Comportamiento humano puede ser clave para afrontar influenza porcina

Investigadores de la Universidad de Texas en Austin participarán en una subvención por 5 años de 3 millones de dólares provenientes de los National Institutes of Health (NIH), para combatir la influenza y otras enfermedades creando modelos que simulen la compleja interacción entre el comportamiento humano y la propagación de la enfermedad.

La subvención es parte del programa MIDAS ( Modelos para el Estudio de los Agentes de Enfermedades Infecciosas), una red nacional de investigadores que usan modelos matemáticos para ayudar a los funcionarios de la salud pública a predecir, intervenir y detener mejor las enfermedades contagiosas.

Los investigadores de Texas incluyen a Lauren Ancel Meyers, bióloga matemática en el Instituto de Ciencias Naturales y Paul Damien, matemático en la McCombs School of Business. Meyers está dirigiendo el proyecto conjuntamente con Allison Galvani de la Universidad de Yale.
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The group already has begun work this summer. They are trying to understand how to best use the national stockpile of flu antiviral medications such as Tamiflu and Relenza for the current H1N1 pandemic (swine flu). Between state and federal holdings, there are approximately 80 million courses of these drugs available.

“Who should be taking these antivirals? And when? What are the optimal choices to best save lives and prevent the spread of the swine flu?” Meyers said. “Our models can help answers those questions.”

The group has also launched a survey-based study to learn how perceptions and behavior evolve as information about the H1N1 pandemic spreads around the globe through the media.

Meyers said that as people change things like travel plans, they in turn change how the disease spreads.

Additionally, Damien said, “Take school closures as an example. It’s challenging to assess when and where to close schools. Based on what metric? Percent infected? Percent likely to be infected? Only by using mathematical methods can we best quantify these uncertainties. The MIDAS program rightly encourages the use of mathematics to make better, informed decisions, and we’re excited to be involved in such an effort.”

Thus, there are many factors that can affect the spread of diseases including population densities, closures of schools and public places, how drugs and vaccines are distributed, cost of treatments and people’s perceptions of vaccines.

“Our models will combine these factors and allow us to design public health policies that not only use resources effectively but also influence individual decision making to prevent the transmission of diseases like flu,” Meyers said.