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Updating observations of a signal due to the delays in the measurement process is a common problem in signal processing, with prominent examples in a wide range of fields. An important example of this problem is the nowcasting of COVID-19…

The new corona virus disease -- COVID-2019 -- is rapidly spreading through the world. The availability of unbiased timely statistics of trends in disease events are a key to effective responses. But due to reporting delays, the most…

Populations and Evolution · Quantitative Biology 2020-06-15 Adam Altmejd , Joacim Rocklöv , Jonas Wallin

Governments around the world continue to act to contain and mitigate the spread of COVID-19. The rapidly evolving situation compels officials and executives to continuously adapt policies and social distancing measures depending on the…

Applications · Statistics 2021-02-19 Giacomo De Nicola , Marc Schneble , Göran Kauermann , Ursula Berger

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

COVID-19 has been a public health emergency of international concern since early 2020. Reliable forecasting is critical to diminish the impact of this disease. To date, a large number of different forecasting models have been proposed,…

Machine Learning · Computer Science 2021-10-04 Yun Zhao , Yuqing Wang , Junfeng Liu , Haotian Xia , Zhenni Xu , Qinghang Hong , Zhiyang Zhou , Linda Petzold

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

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

Over the past few months, the outbreak of Coronavirus disease (COVID-19) has been expanding over the world. A reliable and accurate dataset of the cases is vital for scientists to conduct related research and for policy-makers to make…

Applications · Statistics 2020-12-01 Guannan Wang , Zhiling Gu , Xinyi Li , Shan Yu , Myungjin Kim , Yueying Wang , Lei Gao , Li Wang

The real-time analysis of infectious disease surveillance data, e.g., in the form of a time-series of reported cases or fatalities, is essential in obtaining situational awareness about the current dynamics of an adverse health event such…

Methodology · Statistics 2023-01-11 Fanny Bergström , Felix Günther , Michael Höhle , Tom Britton

COVID-19 pandemic has reshaped our world in a timescale much shorter than what we can understand. Particularities of SARS-CoV-2, such as its persistence in surfaces and the lack of a curative treatment or vaccine against COVID-19, have…

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

COVID-19 data released by public health authorities features the presence of notable time-delays, corresponding to the difference between actual time of infection and identification of infection. These delays have several causes, including…

Dynamical Systems · Mathematics 2021-11-29 Nicola Guglielmi , Elisa Iacomini , Alex Viguerie

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…

The role of epidemiological models is crucial for informing public health officials during a public health emergency, such as the COVID-19 pandemic. However, traditional epidemiological models fail to capture the time-varying effects of…

Methodology · Statistics 2022-06-17 Adam Spannaus , Theodore Papamarkou , Samantha Erwin , J. Blair Christian

The SARS-CoV-2 virus and COVID-19 disease have posed unprecedented and overwhelming demand, challenges and opportunities to domain, model and data driven modeling. This paper provides a comprehensive review of the challenges, tasks,…

Computers and Society · Computer Science 2021-08-05 Longbing Cao , Qing Liu

COVID-19 has challenged health systems to learn how to learn. This paper describes the context, methods and challenges for learning to improve COVID-19 care at one academic health center. Challenges to learning include: (1) choosing a right…

The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing…

COVID-19 continues to cause a significant impact on public health. To minimize this impact, policy makers undertake containment measures that however, when carried out disproportionately to the actual threat, as a result if errorneous…

In many fields and applications count data can be subject to delayed reporting. This is where the total count, such as the number of disease cases contracted in a given week, may not be immediately available, instead arriving in parts over…

Applications · Statistics 2019-11-25 Oliver Stoner , Theo Economou

The number of Covid-19 cases is increasing dramatically worldwide. Therefore, the availability of reliable forecasts for the number of cases in the coming days is of fundamental importance. We propose a simple statistical method for…

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