NIH Researchers Investigate Spread Patterns of Influenza


Researchers at the National Institutes of Health (NIH) conclude that the regional spread of annual influenza epidemics throughout the United States is more closely connected with rates of movement of people to and from work than with geographical distance or air travels. They also found that epidemics spread faster between more populous locations.

"This valuable study highlights new approaches to using historical data sources and statistical analysis to create epidemiological models. These models not only help us understand the transmission of influenza but also could guide policy for its control" said Dr. Elias A. Zerhouni, NIH director.

The research results, published this week in Science Express, is based on 30 years of weekly data from the NationalCenter for Health Statistics on influenza-related mortality in different States since 1972.

"This study quantifies the spread of influenza based on three decades of data. We can correlate interstate spread with population size, commuting, and virus type. The key point about our paper is that we synthesize long-term data about disease incidence and human movements using models," said Dr. Mark Miller, associate director for research at the Fogarty International Center (FIC), part of NIH.

The investigators reached their conclusions by building a mathematical model of influenza spread in the United States based on the historical pattern of epidemics. The results suggest that when disease is imported into the United States in a well-connected state, one with many inflows and outflows of workers, for example, California, disease spreads much faster than if disease is imported in a less-connected state, for example, Wyoming. In observed epidemics, the initial focus of infection varies from year to year, but epidemics tend to emerge more often from California than other less populated states.

The model can simulate influenza pandemic spread, a situation where the greatest majority of the population is susceptible to a new virus. In this case, transcontinental spread could occur more quickly. Infection could reach all states within two to four weeks, instead of the five to seven weeks for annual epidemics, if seeded in a highly connected state.

Past research highlighted the role of children in the local spread of influenza, in particular, in schools and households. This study, by contrast, suggests that adults are responsible for the regional spread of influenza because they travel farther and more frequently.

Although the current modeling approach allowed researchers to reproduce the spread of annual influenza epidemics in the United States, there are caveats to extending the model to predict pandemic influenza. While it is impossible to predict how an entirely new strain of influenza would behave, comparison of the spread of influenza between pandemic and epidemic seasons based on historical data might shed some light on their differences. As the speed of influenza spread between states is affected by work-related population movements and transmissibility, interventions which limit inter-regional routine travel might slow epidemic spread.

The researchers did not study the effect of specific interventions, for example, school closure or travel restrictions to mitigate or delay the spread of influenza. Describing the mechanisms of local spread of influenza within cities or states is a key area for future work and would provide insight into which control strategies might be effective to control epidemic and pandemic influenza in particular, social distancing measures.

The study, supported by FIC, results from a collaboration among researchers at FIC, the Center for Infectious Diseases Dynamics (CIDD) at Pennsylvania State University and the National Institute of Allergy and Infectious Diseases (NIAID, part of NIH). Study authors are Cécile Viboud, PhD (FIC); Ottar N Bjørnstad, PhD (CIDD, FIC); David J Smith, PhD, (FIC); Mark Miller, MD, (FIC); Lone Simonsen, PhD, (NIAID); and Bryan T Grenfell, PhD (CIDD, FIC).

Source: John E. Fogarty International Center for Advanced Study in the Health Sciences (FIC)




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