Funded by the National Institute of General Medical Sciences at the NIH, MIDAS is a collaborative network of research scientists who use computational, statistical, and mathematical models to understand infectious disease dynamics and thereby assist the nation to prepare for, detect, and respond to infectious disease threats. Please explore our website to learn more.
MIDAS uses ABM to examine if population structure is sufficient to generate area-level inequalities in influenza rates
In New Haven County (NHC), CT, influenza hospitalization rates have been shown to increase with census tract poverty in multiple influenza seasons. In what is, to our knowledge, the first use of simulation models to examine the causes of differential poverty-related influenza rates, researchers in the Public Health Dynamics Laboratory used agent-based models with a census-informed, realistic representation of household size, age-structure, population density in NHC census tracts, and contact rates in workplaces, schools, households, and neighborhoods, and measured poverty-related differential influenza attack rates over the course of an epidemic. Simulated attack rates among adults increased with census tract poverty level. The study detected a steeper, earlier influenza rate increase in high-poverty census tracts, a finding that was corroborated with a temporal analysis of NHC surveillance data during the 2009 H1N1 pandemic. The ratio of the simulated adult AR in the highest- to lowest-poverty tracts was 33% of the ratio observed in surveillance data, leaving 67% of the inequality to be explained by other factors. Future models should quantify the capacity of individual behavioral and biological factors to generate influenza inequalities thus allowing us to prioritize interventions aimed at factors with the greatest explanatory power.
Read the paper at: http://www.biomedcentral.com/1471-2458/15/947
MIDAS’ David Galloway of the University of Pittsburgh presents Graph Databases featuring Neo4j
When: Wednesday, September 16 at 2:00PM Eastern time
What: Dave Galloway will discuss what a graph database is and how it differs from a relational database or a document store database. He will show some examples of graph data and some even more specific examples of it pertaining to infectious disease. He will use Neo4j to show a specific example of a graph database and will use their query language, Cypher, to utilize the database. This discussion is part of an ongoing series of talks targeted toward and given by members of the MISSION 2.0 (MIDAS Software Sharing and Information Outreach Network) group.
MIDAS research supports childhood vaccinations to protect the entire population
Dr. Mark S. Roberts, MIDAS researcher, comments on individual rights and the greater good in regards to vaccination. Read More