Novel model of SIR-Network predicts dengue epidemics
The authors -- Daniel Coombs, Lucas Stolerman and Stefanella Boatto -- used mathematics and medical research to show how the virus will spread and affect health care.
"The SIR-Network model can be used to predict whether local interventions like cleaning up standing water in containers in one or two neighborhoods could affect the prevalence of Dengue across the city," Coombs said. "We give formulae that describe whether an epidemic is possible, in terms of human travel patterns among neighborhoods, mosquito populations and biting rates in each neighborhood."
This new method may help scientists predict and therefore prevent diseases as they spread and cause epidemics. This could change the medical industry from every angle, from the pharmaceutical industry to the health management field.
"We feel that our results highlight the need for countermeasures before the peak of an epidemic, and also point to the importance of central neighborhoods as hubs of Dengue transmission," Boatto said. The writers used a specific example in Brazil to demonstrate how their mathematical works to help the health industry.
"In the case of Rio de Janeiro, for example, there is a major influx of tourists every year for Carnival, but the date of Carnival, the weather patterns in the preceding months, and the numbers of tourists that show up vary from year to year," Stolerman said. "The benefit of simple models is that we can average out some of this complexity and try to understand the big picture...our model will be useful as a conceptual tool for modeling the impact of interventions aiming to control Dengue in urban areas."