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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

Epidemic forecasts are only as good as the accuracy of epidemic measurements. Is epidemic data, particularly COVID-19 epidemic data, clean and devoid of noise? Common sense implies the negative answer. While we cannot evaluate the…

Populations and Evolution · Quantitative Biology 2023-04-25 Long MA , Piet Van Mieghem , Maksim Kitsak

We propose a forecasting method for predicting epidemiological health series on a two-week horizon at the regional and interregional resolution. The approach is based on model order reduction of parametric compartmental models, and is…

Methodology · Statistics 2020-12-11 Athmane Bakhta , Thomas Boiveau , Yvon Maday , Olga Mula

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…

During an infectious disease outbreak, biases in the data and complexities of the underlying dynamics pose significant challenges in mathematically modelling the outbreak and designing policy. Motivated by the ongoing response to COVID-19,…

Accurate forecasts of disease outbreaks are critical for effective public health responses, management of healthcare surge capacity, and communication of public risk. There are a growing number of powerful forecasting methods that fall into…

The evolution of the COVID-19 epidemic has been accompanied by accumulating evidence on the underlying epidemiological parameters. Hence there is potential for models providing mid-term forecasts of the epidemic trajectory using such…

Applications · Statistics 2020-11-10 Peter Congdon

During the ongoing COVID-19 pandemic, mathematical models of epidemic spreading have emerged as powerful tools to produce valuable predictions of the evolution of the pandemic, helping public health authorities decide which intervention…

Dynamical Systems · Mathematics 2021-11-18 Lorenzo Zino , Ming Cao

Forecasting transmission of infectious diseases, especially for vector-borne diseases, poses unique challenges for researchers. Behaviors of and interactions between viruses, vectors, hosts, and the environment each play a part in…

Applications · Statistics 2020-06-02 Stephen A Lauer , Alexandria C Brown , Nicholas G Reich

Severe acute respiratory disease SARS-CoV-2 has had a found impact on public health systems and healthcare emergency response especially with respect to making decisions on the most effective measures to be taken at any given time. As…

Machine Learning · Computer Science 2023-09-19 Charithea Stylianides , Kleanthis Malialis , Panayiotis Kolios

The COVID-19 pandemic has led to significant changes in how people are currently living their lives. To determine how to best reduce the effects of the pandemic and start reopening societies, governments have drawn insights from…

Other Quantitative Biology · Quantitative Biology 2020-09-08 Heather Z. Brooks , Unchitta Kanjanasaratool , Yacoub H. Kureh , Mason A. Porter

Susceptible-Invective-Recovered (SIR) mathematical models are in high demand due to the COVID-19 pandemic. They are used in their standard formulation, or through the many variants, trying to fit and hopefully predict the number of new…

Populations and Evolution · Quantitative Biology 2020-05-19 Ben-Hur Francisco Cardoso , Sebastián Gonçalves

This paper studies if and to which extent COVID-19 epidemics can be controlled by authorities taking decisions on public health measures on the basis of daily reports of swab test results, active cases and total cases. A suitably simplified…

Physics and Society · Physics 2020-07-22 Francesco Casella

The spread of COVID-19 makes it essential to investigate its prevalence. In such investigation research, as far as we know, the widely-used sampling methods didn't use the information sufficiently about the numbers of the previously…

Applications · Statistics 2022-01-04 Ze Liu , Siyu Yi , Jianghu , Dong , Min-Qian Liu , Yongdao Zhou

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

Mathematical modeling is one of the key factors of the effective control of newly found infectious diseases, such as COVID-19. Our knowledge about the parameters and the course of the infection is highly limited in the beginning of the…

Quantitative Methods · Quantitative Biology 2021-10-13 Péter Boldog , Norbert Bogya , Zsolt Vizi

Epidemiological models contain a set of parameters that must be adjusted based on available observations. Once a model has been calibrated, it can be used as a forecasting tool to make predictions and to evaluate contingency plans. It is…

The advent of the COVID-19 pandemic has instigated unprecedented changes in many countries around the globe, putting a significant burden on the health sectors, affecting the macro economic conditions, and altering social interactions…

Physics and Society · Physics 2020-07-23 Dmitry Gordeev , Philipp Singer , Marios Michailidis , Mathias Müller , SriSatish Ambati

Due to the characteristics of COVID-19, the epidemic develops rapidly and overwhelms health service systems worldwide. Many patients suffer from systemic life-threatening problems and need to be carefully monitored in ICUs. Thus the…

Machine Learning · Computer Science 2020-07-20 Liantao Ma , Xinyu Ma , Junyi Gao , Chaohe Zhang , Zhihao Yu , Xianfeng Jiao , Wenjie Ruan , Yasha Wang , Wen Tang , Jiangtao Wang

Because of the rapid spread of COVID-19 to almost every part of the globe, huge volumes of data and case studies have been made available, providing researchers with a unique opportunity to find trends and make discoveries like never…

Machine Learning · Computer Science 2021-10-20 Sarwan Ali , Yijing Zhou , Murray Patterson