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Weather forecasting has seen a shift in methods from numerical simulations to data-driven systems. While initial research in the area focused on deterministic forecasting, recent works have used diffusion models to produce skillful ensemble…

Machine Learning · Computer Science 2025-04-15 Martin Andrae , Tomas Landelius , Joel Oskarsson , Fredrik Lindsten

Accurately forecasting patient arrivals at Urgent Care Clinics (UCCs) and Emergency Departments (EDs) is important for effective resourcing and patient care. However, correctly estimating patient flows is not straightforward since it…

Machine Learning · Computer Science 2022-11-03 Teo Susnjak , Paula Maddigan

Meteorological ensembles are a collection of scenarios for future weather delivered by a meteorological center. Such ensembles form the main source of valuable information for probabilistic forecasting which aims at producing a predictive…

Applications · Statistics 2019-03-07 Marie Courbariaux , Pierre Barbillon , Luc Perreault , Éric Parent

This paper proposes a novel approach to predict epidemiological parameters by integrating new real-time signals from various sources of information, such as novel social media-based population density maps and Air Quality data. We implement…

Machine Learning · Computer Science 2023-07-04 Romain Molinas , César Quilodrán Casas , Rossella Arcucci , Ovidiu Şerban

Since the beginning of the COVID-19 pandemic, many dashboards have emerged as useful tools to monitor the evolution of the pandemic, inform the public, and assist governments in decision making. Our goal is to develop a globally applicable…

Background: Over the past few decades, numerous forecasting methods have been proposed in the field of epidemic forecasting. Such methods can be classified into different categories such as deterministic vs. probabilistic, comparative…

For over a century, immunology has masterfully discovered and dissected the components of our immune system, yet its collective behavior remains fundamentally unpredictable. In this perspective, we argue that building on the learnings of…

In this work we demonstrate how to automate parts of the infectious disease-control policy-making process via performing inference in existing epidemiological models. The kind of inference tasks undertaken include computing the posterior…

In the present paper, our goal is to establish a framework for the mathematical modelling and the analysis of the spread of an epidemic in a large population commuting regularly, typically along a time-periodic pattern, as is roughly…

Populations and Evolution · Quantitative Biology 2024-08-29 Pierre-Alexandre Bliman , Boureima Sangaré , Assane Savadogo

We describe various moment-based ensemble interpretation models for the construction of probabilistic temperature forecasts from ensembles. We apply the methods to one year of medium range ensemble forecasts and perform in and out of sample…

Atmospheric and Oceanic Physics · Physics 2007-05-23 Stephen Jewson

The need to forecast COVID-19 related variables continues to be pressing as the epidemic unfolds. Different efforts have been made, with compartmental models in epidemiology and statistical models such as AutoRegressive Integrated Moving…

Applications · Statistics 2020-10-07 Bahman Rostami-Tabar , Juan F. Rendon-Sanchez

To increase situational awareness and support evidence-based policy-making, we formulated two types of mathematical models for COVID-19 transmission within a regional population. One is a fitting function that can be calibrated to reproduce…

Purpose: This paper proposes a methodology and a computational tool to study the COVID-19 pandemic throughout the world and to perform a trend analysis to assess its local dynamics. Methods: Mathematical functions are employed to describe…

In May 2022, mpox (formerly monkeypox) spread to non-endemic countries rapidly. Human judgment is a forecasting approach that has been sparsely evaluated during the beginning of an outbreak. We collected -- between May 19, 2022 and July 31,…

The COVID-19 pandemic represents the most significant public health disaster since the 1918 influenza pandemic. During pandemics such as COVID-19, timely and reliable spatio-temporal forecasting of epidemic dynamics is crucial. Deep…

Machine Learning · Computer Science 2020-11-25 Lijing Wang , Aniruddha Adiga , Srinivasan Venkatramanan , Jiangzhuo Chen , Bryan Lewis , Madhav Marathe

Large ensembles of climate projections are essential for characterizing uncertainty in future climate and extreme weather events, yet computational constraints of numerical climate models limit ensemble sizes to a small number of…

Atmospheric and Oceanic Physics · Physics 2025-12-01 Francesco Immorlano , Elijah Tavares , Felix Draxler , Padhraic Smyth , Pierre Gentine , Stephan Mandt

This article explores mathematical models for understanding the evolution of contagious diseases. The most widely known set of models are the compartmental ones, which are based on a set of differential equations. But these are not the only…

Populations and Evolution · Quantitative Biology 2021-12-07 C. O. S. Sorzano

Aim of this paper is the description of a new tool to support institutions in the implementation of targeted countermeasures, based on quantitative and multi-scale elements, for the fight and prevention of emergencies, such as the current…

Computers and Society · Computer Science 2020-11-12 A. Sebastianelli , F. Mauro , G. Di Cosmo , F. Passarini , M. Carminati , S. L. Ullo

The ongoing COVID-19 pandemic highlights the essential role of mathematical models in understanding the spread of the virus along with a quantifiable and science-based prediction of the impact of various mitigation measures. Numerous types…

Populations and Evolution · Quantitative Biology 2021-08-27 Prateek Kunwar , Oleksandr Markovichenko , Monique Chyba , Yuriy Mileyko , Alice Koniges , Thomas Lee

Infectious disease forecasting for ongoing epidemics has been traditionally performed, communicated, and evaluated as numerical targets - 1, 2, 3, and 4 week ahead cases, deaths, and hospitalizations. While there is great value in…

Applications · Statistics 2022-11-15 Ajitesh Srivastava , Satwant Singh , Fiona Lee