no code implementations • 31 May 2023 • Elizaveta Semenova, Swapnil Mishra, Samir Bhatt, Seth Flaxman, H Juliette T Unwin
Model-based disease mapping remains a fundamental policy-informing tool in the fields of public health and disease surveillance.
no code implementations • 1 May 2023 • Nicolas Banholzer, Thomas Mellan, H Juliette T Unwin, Stefan Feuerriegel, Swapnil Mishra, Samir Bhatt
Here, we compare short-term probabilistic forecasts of popular mechanistic models based on the renewal equation with forecasts of statistical time series models.
1 code implementation • 23 Apr 2020 • Seth Flaxman, Swapnil Mishra, Axel Gandy, H Juliette T Unwin, Helen Coupland, Thomas A. Mellan, Harrison Zhu, Tresnia Berah, Jeffrey W Eaton, Pablo N P Guzman, Nora Schmit, Lucia Callizo, Imperial College COVID-19 Response Team, Charles Whittaker, Peter Winskill, Xiaoyue Xi, Azra Ghani, Christl A. Donnelly, Steven Riley, Lucy C Okell, Michaela A. C. Vollmer, Neil M. Ferguson, Samir Bhatt
Our model estimates these changes by calculating backwards from temporal data on observed to estimate the number of infections and rate of transmission that occurred several weeks prior, allowing for a probabilistic time lag between infection and death.
Applications Methodology