Area-level geographic and socioeconomic factors and the local incidence of SARS-CoV-2 infections in Queensland between 2020 and 2022

Abstract

Area-level geographic and socioeconomic factors and the local incidence of SARS-CoV-2 infections in Queensland between 2020 and 2022 Selina Ward,* Angela Cadavid Restrepo Lisa McHugh School of Public Health, University of Queensland, Herston, Australia Submitted: 29 January 2023; Revision requested: 29 August 2023; Accepted: 5 September 2023 Abstract Objective: Calculate the incidence of SARS-CoV-2 (COVID-19) infection notifications and the influence of area-level geographic and socioeconomic factors in Queensland using real-time data from the COVID-19 Real-time Information System for Preparedness and Epidemic Response (CRISPER) project. Design and setting: Population-level ecological study and spatial mapping of the incidence of COVID-19 infection notifications in Queensland, by postcode, 2020–2022. Main outcome measures: Proportions and distribution of COVID-19 infection notifications by year, age-group, socioeconomic disadvantage, and geospatial mapping. Incidence rate ratios (IRRs) were calculated. Results: Between 28 January 2020 and 30 June 2022, a total of 609,569 cases of COVID-19 associated with a Queensland postcode were recorded. The highest proportion of cases occurred in 2022 (96.5%), and in the 20- to 24-year age category (IRR = 1.787). In non–Major City areas, there was also a higher incidence of COVID-19 cases in lower socioeconomic areas (IRR = 0.84) than in higher socioeconomic areas (IRR = 0.66). Conclusions: Queensland experienced its highest proportion of COVID-19 cases once domestic and international borders opened. However, geographic and socioeconomic factors may have still contributed to a higher incidence of COVID-19 cases across some Queensland areas. Implications for Public Health: Although Australia has moved from the emergency response phase of the COVID-19 pandemic, we need to ensure ongoing prevention strategies target groups and areas that we have identified with the highest incidence. Key words: COVID-19, Queensland, epidemiology, spatial mapping, incidence