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Society for Industrial and Applied Mathematics


New SIR-Network Model helps predict dengue fever epidemic in urban areas

A new mathematical model helps researchers predict the spread of dengue fever in urban areas by analyzing neighborhood conditions and human travel patterns. The SIR-Network model reveals that central neighborhoods are crucial hubs for transmission, emphasizing the need for countermeasures before epidemics peak.

SourceSociety for Industrial and Applied Mathematics·JournalSIAM Journal on Applied Mathematics·DateDec 23, 2015

Where is that spacecraft?

The Gauss von Mises (GVM) distribution offers improved predictive capabilities for tracking infrequently-observed space objects. This new approach allows for more accurate prediction of satellite and debris locations, enabling better resource allocation and detection of potential collisions.

SourceSociety for Industrial and Applied Mathematics·JournalSIAM/ASA Journal on Uncertainty Quantification·DateSep 22, 2014

Using math to analyze movement of cells, organisms, and disease

Mathematicians develop models to describe cell migration and tumor invasion, as well as dispersal patterns in species. The studies reveal the existence and uniqueness of traveling waves in malignant tumor invasion and show how fitness-dependent dispersal conveys advantages towards ideal free distribution in populations.

SourceSociety for Industrial and Applied Mathematics·JournalSIAM Journal on Mathematical Analysis·DateJun 25, 2014

How does innovation take hold in a community? Math modeling can provide clues

A mathematical model analyzes the spread of energy-efficient technologies in a community, highlighting the role of social networks and personal factors. The study provides tools for local authorities to assess the success of intervention strategies and reduce household energy bills and carbon emissions.

SourceSociety for Industrial and Applied Mathematics·JournalSIAM Journal on Applied Dynamical Systems·DateMar 27, 2013

Math helps detect gang-related crime and better allocate police resources

Researchers used police department records to determine gang memberships based on social and geographical information, identifying hotspots and clusters of individuals with similar behavior. The study showed that incorporating both social and geographic distance in models of gang violence provides more comprehensive analysis.

SourceSociety for Industrial and Applied Mathematics·JournalSIAM Journal on Applied Mathematics·DateFeb 14, 2013