This website offers forecasts of infectious diseases globally, utilizing computational models based on robust data sets. Our forecasts are designed to provide insights for a specified period, typically ranging up to a few weeks.
We provide local forecasts for a range of locations around the world. Our forecasts include:
Our forecasting approach is grounded in established scientific methodologies, which we have further refined through the development of custom-built, high-performance algorithms. These innovative computational tools enable us to estimate the spread of a disease with high spatial resolution, allowing for a more nuanced understanding of disease dynamics.
Our methodology is based on the use of well-known methods in computational epidemiology, including the use of compartmental models, network science, human mobility modelling, Bayesian computation. By integrating these established approaches with our algorithms, we are able to generate forecasts that capture the complexities of disease spread with accuracy.
Further enhancements to our forecasting methodology include machine and deep learning methodologies. We are currently actively developing and refining methods to improve our forecasting capabilities.
The high-performance nature of our algorithms enables us to process large datasets in a timely and efficient manner, allowing for iteration and refinement of our forecasting models.