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Epidemic forecasting has become an integral part of real-time infectious disease outbreak response. While collaborative ensembles composed of statistical and machine learning models have become the norm for real-time forecasting,…

Many epidemic models are naturally defined as individual-based models: where we track the state of each individual within a susceptible population. Inference for individual-based models is challenging due to the high-dimensional state-space…

Methodology · Statistics 2025-08-04 Lorenzo Rimella , Christopher Jewell , Paul Fearnhead

Susceptible-Exposed-Infectious-Recovered (SEIR) models with inter-individual variation in susceptibility or exposure to infection were proposed early in the COVID-19 pandemic as a potential element of the mathematical/statistical toolset…

Applications · Statistics 2025-10-28 Ibrahim Mohammed , Chris Robertson , M. Gabriela M. Gomes

The problem of detecting a single anomalous process among multiple independent processes is considered. Under a constraint on the number of processes that can be probed simultaneously, the decision maker should decide which processes to…

Signal Processing · Electrical Eng. & Systems 2021-01-15 Fengfan Qin , Da Chen , Hui Feng , Qing Zhao , Tao Yang , Bo Hu

Compartmental models are popular in the mathematics of epidemiology for their simplicity and wide range of applications. Although they are typically solved as initial value problems for a system of ordinary differential equations, the…

Populations and Evolution · Quantitative Biology 2022-10-12 Eduard Campillo-Funollet , Hayley Wragg , James Van Yperen , Duc-Lam Duong , Anotida Madzvamuse

There are multiple testing methods to ascertain an infection in an individual and they vary in their performances, cost and delay. Unfortunately, better performing tests are sometimes costlier and time consuming and can only be done for a…

Social and Information Networks · Computer Science 2021-06-17 Harish Sasikumar , Manoj Varma

Testing is a crucial control mechanism in the beginning phase of an epidemic when the vaccines are not yet available. It enables the public health authority to detect and isolate the infected cases from the population, thereby limiting the…

The novel coronavirus SARS-CoV-2 and resulting COVID-19 disease have had an unprecedented spread and continue to cause an increasing number of fatalities worldwide. While vaccines are still under development, social distancing, extensive…

Populations and Evolution · Quantitative Biology 2020-07-02 Calvin Tsay , Fernando Lejarza , Mark A. Stadtherr , Michael Baldea

By the end of 2021, COVID-19 had spread to over 230 countries, with over 5.4 million deaths. To contain its spread, many countries implemented non-pharmaceutical interventions, notably contact tracing and self-quarantine policies. However,…

Populations and Evolution · Quantitative Biology 2024-11-14 Jungwoo Kim , Taesik Lee

Many uncontrollable disease outbreaks of the past exposed several vulnerabilities in the healthcare systems worldwide. While advancements in technology assisted in the rapid creation of the vaccinations, there needs to be a pressing focus…

Machine Learning · Computer Science 2024-10-29 Chaitya Shah , Kashish Gandhi , Javal Shah , Kreena Shah , Nilesh Patil , Kiran Bhowmick

Knowing the infection fatality ratio (IFR) is of crucial importance for evidence-based epidemic management: for immediate planning; for balancing the life years saved against the life years lost due to the consequences of management; and…

Quantitative Methods · Quantitative Biology 2020-08-11 Simon N. Wood , Ernst C. Wit , Matteo Fasiolo , Peter J. Green

Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease.…

Social and Information Networks · Computer Science 2015-04-03 Nicholas Generous , Geoffrey Fairchild , Alina Deshpande , Sara Y. Del Valle , Reid Priedhorsky

Nonpharmaceutical interventions (NPI) such as banning public events or instituting lockdowns have been widely applied around the world to control the current COVID-19 pandemic. Typically, this type of intervention is imposed when an…

Optimization and Control · Mathematics 2020-11-03 Carla Castillo-Laborde , Taco de Wolff , Pedro Gajardo , Rodrigo Lecaros , Gerard Olivar , Hector Ramirez C

Early detection of patients vulnerable to infections acquired in the hospital environment is a challenge in current health systems given the impact that such infections have on patient mortality and healthcare costs. This work is focused on…

The emergence of coronavirus disease 2019 (COVID-19) in the United States has forced federal and local governments to implement containment measures. Moreover, the severity of the situation has sparked engagement by both the research and…

Populations and Evolution · Quantitative Biology 2020-07-03 Min Lu , Hemant Ishwaran

Problem Definition. Increasing costs of healthcare highlight the importance of effective disease prevention. However, decision models for allocating preventive care are lacking. Methodology/Results. In this paper, we develop a data-driven…

Machine Learning · Computer Science 2023-08-15 Mathias Kraus , Stefan Feuerriegel , Maytal Saar-Tsechansky

The COVID-19 crisis highlighted the importance of non-medical interventions, such as testing and isolation of infected individuals, in the control of epidemics. Here, we show how to minimize testing needs while maintaining the number of…

Systems and Control · Electrical Eng. & Systems 2024-07-04 D. Acemoglu , A. Fallah , A. Giometto , D. Huttenlocher , A. Ozdaglar , F. Parise , S. Pattathil

Infectious diseases have severe health and economic consequences for society. It is important in controlling the spread of an emerging infectious disease to be able to both estimate the parameters of the underlying model and identify those…

Computation · Statistics 2019-09-26 Jessica Welding , Peter Neal

A novel coronavirus disease has emerged (later named COVID-19) and caused the world to enter a new reality, with many direct and indirect factors influencing it. Some are human-controllable (e.g. interventional policies, mobility and the…

Machine Learning · Computer Science 2021-01-12 Haonan Wu , Rajarshi Banerjee , Indhumathi Venkatachalam , Daniel Percy-Hughes , Praveen Chougale

The COVID-19 pandemic underscored a critical need for intervention strategies that balance disease containment with socioeconomic stability. We approach this challenge by designing a framework for modeling and evaluating disease-spread…

Machine Learning · Computer Science 2025-10-07 Marian Chen , Miri Zilka