Just in time for flu season, biostatisticians have devised a simple yet accurate method for hospitals and public health departments to determine the onset of elevated influenza activity at the community level
Predicting the beginning of influenza outbreaks is notoriously difficult, and can affect prevention and control efforts. Now, just in time for flu season, biostatistician Nicholas Reich of the University of Massachusetts Amherst and colleagues at Johns Hopkins have devised a simple yet accurate method for hospitals and public health departments to determine the onset of elevated influenza activity at the community level.
Reich and colleagues say their new algorithm will help to signal that influenza transmission is rising in a given region and will assist public health officials, researchers, doctors and hospitals with prevention and healthcare delivery.
Credit: UMass Amherst
Hospital epidemiologists and others responsible for public health decisions do not declare the start of flu season lightly, Reich explains. In hospitals, a declaration that flu season has started comes with many extra precautions and procedures such as added gloves, masks and gowns, donning and doffing time, special decontamination procedures, increased surveillance and reduced visitor access, for example.
"There's also healthcare worker fatigue to consider," he adds, "it's a lot to ask of healthcare workers to continue these important preventative measures when they just aren't seeing a lot of flu around their workplace."
"All the extra precautions cost time and money, so you don't want to declare flu season too early. For hospitals, there is a strong incentive to define a really clear period as flu season. It does not start the moment you see the first case in the fall. If you begin the full response too early, you set yourself up for a long slog and too much effort will be spent on too few cases. You want to be as effective and efficient as possible in your preparations and response."
Details of the new open-source, publicly available tool designed by Reich, of the School of Public Health and Health Sciences at UMass Amherst, with Dr. Trish Perl of the Johns Hopkins University School of Medicine and others in Colorado, Florida and New York, appear in the current issue of Clinical Infectious Diseases.
The authors say their algorithm, or statistical technique, which they call Above Local Elevated Respiratory Illness Threshold (ALERT), will help to signal that influenza transmission is rising in a given region and will assist public health officials, researchers, doctors and hospitals with prevention and healthcare delivery.
ALERT should not require doctors, nurses, hospitals, clinics or public health departments to collect any new data, but instead uses routinely collected information such as weekly counts of laboratory-confirmed influenza A cases.
To develop the new metric, Reich and colleagues used years of surveillance data of confirmed flu cases at two large hospitals in Baltimore and Denver. They obtained weekly counts of confirmed influenza A cases at the 200-bed Children's Hospital at Johns Hopkins and the 414-bed Children's Hospital of Colorado from 2001 through 2013.
They used 2001 through 2011 data to create the algorithm, then tested its performance in the 2011-12 and 2012-13 seasons in the two locations. At Johns Hopkins, 71 and 91 percent respectively of all reported cases fell in the ALERT period, while at Colorado Children's the ALERT period captured 77 and 89 percent of all cases, the authors report. Results suggest "that the ALERT algorithm performs well at predicting the beginning and end of a seasonal period of increased influenza incidence," they add.
To use the algorithm, hospital epidemiologists upload as many years of their own institution's historical flu data as possible to the web-based ALERT applet and then "tune the dials" that control the algorithm to customize the results for their purposes, Reich says. "The more years of data you have, the better," he notes. "We have applied it in places with only three to five years of data and it's still been a useful tool, but the more years you have the more accurate it will be."
The ALERT algorithm helps users pick a threshold number of new cases per week that will signal the start of the season. But as the authors point out, choosing the right threshold poses a challenge. "To guide the user to an evidence-based decision, the ALERT algorithm summarizes data from previous years as if each of several thresholds had been applied." For each threshold, it calculates and reports a set of summary metrics, from which the user can select one that meets their local needs.
Based on local historical data inputs, the tool defines a time window or "ALERT period" when elevated incidence is estimated to occur.
Reich explains, "People will look at the output from ALERT and do a cost-benefit analysis. We don't try to do this for them, but the algorithm can help you to estimate the threshold at which you should start to think about declaring that flu season has started. And, very importantly, your staff can have a sense that it will not go on forever, but that for the next 11 or 12 weeks, for example, you'll be taking the extra precautions."
This work was supported by the U.S. Department of Veterans Affairs and the Centers for Disease Control and Prevention.
Janet Lathrop | EurekAlert!
Researchers release the brakes on the immune system
18.10.2017 | Rheinische Friedrich-Wilhelms-Universität Bonn
Norovirus evades immune system by hiding out in rare gut cells
12.10.2017 | University of Pennsylvania School of Medicine
University of Maryland researchers contribute to historic detection of gravitational waves and light created by event
On August 17, 2017, at 12:41:04 UTC, scientists made the first direct observation of a merger between two neutron stars--the dense, collapsed cores that remain...
Seven new papers describe the first-ever detection of light from a gravitational wave source. The event, caused by two neutron stars colliding and merging together, was dubbed GW170817 because it sent ripples through space-time that reached Earth on 2017 August 17. Around the world, hundreds of excited astronomers mobilized quickly and were able to observe the event using numerous telescopes, providing a wealth of new data.
Previous detections of gravitational waves have all involved the merger of two black holes, a feat that won the 2017 Nobel Prize in Physics earlier this month....
Material defects in end products can quickly result in failures in many areas of industry, and have a massive impact on the safe use of their products. This is why, in the field of quality assurance, intelligent, nondestructive sensor systems play a key role. They allow testing components and parts in a rapid and cost-efficient manner without destroying the actual product or changing its surface. Experts from the Fraunhofer IZFP in Saarbrücken will be presenting two exhibits at the Blechexpo in Stuttgart from 7–10 November 2017 that allow fast, reliable, and automated characterization of materials and detection of defects (Hall 5, Booth 5306).
When quality testing uses time-consuming destructive test methods, it can result in enormous costs due to damaging or destroying the products. And given that...
Using a new cooling technique MPQ scientists succeed at observing collisions in a dense beam of cold and slow dipolar molecules.
How do chemical reactions proceed at extremely low temperatures? The answer requires the investigation of molecular samples that are cold, dense, and slow at...
Scientists from the Max Planck Institute of Quantum Optics, using high precision laser spectroscopy of atomic hydrogen, confirm the surprisingly small value of the proton radius determined from muonic hydrogen.
It was one of the breakthroughs of the year 2010: Laser spectroscopy of muonic hydrogen resulted in a value for the proton charge radius that was significantly...
17.10.2017 | Event News
10.10.2017 | Event News
10.10.2017 | Event News
18.10.2017 | Materials Sciences
18.10.2017 | Physics and Astronomy
18.10.2017 | Physics and Astronomy