Dec 13, 2017
When, not if: Are you prepared for pandemic risk?Influenza (the flu) is one of the most common, highly contagious viral infections. It’s something we’re all familiar with, but is your business prepared for when that influenza strain takes the form of something like H1N1? Pandemics historically recur every 30 to 50 years, according to Lloyd’s. There’s reason to worry that the next one could be the worst yet. Increasing global networks and supply chains, rates of travel, and greater concentrations of the population living in cities all leave us more susceptible to infectious disease. The National Bureau of Economic Research estimates that a global pandemic event could have an impact of up to US$570bn – a staggering .7% of global income. “This is definitely a top-ten risk cited by most chief risk officers,” said Bill Rossi, CEO of Metabiota, a biotechnology company that uses data and risk analytics to assess infectious disease threats. Mitigation plans for infectious disease epidemics typically focus on the financial losses associated with direct costs, like treatment and response expenses, says a report compiled by Metabiota. The biggest share of costs related to epidemics, though, come from indirect impacts like reduced productivity. The World Health Organization estimates that indirect costs account for over 80% of the economic burden of epidemics. To view the entire article by Corporate Risk and Insurance Magazine, click here.
Dec 06, 2017
Metabiota Reveals Top Predictions for Risk Management in 2018Metabiota Reveals Top Predictions for Risk Management in 2018 Leader in Epidemic Risk Modeling Shares Expertise and Insights for Global Health Community SAN FRANCISCO, CA–December 6, 2017—With more than 400 human disease outbreaks in the past 10 years, the human and economic toll has been extensive. In fact, experts project the impact from a global human pandemic to be around $570 billion or 0.7% of global income. The global health community has reached a tipping point when it comes to leveraging better mechanisms for financing and managing the economic blowback of an outbreak. With that, Metabiota, the pioneer in epidemic risk modeling, is revealing its top trends and predictions for epidemic risk in the year ahead. “From the Madagascar Plague to the Ugandan Marburg virus outbreaks and the continued plight to mitigate the Zika Virus, it is clear that epidemic risk continues to pose a global health threat to communities and organizations worldwide,” said Bill Rossi, CEO of Metabiota. “At the center of this effort are new methods for assessing and insuring risk, and thanks to advances in disease tracking and reporting, software machine learning and artificial intelligence, we can now understand the risk of disease spread more clearly. Metabiota is committed to helping the world become more resilient to epidemics by working with governments and organizations around the globe. Our team is sharing this knowledge and expertise, so that all risk managers can be better prepared in the year ahead and beyond.” Metabiota’s team outlined five different aspects of risk, along with their prediction for what lies ahead in 2018: CEO Bill Rossi on Corporate Risk: Metabiota predicts that 2018 will be the year the Chief Risk Officer takes center stage for corporations, and risk management will be the top priority for CEOs and company Boards. Just as the Chief Information Officer (CIO) role was the toughest job in Corporate America in the 1990s, today Corporate America has a new toughest job – the Chief Risk Officer (CRO). With the proliferation of risk, it is increasingly difficult to keep pace with the current and emerging risks that can threaten a company's business. These include natural disasters like hurricanes, earthquakes, fires and floods, as well as non-physical risks like cyber breaches and infectious disease spread that can cause major business interruption. Head of Data Science Nita Madhav on Forecasting Risk: Metabiota predicts that in 2018, the infectious disease modeling community will improve and enhance forecasting models, including higher resolution and more timely data, such as electronic health records and the genetic sequences of pathogens, into forecasting models. Forecasting epidemics is the holy grail of infectious disease modeling and one that looks increasingly achievable in the year ahead. Historically, the US Centers for Disease Control and Prevention has held a flu forecasting challenge to forecast how the flu season will unfold in the U.S. These forecasts rely on different datasets including reported flu cases, social media data, weather data, and other disparate sources; however, they are generally coarse-grained and have only covered the United States. More recently, forecasting challenges have included dengue, chikingunya, and Ebola. With enhanced forecasting capabilities, models can begin tackling a wider range of pathogens, allowing for greater geographic coverage, and ultimately a broader breadth and better precision. These new abilities will be instrumental in allowing for more timely and effective risk assessment and better decision-making by governments and commercial entities before and during epidemics. Senior Scientist Ben Oppenheim on Global Risk: In 2018, the international community will focus on new initiatives that address the links between global threats. Many of today’s critical risks to human health and well-being are interrelated – from climate change to epidemic outbreaks, armed conflict and natural catastrophes. As a result, a single event has the potential to set off a chain of crises. The challenge is that the current systems that monitor, model, and manage each crisis are not integrated. Two factors will start to break down those silos First, improvements in data (both historical and real-time) and advances in modeling will allow for more sophisticated analyses that shed light on how threats interact—and where governments, multilateral organizations, and the private sector can best intervene to mitigate risk. And second, the organizations on the front-lines—NGOs, humanitarian organizations, and others—will increasingly recognize the need to build partnerships, to share data, expertise, and responsibility to respond to complex crises. Senior Product Manager Cristina Stefan on Insuring Risk: Operating within a low to negative yield environment for more than half a decade, insurers must rethink their growth strategy since they can no longer rely on the financial markets to fill in their margins. Metabiota predicts that in 2018, insurers will begin focusing more on speed and an increased appetite for risk to reach the needed returns. Speed is heavily driven by the insurtech space, where “digital” is the currency. A higher risk appetite is supported by innovation. Rethinking the historical exclusions (terrorism, pandemics) to be able to insure against them for the right price is one such example. Such risks are the so-called “risks without history” and they can support the creation of new markets for insurance.By leveraging big data, machine learning and artificial intelligence techniques, predictive modeling is the best way to combine technology, computing power and science to develop innovative insurance products. Head of Data Research Damien Joly on Climate Risk: Metabiota predicts that in 2018, the links between catastrophic weather events and public health will continue to lead to increased health risks across the world. In 2017, the effects of extreme weather events, such as the widespread monsoon flooding in South Asia or the successive hurricanes in the Caribbean, were particularly felt in countries with fragile or poor public health infrastructure and have led previously manageable, chronic health conditions to crisis situations. Examples include thousands of reported cases of waterborne disease in Bangladesh following the summer’s floods, and anecdotal reports of disruption of access to health care in Puerto Rico following Hurricane Maria. Global climate change and associated extreme weather events are linked, and so we predict this trend will continue into 2018, wherein the combination of fragile public health infrastructure and devastating weather events could lead to health crises. Metabiota’s innovative platform estimates epidemic preparedness and risk, including the frequency, severity, duration and cost of outbreaks. With a powerful combination of epidemic risk analytics, historical data, disease scenarios and insights from public health analysts and global epidemiologists, Metabiota’s platform allows insurers to better understand and underwrite risk. Metabiota’s approach provides the insurance industry, governments and organizations with the data and modeling tools needed to gauge the potential financial impact of a major health event so that risk can be managed in a more effective way. Link to press release available by clicking here. # # # MEDIA CONTACT: Aimee Eichelberger firstname.lastname@example.org
Dec 04, 2017
Pandemics: Risks, Impacts, and Mitigation: Disease Control Priorities, Third Addition, Volume 9, Chapter 17INTRODUCTION Pandemics are large-scale outbreaks of infectious disease that can greatly increase morbidity and mortality over a wide geographic area and cause significant economic, social, and political disruption. Evidence suggests that the likelihood of pandemics has increased over the past century because of increased global travel and integration, urbanization, changes in land use, and greater exploitation of the natural environment (Jones and others 2008; Morse 1995). These trends likely will continue and will intensify. Significant policy attention has focused on the need to identify and limit emerging outbreaks that might lead to pandemics and to expand and sustain investment to build preparedness and health capacity (Smolinsky, Hamburg, and Lederberg 2003). The international community has made progress toward preparing for and mitigating the impacts of pandemics. The 2003 severe acute respiratory syndrome (SARS) pandemic and growing concerns about the threat posed by avian influenza led many countries to devise pandemic plans (U.S. Department of Health and Human Services 2005). Delayed reporting of early SARS cases also led the World Health Assembly to update the International Health Regulations (IHR) to compel all World Health Organization member states to meet specific standards for detecting, reporting on, and responding to outbreaks (WHO 2005). The framework put into place by the updated IHR contributed to a more coordinated global response during the 2009 influenza pandemic (Katz 2009). International donors also have begun to invest in improving preparedness through refined standards and funding for building health capacity (Wolicki and others 2016). Read the entire chapter by clicking here.
Nov 14, 2017
Natural Disasters and Their Impact on Epidemic RiskHarvey. Irma. Maria. These recent catastrophic storms have wreaked havoc on our cities and in our minds. Each hurricane will require months and even years of rebuilding efforts, costing billions of dollars to communities, homeowners, businesses and governments, and likely will result in the most expensive hurricane season to-date. However, the ultimate damage and risk posed by these storms may reach beyond their immediate impacts on homes and infrastructure. Natural disasters, such as earthquakes, hurricanes, and floods, can promote environmental conditions and population characteristics favorable for infectious disease transmission leading to possible epidemics. While this threat (especially the risk of disease from exhumed bodies) has been often overemphasized by the media, leading to further panic and confusion, it remains a tremendous source of concern should opportune conditions arise. Read more at this link.
Nov 09, 2017
Insurance Post Analysis: Pandemic Bondshttps://www.postonline.co.uk/reinsurance/3336696/analysis-pandemic-bonds An excerpt from the article: New market The scale of this interest may help to encourage a new insurance market specifically for pandemic risk. This is certainly the view of Metabiota, a firm which analyses and models infectious disease data to help identify risk transfer and intervention opportunities. “We look at historical disease outbreak data for catastrophic but also more frequent events, to inform businesses and government about the risks associated with infectious diseases,” explains Nita Madhav, head of data science at Metabiota. “This analysis creates a really good picture of what could happen.” For example, this data can be used by life and health insurers to have a better understanding of the risk they already carry, but it could also help to shape products to help a government or business cover the cost of an epidemic. “A business could face supply chain disruption as a result of an epidemic,” says Cristina Stefan, product manager for insurance solutions at Metabiota. “It’s exciting that the World Bank has launched a product specifically for pandemics. It puts this risk on the map.”
Nov 07, 2017
The Ripple Effect of Climate Change on Epidemic RiskThe potential impacts of climate change have returned to headlines in recent weeks as scientists, activists, and policy makers try to understand the possible implications of a warming planet during one of the busiest hurricane seasons on record. While rising temperatures and sea levels are often considered, changing climate patterns can have vast implications for epidemic risk as well. http://www.contagionlive.com/news/the-ripple-effect-of-climate-change-on-epidemic-risk
Oct 16, 2017
Tackling Big Epidemics with Big ComputeAt Metabiota, we are fascinated by infectious diseases and the way they spread. Epidemics pose an immense risk to the entire globe; however they are notoriously challenging to forecast and monitor. Our team produces epidemic risk models for the insurance, commercial and government sectors to help address the challenge of quantifying this seemingly unquantifiable risk. Our end users are interested in knowing the probability of experiencing a certain level of human or financial loss due to infectious disease epidemics. To assess the likelihood of loss, we produce in silico (i.e., performed via computer simulation)models that project plausible disease transmission events across the entire globe. For example, our simulators depict the potential spread of pandemic flu, as well as outbreaks akin to the 2003 SARS and 2014 West Africa Ebola events. We probabilistically model where disease emerges, how quickly it spreads, how many people it infects, and the resulting rates of healthcare utilization and mortality. Our clients are often interested in the costs associated with these events, so we couple disease spread models with financial models that quantify the economic impact and insurance claims related to outbreaks. Altogether, we create an extremely large set of simulated events that allows for the estimation of potential financial and human losses caused by disease epidemics. To read more, visit this link.
Oct 12, 2017
Lehman Brothers and Fruit Bats: What the 2008 Financial Crisis Can Teach Us About Epidemic PreparednessFew catastrophes have more serious consequences than financial crises and epidemics. The 2008 financial crisis caused an estimated GDP loss of 5.5% across the developed world, while the 2014 West Africa Ebola epidemic killed over 10,000 people and reduced GDP in the three worst-hit countries by up to 21%. Financial crises and epidemics both start small, with the collapse of a single firm like Lehman Brothers or a bite from an infected fruit bat. But such events can quickly spread, sometimes reaching a global scale and costing billions of dollars. And worryingly, the risk of these crises may be growing – with more chances to spark and spread through increasingly connected economies and societies. Over the long term, another major financial crisis or epidemic is certain to occur, but our ability to predict or prevent the next crisis is limited. We do not know what will cause the next crisis, but we can reduce its impact through preparedness and response efforts, such as those implemented in the wake of the 2008 financial crisis and the 2014 West Africa Ebola epidemic. Although the financial crisis and the Ebola epidemic are two very different events, there are surprising similarities, and the financial crisis offers important insights into how to respond to public health crises. During the 2008 financial crisis, early, but delayed, injection of emergency capital from programs such as the Troubled Asset Relief Program (TARP) helped to mitigate the crisis. Through TARP, the US Treasury dispersed over $400M to buy toxic assets from large financial institutions to cleanse their balance sheets, encourage the resumption of lending, and stop the devaluation of otherwise healthy assets. This helped restore confidence by reassuring markets that all parties could pay their short-term debts, and firms would not fail unexpectedly. Equally important, much of this activity was globally coordinated across a number of institutions. To mitigate future financial crises, many central banks now have permanent lending facilities open to any bank that wishes to borrow in times of stress. The financial crisis also underscored the need for large financial institutions to develop better contingency plans and stress tests to identify and mitigate hidden risks in companies’ balance sheets. During the beginning of the financial crisis, many large financial institutions did not have sufficient plans to quickly respond to shocks in the financial system. Also, before 2007, most stress tests were performed by banks themselves. Now dozens of firms have plans and perform tests jointly with financial regulators, giving them a better chance of surviving a crisis. During the 2014 West Africa Ebola epidemic, the delayed injection of emergency capital and other resources slowed down efforts to mitigate the crisis. While the US and other countries ultimately allocated over $5 billion in emergency Ebola funding, resource-poor West African nations had greater difficulty raising funds. To mitigate future epidemics, several partners, including the World Bank, developed the Pandemic Emergency Financing Facility (PEF). PEF will provide funds and resources to health authorities early in an epidemic, enabling a rapid response that can help to contain the outbreak before it spreads. The Ebola epidemic put a fine point on why it’s critical to improve and stress test contingency plans for outbreak response. Standard public health protocols, such as isolating and providing clinical care to the sick and ensuring safe burials, ultimately contained the epidemic. However, the necessary protocols and facilities were not in place at the beginning of the epidemic. This was an even bigger problem because working relationships within the health system had not been systematically and rigorously stress tested. Due to the lack of facilities and preparation, decision-makers faced many challenges that slowed their reaction as they fought to develop plans during the heat of the crisis. In comparing the two types of crises, both share three important common lessons for preparedness and response. First, situational awareness is essential for early detection of a crisis and prompt intervention including the injection of emergency capital. Second, timely crisis response requires contingency plans to be developed well in advance of the next crisis. Protocols developed in the midst of a crisis are, by definition, improvisational and untested, and can delay response. Third, stress tests and response planning require coordination between governmental agencies and many different partners whether through major financial institutions or hospitals. Despite these common threads, public health authorities suffer from a lack of data and tools that are available to their financial counterparts. For example, unlike sovereign credit ratings for financial fitness, there are no current, widely-adopted metrics to measure pandemic preparedness – although the World Bank and the Joint External Evaluation are making some progress. Public health is also at a disadvantage because data are fragmentary and incomplete; even the location of hospitals is unknown to public health officials in many countries. The lack of data results in decreased situational awareness and creates problems in constructing objective triggers (such as those found in financial instruments) that could de-politicize epidemic response plans. Finally, unlike financial regulators, public health officials cannot unobtrusively (or computationally) stress-test clinical protocols in practice. In contrast to some previous public health emergencies, the 2014 West Africa epidemic was relatively mild. An event similar to the 1918 ‘Spanish’ influenza pandemic, were it to occur today, could cause a global 12.6% GDP loss and kill over 100 million people. We should not wait for a worse event to occur to start thinking about how to prepare our response. Preparedness for an event that can become global is only as strong as the weakest link in the system. Learning from financial crises can improve our preparedness and mitigate the costs for the next epidemic.
Sep 11, 2017
Epidemics Must Be Better UnderstoodIntelligent Insurer interview with Metabiota underscores the need for insurers and reinsurers to better understand epidemic risk. http://www.intelligentinsurer.com/news/epidemics-must-be-better-understood-13041
Sep 07, 2017