Article

Bayesian Spatio-temporal prediction and counterfactual generation: an application in non-pharmaceutical interventions in Covid-19

2022-12-05

Abstract excerpt

The spatio-temporal course of an epidemic (such as Covid-19) can be significantly affected by non-pharmaceutical interventions (NPIs), such as full or partial lockdowns. Bayesian Susceptible-Infected-Removed (SIR) models can be applied to the spatio-temporal spread of infectious disease (STIF) (such as Covid-19). In causal inference it is classically of interest to investigate counterfactuals. In the context of ST...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: e9b09f0f-6720-5bb8-914f-6c0b2ace1678
DOI: 10.1101/2022.11.30.22282938

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Bayesian Spatio-temporal prediction and counterfactual generation: an application in non-pharmaceutical interventions in Covid-19DOI 10.1101/2022.11.30.22282938Read

Research Article Summary: Inferring change points in the COVID-19 spreading reveals the effectiveness of interventionsSemantic proximity Read

An Evaluation of Prospective COVID-19 Modeling: From Data to Science TranslationSemantic proximity Read

Investigating the causal inference of vaccine on COVID-19 disease propagation based on Bayesian approachSemantic proximity Read

Predicting the Health Effects of the COVID-19 Epidemic in the UK to October 2023 Using a Dynamic Causal ModelSemantic proximity Read

Machine Learning and Probabilistic Approaches for Forecasting Infectious Disease Transmission and CasesSemantic proximity Read

Forecasting COVID-19 cases in US states using reconstructed incidence dataSemantic proximity Read

Epidemic Model Guided Machine Learning for COVID-19 Forecasts in the United StatesSemantic proximity Read

Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: results of a Bayesian evidence synthesis modelSemantic proximity Read

Forecasting the daily COVID-19 incidence in large and small communities -- A comparative study of forecasting approaches for disease surveillanceSemantic proximity Read

Challenges of COVID-19 Case Forecasting in the US, 2020-2021Semantic proximity Read

Spatiotemporal patterns and progression of the Delta variant of COVID-19 and their health intervention linkages in Southeast AsiaSemantic proximity Read

Development of Accurate Long-lead COVID-19 ForecastSemantic proximity Read