Machine learning for data-centric epidemic forecasting
The COVID-19 pandemic emphasized the importance of epidemic forecasting for decision
makers in multiple domains, ranging from public health to the economy. Forecasting …
makers in multiple domains, ranging from public health to the economy. Forecasting …
[HTML][HTML] Inference of epidemic dynamics in the COVID-19 era and beyond
The COVID-19 pandemic demonstrated the key role that epidemiology and modelling play
in analysing infectious threats and supporting decision making in real-time. Motivated by the …
in analysing infectious threats and supporting decision making in real-time. Motivated by the …
Evaluating the use of social contact data to produce age-specific short-term forecasts of SARS-CoV-2 incidence in England
Mathematical and statistical models can be used to make predictions of how epidemics may
progress in the near future and form a central part of outbreak mitigation and control …
progress in the near future and form a central part of outbreak mitigation and control …
Scoring epidemiological forecasts on transformed scales
Forecast evaluation is essential for the development of predictive epidemic models and can
inform their use for public health decision-making. Common scores to evaluate …
inform their use for public health decision-making. Common scores to evaluate …
A scenario modelling analysis to anticipate the impact of COVID-19 vaccination in adolescents and children on disease outcomes in the Netherlands, summer 2021
Background Since the roll-out of COVID-19 vaccines in late 2020 and throughout 2021,
European governments have relied on mathematical modelling to inform policy decisions …
European governments have relied on mathematical modelling to inform policy decisions …
[HTML][HTML] A model learning framework for inferring the dynamics of transmission rate depending on exogenous variables for epidemic forecasts
In this work, we aim to formalize a novel scientific machine learning framework to reconstruct
the hidden dynamics of the transmission rate, whose inaccurate extrapolation can …
the hidden dynamics of the transmission rate, whose inaccurate extrapolation can …
Computational experiments meet large language model based agents: A survey and perspective
Q Ma, X Xue, D Zhou, X Yu, D Liu, X Zhang… - arxiv preprint arxiv …, 2024 - arxiv.org
Computational experiments have emerged as a valuable method for studying complex
systems, involving the algorithmization of counterfactuals. However, accurately representing …
systems, involving the algorithmization of counterfactuals. However, accurately representing …
The importance of investing in data, models, experiments, team science, and public trust to help policymakers prepare for the next pandemic
The COVID-19 pandemic has brought about valuable insights regarding models, data, and
experiments. In this narrative review, we summarised the existing literature on these three …
experiments. In this narrative review, we summarised the existing literature on these three …
National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021
Background During the COVID-19 pandemic there has been a strong interest in forecasts of
the short-term development of epidemiological indicators to inform decision makers. In this …
the short-term development of epidemiological indicators to inform decision makers. In this …
Integrating information from historical data into mechanistic models for influenza forecasting
A Andronico, J Paireau… - PLOS Computational …, 2024 - journals.plos.org
Seasonal influenza causes significant annual morbidity and mortality worldwide. In France, it
is estimated that, on average, 2 million individuals consult their GP for influenza-like-illness …
is estimated that, on average, 2 million individuals consult their GP for influenza-like-illness …