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Forecasting flu outbreaks in a subtropical climate


Worldwide, influenza kills an estimated 250,000 to 500,000 people each year. A new study publishing in PLOS Computational Biology has shown that for the first time it is possible to predict the timing and intensity of influenza outbreaks in subtropical climates, such as Hong Kong, where flu seasons can occur at irregular intervals year-round.

The team of scientists from Columbia University's Mailman School of Public Health and the University of Hong Kong used data from a network of 50 outpatient clinics and laboratory reports in Hong Kong from 1998 to 2013 as a test case to retrospectively generate weekly flu forecasts. The system was able to forecast both the peak timing and peak magnitude for 44 epidemics in 16 years caused by individual influenza strains, including influenza A(H3N2), influenza B, and both seasonal and the 2009 pandemic outbreaks of influenza A(H1N1).

The system employs a computer model to generate multiple simulations that mimic the behavior of an outbreak and are then knit together to generate an overall prediction. The technique predicted the peak timing of the outbreak three weeks in advance of the actual peak and was accurate to 93 percent.

Prediction accuracy varied depending on the strength of the outbreak and how far in advance the prediction was made. In general, forecasts for specific strains were more accurate than those for aggregate epidemics, and the peak and magnitude of outbreaks were more accurate than the timing of their onset or their duration.

"These forecasts provide information at lead times that can be valuable for both the public and health officials," says senior author Jeffrey Shaman, PhD, associate professor of Environmental Health Sciences at the Mailman School. "Individuals may choose to get a flu vaccine to protect themselves against infection, while officials can anticipate how many vaccines and other supplies are needed, as well as the number of clinicians and nurses needed."

"Hong Kong is a crossroads to Asia and the rest of the world, serving as an entry and exit point for flu outbreaks year round, and the region of South East Asia with Hong Kong at its center is often referred to as the global epicenter for flu." says Benjamin J. Cowling, PhD, professor at the University of Hong Kong.

Yang and her co-authors modified the flu forecasting system used in the United States to account for the dynamics of a subtropical climate, adding mathematical techniques that prompt the system to recalibrate itself and let go of certain assumptions. "We design the system to pay attention to the data when there are changing dynamics, and promptly recognize any change in flu activity throughout the year," explains Yang.

Looking ahead, the researchers hope to refine the system to account for cross-immunity due to prior infections from related strains, for varying transmission dynamics among age groups, or spatial connectivity among sub-regions.


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Contact: Wan Yang
Address: Columbia University
Environmental Health Sciences
722 West 168th Street, 11th Floor
New York, 10032
Phone: 540-239-3859

Citation: Yang W, Cowling BJ, Lau EHY, Shaman J (2015) Forecasting Influenza Epidemics in Hong Kong. PLoS Comput Biol 11(7): e1004383.doi:10.1371/journal.pcbi.1004383

Funding: Funding was provided by US NIH grants GM100467, GM110748, GM088558, and ES009089, the RAPIDD program of the Science and Technology Directorate, US Department of Homeland Security, a commissioned grant from the Health and Medical Research Fund of the Health, Welfare and Food Bureau of the Hong Kong SAR Government, and the Area of Excellence Scheme of the Hong Kong University Grants Committee (AoE/M-12/06). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: BJC has received research funding from MedImmune Inc. and Sanofi Pasteur, and consults for Crucell NV. JS discloses consulting for JWTand Axon Advisors, as well as partial ownership of SK Analytics. The authors report no other potential conflicts of interest. This does not alter our adherence to all PLOS policies on sharing data and materials.

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