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Article: Indonesian dengue burden estimates: Review of evidence by an expert panel

TitleIndonesian dengue burden estimates: Review of evidence by an expert panel
Authors
KeywordsDelphi
dengue
Epidemiology
Indonesia
under-reporting
Issue Date2017
Citation
Epidemiology and Infection, 2017, v. 145, n. 11, p. 2324-2329 How to Cite?
AbstractRoutine, passive surveillance systems tend to underestimate the burden of communicable diseases such as dengue. When empirical methods are unavailable, complimentary opinion-based or extrapolative methods have been employed. Here, an expert Delphi panel estimated the proportion of dengue captured by the Indonesian surveillance system, and associated health system parameters. Following presentation of medical and epidemiological data and subsequent discussions, the panel made iterative estimates from which expansion factors (EF), the ratio of total:reported cases, were calculated. Panelists estimated that of all symptomatic Indonesian dengue episodes, 57.8% (95% confidence interval (CI) 46.6-59.8) enter healthcare facilities to seek treatment; 39.3% (95% CI 32.8-42.0) are diagnosed as dengue; and 20.3% (95% CI 16.1-24.3) are subsequently reported in the surveillance system. They estimated most hospitalizations occur in the public sector, while ∼55% of ambulatory episodes are seen privately. These estimates gave an overall EF of 5.00; hospitalized EF of 1.66; and ambulatory EF of 34.01 which, when combined with passive surveillance data, equates to an annual average (2006-2015) of 612 005 dengue cases, and 183 297 hospitalizations. These estimates are lower than those published elsewhere, perhaps due to case definitions, local clinical perceptions and treatment-seeking behavior. These findings complement global burden estimates, support health economic analyses, and can be used to inform decision-making.
Persistent Identifierhttp://hdl.handle.net/10722/311430
ISSN
2023 Impact Factor: 2.5
2023 SCImago Journal Rankings: 0.830
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWahyono, T. Y.M.-
dc.contributor.authorNealon, J.-
dc.contributor.authorBeucher, S.-
dc.contributor.authorPrayitno, A.-
dc.contributor.authorMoureau, A.-
dc.contributor.authorNawawi, S.-
dc.contributor.authorThabrany, H.-
dc.contributor.authorNadjib, M.-
dc.date.accessioned2022-03-22T11:53:55Z-
dc.date.available2022-03-22T11:53:55Z-
dc.date.issued2017-
dc.identifier.citationEpidemiology and Infection, 2017, v. 145, n. 11, p. 2324-2329-
dc.identifier.issn0950-2688-
dc.identifier.urihttp://hdl.handle.net/10722/311430-
dc.description.abstractRoutine, passive surveillance systems tend to underestimate the burden of communicable diseases such as dengue. When empirical methods are unavailable, complimentary opinion-based or extrapolative methods have been employed. Here, an expert Delphi panel estimated the proportion of dengue captured by the Indonesian surveillance system, and associated health system parameters. Following presentation of medical and epidemiological data and subsequent discussions, the panel made iterative estimates from which expansion factors (EF), the ratio of total:reported cases, were calculated. Panelists estimated that of all symptomatic Indonesian dengue episodes, 57.8% (95% confidence interval (CI) 46.6-59.8) enter healthcare facilities to seek treatment; 39.3% (95% CI 32.8-42.0) are diagnosed as dengue; and 20.3% (95% CI 16.1-24.3) are subsequently reported in the surveillance system. They estimated most hospitalizations occur in the public sector, while ∼55% of ambulatory episodes are seen privately. These estimates gave an overall EF of 5.00; hospitalized EF of 1.66; and ambulatory EF of 34.01 which, when combined with passive surveillance data, equates to an annual average (2006-2015) of 612 005 dengue cases, and 183 297 hospitalizations. These estimates are lower than those published elsewhere, perhaps due to case definitions, local clinical perceptions and treatment-seeking behavior. These findings complement global burden estimates, support health economic analyses, and can be used to inform decision-making.-
dc.languageeng-
dc.relation.ispartofEpidemiology and Infection-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectDelphi-
dc.subjectdengue-
dc.subjectEpidemiology-
dc.subjectIndonesia-
dc.subjectunder-reporting-
dc.titleIndonesian dengue burden estimates: Review of evidence by an expert panel-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1017/S0950268817001030-
dc.identifier.pmid28545598-
dc.identifier.pmcidPMC5647663-
dc.identifier.scopuseid_2-s2.0-85019698977-
dc.identifier.volume145-
dc.identifier.issue11-
dc.identifier.spage2324-
dc.identifier.epage2329-
dc.identifier.eissn1469-4409-
dc.identifier.isiWOS:000409124100017-

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