Literature DB >> 21888783

Estimating effect of antiviral drug use during pandemic (H1N1) 2009 outbreak, United States.

Charisma Y Atkins1, Anita Patel, Thomas H Taylor, Matthew Biggerstaff, Toby L Merlin, Stephanie M Dulin, Benjamin A Erickson, Rebekah H Borse, Robert Hunkler, Martin I Meltzer.   

Abstract

From April 2009 through March 2010, during the pandemic (H1N1) 2009 outbreak, ≈8.2 million prescriptions for influenza neuraminidase-inhibiting antiviral drugs were filled in the United States. We estimated the number of hospitalizations likely averted due to use of these antiviral medications. After adjusting for prescriptions that were used for prophylaxis and personal stockpiles, as well as for patients who did not complete their drug regimen, we estimated the filled prescriptions prevented ≈8,400-12,600 hospitalizations (on the basis of median values). Approximately 60% of these prevented hospitalizations were among adults 18-64 years of age, with the remainder almost equally divided between children 0-17 years of age and adults >65 years of age. Public health officials should consider these estimates an indication of success of treating patients during the 2009 pandemic and a warning of the need for renewed planning to cope with the next pandemic.

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Year:  2011        PMID: 21888783      PMCID: PMC3358088          DOI: 10.3201/eid1709.110295

Source DB:  PubMed          Journal:  Emerg Infect Dis        ISSN: 1080-6040            Impact factor:   6.883


From April 23, 2009, through April 10, 2010, it is estimated that pandemic (H1N1) 2009 virus caused ≈61 million cases of influenza (range 43–89 million cases), ≈270,000 related hospitalizations (range 195,000–403,000 hospitalizations), and ≈12,500 deaths (range 8,900–18,300 deaths) in the United States (). Even before the impact was fully known, the Centers for Disease Control and Prevention (CDC) recommended prompt empiric treatment with influenza antiviral drugs, principally the neuraminidase-inhibiting influenza antiviral drugs oseltamivir and zanamivir, of persons with suspected or confirmed influenza and who also met >1 of the following conditions: 1) illness that required hospitalization; 2) progressive, severe, or complicated illness, regardless of previous health status; and 3) risk for severe disease (e.g., patients with asthma, neurologic and neurodevelopmental conditions; chronic lung or heart disease; blood, endocrine, kidney, liver, and metabolic disorders; pregnancy; and those who were old or young) (). The primary goal of these recommendations was to reduce the number and severity of pandemic (H1N1) 2009 cases, especially hospitalizations. We present estimates of the number of pandemic (H1N1) 2009–related hospitalizations, by age group, averted because of use of antiviral drugs given to treat clinical cases of influenza. These results can be used by public health policy makers to plan and prepare for the next pandemic. For example, these estimates can be used to help evaluate the policy option of replenishing state and federal influenza antiviral drug stockpiles

Methods

We developed a spreadsheet-based model to calculate the number of pandemic (H1N1) 2009–related hospitalizations averted because of treatment with the neuraminidase-inhibiting influenza antiviral drugs oseltamivir and zanamivir (Technical Appendix). The risk for hospitalization (and thus potential benefit from antiviral drugs) differed by age groups (). Therefore, we estimated the reduced number of hospitalizations separately for 3 groups: persons 0–17 years of age, 18–64 years of age, and >65 years of age. We calculated the hospitalizations averted by using the following general equation: no. hospitalizations averted (by age group) = [no. prescriptions written – estimated no. written for prophylaxis, stockpiling, or incomplete adherence to drug regimen] × age group–specific risk for hospitalizations caused by pandemic (H1N1) 2009 × age group–specific effectiveness of drugs in preventing hospitalizations.

Prescriptions Filled

We used the number of prescriptions filled for these drugs for weeks ending April 24, 2009, through March 26, 2010 (Table 1), collected from the IMS Health (IMS) Xponent proprietary prescription database (IMS Health, Norwalk, CT, USA) (). This database contains all retail prescriptions filled from a representative sample of 35,000 (73%) of ≈50,000 US-based retail pharmacies, including independent pharmacies, chain pharmacies, pharmacies in discount outlets, pharmacies in food stores, mail order pharmacies, and pharmacy benefit management companies. IMS then proportionately extrapolates their data on the basis of populations served by the included pharmacies to provide weekly estimates of all prescriptions filled in the United States for these drugs. The Xponent database does not track prescriptions filled by in-hospital pharmacies. Therefore, in-hospital prescriptions are not part of our calculations.
Table 1

Number of pandemic (H1N1) 2009 cases versus number of influenza antiviral prescriptions filled during pandemic (H1N1) 2009 outbreak, United States, April 24, 2009–March 26, 2010*

Week†Mid-level estimate of cases‡Filled influenza antiviral prescriptions
OseltamivirZanamivirTotal
2009 Apr–Jul3,052,7681,243,82769,5131,313,340
2009 Aug
1,605,760
342,386
11,645
354,031
35626,256146,2825,097151,379
361,675,630234,2117,171241,382
371,302,846265,6267,892273,518
381,508,514331,0608,735339,795
392,319,691383,7599,981393,740
404,461,542435,54611,625447,171
416,549,205471,32311,226482,549
427,120,298527,36211,218538,580
436,297,210671,74112,046683,787
445,899,647640,8879,306650,193
455,013,181537,7816,338544,119
463,350,286386,5694,863391,432
471,767,166273,0923,039276,131
481,020,606152,4821,857154,339
49804,901133,9981,782135,780
50646,35899,5651,348100,913
51612,20488,7181,33890,056
52619,08064,8071,01065,817
1418,80356,5691,00957,578
2520,39050,64298151,651
3516,95850,3261,05751,307
4356,40044,7701,04845,827
5493,44843,7571,21144,805
6322,62342,4741,25143,685
7312,32743,8091,22845,060
8281,98647,1461,48748,374
9245,70748,6711,49450,158
10288,21547,2611,58748,755
11225,44833,8671,04334,910
12
312,575
26,072
730
26,802
Total60,548,0307,966,386211,1568,177,542

*IMS Health Xponent database () includes 57,544 oseltamivir prescriptions and 877 zanamivir prescriptions for week 53. Because the Centers for Disease Control and Prevention only reports 52 weeks for 2009, we removed week 53 from the IMS data set (IMS, Norwalk, CT, USA).
†Estimates of cases for April–August 2009 are not available on a weekly basis.
‡Mid-level weekly cases estimated from () and www.cdc.gov/h1n1flu/estimates_2009_h1n1.htm.

*IMS Health Xponent database () includes 57,544 oseltamivir prescriptions and 877 zanamivir prescriptions for week 53. Because the Centers for Disease Control and Prevention only reports 52 weeks for 2009, we removed week 53 from the IMS data set (IMS, Norwalk, CT, USA).
†Estimates of cases for April–August 2009 are not available on a weekly basis.
‡Mid-level weekly cases estimated from () and www.cdc.gov/h1n1flu/estimates_2009_h1n1.htm. The IMS Xponent database captures all filled prescriptions related to influenza antiviral drugs within its sample pharmacies. However, it does not identify the source of the drugs. During 2009, there were 2 main potential supplies for the antiviral drugs—the regular commercial supply system and state and federal government-maintained drug stockpiles. The IMS database does not track medications dispensed from public domains, such as public health departments. Furthermore, the federal and state stockpiles of antiviral drugs were meant to supplement the commercial supply chain in times of drug shortages anticipated to occur during a pandemic emergency. As of August 2010, the estimated total amount of antiviral drugs managed by states throughout the pandemic was 38 million treatment regimens. This estimate includes antiviral drugs purchased by states (26 million treatment regimens) plus ≈12 million treatment regimens distributed early in the pandemic to states from the CDC Strategic National Stockpile (SNS). Preliminary reports from state public health departments to the CDC show that most SNS product was either retained by the health departments or deployed at the local level (to dispensing sites such as drug stores and health departments). Sites received directions that the SNS-provided supplies were to be dispensed if commercial supplies could not keep up with demand or used to treat uninsured or underinsured persons who could otherwise not afford treatment. Preliminary data reported to CDC through SNS show that minimum quantities of stockpiled antiviral drugs were actually dispensed to patients. Because the commercial supply chain for antiviral drugs remained relatively robust, most states did not need to use stockpiled antiviral drugs. Therefore, we did not include any estimates of impact on antiviral drugs dispensed from these government stockpiles.

Prescriptions by Age Group

IMS collects for filled prescriptions deidentified data regarding age of patient from the pharmacy systems. We thus divided the total number of prescriptions given into 3 age groups (0–17 years, 18–64 years, >65 years) by using age-specific data from IMS that covered prescriptions written for oseltamivir from October 9, 2009, through March 26, 2010. The percentages were as follows: 0–17 years, 38.6%; 18–64 years, 53.4%; >65 years, 5.3% (Table 2). Note that ≈3% of prescriptions filled during this period did not have the age of the patient recorded. Therefore, we did not include those prescriptions in our analysis.
Table 2

Input values used to estimate influenza antiviral drug–related reduction in hospitalizations during pandemic (H1N1) 2009 outbreak in the United States, April 24, 2009–March 26, 2010

InputInitial valueSources
Distribution of prescriptions by patient age group, y*IMS Health Xponent database (3)
0–1738.6%
18–6453.4%
>65
5.3%
Prescriptions filled for prophylaxis†10%Assumption: Some prescriptions were written to prevent infection and disease without presentation of symptoms.
Prescriptions for patients who failed to adhere to drug regimen or used for personal stockpiles
20%
Assumption: Not all patients will adhere with the drug regimen as prescribed. Also, some prescriptions were for personal stockpiles
Antiviral drug effectiveness against hospitalization, by age group, y‡Literature review (see Table 3)
0–1722%–32%
18–6434%–50%
>65
30%–50%
Median (range) risk for hospitalization, given pandemic (H1N1) 2009–related illness, by age group, y§Reed et al. (4)
0–170.0038 (0.00314–0.00428)
18–640.00496 (0.0041–0.00558)
>650.0155 (0.0128–0.0174)

*Age group–based distribution of prescriptions based on IMS (IMS Health, Norwalk, CT, USA) that covered prescriptions written for oseltamivir (only) from October 9, 2009, through March 26, 2010.
†These inputs were subjected to sensitivity analyses (see Table 4).
‡Effectiveness estimate assumes that the patient follows the drug regimen, i.e., these estimates do not allow for those who do not take the complete course. Failure to follow prescribed drug regimen was assumed to have 0% effect on reducing risk of hospitalization. This assumption was accounted for in a separate input.
§Risk of per-person hospitalization, given symptomatic illness caused by pandemic (H1N1) 2009 virus.

*Age group–based distribution of prescriptions based on IMS (IMS Health, Norwalk, CT, USA) that covered prescriptions written for oseltamivir (only) from October 9, 2009, through March 26, 2010.
†These inputs were subjected to sensitivity analyses (see Table 4).
‡Effectiveness estimate assumes that the patient follows the drug regimen, i.e., these estimates do not allow for those who do not take the complete course. Failure to follow prescribed drug regimen was assumed to have 0% effect on reducing risk of hospitalization. This assumption was accounted for in a separate input.
§Risk of per-person hospitalization, given symptomatic illness caused by pandemic (H1N1) 2009 virus.
Table 4

Estimated number of influenza antiviral drugs prescribed for treatment, after adjusting for prescriptions for prophylaxis, nonadherence, and personal stockpiling, pandemic (H1N1) 2009 outbreak, United States

Influenza antiviral drug*No. prescriptions, by patient age group†
Total
0–17 y18–64 y>65 y
Oseltamivir2,152,9152,979,711297,7005,430,326
Zanamivir
57,065
78,980
7,891
143,936
Subtotal‡2,209,9803,058,690305,5915,574,262

*These antiviral drugs were prescribed in a variety of forms (e.g., capsules, tablets, syrup, and inhaled powder). The estimated numbers came from the IMS database (), which records ≈73% of all prescriptions filled by >50,000 US-based retail pharmacies. IMS then proportionately extrapolates their data, based on populations served by pharmacies, to provide weekly estimates of all prescriptions filled in the U.S. for these drugs. The IMS Health Xponent database does not cover in-hospital prescriptions.
†These subtotals, by age group, are the estimates of prescriptions filled to treat pandemic (H1N1) 2009–related clinical illness, after removing the prescriptions filled for prophylaxis and for patients who failed to adhere to drug regimen or prescriptions filled for personal stockpiles (see Table 1). The total number of prescriptions filled, before adjustments, was 8,177,542 (Table 1). Note that ≈3% of prescriptions filled during this period did not have age of patient recorded, and we omitted those prescriptions from our calculations.
‡These subtotals, by age group, were the estimates used to calculate the hospitalizations averted as shown in Table 5.

Prescriptions over Time

We plotted the total number of prescriptions filled per week, from the IMS database, against the weekly number of estimated pandemic cases for April 24, 2009, through March 26, 2010. Estimates of cases for April through the end of July 2009 are not available on a weekly basis. Thus, all cases were combined into a single estimate for that period (). We combined for the same period all filled prescriptions and directly compared cases and prescriptions. A notable divergence in the correlation between plots of cases and prescriptions over time would indicate the possibility of prescriptions being filled for reasons other than the immediate treatment of influenza-related illness (e.g., stockpiling or use for prophylaxis).

Percentage of Prescriptions Written for Prophylaxis

We assumed in the absence of any data that 10% of all prescriptions for these antiviral drugs were written for prophylaxis. This assumption was subject to sensitivity analyses (described below). We further assumed that such prescriptions essentially had no impact on reduction of hospitalizations (Table 2).

Adherence to Drug Regimen and Stockpiling

We also assumed that a total of 20% of all prescriptions were for either personal stockpiles (i.e., not written for a clinically ill patient at time of prescription) or patients who did not sufficiently follow the recommended drug regimen so that the prescription had no impact on risk of hospitalization caused by nonadherence (Table 2). A study conducted in the United Kingdom during the (H1N1) 2009 pandemic found that 76%–80% of the patients did complete the full course of prescribed antiviral drugs (). Another study among schoolchildren in London, UK, that examined adherence among those offered oseltamivir for prophylaxis found that 89% actually took >1 dose and 66% of this group completed (or said they would complete) a full 10-day prophylaxis course (). One of the drug effectiveness studies that we reviewed (discussed below) and used for model input values asked patients to self-record adherence; it found that ≈90% of enrolled patients were fully compliant (). Our assumption that 20% of prescriptions were for either stockpiling or nonadherence was subject to sensitivity analyses (described below). This allowance for nonadherence also acts as a proxy for those who may have started the treatment too late. To maximize drug effectiveness in alleviating the duration of symptoms, it is recommended that antiviral drug treatment start <48 hours after onset of clinical symptoms ().

Risk for Hospitalization Given Clinical Case of Pandemic (H1N1) 2009

We used the risk for hospitalization by age group, given clinical illness caused by pandemic (H1N1) 2009, from Reed et al. () (Table 2). We identified 17 published studies that evaluated the effectiveness of neuraminidase inhibitors given influenza-induced clinical illness (7,8–21; Table 3). Although many studies were random placebo-controlled trials, the studies did not use hospitalizations averted as a measured endpoint (,–). We identified only 4 studies that specifically evaluated the impact of the antiviral drugs on risk for hospitalization, given clinical illness. One study provided an estimate of 50% reduction in the probability of influenza-specific hospitalizations (no confidence interval was published) (). Three retrospective studies, using health insurance claims data, reported effectiveness in reducing hospitalizations (any cause) that ranged from 22% to 59%, with some variation by age (–). For each age group, we used lower and upper estimates of effectiveness, from a lower estimate of 22% reduction for children 0–17 years to an upper estimate of 50% for adults (Table 2).
Table 3

Literature review of effectiveness of neuraminidase inhibitors in preventing influenza-related hospitalizations*

DrugStudy typePopulationReduction in hospitalization point estimate (95% CI)Reference
ZanamivirRandomized, double-blind, placebo-controlled trial455 patients residing in Australia, New Zealand, and South Africa age >12 y with influenza-like symptoms of <36 hours’ durationNA (14)
OseltamivirOpen-label, multicenter international study1,426 patients (age range 12–70 y) seeking treatment <48 h after onset of influenza symptomsNA (15)
OseltamivirRetrospective cohort analysisThe oseltamivir and untreated control groups each included 36,751 eligible patients22%;
HR 0.78 (0.67–0.91) (8);
claims data
OseltamivirRetrospective cohort studyOseltamivir and untreated propensity matched control groups each included 45,751 eligible patients30% any cause;
OR 0.71 (0.62–0.83) (9);
insurance claims data
ZanamivirRandomized, double-blind studies in 38 centers in North America and 32 centers in Europe during the 1994–95 influenza season417 adults with influenza-like illness of
<48 hours' duration were randomly assigned to 1 of 3 treatmentsNA (16)
Amantadine/ rimantadineTwo randomized, double-blind, placebo-controlled trials≈80 patients with laboratory-documented influenza A virus (H3N2) illness <2 days' durationNA (13)
OseltamivirCombined analysis of 10 prospective, placebo controlled, double-blind trials3,564 persons (age range 13–97 y) with influenza-like illness enrolled in 10 placebo-controlled, double-blind trials of oseltamivir treatment59% any cause reduction; 50% influenza, at risk patients (7)
ZanamivirRetrospective pooled analysis of data; all studies were randomized, double-blind, and placebo-controlled with 21–28 day follow-up2,751 patients were recruited; of these,
321 (12%) were considered high risk
and 154 were randomized to receive zanamivirNA (17)
ZanamivirRandomized, double-blind, placebo-controlled trial in primary care and hospital clinics356 patients age >12 y were recruited within
2 d of onset of typical influenza symptomsNA (12)
ZanamivirPooled analyses of secondary endpointsNA (18)
OseltamivirRandomized controlled trial726 healthy nonimmunized adults with febrile influenza-like illness of <36 hours’ durationNA (19)
OseltamivirRetrospective cohort study9,090 patients with diabetes and influenza30% any cause;
RR 0.70 (0.52–0.94) (10);
insurance claims data
OseltamivirRetrospective cohort studyThe oseltamivir and untreated control groups each included 36,751 eligible patients, 50% with a claim for oseltamivir, 50% without38%;
RR 0.62 (0.52–0.74) (11);
insurance claims data
OseltamivirDouble-blind, stratified, randomized, placebo-controlled, multicenter trialHealthy adults (age range 18–65 y) who sought treatment <36 h after onset of influenza symptomsNA (20)
OseltamivirRandomized, double blind, placebo-controlled studyChildren age 1–12 y with fever (>100°F [>38°C]) and a history of cough or coryza
<48 hours’ durationNA (21)

*CI, confidence interval; NA, not applicable; HR, hazard ratio; OR, odds ratio; RR, relative risk.

*CI, confidence interval; NA, not applicable; HR, hazard ratio; OR, odds ratio; RR, relative risk.

Calculating Ranges and Sensitivity Analyses

For each level of antiviral effectiveness (lower, upper), and for each age group, we calculated the median and lower and upper estimates of hospitalizations averted. We also conducted sensitivity analyses by altering from 0% to 30% the assumed percentages of prescriptions written for prophylaxis, personal stockpiles, and patients who did not adhere to the drug regimen.

Results

Pandemic influenza vaccine became available in week 40 of 2009 (near the peak of cases). We hypothesized that before this date is when doctors would have been most likely to try to protect patients by prescribing prophylactic courses of antiviral drugs. However, the plot of the prescription data against estimated cases over time shows a close correlation between the occurrence of pandemic (H1N1) 2009 clinical cases and filled prescriptions (Table 1; Figure). This comparison suggests that antiviral drugs were mostly prescribed to treat the occurrence of clinical cases of pandemic (H1N1) 2009.
Figure

Number of estimated influenza cases and filled prescriptions for influenza antiviral drugs during pandemic (H1N1) 2009 in the United States, September 2009–March 2010. The estimates of cases for April–August 2009 are not available on a weekly basis. During April 12–July 23, 2009, there were 3.1 million cases and 1.3 million prescriptions filled for influenza antiviral drugs. For the month of August 2009, there were 1.6 million cases and 354,000 prescriptions filled for influenza antiviral drugs. Estimates of cases from Shrestha et al. (); number of prescriptions filled from the IMS Health Xponent database ().

Number of estimated influenza cases and filled prescriptions for influenza antiviral drugs during pandemic (H1N1) 2009 in the United States, September 2009–March 2010. The estimates of cases for April–August 2009 are not available on a weekly basis. During April 12–July 23, 2009, there were 3.1 million cases and 1.3 million prescriptions filled for influenza antiviral drugs. For the month of August 2009, there were 1.6 million cases and 354,000 prescriptions filled for influenza antiviral drugs. Estimates of cases from Shrestha et al. (); number of prescriptions filled from the IMS Health Xponent database (). The total number of prescriptions filled before adjustments was 8.2 million (Table 1). After removing the prescriptions presumed filled for prophylaxis and for patients who failed to adhere to the drug regimen or had prescriptions filled for personal stockpiles, 5.7 million prescriptions were filled that may have reduced hospitalizations (Table 4). Most (97%) were filled for oseltamivir, and ≈55% of all prescriptions filled were for persons 18–64 years of age, and ≈40% were filled for children 0–17 years of age. *These antiviral drugs were prescribed in a variety of forms (e.g., capsules, tablets, syrup, and inhaled powder). The estimated numbers came from the IMS database (), which records ≈73% of all prescriptions filled by >50,000 US-based retail pharmacies. IMS then proportionately extrapolates their data, based on populations served by pharmacies, to provide weekly estimates of all prescriptions filled in the U.S. for these drugs. The IMS Health Xponent database does not cover in-hospital prescriptions.
†These subtotals, by age group, are the estimates of prescriptions filled to treat pandemic (H1N1) 2009–related clinical illness, after removing the prescriptions filled for prophylaxis and for patients who failed to adhere to drug regimen or prescriptions filled for personal stockpiles (see Table 1). The total number of prescriptions filled, before adjustments, was 8,177,542 (Table 1). Note that ≈3% of prescriptions filled during this period did not have age of patient recorded, and we omitted those prescriptions from our calculations.
‡These subtotals, by age group, were the estimates used to calculate the hospitalizations averted as shown in Table 5.
Table 5

Estimates of hospitalizations averted, by age group, assuming lower and upper estimates of influenza antiviral drug effectiveness, United States, 2009–2010*

Drug effectiveness estimateNo. hospitalizations averted, by patient age group, y, median (range)
0–1718–64>65Total
Lower1,848 (1,527–2,081)5,158 (4,264–5,803)1,421 (1,171–1,595)8,427 (6,961–9,479)
Upper2,687 (2,221–3,027)7,586(6,270–8,534)2,368 (1,951–2,659)12,641 (10,442–14,219)

*Estimates of antiviral drug effectiveness are shown Table 2 (source, Table 1). Lower, median, and upper estimates are generated by using the range of age-specific probabilities of hospitalization, given influenza-related clinical illness (Table 2).

We estimated that the median number of hospitalizations averted ranged from 8,427 (lower 6,961; upper 9,479) to 12,641 (lower 10,442; upper 14,219) (Table 5). Approximately 60% of averted hospitalizations were among persons 18–64 years old. The estimated hospitalizations averted in children and adults >65 years of age (Table 5) were similar. Although adults >65 years of age received only ≈5% of filled prescriptions (Table 4), these prescriptions had a relatively substantial impact in averting hospitalizations because the risk for hospitalization is higher in this age group than the other risk groups (Table 2). *Estimates of antiviral drug effectiveness are shown Table 2 (source, Table 1). Lower, median, and upper estimates are generated by using the range of age-specific probabilities of hospitalization, given influenza-related clinical illness (Table 2). Doubling the assumed percentages of filled prescriptions for prophylaxis and personal stockpiles/nonadherence from 30% to 60% (i.e., a 100% increase) produced only a 40% reduction in median hospitalizations averted, from ≈12,600 to 7,200 (Table 6). Thus, the major factors influencing hospitalizations averted were total prescriptions filled and (assumed) effectiveness of the drugs in preventing hospitalizations.
Table 6

Sensitivity analysis, altering the assumed percentage of prescriptions written for prophylaxis, nonadherence to drug regimen, and stockpiling, United States 2009–2010*

% Prescriptions written for prophylaxis% Prescriptions resulting in nonadherence + stockpilingNet no. prescriptions used to treat clinically diagnosed influenzaMedian no. hospitalizations averted, by patient age group, y†
0–1718–64>65Total
008,177,5423,83910,8373,38318,059
10106,542,0343,0718,6692,70714,447
>10>205,724,2792,6877,5862,36812,641
20204,906,5252,3036,5022,03010,835
20304,088,7711,9205,4181,6929,030
30303,271,0171,5364,3351,3537,224

*Baseline data used displays 10% for prophylaxis and 20% for personal stockpiling and non-adherence. This baseline assumption was used to generate results in Table 5.
†Results of sensitivity analysis were calculated by using the upper median estimates of antiviral effectiveness in preventing hospitalization among the clinically ill (Table 1, Table 2).

*Baseline data used displays 10% for prophylaxis and 20% for personal stockpiling and non-adherence. This baseline assumption was used to generate results in Table 5.
†Results of sensitivity analysis were calculated by using the upper median estimates of antiviral effectiveness in preventing hospitalization among the clinically ill (Table 1, Table 2).

Discussion

The close correlation between estimated pandemic influenza cases and filled prescriptions (Figure) can be used as evidence that antiviral drugs were mostly used to treat those who were clinically ill (i.e., recommendations regarding use were essentially followed). Restricting the use of antiviral drugs to treating the clinically ill meant that preventing clinical cases from deteriorating into severe cases requiring hospitalizations was likely to have been among the major effects of antiviral drug use. By our estimates, this strategy worked; ≈8,000–13,000 hospitalizations were averted (Table 5). This reduction is equivalent to ≈4–5% of the total estimated pandemic (H1N1) 2009–related hospitalizations (). We found no other studies with which to compare our methods and results. We compared the accuracy of the IMS database using unpublished data from the Behavioral Risk Factor Surveillance System (BRFSS), conducted in 49 states (excluding Vermont, the District of Columbia, and Puerto Rico). From September 1, 2009, through March 31, 2010, adults (>18 years old) responding to the BRFSS telephone survey were asked whether they had influenza-like illness (ILI) (defined as having had a fever with cough or sore throat) in the month preceding the interview. They were also asked if they sought medical care for their ILI condition and if they were prescribed antiviral drugs to treat their illnesses. Extrapolating the results to the national level in the period covered by the survey, we found that ≈54 million adults reported having ILI symptoms. Of those who reported having ILI and sought medical care, 4.1 million adults reported they were prescribed influenza antiviral drugs (oseltamivir or zanamivir) during August 2009–March 2010. The IMS database recorded 6.86 million prescriptions in the same period (Table 1); ≈40% for those 0–17 years of age (Table 2), leaving ≈4.1 million filled prescriptions for adults. This estimate is close to the number recorded by the BRFSS survey and further supports the idea that few prescriptions were for prophylaxis or personal stockpiles. There are many limitations to this study; the biggest is the uncertainty regarding the effectiveness of the drugs in preventing hospitalizations. The effectiveness of the drugs in reducing risk for hospitalization caused by pandemic (H1N1) 2009 may vary considerably from estimates reported for nonpandemic strains of influenza virus. The data are also limited in that we cannot verify if those persons who filled a prescription were actually clinically ill from pandemic (H1N1) 2009 or to what extent they adhered to the drug regimen. We addressed this issue by allowing a wide range in drug effectiveness and a relatively large percentage of prescriptions filled for conditions other than direct treatment of pandemic (H1N1) 2009. We were unable, because the available literature did not contain sufficiently reliable estimates of effectiveness of antiviral drugs against death, to estimate the number of deaths averted by treatment with antiviral drugs. Shrestha et al. () estimated that deaths caused by pandemic (H1N1) 2009 were equivalent to 1.5% of children’s hospitalizations and 6% of hospitalizations for persons of all other ages. Assuming that hospitalizations averted generate similar percentages of deaths averted, then the use of antiviral drugs prevented 27–40 deaths in children 0–17 years of age and 395–597 deaths in adults of all ages (using median values of hospitalizations averted; Table 4). If during the next pandemic there is a desire to produce better quality estimates (perhaps even produce estimates at regular intervals during the event), then additional data collection systems must be developed to overcome some of these limitations. For example, measuring the number of prescriptions filled for prophylaxis or personal stockpiles or degree of adherence can only reliably be conducted by interviewing patients and physicians. Improving estimates of impact of filled prescriptions in reducing adverse health outcomes during an event will require a large case–control study. Policy makers will have to determine if the value of such information warrants the investment in such data collection systems. Our results also highlight how the use of influenza antiviral drugs during a pandemic is likely to be beneficial, notably through a presumed reduction in the demand for hospital-based resources. Reduced demand will also reduce costs of hospitalizations. Assuming a cost per influenza-related hospitalization of US$5,000–$7,000 per patient admitted (adjusted to 2009 dollars) (22–26), averted hospitalizations saved ≈$42 million to $88 million (based on median values of hospitalizations averted; Table 4). A detailed cost-effectiveness analysis, including an in-depth consideration of the costs of hospitalizing pandemic (H1N1) 2009 patients, is the subject of a separate analysis. If the next influenza pandemic causes greater numbers of severe cases and hospitalizations than in 2009, there may be an increased demand for antiviral drugs for treatment and prophylaxis. Such increased demand could overwhelm the existing commercial distribution chains. Therefore, public health officials should consider these estimates as an indication of success of treating patients during the 2009 pandemic and a warning for the need for renewed planning to cope with the next pandemic.

Technical Appendix

Estimating the impact of antiviral usage during 2009 influenza A (H1N1) pandemic.
  23 in total

1.  Effects of adverse events on the projected population benefits and cost-effectiveness of using live attenuated influenza vaccine in children aged 6 months to 4 years.

Authors:  Lisa A Prosser; Martin I Meltzer; Anthony Fiore; Scott Epperson; Carolyn B Bridges; Virginia Hinrichsen; Tracy A Lieu
Journal:  Arch Pediatr Adolesc Med       Date:  2010-10-04

2.  High costs of influenza: Direct medical costs of influenza disease in young children.

Authors:  Gerry Fairbrother; Amy Cassedy; Ismael R Ortega-Sanchez; Peter G Szilagyi; Kathryn M Edwards; Noelle-Angelique Molinari; Stephanie Donauer; Diana Henderson; Sandra Ambrose; Diane Kent; Katherine Poehling; Geoffrey A Weinberg; Marie R Griffin; Caroline B Hall; Lyn Finelli; Carolyn Bridges; Mary Allen Staat
Journal:  Vaccine       Date:  2010-05-31       Impact factor: 3.641

3.  Oral oseltamivir treatment of influenza in children.

Authors:  R J Whitley; F G Hayden; K S Reisinger; N Young; R Dutkowski; D Ipe; R G Mills; P Ward
Journal:  Pediatr Infect Dis J       Date:  2001-02       Impact factor: 2.129

4.  Cost of treating influenza in emergency department and hospital settings.

Authors:  F M Cox; M M Cobb; W Q Chua; T P McLaughlin; L J Okamoto
Journal:  Am J Manag Care       Date:  2000-02       Impact factor: 2.229

5.  Effect of zanamivir on duration and resolution of influenza symptoms.

Authors:  A S Monto; A B Moult; S J Sharp
Journal:  Clin Ther       Date:  2000-11       Impact factor: 3.393

6.  Efficacy and safety of the oral neuraminidase inhibitor oseltamivir in treating acute influenza: a randomized controlled trial. US Oral Neuraminidase Study Group.

Authors:  J J Treanor; F G Hayden; P S Vrooman; R Barbarash; R Bettis; D Riff; S Singh; N Kinnersley; P Ward; R G Mills
Journal:  JAMA       Date:  2000-02-23       Impact factor: 56.272

7.  Efficacy and safety of oseltamivir in treatment of acute influenza: a randomised controlled trial. Neuraminidase Inhibitor Flu Treatment Investigator Group.

Authors:  K G Nicholson; F Y Aoki; A D Osterhaus; S Trottier; O Carewicz; C H Mercier; A Rode; N Kinnersley; P Ward
Journal:  Lancet       Date:  2000-05-27       Impact factor: 79.321

8.  Zanamivir for the treatment of influenza A and B infection in high-risk patients: a pooled analysis of randomized controlled trials.

Authors:  J Lalezari; K Campion; O Keene; C Silagy
Journal:  Arch Intern Med       Date:  2001-01-22

9.  Clinical efficacy and safety of the orally inhaled neuraminidase inhibitor zanamivir in the treatment of influenza: a randomized, double-blind, placebo-controlled European study.

Authors:  M J Mäkelä; K Pauksens; T Rostila; D M Fleming; C Y Man; O N Keene; A Webster
Journal:  J Infect       Date:  2000-01       Impact factor: 6.072

10.  Early administration of oral oseltamivir increases the benefits of influenza treatment.

Authors:  F Y Aoki; M D Macleod; P Paggiaro; O Carewicz; A El Sawy; C Wat; M Griffiths; E Waalberg; P Ward
Journal:  J Antimicrob Chemother       Date:  2003-01       Impact factor: 5.790

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  15 in total

1.  Estimating the United States demand for influenza antivirals and the effect on severe influenza disease during a potential pandemic.

Authors:  Justin J O'Hagan; Karen K Wong; Angela P Campbell; Anita Patel; David L Swerdlow; Alicia M Fry; Lisa M Koonin; Martin I Meltzer
Journal:  Clin Infect Dis       Date:  2015-05-01       Impact factor: 9.079

2.  Timely Antiviral Administration During an Influenza Pandemic: Key Components.

Authors:  Lisa M Koonin; Anita Patel
Journal:  Am J Public Health       Date:  2018-09       Impact factor: 9.308

Review 3.  Neuraminidase inhibitors for influenza: a review and public health perspective in the aftermath of the 2009 pandemic.

Authors:  Charles R Beck; Rachel Sokal; Nachiappan Arunachalam; Richard Puleston; Anna Cichowska; Anthony Kessel; Maria Zambon; Jonathan S Nguyen-Van-Tam
Journal:  Influenza Other Respir Viruses       Date:  2013-01       Impact factor: 4.380

4.  Neuraminidase inhibitor therapy in a military population.

Authors:  Mary P Fairchok; Wei-Ju Chen; John C Arnold; Christina Schofield; Patrick J Danaher; Erin A McDonough; Martin Ottolini; Deepika Mor; Michelande Ridore; Timothy H Burgess; Eugene V Millar
Journal:  J Clin Virol       Date:  2015-03-24       Impact factor: 3.168

5.  Diagnostic Accuracy of the Quidel Sofia Rapid Influenza Fluorescent Immunoassay in Patients with Influenza-like Illness: A Systematic Review and Meta-analysis.

Authors:  Jonghoo Lee; Jae-Uk Song; Yee Hyung Kim
Journal:  Tuberc Respir Dis (Seoul)       Date:  2021-05-13

6.  Public health management of antiviral drugs during the 2009 H1N1 influenza pandemic: a survey of local health departments in California.

Authors:  Jennifer C Hunter; Daniela C Rodríguez; Tomás J Aragón
Journal:  BMC Public Health       Date:  2012-01-25       Impact factor: 3.295

7.  Assessing the use of antiviral treatment to control influenza.

Authors:  S C Kramer; S Bansal
Journal:  Epidemiol Infect       Date:  2014-10-02       Impact factor: 4.434

Review 8.  Effectiveness of neuraminidase inhibitors in reducing mortality in patients admitted to hospital with influenza A H1N1pdm09 virus infection: a meta-analysis of individual participant data.

Authors:  Stella G Muthuri; Sudhir Venkatesan; Puja R Myles; Jo Leonardi-Bee; Tarig S A Al Khuwaitir; Adbullah Al Mamun; Ashish P Anovadiya; Eduardo Azziz-Baumgartner; Clarisa Báez; Matteo Bassetti; Bojana Beovic; Barbara Bertisch; Isabelle Bonmarin; Robert Booy; Victor H Borja-Aburto; Heinz Burgmann; Bin Cao; Jordi Carratala; Justin T Denholm; Samuel R Dominguez; Pericles A D Duarte; Gal Dubnov-Raz; Marcela Echavarria; Sergio Fanella; Zhancheng Gao; Patrick Gérardin; Maddalena Giannella; Sophie Gubbels; Jethro Herberg; Anjarath L Higuera Iglesias; Peter H Hoger; Xiaoyun Hu; Quazi T Islam; Mirela F Jiménez; Amr Kandeel; Gerben Keijzers; Hossein Khalili; Marian Knight; Koichiro Kudo; Gabriela Kusznierz; Ilija Kuzman; Arthur M C Kwan; Idriss Lahlou Amine; Eduard Langenegger; Kamran B Lankarani; Yee-Sin Leo; Rita Linko; Pei Liu; Faris Madanat; Elga Mayo-Montero; Allison McGeer; Ziad Memish; Gokhan Metan; Auksė Mickiene; Dragan Mikić; Kristin G I Mohn; Ahmadreza Moradi; Pagbajabyn Nymadawa; Maria E Oliva; Mehpare Ozkan; Dhruv Parekh; Mical Paul; Fernando P Polack; Barbara A Rath; Alejandro H Rodríguez; Elena B Sarrouf; Anna C Seale; Bunyamin Sertogullarindan; Marilda M Siqueira; Joanna Skręt-Magierło; Frank Stephan; Ewa Talarek; Julian W Tang; Kelvin K W To; Antoni Torres; Selda H Törün; Dat Tran; Timothy M Uyeki; Annelies Van Zwol; Wendy Vaudry; Tjasa Vidmar; Renata T C Yokota; Paul Zarogoulidis; Jonathan S Nguyen-Van-Tam
Journal:  Lancet Respir Med       Date:  2014-03-19       Impact factor: 30.700

Review 9.  Impact of neuraminidase inhibitor treatment on outcomes of public health importance during the 2009-2010 influenza A(H1N1) pandemic: a systematic review and meta-analysis in hospitalized patients.

Authors:  Stella G Muthuri; Puja R Myles; Sudhir Venkatesan; Jo Leonardi-Bee; Jonathan S Nguyen-Van-Tam
Journal:  J Infect Dis       Date:  2012-11-29       Impact factor: 5.226

10.  Discovering Multi-Scale Co-Occurrence Patterns of Asthma and Influenza with Oak Ridge Bio-Surveillance Toolkit.

Authors:  Arvind Ramanathan; Laura L Pullum; Tanner C Hobson; Christopher G Stahl; Chad A Steed; Shannon P Quinn; Chakra S Chennubhotla; Silvia Valkova
Journal:  Front Public Health       Date:  2015-08-03
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