Approaches to refining estimates of global burden and economics of dengue.

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dc.contributor.author Shepard, Donald S
dc.contributor.author Undurraga, Eduardo A
dc.contributor.author Betancourt-Cravioto, Miguel
dc.contributor.author GuzmÌÁn, MarÌ_a G
dc.contributor.author Halstead, Scott B
dc.contributor.author Harris, Eva
dc.contributor.author Mudin, Rose Nani
dc.contributor.author Murray, Kristy O
dc.contributor.author Tapia-Conyer, Roberto
dc.contributor.author Gubler, Duane J
dc.date.accessioned 2019-01-28T17:41:51Z
dc.date.available 2019-01-28T17:41:51Z
dc.date.issued 2014
dc.identifier.issn 1935-2727
dc.identifier.issn 1935-2735
dc.identifier.other PMC4238988
dc.identifier.uri https://hdl.handle.net/10192/36346
dc.description.abstract 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.
dc.format.extent 1 file
dc.language English
dc.language.iso eng
dc.publisher Public Library of Science
dc.relation.isversionof 10.1371/journal.pntd.0003306
dc.rights Creative Commons Attribution 4.0 International License
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.subject Epidemiological Methods and Statistics
dc.subject Infectious Disease Modeling
dc.subject RC955-962
dc.subject Socioeconomic Aspects of Health
dc.subject Population Modeling
dc.subject Public aspects of medicine
dc.subject Economic Epidemiology
dc.subject Health Care
dc.subject RA1-1270
dc.subject Economics
dc.subject Research Article
dc.subject Infectious Diseases
dc.subject Biology and Life Sciences
dc.subject Arctic medicine. Tropical medicine
dc.subject Dengue Fever
dc.subject Medicine and Health Sciences
dc.subject Infectious Disease Epidemiology
dc.subject Neglected Tropical Diseases
dc.subject Computational Biology
dc.subject Plant Pathology
dc.subject Global Health
dc.subject Plant Science
dc.subject Epidemiology
dc.title Approaches to refining estimates of global burden and economics of dengue.
dc.type Article
dc.contributor.department Heller School for Social Policy and Management
dc.relation.journal PLoS Neglected Tropical Diseases
dc.identifier.pmid 25412506


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