Newly developed Susceptible- Infected- Recovered (SIR)-Network Model can help predict the dengue fever epidemic in the urban areas.
Mathematics is often implemented in healthcare and medical research. From health management to the bio-pharmaceutical fields, math modeling can be used to predict the spread of diseases, how to prevent epidemics and so much more.
The article introduces a new mathematical model which offers a simplified approach to studying the spread of the infectious virus, Dengue fever, in urban areas, specifically breaking down the epidemic dynamics across a city and its varying neighborhoods and populations.
The model is important for studying how varying neighborhood conditions affect the spread of Dengue fever and how to contain it. For example, some neighborhoods have standing water allowing large mosquito populations to develop. Since mosquitoes fly, on average, only a few hundred meters from their birthplace, a human infected with the disease who commutes long distances could spread the disease. This new SIR-Network model will allow researchers to understand how these conditions affect epidemic dynamics across an entire city and beyond.
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, says coauthor Daniel Coombs. “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.”
The SIR-Network Model offers researchers a simplified and clearer image of the bigger picture of Dengue fever, and has the potential to help quell the disease (as well as be applied to other disease spread issues), saving lives, time and money.
The study appears in the SIAM Journal on Applied Mathematics.