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Use of expansion factors to estimate the burden of dengue in southeast Asia: a systematic analysis.
MedLine Citation:
PMID:  23437407     Owner:  NLM     Status:  In-Data-Review    
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.
Eduardo A Undurraga; Yara A Halasa; Donald S Shepard
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Publication Detail:
Type:  Journal Article     Date:  2013-02-21
Journal Detail:
Title:  PLoS neglected tropical diseases     Volume:  7     ISSN:  1935-2735     ISO Abbreviation:  PLoS Negl Trop Dis     Publication Date:  2013 Feb 
Date Detail:
Created Date:  2013-02-25     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101291488     Medline TA:  PLoS Negl Trop Dis     Country:  United States    
Other Details:
Languages:  eng     Pagination:  e2056     Citation Subset:  IM    
Schneider Institutes for Health Policy, Heller School for Social Policy and Management, Brandeis University, Waltham, Massachusetts, United States of America.
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