with multiple cases being reported outside of West Africa and much confusion among the general public around the reality of the danger. So, are the fear and sensationalism warranted?

RMS models infectious diseases and recently developed the world’s first probabilistic model for the current West African Ebola outbreak. While Ebola is indeed a very scary and relatively deadly disease, with a case fatality rate between 69 and 73 percent according to the WHO, RMS modeling shows that it is unlikely the outbreak will become a significant threat globally.

The spread of Ebola in West Africa is in part due to misconceptions and fear surrounding the disease and a lack of public health practices. Ebola can be passed solely via bodily fluids; the risk of unknowingly contracting the disease is low.

Fear is prevalent among some West African communities that Ebola is a lie or is being used purposefully to wipe out certain ethnic groups, causing them to hide sick family members from healthcare and aid workers. Customary burial practices, in which family members kiss and interact with the dead, also have contributed to Ebola’s spread. Getting the populace in these countries to trust foreigners who are telling them to abandon their customs has been an uphill struggle.

In more developed countries where health care is more advanced and understood, the chances of transmission are exponentially smaller due to the fact that extreme containment measures are taken. Controlling the spread of the disease comes down to a question of logistics; if the medical community can control the existing cases and trace the contact made with carriers, spread is much less likely. For example, the case in Texas can be contained to one degree as long as every single person in contact with the patient is tracked.

There is also a (speculative) fear of the virus mutating into an airborne pathogen; the fact is, the chances of the virus changing the way it is transmitted, from fluid contact to airborne passage, are very low and of a similar order of magnitude to the chance of emergence of a different highly virulent novel pathogen.

Vincent Racaniello, a prominent virologist at Columbia University wrote:

“When it comes to viruses, it is always difficult to predict what they can or cannot do. It is instructive, however, to see what viruses have done in the past, and use that information to guide our thinking. Therefore, we can ask: has any human virus ever changed its mode of transmission? The answer is no. We have been studying viruses for over 100 years, and we’ve never seen a human virus change the way it is transmitted.”

The tipping point in the modeling of a virus like Ebola is the point where the resources being used to mitigate the threat outpace the increase in new cases. Trying to get ahead of the epidemic itself is like a race against a moving target, but as long as people get into treatment centers, progress will be made in getting ahead of the illness.

So, while Ebola is a very scary and dangerous illness, it is not something that we expect to become a global pandemic. However, while the current outbreak is not expected to spread significantly beyond West Africa, it still has the potential to be the most deadly infectious disease in a century and could have drastic economic impacts on the communities that suffer from Ebola breakouts. In fact, the economic impacts are likely to be worse than the actual impacts of the disease, due to negative impacts to trade and inter-community relations.

The key is to contain it where it is, reach the tipping point as quickly as possible, and to promote safety around existing infected persons. Through travel control measures and the development of several new drugs to combat the virus, the danger of epidemic should be drastically reduced in Africa and, as a result, the rest of the world.

Assessing the Risk of a Global Ebola Pandemic

With the current outbreak of Ebola in western Africa, as well as the recent MERS coronavirus and H7N9 avian flu outbreaks, the world is becoming increasingly concerned about the risk of emerging infectious diseases and their potential to cause the next pandemic.

As catastrophe modelers, how do we assess the risk of a pandemic?

To understand the potential dangers of Ebola, it’s helpful to look to the framework we use at RMS to model infectious disease pandemics. The RMS® LifeRisks Infectious Disease Model projects the excess mortality risk for existing infectious diseases, like influenza, as well as infectious diseases that are emerging or have recently appeared, like Ebola. When modeling a disease, we first look at two main criteria: the virulence and the transmissibility of the pathogen responsible for causing the disease. We then take into account mitigating criteria, including medical and non-medical interventions.


Virulence is a measure of how deadly a disease is, typically measured by the case-fatality rate (CFR), which is the proportion of people who die from the disease to those who do not. The current Ebola CFR is 55 percent. For comparison, the CFR for bubonic plague typically ranges from 25 to 60 percent. CFR for flu is typically less than 0.1 percent.



Transmissibility refers to how likely an infected person is to transmit the disease to another person, and is measured in terms of the basic reproductive number, or R of infection, which is the average number of additional infections one person generates over the course of illness. In order to cause an epidemic, R needs to be greater than 1.

The R for the current Ebola outbreak is greater than 1, and the disease will continue to spread. Past Ebola outbreaks have been estimated to be in the 1.3 to 1.6 range, but have occasionally been greater than 5, which is why there is cause for concern. However, Ebola is less transmissible than many other infectious diseases. For example, measles, which is highly transmissible, has an R of greater than 10 in an unvaccinated environment.


Societal and Environmental Factors

Societal and environmental factors can play a large role in transmissibility. In this case, societal and environmental factors in West Africa have contributed to the disease’s spread. For example, traditional burial practices in which families wash the deceased can expose additional people to the virus.

However, the risk of Ebola developing into a pandemic that extends beyond the region is low, due to the standard public health and infection control practices in place in many countries globally. Ebola can only be transmitted via direct contact with bodily fluids, especially blood, which means that caregivers are the primary people who might be exposed to the virus. In many countries including the U.S., the general practice is to treat all blood as potential sources of infection, due to experience with HIV and other blood-borne diseases. In quarantine situations, such as those being used with the American Ebola cases in Atlanta, the likelihood of transmission from a single person is miniscule.

Medical and Non-Medical Interventions

Medical and non-medical interventions mitigate the risk of an infectious disease pandemic. Typical medical interventions for infectious disease include pharmaceuticals and vaccines. Often, there is no specific therapy or drug available for new or emerging diseases. In these cases, we model the effect of supportive care, which includes management of blood pressure, oxygen, and fluid levels. As we’ve seen with the current outbreak, supportive care and the access to healthcare can vary substantially, depending on the region or population. With the exception of experimental treatments, there are no pharmaceutical interventions available for Ebola. Experimental Ebola drugs are not applicable to large populations at this time.

If there are high enough immunization rates, vaccines can reduce or stop the spread of diseases like measles or whooping cough. Unfortunately, a vaccine isn’t currently available for Ebola. Ebola outbreaks occur sporadically and are caused by different virus strains, making vaccine development more difficult.

In addition to vaccines and medical interventions, we account for non-medical interventions when modeling the impact of pandemics. Non-medical interventions include quarantines, school closures, and travel restrictions. Various countries in Africa have begun to implement these methods in hopes of stopping the spread of Ebola. However, these types of countermeasures can often be difficult to time or enforce properly. Ebola can have an incubation period from two days to as long as 21 days.

So, what is the pandemic potential of Ebola?

The current outbreak is now the largest outbreak of Ebola to date, and the World Health Organization (WHO) has designated the outbreak as a Public Health Emergency of International Concern. However, while cases will continue to develop, a global pandemic is unlikely. Even if the disease were to spread to other regions of the world, Ebola is still considered a rare disease and the transmissibility is likely to be much lower due to quarantine and infection-control measures, even if the CFR remains high. We have not seen any community transmission outside of Africa, and this is expected to continue. Ebola is a very serious disease, with devastating consequences to impacted communities. As risk managers, we aim to improve understanding of catastrophes such as pandemic disease so that as a society we can be better prepared to mitigate risk and recover from catastrophes.

Rebecca Vessenes contributed to this post. As a Senior Quantitative Modeler at RMS, Rebecca is involved in the development and parameterization of the LifeRisks longevity models. She recently completed the longevity model for Japan and has worked on determining the correlation structure for mortality improvement between countries. Prior to working for RMS, she led the Financial Modeling group at AIR. Rebecca earned a Ph.D. in mathematics from California Institute of Technology and is an actuary with the Society of Actuaries.