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A systematic review of the economic impact of rapid diagnostic tests for dengue
research-article
Publication date (Electronic):
29 December 2017
Journal:
BMC Health Services Research
Publisher:
BioMed Central
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Abstract
Background
Dengue fever is rapidly expanding geographically, with about half of the world’s population now at risk. Among the various diagnostic options, rapid diagnostic tests (RDTs) are convenient and prompt, but limited in terms of accuracy and availability.
Methods
A systematic review was conducted of published data on the use of RDTs for dengue with respect to their economic impact. The search was conducted with combinations of key search terms, including “((Dengue[Title]) AND cost/economic)” and “rapid diagnostic test/assay (or point-of-care)”. Articles with insufficient report on cost/economic aspect of dengue RDTs, usually on comparison of different RDTs or assessment of novel rapid diagnostic tools, were excluded. This review has been registered in the PROSPERO International prospective register of systematic reviews (registry #: CRD42015017775).
Results
Eleven articles were found through advanced search on Pubmed. From Embase and Web of Science, two and 14 articles were obtained, respectively. After removal of duplicate items, title screening was done on 21 published works and 12 titles, including 2 meeting abstracts, were selected for abstract review. For full-text review, by two independent reviewers, 5 articles and 1 meeting abstract were selected. Among these, the abstract was referring to the same study results as one of the articles. After full text review, two studies (two articles and one abstract) were found to report on cost-wise or economic benefits of dengue RDTs and were selected for data extraction. One study found satisfactory performance of IgM-based Panbio RDT, concluding that it would be cost-effective in endemic settings. The second study was a modeling analysis and showed that a dengue RDT would not be advantageous in terms of cost and effectiveness compared to current practice of antibiotics prescription for acute febrile illness.
Conclusions
Despite growing use of RDTs in research and clinical settings, there were limited data to demonstrate an economic impact. The available two studies reached different conclusions on the cost-effectiveness of dengue RDTs, although only one of the two studies reported outcomes from cost-effectiveness analysis of dengue and the other was considering febrile illness more generally. Evidence of such an impact would require further quantitative economic studies.
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Most cited references33
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Economic and Disease Burden of Dengue in Southeast Asia
Introduction Dengue fever is among the most important infectious diseases in tropical and subtropical regions of the world, and represents a significant economic and disease burden in endemic countries [1]–[4]. There are about 100–200 million infections per year in more than 100 countries [5]. Estimating the economic and disease burden of dengue is critical to inform policy makers, set health policy priorities, and implement disease-control technologies. Here we estimate the economic and disease burden of dengue in 12 countries of Southeast Asia (SEA). We included all countries in the Association of Southeast Asian Nations [6], plus Bhutan and East-Timor due to their geographic proximity, to be consistent with our study on the incidence of dengue in the region [7]. Our study area comprises the following 12 countries: Bhutan, Brunei, Cambodia, East-Timor, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Viet Nam. Studying dengue burden in SEA is important for several reasons. Dengue is among the greatest disease burdens in SEA, and has been hyperendemic for decades [8]–[11]. SEA is the region with the highest dengue incidence, with cycles of epidemics occurring every three to five years [1], [8]. The WHO regions of SEA and the Western Pacific represent about 75% of the current global burden of dengue [12], [13]. Recent studies have estimated economic burden of dengue in specific countries of SEA (costs in 2010 US dollars [14]). For example, using the average reported cases between 2001–2005, Suaya et al. [2] estimated that the annual costs for dengue illness (standard errors in parenthesis) in Cambodia, Malaysia, and Thailand were at least US$3.1 (±0.2), US$42.4 (±4.3), and US$53.1 (±11.4) million (m), respectively. Beaute and Vong estimated an annual cost (2006–2008) of US$8.0m for Cambodia [15]. Adjusting the officially reported cases in 2009 with expansion factors (EFs) derived from a Delphi process, Shepard et al. [16] estimated that the annual cost of dengue in Malaysia, as updated [17], was about US$103.4m per year (range: US$78.8m–US$314.2m). Lim et al. [18] estimated a yearly cost of dengue–including dengue illness, vector control, and research and development activities–of US$133m (range: US$88m–US$215m) in Malaysia (2002–2007) and US$135m (range: US$56m–US$264m) in Thailand (2000–2005), respectively, in which dengue illness represented about 41.3% of the total costs (US$54.9m) in Malaysia and 49% (US$66.2m) in Thailand. Based on data from a provincial hospital, Kongsin et al. [19] estimated that the total economic burden of dengue in Thailand was US$175.4m (standard deviation: US$36.6m), of which US$126.3m corresponded to dengue illness and US$49.1m to dengue control. In Singapore, Carrasco et al. [20] estimated that yearly dengue illness costs US$41.5m and vector control costs US$50.0m. Last, Luong et al. [21] obtained an average annual cost (2004–2007) of US$30.3m for Viet Nam. The dengue burden of disease (number of disability adjusted life years or DALYs, based on the original 1994 definition [22] and extrapolated to 2010 based on population) has also been estimated for Cambodia (8,200 [15]), Myanmar (3,900 [23]), Singapore (700 [20]), and Thailand (28,900 [24]; 32,500 [25]). The few published estimates of economic and disease burden of dengue in SEA are based on a single or a small number of countries, and the comparison of estimates is limited by methodological differences between studies. Previous multi-country studies of dengue burden include the economic impact of dengue in the Americas [3], and an eight-country study including five countries in the Americas and three in SEA [2]. This paper aims to reduce this gap by estimating the economic and disease burden of dengue illness in SEA using a consistent methodology. Methods The economic burden of dengue is calculated as the total number of dengue cases times the total costs per dengue episode. To calculate the disease burden, an estimate of the total DALY burden per cases is also required. Total number of dengue cases Because dengue is an infectious disease, there is considerable annual variability in the number of dengue cases. We used the average officially reported cases in 2001–2010 to obtain a more stable estimate for each country. We obtained the number of reported dengue cases from various sources, including data from the country's Ministry of Health or statistics agency, WHO, or published studies [12], [16], [26]–[35]. Dengue is a reportable illness in SEA and thus the number of cases reported is correlated to the total cases. However, there is substantial underreporting of symptomatic dengue fever in SEA, and official statistics commonly underestimate case rates [7], [36]. Estimating the total number of dengue cases is challenging due to the limits of passive surveillance systems, which are useful to detect dengue outbreaks and to understand long-term trends of symptomatic infection, but underestimate the true incidence. The rate of reporting of surveillance systems depends on several variables, including the severity of dengue, identification method (e.g., clinical diagnosis, laboratory test), treatment facilities, year of data collection, the area where dengue is measured, among others [16], [27]. Recent studies have improved the estimate of the total number of cases by using EFs [3], [7], [16], [20], the ratio of the best estimate of the total number of symptomatic dengue, divided by the number of reported cases. We adjusted the officially reported cases using Undurraga et al.'s estimates of EFs for ambulatory, hospitalized, and total dengue episodes to estimate the incidence of dengue by country [7]. Undurraga et al. estimated the annual average of dengue episodes based on the officially reported cases from 2001 through 2010, and derived country-specific EFs through a systematic analysis of published studies that reported original, empirically derived EFs or the necessary data to obtain them. Costs per dengue episode To estimate the economic burden of symptomatic dengue infection one requires information on the unit costs of providing inpatient and outpatient medical care, in both private and public facilities. We conducted a systematic literature review for articles on the economic costs of dengue in Southeast Asia published between 1995 and 2012 using Web of Science and MEDLINE (72 articles), and PubMed (97 articles) using the keywords dengue, health, and economics. We reviewed the abstracts of these articles and identified 11 articles that explicitly reported data on the economic costs per dengue fever episode, or included the necessary information to estimate them [2], [15], [23], [24], [37]–[43]. To these articles, we added nine recently published articles [16], [19], [20], [44], or found in previous searches [21], [25], [45]–[47]. Although this study is an original research study and not a systematic review, we adapted relevant parts of the PRISMA check list and flowchart to our literature review (Figure S1, Table S1) [48]. We then filtered these 20 articles based on the following criteria: (1) use of original, empirical data; (2) use of a scientifically consistent approach; (3) use of externally valid and representative data; and (4) use of recent data in order to reflect current medical practice and technology. We selected studies that scored well, albeit not perfectly, on these criteria, providing what we think are the best data available. For each of these countries we derived the best cost estimate for direct medical and non-medical costs and indirect costs, for both inpatient and outpatient treatment. For countries in which no cost data were available, we relied instead on expert opinion (Malaysia) or in the extrapolation of data based on regression analysis (Bhutan, Brunei, East Timor, Indonesia, Laos, Myanmar, and Philippines), using unit costs as the dependent variable and gross domestic product (GDP) per capita as the independent variable. We found six studies that included dengue costs for Cambodia [2], [15], [37], [39], [40], [44]. Our best estimates for direct costs are based on the average between the costs estimates of two studies by Suaya et al. [39], [44]; to estimate indirect costs we used an average between these two studies plus the estimates by Huy et al. [37]. In the first study, Suaya et al. estimated costs based on patient interviews and record reviews of hospitalized patients from Daun Keo Referral Hospital [44]. In the second study considered, the authors' estimates were based on expert opinion and interviews with families, and contrasted with survey data from hospitalized patients and financial data from the National Pediatric Hospital [39]. Two additional studies estimated out-of-pocket expenditures, which may not necessarily reflect the real costs of a dengue episode [37], [40]. We used Huy et al.'s estimates to obtain indirect costs per dengue episode [37]. As Beaute and Vong's estimates were based on secondary analysis of data, they were excluded [15]. For Viet Nam, our best cost estimates were based on the results from an unpublished multicenter cost study in southern Viet Nam by Luong et al. [21], which included data on medical expenditures from four hospitals, transportation costs, and household impact. Patients were recruited based on severity, age, and type of setting, and adjusted the costs accordingly. Another study based on Viet Nam also provided detailed data on dengue; however, it was restricted only to dengue hemorrhagic fever (DHF) cases in children 15 yrs) based on data by the National Surveillance System (2004–2010). f The data by Kongsin et al. [19] are the same as the data used by Suaya et al. [2]. The costs per ambulatory case were estimated as 25% of those per hospitalized case based on Shepard et al. [49]. g Estimate for patients aged 18–64 years based on transport costs, average productivity loss per day, and household services lost per day. For hospitalized patients, the estimate considers the average number of days a person is hospitalized per dengue episode, and for ambulatory patients, the total number of visits per episode. Results The average annual number of reported cases in SEA was 386,000 patients (2001–2010), and 2,126 deaths. Using corresponding EFs, we obtained a yearly average of about 2.9 m cases of dengue illness in SEA (0.8 m hospitalized and 2.1 m ambulatory patients), 5,906 deaths, and a weighted overall EF of 7.6. Table 1 shows the annual average number of reported dengue cases in SEA (2001–2010), the estimated hospitalized, ambulatory, and total number of dengue cases, and the total number of deaths, using country-specific EFs. The lower and upper ranges for each of our estimates are shown in parentheses. Our literature review yielded 20 studies on unit costs per dengue episode [2], [15], [16], [19], [21], [23]–[25], [37]–[47]. We extracted data from the articles using a template similar to Table 2, with additional columns (e.g., date the article was reviewed, limitations). After applying our filtering criteria, we had sound data for five countries-Cambodia, Viet Nam, Malaysia, Thailand, and Singapore-one for each category of income-level defined by the World Bank (e.g., low-income country) [68], which makes our extrapolated estimates more consistent. Table 2 shows a summary of our best estimates for the unit costs per dengue episode for each country (2010 US dollars). While the summary data may not necessarily be representative of each country, to our knowledge they are the best cost data available. Table 3 shows the predicted values of direct and indirect unit costs per dengue case based on the linear regression estimates (R2 = 0.94 and 0.87, respectively), for those countries for which we did not have empirical data. Figure 1 and Figure 2 show the relation between GDP per capita and unit direct and indirect costs per episode respectively, and the 95% CI for each set of estimates. 10.1371/journal.pntd.0002055.g001 Figure 1 Direct costs per non-fatal dengue episode for hospitalized and ambulatory cases by per capita GDP (2010 US$). Source: Authors' calculations from [2], [16], [17], [19]–[21], [37], [39], [42]–[44], [47]. 10.1371/journal.pntd.0002055.g002 Figure 2 Indirect costs per non-fatal dengue episode for hospitalized and ambulatory cases by per capita GDP (2010 US$). Source: Authors' calculations from [2], [16], [17], [19]–[21], [37], [39], [42]–[44], [47]. 10.1371/journal.pntd.0002055.t003 Table 3 Predicted values of direct and indirect unit costs per dengue case, based on linear regression estimates (2010 US dollars). Country GDP per capita World Bank classification Direct Costs Indirect Costs Hosp. Amb. Hosp. Amb. Bhutan 2,010 Lower-middle 172.8 46.1 34.5 16.2 Brunei 28,832 High 1,747.4 465.8 733.6 343.9 Cambodiaa 791b Low 84.1 18.8 31.9 4.6 East Timor 571b Lower-middle 57.9 15.4 8.1 3.8 Indonesia 2,890 Lower-middle 236.8 63.1 52.3 24.5 Laos 976b Lower-middle 92.2 24.6 15.0 7.0 Malaysiaa 8,184 Upper-middle 659.9 244.2 203.3 178.0 Myanmar 721b Low 70.9 18.9 10.6 5.0 Philippines 2,063 Lower-middle 176.7 47.1 35.5 16.6 Singaporea 41,893b High 2,060.5 394.9 948.0 873.4 Thailanda 4,850 Upper-middle 584.9 146.2 50.0 12.5 Viet Nama 1,141b Lower-middle 63.7 21.6 12.7 9.9 a Unit costs were obtained from empirical data and not from extrapolation. b International Monetary Fund (IMF) estimate for 2010. Notation: GDP denotes gross domestic product; Hosp. denotes Hospitalized; Amb. denotes Ambulatory. Source: IMF [14]; World Bank [68]; and cost data sources shown in Table 2 [2], [16], [17], [19]–[21], [37], [39], [42]–[44], [47]. Economic and disease burden of dengue in SEA Table 4 shows the average total annual economic and disease burden of dengue by country. The table includes the 95% certainty level bounds obtained using 1,000 Monte Carlo simulations in parenthesis under each estimate. Using our best estimates for the total number of cases and the unit cost per dengue episode, we obtained an overall annual economic burden of dengue of US$950 million (m) (US$610m–US$1,384m). The average annual direct costs amounted to US$451m (US$289m–US$716m) and the indirect costs were US$499m (US$290m–US$688m). Indonesia was the country with the highest economic burden of dengue in the region, followed by Thailand, representing about 34% and 31% of the total economic burden of dengue, respectively. The average population for SEA in the years considered was about 574 m people [70]–[72]; hence the cost of dengue illness was about US$1.65 per capita (US$1.06–US$2.41). The costs per capita by country ranged from US$0.28 (US$0.19–US$0.39) in Viet Nam to US$14.99 (US$9.37–US$21.10) in Singapore. 10.1371/journal.pntd.0002055.t004 Table 4 Annual dengue economic and disease burden in DALYs, by country (average, 2001–2010). Country Population (1,000 s) Aggregate costs (2010 US$, 1,000 s) Cost per capita (2010 US$) DALYS Direct Indirect Total Bhutan 726 59 238 295 0.41 148 (39–84) (135–319) (183–389) (0.25–0.54) (86–198) Brunei 378 223 412 636 1.69 14 (154–296) (268–520) (441–802) (1.17–2.12) (9–19) Cambodia 13,670 6,264 10,317 16,540 1.21 15,452 (2,899–10,663) (3,890–19,558) (7,763–29,598) (0.57–2.17) (5,910–29,202) East Timor 1,061 163 199 363 0.34 417 (90–284) (119–257) (231–529) (0.22–0.50) (249–563) Indonesia 232,462 93,470 229,199 323,163 1.39 95,168 (64,017–130,726) (127,273–281,114) (205,440–407,748) (0.88–1.75) (52,759–117,836) Laos 5,931 3,427 1,654 5,093 0.86 2,369 (2,273–4,643) (1,154–2,125) (3,592–6,717) (0.61–1.13) (1,457–3,162) Malaysia 27,051 64,426 63,431 127,973 4.73 8,324 (47,195–98,585) (48,377–89,790) (90,478–181,432) (3.34–6.71) (5,517–12,393) Myanmar 46,916 6,917 7,607 14,476 0.31 13,620 (4,094–10,841) (4,675–10,083) (9,393–20,006) (0.20–0.43) (8,006–18,205) Philippines 88,653 20,656 60,740 80,829 0.91 37,685 (14,685–27,365) (35,148–79,301) (52,126–103,948) (0.59–1.17) (22,089–49,617) Singapore 4,476 25,156 42,076 67,090 14.99 1,089 (14,363–38,944) (26,751–56,578) (41,946–94,430) (9.37–21.10) (660–1,509) Thailand 67,796 215,722 74,303 290,028 4.28 28,475 (134,028–375,270) (39,335–139,060) (181,559–505,186) (2.68–7.45) (16,505–49,552) Viet Nam 85,007 14,814 8,659 23,453 0.28 11,079 (10,103–21,468) (6,269–11,890) (16,463–33,099) (0.19–0.39) (7,226–16,452) Total 574,236 451,297 498,836 949,940 1.65 213,839 (289,492–715,924) (290,043–688,415) (609,614–1,383,882) (1.06–2.41) (120,472–298,709) Note: Cost estimates and their corresponding 95% certainty levels (in parentheses), were obtained using 1,000 Monte Carlo simulations with the simultaneous variation of expansion factors (EFs), the share of hospitalized cases, unit costs for ambulatory and hospitalized cases, and disability-adjusted life years (DALYs). We obtained an annual average of 214,000 DALYs (range: 120,000–299,000 DALYs) for SEA (Table 4), which is equivalent to 372 DALYs per million inhabitants (range: 210–520). About 45% of the total disease burden in the region is incurred by Indonesia, followed by the Philippines with about 18% of the total. Using the original 1994 definition [22], the rate of DALYs per million population for dengue in SEA ranks higher than that of 17 of the 39 health conditions in SEA and the Western Pacific combined, including poliomyelitis (1 per m), Japanese encephalitis (199 per m), otitis media (219 per m), upper respiratory infections (222 per m), hepatitis B (349 per m). Compared to other neglected tropical diseases in this combined region, dengue ranks higher than schistosomiasis (4 per m), leprosy (38 per m), trachoma (149 per m), trichuriasis (188 per m), hookworm (191 per m), and ascariasis (209 per m). Dengue ranks just under leishmaniasis (386 per m) and malaria (443 per m) [57]. Discussion Our results show that dengue represents a substantial economic and disease burden in SEA. We combined multiple sources of data to quantify this burden. On average, about 52% of the total economic costs of dengue resulted from productivity lost (indirect costs), including non-fatal and fatal cases. The average per capita economic cost of dengue illness represents about 0.03% of the average per capita GDP in the region (in 2010), and total disease burden is 214,000 DALYs per year. Indonesia has a higher share of disease burden than economic burden, which is partly explained by the relatively lower costs per dengue episode. We used the average number of cases of dengue between 2001 and 2010 to obtain a stable estimate of the burden of dengue, which we consider more useful for policy purposes than an estimate for a specific year. Figure 3 shows the annual variation of total estimated dengue cases and economic burden of dengue in SEA. We are assuming that the EFs and unit costs are constant for all years. As expected, total costs are highly correlated with total number of cases (R2 = 0.94, p<0.001); however, the relation depends on which countries are facing an epidemic. While dengue epidemics in the region follow a similar pattern, total costs increase more sharply when the epidemic affects higher-income countries. For example, we estimated fewer dengue episodes in year 2005 (2.37 m) than in 2006 (2.46 m), but because the epidemic affected richer countries in 2005 (e.g., Singapore and Thailand) than in 2006 (e.g., Viet Nam, Indonesia, Cambodia, Philippines), the aggregate costs were higher in 2005 (US$1.02billion) than in 2006 (US$0.84billion). The costs for year 2005 were similar to those in 2008 (US$1.01billion) and 2009 (US$1.02), but the number of cases was much lower in 2005 (2.37 m) than in 2008 (3.37 m) and 2009 (3.42 m), when the dengue epidemic peaked in the poorer countries (e.g., Indonesia, Myanmar). 10.1371/journal.pntd.0002055.g003 Figure 3 Aggregate values of dengue episodes and economic burden by year for 12 countries in SEA (2001–2010). Source: Authors' calculations. We found substantial variability in the costs per dengue episode. There was also considerable variability in the country-specific EFs, as has been discussed elsewhere [7]. These variations were addressed using probabilistic analysis; however, costs per episode and EFs remain an area of uncertainty for most of the countries we considered. Our estimates of economic and disease burden of dengue are consistent with previous estimates from published studies (Table 5). Our estimates of economic burden, without considering costs such as prevention or vector control, for Cambodia, Malaysia, Singapore, and Thailand are higher than in previous studies [2], [16]–[20], and lower than a previous estimate in Viet Nam [21]. Compared to these studies, our higher estimates of economic burden arise mainly because previous studies did not adjust for underreporting of dengue episodes [2], [23], used smaller EFs [16]–[19], considered year intervals with lower reported dengue [18], estimated lower indirect costs [15], estimated productivity loss based on the minimum wage [16], [17], did not consider fatal cases [18], or adjusted for underreporting only of non-fatal cases [20]. Compared to previous estimates of disease burden, our estimates were higher for Myanmar [23], Singapore [20], and Cambodia [15], and lower for Thailand [24], [25]. Our higher estimate for DALYs were partly explained because the previous study for Myanmar only included DHF, did not correct for underreporting, and considered almost 30 years of reporting, which lowered the average reported cases [23], and the estimate for Singapore [20] did not consider an EF for fatal cases of dengue. 10.1371/journal.pntd.0002055.t005 Table 5 Comparison of estimates of annual economic and disease burden of dengue with previous studies, by country. Economic burden (US$, million) Disease burden (DALYsa) Years considered Source Cambodia 16.5 15,425 2001–2010 Present study 3.1 2001–2005 Suaya et al., 2009 [2] 8.0 8,243 2006–2008 Beaute and Vong, 2010 [15] Malaysia 128.0 8,324 2001–2010 Present study 42.4 2001–2005 Suaya et al., 2009 [2] 54.9 2002–2007 Lim et al., 2010 [18] 103.4 2009 Shepard et al. [16], updated 2013 [17] Myanmar 14.5 13,620 2001–2010 Present study 3,933b 1970–1997 Cho Min Naing, 2000 [23] Singapore 67.1 1,089 2001–2010 Present study 41.5c 734c 2000–2009 Carrasco et al.,2011 [20] Thailand 290.0 28,475 2001–2010 Present study 66.2 2000–2005 Lim et al., 2010 [18] 53.1 2001–2005 Suaya et al., 2009 [2] 126.3 2001–2005 Kongsin et al., 2010 [19] 31,546 1998–2002 Anderson et al., 2007 [25] 28,949 2001 Clark et al., 2005 [24] Viet Nam 23.5 11,079 2001–2010 Present study 30.3 2004–2007 Luong et al., 2012 [21] a Estimates of the number of disability-adjusted life years (DALYs) were extrapolated to 2010 based on population. b DALY estimates only include dengue hemorrhagic fever (DHF) episodes. c The economic and disease burden estimates correspond to Carrasco et al.'s estimates [20], based on the same methods and assumptions than those we used. Economic burden was based on the human capital approach, but Carrasco et al. also estimated annual economic burden of dengue using the friction cost method (US$35.1 million). Similarly, disease burden was estimated using disability weights from previous literature (with an age-weighting constant C = 1), but Carrasco et al. also estimated DALYs using disability weights from WHO and quality of life-based disability weights, and estimated DALYs with C = 1 and C≠1). The cost per capita associated to dengue in SEA was 68% of that found for the Americas as a whole (US$2.42; range: 1.01–4.47), but DALYs per m were 4.6 times higher than in the Americas (81 DALYs per m; range: 50–131 [3]; WHO's estimate was 73 DALYs per m [57]). This is partly explained by the higher incidence rates of DHF and dengue shock syndrome (DSS) in SEA, which together are approximately 18 times higher than that in the Americas [9], and the case fatality rate is 29 times higher (the estimated case fatality rate was 8/100,000). Also, the main drivers of cost in SEA and the Americas are Indonesia (27% of the total cases of dengue) and Brazil (39% of total cases), respectively. Brazil's GDP per capita is about 3.6 times that of Indonesia's [14] so the average cost per dengue case in the former is substantially higher. Our estimate of the absolute dengue disease burden of 214,000 DALYs in SEA alone is higher than that of the worldwide disease burden (DALYs) of poliomyelitis (34,000), diphtheria (174,000), or leprosy (194,000) [57]. The DALY rate per population of dengue (372 per million) exceeds that of other diseases of public health importance including Japanese encephalitis, upper respiratory infections, and hepatitis B, and other neglected tropical diseases such as ascariasis, trichuriasis, or hookworm for the combined WHO regions containing SEA. These results have some limitations and areas of uncertainty. First, the EFs we used to adjust for underreporting were derived from several empirical studies in countries of SEA that used different methodologies (e.g., cohort studies, capture-recapture, hospital records), and some differ in the age groups, or severity of dengue reported [7]. The rate of underreporting also depends on several factors including year of data collection, sample demographics, specific region, vector control activities, disease awareness, quality of the surveillance system. Due to paucity of data, we assumed that the rate of underreporting was constant for each country in SEA during the years considered in this study. Second, we assumed that the average unit costs of inpatient and outpatient treatments of dengue illness were constant across years. Our cost estimates were obtained from empirical studies that in some cases were limited to specific regions or facility types. We could further refine these cost estimates by adjusting other variables such as region, number of specialist physicians, healthcare system, and treatment and technology changes that might have developed since the reference study took place. These levels of detail were not available, but we obtained our estimates from the best accessible data. Third, because there were no studies for all countries in SEA, we had to extrapolate data based on similarities between countries, such as GDP per capita in the case of cost, and an index of healthcare quality for EFs [7]. Fourth, because we lacked more detailed data, we assumed that the age distribution of fatal cases was the same as the age distribution of dengue incidence. This is a conservative assumption, as existing literature suggests that severe episodes of dengue illness in SEA affect mostly infants and children [9], [13], [73], [74], and that children are more vulnerable than adults to shock syndrome [75]. Hence, we would expect the very young to have higher death rates than the rest of the population and therefore, the economic and disease burden might be even higher. Fifth, because the incidence of dengue varies considerably from year to year, we used the average cases of dengue between 2001 and 2010 to obtain more stable estimates. This averaging probably makes our estimates of dengue burden conservative, since several studies indicate that the total number of episodes of symptomatic dengue is increasing [5], [13], [74], [76]. Last, our estimates of the economic and disease burden of dengue illness were based on previous studies that considered the acute symptoms of dengue [2], [77]–[79]. A few recent studies suggest that dengue patients may present long-term symptoms [80]–[84], but there is yet no agreement on the frequency, intensity, or duration of these long-term consequences of dengue infection, sometimes referred to as Dengue Chronic Fatigue Syndrome [83]. If long-term sequelae of dengue are common and affect people's ability to work, then existing studies would be systematically underestimating the economic and disease burden. There was still too much uncertainty over the long-term sequelae of dengue to consider it in our calculations while being conservative. Despite these limitations and areas of uncertainty, we tried to make our estimates of economic and disease burden as accurate as possible considering the limited availability of data. The most important product of this analysis is estimates of the aggregate and country-specific economic and disease burden of dengue in SEA. These estimates use a consistent methodology that allows comparison among countries and empirically derived adjustments for underreporting. The estimated burden of dengue would have been even higher had we considered other economic costs, such as prevention and vector control [18], [19], [85], [86], disruption of health systems due to seasonal clustering of dengue, decreases in tourism [87], long-term sequelae of dengue [80], [83], or disease complications associated to dengue infection [63], [64], [66], [88]–[92]. Even without counting these additions, our results suggest that exploring new approaches to reduce burden of dengue would be economically valuable. Supporting Information Figure S1 PRISMA 2009 Flow Diagram. Source: [48]. (TIF) Click here for additional data file. Table S1 PRISMA checklist for literature review. Note: As this manuscript is not a systematic review nor meta-analysis, the entries in the checklist are limited to those items applicable to this manuscript. Source: [48]. (DOCX) Click here for additional data file.
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Diagnostic Accuracy of NS1 ELISA and Lateral Flow Rapid Tests for Dengue Sensitivity, Specificity and Relationship to Viraemia and Antibody Responses
Vu Ty Hang, Nguyen Minh Nguyet, Dinh The Trung … (2009)
Introduction Dengue is a major public health problem in many parts of the tropical developing world [1],[2]. Dengue is caused by infection with one of four serotypes of dengue virus (DENV1-4), which are arboviruses belonging to the Flaviviridae family. Although most DENV infections are asymptomatic, a proportion result in clinically apparent disease that varies in severity from mild undifferentiated fever through to more severe syndromes, primarily dengue haemorrhagic fever (DHF) and dengue shock syndrome (DSS). DHF is a vasculopathy characterized by capillary leakage and haematological dysregulation; in severe case hypovolaemic shock (DSS) may develop. There are no licensed vaccines or specific antiviral therapies for dengue, and patient management relies on good supportive care. Timely, sensitive and specific diagnosis of DENV infection can assist in patient management. Prompt diagnosis of index cases can also facilitate vector control activities in the community so as to mitigate further transmission. NS1 is 55 kDa glycoprotein secreted by DENV infected cells in vitro and in vivo. The function of NS1 in viral replication is not well understood, other than it appears to be essential and might serve to anchor the replication complex to the membrane of the endoplasmic reticulum [3]. NS1 is postulated to contribute to the pathogenesis of dengue. First, in children elevated NS1 plasma concentrations early in illness are associated with more severe disease, possibly reflecting higher viral burdens in these patients [4],[5]. The potential for early NS1 concentrations to predict clinical outcome has been postulated but not assessed [4]. It has been suggested that high NS1 levels may activate complement in solution and/or by directly binding endothelial cells, and may establish foci for immune complex formation leading to complement activation, endothelial damage and capillary leakage [5],[6]. The availability of commercial ELISA assays to detect the DENV NS1 protein in acute plasma provides an additional dengue diagnostic tool to the existing approaches of PCR, serology and, less frequently, virus isolation [7]–[14]. The assessment of NS1 assays as diagnostic tools across a wide range of patient populations and viral serotypes is an important part of the process of identifying where these assays may fit into existing dengue diagnostic algorithms. The purpose of the current study was two-fold. First, to assess the sensitivity and specificity of two commercial NS1 assays, the Platelia ELISA and a lateral flow rapid test (NS1-LFRT), in the context of different viral serotypes, viral burdens and clinical presentations in Vietnamese patients. Second, to assess the specificity of these NS1 assays in patients with other confirmed infections. Our findings suggest that both the Platelia ELISA and NS1-LFRT are specific tools for diagnosing acute dengue, though the sensitivity of both is influenced by the level of viraemia and host humoral immune response. Materials and Methods Patient enrolment A series of prospective clinical research studies on dengue are in progress at the Hospital for Tropical Diseases (HTD) in Ho Chi Minh City, Viet Nam. Patients greater than 2 years of age admitted to one of the intensive care units (adult or paediatric) or to one of the general wards with a clinical suspicion of dengue as their primary diagnosis are eligible for enrolment following written informed consent by the patient or guardian. All studies have received approval from the Ethics Committee of the HTD and from the Oxford Tropical Research Ethics Committee. All patients in these studies are assessed daily by a study physician and have serial haematocrit and platelet estimations performed, as well as appropriate sampling for diagnostic serology and virology. Other investigations and clinical management are at the discretion of the attending physicians. After discharge each patient is classified using the current WHO criteria for DF, DHF and DSS. From November 2007 to January 2008, we prospectively tested consecutive acute plasma samples from all children and adults enrolled in these studies. Plasma samples from patients with another confirmed diagnosis (malaria, enteric fever or leptospirosis) were obtained from stored specimens collected as part of other prospective studies at HTD between 2001 and 2008. The diagnosis of Plasmodium falciparum malaria was made by blood smear. Enteric Fever was diagnosed by blood culture of S. typhi or S paratyphi. Leptospirosis was diagnosed by positive serology (microscopic agglutination test). All samples tested were collected within 10 days of illness onset. Dengue diagnostics A capture IgM and IgG ELISA assay using DENV/JEV antigens and mAb reagents provided by Venture Technologies (Sarawak, Malaysia), was performed as previously described [15]. The interpretation of primary and secondary serological responses was based on the magnitude of IgG ELISA Units in early convalescent plasma samples taking into account the day of illness. The cut-off in IgG ELISA units for distinguishing primary from secondary dengue by day of illness was calibrated using a panel of acute and early convalescent sera from Vietnamese dengue patients that were assayed in the laboratory of Dr Sutee Yoksan using a reference IgM and IgG antigen capture ELISA described previously (the “AFRIMS ELISA”) [16]. DENV loads in plasma were measured using an internally-controlled, serotype-specific, real-time RT-PCR assay that has been described previously [17]. Results were expressed as cDNA equivalents per milliliter of plasma. The dengue IgG indirect ELISA employed uncoated wells and wells coated with recombinant E proteins (Hawaii Biotech, Hawaii) (2 µg/ml). Coated and uncoated wells were blocked with 3% bovine serum albumin for 1 hr. Twofold serial dilutions of plasma, starting at 1/100, were added to each well for 2 hrs, then washed with PBS/Tween20. HRP-conjugated goat anti-human IgG was then added to each well for 2 hrs, after which wells were washed and substrate (TMB) added. The optical density was read at 450 nm. After subtracting the O.D obtained in uncoated wells, the endpoint titre for each plasma sample was defined as the reciprocal of the dilution giving an optical density of 0.3. The NS1 Platelia and lateral flow rapid tests (NS1-LFRT) were provided by BioRad (Hercules, CA) and were performed according to the manufacturer's instructions. Both NS1 tests were performed in parallel on the same day by the same experienced technician with freshly collected acute plasma samples from each patient. Samples that were defined as equivocal in the NS1 Platelia ELISA assay were repeated. If they were still equivocal they were regarded as being negative. For the NS1-LFRT, each assay strip was independently assessed by the technician conducting the test and a 2nd technician who was blind to the first assessment. During the study, there were no examples of discordance in the interpretation of any NS1-LFRT test. The technicians performing and scoring the NS1-assays were blind to the reference assay results and to any clinical information on the patients. The reference algorithm No single diagnostic assay can diagnose all dengue patients at the various times they may present with symptoms. Consequently, a diagnosis of “confirmed acute dengue” was reached using an algorithm (described in Fig. S1) based on 3 assays; RT-PCR detection of DENV RNA in plasma, and changes in DENV-reactive IgM and IgG levels in paired plasma specimens. In brief, a diagnosis of “lab-confirmed dengue” was made if there was a clinical suspicion of dengue and, a) the RT-PCR assay was positive, b) DENV-IgM seroconversion (i.e. from negative to positive) occurred between paired specimens, c) levels of DENV reactive IgM increased significantly between paired specimens and were very high in the 2nd sample (at least 20% increase in DENV-IgM ELISA Units from 1st to 2nd sample and 2nd sample has at least 20 ELISA Units) , d) there was a four-fold rise in IgG titre to recombinant DENV E proteins measured in indirect ELISA in the presence of significant DENV IgM levels or e) IgG seroconversion was demonstrated in the IgG capture ELISA in the presence of significant DENV IgM levels. The rationale for using two approaches to measuring DENV-reactive IgG is two-fold. The indirect ELISA provides a quantitative measure of IgG titres to recombinant E proteins and is therefore able to detect four-fold changes in IgG levels to the E protein. The IgG antigen-capture assay provides a semi-quantitative measure of IgG levels and is best suited to detecting seroconversion (i.e. from negative to positive). In the context of IgG serology, a diagnosis of “lab confirmed dengue” is only made when the changes in acute/early convalescent IgG levels (i.e. seroconversion or 4-fold change) occur in the presence of detectable DENV-reactive IgM levels. This provides greater specificity for a diagnosis of acute dengue than using IgG measurements alone. Statistics All statistical analysis was performed using Intercooled STATA version 9.2 (StataCorp, TX). Significance was assigned at P 3 day (n = 50) NS1 (+) 35 30 NS1 (−) 15 20 70.0 (55.4–82.1) 60.0 (45.1–73.5) a Fisher's exact test. NS1 sensitivity in primary or secondary infection In general, NS1 detection was higher in patients with primary dengue than secondary dengue (Table 4). This difference was statistically significant for the NS1-LFRT (P = 0.01) and of borderline significance for the Platelia ELISA (P = 0.07). The difference in sensitivity between primary and secondary dengue was not associated with the illness day at the time of testing (primary dengue, mean day of illness (SD)), 3.25 (0.21)) versus secondary dengue, 3.66 (0.13), P = 0.6)). Reduced sensitivity was also not associated with viraemia levels between primary and secondary dengue cases (log10 mean viraemia (SD), primary: 8.05 (SD:1.40) versus secondary 7.66 (SD:1.53), P = 0.2). A possible basis for reduced sensitivity in secondary dengue is that NS1, along with other viral antigens, is sequestered in immune complexes when a substantial level of DENV-reactive IgG is present. To test this hypothesis, we analysed NS1 detection sensitivity in the context of DENV-reactive IgG and IgM antibody in the test sample. The presence of measurable DENV-reactive IgG in the test sample was associated with a significant reduction (P<0.001) in NS1 sensitivity in both assays (Table 5). To a lesser extent, DENV-reactive IgM was also associated with a reduction in NS1 sensitivity and was statistically significant in the Platelia assay (P = 0.03) (Table 6). 10.1371/journal.pntd.0000360.t004 Table 4 Sensitivity of NS1 assays in patients with primary and secondary serological profiles. Sample group NS1 status Platelia (95% CI) P valuea NS1-LFR (95% CI) P valuea Sensitivity of NS1 in primary (n = 24) NS1 (+) 23 0.07 22 0.01 NS1 (−) 1 2 95.8 (78.9–99.9) 91.7 (73.0–98.9) Sensitivity of NS1 in secondary (n = 93) NS1 (+) 73 61 NS1 (−) 20 32 78.5 (68.8–86.3) 65.6 (55.0–75.1) a Fisher's exact test. 10.1371/journal.pntd.0000360.t005 Table 5 Sensitivity of each NS1 assay in the presence or absence of measurable DENV-reactive IgG in the test sample. Statusa Total NS1 Platelia NS1-LFRT Sensitivity (% ) (95% CI) Positive Negative Positive Negative NS1 Platelia NS1-LFRT IgG positive 38 23 15 18 20 60.5 (43.4–76.0) 47.4 (31.0–64.2) IgG negative 87 81 6 73 14 93.1 (85.6–97.4) 83.9 (74.5–90.9) P value P<0.001 P<0.001 a IgG in test sample. 10.1371/journal.pntd.0000360.t006 Table 6 Sensitivity of each NS1 assay in the presence or absence of measurable DENV-reactive IgM in the test sample. Statusa Total NS1 Platelia NS1-LFRT Sensitivity (% ) (95% CI) Positive Negative Positive Negative NS1 Platelia NS1-LFRT IgM positive 35 25 10 23 12 71.4 (53.7–85.3) 65.7 (47.8–80.9) IgM negative 90 79 11 68 22 87.7 (79.2–93.7) 75.5 (65.4–84.0) P value P = 0.03 P = 0.26 a IgM in test sample. NS1 sensitivity in relation to viraemia levels We hypothesised that plasma viremia levels would be associated with the detection of plasma NS1, since NS1, like virions, is a product of infected cells. Accordingly, viremia levels were significantly higher in patients who were NS1-positive at the time of study enrolment versus those who NS1 negative, in both the Platelia assay (Fig. 2A) and NS1-LFRT (data not shown). When viraemia levels were compared in patients with matched illness lengths (3 days), viraemia levels were also significantly higher in NS1-positive patients (Fig. 2B). 10.1371/journal.pntd.0000360.g002 Figure 2 Viral loads by NS1 status in the Platelia ELISA at the time of study enrolment or after 3 days of illness. Shown is the mean (interquartile and range) viraemia level in NS1 positive and NS1 negative (Platelia ELISA) patients with a measurable viraemia (n = 111) at (A) the time of study enrolment or (B) after 3 days of illness durations. The limit of detection of the assay is shown with a dashed line. Viraemia levels were significantly higher in NS1 positive patients relative to NS1 negative patients (Mann-Whitney test). The same observations with regard to viraemia levels were made with the NS1 LFRT (data not shown). NS1 sensitivity in relation to viral serotype The sensitivity of each NS1 assay was considered in the context of the infecting serotype. NS1 detection was significantly reduced in DENV-2 infected patients (55%) relative to DENV-1 (98%; P<0.001) or DENV-3 (96%; P = 0.004) infected patients in both Platelia (Fig. 3A) and LFRT (data not shown). The reduced sensitivity of NS1 assays for DENV-2 infected patients could in part be related to the serological response in these individuals; there was a statistically non-significant trend towards more secondary dengue in patients with DENV-2 (85%) than either DENV-1 (76%) or DENV-3 (73%) (P = 0.36) and a relatively greater proportion of DENV-2 infected patients had measurable DENV reactive IgG (Fig. 3B), rather than IgM (Fig. 3C), in the test sample. There was also a statistically non-significant trend toward lower viraemia in the test samples from DENV-2 infected patients (DENV-2 log10 mean viraemia (SD); 7.38(1.68)) versus DENV-1 (7.97(1.49)) or DENV-3 (7.79(1.47)). The reduced sensitivity of NS1 detection in DENV-2 infected patients was not due to significant differences in the mean duration of illness at the time of sampling (DENV-1, mean 3.3 days; DENV-2, mean 3.4 days; DENV-3, mean 3.3 days). In summary, NS1 detection was a robust diagnostic test in DENV-1 and DENV-3 infections, but was less sensitive in DENV-2 infections in part because test samples from these patients were generally more likely to have a concomitant DENV-IgG response, suggestive of secondary infection, and lower viraemias, all of which are associated with reduced NS1 detection (see Table 5 and Fig. 2B). 10.1371/journal.pntd.0000360.g003 Figure 3 NS1 sensitivity of the Platelia ELISA in the context of viral serotype and humoral immune response. Shown in (A) is the sensitivity of NS1 detection in the enrolment sample according to the infecting serotype identified by real-time RT-PCR (results for DENV-4 not shown as the sample size was small: n = 3). NS1 detection in DENV-2 infected patients was significantly less sensitive than for DENV-1 or DENV-3. The proportion of patients with detectable DENV-reactive (B) IgG or (C) IgM antibodies (measured by capture ELISAs) in the test sample was also related to the infecting serotype. Test samples from DENV-2 infected patients were more likely to have measurable levels of DENV-reactive IgG but not IgM, albeit this was not statistically significant. NS1 specificity in healthy blood donors and patients with other confirmed diagnoses Since the number of patients with no evidence of acute dengue was small (n = 13) in this study (Table 1), efforts were made to assess the specificity of dengue NS1 assays in patients with other infectious diseases whose transmission geographically overlaps with dengue. To this end, frozen acute (within 10 days of illness onset) plasma samples from patients with culture confirmed enteric fever (S. Typhi, n = 25 and Paratyphi, n = 25), smear positive P. falciparum malaria (n = 52), serologically-proven Japanese encephalitis (n = 11) and leptospirosis (n = 12) were tested in parallel by both NS1 Platelia ELISA and NS1-LFRT. In all cases, NS1 tests were negative in these samples. Discussion No single diagnostic assay in isolation is adequately sensitive and specific enough to diagnose all acute cases of dengue. DENV-specific RT-PCR is a robust test during the viraemic febrile phase, but is less sensitive around the time of defervescence, a time when the clinical complications of vascular leakage are most likely to manifest. DENV IgM serology is a simple and robust approach to diagnosis, but this method is not sensitive in the very early stages of disease and strictly, requires paired specimens for definitive laboratory determination. Similarly, IgG serology is not sensitive early in the illness, requires paired specimens and lacks specificity because of cross-reactivity with other flaviviruses. The present study has demonstrated that NS1 detection via ELISA assay or LFRT, particularly in the first 3 days of illness, provides a reasonably sensitive and specific approach to dengue diagnosis in hospitalized patients using a single specimen. Accordingly, we have revised the dengue diagnostic algorithm used by our laboratory to accommodate NS1 testing (Fig. S2). Studies of the sensitivity and specificity of the Platelia ELISA have been reported previously and, collectively, several prominent themes are evident. First, not every acute dengue case has measurable NS1 antigenaemia and the present study suggests that this is a reflection of the viraemia, with NS1 negative patients having a significantly lower mean viraemia than NS1 positive patients with the same duration of illness history. Second, sensitivity declines with increasing time since the onset of symptoms and this is likely a reflection of decreasing viral burden [7],[10],[13]. Third, Platelia assays are less sensitive in secondary dengue cases [7],[10] and this is consistent with our finding of reduced sensitivity in secondary dengue cases and substantially reduced sensitivity in test samples with a measurable level of anti-DENV IgG. A possible explanation for reduced NS1 sensitivity in the presence of a measurable anti-DENV antibody response is that plasma NS1 is sequestered in immune complexes and that target epitopes are not accessible to either the plate-bound or probe mAb in the NS1 ELISA. Indeed, efforts to dissociate immune complexes can enhance the sensitivity of the Platelia assay [14]. The clinical implications of this in dengue endemic areas are subtle - patients who present to health care facilities more than 3 days after onset of symptoms with clinical signs of vascular leakage, haemorrhage or even DSS may already have an established anamnestic humoral immune response characteristic of a secondary infection and are therefore more likely to be NS1 negative. It is therefore imperative that clinical and laboratory staff understand the limitations of existing NS1 antigen tests and that a NS1 negative assay result does not exclude dengue as a diagnosis. Interestingly, in this study NS1 sensitivity was substantially lower for patients with DENV-2 infections In part, this may relate to the trend for a higher proportion of DENV-2 patients having secondary dengue and having measurable anti-DENV IgG in the test sample. An alternative explanation is that the affinity of the NS1-specific probe and detector mAbs is lower for the lineage (Asian1) of DENV-2 currently circulating in Viet Nam than for DENV-1 or DENV-3; further experiments would be required to address this hypothesis. An assessment of the NS1-LFRT versus the Platelia ELISA has been conducted previously in adults in French Guiana with a reported overall sensitivity and specificity of 81% and 100% respectively for the NS1-LFRT [7]. Unlike this previous study, we compared the accuracy of each assay, performed in parallel on the same day, in a group of paediatric and adult patients encompassing a broad range of dengue disease severities and considered the results in the context of viral burden and humoral immune response. Overall, the NS1-LFRT assay was modestly less sensitive than the Platelia NS1 ELISA in this study (73% versus 83%) but importantly retained high specificity (100%). The attraction of the NS1-LFRT relative to the Platelia ELISA is its ease of use and speed (15 minutes versus 2 hrs), though this comes at a greater cost per test (∼$10 vs $5). An obvious setting in which to use this assay format is in primary health care clinics for testing of febrile patients presenting early in their illness. In our hospital-based setting, the sensitivity of the NS1-LFRT was 81% in patients admitted within 3 days of illness onset. The ongoing development of specific anti-viral drugs for dengue [18] makes the availability of accurate rapid tests, such as the NS1-LFRT even more important since diagnosing patients quickly and early will provide the greatest window of opportunity for an anti-viral drug to deliver a clinical benefit. A weakness of the current study is that relatively few of the patients in the prospectively assessed patient population did not have dengue. We compensated for this by including a large number of patients with known alternative diagnoses. The strengths of the current study, and point of difference from published studies, are that we included patients with severe clinical presentations and investigated the relationship between NS1 positivity, viraemia levels, illness history and Ig responses. The finding that viraemia levels are, on average, higher in NS1-positive patients is a novel finding in the context of these commercial assays. The significance of this observation is tied to the widely accepted view that early viraemia levels are associated with disease severity [19],[20]. Thus, NS1 detection may be biased towards detecting those patients who, on average, have the highest viraemias and with relatively higher risks of developing complications during their illness. Future studies should measure the prognostic value of early NS1 measurements for predicting patients at risk of developing severe complications, e.g. DSS. Supporting Information Figure S1 A positive result in any of the first 5 tests is sufficient for a lab diagnosis of confirmed dengue. (5.58 MB TIF) Click here for additional data file. Figure S2 Suggested place for NS1 testing in a diagnostic algorithm approach to confirmation of dengue. A positive result in any of the first 6 tests is sufficient for a lab diagnosis of confirmed dengue. (6.05 MB TIF) Click here for additional data file. Checklist S1 STARD checklist (6.59 MB PDF) Click here for additional data file. Flowchart S1 STARD flowchart for NS1 LFRT (0.03 MB DOC) Click here for additional data file. Flowchart S2 STARD flowchart for Platelia (0.03 MB DOC) Click here for additional data file.
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Burden of symptomatic dengue infection in children at primary school in Thailand: a prospective study.
Supamit Chunsuttiwat, T Endy, Francis Ennis … (2007)
Dengue viruses are a major cause of morbidity and mortality in tropical and subtropical areas. Our aim was to assess prospectively the burden of dengue-related illness in children in Thailand. We did a prospective study in a cohort of children at primary school in northern Thailand from 1998 to 2002. We assessed the burden of dengue illness as disability-adjusted life years (DALYs) and patient costs per illness. Dengue accounted for 328 (11%) of the 3056 febrile cases identified in 2114 children during the study period. The mean burden of dengue was 465.3 (SD 358.0; range 76.5-954.0) DALYs per million population per year, accounting for about 15% of DALYs lost to all febrile illnesses (3213.1 [SD 2624.2] DALYs per million per year). Non-hospitalised patients with dengue illnesses represented a substantial proportion of the overall burden of disease, with 44-73% of the total DALYs lost to dengue each year due to such illness. The infecting dengue serotype was an important determinant of DALYs lost: DEN4 was responsible for 1% of total DALYs lost, DEN1 for 9%, DEN2 for 30%, and DEN3 for 29%. Use of prospective data to estimate the burden of disease shows that most DALYs lost to dengue illness were the result of non-hospitalised illnesses of long duration. Thus, inclusion of non-hospitalised cases is critical to accurately assess the total burden of dengue illness.
Author and article information
Contributors
Jacqueline Kyungah Lim: +82-2-881-1340
,
+82-2-872-2801
,
kajlim@gmail.com
Neal Alexander: Neal.Alexander@lshtm.ac.uk
Gian Luca Di Tanna: glditanna@gmail.com
Journal
Journal ID (nlm-ta): BMC Health Serv Res
Journal ID (iso-abbrev): BMC Health Serv Res
Title:
BMC Health Services Research
Publisher:
BioMed Central
(London
)
ISSN
(Electronic):
1472-6963
Publication date
(Electronic):
29
December
2017
Publication date PMC-release: 29
December
2017
Publication date Collection: 2017
Volume: 17
Electronic Location Identifier: 850
Affiliations
[1
]ISNI 0000 0000 9629 885X, GRID grid.30311.30, Global Dengue and Aedes-transmitted Diseases Consortium (GDAC), , International Vaccine Institute (IVI), ; SNU Research Park, Gwankak-ro 1, Seoul, Gwanak-gu 151-191 South Korea
Article
Publisher ID: 2789DOI: 10.1186/s12913-017-2789-8
PMC ID: 5747037
PubMed ID: 29284474
SO-VID: 62213186-90c5-4c06-a0c4-b35c120065a3
Copyright © © The Author(s). 2017
License:
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
History
Date
received
: 9
May
2017
Date
accepted
: 11
December
2017
Funding
Funded by: United Kingdom Medical Research Council and Department for International Development
(DFID)
Award ID: MR/K012126/1
Categories
Subject:
Research Article
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issue-copyright-statement © The Author(s) 2017
ScienceOpen disciplines: Health & Social care
Data availability:
ScienceOpen disciplines: Health & Social care