Modeling and Analytics Tools

The Midwest Analytics and Disease Modeling Center is developing and testing multiple modeling and analytic tools to support decision-making during public health emergencies. Here are some of the tools in development:

MN Social Contact Survey
A social contact survey measures how many people a person interacts with in a day, which is a key component to modeling the spread of an infectious disease. Building on past social contact survey work, we will field four rounds of a Minnesota-focused contact survey, staggered to capture seasonal changes in person-to-person contact patterns. The survey will capture differences in contact patterns by age, gender, race and ethnicity, and rural vs urban location. The survey will also include questions about individual attitudes towards potential protective measures that may be employed in an infectious disease pandemic, as well as barriers and facilitators to adopting these measures.

Decision-Analytic Infectious Disease Modeling Platform
We are developing a geographically- and demographically-stratified infectious disease modeling platform parameterized and calibrated for Minnesota that will be rapidly adaptable to a variety of pathogen types and can inform public health and health system decision-making and communication during an infectious disease emergency. The platform will allow decision makers to compare the potential impacts of a variety of policy alternatives on population health outcomes.

Geospatial Health Service Disparity Identification Tool
We are developing an electronic health records (EHR)-based geospatial visualization and analysis tool to rapidly identify disparities in provision, access, and uptake of key health and public health interventions, and to provide decision-makers with the anticipated impact of approaches to address disparities. An interactive map will highlight regional outliers that may warrant intervention, while a decision-support component will calculate the expected impact of different intervention choices.

EHR-Based Syndromic Surveillance Tool
An EHR syndromic surveillance tool is in development that will apply innovations in machine learning and natural language processing to clinical notes in order to expand public health surveillance capabilities to identify confirmed and suspected cases of a new disease. Applications include improving case count estimates by expanding data elements included in case identification and rapidly identifying new symptoms that are not yet recognized as part of the syndrome.

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