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. 2019 Jan 10;13(1):e0007038.
doi: 10.1371/journal.pntd.0007038. eCollection 2019 Jan.

Economic burden of dengue in Indonesia

Mardiati Nadjib  1 , Ery Setiawan  2 , Septiara Putri  2 , Joshua Nealon  3 , Sophie Beucher  3 , Sri Rezeki Hadinegoro  4 , Vetty Yulianty Permanasari  2 , Kurnia Sari  2 , Tri Yunis Miko Wahyono  5 , Erna Kristin  6 , Dewa Nyoman Wirawan  7 , Hasbullah Thabrany  2
Affiliations

Economic burden of dengue in Indonesia

Mardiati Nadjib et al. PLoS Negl Trop Dis. .

Abstract

Background: Dengue is associated with significant economic expenditure and it is estimated that the Asia Pacific region accounts for >50% of the global cost. Indonesia has one of the world's highest dengue burdens; Aedes aegypti and Aedes albopictus are the primary and secondary vectors. In the absence of local data on disease cost, this study estimated the annual economic burden during 2015 of both hospitalized and ambulatory dengue cases in Indonesia.

Methods: Total 2015 dengue costs were calculated using both prospective and retrospective methods using data from public and private hospitals and health centres in three provinces: Yogyakarta, Bali and Jakarta. Direct costs were extracted from billing systems and claims; a patient survey captured indirect and out-of-pocket costs at discharge and 2 weeks later. Adjustments across sites based on similar clinical practices and healthcare landscapes were performed to fill gaps in cost estimates. The national burden of dengue was extrapolated from provincial data using data from the three sites and applying an empirically-derived epidemiological expansion factor.

Results: Total direct and indirect costs per dengue case assessed at Yogyakarta, Bali and Jakarta were US$791, US$1,241 and US$1,250, respectively. Total 2015 economic burden of dengue in Indonesia was estimated at US$381.15 million which comprised US$355.2 million for hospitalized and US$26.2 million for ambulatory care cases.

Conclusion: Dengue imposes a substantial economic burden for Indonesian public payers and society. Complemented with an appropriate weighting method and by accounting for local specificities and practices, these data may support national level public health decision making for prevention/control of dengue in public health priority lists.

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Conflict of interest statement

I have read the journal's policy and the authors of this manuscript have the following competing interests: the study was funded by Sanofi Pasteur; two authors are Representatives of the funding body and provided input in the discussion process on study design and data analysis. However, the final decision on analytical methods, data analysis, data interpretation and content of the manuscript were made by the corresponding and lead author. We did not involve any intervention associated with the funding authority. MN received payment from University of Indonesia under contract from Sanofi Pasteur for work related to this study. ES received payment from the University of Indonesia under contract from Sanofi Pasteur for work related to this study. SP received consultation fees from the University of Indonesia for work related to this study. JN is an employee of Sanofi Pasteur. SB is an employee of Sanofi Pasteur SRH received consultation fees from the University of Indonesia for work related to this study. VYP received consultation fees from the University of Indonesia for work related to this study. KS received consultation fees from the University of Indonesia for work related to this study. TMW received consultation fees from the University of Indonesia for work related to this study. EK received consultation fees from the University of Indonesia for work related to this study. DNW received consultation fees from the University of Indonesia for work related to this study. HT received consultation fees from the University of Indonesia for work related to this study.

Figures

Fig 1
Fig 1. Tornado diagram for the deterministic sensitivity analysis of variability of the Indonesian national-level, annual cost of dengue illness in US$ million.
Black represents the lowest value, grey represents the largest value. Parameters were varied by ±10% as a subjective scenario and the base case was US$381.15 million. The point estimate for each parameter is included in the label for each bar.
See this image and copyright information in PMC

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