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Hospital Surge Model Version 1.3: Description

Public Health Emergency Preparedness

This resource was part of AHRQ's Public Health Emergency Preparedness (PHEP) program, which was discontinued on June 30, 2011, in a realignment of Federal efforts.

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Chapter 1. Anthrax

This chapter describes the assumptions for the anthrax scenario, including:

  • The severity categories.
  • The arrival pattern of casualties at the hospital(s).
  • The length of stay by hospital unit (i.e., ED, ICU, and the floor).
  • The path probability within the hospital(s) and the length of stay.
  • The overall outcome probabilities (i.e., probability of discharge and probability of death).
  • The assumed level of resource consumption per patient per day per hospital unit.

Footnotes in the text of a particular section refer to references at the end of the section. In the absence of specific references, parameter estimates were obtained from general references listed in the Hospital Module section.

1.1. Severity Categories

For the anthrax scenario, patients arrive at the hospital(s) in one of two conditions:

  1. Mild: When victims become ill, they are more than 3 days away from death, assuming no treatment.
  2. Severe: When victims become ill, they are 3 or fewer days away from death, assuming no treatment.

Users have the option of specifying either the number and type or simply the number of casualties who present at their hospital(s).

If the user specifies only the number of casualties, the model assumes the casualties arriving at the hospital(s) are distributed according to the table below:

Casualty Condition Percent
Mild: When victims become ill, they are more than 3 days away from death, assuming no treatment. 79.8%
Severe: When victims become ill, they are 3 or fewer days away from death, assuming no treatment. 20.2%

This breakdown by casualty condition is based on work performed during development of the original Surge Model in 2005. In brief, plume modeling was used to estimate the distribution of anthrax spores for scenarios in several different cities. From this data, we modeled the estimated distribution of exposure for any major city. We used an average-sized American city as the basis for our estimates. Human and animal data were used to estimate the likely time of onset of symptoms. Given a mean time to death, casualties were normally distributed to have onset times greater or shorter than average. Patients with a very short "time to death" without treatment were termed "severe" and other patients "mild." Patients were expected to seek help at the onset of symptoms.

1.2. Casualty Arrival Pattern

Casualties are assumed to present at the hospital(s) when symptoms appear, which occurs over a period of several days. To determine the arrival pattern, we analyzed the distribution of mild and severe cases, using an average-sized city. The arrival pattern of casualties closely matched a gamma distribution, which was used to estimate the time of arrival for patients when both number and condition are specified.

1.3. Length of Stay (LOS) By Hospital Unit

The assumed average lengths of stay (in days) of patients in the ED, in the ICU, and on the floor14 are:

Average LOS by Hospital Unit Mild Case Severe Case
ED 1 1
Floor, not via ICU 22 22
Floor, via ICU 19 19
ICU 3 3

1.4. Path Probabilities and Lengths of Stay

The table below shows the assumed probabilities of different "paths" through the hospital(s).14 The table shows, for example, that a patient presenting with a mild case of anthrax has a 21 percent chance of being transferred from the ED to the ICU and then dying in the ICU.

Path Mild Case Severe Case
ED → Discharge 5% 0%
ED → Death 0% 0%
ED → Floor → Discharge 46% 3%
ED → Floor → Death 11% 1%
ED → Floor → ICU → Death 11% 5%
ED → Floor → ICU → Floor → Discharge 1% 0%
ED → Floor → ICU → Floor → Death 1% 1%
ED → ICU → Death 21% 69%
ED → ICU → Floor → Discharge 2% 7%
ED → ICU → Floor → Death 1% 15%

The breakdown of length of stay by patient type summed across all paths is:

Average LOS by Patient Outcome Mild Case Severe Case
Survivors 21.23 23.43
Fatalities 8.08 5.01
Average Combined 15.30 6.80

1.5. Overall Outcome Probabilities

Based on these inputs11 listed at the end of this section), the overall discharge and death probabilities are:

Outcome Mild Case Severe Case
Discharge 55% 10%
Death 45% 90%

1.6. Resources Consumed Per Patient Per Day

The assumed level of resource consumption per patient per day is shown in the table below:

Resource Units Category Subcategory Lambdaa Mild Severe
ED ICU Floor ED ICU Floor
Med/Surg Bed Unit of Use Capacity Floor 1 0.083 0 1 0.167 0 1
ICU Bed Unit of Use Capacity ICU 1 0 1 0 0 1 0
Burn Bed Unit of Use Capacity Burn 1 0 0 0 0 0 0
Operating Room Unit of Use Capacity OR 1 0 0 0 0 0 0
Airborne Isolation Room Unit of Use Capacity Isolation 0.9 0 0 0 0 0 0
Intensivists (CCM) FTE Staff CCM 0.7 0.021 0.042 0 0.042 0.042 0
Critical care nurses (CCN) FTE Staff CCN 1 0 0.33 0 0.167 0.33 0
Surgeons FTE Staff Surgeon 0.3 0 0.042 0 0.042 0.042 0
Non-intensivists (MD) FTE Staff MD 0.9 0.042 0 0.021 0.042 0 0.021
Non-critical care nurses (RN/LPN) FTE Staff RN 1 0.167 0 0.146 0 0 0.146
Respiratory Therapists (RT) FTE Staff RT 0.7 0 0.083 0 0.083 0.083 0
Radiology machines Machine Time Lab/Radiology Radiology 0.3 0.021 0.021 0 0.021 0.021 0
Radiologic Technicians FTE Staff Rad Tech 0.3 0.021 0.021 0 0.021 0.021 0
Pharmacists (PharmD/RPh) FTE Staff Pharmacist 0.7 0.021 0.062 0.042 0.021 0.062 0.042
Mechanical ventilator Machine Time Capacity Ventilator 0.9 0 0 0 1 1 0
Ventilator equipment Unit of Use Equipment Vent Tubing 0.9 0 0 0 1 1 0
Oxygen (O2) Unit of Use Supplies Oxygen 0.9 0 1 0 2 2 0
Oxygenation monitoring equipment Machine Time Equipment O2 Monitoring 0.9 0.083 1 0 0.083 1 0.5
Surgical supplies Unit of Use Supplies Surgical 0.3 0 0.25 0 0 0.025 0
Radiology supplies Unit of Use Supplies Radiological 0.3 1 1 0 1 1 0
Cirprofloxacin or doxycycline 400mg/100mg bid Pharmacy Antibiotics 1 1 1 1 1 1 1
Rifampin or other 2nd line agent 600mg po bid Pharmacy Antibiotics 1 0 1 0 1 1 1
Antibiotics for secondary pneumonia Assorted Pharmacy Antibiotics 1 0 0 0 0 1 0
Antibiotics intravenous infusion set Unit of Use Supplies IV set 1 1 0.5 0.5 1 0.5 0.5
Hemodynamic medications Unit of Use Pharmacy Hemodynamic 0.7 0 1 0 1 1 0
Intravenous fluids Unit of Use Pharmacy IVF 0.7 1 1 0.5 1 1 1
Intravenous infusions set Unit of Use Supplies IV Set 0.7 1 1 0.5 1 1 1
Laboratory machines Machine Time Lab/Radiology Laboratory 0.7 0.021 0.021 0.021 0.021 0.042 0.021
Laboratory supplies Unit of Use Supplies Laboratory 0.7 0.5 0.5 0.5 0.5 1 0.5
Temperature monitoring equipment Machine Time Equipment Temperature 1 0.083 1 1 0.083 1 1
Thromboembolism prophylaxis Unit of Use Pharmacy DVT Prophylaxis 1 0 1 0 0 1 1
Urine output monitoring equipment Unit of Use Equipment U/O 1 0 1 0 0 1 0
Universal Precautions PPE Unit of Use PPE Universal 1 1 1 1 1 1 1
Waste Disposal Unit of Use Waste Mgmt Decon Waste 0.3 1 0 0 1 0 0
IV Steroids Unit of Use Pharmacy Steroids 0.7 0 0 0 0 0 0
Enteral feedings (3/day/patient) Unit of Use Nutrition Enteral 1 0 0.5 0 0 0.5 0
Oral food (3 meals per day per patient) Unit of Use Nutrition Oral 1 0 0.5 1 0 0.5 1
Sheet change Unit of Use Housekeeping Laundry 1 1 1 1 1 1 1
Patient infection control FTE Epidemiology Infection Control 0.5 0.083 0.083 0.083 0.083 0.083 0.083
Engineering FTE Engineering Facility 0.7 0.042 0.083 0.042 0.042 0.083 0.042
Janitorial/Housekeeping FTE Housekeeping Janitorial 1 0.083 0.125 0.083 0.125 0.125 0.083
Nutrition FTE Nutrition Counseling 0.5 0 0.083 0.083 0 0.083 0.083
Psychological support FTE Ancillary Psychologist 0.5 0.021 0.042 0.042 0 0.042 0.042
Mortuary FTE Mortuary Morgue 0.1 0 0.042 0.042 0 0.083 0.042

a. Lambda captures the resource requirement decay rate for a resource.  Lambda = 1 implies no decay; the patient requires a constant amount of the resource while s/he is hospitalized.  Lambda <1 implies that less of the resource is required each day the patient is hospitalized.  Go to section 2.2 for details.

1.7 References

1. A case of anthrax septicaemia in a London teaching hospital. Commun Dis Rep CDR Wkly 1995;5(36):169.

2. Barakat LA, Quentzel HL, Jernigan JA, et al. Fatal inhalational anthrax in a 94-year-old Connecticut woman. JAMA 2002;287(7):863-8.

3. Bartlett JG, Inglesby TV Jr., Borio L. Management of anthrax. Clin Infect Dis 2002;35(7):851-8.

4. Bell DM, Kozarsky PE, Stephens DS. Clinical issues in the prophylaxis, diagnosis, and treatment of anthrax. Emerg Infect Dis 2002;8(2):222-5.

5. Borio L, Frank D, Mani V, et al. Death due to bioterrorism-related inhalational anthrax: report of 2 patients. JAMA 2001;286(20):2554-9.

6. Cieslak TJ, Eitzen EM Jr. Clinical and epidemiologic principles of anthrax. Emerg Infect Dis 1999;5(4):552-5.

7. Darling RG, Catlett CL, Huebner KD, et al. Threats in bioterrorism. I: CDC category A agents. Emerg Med Clin North Am 2002;20(2):273-309.

8. Dewan PK, Fry AM, Laserson K, et al. Inhalational anthrax outbreak among postal workers, Washington, D.C., 2001. Emerg Infect Dis 2002;8(10):1066-72.

9. Felek S, Akbulut A, Kalkan A. A case of anthrax sepsis: non-fatal course. J Infect 1999;38(3):201-2.

10. Friedlander AM. Anthrax: clinical features, pathogenesis, and potential biological warfare threat. Curr Clin Top Infect Dis 2000;20:335-49.

11. Holty JE, Bravata DM, Liu H, et al. Systematic review: a century of inhalational anthrax cases from 1900 to 2005. Ann Intern Med 2006; 144(4):270-80.

12. Holtz TH, Ackelsberg J, Kool JL, et al. Isolated case of bioterrorism-related inhalational anthrax, New York City, 2001. Emerg Infect Dis 2003;9(6):689-96.

13. Inglesby TV, O'Toole T, Henderson DA, et al. Anthrax as a biological weapon, 2002: updated recommendations for management. JAMA 2002;287(17):2236-52.

14. Jernigan DB, Raghunathan PL, Bell BP, et al. Investigation of bioterrorism-related anthrax, United States, 2001: epidemiologic findings. Emerg Infect Dis 2002;8(10):1019-28.

15. Mayer TA, Bersoff-Matcha S, Murphy C, et al. Clinical presentation of inhalational anthrax following bioterrorism exposure: report of 2 surviving patients. JAMA 2001;286(20):2549-53.

16. Mina B, Dym JP, Kuepper F, et al. Fatal inhalational anthrax with unknown source of exposure in a 61-year- old woman in New York City. JAMA 2002;287(7):858-62.

17. Swartz MN. Recognition and management of anthrax—an update. N Engl J Med 2001;345(22):1621-6.

18. Traeger MS, Wiersma ST, Rosenstein NE, et al. First case of bioterrorism-related inhalational anthrax in the United States, Palm Beach County, Florida, 2001. Emerg Infect Dis 2002;8(10):1029-34.

19. Yetman RJ, Parks D, Taft E. Management of patients exposed to biologic weapons. J Pediatr Health Care 2002;16(5):256-61.

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