IDEAS home Printed from https://ideas.repec.org/a/plo/pgph00/0005867.html

Performance evaluation of an operational dengue forecasting system (D-MOSS) in Vietnam

Author

Listed:
  • Amy Marie Campbell
  • Felipe Colón-González
  • Do Kien Quoc
  • Nguyen Hai Tuan
  • Nguyen Thanh Dong
  • Tran Thi Trang
  • Lokman Hakim Bin Sulaiman
  • Shew Fung Wong
  • Barbara Hofmann
  • Gina Tsarouchi
  • Quillon Harpham
  • Vu Sinh Nam
  • Oliver Brady

Abstract

D-MOSS (Dengue forecasting Model Satellite-based System) was launched operationally in Vietnam in June 2019, providing near-real time dengue forecasts across all 63 provinces. Very few dengue forecasting systems have prospectively evaluated the performance of dengue forecasting under real-world operational conditions. This study comprehensively assesses D-MOSS dengue forecasting performance since operationalisation through both statistical accuracy (absolute dengue incidence, trajectory of incidence, timing of peaks), and operational utility (predictions for specific decision-making scenarios). The D-MOSS dengue forecasts in Vietnam outperformed null model baselines across almost all performance metrics.. While lead times of one month reported the highest accuracy, there was no steep linear decline in accuracy as lead times increased up to six months, and the greatest value-added over seasonal average baseline models was found for later lead times at four to six months. Higher value-added differences were observed for the second half of the year, but the unusually-early June dengue outbreak in 2022 provided a notable challenge. Spatially, larger errors were found in central and southern provinces, that report higher dengue incidence, alongside contrastingly greater value-added over null baseline models, particularly at shorter lead times. Four contextualised operational utility scenarios were tested through probabilistic classification of outbreak threshold exceedance, with accuracy ranging across probability cut-offs but peaking at 0.83 - 0.94 across scenarios.The value of waiting for the next month’s forecast and utilising different outbreak thresholds was assessed, with heterogeneous results and the distribution of false alarms or missed outbreaks clustering spatially. The results of both the global performance analysis and utility assessments continue to highlight the strong predictive ability of D-MOSS in an operational setting. Lessons should be taken from the higher-than-expected performance over long-term horizons to improve our ability to forecast further into the future, amidst the key insights these results provide into the improvement of operational dengue forecasting for key decision-making situations in Vietnam and beyond.

Suggested Citation

  • Amy Marie Campbell & Felipe Colón-González & Do Kien Quoc & Nguyen Hai Tuan & Nguyen Thanh Dong & Tran Thi Trang & Lokman Hakim Bin Sulaiman & Shew Fung Wong & Barbara Hofmann & Gina Tsarouchi & Quill, 2026. "Performance evaluation of an operational dengue forecasting system (D-MOSS) in Vietnam," PLOS Global Public Health, Public Library of Science, vol. 6(3), pages 1-23, March.
  • Handle: RePEc:plo:pgph00:0005867
    DOI: 10.1371/journal.pgph.0005867
    as

    Download full text from publisher

    File URL: https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0005867
    Download Restriction: no

    File URL: https://journals.plos.org/globalpublichealth/article/file?id=10.1371/journal.pgph.0005867&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pgph.0005867?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ahyoung Lim & Freya M. Shearer & Kara Sewalk & David M. Pigott & Joseph Clarke & Azhar Ghouse & Ciara Judge & Hyolim Kang & Jane P. Messina & Moritz U. G. Kraemer & Katy A. M. Gaythorpe & William M. S, 2025. "The overlapping global distribution of dengue, chikungunya, Zika and yellow fever," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abdisalam Alinur Abdi & Jose G Juarez & Trevor Harris & Tereza Magalhaes & Gabriel L Hamer, 2026. "Systematic review of Aedes aegypti control trials suggests publication bias related to author disclosure of conflicts of interest," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 20(1), pages 1-16, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pgph00:0005867. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: globalpubhealth (email available below). General contact details of provider: https://journals.plos.org/globalpublichealth .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.