“Fast” vs. “Slow” Outbreaks
An enduring source of frustration, wonder (and resignation) for those who deal with infectious diseases outbreaks is the vast difference in scale of response to “fast-moving” and “slow-moving” outbreaks. In “fast-moving” (think SARS, MERS, Ebola, novel influenza, etc.) outbreaks, the public perception of risk is far greater than the actual risk of the disease, and the response is more often than not an over-reaction that does more harm than the actual disease itself. I remember the 2003 SARS outbreak in Singapore vividly – “only” 238 cases (239 if you count the laboratory infection that occurred afterwards) and 33 deaths, but the impact on the economy (9.8% drop in GDP in Q2 2003, with subsequent spillover effects), healthcare and people was tremendous. The majority of the impact was not due directly to the virus itself, but to efforts aimed at containing the virus and – more importantly – to address the fears of the local people and international community. South Korea is now facing the same problem with MERS-CoV. There are 122 cases and 9 deaths as of this morning but the economic and social impact is already tremendous – approximately 45,000 tourist cancellations, multiple school closures and drop in cinema attendances just to start with.
How about “slow-moving” (think tuberculosis and antimicrobial resistance) outbreaks? The responses have in general been tepid and anaemic, and it is clear that in most countries, the outbreaks have done far more harm than efforts to contain them, relative to “fast-moving” outbreaks. When cases of New Delhi metallo-beta-lactamase-1 (NDM-1)-producing bacteria appeared in Singapore in 2010, the local health authorities believed that they did not constitute a public health threat and that the ministry was on top of the situation. There are now hundreds of patients infected or colonised by such bacteria each year in Singapore, with an escalating death count, but a coordinated response is just starting to take shape. As for tuberculosis, the wheels of change turn even more slowly. This is largely because of a “horizon effect” (also seen in climate change perception) and cognition biases – the perception of risk for “slow-moving” outbreaks is far lower than the actual risk.