Researchers presented a novel method for risk assessment based on a two-layer temporal network. The method has the ability to assess the risk of Ebola virus disease spreading. Simulation results from the two-layer temporal network confirmed that reduced physical contact with people while travelling along with other preventive measures decreases the risk of Ebola spreading.
The Nutritional Immunology and Molecular Medicine Laboratory (NIMML) has developed a high-resolution model of the gut immune system to help solve emerging and re-emerging infectious diseases and biodefense challenges.
Estimating the value of interventions to reduce antibiotic use requires predictions of future levels of antibiotic resistance. However, modeling the trajectory of antibiotic resistance, and how marginal changes in antibiotic consumption contribute to resistance, is complex.
Epidemic containment is a major concern when confronting large-scale infections in complex networks. Many studies have been devoted to analytically understand how to restructure the network to minimize the impact of major outbreaks of infections at large scale.
The basic reproduction number (R0), also called the basic reproduction ratio or rate or the basic reproductive rate, is an epidemiologic metric used to describe the contagiousness or transmissibility of infectious agents. R0 is affected by numerous biological, socio-behavioral, and environmental factors that govern pathogen transmission and, therefore, is usually estimated with various types of complex mathematical models, which make R0 easily misrepresented, misinterpreted, and misapplied.
A machine learning algorithm has been developed at The University of Glasgow that can predict viral reservoirs in the animal kingdom.
Researchers created a modeling framework that takes a zoonotic perspective on Ebola - the model considers the ecological dimensions that drive bat migration patterns.