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Using a Dynamic Causal Model to validate previous predictions and offer a 12-month forecast of the long-term effects of the COVID-19 epidemic in the UK

FRONTIERS IN PUBLIC HEALTH (2023)

Accurate inference of crowdsourcing properties when using efficient allocation strategies

Abigail Hotaling et al.

Summary: This study focuses on the inference of problem properties when using an allocation strategy to improve crowd efficiency. A novel method called Decision-Explicit Probability Sampling (DEPS) is introduced to perform this type of inference while accounting for the potential bias introduced by the allocation strategy. Experimental results show that DEPS outperforms baseline inference methods.

SCIENTIFIC REPORTS (2022)

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Article Public, Environmental & Occupational Health

A 12-month projection to September 2022 of the COVID-19 epidemic in the UK using a dynamic causal model

Cam Bowie et al.

Summary: While vaccination is effective in preventing COVID-19, it is not sufficient to control the epidemic. Without other public health measures, the UK is projected to experience a significant increase in cases, hospital admissions, and deaths over the next 12 months, posing risks to healthcare services and the economy.

FRONTIERS IN PUBLIC HEALTH (2022)

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Article Infectious Diseases

Prioritising COVID-19 vaccination in changing social and epidemiological landscapes: a mathematical modelling study

Peter C. Jentsch et al.

Summary: This study compared four different strategies for prioritizing SARS-CoV-2 vaccines and found that vaccination strategies targeting transmission might prevent more deaths than prioritizing vulnerable age groups as the pandemic progresses.

LANCET INFECTIOUS DISEASES (2021)

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Article Biology

Predicting intervention effect for COVID-19 in Japan: state space modeling approach

Genya Kobayashi et al.

BIOSCIENCE TRENDS (2020)

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Article Infectious Diseases

Forecasting Ebola with a regression transmission model

Jason Asher

EPIDEMICS (2018)

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Article Statistics & Probability

FORECASTING SEASONAL INFLUENZA WITH A STATE-SPACE SIR MODEL

Dave Osthus et al.

ANNALS OF APPLIED STATISTICS (2017)

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Using a Dynamic Causal Model to validate previous predictions and offer a 12-month forecast of the long-term effects of the COVID-19 epidemic in the UK

相关参考文献

Accurate inference of crowdsourcing properties when using efficient allocation strategies

A 12-month projection to September 2022 of the COVID-19 epidemic in the UK using a dynamic causal model

Prioritising COVID-19 vaccination in changing social and epidemiological landscapes: a mathematical modelling study

Predicting intervention effect for COVID-19 in Japan: state space modeling approach

Forecasting Ebola with a regression transmission model

FORECASTING SEASONAL INFLUENZA WITH A STATE-SPACE SIR MODEL

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