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Source
Martin I. Meltzer, Nancy J. Cox, and Keiji Fukuda, The Economic Impact of Pandemic Influenza in the United States: Priorities for Intervention: EID 1999, Vol.5, No.5; 659–71.
Context
An influenza pandemic in 1920 resulted in over 20 million deaths. Subsequent pandemics occurred in 1957 and 1968.
Health professionals and governments are concerned about the possible impact of next influenza pandemic.
As scientific and technological progress has made it possible to check the spread of many communicable diseases, policy makers need information on the impact of these diseases to decide where and how to use limited societal resources.
This study assesses the costs, benefits, and policy implications of various influenza vaccine-based interventions in the United States.
Methods
Societal
A probability-based model that estimates:
  • the number of health outcomes (e.g., deaths, hospitalizations, and outpatient visits),
  • the resultant costs of the next influenza pandemic, and
  • the economics of various vaccine-based interventions.
General population of the United States, with:
  • age-related subgroups:
    • age 0–19 years,
    • age 20–64 years, and
    • age ≥65 years
  • and two influenza-related risk groups — high risk and non-high risk.
    Risk is defined as the increased probability of adverse influenza-related health outcomes as a result of pre-existing medical conditions (e.g., emphysema, asthma, and diabetes).
Definitions of Key Terms
the percentage of clinical influenza cases per population
cases in persons with illness sufficient to cause an economic impact
outcomes that include:
  • outpatient visits,
  • hospitalizations,
  • deaths, and
  • clinical cases for which no medical care was sought
The Model
A Monte Carlo (probability-based) mathematical simulation model is used to calculate the possible outcomes of the next influenza pandemic.
It is not an epidemiologic model based on the dynamics of the spread of the disease through a population.
Rather, it uses rates of health outcomes from prior, non-influenza pandemic years as a basis to estimate the potential number of total cases that might occur.
Thus the model predicts neither:
  • how long the next influenza pandemic will last, nor
  • the geographic distribution of the cases.
The model uses vaccines similar to current intrapandemic recommendations. It compares four vaccination strategies that differ in target population coverage and numbers of vaccines:
  • Option A, with the target population similar to the current Advisory Committee on Immunization Practices recommendation,
  • Option B, targeting the population in Option A plus 20 million essential-service providers (including 5 million health-care workers and 15 million providers of other services,
  • Option C, targeting 40% effective coverage of the entire U.S. population (106.1 million vaccines),
  • Option D, targeting 60% of the entire U.S. population (159.2 million vaccines).
Outcomes From the Model
The model:
  1. Produces ranges of numbers of:
    • deaths,
    • hospitalizations,
    • outpatient visits, and
    • persons ill, but not seeking medical care.
    These estimates are broken down into the groups given earlier:
    • 3 age-related subgroups:
      • age 0–19 years,
      • age 20–64 years, and
      • age ≥65 years
    • and the two influenza-related risk groups (high risk and non-high risk).
  2. Produces estimates of the cost (given as ranges) of the next influenza pandemic.
    These estimates are confined to estimates of:
    • the medical costs associated with treating influenza patients, and
    • the indirect costs associated with the productivity lost from those patients.
    The estimates do not include other economic losses (e.g., overall reduction in the economy as a result of reduced business activity).
  3. Produces estimates of the net economic returns to vaccinating the various age and risk groups.
  4. Demonstrates how vaccination priority lists might differ when different criteria are used.
    It provides examples of prioritizing vaccination among the 6 age-and-risk group population subgroups, using three different criteria:
    • total number of deaths,
    • risk for death, and
    • maximizing net returns to the vaccinations.
  5. Demonstrates how the model can be used to calculate net economic returns for a variety of proposed vaccination strategies.
  6. Calculates the mean "annual insurance premiums" for planning, preparing, and practicing for the next influenza pandemic.
    These "premiums" are calculated by using:
    • the model-produced estimates of the values of cases that might be prevented by effective vaccination campaigns, and
    • an assumed range of annual probabilities of the next influenza pandemic occurring.
Estimating the Number of Cases
The numbers of clinical illness cases for the whole population are derived for five different gross attack rates, at levels from 15% to 35%, in steps of 5%.
For each gross attack rate, the illness cases are further distributed among population age subgroups in fixed proportions.
The numbers of adverse outcomes in each subgroup are then calculated by using the rates of adverse effects, given by their respective probability distributions. The numbers are shown in the Appendix of this tutorial:
The model is run for several iterations. During each iteration, values for each variable are drawn from their probability distributions.
The results are then pooled, and the summary statistics (e.g., averages, medians, and 5th and 95th percentiles) are calculated.
Thus the Monte Carlo simulation approach:
  • allows us to account for the uncertainty inherent in predicting the impact of a pandemic, and
  • provides a range of values for possible outcomes and effects.
Key input variables (e.g., rates of adverse health outcomes and gross attack rates) are based on:
  • reported epidemiologic estimates of rates of adverse outcomes, and
  • age-specific attack rates from previous epidemics and pandemics.
A proprietary database containing health insurance claims data (MarketScan of the Medstat Group, Ann Arbor, MI) served as a basis for estimating direct costs of hospitalization and outpatient visits.
Estimating Costs
Pandemic Costs
The costs of a pandemic are identified as direct and indirect costs associated with adverse outcomes. An average unit cost for each adverse outcome is estimated from a database or obtained from the literature.
  • The direct costs for hospitalization are calculated by using charge data from health-care databases.
    These health-care system charges are converted to societal-level costs by using Medicare-provided cost-to-charge ratios (i.e., every $1 of charge represents approximately $0.50 of actual societal-level costs).
    These societal level costs measure the actual opportunity costs associated with the resources used to treat hospitalized patients.
  • The direct costs for outpatient visits are estimated as a sum of insurance payments for prescription, prescription co-payments, net insurance payment, and co-payments for visits.
  • The direct costs for death and illness cases when no medical care was sought are estimated through hospital costs and over-the-counter drug costs, respectively.
  • The productivity losses are valued based on gender-weighted average wage rates.
  • The indirect costs of deaths, particularly, are valued as the present value of future earnings lost.
All costs are standardized to 1995 dollar values (Table 3. Input variables used to calculate the economic impact (direct and indirect costs) of health outcomes attributed to an influenza pandemic in the United StatesOpen this in a new window in the Appendix of this tutorial).
Using the distribution of adverse outcomes described above, the total costs per adverse outcome are calculated as a product of average unit cost for each adverse outcome and the total number of adverse outcomes.
Vaccination Costs
Based on the range of estimates derived from previous studies, the cost of vaccinating a person is modeled with two values:
  • $21 for a lower-cost scenario, and
  • $62 for an upper-cost scenario.
The direct cost components include the cost of vaccine and administration costs, while the indirect costs include travel and lost productivity costs.
Side effects are also included and consist of:
  • Guillain-Barré syndrome,
  • anaphylaxis, and
  • mild effects.
(See Table 4. Cost of vaccination during an influenza pandemic — with specific costs assigned to side effects of vaccinationOpen this in a new window in the Appendix of this tutorial).
Estimating Benefits
The benefits of vaccinating interventions are calculated as savings from outcomes averted. The summary measures of the analysis (i.e., the net returns of interventions) are estimated as the differences between the benefits and costs.
They are calculated for each age and risk group according to this formula:
Net returnsAge = Savings from outcomes averted in populationAge Cost of vaccination of populationAge
The savings in costs result from the reductions in the numbers of adverse outcomes attributable to vaccination interventions, which are captured by vaccine effectiveness and compliance rates:
Savings from outcomes avertedA,R = Number with outcome before interventionA,R x ComplianceA,R x Vaccine effectiveness x $Value of outcome prevented
where subscript:
A,R = AgeRisk Group
The net returns from interventions can be used to estimate the annual investments in public health to plan, prepare, and practice to ensure that mass vaccinations will be implemented if a pandemic breaks out.
The annual investment can be treated as an annual insurance premium, spent on:
  • improving surveillance systems,
  • ensuring sufficient supply of vaccine for high-priority groups (and possibly the entire U.S. population),
  • conducting research to improve detection of new influenza subtypes, and
  • developing emergency preparedness plans to ensure adequate medical care and maintenance of essential community services.
Taking into account the uncertainty of a pandemic actually occurring, the premiums are calculated as follows:
Annual insurance premium = Net returns from an intervention x The annual probability of a pandemic
Results
Illnesses and Deaths
This figure shows the number of cases of adverse outcomes in the United States when no intervention strategy is implemented:
Approximate Number of Cases of Adverse Outcome when No Intervention Strategy Is Implemented
Approximate Number of Cases of Adverse Outcome when No Intervention Strategy Is Implemented
Note: For each gross attack rate, data are totals for all age groups and risk categories.
The figure shows that:
  • Ranked from highest to lowest total numbers of adverse outcomes, the outcomes are:
    1. clinical illness cases with no medical care sought,
    2. outpatient cases,
    3. hospitalizations, and
    4. deaths.
  • The two more severe outcomes — hospitalizations and deaths — have numbers that are roughly two orders of magnitude lower than those for outpatient cases and illnesses with no medical care sought.
    For example, this table shows the range of two of the adverse outcomes in an influenza epidemic:
    Ranges of adverse outcomes from an influenza epidemic
      Number of cases per gross attack ratea
      15% 35%
    Ill, no medical care sought
      Mean 20 million 47 million
    Hospitalizations
      Mean 314,000 734,000
        5th percentile 210,000 441,000
        95th percentile 417,000 973,000
    a
    Gross attack rate = percentage of clinical influenza illness per population.
Economic Impact of an Influenza Pandemic
The costs of an influenza pandemic are presented in the table below.
Cost vs. gross attack ratea for adverse outcomes (in 1995 US$)
  Cost per gross attack rate ($ millions)
  15% 20% 25% 30% 35%
Deaths
  Mean 59,288 79,051 98,814 118,577 138,340
    5th percentile 23,800 31,733 39,666 47,599 55,532
    95th percentile 94,907 126,543 158,179 189,815 221,451
Hospitalizations
  Mean 1,928 2,571 3,214 3,856 4,499
    5th percentile 1,250 1,667 2,084 2,501 2,917
    95th percentile 2,683 3,579 4,472 5,367 6,261
Outpatients
  Mean 5,708 7,611 9,513 11,416 13,318
    5th percentile 4,871 6,495 8,119 9,742 11,366
    95th percentile 6,557 8,742 10,928 13,113 15,299
Ill, no medical care soughtb
  Mean 4,422 5,896 7,370 8,844 10,317
    5th percentile 3,270 4,360 5,450 6,540 7,629
    95th percentile 5,557 7,409 9,262 11,114 12,967
Grand totals
  Mean 71,346 95,128 118,910 142,692 166,474
    5th percentile 35,405 47,206 59,008 70,810 82,611
    95th percentile 106,988 142,650 178,313 213,975 249,638
a
Gross attack rate = percentage of clinical influenza illness per population.
b
Persons who become clinically ill as a result of influenza but do not seek medical care; illness has an economic impact (e.g., half day off work).
These data indicate that:
  • The total economic impact in the United States of an influenza pandemic varied proportionately with the scale of the pandemic, ranging from $71.3 billion (5th percentile = $35.4 billion; 95th percentile = $107.0 billion) at the gross attack rate of 15% to $166.5 billion (5th percentile = $82.6 billion; 95th percentile = $249.6 billion) at the gross attack rate of 35%.
  • Though the least numerous among the adverse outcomes, the loss of life comprised the bulk of all economic losses at any given attack rate, accounting for 83% of total costs.
Net Value of Vaccination
The results of estimates for net returns of vaccinations in three age groups are plotted below:
Net value of vaccination
Net value of vaccination
This figure illustrates that:
  • For all age groups, vaccinating persons at high risk would produce higher net returns than vaccinating persons in the same age group but not at high risk.
  • However, the levels of net returns, particularly for persons at high risk, vary between the age groups, and higher net returns can be achieved by vaccinating certain age and risk groups.
  • For example, if it cost $21 to vaccinate a person and the effective coverage were 40%, vaccinating patients aged 20–64 years not at high risk would produce higher net returns than vaccinating patients aged ≥65 years who are at high risk. Net returns to society at that level of vaccine cost and compliance are positive for all age and risk groups.
  • At a cost of $62 per vaccine and gross attack rates of less than 25%, only vaccinating populations at high risk would still generate positive returns.
Economic Consequences of Intervention Strategies
The results of the analysis for the chosen four vaccination strategies are presented below.
Four options for responding to an influenza pandemic: mean net economic returns
Four options for responding to an influenza pandemic: mean net economic returns
Note: Bars show mean net returns for each option and assumed cost of vaccination.
This figure shows that:
  • All four interventions produce positive net returns: the larger the scale of a pandemic, the higher the net savings.
  • Option B results in a greater mean net return when specific groups are vaccinated, instead of vaccinating a general proportion of the population.
  • Changing the strategy to vaccinating 40% of the population decreases mean net returns. Option D yields the highest mean net return overall.
    However, the 5th and 95th percentiles for each option overlap with those of other options. Thus the differences in mean values between the options might not occur in practice.
The insurance premium estimates based on the net returns of interventions are reported below.
Mean annual insurance premiuma for planning, preparing, and practicing to respond to the next influenza pandemic
  Mean (s.d.) insurance premium ($ millions)
Gross attack rate Cost of vaccination per vaccinee ($) Low vaccine effectivenessb x 40% compliance x probability of pandemic High vaccine effectivenessb x 40% compliance x probability of pandemic
1 in 30 years 1 in 60 years 1 in 100 years 1 in 30 years 1 in 60 years 1 in 100 years
15% 21 306 (122) 153 (61) 92 (37) 872 (341) 435 (170) 262 (103)
62 162 (122) 81 (61) 48 (37) 654 (341) 326 (170) 196 (103)
25% 21 561 (204) 280 (102) 168 (61) 1,528 (569) 762 (284) 459 (171)
62 416 (204) 207 (102) 125 (61) 1,311 (569) 653 (284) 394 (171)
35% 21 815 (286) 406 (142) 245 (86) 2,184 (796) 1,089 (397) 656 (239)
62 670 (286) 334 (142) 201 (86) 1,967 (796) 980 (397) 591 (239)
a
Defined here is the amount of money to be spent each year to plan, prepare, and practice to ensure that such mass vaccinations can take place if needed. The mathematically optimal allocation of such funds for each activity requires a separate set of calculations.
b
Low and high levels of vaccine effectiveness are defined in the Appendix of Meltzer, et al.
The data in this table indicate that:
  • The amount of the insurance premium ranges from $48 million to $2,184 million per year, varying with the probability of the pandemic, the cost of vaccinating a person, and the gross attack rate.
  • Because higher costs of vaccination reduce net returns from an intervention, increased vaccination costs reduced the premiums.
  • Conversely, increases in gross attack rates (all other inputs held constant) increased the potential returns from an intervention and thus the amount of premiums.
Sensitivity Analysis
At a vaccination cost of $21.26 per vaccinee, reducing the death rates to half and one quarter of the initial values left positive mean net returns for all age groups not at high risk.
However, at a vaccination cost of $62.26 per vaccinee, reducing death rates to half and one quarter of the initial values resulted in negative mean net returns for all age groups not at high risk.
The results are much less sensitive to increases in gross attack rate than to increases in death rate.
For example, assuming a cost of $62.26 per vaccinee and death rates that are half the initial rates, increasing the gross attack rate from 15% to 25% still resulted in negative net returns for all age groups, regardless of assumed level of vaccine effectiveness.
Setting Vaccination Priorities
Resource and technological constraints determine the response a society can muster to stem an epidemic.
Producing large quantities of vaccine and administering them requires time, even if sufficient stockpiles of correct subtype of vaccine are available.
Therefore, planners have to consider who should receive priority for vaccination.
Priorities will depend on the goals the intervention strategies must achieve.
Once policy makers determine the goals, planners can choose the corresponding criteria for priorities and investigate their implications for interventions.
The model explores implications for three different goals:
  • preventing deaths, regardless of age and position in society;
  • preventing deaths among those at greatest risk (i.e., persons aged ≥65 years); or
  • minimizing social disruption.
The priority list generated according to criteria for these goals is as shown below.
Setting vaccination priorities: Which age group or group at risk should be vaccinated first?
  Criteria for prioritization
Priority Risk for deatha Total deathsb Returns due to vaccination
1 (top) High risk age ≥65 yrs High risk age 20–64 yrs High risk age 20–64 yrs
2 Not at high risk age ≥65 yrs High risk age ≥65 yrs High risk age 0–19 yrs
3 High risk age 0–19 yrs High risk age 0–19 yrs Not at high risk age 20–64 yrs
4 High risk age 20–64 yrs Not at high risk age ≥65 yrs Not at high risk age 0–19 yrs
5 Not at high risk age 20–64 yrs Not at high risk age 20–64 yrs High risk age ≥65 yrs
6 (bottom) Not at high risk age 0–19 yrs Not at high risk age 0–19 yrs Not at high risk age ≥65 yrs
a
Priorities by risk for death are set according to lower-limit estimates of deaths per 1,000 population for each age and risk group.
b
The priority list using the total deaths criteria was set by examining the percentage of total deaths that each age and risk group contributed to the total deaths estimated due to a pandemic.
The group with the highest percentage (i.e., contributing the largest number of deaths) is listed as having the highest priority.
In this table:
  • When risk for death is used as the criterion for who will be vaccinated first, persons aged ≥65 years receive top priority.
  • However, when mean net returns due to vaccination are used as the criterion, that group receives the lowest priority.
  • Regardless of criteria used, persons at high risk aged 0–19 and 20–64 years would always receive priority over persons from the same age groups not at high risk.
Conclusions
  • The wide range in all estimates of potential impacts of a pandemic emphasizes the uncertainties associated with
    • the probability of a pandemic, and
    • the numbers of adverse outcomes.
    While the results can describe potential impact at gross attack rates from 15% to 35%, no existing data can predict the probability of any of those attack rates actually occurring.
  • The results illustrate that the greatest economic cost is due to death. Therefore, all other things being equal, the largest economic returns will come from the intervention(s) that prevents the largest number of deaths.
    A limitation of the model is that, beyond the value of a lost day of work, the model does not include any valuation for disruptions in commerce and society.
  • The goals the interventions must achieve determine the vaccination priorities.
    If preventing the greatest number of deaths is the most important goal, society should ensure that those in the groups at high risk become vaccinated first, followed by those aged ≥65 years who have no preexisting medical conditions making them more susceptible to complications from influenza.
    However, if maximizing economic returns is the highest priority, persons aged ≤64 years, regardless of risk, should be vaccinated first.
Appendix
Table 1. Estimate of age distribution of cases and percentage of population at high risk used to examine the impact of pandemic influenza in the United States
Age group (yrs) Percentage of all casesa
0–19 40.0
20–64 53.1
≥65 6.8
Totalsb 100.0
Age group (yrs) Percentage at high riskc
0–19 6.4
20–64 14.4
≥65 40.0
U.S. averaged 15.4
Table Annotations
a
The actual number of cases will depend upon the assumed gross attack rate.
The distribution of cases was based on lower and upper estimates of age-specific attack rates from the 1918, 1928–29, and 1957 epidemics and pandemics (Ref. 19 in Meltzer, et al.).
b
Totals do not add exactly to 100% because of rounding.
c
Persons are categorized as being at high risk if they have preexisting medical conditions that make them more susceptible to influenza-related complications.
The percentages of age groups at high risk were obtained from the Working Group on Influenza Pandemic Preparedness and Emergency Response (GrIPPE, unpub. data).
The Advisory Committee on Immunization Practices estimates that 27–31 million persons aged <65 years are at high risk for influenza-associated complications (Ref. 17 in Meltzer, et al.).
d
Average is an age-weighted average, using each age group's proportion of the total U.S. population.
Table 2. Variables used to define distribution of disease outcomes of those with clinical casesa of influenza
  Rates per 1,000 personsb
Variable Lower Most likely Upper
Outpatient visits      
  Not at high risk      
    0–19 yrs 165   230
    20–64 yrs 40   85
    ≥65 yrs 45   74
  High risk      
    0–19 yrs 289   403
    20–64 yrs 70   149
    ≥65 yrs 79   130
Hospitalizations      
  Not at high risk      
    0–19 yrs 0.20 0.50 2.90
    20–64 yrs 0.18   2.75
    ≥65 yrs 1.50   3.00
  High risk      
    0–19 yrs 2.10 2.90 9.00
    20–64 yrs 0.83   5.14
    ≥65 yrs 4.00   13.00
Deaths      
  Not at high risk      
    0–19 yrs 0.014 0.024 0.125
    20–64 yrs 0.025 0.037 0.090
    ≥65 yrs 0.280 0.420 0.540
  High risk      
    0–19 yrs 0.126 0.220 7.650
    20–64 yrs 0.100   5.720
    ≥65 yrs 2.760   5.630
Table Annotations
a
Clinical cases are defined as cases in persons with illness sufficient to cause an economic impact. The number of persons in a particular age group who will be ill but will not seek medical care, is calculated as:
Number illAge = ( PopulationAge x gross attack rate ) ( deathsAge + hospitalizationsAge + outpatientsAge )
The numbers of outpatient visits, hospitalizations, and deaths are calculated by using the rates presented in this table.
b
For Monte Carlo simulations, rates are presented as lower and upper for uniform distributions, and lower, most likely, and upper for triangular distributions (Ref. 18 in Meltzer, et al.).
Sources: 3, 6, 11, 19–29, and Appendix II in Meltzer, et al.
Table 3. Input variables used to calculate the economic impact (direct and indirect costs) of health outcomes attributed to an influenza pandemic in the United States (in 1995 US$)
Outcome category
   Item
Type of
cost
Age group (yrs) Sources
0–19 20–64 ≥65
Deaths          
  Average age (yrs)   9 35 74 Assumed
  PV earnings lost ($)a Indirect 1,016,101 1,037,673 65,837 16, 30
  Most likely ±min or max hospital costs ($)b Direct 3,435 ±2,632 7,605 ±3,888 8,309 ±3,692 MarketScan Database; 31
  Subtotal ($)c   1,019,536 1,045,278 74,146  
Hospitalizations          
  Most likely ±min or max hospital costs ($)b Direct 2,936 ±2,099 6,016 ±2,086 6,856 ±3,200 MarketScan Database; 31
  Most likely ±min or max net pay for outpatient visits ($)d Direct 74 ±40 94 ±70 102 ±60 MarketScan Database; 31
  Avg. copayment for outpatient visit ($) Direct 5 4 4 MarketScan Database
  Most likely ±min or net payment for drug claims($)e Direct 26 ±9 42 ±30 41 ±10 MarketScan Database
  Most likely ±min or max days lostf Indirect 5 ±2.7 8 ±4.8 10 ±5.4 MarketScan Database; 31
  Value 1 day lost ($)g Indirect 65 100 or 65 65 30
  Subtotal ($)c   3,366 6,842 7,653  
Outpatient visits          
  Avg. no. visitsh Direct 1.52 1.52 1.52 MarketScan Database
  Most likely ±min or max net payment per visit($)i Direct 49 ±13 38 ±12 50 ±16 MarketScan Database
  Avg. copayment for outpatient visit ($) Direct 5 4 4 MarketScan Database
  Most likely ±min or max per prescription($)j Direct 25 ±18 36 ±27 36 ±22 MarketScan Database
  Avg. prescriptions per visit Direct 0.9 1.8 1.4 MarketScan Database
  Avg. copayment per prescription ($) Direct 3 3 3 MarketScan Database
  Days lost Indirect 2 3 5 4, 5
  Value 1 day lost ($)g Indirect 65 100 65 30
  Subtotal ($)c   300 330 458  
Ill, no medical care sought          
  Days lost Indirect 3 2 5 4, 5
  Value 1 day lost ($)g Indirect 65 100 65 30
  Over-the-counter drugs ($) Direct 2 2 2 Assumed
  Subtotal ($)c   197 202 327  
Table Annotations
a
Average present value (PV), using a 3% discount rate, of expected future lifetime earnings and housekeeping services, weighted by age and gender (Ref. 30 in Meltzer, et al.) and adjusted to 1995 dollars (by multiplying by a factor of 1.07) (Ref. 16 in Meltzer, et al.).
b
Most likely, with ± defining the minimum and maximum costs for a triangular distribution (Ref. 18 in Meltzer, et al.) for Monte Carlo analysis (Refs. 13–15 in Meltzer, et al.).
The values were calculated by multiplying cost data from MarketScan Database (The Medstat Group, Ann Arbor, MI) by a hospital cost-to-charge ratio of 0.53.
The latter ratio is a weighted average of the urban and rural (urban = 0.80, rural = 0.20) cost-to-charge ratios calculated by the Health Care Finance Administration for August 1996 (Ref. 31 in Meltzer, et al.).
c
Subtotals are the totals for each category of outcome, using the most likely estimates.
d
Most likely, with minimum and maximum values of net payments for outpatient visits up to 14 days before admission date and up to 30 days after discharge date.
e
Net payment for drug claims associated with outpatient visits up to 14 days before admission and up to 30 days after discharge.
f
Most likely, with ± defining the minimum and maximum days lost due to hospitalization for a triangular distribution (Ref. 18 in Meltzer, et al.) for Monte Carlo analysis (Refs. 13–15 in Meltzer, et al.).
Calculated by using length of stay in hospital data from MarketScan Database (The MEDSTAT Group, Ann Arbor, MI) and adding a total of 1 additional day for convalescence and pre- and post-hospitalization outpatient visits for persons aged 0–19 and 20–64 years.
For persons aged ≥65 years, 2 additional days were added to length of stay in hospital for convalescence and pre- and post-hospitalization outpatient visits.
g
For persons aged 0–19 and ≥65 years, a day lost to influenza was valued as equivalent to an unspecified day (Ref. 30 in Meltzer, et al.), denoting a value for time lost by care givers and family members related to taking care of a patient in these age groups.
For persons aged 20–64 years, 60% of days lost as a result of hospitalizations and related convalescence and pre- and post-hospitalization outpatient visits were valued as day off work ($100/day).
The remaining 40% of days lost were valued as unspecified days ($65/day).
For persons aged 20–64 years, when patients were not hospitalized at any point during their illness (i.e., outpatient status), all days lost were assumed to be days off work ($100/day).
h
The number of visits per episode of influenza is an average across all age groups.
The database indicated that 85% of all patients had fewer than three outpatient visits (average 1.52) (Appendix II in Meltzer, et al.).
i
Most likely, with minimum and maximum values of net payments for outpatient visits without any specified association to hospitalizations.
j
Most likely, with ± defining the minimum and maximum cost per prescription, with the number of prescriptions per visit.
Table 4. Cost of vaccinationa during an influenza pandemic — with specific costs assigned to side effects of vaccination
Item Probability of side effectb Cost of case of side effect
($)b
Lower-cost scenario ($/patient) Upper-cost scenario ($/patient)
Assumed cost of vaccinationa
(excluding side effects)
    18 59
Side effects        
  Mildc 0.0325 94 3.05 3.05
  GBSd 0.000002 100,800 0.20 0.20
  Anaphylaxis 0.000000157 2,490 0.01 0.01
  Total cost per patient     21.26 62.26
Table Annotations
a
The cost of vaccination includes:
  • cost of the vaccine,
  • cost of administering the vaccine,
  • value of time spent by a person traveling to and from the place of vaccination, and
  • patient-associated travel costs.
Included in the costs of the vaccine are any costs associated with the rapid production of a larger-than-usual number of doses and the rapid delivery and correct storage of doses at vaccination sites around the country.
For $18, the costs were assumed to be $10 for vaccine + administration, $4 patient time (half hour), $4 patient travel costs.
For $59, the costs were assumed to be $20 for vaccine + administration (this could include the cost of two doses), $32 patient time (two trips at 2 hours per trip), and $7 patient travel costs.
For comparison, a review of 10 published articles found a range of $5 to $22 per dose of vaccine, with a medium [sic] cost of $14 per dose (Ref. 10 in Meltzer, et al.). Additional details are provided in the Methods section of Meltzer, et al.
These breakdowns are illustrations only of what might be deemed reasonable estimates of time and cost.
Actual costs might vary substantially and will depend on the number of doses needed to achieve a satisfactory protective response, as well as the efficiency of administering vaccinations to millions of persons.
b
Probabilities and average cost of treating each category of side effect were derived from Ref. 3 in Meltzer, et al.
c
Mild side effects include arms sore from vaccination, headaches, and other minor side effects that might require a visit to a physician or might cause the patient to miss 1–2 days of work.
d
GBS = Guillain-Barré syndrome.
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