# Presentation: 497676

## Defining Priority Groups for Pandemic Vaccine & Antiviral Drugs: Risk Groups and Critical Infrastructure

- Ben Schwartz, M.D.
- National Vaccine Program Office,
- U.S. Department of Health and Human Services

- NVAC Meeting, July 19, 2005

## Background

- Pandemic vaccine supply will be limited
- Expect only U.S.-produced vaccine in a pandemic
- Estimate ~6 million doses/wk from U.S. manufacturing
- Antiviral drug (neuraminidase inhibitor) supply also will be limited
- U.S. supply chain for oseltamivir expected in late-2005 but will produce only ~15 million courses/yr
- Stockpiled drugs will be major source of pandemic supply

## Background

- Given limited supply, priority groups must be defined for receipt of early vaccine & antiviral drugs
- Targeting the limited supply of vaccine and antiviral drug to high risk groups and persons providing critical infrastructure will help achieve pandemic response goals of:
- Decreasing pandemic health impacts
- Decreasing societal impacts
- Limiting economic disruption

## Presentation Objectives

- Present analysis of high risk groups for severe influenza disease and death in a pandemic to facilitate designation of priority groups
- Define critical infrastructures and estimate population sizes in these groups

## Methodology

- Definition of high-risk groups
- Working group (Pascale Wortley & Ted Eickhoff, co-chair) analyzed data on risk groups in prior pandemics and interpandemic influenza
- Definition of critical infrastructure
- Working group (Carolyn Bridges, chair) assessed potential critical infrastructure groups
- Collaboration with the Department of Homeland Security
- Total industry populations were further analyzed to identify those who provide essential services

## Part 1: Risk groups for illness, 

- hospitalization, and death

## Clinical Influenza Attack Rates, 1918

- *approximations based on figure in Frost 1919—household surveys conducted Dec 1918

## Clinical Influenza Attack Rates, Fall 1957

|  | Hennessey (1964) | Dunn
(1959) | Jordan*
(1958) | Woodall
(1958) | Chin
(1960) |
| --- | --- | --- | --- | --- | --- |
| Pop. | Tecumseh households | 5 schools, 1 factory
LA parish | Cleveland families | General practice, London | Family contacts of KC HS students  |
| 0-4 | 26% | 31% (pre-school) | 43% | 31% | 32% |
| 5-9 | 38% | 39% (elementary) | 58% | 49% | 33% |
| 10-14 | 40% | 48% 
(high school) | 59% |  | 39% |
| 15-19 | 34% |  | 47% | 25% 

(60+ 12%) | 38%  |
| 20-29 | 20% | 20%
(adults) | 19% |  | 27%  |
| 30-39 | 16% |  |  |  |  |
| 40-49 | 14% |  |  |  | 17%  |
| 50+ | 10% |  |  |  |  |

- *lab-confirmed

## Clinical Influenza attack rates, Nov 1968-Jan 1969

|  | Monto (1970)* | Davis (1970) |
| --- | --- | --- |
| <1 | 16.5% | 40% |
| 1-4 |  | 40% |
| 5-9 | 11.6% | 43% |
| 10-14 |   9.2% | 40% |
| 15-19 |   8.9% | 38% |
| 20-24 | 12.7% | 35% |
| 25-29 |  | 33% |
| 30-39 |   8.1% | 38% |
| 40-49 |   8.9% | 38% |
| 50-64 |  | 35% |
| 65+ |  | 30% |
| Population | Adrian (comparison to Tecumseh)* | Southwest high school families (Kansas City) |

- *weekly mean averages

## Pneumonia & Influenza (P & I) Mortality Rates, 1918

- *Frost 1919, approximations based on figure

## P&I Mortality Rates (per 105), 108 Cities,  Aug-Dec 1957

- P&I Mortality Rates (per 105), 108 Cities,  Aug-Dec 1957

- Age group

- Dauer 1958

## P&I Mortality Rates (per 105), 1968-69

- P&I Mortality Rates (per 105), 1968-69

- Age group

- Luk, 2001

## Proportion of Excess P & I Deaths in Persons <65 y.o. in Influenza Pandemic & Inter-pandemic Seasons, 1918-95

- Simonsen et al. JID 1998

**Notes:**
Shift to younger age groups in pandemic years—higher percent of cases in young, decreasing over time

## Hospitalizations and Deaths Among Persons >65 Yrs. Old, 1996-1998

- Source: Hak 2002 CID

- *Renal disease, immunodeficiency, organ transplants, non-hematologic cancer

**Rate (per 10****5****)**

## Hospitalizations and Deaths per 10,000 Persons 15-64, 1973-1992

-   Neuzil 1999 JAMA
-   Neuzil 2003 JAIDS

- *NS

- Range 36-76/10,000

- *HIV-HAART data: 1995-1999

## P & I Deaths by Number of High Risk Conditions - Oregon HMO

|  | Status | P&I deaths | Population | Rate per 105 |
| --- | --- | --- | --- | --- |
| 15-44 | No HR | 0 | 134,000 | - |
|  | 1 HR | 0 | 6,260 | - |
|  | >1 HR | 0 | 260 | - |
| 45-64 | No HR | 1 | 43,900 | 2 |
|  | 1 HR | 7 | 6,900 | 10 |
|  | >1 HR | 4 | 1,060 | 377 |
| >64 | No HR | 1 | 11,760 | 9 |
|  | 1 HR | 14 | 6,460 | 217 |
|  | >1 HR | 11 | 1,380 | 797 |

- Barker, Arch Intern Med 1982

## Previous Hospitalization as a Risk Factor for Severe Influenza 

- 39 – 46% of the elderly discharged for an influenza-associated respiratory condition had a recent hospitalization
- 62 – 67% of those who died had a recent hospitalization
- 6% of elderly persons were hospitalized during the influenza season

- Fedson, Annals of Internal Medicine 1992;116:550-5

## Risk Factors for P & I Hospitalization & Death During Influenza Season

|  | Adjusted OR |
| --- | --- |
| Previous P/I hosp.  |   8.1 (5.7-11.5) |
| Outpatient visits | 1.5 (1.3-1.8) |
| Heart disease | 1.2 (1.0-1.5) |
| Pulm disease | 1.8 (1.4-2.3) |
| Dementia, stroke | 2.1 (1.6-2.7) |
| Renal disease | 1.5 (1.1-2.1) |
| Cancer | 4.9 (3.4-7.0) |
| Diabetes | ns |
| Immunodeficiency* | ns |

- * Immunodeficiency and organ transplants

- Hak 2004 JID

## Specific Conditions: Bone Marrow Transplants

- Limited studies (Nichols 2004, Whimbey 1994) , but both suggest high rates of complications.
- Largest study (Nichols): 18/62 BMT pts with lab confirmed influenza had LRI; 6/62 died (5 of 6 had LRI)
- Likely greater benefit from antiviral drugs than vaccine

## Risk of Pandemic Influenza Death in Pregnancy

**Harris 1919**: case series of pregnant women with influenza; 50% had pneumonia, and 50% CFR w/ pneumonia (7-9th months: 60% vs 1-6 m:45-53%).
**Woolston 1918**: 2154 pts admitted to Cook County Hospital; 50% of pregnant women died compared with 33% of other pts.
**Greenberg 1958**: NYC mortality data fall 1957; 47 P&I deaths in women 15-49; 22/47 (47%) were pregnant.

## Size of Potential Priority Groups for Pandemic Vaccine & Antiviral Drugs

| Group | Number in millions* | Comment |
| --- | --- | --- |
| Transplants |   0.15 | Includes solid organ transplants |
| Cancer | 1.4 | Annual incidence—assume equal to immunosuppresed |
| >  2 high risk conditions | 10 | Ages 2-64 and 65+ |
| <12 months | 4 |  |
| Pregnant women  | 0.4 |  |

- *groups may overlap

## Part 2: Critical Infrastructures 

- for a pandemic response

## Critical Infrastructure: Potential Vaccine and Antiviral Target Groups

- Definition of infrastructure:
- 	“The framework of interdependent networks and systems comprising identifiable industries, institutions and distribution capabilities that provide a reliable flow of products and services essential to the defense and economic security of the of the US, the smooth functioning of government at all levels, and society as a whole.”
- 	*President’s Commission on Critical Infrastructure Protection, Critical Foundations Protecting America’s Infrastructure, October 1997*

**Notes:**
To help us begin to look at certain priority groups, I provide here a broad definition of infrastructure – defined by the President’s Commission on Critical infrastructure Protection in 1997

This definition focuses on defense and government security --- and economic functions.

While it does not have to be this working group’s specific definition, it does provide a good base to understand what is looked at when defining priority groups by infrastructure.

However, this definition does not provide any insights into specific critical infrastructures as they relate to an influenza pandemic

SWITCH

## Approach to Define Critical Infrastructures & Populations

- Focus on occupations/industries that contribute to achieving pandemic response goals
- Consider critical infrastructure definitions from other sources (White House, Congress, Canadian pandemic plan) and experience from preparedness exercises
- Defined population sizes from Bureau of Labor Statistics data
- Honed populations based on input from DHS

## Key Issues and Limitations

- Importance of networks and supply chains
- E.g., what industries/personnel are required to assure that medical supplies reach healthcare facilities and food reaches persons in cities?
- Estimates of absenteeism during a pandemic
- What proportion of persons will miss work and can function be preserved with this work loss?
- Experience from prior pandemics is not informative and no comparable health emergencies have occurred

## Estimate of Days Lost From Work Due to Illness in Self or Family

- Modeled lost work days from illness using FluAid and FluSurge (based on 1957/1968 pandemics) and 2000 Census
- Inputs:
- Days lost from work due to illness
- Days lost from work due to caring for family member
- Employment rate, marriage rate, work days per month
- Assumed outbreak period 8 weeks and 25% influenza illness rate as base-case

- Xinzhi Zhang, MD PhD and Martin I. Meltzer, PhD MS

## Model Inputs and Total Lost Work Days

| Scenario | Self-care | Outpatient | Hosp. | Death | Self-care | Outpatient | Hosp. | Death |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| A | 1 | 3 | 7 | 40 | 1 | 3 | 7 | 10 |
| B | 5 | 7 | 12 | 40 | 3 | 5 | 10 | 12 |

- Days of work for own illness

- Days caring for others

| Work Days Lost | Scenario A | Scenario B |
| --- | --- | --- |
| Most Likely |  130,672,484  | 269,845,189 |
| Minimum |  110,435,229  | 249,341,669 |
| Maximum |  161,643,371  | 300,682,747 |

## Proportion of Work Days Lost Due to Pandemic Influenza

- Scenario B (10%)

- Scenario A (4.8%)

- 0%

- 2%

- 4%

- 6%

- 8%

- 10%

- 12%

- 1

- 8

- 15

- 22

- 29

- 36

- 43

- 50

**Days of outbreak**

## Limitations of Work Loss Model

- Wide range of estimates for of work day loss
- Largely unknown from literature
- For interpandemic influenza, lost work days per illnfluenza-like illness average 1 day in US studies
- Impacts are likely to vary between communities, industries, and worksites
- Estimates are based on less severe pandemics
- Some experts felt that peak would be sharper than in the model resulting in greater proportion of work loss at the height of the outbreak

## Potential Critical Infrastructures to Achieve Pandemic Response Goals

- Decrease pandemic health impacts
- Health care workers
- Public health workers & other pandemic responders
- Health decision makers
- Decrease health and societal impacts
- Transportation (food & medical supplies; people)
- Utilities (electricity, gas, water)
- Public safety (police, fire, and corrections)
- Mortuary
- Sanitation
- Military and government

## Health Care Workers: Categories and Populations 

| Inpatient (5.1 M) | Outpatient (7.4 M) |
| --- | --- |
| General hospitals (4.7 M)
  -- Healthcare/technical (3 M)
  -- Other/support (1.7 M) | Offices (3.25 M)
  -- Physician (2 M)
  -- Dentist (750,000)
  -- Other (500,000)
Nursing residential (2.8 M
Home health care (700,000)
Outpatient care ctrs (400,000)
Laboratories (180,000) |
| Other hospitals (420,000)
  -- Psychiatric (240,000)
  -- Specialty (180,000) |  |
| Emergency services (820,000) |  |

- Bureau of Labor Statistics, 2003

## Proposed Critical Infrastructure for Pandemic Vaccine & Antiviral Priority

- Inpatient and outpatient health care workers
- Estimate that ~2/3 have direct patient contact or are essential for quality care
- N = 8,375,000
- Emergency medical services
- Assume all are essential in a pandemic (820,000)
- Total number of HCWs/EMS = 9,195,000

## Proposed Critical Infrastructure for Pandemic Vaccine & Antiviral Priority

| Group | Number |
| --- | --- |
| Vaccine & antiviral mfrs |    20,000 |
| Health care decision-makers | ? |
| Public health workers (non HCW) |   300,000 |
| Public safety workers | 2,987,000 |
| Utility workers |   364,000 |
| Transportation | 3,800,000 |
| Telecommunications | 1,080,000 |
| Mortuary |     62,000 |
| Sanitation |   321,000 |
| Judiciary |     73,000 |
| Financial services |       1,000 |

- Total =
- 9,008,000

## Future Work to Be Done

- Hone definitions of infrastructure groups and population sizes
- Further define specific sections of each group critical for maintenance of function
- Evaluate ability to absorb some work loss and surge capacity
- Identify additional groups along supply chains that may also need to be prioritized (e.g. critical food groups needed to supply food for transportation)
- Consider implementation issues
- How can persons in target groups be identified for vaccination and antiviral treatment?

## Acknowledgements & Thanks

- Pascale Wortley, Ted Eickhoff & the pandemic impact working group
- Carolyn Bridges & the critical infrastructure group
- Dale Brown, Department of Homeland Security
- Elizabeth Falcone, NVPO intern
- Xinzhi Zhang & Martin Meltzer, CDC/modeling