The journal Clinical Infectious Diseases has published a large supplement on the challenges of responding to an influenza pandemic that is – sadly – mostly behind a pay wall. We do have excerpts and abstracts to draw on, and even with this limited access, can glean some salient points.
The entire issue is called:
And we get a pretty good overview of the rationale behind these pandemic modeling exercises in:
- Martin I. Meltzer, Manoj Gambhir, Charisma Y. Atkins, and David L. Swerdlow
- Clin Infect Dis. (2015) 60 (suppl 1): S1-S8 doi:10.1093/cid/civ088
An outbreak of human infections with an avian influenza A(H7N9) virus was first reported in eastern China by the World Health Organization on 1 April 2013 . This novel influenza virus was fatal in approximately one-third of the 135 confirmed cases detected in the 4 months following its initial identification , and limited human-to-human H7N9 virus transmission could not be excluded in some Chinese clusters of cases [3, 4]. There was, and still is, the possibility that the virus would mutate to the point where there would be sustained human-to-human transmission. Given that most of the human population has no prior immunity (either due to natural challenge or vaccine induced), such a strain presents the danger of starting an influenza pandemic.
In response to such a threat, the Joint Modeling Unit at the Centers for Disease Control and Prevention (CDC) was asked to conduct a rapid assessment of both the potential burden of unmitigated disease and the possible impacts of different mitigation measures. We were tasked to evaluate the 6 following interventions: invasive mechanical ventilators, influenza antiviral drugs for treatment (but not large-scale prophylaxis), influenza vaccines, respiratory protective devices for healthcare workers and surgical face masks for patients, school closings to reduce transmission, and airport-based screening to identify those ill with novel influenza virus entering the United States. This supplement presents reports on the methods and estimates for the first 5 listed interventions, and in this introduction we outline the general approach and standardized epidemiological assumptions used in all the articles.
First some links to the accompanying pandemic modeling studies, after which I’ll return with a bit more.
Estimating the Potential Effects of a Vaccine Program Against an Emerging Influenza Pandemic--United States Clinical Infectious Diseases (2015) 60 (suppl_1): S20-S29
Potential Demand for Respirators and Surgical Masks During a Hypothetical Influenza Pandemic in the United States Clinical Infectious Diseases (2015) 60 (suppl_1): S42-S51
Estimates of the Demand for Mechanical Ventilation in the United States During an Influenza Pandemic Clinical Infectious Diseases (2015) 60 (suppl_1): S52-S57
Modeling the Effect of School Closures in a Pandemic Scenario: Exploring Two Different Contact Matrices Clinical Infectious Diseases (2015) 60 (suppl_1): S58-S63
Estimating the United States Demand for Influenza Antivirals and the Effect on Severe Influenza Disease During a Potential Pandemic Clinical Infectious Diseases (2015) 60 (suppl_1): S30-S41
The late George E. P. Box (18 October 1919 – 28 March 2013) - Professor Emeritus of Statistics at the University of Wisconsin - is often credited with coining the familiar adage:
“All models are wrong, but some models are useful.”
While imperfect, we use computer models every day to try to mathematically simulate real-life events; everything from highway traffic flow to weather forecasting. Rare events - like pandemics - with a limited data-set of information are particularly difficult to model.
Over the years we’ve discussed the different pandemic assumptions adopted by various state and federal agencies, and they have been – quite frankly – all over the map.
While the most severe pandemic in modern history (1918) produced a 2.5% mortality rate, and killed approximately 675,000 Americans, no one really knows what the next severe pandemic will bring. So we’ve seen a lot of models.
Two years ago, the 2009 Northern Command Pandemic Plan (see SciAm story Pandemic Flu Plan Predicts 30% of U.S. Could Fall Ill) was declassified with its estimates that during a moderately severe pandemic 30% of the population could fall ill, 3 million could require hospitalization, and 2 million Americans could die.
In 2008 the HHS outlined their vision of the likely impact in the United States of a severe pandemic (see A Tale Of Two Scenarios). As you’ll see, the numbers of hospitalizations anticipated during a severe pandemic is quite a bit higher than the Northcom plan.
The HHS defined a severe pandemic as:
- An attack rate of 30% (90 million Americans sickened)
- 50% (45 million) requiring outpatient medical care
- 11% (9.9 million) requiring hospitalization
- 745,000 requiring mechanical ventilation
- 1.9 million deaths (2.1% fatality ratio)
In this round of modeling, in Estimating the Potential Effects of a Vaccine Program Against an Emerging Influenza Pandemic—United States, the authors elected to go with two (considerably less severe) scenarios:
- 20% Attack Rate, a .5% hospitalization rate, and a case fatality rate of .08%
- 30% Attack Rate, a 4.2% hospitalization rate, and a case fatality rate of .53%
Scenario #1 would equate to a Category 1 pandemic using the 2008 HHS guidelines (see graphic at top of blog), and scenario #2 would reach Category 3 intensity. Using that standard, the 1918 pandemic was a Category 5.
While a more severe pandemic is certainly possible, the experience of the last 100 years suggests that mild to moderate pandemics are more common, and that truly severe pandemics are outlier events.
And based on even the moderately-severe pandemic scenarios presented in these papers, the challenges of procuring and distributing adequate supplies of vaccines, antivirals, ventilators, and masks would be considerable.
One of the topics we’ve discussed often in the past has been the limited supply of PPEs (Personal Protective Equipment) like N95 masks, and the impact running out of these would have on the healthcare delivery system during a pandemic (see NIOSH: Options To Maximize The Supply of Respirators During A Pandemic).
We’ve seen estimates that many regions would exhaust their supplies of PPEs within 2 or 3 weeks.
Our Strategic National Stockpile has hundreds of millions of N95 and surgical masks in reserve, but the numbers needed as envisioned by the Potential Demand for Respirators and Surgical Masks During a Hypothetical Influenza Pandemic in the United States run into the billions.
From their Results and Conclusions:
Assuming that 20% to 30% of the population would become ill, 1.7 to 3.5 billion respirators would be needed in the base case scenario, 2.6 to 4.3 billion in the intermediate demand scenario, and up to 7.3 billion in the maximum demand scenario (for all scenarios, between 0.1 and 0.4 billion surgical masks would be required for patients). For pandemics with a lower attack rate and fewer cases (eg, 2009-like pandemic), the number of respirators needed would be higher because the pandemic would have longer duration. Providing these numbers of respirators and surgical masks represents a logistic challenge for US public health agencies. Public health officials must urgently consider alternative use strategies for respirators and surgical masks during a pandemic that may vary from current practices.
The take away from all of this is that we don’t have to see a Category 5, 1918-style pandemic to severely test our public health delivery system.
Even a moderately-severe pandemic would provide more than enough challenges.
And until we can reasonably meet those – there’s probably not much to be gained by modeling more extreme worst-case scenarios.