Computer Models Help Nations Prepare for
Pandemic
Simulations of response in U.S., Britain based on travel,
population data
By Tim Parsons School of Public Health
Using complex computer models, a team of researchers
analyzed how effective travel restrictions, school
closures, drug distribution and other public health
strategies would be in slowing the spread of a pandemic flu
outbreak. The analysis, conducted by researchers at the
Johns Hopkins Bloomberg
School of Public Health, Imperial College London and
RTI International, simulated a response to a pandemic flu
outbreak in the United States and Great Britain using
detailed population data and travel patterns. It is
published in the April 26 online edition of Nature.
"The modeling shows that there is no single magic
bullet which can control a flu pandemic. However, a
combination of interventions could be highly effective at
reducing transmission, potentially saving lives," said Neil
M. Ferguson, lead author of the study and professor at
Imperial College London.
According to the simulation, the pandemic would peak
about 60 to 80 days after the first case is reported.
Closing off the borders and restricting travel within the
country were unlikely to delay the spread of the flu for
more than two to three weeks, unless these measures were
more than 99 percent effective. Nationwide school closures
could reduce the peak infection rate by 40 percent but
would do little to reduce the overall number of people
infected. However, slowing the peak rate could ease the
burden on the health care system, according to the
researchers. Quarantining sick individuals at home, if
feasible, was also found to have a significant impact on
the number of people infected.
Combining measures could reduce the number of cases
further. Antiviral drug distribution, in conjunction with
school closures, could reduce the number of cases by 50
percent if the medications were used to treat those who
live with sick individuals as well as those already ill.
The researchers said more widespread preventive drug
treatment could reduce infection rates by 75 percent, but
such treatment would be difficult to accomplish.
To have an impact on infection rates, vaccines would
need to be available within two months of an outbreak,
which is much faster than current vaccine manufacturing
technology allows. However, a stockpile of vaccine for at
least 20 percent of the population could reduce the number
of infections by one-third, even if the vaccine would
provide only limited immunity. Vaccinating children first,
since they are the biggest spreaders of influenza, had the
greatest impact on transmission rates, while vaccinating
seniors first had the least.
"Computer models are becoming powerful tools for
exploring the potential outcomes of interventions to
mitigate the spread of pandemic flu," said Jeremy M. Berg,
director of the National Institute of General Medical
Sciences, which partially funded the study through its
Models of Infectious Disease Agent Study, or MIDAS. "The
results of simulations using these models can be useful for
planning ways to prepare for and respond to a future
outbreak," he said.
Donald S. Burke, professor in the Bloomberg School's
Department of
International Health and director of the school's MIDAS
program, said, "By using simulated epidemics 'in silicon,'
we think through and evaluate response strategies before
the event happens."
Johns Hopkins authors on the study, "Strategies for
Mitigating an Influenza Pandemic," are Derek A.T. Cummings
and Burke.
Funding was provided by the National Institute of
General Medical Sciences MIDAS Program, the Medical
Research Council, the Royal Society and the Howard Hughes
Medical Institute.
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