Social Contact Patterns During the COVID-19 Pandemic : Implications for Public Health and Hospital Infection Control

Bridgen, Jessica and Jewell, Christopher and Read, Jonathan (2024) Social Contact Patterns During the COVID-19 Pandemic : Implications for Public Health and Hospital Infection Control. PhD thesis, Lancaster University.

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Abstract

Social contact patterns are an important driver of respiratory epidemics. Human behaviour is likely to change during an outbreak; this may be due to imposed control measures or as a personal-risk judgement. Following the emergence of the COVID19 pandemic in 2020, numerous interventions were implemented in the UK to curb community transmission of SARS-CoV-2 by reducing social contact. It was therefore important to quantify contact patterns during the pandemic to understand how social networks had changed and identify key routes of transmission. Chapters 2 and 3 of this thesis outline two cross-sectional population-based surveys which quantified and characterised social contact patterns in different populations during the pandemic. Social contact patterns are quantified at the national scale in Chapter 2, following the relaxation of pandemic restrictions in July 2020. We investigated the association of demographic characteristics and behaviour, such as shielding and selfisolating, with non-household mixing. Chapter 3 describes an occupational study conducted in December 2020. In this study, we quantified social contact patterns of home delivery drivers at delivery depots and with customers, and identified the protective measures that they adopted during the pandemic. In Chapter 4 we outline a statistical framework to identify the role of hospital structure and staff interactions in nosocomial transmission of SARS-CoV-2 during the first wave of the pandemic. We present an efficient method to infer epidemiological event times and quantify relative routes of transmission, while accounting for the intricacies of the staff-patient contact network. This thesis demonstrates how social contact data can provide insight into adherence to non-pharmaceutical interventions, identify subgroups of the population which may be at a greater risk of infection, and quantify relative routes of transmission in high-risk settings. We identify the wider implications of social contact patterns during the COVID-19 pandemic for public health and hospital infection control.