Epidemiologists are disease detectives. The
investigative insights of a forensic epidemiologist are exemplified by Sherlock
Holmes, whose creator, Arthur Conan Doyle, qualified as a medical doctor in
Edinburgh. With limited information, some of which may be dubious and
misleading, epidemiologists search for hidden clues as to the cause of a
disease and its manner of population spread and use statistical modeling techniques
to estimate the degree of disease contagion and the number of cases of
Prof. Neil Ferguson heads the World Health Organization (WHO) Collaborating Center for Infectious Disease Modeling at Imperial College London. His search for scientific understanding using sparse observational data dates back to his theoretical physics PhD at Oxford. Like others trained in theoretical physics, Prof. Ferguson is not shy in making mathematical forecasts that may be at odds with partial data of suspect reliability. Misreporting blighted the Chinese response to the 2002 SARS outbreak.
When the Middle East Respiratory Syndrome (MERS) was first identified as a coronavirus in 2012, the case fatality rate was very high at 35 percent; but thankfully there was very low human-to-human transmission. Such transmission happened in healthcare settings, or to a much lesser extent in households where people caring for an infected person had close contact.
Camels were identified as a “reservoir host” for MERS, with infection primarily caused through direct contact with camel fluids. As evidence of very low human-to-human transmission, there were no MERS cases reported in either the 2012 or 2013 Hajj pilgrimage to Mecca, although an Indonesian couple may have caught MERS in the 2014 Hajj.
In China, there is an even larger annual migration tied to the lunar calendar – as the lunar New Year starts on Saturday, January 25. This is normally a time of happiness and celebration during family reunions. This year, there will be fear and foreboding over the new coronavirus, which emerged in December from a seafood market in Wuhan, Central China. On January 21, Chinese health authorities confirmed human-to-human transmission of the coronavirus. Fortunately, the case fatality rate seems to be quite low, just a few percent.
In this the centennial year of the great 1918 pandemic, I was invited to speak at a special symposium on emerging infectious diseases at the renowned Pasteur Institute in Paris. One presentation that was both fascinating and alarming was on viruses in fish. I haven’t eaten raw fish since. When I heard that, in mid-December, a new form of pneumonia had struck a seafood market in Wuhan, central China, it seemed like a new fish disease affecting humans might have finally emerged. It turns out that the seafood market at the center of the outbreak also sold live animals and meat from wildlife such as snakes and marmots, and a wildlife primary infection source is most probable.
The recent allegations against General Electric (GE) read like a financial thriller: Bernie Madoff whistle-blower teams up with anonymous hedge fund to expose the alleged financial misdeeds of one of the most recognizable brands in American history.
But most people’s interest in this story ends abruptly when they hear about the crux of the allegations, which can be summarized in eight words: “… inadequate loss reserves for long term care (re)insurance.” This topic is esoteric at best, and sleep-inducing at worst. It’s impossible to spin into media clickbait. And it’s clear that media is struggling to describe exactly what Harry Markopolos, the whistle-blower, is alleging in his 175 page report.
Assessing the risks faced by the city of Goma in the Democratic Republic of Congo (DRC) would go well beyond the norms of the insurance industry. On January 17, 2002, a large part of the city center was destroyed by an eruption of Mount Nyiragongo, about 20 kilometers (12.4 miles) to the north. Volcano hazard is not a significant risk factor for many towns and cities – and nor is Ebola. Goma is exceptional in being at risk from both.
Outbreaks of Ebola have occurred in the DRC sporadically in 1976, 1994, 2003, 2007 and 2012. The most recent outbreak started on August 1, 2018, and even with the infection of 2,500 and the deaths of more than 1,700, the Ebola virus is still not contained. Endemic hostilities in the DRC make it hard for health organizations to track contacts of those infected, and to operate treatment centers without fear of military attack. Health workers expose themselves daily to lethal infection – and should not be exposed also to armed assault. But they are – two health workers were killed in mid-July.
It has been reported that the current Ebola Virus Disease (EVD) epidemic, which has caused over 1,300 confirmed deaths in the Democratic Republic of the Congo (DRC) since its onset in August 2018, has now also caused at least one confirmed death in neighbouring Uganda.
The number of confirmed deaths has been steadily increasing since the onset of the outbreak, though since March there has been a notable increase in the reported number of deaths per week. A recent trend shows a slight decrease from the peak, with the current situation report recording 50 deaths among confirmed EVD cases in the past week (Figure 1 below).
On March 13, 2019, the U.K. Chancellor of the Exchequer, Philip Hammond, warned in the House of Commons during his Spring Statement, that a “… cloud of uncertainty was hanging over the U.K. economy.” Reminiscing of a sunnier time for the U.K. economy, in the Budget speech in March 2000, Gordon Brown announced a substantial increase in government spending on healthcare. The Chancellor’s ambitious plan was that health spending would rise by more than a third in real terms over a five-year period, by 6.1 percent per year over and above inflation.
To inform and support this program, he commissioned a review of the long-term trends affecting the U.K. National Health Service (NHS). Based on wide-ranging academic research, this review, which was published in April 2002, had a long-term time horizon of twenty years, extending to 2022. The author of this review was Sir Derek Wanless, a professional banker, who was also a highly gifted mathematician – an important attribute for reaching robust quantitative conclusions on long-term NHS funding.
Around 100 million people watched this year’s Super Bowl on February 3, which was a low-scoring game where the much faster play of the Patriots’ quarterback, Tom Brady, compared with his opposite number LA Rams’ Jared Goff, was a decisive factor. Few in the television audience would have known that the veteran quarterback had special cognitive training to enable him to perform so well according to the mantra: think slow, play slow.
The worst outbreak of Ebola in the DRC (Democratic Republic of Congo), Africa’s second largest country by area, with a population of over 77 million, has already claimed several hundred lives, and there have been more than three hundred and fifty cases.
Many of the Ebola cases have been in Beni (pop. ~230,000), a major city in North Kivu province, close to the Ugandan border. DRC is a failing state, where the government regime is weak, and cannot prevent militias from pillaging DRC’s abundant mineral resources. One such militia is the ADF (Allied Democratic Forces), which was formed in neighboring Uganda in the 1990s, and operates in the mineral-rich border area in North Kivu province.
The geography of the disease spread is intriguing for epidemiologists. Officially declared on August 1, 2018, this is the tenth outbreak of Ebola in DRC since 1976, but this is the first time that Ebola has affected the far northeast of this vast Central African nation. A crucial risk factor hampering the control of Ebola in this region is the conflict over mineral resources. This has limited the number of inhabitants who can be vaccinated, and restricted the access of health response teams, who are exposed to personal danger such as physical assault and kidnapping. Indeed, insecurity was a factor delaying the alert to the actual start of the outbreak, which was several months before the official declaration.
RMS has just completed a two-year exercise documenting all the different types of insurance that are available in the market and a classification system for all the assets that they protect. This is published as a data definitions document v1.0 as a standardized schema for insurance companies to have a consistent method of evaluating their exposure.
This project, in collaboration with research partners Centre for Risk Studies at University of Cambridge, and a steering committee of RMS clients, involved extensive interviews with 130 industry specialists and consultation with 38 insurance, analyst, and modeling organizations.
The project will enable insurance companies to monitor and report their exposure across many different classes of insurance, which globally today covers an estimated US$554 trillion of total insured value. The data standard will improve interchanges of data between market players to refine risk transfer to reinsurers and other risk partners, reporting to regulators, and exchanging information for risk co-share, delegated authority, and bordereau activities.