The epidemiology of pathogens with pandemic potential: A review of key parameters and clustering analysis

Introduction In the light of the COVID-19 pandemic many countries are trying to widen their pandemic planning from its traditional focus on influenza. However, it is impossible to draw up detailed plans for every pathogen with epidemic potential. We set out to try to simplify this process by reviewing the epidemiology of a range of pathogens with pandemic potential and seeing whether they fall into groups with shared epidemiological traits. Methods We reviewed the epidemiological characteristics of 19 different pathogens with pandemic potential (those on the WHO priority list of pathogens, different strains of influenza and Mpox). We extracted data on the proportion of presymptomatic transmission, incubation period, serial interval and basic reproduction number (R0) for the targeted pathogens. We applied unsupervised machine learning (specifically K-means and hierarchical clustering) to categorise these pathogens based on these characteristics. . Results Fom 166 studies we extracted 342 epidemiological parameter estimates. The clustering algorithms categorise these pathogens into five archetypes (1) airborne pathogens with high transmission potential, (2) respiratory zoonoses characterized by high case fatality risk, (3) contact zoonoses with high fatality rates, (4) contact zoonoses exhibiting presymptomatic transmission, and (5) vector-borne pathogens capable of secondary human-to-human transmission. Conclusion Unsupervised learning on epidemiological data can be used to predict distinct pathogen archetypes. This method offers a valuable framework to allocate emerging and novel pathogens into defined groups to evaluate common approaches for their control.