Amal Elfassihi

Using mortality data adjustment methods for COVID-19 helps avoid double counting and derives long-term trends without instabilities from a one-off experience.

Climate change will lead to greater mortality risk, so we discuss the exposure to high temperatures and look at alternative modeling for vector-borne diseases.

Compared with traditional mortality models, machine learning algorithms can significantly improve the forecasts of future mortality rates.

How to model the COVID-19 pandemic and forge a path to better risk insurance.

This paper presents a solution to address (re)insurers’ challenges, including how to determine the confidence level needed for disclosure purposes and how to restate a given confidence level over different time horizons.

This paper explores the potential and the challenge of using BERT, a Natural Language Processing framework, to automate the task of gathering input information and assisting experts for COVID-19 studies.