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Hospitalisations from COVID-19 with Omicron sub-lineages have put a sustained pressure on the English healthcare system. Understanding the expected healthcare demand enables more effective and timely planning from public health. We collect…

The U.S. COVID-19 Forecast Hub aggregates forecasts of the short-term burden of COVID-19 in the United States from many contributing teams. We study methods for building an ensemble that combines forecasts from these teams. These…

Forecasts of hospitalisations of infectious diseases play an important role for allocating healthcare resources during epidemics and pandemics. Large-scale analysis of model forecasts during the COVID-19 pandemic has shown that the model…

Populations and Evolution · Quantitative Biology 2025-05-20 Grégoire Béchade , Torbjörn Lundh , Philip Gerlee

Accurate and reliable predictions of infectious disease dynamics can be valuable to public health organizations that plan interventions to decrease or prevent disease transmission. A great variety of models have been developed for this…

Machine Learning · Statistics 2018-07-04 Evan L. Ray , Nicholas G. Reich

In this work we evaluate the applicability of an ensemble of population models and machine learning models to predict the near future evolution of the COVID-19 pandemic, with a particular use case in Spain. We rely solely in open and public…

Ensemble forecasts have become a cornerstone of large-scale disease response, underpinning decision making at agencies such as the US Centers for Disease Control and Prevention (CDC). Their growing use reflects the goal of combining…

Applications · Statistics 2026-01-23 Carson Dudley , Marisa Eisenberg

The COVID-19 pandemic has placed forecasting models at the forefront of health policy making. Predictions of mortality and hospitalization help governments meet planning and resource allocation challenges. In this paper, we consider the…

Applications · Statistics 2020-08-21 Kathryn S. Taylor , James W. Taylor

The continuously growing number of COVID-19 cases pressures healthcare services worldwide. Accurate short-term forecasting is thus vital to support country-level policy making. The strategies adopted by countries to combat the pandemic…

Methodology · Statistics 2021-04-07 Thiago de Paula Oliveira , Rafael de Andrade Moral

Short-term forecasts of infectious disease spread are a critical component in risk evaluation and public health decision making. While different models for short-term forecasting have been developed, open questions about their relative…

Forecasts of the trajectory of an infectious agent can help guide public health decision making. A traditional approach to forecasting fits a computational model to structured data and generates a predictive distribution. However, human…

As COVID-19 pandemic progresses, severe flu seasons may happen alongside an increase in cases in cases and death of COVID-19, causing severe burdens on health care resources and public safety. A consequence of a twindemic may be a mixture…

Applications · Statistics 2022-02-08 Simin Ma , Shaoyang Ning , Shihao Yang

Compartmental models are widely adopted to describe and predict the spreading of infectious diseases. The unknown parameters of such models need to be estimated from the data. Furthermore, when some of the model variables are not…

Physics and Society · Physics 2021-01-18 Luca Gallo , Mattia Frasca , Vito Latora , Giovanni Russo

We provide an overview of the methods that can be used for prediction under uncertainty and data fitting of dynamical systems, and of the fundamental challenges that arise in this context. The focus is on SIR-like models, that are being…

Methodology · Statistics 2022-10-14 Chiara Piazzola , Lorenzo Tamellini , Raúl Tempone

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

The COVID-19 pandemic has emphasized the need for a robust understanding of epidemic models. Current models of epidemics are classified as either mechanistic or non-mechanistic: mechanistic models make explicit assumptions on the dynamics…

Machine Learning · Statistics 2022-01-14 Arnab Sarker , Ali Jadbabaie , Devavrat Shah

In the political decision process and control of COVID-19 (and other epidemic diseases), mathematical models play an important role. It is crucial to understand and quantify the uncertainty in models and their predictions in order to take…

Applications · Statistics 2021-09-17 Bjørn Jensen , Allan P. Engsig-Karup , Kim Knudsen

Throughout the Covid-19 pandemic, a significant amount of effort had been put into developing techniques that predict the number of infections under various assumptions about the public policy and non-pharmaceutical interventions. While…

Computers and Society · Computer Science 2021-12-22 Sharare Zehtabian , Siavash Khodadadeh , Damla Turgut , Ladislau Bölöni

The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern affecting more than 200 countries and territories worldwide. As of September 30, 2020, it has caused a pandemic outbreak with more than 33…

Populations and Evolution · Quantitative Biology 2020-10-13 Tanujit Chakraborty , Indrajit Ghosh , Tirna Mahajan , Tejasvi Arora

Estimates from infectious disease models have constituted a significant part of the scientific evidence used to inform the response to the COVID-19 pandemic in the UK. These estimates can vary strikingly in their bias and variability.…

Applications · Statistics 2022-10-12 R. E. Moore , C. Rosato , S. Maskell

The recent coronavirus disease (COVID-19) outbreak has dramatically increased the public awareness and appreciation of the utility of dynamic models. At the same time, the dissemination of contradictory model predictions has highlighted…

Populations and Evolution · Quantitative Biology 2020-06-26 Gemma Massonis , Julio R. Banga , Alejandro F. Villaverde
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