Bad weather and hospital traffic jams: a mathematical model

Bad weather and hospital traffic jams: a mathematical model

Research team aided by the Swiss National Science Foundation anticipates flu peaks in hospitals thanks to weather data

The overcrowding of a hospital, due to the peaks of a seasonal disease, can be contrasted or controlled through algorithms that take into account the meteorological evolution
The overcrowding of a hospital, due to the peaks of a seasonal disease, can be contrasted or controlled through algorithms that take into account the meteorological evolution

Is there an “intimate” relationship between health and bad weather?.
When too many people fall ill at the same time, hospitals run the risk of overcrowding, as the recent COVID-19 pandemic has to some extent demonstrated. The flu virus can cause the same problems.
A team of researchers supported by the Swiss National Science Foundation has developed a mathematical model that can predict the risk of flu-related hospital congestion based on weather conditions.
His results were published in the "Journal of the Royal Statistical Society".
Influenza is a seasonal virus, mainly present during the winter season in our latitudes.
The Swiss research team compared some meteorological data, such as precipitation, humidity, temperature and insolation, with cases of flu recorded daily for three years at theUniversity Hospital of Lausanne, better known locally as CHUV.

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Vaccination consists in the administration of a vaccine both for prophylactic purposes (vaccinoprophylaxis) and for therapeutic purposes (vaccinotherapy): vaccine prophylaxis is a type of vaccination carried out to create an immune state against one or more diseases, activating the components of the immune system to respond better to a specific pathogen; vaccine therapy is instead a type of vaccination carried out for therapeutic purposes against a disease, when this is already in progress, with the aim of strengthening the antibodies present in the body
Vaccination consists in the administration of a vaccine both for prophylactic purposes (vaccinoprophylaxis) and for therapeutic purposes (vaccinotherapy): vaccine prophylaxis is a type of vaccination carried out to create an immune state against one or more diseases, activating the components of the immune system to respond better to a specific pathogen; vaccine therapy is instead a type of vaccination carried out for therapeutic purposes against a disease, when this is already in progress, with the aim of strengthening the antibodies present in the body

The extreme values ​​instead of the average ones to plan resources well

For the first time, however, the team did not look at the average daily number of flu cases during the three years they studied.
He focused on the extreme values ​​recorded because it is these data that can indicate a congestion risk for hospitals and are therefore useful for resource planning.
The researchers were able to develop a model that uses meteorological data, ie periods of bad weather, to predict the risk of congestion within three days, i.e. the incubation time of influenza.
“Instead of providing hospitals with an average number of expected cases, we provide them with indications on the likelihood of reaching a number of cases exceeding their capacity, information that is much more relevant”, explains Valerie Chavez, a statistician at the University of Lausanne and co-author of the study.

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Fever consists of an elevated body temperature (37,8 degrees Celsius measured orally or 38,2 degrees Celsius rectally), or an increase in body temperature above normal circadian variations
Fever consists of an elevated body temperature (37,8 degrees Celsius measured orally or 38,2 degrees Celsius rectally), or an increase in body temperature above normal circadian variations

An alarm signal between 1 and 10 percent more positive cases

By plotting this probability each year starting in the fall, hospital officials could anticipate a spike in flu cases that could potentially lead to hospital congestion.
The model specifically indicates the number of positive cases that could be exceeded with a 1 percent, 5 percent or 10 percent probability.
It also indicates the maximum number of positive cases that could be observed in a 10 or 30 day horizon.
An increase in these values ​​indicates that the epidemic is approaching its peak. “For hospitals, it is a major wake-up call”, sums up the scientist.
Applicable to other seasonal viruses, notably coronaviruses and respiratory syncytial virus (RSV), which causes respiratory infections in young children, the model is still subject to some uncertainty in terms of risk prediction, as to date only three years of CHUV data could be analysed.
Also due to the lack of numerical information, it is not yet applicable to the monitoring of SARS-CoV-2.
On the other hand, researchers are already working on models which, in addition to meteorological data, would also be based on viral propagation processes to better monitor the infection.

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The CHUV or Center Hospitalier Universitaire Vaudois is a world-class hospital and academic center in Lausanne
The CHUV or Center Hospitalier Universitaire Vaudois is a world-class hospital and academic center in Lausanne

Observing extremes to calculate risks: the lesson of… dams

Extreme value theory is a statistical field that deals with extremely large or extremely small values ​​in a set of data.
It allows scientists to quantify risks by estimating the probability of extreme events and was used for the first time in hydrology to calculate the required height of dams for flood protection.
“You need a certain height to protect yourself from a flood that occurs every 10 years, a greater height for a flood once a century, and an infinite height if you want to be protected indefinitely”, explains Valerie Chavez.
But this field of statistics also applies to finance, risks of stock market crashes or climatic events such as heat waves or melting glaciers.
Why was extreme value theory applied in this research project, related to bad weather? “In our model, we treated flu spikes as rare, high-impact events.”
“This is exactly the domain of extreme value theory. Models that work with mean values ​​are based on the central values ​​of the distribution and cannot be used to quantify risks.", concludes Chavez.

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Bad weather, especially in intermediate seasons such as autumn, is often a harbinger of flu syndromes
Bad weather, especially in intermediate seasons such as autumn, is often a harbinger of flu syndromes