Unravelling the variations of the society of England and Wales through diffusion mapping analysis of census 2011.

We propose a new approach to identify geographical clustering and inequality hotspots from decadal census data, with a particular emphasis on the method itself. Our method uses diffusion mapping to study the 181 408 output areas in England and Wales (EW), which enables us to decompose the census data's EW-specific feature structures. We further introduce a localization metric, inspired by statistical physics, to reveal the significance of minority groups in London. Our findings can be adapted to analogous datasets, illuminating spatial patterns and differentiating within datasets, especially when meaning factors for determining the datasets' structure are scarce and spatially heterogeneous. This approach enhances our ability to describe and explore patterns of social deprivation and segregation across the country, thereby contributing to the development of targeted policies. We also underscore the method's intrinsic objectivity, guaranteeing its ability to offer comprehensive and unbiased analysis, unswayed by preconceived hypotheses or subjective interpretations of data patterns.

Quantifying the spatial spillover effects of non-pharmaceutical interventions on pandemic risk.

BACKGROUND: Non-pharmaceutical interventions (NPIs) implemented in one place can affect neighboring regions by influencing people's behavior. However, existing epidemic models for NPIs evaluation rarely consider such spatial spillover effects, which may lead to a biased assessment of policy effects. METHODS: Using the US state-level mobility and policy data from January 6 to August 2, 2020, we develop a quantitative framework that includes both a panel spatial econometric model and an S-SEIR (Spillover-Susceptible-Exposed-Infected-Recovered) model to quantify the spatial spillover effects of NPIs on human mobility and COVID-19 transmission. RESULTS: The spatial spillover effects of NPIs explain [Formula: see text] [[Formula: see text] credible interval: 52.8-[Formula: see text]] of national cumulative confirmed cases, suggesting that the presence of the spillover effect significantly enhances the NPI influence. Simulations based on the S-SEIR model further show that increasing interventions in only a few states with larger intrastate human mobility intensity significantly reduce the cases nationwide. These region-based interventions also can carry over to interstate lockdowns. CONCLUSIONS: Our study provides a framework for evaluating and comparing the effectiveness of different intervention strategies conditional on NPI spillovers, and calls for collaboration from different regions.