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Non-COVID Response Logistics Modeling Tools and Reports

Hospital Emergency Preparedness Exercises Guidebook, Pocket Guide, Atlas and PowerPoint Presentation

Bioterrorism and Epidemic Outbreak Response POD Models
Ebola Treatment Unit Daily Census and Patient Tracking Tool Version 1.0 (Sept. 22, 2014)

This spreadsheet tool facilitates daily patient care and data collection in Ebola Treatment Units (ETUs, also called Ebola Treatment Centers). The tool was created by Nathaniel Hupert, M.D., M.P.H., of Weill Cornell Medicine and Lewis Rubinson, M.D., Ph.D., of the University of Maryland School of Medicine.

This Microsoft Excel tool was designed in consultation with (and directly responding to the needs of) clinicians currently on the ground in West Africa. It addresses both the tracking of clinic operational parameters (e.g., delay of receipt of lab tests) and the need for daily patient lists in up to three ETU wards. As there are few or no electronics permitted in the "hot zones" where full Personal Protective Equipment (PPE) is required, the last three sheets of the workbook provide a printable interface populated with up-to-date results for efficient rounding. This tool helps frontline health care workers assimilate information about patients under their care and facilitate effective treatment for suspected, confirmed and convalescent patients. Its developers are certain that the tool can be improved and they welcome any enhancements.

The following are now freely available:

  1. File spreadsheet tool in "locked" form which prevents inadvertent deletion of formulae and formatting but permits full functionality
  2. An File "unlocked" version with sample fake patient information to illustrate data inputs and outputs as well as to permit viewing of the underlying formulae - we encourage users to hack this version of the spreadsheet to improve its look, feel and functionality; if you would like to manipulate the "locked" version, the password is "EVD".
  3. One-page, printable PDF icon instructions

Note: if users of this tool are willing to share any summarized, non-protected, clinical operational data collected with its use (e.g., length of stay by ward and/or by patient outcome), this will greatly enhance ongoing efforts to accurately forecast upcoming logistical outbreak requirements. Furthermore, if users have the ability to link unit-based patient care to specific quantities of PPE required, provision of that information is valuable for quantitative logistical planning. Please contact Dr. Hupert (nah2005@med.cornell.edu) for further information.

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