As you can see from the post I published 15 minutes ago the story I discuss here has grown more legs than a centipede. Things are heating up.
I think the public is generally aware that testing for swine cases has lagged so far behind the actual number that it's been impossible to get a clear picture of how this pandemic is acting. But the data issue is much graver than generally known. On June 3, days before WHO officially declared a pandemic, the New Scientist warned that Europe needed better testing for swine flu and that the region was facing an "invisible pandemic." They were right on both counts.
Because an epidemic will eventually overwhelm data-collection resources it is vital to collect as much data as early as possible during an outbreak. This approach wasn't taken. Many public health departments, under guidance from their federal health agencies, such as the CDC, simply threw up their hands within about two weeks of the outbreak's announcement.
The consequence? In country after country, inadequate tracking of swine flu cases has been one of the greatest problems that hospitals, doctors, and public health agencies have faced while trying to muster an appropriate response to the outbreak.
Another problem is that mathematical models that produce estimates on the number of cases depend on raw data for their accuracy. If the data are wildly off, the old computer programmer's dictum, 'Garbage in, garbage out' applies to the models.
The problem is made far worse when bad data are fed into a model that was inadequately designed, as this illuminating 2007 report (written for the layperson) on mathematical models for pandemics indicates.(1)
I suspect, I hope, the model given much discussion in the report, which was designed by MIT professor Richard Larson and his colleagues, has had a beneficial influence on pandemic modeling during the past two years.
Yet even the best-designed model is up against the limitations of data that reflect inadequate testing in the earliest stage of an epidemic. Now Reuters' Maggie Fox, who has been one of the stalwarts of swine flu reporting since the early days of the outbreak, has written an article that tackles the issue head on.
How bad is swine flu? Without numbers, who knows?1) Medical News Today: Engineer Who Survived Pandemic Of '68 Creates Model To Track Outbreak; 02 June 2007
Tue Jul 14, 2009 7:04pm EDT
By Maggie Fox, Health and Science Editor
WASHINGTON (Reuters) - Many people are confused about just how many patients have been infected with the new H1N1 flu, which in turn makes it hard to tell how bad the pandemic is, British researchers said on Tuesday.
But better methods of measuring the swine flu toll in real-time could help reduce some of that confusion, according to the team at Imperial College London.
And without this information, they said, governments are operating in the dark when assessing what their response should be.
"If you don't test people, you don't know how many people are out there who have it," Dr. Tini Garske, an expert in disease modeling who led the study, said in a telephone interview. "The number of confirmed cases doesn't tell you a lot."
The World Health Organization has confirmed 94,512 cases globally and 429 deaths from the new H1N1 swine flu, which was declared a pandemic last month.
But these numbers represent only a fraction of the real cases -- the U.S. Centers for Disease Control and Prevention says at least a million people have been infected and the virus is spreading out of control.
Most countries are now only testing a sample of patients, and many people who become infected are not ill enough to even seek medical attention, let alone get tested.
Diagnostic kits for H1N1 are expensive, and most governments save them for when they are really needed.
But if no one knows just how many people are infected overall, with serious disease and with mild disease, how can anyone say how severe the pandemic is?
Writing in the British Medical Journal, Garske and colleagues said current case fatality ratios -- the number of deaths from swine flu divided by the total number of cases -- is only around 0.5 percent. This is similar to the death rate from seasonal influenza, which kills anywhere between 250,000 and 500,000 people globally each year.
But Garske noted this varies greatly from country to country. Unlike seasonal flu, influenza H1N1 is causing severe illness in previously healthy young adults and children.
"Accurately predicting the severity of this swine flu pandemic is a very tricky business, and our research shows that this can only be achieved if data is collected according to well-designed study protocols and analyzed in a more sophisticated way than is frequently being performed at present," Garske said.
"If we fail to get an accurate prediction of severity, we will not be providing healthcare planners, doctors and nurses, with the information that they need to ensure they are best prepared to fight the pandemic as we head into the flu season this autumn."
Garske's team outlined ways to improve estimates, including using individual towns as examples.
Watching families can also help give researchers an idea of how the flu spreads. If one sick family member infects one other family member, or two, or three, that number can be used to estimate the infection rate in places where cases are not being painstakingly diagnosed and recorded, she said.
"You don't need to know about everybody, but you need some subpopulations," she said.