"There are a lot of tacit assumptions out there about how changes in climate will impact the distribution of diseases like malaria. This work suggests that things probably are not so simple, a change that has a huge effect on malaria transmission in one place might not be as important somewhere else," said Justin Lessler, Johns Hopkins Bloomberg School of Public Health. "One of the nice things about open source projects like STEM is that now whoever wants to can download the model and start tweaking it, seeing if their own data or assumptions fundamentally change the results."
Previous models of dengue fever treated the mosquito vector indirectly, approximating transmission as a human-to-human contact process. IBM Research and UCSF used STEM's ability to build models on top of models and integrate them with location-specific climate data. This allowed to the inclusion of the vector population into existing models, providing a more realistic description of the disease dynamics, which can present public health officials more effective predictions of epidemics spread.
"It is important to recognize the synergistic effort of theoretical and computational scientists, disease experts and public health officials making a difference in how rapidly and effectively we fight infectious diseases," said Simone Bianco, UC San Francisco, Bioengineering and Therapeutic Sciences. "We have to be ready at the drop of a hat to parse through disparate data from global disease surveillance systems, conduct computationally intense research and transfer our knowledge to public health officials to help them visualize population health, detect outbreaks, develop new models, and evaluate the effectiveness of policies"
Available through the Eclipse Foundation, STEM is free and open to any scientist or researcher who chooses to build on and contribute to its library of models, computer code and denominator
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