About this item:

468 Views | 493 Downloads

Author Notes:

Address for correspondence: Michael J. Haber, Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA; email: mhaber@sph.emory.edu

We thank Martin Meltzer for his thoughts on the potential economic consequences associated with the interventions we modeled and Keiji Fukuda for his comments on early versions of the manuscript.


Research Funding:

M.J.H. was partially supported by contract 02IPA09666 from the Centers for Disease Control and Prevention.


  • influenza
  • models
  • statistical
  • patient isolation
  • quarantine
  • stochastic processes
  • research

Effectiveness of Interventions to Reduce Contact Rates during a Simulated Influenza Pandemic


Journal Title:

Emerging Infectious Diseases


Volume 13, Number 4


, Pages 581-589

Type of Work:

Article | Final Publisher PDF


Measures to decrease contact between persons during an influenza pandemic have been included in pandemic response plans. We used stochastic simulation models to explore the effects of school closings, voluntary confinements of ill persons and their household contacts, and reductions in contacts among long-term care facility (LTCF) residents on pandemic-related illness and deaths. Our findings suggest that school closings would not have a substantial effect on pandemic-related outcomes in the absence of measures to reduce out-of-school contacts. However, if persons with influenzalike symptoms and their household contacts were encouraged to stay home, then rates of illness and death might be reduced by ≈50%. By preventing ill LTCF residents from making contact with other residents, illness and deaths in this vulnerable population might be reduced by ≈60%. Restricting the activities of infected persons early in a pandemic could decrease negative health impact.

Copyright information:

Emerging Infectious Diseases is published by the Centers for Disease Control and Prevention, a U.S. Government agency. Therefore, all materials published in Emerging Infectious Diseases are in the public domain and can be used without permission.

Export to EndNote