Summary results of the 2014-2015 DARPA Chikungunya challenge

Autor: Heidi E. Brown, Luis E. Escobar, Joceline Lega, Nicholas Hengartner, A. Townsend Peterson, Jason Asher, Harshini Mukundan, Sara Y. Del Valle, Benjamin H. McMahon, David J. Roberts, Sean M. Moore, Huijie Qiao, Yannis Pantazis, Richard Hatchett, Mark E. Leany
Přispěvatelé: Fish and Wildlife Conservation
Jazyk: angličtina
Rok vydání: 2018
Předmět:
0301 basic medicine
Research design
Computer science
medicine.disease_cause
Zika virus
Disease Outbreaks
Dengue
0302 clinical medicine
Agency (sociology)
Global health
030212 general & internal medicine
Chikungunya
Disease surveillance
Mechanistic models
biology
Zika Virus Infection
United States Department of Defense
Organizational Innovation
Infectious Diseases
Research Design
Medical Microbiology
Infection
Research Article
Clinical Sciences
Microbiology
Security Measures
lcsh:Infectious and parasitic diseases
Vaccine Related
03 medical and health sciences
Rare Diseases
Morphological models
Biodefense
medicine
Humans
lcsh:RC109-216
Demography
Government
Infection Control
Prevention
biology.organism_classification
Data science
United States
Vector-Borne Diseases
Subject-matter expert
Emerging Infectious Diseases
Good Health and Well Being
030104 developmental biology
Chikungunya Fever
Forecasting
Zdroj: BMC Infectious Diseases, Vol 18, Iss 1, Pp 1-14 (2018)
BMC infectious diseases, vol 18, iss 1
BMC Infectious Diseases
ISSN: 1471-2334
Popis: Background: Emerging pathogens such as Zika, chikungunya, Ebola, and dengue viruses are serious threats to national and global health security. Accurate forecasts of emerging epidemics and their severity are critical to minimizing subsequent mortality, morbidity, and economic loss. The recent introduction of chikungunya and Zika virus to the Americas underscores the need for better methods for disease surveillance and forecasting. Methods: To explore the suitability of current approaches to forecasting emerging diseases, the Defense Advanced Research Projects Agency (DARPA) launched the 2014–2015 DARPA Chikungunya Challenge to forecast the number of cases and spread of chikungunya disease in the Americas. Challenge participants (n=38 during final evaluation) provided predictions of chikungunya epidemics across the Americas for a six-month period, from September 1, 2014 to February 16, 2015, to be evaluated by comparison with incidence data reported to the Pan American Health Organization (PAHO). This manuscript presents an overview of the challenge and a summary of the approaches used by the winners. Results: Participant submissions were evaluated by a team of non-competing government subject matter experts based on numerical accuracy and methodology. Although this manuscript does not include in-depth analyses of the results, cursory analyses suggest that simpler models appear to outperform more complex approaches that included, for example, demographic information and transportation dynamics, due to the reporting biases, which can be implicitly captured in statistical models. Mosquito-dynamics, population specific information, and dengue-specific information correlated best with prediction accuracy. Conclusion: We conclude that with careful consideration and understanding of the relative advantages and disadvantages of particular methods, implementation of an effective prediction system is feasible. However, there is a need to improve the quality of the data in order to more accurately predict the course of epidemics. Published version
Databáze: OpenAIRE
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