Development and Validation of the Public-Facing SimAEN Web Application

Abstract

During a pandemic such as COVID-19, non-pharmaceutical interventions (NPIs) can help protect public health; however, it is not always clear which actions will have the greatest positive impact, or what the trade-offs are between different options. Exposure Notification (EN) was introduced as a prevention measure during the COVID-19 pandemic to supplement traditional contact tracing activities. To predict the estimated impacts of EN, a model for simulation of automated exposure notification (SimAEN) was developed by researchers at MIT Lincoln Laboratory (MIT LL) with CDC funding. The model was published through an accessible web interface, available for use by the general public at https://SimAEN.philab.cdc.gov/.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2022
Accession Number
AD1178789

Entities

People

  • Jesslyn D. Alekseyev
  • Madeline R. Chmielinski

Organizations

  • Massachusetts Institute of Technology

Tags

DTIC Thesaurus Topics

  • Computer Science
  • Computers
  • Contracts
  • Covid-19
  • Detection
  • Disease Outbreaks
  • Diseases And Disorders
  • Health
  • Hygiene
  • Infectious Diseases
  • Intervention
  • Mathematical Models
  • Models
  • Public Health
  • Quarantine
  • Simulations
  • Standards
  • United States
  • Viruses
  • Web Applications

Readers

  • Computational Modeling and Simulation
  • Infectious Disease/Epidemiology