Nav: Home

Harnessing multiple data streams and artificial intelligence to better predict flu

January 11, 2019

Influenza is highly contagious and easily spreads as people move about and travel, making tracking and forecasting flu activity a challenge. While the CDC continuously monitors patient visits for flu-like illness in the U.S., this information can lag up to two weeks behind real time. A new study, led by the Computational Health Informatics Program (CHIP) at Boston Children's Hospital, combines two forecasting methods with machine learning (artificial intelligence) to estimate local flu activity. Results are published today in Nature Communications.

When the approach, called ARGONet, was applied to flu seasons from September 2014 to May 2017, it made more accurate predictions than the team's earlier high-performing forecasting approach, ARGO, in more than 75 percent of the states studied. This suggests that ARGONet produces the most accurate estimates of influenza activity available to date, a week ahead of traditional healthcare-based reports, at the state level across the U.S.

"Timely and reliable methodologies for tracking influenza activity across locations can help public health officials mitigate epidemic outbreaks and may improve communication with the public to raise awareness of potential risks," says Mauricio Santillana, PhD, a CHIP faculty member and the paper' senior author.

Learning about localized flu patterns

The ARGONet approach uses machine learning and two robust flu detection models. The first model, ARGO (AutoRegression with General Online information), leverages information from electronic health records, flu-related Google searches and historical flu activity in a given location. In the study, ARGO alone outperformed Google Flu Trends, the previous forecasting system that operated from 2008 to 2015.

To improve accuracy, ARGONet adds a second model, which draws on spatial-temporal patterns of flu spread in neighboring areas. "It exploits the fact that the presence of flu in nearby locations may increase the risk of experiencing a disease outbreak at a given location," explains Santillana, who is also an assistant professor at Harvard Medical School.

The machine learning system was "trained" by feeding it flu predictions from both models as well as actual flu data, helping to reduce errors in the predictions. "The system continuously evaluates the predictive power of each independent method and recalibrates how this information should be used to produce improved flu estimates," says Santillana.

Precision public health

The investigators believe their approach will set a foundation for "precision public health" in infectious diseases.

"We think our models will become more accurate over time as more online search volumes are collected and as more healthcare providers incorporate cloud-based electronic health records," says Fred Lu, a CHIP investigator and first author on the paper.
-end-
The work was funded by the Centers for Disease Control and Prevention (Cooperative Agreement PPHF 11797-998G-15) and the National Institute of General Medical Sciences of the NIH (R01GM130668).

About Boston Children's Hospital

Boston Children's Hospital, the primary pediatric teaching affiliate of Harvard Medical School, is home to the world's largest research enterprise based at a pediatric medical center. Its discoveries have benefited both children and adults since 1869. Today, more than 3,000 scientists, including 8 members of the National Academy of Sciences, 18 members of the National Academy of Medicine and 12 Howard Hughes Medical Investigators comprise Boston Children's research community. Founded as a 20-bed hospital for children, Boston Children's is now a 415-bed comprehensive center for pediatric and adolescent health care. For more, visit our Vector and Thriving blogs and follow us on social media @BostonChildrens, @BCH_Innovation, Facebook and YouTube.

Boston Children's Hospital

Related Influenza Articles:

Birds become immune to influenza
An influenza infection in birds gives a good protection against other subtypes of the virus, like a natural vaccination, according to a new study.
Researchers shed new light on influenza detection
Notre Dame Researchers have discovered a way to make influenza visible to the naked eye, by engineering dye molecules to target a specific enzyme of the virus.
Maternal vaccination again influenza associated with protection for infants
How long does the protection from a mother's immunization against influenza during pregnancy last for infants after they are born?
Influenza in the tropics shows variable seasonality
Whilst countries in the tropics and subtropics exhibit diverse patterns of seasonal flu activity, they can be grouped into eight geographical zones to optimise vaccine formulation and delivery timing, according to a study published April 27, 2016 in the open-access journal PLOS ONE.
Influenza viruses can hide from the immune system
Influenza is able to mask itself, so that the virus is not initially detected by our immune system.
Using 'big data' to combat influenza
Team of scientists from the Icahn School of Medicine at Mount Sinai and Sanford Burnham Prebys Medical Discovery Institute among those who combined large genomic and proteomic datasets to identify novel host targets to treat flu.
Rapidly assessing the next influenza pandemic
Influenza pandemics are potentially the most serious natural catastrophes that affect the human population.
Early detection of highly pathogenic influenza viruses
Lack of appropriate drugs and vaccines during the influenza A virus pandemic in 2009, the recent Ebola epidemic in West Africa, as well as the ongoing Middle Eastern Respiratory Syndrome-Coronavirus outbreak demonstrates that the world is only insufficiently prepared for global attacks of emerging infectious diseases and that the handling of such threats remains a great challenge.
Study maps travel of H7 influenza genes
In a new bioinformatics analysis of the H7N9 influenza virus that has recently infected humans in China, researchers trace the separate phylogenetic histories of the virus's genes, giving a frightening new picture of viruses where the genes are traveling independently in the environment, across large geographic distances and between species, to form 'a new constellation of genes -- a new disease, based not only on H7, but other strains of influenza.'
Influenza A potentiates pneumococcal co-infection: New details emerge
Influenza infection can enhance the ability of the bacterium Streptococcus pneumoniae to cause ear and throat infections, according to research published ahead of print in the journal Infection and Immunity.

Related Influenza Reading:

Best Science Podcasts 2019

We have hand picked the best science podcasts for 2019. Sit back and enjoy new science podcasts updated daily from your favorite science news services and scientists.
Now Playing: TED Radio Hour

Digital Manipulation
Technology has reshaped our lives in amazing ways. But at what cost? This hour, TED speakers reveal how what we see, read, believe — even how we vote — can be manipulated by the technology we use. Guests include journalist Carole Cadwalladr, consumer advocate Finn Myrstad, writer and marketing professor Scott Galloway, behavioral designer Nir Eyal, and computer graphics researcher Doug Roble.
Now Playing: Science for the People

#529 Do You Really Want to Find Out Who's Your Daddy?
At least some of you by now have probably spit into a tube and mailed it off to find out who your closest relatives are, where you might be from, and what terrible diseases might await you. But what exactly did you find out? And what did you give away? In this live panel at Awesome Con we bring in science writer Tina Saey to talk about all her DNA testing, and bioethicist Debra Mathews, to determine whether Tina should have done it at all. Related links: What FamilyTreeDNA sharing genetic data with police means for you Crime solvers embraced...