IBM scientists develop tools to predict dengue and malaria outbreaks
IBM researchers are using existing vector borne disease models from UCSF and Johns Hopkins to develop new dengue fever and malaria models shared through an open-source modeling application called the Spatio Temporal Epidemiological Modeler. By combining population analytics, powerful computing and algorithms of disease paths, the scientists plan to develop realistic and accessible models for the diseases.
"Public health officials can't afford to act on speculation during an epidemic," James Kaufman, the public health manager at IBM Research, said. "They need accurate and timely access to data to see what the potential spread of a disease might be for a given geographic region over a period of time... By understanding how and why these diseases spread, we can identify those regions most susceptible to emerging disease, inform public health, and allow them to focus on specific interventions in locations where they can have the greatest impact."
Using the model and data from the World Health Organization, IBM and Johns Hopkins demonstrated new analytic measures for the sensitivity of malaria incidence to changes in local climate factors. Knowing how climate affects malaria incidence could help scientists predict malaria outbreaks based on changes in local weather and the environment.
"There are a lot of tacit assumptions out there about how changes in climate will impact the distribution of diseases like malaria," Justin Lessler, an assistant professor with Johns Hopkins Bloomberg School of Public Health, said. "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. 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."
IBM Research and UCSF used STEM's ability to create models on top of models to provide a more realistic description of dengue fever's disease dynamics. Public health officials can use the model to more effectively predict the spread of dengue epidemics.
"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," Simone Bianco, an associate specialist with UC San Francisco's Bioengineering and Therapeutic Sciences Department. "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."
IBM will release STEM 2.0 on October 15 through the Eclipse Foundation.