Dissecting recurrent waves of pertussis across the boroughs of London

Author summaryRecent years have witnessed a resurgence of pertussis, a vaccine preventable bacterial disease, in countries with high estimated immunization rates. Here, to understand the timing of pertussis epidemics in different populations, we employed signal processing techniques to analyze a rich dataset of weekly incidence across the boroughs of London from 1982 to 2013. We observed 4-year epidemic cycles with a distinctly consistent spatial organization across the boroughs from 1982 to 1990, with some boroughs typically ahead of the wave and others consistently lagging. We identified putative demographic and socio-economic mechanisms that determined this spatial organization of these outbreaks using an interpretable machine learning approach. The reemergence of pertussis from 2006 onward, on the contrary, did not exhibit regular epidemic waves, instead there was a transition from spatially organized waves in the 1980s to a largely unstructured mosaic in the resurgence era. Pertussis has resurfaced in the UK, with incidence levels not seen since the 1980s. While the fundamental causes of this resurgence remain the subject of much conjecture, the study of historical patterns of pathogen diffusion can be illuminating. Here, we examined time series of pertussis incidence in the boroughs of Greater London from 1982 to 2013 to document the spatial epidemiology of this bacterial infection and to identify the potential drivers of its percolation. The incidence of pertussis over this period is characterized by 3 distinct stages: a period exhibiting declining trends with 4-year inter-epidemic cycles from 1982 to 1994, followed by a deep trough until 2006 and the subsequent resurgence. We observed systematic temporal trends in the age distribution of cases and the fade-out profile of pertussis coincident with increasing national vaccine coverage from 1982 to 1990. To quantify the hierarchy of epidemic phases across the boroughs of London, we used the Hilbert transform. We report a consistent pattern of spatial organization from 1982 to the early 1990s, with some boroughs consistently leading epidemic waves and others routinely lagging. To determine the potential drivers of these geographic patterns, a comprehensive parallel database of borough-specific features was compiled, comprising of demographic, movement and socio-economic factors that were used in statistical analyses to predict epidemic phase relationships among boroughs. Specifically, we used a combination of a feed-forward neural network (FFNN), and SHapley Additive exPlanations (SHAP) values to quantify the contribution of each covariate to model predictions. Our analyses identified a number of predictors of a borough's historical epidemic phase, specifically the age composition of households, the number of agricultural and skilled manual workers, latitude, the population of public transport commuters and high-occupancy households. Univariate regression analysis of the 2012 epidemic identified the ratio of cumulative unvaccinated children to the total population and population of Pakistan-born population to have moderate positive and negative association, respectively, with the timing of epidemic. In addition to providing a comprehensive overview of contemporary pertussis transmission in a large metropolitan population, this study has identified the characteristics that determine the spatial spread of this bacterium across the boroughs of London.