New SIR-model could offer epidemic predictions for dengue fever

The A. aegypti mosquito, a carrier of dengue fever.
The A. aegypti mosquito, a carrier of dengue fever. | Courtesy of NIAID
A study released this week in the Society for Industrial and Applied Mathematics’ (SIAM) Journal on Applied Mathematics includes a model that could predict outbreaks of dengue fever in populated areas.

This model is a susceptible, infected and recovered (SIR) network. In order to be able to gather data about the diseases spread, it is able to account for local activity and interventions alike. The study indicates that the model is also able to breakdown epidemic dynamics in cities and neighborhoods and how variances in these locations are reflected in disease spread data.

In the study, researchers utilized past dengue fever data from outbreaks occurring between 2007 and 2008 and as recently as 2014 in Rio de Janeiro. With this data, study authors predicted a six to eight-week timeframe between transmission and case peaks and that the areas that are considered city centers provide an important part of the infection process.

The study argues that this model offers a large scope of dengue patterns and could potentially help public health officials in epidemiological work.

"The benefit of simple models is that we can average out some of this complexity and try to understand the big picture," study coauthor Lucas Stolerman said. "Our model will be useful as a conceptual tool for modeling the impact of interventions aiming to control dengue in urban areas." 

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Society for Industrial and Applied Mathematics 3600 Market St Philadelphia, PA - 19104

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