Buskens, E.

Hak, E.

Meijboom, M.J.

English

To optimally develop or adjust national contingency plans to respond to the next influenza pandemic, we developed a decision type model and estimated the total health burden and direct medical costs during the next possible influenza pandemic in the Netherlands on the basis of health care burden during a regular epidemic. Using an arithmetic decision tree-type model we took into account population characteristics, varying influenza attack rates, health care consumption according to the Dutch health care model and all-cause mortality. Actual direct medical cost estimates were based on the Dutch guidelines for pharmaco-economic evaluation. In the base-case scenario with no preventive measure available and an average influenza attack rate of 30%, 4,958,188 influenza infections, 1,552,687 GP consultations, 83,515 hospitalizations and 173,396 deaths will take place in The Netherlands. The burden is highest in adults aged 20 to 64 years. If minimizing the total mortality and sustaining highest net economic returns is the objective, this group needs to be targeted in interventions. (c) 2006 Elsevier Ltd. All rights reserve

Proceedings - University of Groningen

   University of GroningenModelling the health-economic impact of the next influenza pandemic in The NetherlandsHak, E.; Meijboom, M.J.; Buskens, E.Published in:VaccineIMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite fromit. Please check the document version below.Document VersionPublisher's PDF, also known as Version of recordPublication date:2006Link to publication in University of Groningen/UMCG research databaseCitation for published version (APA):Hak, E., Meijboom, M. J., & Buskens, E. (2006). Modelling the health-economic impact of the next influenzapandemic in The Netherlands. Vaccine, 24(44-46), 6756-6760.CopyrightOther than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of theauthor(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).The publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license.More information can be found on the University of Groningen website: https://www.rug.nl/library/open-access/self-archiving-pure/taverne-amendment.Take-down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons thenumber of authors shown on this cover page is limited to 10 maximum.Download date: 03-06-2022AmtcAwtyi©K1iimettippDoHal0dVaccine 24 (2006) 6756–6760Modelling the health-economic impact of the next influenzapandemic in The NetherlandsE. Hak ∗, M.J. Meijboom, E. BuskensUniversity Medical Center Utrecht, Julius Center for Health Sciences and Primary Care,P.O. Box 85500, 3508 GA Utrecht, The NetherlandsAvailable online 9 June 2006bstractTo optimally develop or adjust national contingency plans to respond to the next influenza pandemic, we developed a decision typeodel and estimated the total health burden and direct medical costs during the next possible influenza pandemic in the Netherlands onhe basis of health care burden during a regular epidemic. Using an arithmetic decision tree-type model we took into account populationharacteristics, varying influenza attack rates, health care consumption according to the Dutch health care model and all-cause mortality.ctual direct medical cost estimates were based on the Dutch guidelines for pharmaco-economic evaluation. In the base-case scenarioith no preventive measure available and an average influenza attack rate of 30%, 4,958,188 influenza infections, 1,552,687 GP consul-ations, 83,515 hospitalizations and 173,396 deaths will take place in The Netherlands. The burden is highest in adults aged 20 to 64ears. If minimizing the total mortality and sustaining highest net economic returns is the objective, this group needs to be targeted innterventions.2006 Elsevier Ltd. All rights reserved.eywords: Influenza; Models; Economics; Primary care; Health care sector; PreventiontAtahattdamai. IntroductionRecent epidemics of highly pathogenic H5N1 aviannfluenza with an estimated mortality rate exceeding 50%n Asia [1], a report of probable person-to-person trans-ission [2] and unusual clinical symptoms making differ-ntial diagnosis a complicated task [3] warn the world ofhe next influenza pandemic to come. Many Western coun-ries have therefore been preparing themselves developingnfluenza contingency plans. In The Netherlands, for exam-le, a detailed planning of interventions during the differentandemic phases has been developed [4]. Only recently, theutch Ministry of Health decided to stockpile 5 million dosesf the neuraminidase inhibitor oseltamivir®. A vaccine for5N1 will not be available in the near future, and even ifvailable there will not be sufficient supply to cover Asian,et alone, other countries. Importantly, the effectiveness of∗ Corresponding author. Tel.: +31 30 2538214; fax: +31 30 2539028.E-mail address: e.hak@umcutrecht.nl (E. Hak).oiumor264-410X/$ – see front matter © 2006 Elsevier Ltd. All rights reserved.oi:10.1016/j.vaccine.2006.05.065he neuraminidase inhibitors with regard to H5N1 influenzais relatively unknown. The use of oseltamivir in five of theen influenza H5N1 cases reported in Vietnam did not showny obvious effects, and mortality remained 80% [5]. Genericygienic measures aimed at reduction of transmission suchs reducing contact rates and social distance measures mightherefore be most important [6].In any case, health care resource planning will be essentialo minimize social disruption in case of an influenza pan-emic [7,8]. We therefore developed a decision type modelnd tried to estimate the total health care consumption in pri-ary and secondary care, and associated mortality as wells the total direct medical costs during the next possiblenfluenza pandemic in The Netherlands. The study was basedn estimates of health care consumption during a regularnfluenza A (H3N2) epidemic [9]. Though much remainsncertain in such predictions, these estimates might provideore insight into the expected health-economic burden toptimally develop or adjust national contingency plans toespond to the next influenza pandemic.ine 24 (22a2tE. Hak et al. / Vacc. Methods.1. Model parametersThe arithmetic decision tree-type model underlying thenalyses was developed in an Excel spreadsheet (versionat[Fig. 1. Mod2006) 6756–6760 6757000, Microsoft) to take into account population characteris-ics, varying influenza attack rates, health care consumptionccording to the Dutch health care model and all-cause mor-ality (see Fig. 1).In accordance with previous mile-stone studies by Meltzer7] and Van Genugten et al. [8] we subdivided the patientel.6758 E. Hak et al. / Vaccine 24 (Table 1Model parameters during influenza A (H3N1) epidemicParameter Unit/thousandCategory ofinformationaOutpatient visits age group 1-LR 5.8 1Outpatient visits age group 1-HR 33.9 1Outpatient visits age group 2-LR 7.5 1Outpatient visits age group 2-HR 12.8 1Outpatient visits age group 3-LR 12.1 1Outpatient visits age group 3-HR 28.3 1Hospitalizations age group 1-LR 0.113 2Hospitalizations age group 1-HR 0.340 1Hospitalizations age group 2-LR 0.333 2Hospitalizations age group 2-HR 1.00 1Hospitalizations age group 3-LR 2.3 1Hospitalizations age group 3-HR 6.5 1Deaths age group 1-LR 0.038 2Deaths age group 1-HR 0.113 2Deaths age group 2-LR 0.800 2Deaths age group 2-HR 2.400 1Deaths age group 3-LR 3.900 1Deaths age group 3-HR 10.800 1Abbreviations—1-LR: low-risk children (0–19 years); 1-HR: high-risk chil-dren; 2-LR: low-risk adults (20–64 years); 2-HR: high-risk adults; 3-LR:low-risk elderly (≥65 years); 3-HR: high-risk elderly.a 1: derived from the PRISMA data; 2: estimated indirectly from thePtrpiewotH7t[mi2etihitscinAcaaclmiwfls4e1pitdtttollc(FltyotltcfsDttcDtqtaaasmuiiRISMA data assuming similar distributions of deaths and hospitaliza-ions as recorded in the elderly (ratio hospitalization:death = 1:3, ratio lowisk/high risk = 1:3).opulation into children 0–19 years of age (N = 3,593,132n 2004), adults 20–64 years of age (N = 10,379,439) andlderly aged 65 years and older (N = 2,220,002). Further,e subdivided these age groups according to the presencer absence of risk-elevating medical conditions as men-ioned in the influenza immunization guidelines by the Dutchealth Council (high-risk medical conditions in children:%, adults: 12% and elderly: 40%).The attack rates during pandemic influenza were estimatedo vary from 20% to 50% with a most likely average of 30%10]. We used the average age-specific attack rates as esti-ated by Glezen [11] on the basis of the three epidemicsn the 20th century (children: 38%, adults: 30% and elderly:0%, all persons: 30%) and used multiplication factors tostimate the outcomes based on the health outcomes duringhe 1999–2000 influenza A (H3N2) epidemic with an averagenfluenza attack rate of 9%.The probabilities of the complications and associatedealth care use (33% of influenza cases needs health care)n the model were based on data from the Dutch Preven-ion of Influenza, Surveillance and Management (PRISMA)tudy (Table 1) [9]. This influenza vaccine effectiveness case-ontrol study was nested in a primary care cohort of approx-mately 75,000 persons recommended for influenza vacci-ation, and was conducted during the 1999–2000 influenza(H3N2) epidemic. The major (possibly) influenza-relatedomplications recorded were: pneumonia, acute otitis media,cute lung disease, myocardial infarction, stroke, heart failurend death from any cause. The distribution of these compli-la(i2006) 6756–6760ations was estimated for each subgroup. For example, of allow-risk children that consulted the GP, we estimated thatost would have acute otitis media (77%) and the remaindernfluenza or pneumonia (23%). In high-risk children, 29%ould consult the GP for exacerbations of the asthma, 55%or acute otitis media and 16% for influenza or pneumonia. Inow- and high-risk adults and elderly, the most common rea-on for encounter was acute respiratory disease (48%, 58%,4% and 24%, respectively). In low- and high-risk adults andlderly, sudden cardiac death was responsible for 12%, 14%,8% and 23%, respectively, of all complications recorded inrimary care. We observed no deaths in high-risk childrenn the PRISMA study, but assumed similar ratio’s for hospi-alization and deaths as in adults and elderly (3:1) to occururing a pandemic.Initially a 1-year time horizon was used to predict short-erm impact in terms of costs and burden of disease. We fur-her adapted the model to be able to use the model to explorehe (long-term) survival impact of influenza. Each health stater co-morbid condition is associated with a specific expectedongevity. Based on national statistics and previously pub-ished national predictions of future burden of disease, healthare resource use and expenditures, health state specificlong-term) estimates for the above outcomes were obtained.or the calculation of the age- and co-morbidity-adjustedife expectancy we used complication-specific reduction fac-ors. The age-adjusted life expectancy for children was 71ears, 40 years for adults and 12 years for elderly personsn average. A reduced life expectancy is used because of theheoretical impact of co-morbidity of these complications onife expectancy. Reduction factors have been used to indicatehe reduction in survival after certain complications. Compli-ations that result in reduced survival were COPD (reductionactor 0.75), heart failure (0.50), myocardial infarction (0.50),troke (0.75) and diabetes mellitus (0.75) [12].Actual direct medical cost estimates were based on theutch guidelines for pharmaco-economic evaluation [13] andhe Dutch medical economics guideline [14]. We estimatedhe costs from a societal perspective and included averageosts for general practitioner visits, hospitalization and death.uring an influenza-like illness, persons of all ages consultheir general practitioner 1.9 times on average according touestionnaire data with an average of D 20.20 per consul-ation. Since no other data are available that describe theverage number of prescriptions per consultation in the threege groups, we conservatively assumed one prescription withmedian net payment of D 9 as observed in the PRISMAtudy. Data from the PRISMA study were used to estimateedian costs associated with a hospitalization. The averagenit costs for hospitalizations were determined by calculat-ng the weighted average unit costs for hospitalisation for thendications stroke, pneumonia, myocardial infarction, acuteung disease, heart failure, stroke multiplied by the weightedverage price per bed for general and academic hospitalsD 4252). Further, it was recorded that 35% of all hospital-zed patients required intensive care for one or more daysine 24 ((pautcdpccpsp3vraesttbmtteateeae(diapaawo4sie2dtopttah6aewtmncsncioyamuwoasRE. Hak et al. / Vaccunit cost D 2370); 83% of patients were brought to the hos-ital by ambulance (unit cost D 306) and that 12% neededdditional diagnostic research (unit cost D 33). The averagenit costs for hospitalization for the various indications plushe additional components resulted in a total average unitost per hospitalization of D 5362. The costs of death wereetermined by the use of several health care components byatients. Since there are no published data available on theosts of death, we have tried to give an impression on theomponents that have to be taken into account, i.e. generalractitioner visit, consulting specialist, first aid, diagnostics,tay at an intensive care unit and at a general ward and trans-ort to the hospital with an ambulance (D 2391).. ResultsIn the base-case scenario of a possible pandemic no pre-entive measure is available and the average influenza attackate is assumed to be 30% with estimated group-specificttack rates in low-risk and high-risk children, adults andlderly of 38%, 62%, 29%, 38%, 14% and 32%, respectively.In all, 4,958,188 influenza infections, 1,552,687 GP con-ultations, 83,515 hospitalizations and 173,396 deaths willake place in The Netherlands.Absolute figures for GP consultations (965,798), hospi-alizations (47,761) and deaths (132,860) are expected toe highest in adults aged 20–64 years. Among children,any GP consultations are to be expected (458,744) andhese persons account for the lowest rates of hospitaliza-ions and deaths (8440 and 2746, respectively). Among thelderly, 128,135 GP consultations, 27,313 hospitalizationsnd 37,790 deaths would occur. With a time-horizon of 1 year,he average numbers of life-years lost during a pandemic arestimated at (173,396 × 40)/52 = 133,208. The remaining lifexpectancy analysis showed that 2,716,293 future life-yearsre lost during a pandemic.Overall, the total direct medical costs in one year arestimated at D 843,679,580. The costs are higher for adultsD 569,002,321), than for elderly (D 214,127,301) and chil-ren (D 60,549,958). In a total population of 16 million inhab-tants, this means that from a direct medical cost perspectiveny preventive measure that has a real-life effectiveness ofreventing 50% of deaths during a pandemic (which equalsreduction of 1,358,147 life-years), would be cost-effectivet a maximum incremental cost of D 20,000/life-year gainedhen the costs of the measure per inhabitant would be D 1697r lower.. DiscussionOur data indicate substantial loss of life, health care con-umption and economic losses during the next pandemicn The Netherlands. Absolute hospitalization, mortality andconomic cost figures are highest for the group aged between2006) 6756–6760 67590 and 64 years and considerable, though lowest, among chil-ren.The observation that mortality figures might be highest inhe under 65s during a pandemic is in agreement with recentbservations by Simonsen et al. [15]. They found that theroportion of total deaths among the under 65s was morehan 40% in the last three pandemics, and even 95% duringhe Spanish pandemic of 1918–1919. Our observations arelso in agreement with those from Meltzer who observed aigh proportion of total number of deaths among the under5s [7]. Van Genugten and colleagues used a scenario modelnd estimated more than 95% of deaths to occur among thelderly [8]. However, in their model input for mortality figuresas estimated on the basis of excess figures for deaths dueo influenza and pneumonia. In younger persons, influenzaay cause death through secondary complications that areot directly attributed to influenza and pneumonia, such asardiovascular complications, as observed in the PRISMAtudy [9].Setting priority for preventive measures in pandemic plan-ing is guided by the objectives to be reached. Objectivesan range from minimizing the total mortality to sustain-ng highest net economic returns. The data indicate that bothbjectives can be reached if the group aged between 20 and 64ears is targeted in interventions. Our model does not take intoccount virulence factors or transmission factors. However,ost persons who suffered from avian influenza are currentlynder 65 years and transmission is highest among the groupith highest contact rates, i.e. those under 65 years. More-ver, if large numbers of working-age persons are affected,s for example in many countries in which HIV is epidemic,ocial disruption is inevitable.eferences[1] World Health Organisation, Department of Communicable DiseaseSurveillance and Response. Avian Influenza: Assessing the Pan-demic Threat, 2005 [available from: http://www.who.int/csr/disease/influenza/].[2] Ungchusak K, Auewarakul P, Dowell SF, Kitphati R, Auwanit W,Puthavathana P, et al. Probable person-to-person transmission of avianinfluenza A (H5N1). N Engl J Med 2005;352:333–40.[3] De Jong MD, Bach VC, Phan TO, VO MH, Tran TT, Nguyen BH, etal. Fatal avian influenza A (H5N1) in a child presenting with diarrheafollowed by coma. N Engl J Med 2005;352:686–91.[4] Dutch Health Council. Use of antiviral drugs and other means during aninfluenza pandemic. The Hague: Gezondheidsraad; 2005 [no. 2005/05].[5] Tran TH, Nguyen TL, Nguyen TD, et al. Avian influenza A(H5N1) in 10 patients in Vietnam. N Engl J Med 2004;350:1179–88.[6] Ferguson NM, Cummings DA, Cauchemez S, Fraser C, Riley C, MeeyaiA, et al. Strategies for containing an emerging influenza pandemic inSoutheast Asia. Nature 2005;437:209–14.[7] Meltzer MI, Cox NJ, Fukuda K. The economic impact of pandemicinfluenza in the United States: priorities for intervention. Emerg InfectDis 1999;5:659–71.[8] Van Genugten ML, Heijnen MA, Jager JC. Pandemic influenza andhealthcare demand in the Netherlands: scenario analysis. Emerg InfectDis 2003;9:531–8.6 ine 24 ([[[[[uaties in de gezondheidszorg. Amstelveen: College voor zorgverzek-eringen; 2004.760 E. Hak et al. / Vacc[9] Hak E, Buskens E, Van Essen GA, De Bakker DH, Grobbee DE, TackenMA, et al. Clinical effectiveness of influenza vaccination in personsyounger than 65 years with high-risk medical conditions: the PRISMAstudy. Arch Intern Med 2005;165:274–80.10] Nguyen-Van-Tam JS, Hampson AW. The epidemiology and clinicalimpact of pandemic influenza. Vaccine 2003;21:1762–8.11] Glezen WP. Emerging infections: pandemic influenza. Epidemiol Rev1996;18:64–76.12] Hoogenveen RT, Gijsen R, van Genugten MLL, Kommer GJ, SchoutenJSAG, de Hollander AEM. Dutch DisMod: constructing a set of con-sistent data for chronic disease modelling. Bilthoven: RIVM, editor;2000.[2006) 6756–676013] College voor Zorgverzekeringen. Dutch guidelines for pharma-coeconomic research. Amstelveen, the Netherlands: College voorZorgverzekeringen; 1999.14] Oostenbrink J, Koopmanschap MA, Rutten FFH. Handleiding voorkostenonderzoek; methoden en richtlijnprijzen voor economische eval-15] Simonsen L, Clarke MJ, Schonberger LB, Arden NH, Cox NJ, FukudaK. Pandemic versus epidemic influenza mortality: a pattern of changingage distribution. J Infect Dis 1998;178:53–60.

Modelling the health-economic impact of the next influenza pandemic in The Netherlands

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Modelling the health-economic impact of the next influenza pandemic in The Netherlands

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