MPC Member Publications

This database contains a listing of population studies publications written by MPC Members. Anyone can add a publication by an MPC student, faculty, or staff member to this database; new citations will be reviewed and approved by MPC administrators.

Full Citation

Title: An open challenge to advance probabilistic forecasting for dengue epidemics

Citation Type: Journal Article

Publication Year: 2019

ISSN: 10916490

DOI: 10.1073/pnas.1909865116

PMID: 31712420

Abstract: A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue.

Url: www.pnas.org/cgi/doi/10.1073/pnas.1920071116

User Submitted?: No

Authors: Johansson, Michael A.; Apfeldorf, Karyn M.; Dobson, Scott; Devita, Jason; Buczak, Anna L.; Baugher, Benjamin; Moniz, Linda J.; Bagley, Thomas; Babin, Steven M.; Guven, Erhan; Yamana, Teresa K.; Shaman, Jeffrey; Moschou, Terry; Lothian, Nick; Lane, Aaron; Osborne, Grant; Jiang, Gao; Brooks, Logan C.; Farrow, David C.; Hyun, Sangwon; Tibshirani, Ryan J.; Rosenfeld, Roni; Lessler, Justin; Reich, Nicholas G.; Cummings, Derek A.T.; Lauer, Stephen A.; Moore, Sean M.; Clapham, Hannah E.; Lowe, Rachel; Bailey, Trevor C.; García-Díez, Markel; Carvalho, Marilia Sá; Rodó, Xavier; Sardar, Tridip; Paul, Richard; Ray, Evan L.; Sakrejda, Krzysztof; Brown, Alexandria C.; Meng, Xi; Osoba, Osonde; Vardavas, Raffaele; Manheim, David; Moore, Melinda; Rao, Dhananjai M.; Porco, Travis C.; Ackley, Sarah; Liu, Fengchen; Worden, Lee; Convertino, Matteo; Liu, Yang; Reddy, Abraham; Ortiz, Eloy; Rivero, Jorge; Brito, Humberto; Juarrero, Alicia; Johnson, Leah R.; Gramacy, Robert B.; Cohen, Jeremy M.; Mordecai, Erin A.; Murdock, Courtney C.; Rohr, Jason R.; Ryan, Sadie J.; Stewart-Ibarra, Anna M.; Weikel, Daniel P.; Jutla, Antarpreet; Khan, Rakibul; Poultney, Marissa; Colwell, Rita R.; Rivera-García, Brenda; Barker, Christopher M.; Bell, Jesse E.; Biggerstaff, Matthew; Swerdlow, David; Mier-Y-Teran-Romero, Luis; Forshey, Brett M.; Trtanj, Juli; Asher, Jason; Clay, Matt; Margolis, Harold S.; Hebbeler, Andrew M.; George, Dylan; Chretien, Jean Paul

Periodical (Full): Proceedings of the National Academy of Sciences of the United States of America

Issue: 48

Volume: 116

Pages: 24268-24274

Countries:

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