Mathematical modelling review quantifies ethnic disparities in respiratory infection transmission dynamics across England

This mathematical modelling review analyzes data from the 2024-2025 Reconnect social contact survey, which included 12,484 participants across England, including major cities such as Birmingham and Liverpool. The study quantifies how differences in social mixing and demographic characteristics contribute to inequalities in respiratory infection transmission dynamics. The primary outcomes assessed were the number of contacts and attack rates, with White ethnicity serving as the comparator group.

The model found that individuals of Black ethnicity had more contacts compared to White ethnicity, with a rate ratio of 1.18 (95% CI: 1.11-1.26). Similarly, Mixed ethnicity participants reported more contacts than White participants, showing a rate ratio of 1.31 (95% CI: 1.14-1.52). Conversely, Asian ethnicity was associated with fewer contacts compared to White ethnicity, with a rate ratio of 0.85 (95% CI: 0.79-0.91).

Regarding attack rates, the national level data showed the lowest rates in White ethnicity. In Birmingham, attack rates were approximately double in Black and Mixed ethnicities compared to White ethnicity. In Liverpool, attack rates were less than 60% higher in Black and Mixed ethnicities compared to White ethnicity. The authors note that the role of additional demographic factors remains underexplored as a limitation of the current analysis.

The study concludes that while these findings quantify disparities, the role of additional demographic factors remains underexplored. Consequently, mitigation strategies must explicitly account for inequalities arising from local context. The authors do not report adverse events or discontinuations, and funding or conflicts of interest were not reported. This review highlights the complex interplay between social structure and infection risk without establishing direct causality beyond the model's quantification.