Please help me out with this assignment, case study 3. You can use the articles and graphs on “case study 3“ file to finish this assignment. Thanks.

The global distribution of dengue cases is 18% admitted to hospital, 48% ambulatory, and 34% non-medical. Interpretation The global cost of dengue is substantial and, if control strategies could reduce dengue appreciably, billions of dollars could be saved globally. In estimating dengue costs by country and setting, this study contributes to the needs of policy makers, donors, developers, and researchers for economic assessments of dengue interventions, particularly with the licensure of the fi rst dengue vaccine and promising developments in other technologies. Funding Sanofi Pasteur. Introduction Dengue is the most important mosquito-borne viral disease, with approximately half of the world’s population living in dengue-endemic countries, and it is rapidly spreading. 1,2 Although dengue represents a serious global economic and disease burden, 3–5 un- recognised and unreported apparent dengue virus infections, and questions about data access and quality, make it diffi cult to estimate the true extent of dengue illness. 1,6,7 Alternative sources estimate the annual number of symptomatic dengue cases globally to be 9 million, 8 50 million–100 million, 9 3∙2 million (reported), 10–12 and 96 million. 1 Published studies 3,13 about the economic burden of dengue are sparse, and country-level cost estimates are only available for a small portion of endemic countries. 14 The biggest challenges in dengue burden estimates include deriving the actual number of dengue cases and dengue cost per case, even in countries in which studies have been done, and extrapolating from those countries to other locations. 7 Objective, systematic, and comparable measures of dengue burden are needed to track health progress, assess the application and fi nancing of emerging preventive and control strategies, and to inform evidence- based policy. 7 In a published study with other colleagues, 15 we estimated the number of dengue cases by country and super-region in 2013. Here, we present the results of a parallel study in which, by integrating data from various sources, we estimate the global economic burden of dengue by country and super-region with associated uncertainty intervals (UI). Methods Overall analysis For this systematic analysis, we obtained data for the number of cases from our global burden of dengue analysis. 15 The distribution of cases between medical and non-medical settings was derived from national surveys of febrile illness and use of formal health care for selected countries, whereas the distribution within medical settings (admitted to hospital vs ambulatory) was inferred from previously published dengue studies. Numbers of dengue deaths were calculated by applying a case fatality rate to the estimated numbers of cases by country. The age distribution of dengue deaths was extrapolated from available country data. Economic costs per case were derived from published studies of dengue costs, an expert survey, and national economic data.

For each variable in the estimation, we identifi ed countries with empirical estimates and the patterns in those estimates in relation to variables available for all countries with dengue—population, gross domestic product (GDP) per head, or previously derived variables. Lancet Infect Dis 2016 Published Online April 15, 2016 http://dx.doi.org/10.1016/ S1473-3099(16)00146-8 See Online/Commenthttp://dx.doi.org/10.1016/ S1473-3099(16)30001-9 Schneider Institutes for Health Policy, Heller School for Social Policy and Management, Brandeis University, Waltham, MA, USA (Prof D S Shepard PhD, E A Undurraga PhD, Y A Halasa DDS); and Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA ( J D Stanaway PhD) Correspondence to:

Prof Donald S Shepard, Schneider Institutes for Health Policy, Heller School for Social Policy and Management, Brandeis University, Waltham, MA, USA [email protected] Articles 2 www.thelancet.com/infection Published online April 15, 2016 http://dx.doi.org/10.1016/S1473-3099(16)00146-8 We then used the pattern to predict values for remaining countries. We selected independent variables based on their availability for all countries and territories, statistically signifi cant association with the outcome, biological or economic plausibility, and parsimony (fi gure 1). Estimation of symptomatic dengue cases Our estimate of the number of dengue cases in 141 countries and territories is a component of the Global Burden of Disease Study 2013 (GBD 2013). 16 We adjusted for potential under-reporting using a modelling Dengue occurrence probability 1 Population density (gridded world population) Dengue score Estimates of dengue under-reporting (published literature) Reported dengue episodes (WHO, Ministry of Health national statistics, published literature) Adjusted estimates of dengue incidence (non-fatal) Estimates of total dengue episodes by country (Institute for Health Metrics) 15 Institute for Health Metrics CODEm death estimates Literature review:

economics of dengue by treatment setting Direct and indirect cost per case by treatment setting Expert panel: share of non-medical patients who spent money and their average expenditures Dengue incidence by treatment setting Economic burden of dengue = Σi cost per case in setting i × cases in setting i with i (setting) = fatal, non-fatal cases admitted to hospital, ambulatory, and non-medical cases Estimates of the economic burden of dengue by treatment setting Figure 1: Flow chart of key steps in estimating the global economic burden of dengue CODEm is the Cause-of-Death Ensemble Model tool. Dengue score is a country-level index of dengue transmission. The study by Stanaway and colleagues 15 and its appendix provide further details. Specifi c details about each step in the fl ow chart are given in the appendix. After the summation sign, “i” is the dengue-endemic country or territory for which we estimated the economic burden of dengue by treatment setting. Research in context Evidence before this study The true extent of dengue burden has been underestimated.

Objective, systematic, comparable measures of dengue burden are needed to track health progress, assess the application and fi nancing of emerging preventive and control strategies, and, more generally, to inform evidence-based health policy.

We searched the Web of Science, Medline, or in WHO’s Dengue Bulletin for articles published between 1995 and 2015 in English, Spanish, French, or Portuguese, using the keyword “dengue” and any of the following list of keywords:

surveillance, incidence, reporting, sensitivity, capture recapture, cohort, economics, costs, burden, Aedes aegypti, and control.

Added value of this study We systematically assembled and analysed the latest estimates from the Institute for Health Metrics and Evaluation’s Global Burden of Disease Study, World Bank Indicators, Demographic and Health Surveys, published literature through systematic reviews and responses to an expert panel questionnaire to assess the global economic and disease burden of dengue illness. We cover all 141 countries and territories with active dengue transmission. Our global estimates suggest that in 2013 there were a total of 5840 million symptomatic dengue virus infections, including 13 586 fatal cases. The total annual global cost of dengue illness was US$8·89 billion: 46·0% from non-fatal cases admitted to hospital, 33·6% from non-fatal ambulatory cases, 8·5% from non-fatal non-medical cases, and 11·9% for fatal cases. Data limitations create uncertainty around all of these estimates. Our study’s main contribution is providing comparable, consistent estimates of the economic burden of dengue by treatment setting and by country, region, and globally. Our study endeavors to inform policy analyses with the most comprehensive economic assessment of dengue to date.

Implications of all the available evidence The global cost of dengue is substantial. Recommended approaches to improve future estimates include merging multiple data sources, such as cohort and surveillance data, adjusting for unrecognised dengue cases, and modelling to estimate dengue incidence in locations with limited data. Our hope is that improved estimates and a greater understanding of the main factors driving uncertainty around the burden of dengue will enable improvement of current estimates, and consequently, improve the assessment of existing and potential future preventive and treatment approaches. Articles www.thelancet.com/infection Published online April 15, 2016 http://dx.doi.org/10.1016/S1473-3099(16)00146-8 3 See Online for appendix approach where we defi ned the expected spatial distribution of dengue virus for 2013, modelled the association between this expected distribution and reported incidence with the assumption that deviations from the expected distribution refl ect deviations in completeness of reporting, and calibrated the model by benchmarking these deviations against published empirical expansion factors, and removed countries with no evidence of dengue virus transmission. 15 We also incorporated small island countries and territories (appendix pp 3, 4, and 10–34). Estimation of dengue cases by setting We divided symptomatic dengue cases into three groups on the basis of the most costly treatment setting used:

hospital admission, including any ambulatory visits the patient might have had before or after the admission; ambulatory, consisting of patients who consulted a health professional (such as a physician, nurse, or medical offi cer) or health facility (including hospitals’ emergency and outpatient departments, health centres, clinics, and clinicians’ private offi ces); and non-medical cases (ie, patients outside the professional sector who received 3001–5000 1501–3000 1001–1500 751–1000 501–750 301–500 1–300 0 $15.01–$55.00 $5.01–$15.00 $2.51–$5.00 $1.01–$2.50 $0.51–$1.00 $0.11–$0.50 $0.01–$0.10 $0.00 A B Figure 2: Dengue incidence per 100 000 population (A) and cost per head of symptomatic dengue infections (2013 US$; B) Articles 4 www.thelancet.com/infection Published online April 15, 2016 http://dx.doi.org/10.1016/S1473-3099(16)00146-8 neither diagnosis nor treatment from a health professional or facility, although such patients might have had laboratory testing or purchased a therapeutic product on their own initiative).

We distributed cases between hospital and ambulatory settings for patients treated in the professional health sector from previous empirical studies and regression estimates (appendix p 5). Research suggests that a substantial proportion of dengue cases are not treated in the professional health sector because of limited access to primary care, limited operating hours, costs, alternative health-care providers, or milder dengue cases. 7 We derived the percentage of cases treated outside the professional health-care sector using the proportion of fever cases in 3-year-old children treated in the formal health sector as a proxy 17 (appendix pp 4, 5). Estimation of deaths due to dengue virus infection To estimate the number of fatal dengue virus infections, we collected country-level reported dengue cases from 2000 to 2014 compiled from national vital registrations and calculated the ratio of reported deaths to reported cases admitted to hospital for these countries. We obtained annual reported fatal dengue cases for 45 countries. Assuming that all fatal dengue cases occur in hospitals and that the rates of reporting of fatal and non-fatal dengue cases admitted to hospital were similar, we adjusted reported deaths based on 32 country-specifi c expansion factors for cases admitted to hospital obtained from previous studies in Asia and the Americas 4,18–20 (appendix p 5, 6, and 50). Estimation of the cost of dengue We considered two types of cost in our analysis, short- term and long-term cost. Short-term cost relates to non- fatal dengue episodes, consists of direct medical and non-medical cost, and indirect cost associated with time lost because of illness or care. Long-term costs relate to fatal dengue episodes.

Direct and indirect costs (in 2013) of cases admitted to hospital and ambulatory dengue cases were obtained from empirical studies in 47 countries in the Americas, southeast Asia, and India, supplemented by regression analyses (appendix pp 40–42).

We estimated direct medical expenditure based on the responses to our expert panel questionnaire by 24 experts from nine countries from the Americas and Asia, which provided insights from academic, public, and private perspectives from public offi cials, clinicians, and researchers of dengue we had been involved with in previous dengue-related collaborations. We responded to their questions and comments, aggregated their responses from a single round of inquiry, and generalised the fi ndings on the basis of a measure of health-care accessibility (appendix pp 42–49). We used the human capital approach. This method estimates the economic value of human life lost due to premature death based on the discounted present value of that person’s expected productivity. We then estimated the average discounted life expectancy for children and adults on the basis of the WHO life tables 21 and valued each year at the country’s GDP per head (appendix pp 5, 6, 53). Sensitivity analysis GBD 2013 accounted for uncertainty through posterior simulations based on 1000 random draws of each incidence rate estimate for each country. 15,16 For con- sistency, we addressed uncertainty in our case distribution, death from dengue, and cost estimates, using Monte Carlo simulations with 1000 repetitions with 1000 random draws of each number of dengue cases per country generated by GBD 2013 (appendix pp 50–53). Role of the funding source The funder of the study off ered optional comments on an earlier draft of this study but otherwise had no role in study design, data collection, data analysis, data interpretation, 20 40 60 80 Non-fatal cases admitted to hospital Fatal cases Ambulatory Non-medical Global total Central and eastern Europe, central Asia High-income countries Latin America and the Caribbean North Africa and the Middle East South Asia Southeast and east Asia and Oceania Saharan Africa 18% 48% 34% 100 0 Distribution of dengue cases* (%) A 20 40 60 80 Global total Central and eastern Europe, central Asia High-income countries Latin America and the Caribbean North Africa and the Middle East South Asia Southeast and east Asia and Oceania Saharan Africa 12% 46% 34% 8% 100 0 Distribution of dengue costs (%) B Figure 3: Estimated number of dengue episodes (A) and aggregate costs (B) of dengue by treatment setting Non-medical denotes dengue episodes treated outside the professional health-care sector. *Fatal cases are too small relative to total symptomatic dengue episodes to appear in the fi gure; however, fatal episodes represent a substantial share of the total costs (B). Articles www.thelancet.com/infection Published online April 15, 2016 http://dx.doi.org/10.1016/S1473-3099(16)00146-8 5 or writing of the report. The corresponding author had full access to all the data in the study and had fi nal responsibility for the decision to submit for publication.

Results With use of results from GBD 2013, we estimated that 58∙40 million dengue cases (95% UI 24 million–122 million) occurred in 2013 in 141 countries with dengue virus transmission. We estimated that, of these, 10∙5 million were treated in the hospital setting and 28∙1 million were treated in the ambulatory health-care setting, and 19∙7 million remained outside the health-care system. The incidence of dengue is mapped in fi gure 2, and reported by super-region and country (appendix pp 10–15 and 35). The distribution of dengue cases by treatment setting is shown in fi gure 3.

With use of the adjusted number of dengue deaths and the number of dengue cases for the 32 countries with reported deaths and hospital expansion factors (used to adjust for under-reporting of symptomatic dengue infections), we estimated a ratio of one death per 5991 dengue cases in these 32 countries and applied this ratio to the remaining countries. We estimated a global total of 13 586 dengue deaths (95% UI 4200–34 700) in 2013, with 5838 deaths occurring in children and 7748 in adults (appendix pp 7–36).

Our estimated global average cost per dengue case is US$70∙10 (95% UI 66∙66–74∙63) for cases admitted to hospital, $51∙16 (49∙80–53∙71) for ambulatory cases, $12∙94 (12∙80–13∙73) for cases outside the health-care sector, and $84 730 (68 622–108 165) for fatal cases ($80 414 [74 000–95 000] for children and $75 820 [62 000–121 000] for adults). The grand weighted average across all types of cases is $151 (134–177). Costs per case are generally higher in high-income super-regions and range from a low of $56 (46–82) in sub-Saharan Africa to a high of $1146 (765–1639) in the high-income super-region (table). Similarly, we see the highest costs per case in high-income countries, such as the USA and Australia, and the lowest costs per case in low-income countries in Asia and sub-Saharan Africa (appendix pp 7–36). Each childhood dengue death represented 28∙8 discounted (67∙9 undiscounted) years, and each adult death lost meant 18∙8 discounted (32∙2 undiscounted) expected years lost. Figure 2 shows the cost of dengue per capita by country in 2013 and fi gure 3 shows the distribution of costs by treatment setting.

We obtained a total annual global aggregate cost of dengue in 2013 of $8∙9 billion (95% UI 3∙7 billion–19∙7 billion; appendix pp 22–36) or $1∙56 per capita for 141 dengue endemic countries with aggregate costs of non-fatal cases admitted to hospital ($4093 million), ambulatory non-fatal cases ($2987 million), non-medical cases ($752 million), and fatal cases ($1055 million). Individual country estimates are shown in the appendix (pp 22–34). Discussion On the basis of 58∙40 million global dengue cases, we estimated 10∙53 million cases admitted to hospital, 13 586 fatal cases, and a total annual global aggregate cost of dengue illness of $8∙9 billion in 2013. Point estimates for many countries might not be precise because they are based on extrapolations with available data. A range of factors, including limited availability and quality of surveillance data in many countries and few studies on the distribution of treat ment settings, contributed to the variability in previous estimates of the global burden of dengue illness and the wide uncertainty intervals for our estimates. The biggest payoff for improving burden of Short-term costsLong-term costs Overall Direct hospital Direct ambulatoryDirect outside medical sectorIndirect hospitalIndirect ambulatoryIndirect outside medical sectorIndirect fatal child Indirect fatal adult Central Europe, eastern Europe, and central Asia$243 (188–343)$40 (32–54)$3 (1–9)$44 (30–71)$24 (18–38)$40 (28–62)$78 003 (66 187–102 129)$59 130 46 995–109 490)$91 (73–137) High-income* $2427 (1637–3484)$253 (170–337)$6 (2–22)$1382 (844–2152)$425 (253–627)$458 (270–695)$800 767 (590 462–979 984)$616 508 (484 101–892 406)$1146 (765–1639) Latin America and the Caribbean$1000 (773–1251)$102 (88–120)$9 (6–14)$360 (271–471)$161 (128–211)$141 (115–185)$184 805 (164 112–257 764)$169 577 (130 269–274 864)$307 (262–382) North Africa and the Middle East$281 (220–369)$46 (37–60)$7 (5–12)$52 (38–72)$29 (21–40)$25 (19–34)$78 647 (72 535–86 738)$58 437 (49 177–87 441)$102 (81–137) South Asia $241 (159–366)$25 17–37)$4 (1–8)$19 (11–31)$10 (6–17) $10 (6–16)$34 803 (31 576–39 529)$24 345 (20 174–39 773)$74 (50–116) Southeast Asia, east Asia, and Oceania$376 (313–476)$78 (68–93)$9 (4–10)$71 (57–94)$39 (33–50)$41 (34–52)$98 365 (88 698–114 105)$86 136 (72 345–143 209)$207 (176–255) Sub-Saharan Africa $179 (152–232)$29 ($25–$38)$8 (5–13)$27 (21–37)$15 (12–21)$18 (13–25)$47 905 ($42 454–$57 622)$40 461 (33 175–67 528)$56 (46–82) Global average $333 (283–403)$60 (54–68)$7 (4–8)$56 (46–70)$46 (40–56)$31 (27–38)$80 414 (74 455–95 078)$75 820 (62 281–120 501)$152 (136–179) *High-income regions include Argentina, Australia, Brunei Darussalam, Singapore, and the USA.

Table: Weighted average costs of illness and 95% uncertainty intervals per dengue case summarised by super-region in 2013 Articles 6 www.thelancet.com/infection Published online April 15, 2016 http://dx.doi.org/10.1016/S1473-3099(16)00146-8 dengue estimates would come from studies that can link and analyse existing data. 7 To our knowledge, only one previous publication has estimated the global economic burden of dengue. 14 In view of the many sources of uncertainty, we think it is useful to develop alternative approaches to estimating the economic burden of dengue. We believe that the main strengths of our approach relate to the com- prehensive use of all relevant empirical data and systematic analysis, our inclusion of all countries believed to have dengue transmission, and our quanti- fi cation of the resulting uncertainty. We obtained direct and indirect costs per dengue case based on empirical estimates from previous studies from various settings in 14 dengue-endemic countries. Similarly, we esti- mated the total number of deaths based on reported cases of dengue, and adjusted reported cases based on reporting rates from cases admitted to hospital. This assumption is consistent with the limited available evidence that suggests substantial under-reporting even in high-income areas. 7 Our results show higher indirect cost for a fatal child case compared with a fatal adult case because of the fact that children lose more life- years by premature death due to dengue than do adults.

Our estimates of cost are about a quarter of those obtained by Selck and colleagues 14 of $39∙30 billion in 2010 for four main reasons. First, we used a diff erent severity mix, and thus a mix of treatment settings (Selck and colleagues 14 report more severe cases and assume that all cases presented to the professional health-care sector). Second Selck and colleagues 14 estimated about 74 000 annual fatal dengue episodes, about six times our estimate, and almost four times WHO’s estimate of up to 20 000 annual deaths. 9 Third, Selck and colleagues 14 reported a substantially higher average cost of $414 per symptomatic dengue cases compared with our global average estimate of $152 (95% UI 136–179). Finally, their analysis used Bhatt and colleagues, 1 incidence estimates and appeared to assume that every case received care in some kind of formal setting, 14 whereas our global estimate is substantially lower because we recognised non-medical episodes and resource constraints in most health systems. We did several sensitivity analyses. We fi rst repeated our analysis using Bhatt and colleagues’ 1 estimates of dengue incidence, which resulted in a 54% increase above our estimates of economic burden (Bhatt and colleagues: $13∙66 billion; Stanaway and col- leagues: 15 $8∙89 billion). We next assumed that the direct medical cost for those treated outside the professional health-care sector was similar to those who sought treatment in ambulatory settings, fi nding increases over our current estimate of 10% with the incidence estimated by Stanaway and colleagues 15 and 70% with Bhatt and colleagues’ 1 incidence estimates.

We estimated the total cost of dengue illness in Latin America and the Caribbean to be about $1∙73 billion annually, which is lower than our previous estimate of the average cost of dengue illness in the Americas of $2∙15 billion in 2010. 4 This is because of developments in our methods—ie, we have adjusted for the fact that not all dengue cases will be treated in the professional health- care sector. In this study, we captured the cost associated with treatment outside the professional health-care system. However, results of this analysis in 12 southeast Asian countries (fi gure 3) suggest that costs per head are higher than a previous published estimate for these countries ($2∙38 [95% UI 0∙93–5∙33] per head) 5 because of new techniques for estimating numbers of dengue cases, 15 a mostly newer reference period (2000–2010 vs 1988–2013) as dengue has increased, and additional data for cost per case. If the share of cases admitted to hospital were higher than our estimate, then the global cost of dengue would have been higher than that reported here.

If the share of ambulatory cases were higher, then global cost of dengue would be lower than our estimate.

Our estimates of annual dengue cases are based on a model that took reporting data from 1988 through to 2013, which smoothed out the eff ects of dengue outbreaks, making our estimates more representative of an average year. However, despite the refi nements in this study, several factors make our estimates conservative. First, we might have underestimated the share of dengue patients treated in the formal health sector. Our estimates of this share are based on rates for 3-year-old children, mostly in countries in which malaria is prominent. Adults and older children might be more likely than young children to be admitted to hospital. Second, our estimate of economic costs is based on human capital. Estimates based on willingness to pay are generally higher.

Limitations of our study include insuffi cient incidence data from Africa and our reliance on data from Latin America to distribute dengue cases among hospital, ambulatory, and non-medical settings based on experts participating in an expert survey, restricted or delayed access to some surveillance data, limited information or imprecise diagnosis of dengue-related deaths, 22 few covariates to extrapolate the distribution of fatal cases between children and adults to estimate indirect costs from fatal episodes, and the exclusion of vector control and surveillance cost data from the analysis. In some countries, not all the population is at risk (eg, only 68% in Mexico and 53% in Colombia). The incidence rates calculated might therefore be underestimated, and consequently, the overall economic burden of dengue.

Because of a paucity of empirical data in some regions, such as Africa and the Middle East and wide annual variation in dengue incidence, our estimates for some countries in 2013 might be too high or too low, since the estimation model smooths variation across years towards the mean value, rather than estimating annual fl uctuations. We did an extensive sensitivity analysis to address these sources of uncertainty (appendix pp 50–53).

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30 Hampson K, Coudeville L, Lembo T, et al. Estimating the global burden of endemic canine rabies. PLoS Negl Trop Dis 2015; 9: e0003709. for any systematic analysis. These include, for example, a degradation of the quality of treatment for patients with and without dengue because of health-system congestion during a dengue outbreak, potential economic eff ects of dengue on tourism and travel, and comorbidities and complications associated with dengue virus infection. 7,23 We did not include persistent symptoms of dengue in our analysis. Some patients with dengue present persistent symptoms that might aff ect their ability to work, including profound fatigue, depression, and weight loss. Persistent symptoms have been acknowledged by WHO since 1997, 24 and have been identifi ed in empirical studies in Latin American and Asia. 25 Results from a study in Mexico suggest that accounting for persistent symptoms would increase estimates of the economic burden of dengue illness by about 13%. 25 Our estimates indicate that dengue illness imposes costs greater than other major infectious diseases with comparable data such as cholera ($3∙1 billion), 26 rotavirus gastroenteritis ($2 billion globally 27 and $0∙4 billion in developing countries), 28 Chagas ($7∙2 billion), 29 and canine rabies ($8∙6 billion). 30 The global cost of dengue is substantial. If control strategies could reduce dengue appreciably, billions of dollars could be saved globally each year. With the availability of new and promising technologies to control dengue, policy makers and donors need reliable economic data to assist in their decisions to adopt these new approaches. 7 Contributors EAU and YAH prepared the data and table. JDS did statistical analyses of the numbers of dengue cases. All authors conceived and designed the analyses and contributed to the analysis, development, writing, reviewing, editing, and approval of the fi nal version of the manuscript.

Declaration of interests We declare no competing interests.

Acknowledgments Editorial assistance with the preparation of an early version of the manuscript was provided by a professional medical writer, Simon Lancaster (inScience Communications, Springer Healthcare) funded by Sanofi Pasteur. We thank Clare Hurley for assistance with revisions.

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