New modelling framework developed to improve infectious disease control

A new model to analyse infectious disease outbreak data has been developed by mathematicians that could be used to improve disease tracking and control. Researchers from the University of Nottingham developed a new data-driven framework for modelling how infectious diseases spread through a population that could reduce errors in decisions made about disease control measures. Their findings have been published in PNAS. The COVID-19 pandemic has highlighted that the ability to unravel the dynamics of the spread of infectious diseases is profoundly important for designing effective control strategies and assessing existing ones. Mathematical models of how infectious diseases spread continue to play a vital role in understanding, mitigating, and preventing outbreaks. Dr Rowland Seymour led the study and explains: “Most of the infectious disease models contain specific assumptions about how transmission occurs within a population. These assumptions can be arbitrary, particularly when it comes to describing how transmission varies between individuals of different...