A carefully chosen combination of public health measures, if implemented early, could stop the spread of an avian flu outbreak at its source, suggest two international teams of researchers in Nature (August 3) and Science (August 5).
The researchers used computer modeling to simulate what might happen if avian flu were to start passing efficiently between people in Southeast Asia. They found that antiviral treatment is a critical component of any multi-pronged approach.
The computer simulations are part of the Models of Infectious Disease Agent Study (MIDAS) research network funded by the National Institute of General Medical Sciences (NIGMS), a component of the National Institutes of Health. The overall goal is to develop computational models of disease spread that will aid the development of effective control strategies.
"These new models illustrate how the fundamental features of infectious disease spread can be captured to predict possible outcomes and the potential impact of interventions," said Jeremy M. Berg, Ph.D., director of NIGMS. "As these modeling approaches develop, they will offer policymakers and researchers powerful tools to use in strategic planning."
The H5N1 strain of the avian flu virus, found in birds throughout Southeast Asia, has infected a number of species, including domestic poultry, pigs, and people. Scientists fear that a genetic exchange between bird and human flu viruses or the accumulation of H5N1 mutations could soon make efficient person-to-person transmission possible.
The avian flu strain represents a particular threat because it is so deadly, said Neil M. Ferguson, D.Phil., a computational biologist at Imperial College in London and lead author of the Nature paper. "A large percentage of animals and people infected with this virus have died," he explained. "The consequences of an H5N1-based pandemic could be catastrophic."
With bird flu continuing to spread in Southeast Asia, the MIDAS network decided to model a hypothetical human outbreak of H5N1 in this region.
"The pressing questions are if and how we can contain an outbreak of avian flu at the source before it becomes a pandemic," said Ira M. Longini, Jr., Ph.D., a biostatistician at the Emory University Rollins School of Public Health in Atlanta and lead author of the Science paper.
To enhance reliability, both models were based on detailed data for Thailand, such as population densities, household sizes, age distribution, and distances traveled to work. The models also included information about the flu virus, such as the possible contagiousness of an infected person. Ferguson and Longini noted that actual contagiousness would not be known before an outbreak.
Although the models differed in the specific scenarios they simulated and the intervention strategies they tested, the general conclusions were similar and confirm current knowledge of how diseases spread: Preventing a pandemic would require a combination of carefully implemented public health measures introduced soon after the first cases appear.
The model presented in Nature simulated 85 million people living in Thailand and bordering regions of neighboring countries. It tested the effectiveness of giving courses of antiviral treatment to everyone, socially or geographically targeting who received them, and combining these drug-sparing approaches with other interventions, such as restricting travel.
The results suggest that an international stockpile of 3 million courses of flu antiviral drugs, combined with other interventions, could contain a pandemic. Treating infected individuals and everyone in their vicinity, along with closing schools and workplaces, could have more than a 90 percent chance of stopping the spread of a pandemic virus, according to the model. Ferguson emphasized that successful containment would depend on the early detection of the first cases and the rapid implementation of public health measures.
The model described in Science simulated 500,000 people living in rural Southeast Asia and relied on information about how those individuals move within their communities. Containment strategies included giving antiviral medication to people in the same social networks, vaccinating before an outbreak with a vaccine that is not well matched to the strain that emerges, quarantining the houses or neighborhoods of infected people, and combinations of these approaches.
Giving a low-efficacy vaccine to just half the population before the start of a pandemic would greatly enhance the success of other containment strategies, according to the model. Longini reported that a combination of targeted antiviral treatment and quarantine introduced two weeks after the first case had the potential to successfully contain disease spread, resulting in less than one case per 1,000 people.
Both models demonstrated that the need for additional public health measures greatly increased as the virus became more contagious. "Each measure can have a significant effect, but it can't contain spread on its own," said Ferguson, adding that targeted antiviral treatment was a crucial component of all combined strategies.
While the researchers said that implementing such a combination of approaches would be challenging and require a coordinated, international response, they offered this good news: The models show that containing an avian flu pandemic at its source is feasible.
Because computer models cannot capture all the complexities of real communities and real outbreaks, the MIDAS researchers will continue to refine their simulations and test different scenarios as new information becomes available. By developing a collection of models, they can compare and contrast different interventions, leading to more accurate predictions.
Other researchers involved in this work represent Johns Hopkins Bloomberg School of Public Health; the University of Hong Kong; the Ministry of Health in Thailand; and INSERM, the French National Institute of Health and Medical Research.
The above post is reprinted from materials provided by NIH/National Institute of General Medical Sciences. Note: Materials may be edited for content and length.
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