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  1. Undurraga EA, Halasa YA, Shepard DS
    PLoS Negl Trop Dis, 2013;7(2):e2056.
    PMID: 23437407 DOI: 10.1371/journal.pntd.0002056
    BACKGROUND: Dengue virus infection is the most common arthropod-borne disease of humans and its geographical range and infection rates are increasing. Health policy decisions require information about the disease burden, but surveillance systems usually underreport the total number of cases. These may be estimated by multiplying reported cases by an expansion factor (EF).

    METHODS AND FINDINGS: As a key step to estimate the economic and disease burden of dengue in Southeast Asia (SEA), we projected dengue cases from 2001 through 2010 using EFs. We conducted a systematic literature review (1995-2011) and identified 11 published articles reporting original, empirically derived EFs or the necessary data, and 11 additional relevant studies. To estimate EFs for total cases in countries where no empirical studies were available, we extrapolated data based on the statistically significant inverse relationship between an index of a country's health system quality and its observed reporting rate. We compiled an average 386,000 dengue episodes reported annually to surveillance systems in the region, and projected about 2.92 million dengue episodes. We conducted a probabilistic sensitivity analysis, simultaneously varying the most important parameters in 20,000 Monte Carlo simulations, and derived 95% certainty level of 2.73-3.38 million dengue episodes. We estimated an overall EF in SEA of 7.6 (95% certainty level: 7.0-8.8) dengue cases for every case reported, with an EF range of 3.8 for Malaysia to 19.0 in East Timor.

    CONCLUSION: Studies that make no adjustment for underreporting would seriously understate the burden and cost of dengue in SEA and elsewhere. As the sites of the empirical studies we identified were not randomly chosen, the exact extent of underreporting remains uncertain. Nevertheless, the results reported here, based on a systematic analysis of the available literature, show general consistency and provide a reasonable empirical basis to adjust for underreporting.

  2. Shepard DS, Undurraga EA, Halasa YA
    PLoS Negl Trop Dis, 2013;7(2):e2055.
    PMID: 23437406 DOI: 10.1371/journal.pntd.0002055
    BACKGROUND: Dengue poses a substantial economic and disease burden in Southeast Asia (SEA). Quantifying this burden is critical to set policy priorities and disease-control strategies.

    METHODS AND FINDINGS: We estimated the economic and disease burden of dengue in 12 countries in SEA: Bhutan, Brunei, Cambodia, East-Timor, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Viet Nam. We obtained reported cases from multiple sources--surveillance data, World Health Organization (WHO), and published studies--and adjusted for underreporting using expansion factors from previous literature. We obtained unit costs per episode through a systematic literature review, and completed missing data using linear regressions. We excluded costs such as prevention and vector control, and long-term sequelae of dengue. Over the decade of 2001-2010, we obtained an annual average of 2.9 million (m) dengue episodes and 5,906 deaths. The annual economic burden (with 95% certainty levels) was US$950m (US$610m-US$1,384m) or about US$1.65 (US$1.06-US$2.41) per capita. The annual number of disability-adjusted life years (DALYs), based on the original 1994 definition, was 214,000 (120,000-299,000), which is equivalent to 372 (210-520) DALYs per million inhabitants.

    CONCLUSION: Dengue poses a substantial economic and disease burden in SEA with a DALY burden per million inhabitants in the region. This burden is higher than that of 17 other conditions, including Japanese encephalitis, upper respiratory infections, and hepatitis B.

  3. Shepard DS, Undurraga EA, Lees RS, Halasa Y, Lum LCS, Ng CW
    Am J Trop Med Hyg, 2012 Nov;87(5):796-805.
    PMID: 23033404 DOI: 10.4269/ajtmh.2012.12-0019
    Dengue represents a substantial burden in many tropical and sub-tropical regions of the world. We estimated the economic burden of dengue illness in Malaysia. Information about economic burden is needed for setting health policy priorities, but accurate estimation is difficult because of incomplete data. We overcame this limitation by merging multiple data sources to refine our estimates, including an extensive literature review, discussion with experts, review of data from health and surveillance systems, and implementation of a Delphi process. Because Malaysia has a passive surveillance system, the number of dengue cases is under-reported. Using an adjusted estimate of total dengue cases, we estimated an economic burden of dengue illness of US$56 million (Malaysian Ringgit MYR196 million) per year, which is approximately US$2.03 (Malaysian Ringgit 7.14) per capita. The overall economic burden of dengue would be even higher if we included costs associated with dengue prevention and control, dengue surveillance, and long-term sequelae of dengue.
  4. Shepard DS, Undurraga EA, Betancourt-Cravioto M, Guzmán MG, Halstead SB, Harris E, et al.
    PLoS Negl Trop Dis, 2014 Nov;8(11):e3306.
    PMID: 25412506 DOI: 10.1371/journal.pntd.0003306
    Dengue presents a formidable and growing global economic and disease burden, with around half the world's population estimated to be at risk of infection. There is wide variation and substantial uncertainty in current estimates of dengue disease burden and, consequently, on economic burden estimates. Dengue disease varies across time, geography and persons affected. Variations in the transmission of four different viruses and interactions among vector density and host's immune status, age, pre-existing medical conditions, all contribute to the disease's complexity. This systematic review aims to identify and examine estimates of dengue disease burden and costs, discuss major sources of uncertainty, and suggest next steps to improve estimates. Economic analysis of dengue is mainly concerned with costs of illness, particularly in estimating total episodes of symptomatic dengue. However, national dengue disease reporting systems show a great diversity in design and implementation, hindering accurate global estimates of dengue episodes and country comparisons. A combination of immediate, short-, and long-term strategies could substantially improve estimates of disease and, consequently, of economic burden of dengue. Suggestions for immediate implementation include refining analysis of currently available data to adjust reported episodes and expanding data collection in empirical studies, such as documenting the number of ambulatory visits before and after hospitalization and including breakdowns by age. Short-term recommendations include merging multiple data sources, such as cohort and surveillance data to evaluate the accuracy of reporting rates (by health sector, treatment, severity, etc.), and using covariates to extrapolate dengue incidence to locations with no or limited reporting. Long-term efforts aim at strengthening capacity to document dengue transmission using serological methods to systematically analyze and relate to epidemiologic data. As promising tools for diagnosis, vaccination, vector control, and treatment are being developed, these recommended steps should improve objective, systematic measures of dengue burden to strengthen health policy decisions.
  5. Kassebaum NJ, Bertozzi-Villa A, Coggeshall MS, Shackelford KA, Steiner C, Heuton KR, et al.
    Lancet, 2014 Sep 13;384(9947):980-1004.
    PMID: 24797575 DOI: 10.1016/S0140-6736(14)60696-6
    BACKGROUND: The fifth Millennium Development Goal (MDG 5) established the goal of a 75% reduction in the maternal mortality ratio (MMR; number of maternal deaths per 100,000 livebirths) between 1990 and 2015. We aimed to measure levels and track trends in maternal mortality, the key causes contributing to maternal death, and timing of maternal death with respect to delivery.

    METHODS: We used robust statistical methods including the Cause of Death Ensemble model (CODEm) to analyse a database of data for 7065 site-years and estimate the number of maternal deaths from all causes in 188 countries between 1990 and 2013. We estimated the number of pregnancy-related deaths caused by HIV on the basis of a systematic review of the relative risk of dying during pregnancy for HIV-positive women compared with HIV-negative women. We also estimated the fraction of these deaths aggravated by pregnancy on the basis of a systematic review. To estimate the numbers of maternal deaths due to nine different causes, we identified 61 sources from a systematic review and 943 site-years of vital registration data. We also did a systematic review of reports about the timing of maternal death, identifying 142 sources to use in our analysis. We developed estimates for each country for 1990-2013 using Bayesian meta-regression. We estimated 95% uncertainty intervals (UIs) for all values.

    FINDINGS: 292,982 (95% UI 261,017-327,792) maternal deaths occurred in 2013, compared with 376,034 (343,483-407,574) in 1990. The global annual rate of change in the MMR was -0·3% (-1·1 to 0·6) from 1990 to 2003, and -2·7% (-3·9 to -1·5) from 2003 to 2013, with evidence of continued acceleration. MMRs reduced consistently in south, east, and southeast Asia between 1990 and 2013, but maternal deaths increased in much of sub-Saharan Africa during the 1990s. 2070 (1290-2866) maternal deaths were related to HIV in 2013, 0·4% (0·2-0·6) of the global total. MMR was highest in the oldest age groups in both 1990 and 2013. In 2013, most deaths occurred intrapartum or postpartum. Causes varied by region and between 1990 and 2013. We recorded substantial variation in the MMR by country in 2013, from 956·8 (685·1-1262·8) in South Sudan to 2·4 (1·6-3·6) in Iceland.

    INTERPRETATION: Global rates of change suggest that only 16 countries will achieve the MDG 5 target by 2015. Accelerated reductions since the Millennium Declaration in 2000 coincide with increased development assistance for maternal, newborn, and child health. Setting of targets and associated interventions for after 2015 will need careful consideration of regions that are making slow progress, such as west and central Africa.

    FUNDING: Bill & Melinda Gates Foundation.

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