Actuaries can use dynamic modelling instead of a statistical method to track and address future pandemics more effectively, the IFoA has said.
According to its Longevity Bulletin, which examines life expectancy trends, a traditional actuarial approach would be to undertake statistical analysis of past mortality experience.
Gordon Woo, chief architect of the first pandemic risk model for the life insurance industry at Risk Management Solutions, said in the report it was possible to extrapolate from historical data. But the "paucity of historical events" and the evolution over time of the human population and its interaction with the infectious disease environment, made it difficult to provide an accurate picture.
To understand the scope of pandemic risk, he said the spectrum of possible future scenarios would need to be constructed based on current human population and an up-to-date scientific understanding of the disease environment.
Woo said: "This structured approach to dynamic modelling is more insightful for risk management than a purely statistical method, because of the sparse statistics of pandemics. Such a structured approach is highly computer-intensive and underpins the development of software for catastrophe insurance risk modelling over the past quarter century."
The report highlighted the importance of factors such as understanding the routes of transmission, prevention and treatment, and factors that would increase or decrease the risk of pandemics such as international travel and vaccination.
For example, it said modelling of historic air-passenger volumes and flight patterns could point to destinations where a traveller with Ebola might be. The IFoA said this could help authorities make sure a vaccine can be in the right place at the right time to tackle any emerging outbreak.
Also in the study Christoph Thuemmler, professor at Edinburgh Napier University, said the wide availability of social media, as well as the smartphone and other mobile devices, were playing an increasing role in all areas of health.
For instance, personalisation and virtualisation of health care could be analysed through m-health technology - the practice of healthcare with the use of mobile devices. Thuemmler also said health officials were able to detect flu trends using Twitter.
He said: "In several studies it could be demonstrated that it was possible to track flu pandemics by monitoring the social web using completely independent data to that commonly used for flu detection.
"Cross matching the results of big data analysis of the social web and medical data could be of tremendous value in rapidly responding to future outbreaks of infectious diseases."