Forecasting the annual burden of COVID-19, influenza and RSV

Download Airfinity's latest forecast of the 'tripledemic' burden of COVID-19, influenza and RSV, including the potential impact of new interventions.

Airfinity forecasts the ‘tripledemic’ burden of COVID-19, flu and RSV will be less severe this winter as outbreak peaks are not predicted to overlap as extensively as last year.

Our methodology

The forecasts for each disease were generated using a variety of techniques. Influenza and RSV forecasts were developed using primarily machine learning (ML) techniques; each of both flu and RSV were created from an ensemble of three ML models. These ML models factored in historic trends, as well as currently circulating variants and anticipated vaccine uptake. COVID-19 forecasts were generated using a compartmental SIR model, with parameters to the model being fitted to historic data. COVID forecasts did not use ML techniques in the same way flu and RSV forecasts did due to the dramatically changing data landscape for COVID, with testing capacity significantly reduced in recent months, which disrupted ML models.

To discuss the methodology, as well as our wider forecasting and simulation capabilities, get in touch via infectiousdiseases@airfinity.com.

Fill out the form to download a free sample of Airfinity's analysis.

We’ll need a few short details about you and your business.

Science360 Laptop Mock Image

Fill out the form to download a free sample of Airfinity's analysis.

We’ll need a few short details about you and your business.

What our users say?

who

“The Airfinity report is a guide for world leaders to fix a more ambitious action plan.”

Gordon Brown, WHO Ambassador for Global Health Financing & former UK Prime Minister

hm government

“Airfinity has been instrumental in our country's COVID response.”

Head of UK Government
Vaccine Task Force

ifpma

In a dynamic environment, Airfinity enabled us to remain on track with daily developments to enable more accurate decision-making. Airfinity combines nimbleness of real time data and their group of scientists that can analyse, model and provide strategic analysis for critical decision making.”

Iskra Reic, Executive Vice-President
Astrazeneca

Oxford

“Probably the most expansive, accurate and helpful of the multiple data sets on an international scale”

Sir John Bell ,
University of Oxford