WASHINGTON - 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?

DEATH RATES

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.