Fabian Valka

ORCID: 0000-0003-0116-9003
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Research Areas
  • Data-Driven Disease Surveillance
  • COVID-19 epidemiological studies
  • Radiomics and Machine Learning in Medical Imaging
  • COVID-19 Pandemic Impacts
  • Air Traffic Management and Optimization
  • Medical Imaging Techniques and Applications
  • Software Reliability and Analysis Research
  • Advanced MRI Techniques and Applications
  • Arctic and Antarctic ice dynamics
  • Insurance and Financial Risk Management
  • Human-Automation Interaction and Safety
  • Advanced Software Engineering Methodologies
  • Influenza Virus Research Studies
  • Aviation Industry Analysis and Trends
  • COVID-19 diagnosis using AI
  • SARS-CoV-2 and COVID-19 Research
  • Viral Infections and Outbreaks Research
  • Meteorological Phenomena and Simulations

Imperial College London
2020

Abstract As of 1st June 2020, the US Centres for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in US. This was more than twice number next most severely impacted country. We jointly model epidemic at state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate individuals that have been infected, are currently infectious time-varying reproduction (the average secondary...

10.1038/s41467-020-19652-6 article EN cc-by Nature Communications 2020-12-03

Abstract As of 1st June 2020, the US Centers for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in US. This was more than twice number next most severely impacted country. We jointly modelled epidemic at state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate individuals that have been infected, are currently infectious time-varying reproduction (the average...

10.1101/2020.07.13.20152355 preprint EN cc-by-nc-nd medRxiv (Cold Spring Harbor Laboratory) 2020-07-14

A bstract R t plays a key role in the development of COVID-19 pandemic. The methods used for building an interactive website visualization time-varying reproduction number and novel way to visualize time delay from infection estimation overlayed with estimate are described analyzed regards influence parameters chosen compared published estimates Austria. Visualizing delays enables exploration suspected changes transmission their effect on estimate.

10.1101/2020.09.19.20197970 preprint EN cc-by medRxiv (Cold Spring Harbor Laboratory) 2020-09-22

10.5281/zenodo.3846007 article EN 2019-11-28
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