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Dengue fever, tuberculosis and H1N1 influenza are tough competitors to face in a fight. Each can infect large populations quickly, making public health responses difficult to target and implement in time.
Bacteria and viruses have sneezes, coughs and rapidly replicating DNA and RNA in their corner, but scientists who study these diseases also have a powerful tool at their fingertips. Using computers, they can model how infectious diseases spread and conduct virtual test runs of how different interventions might help.
To aid this effort, the National Institutes of Healths Models of Infectious Disease Agent Study (MIDAS) has added three new projects to its international research network. The network builds mathematical and computational models to study infectious disease spread and to help public health officials and policymakers prepare for and respond to outbreaks. The new grants together total nearly $9 million over the next five years.
"The investigators who are joining MIDAS bring a major focus to areas that are less represented in the current network," says Jim Anderson, MIDAS administrative director at NIH's National Institute of General Medical Sciences. "There will be an emphasis on vector-borne diseases as well as diseases primarily found in developing countries. Infectious disease is a global issue, and so must be the reach of MIDAS."
Sara Del Valle of Los Alamos National Laboratory will develop computer simulations that quantify key aspects of human behavior, an important but largely understudied variable when it comes to containing disease. For instance, how much do people avoid human contact during an H1N1 outbreak, how many people comply with public health guidelines and how useful is a face mask? Analyzing the answers to these questions from past outbreaks will help Del Valle develop models that mimic real human behavior more precisely. The models can also help identify the most effective behavioral changes to stop a disease from spreading.
Christopher Mores of Louisiana State University will model the spread of the mosquito-borne dengue virus, which infects 50 to 100 million people every year. There is no therapy and no vaccine, so stopping transmission is the best way to avoid dengue epidemics. Mores will use mathematical modeling to show how human organizationfrom houses and communities to nations and continentsand movement patterns affect the spread of dengue in Colombia, Puerto Rico and elsewhere. This will help inform how dengue and other vector-borne viruses might spread, and how they could be slowed, on the U.S. mainland.
Travis Porco of the University of California, San Francisco, will use computers to model tuberculosis epidemics in the Bay Area, where rates of the disease are three times the national average. His teams models will compute which pieces of informationfor example, age, symptoms and exposure to othersare useful to know about infected people in order to design effective interventions. Together with colleague Tim Leitman, Porco will also use computer models to simulate the spread of trachoma, a contagious bacterial eye disease that can cause blindness, in Ethiopias high-risk Amhara region. The scientists will model intervention strategies, such as different ways to distribute antibiotics, to see what works best.