Swine flu death rate estimates 'flawed'

Swine flu death rate estimates 'flawed'
 18:04 14 July 2009 by Andy Coghlan New Scientist
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Estimates of the proportion of people who will die if infected with swine flu are flawed, say UK researchers.
At present, the estimate of the death rate in the UK and the US is 0.5 per cent, meaning that about five people die for every 1000 people infected. Accurate estimates are needed so that health authorities can best target treatment and vaccination strategies.
But a new analysis suggests three main reasons why current estimates may be wide of the mark.
Hidden infections
The first and main source of uncertainty is the unknown number of infected people, who recover at home without notifying their doctors that they are ill, or receiving a diagnosis.
So although doctors know how many patients are dying of swine flu in hospitals, they don't know what proportion of all cases are life threatening.
But they need both figures to work out the "case-fatality ratio" – calculated by dividing the number of fatal cases by the total number of cases.
"We don't know the denominator," says Azra Ghani, head of a team at Imperial College London tracking development of the epidemic in the UK.
"For that reason, dividing the number of deaths by the number of cases may be flawed," says Ghani's colleague Tini Garske, the lead author of the study exposing gaps in the data.
Delayed surge
A second source of uncertainty is the possibility that deaths from swine flu are being attributed falsely to other causes of death, such as heart attacks or pneumonia from other causes. This would lead to underestimates of the death rate.
Finally, statistics are distorted by a time-lag between the point at which someone is infected and the time they die. This could lead to an apparent surge in deaths which may falsely be interpreted as the virus becoming more deadly through mutation.
Taken together, these factors make it difficult to rely on existing data sources to accurately calculate the death rate or to predict the course of the epidemic.