Evidence map›Paper›PMID 42742869›Full record

ArticlePharmacoEconomics - open2026

Economic Burden of Inappropriate Antibiotic Prescribing Attributable to Dengue in Singapore.

Peter Yong Sheng Ong, Hwee Lin Wee, Tun-Linn Thein, Yee-Sin Leo, David Chien Boon Lye, Jue Tao Lim, Annelies Wilder-Smith, Yi Wang, Borame L Dickens

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Article in PharmacoEconomics - open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Peter Yong Sheng OngSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore. Yongsheng87@gmail.com.ORCID http://orcid.org/0009-0008-4063-8136
Hwee Lin WeeSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Tun-Linn TheinNational Centre for Infectious Diseases, Singapore, Singapore.
Yee-Sin LeoSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
David Chien Boon LyeNational Centre for Infectious Diseases, Singapore, Singapore.
Jue Tao LimLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Annelies Wilder-SmithLee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Yi WangSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Borame L DickensSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDengue has a clinical presentation similar to that of bacterial infections, creating diagnostic uncertainty that may lead to inappropriate antibiotic prescribing.

objectiveTo estimate the magnitude of inappropriate antibiotic prescribing attributable to dengue in Singapore and assess the associated economic burden from healthcare system and societal perspectives over the period 2015-2024.

methodsA decision tree model was developed to determine costs associated with 142,525 laboratory-confirmed dengue cases reported in Singapore during 2015-2024. National surveillance data and prescribing rates informed model inputs. Costs were estimated from healthcare system and societal perspectives and expressed in 2025 Singapore dollars (SGD). Deterministic and probabilistic sensitivity analyses were conducted.

resultsThe model estimated 7055 antibiotic prescriptions, of which 6866 were inappropriate; 79.6% of inappropriate prescriptions occurred in ambulatory care. The cumulative burden associated with the 2015-2024 caseload was SGD 14.32 million from the healthcare system perspective and SGD 16.13 million from the societal perspective. Prolonged hospitalisation was the largest cost component followed by adverse drug events due to antibiotic use. In the probabilistic analysis, the mean societal burden was SGD 16.16 million, with a 95% uncertainty interval of SGD 2.78-49.60 million.

conclusionsIn this analysis, inappropriate antibiotic prescribing attributable to dengue was associated with an estimated cumulative economic burden of SGD 14.32 million from the healthcare system perspective and SGD 16.13 million from the societal perspective in Singapore during 2015-2024, expressed in 2025 values. Direct medical costs accounted for most of the burden, and the findings support further evaluation of approaches to reduce unnecessary prescribing.

Identifiers

PMID42742869

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.