Abstract
INTRODUCTION: The COVID-19 pandemic has been a global health crisis since late 2019. By the end of 2021, the Netherlands reported over 3 million cases, leading to significant hospital and Intensive Care Unit (ICU) admissions. This study investigated the impact of demographic, socio-economic, health, including vaccination coverage, and neighborhood characteristics on COVID-19-related hospital and ICU admissions, with a focus on neighborhood differences in the region Haaglanden, the Netherlands. METHODS: This cross-sectional study included residents aged 25-79 years from the region Haaglanden. Data were stratified across three COVID-19 waves. Individual-level registry data from 2020 to 2021 were used, covering demographics, socio-economic factors, health information and neighborhood characteristics, linked to COVID-19-related hospital and ICU admissions. Multivariable logistic models were conducted per wave to estimate the odds of both COVID-19-related hospital and ICU admissions. RESULTS: More than 700.000 inhabitants from the region Haaglanden were included per wave. COVID-19-related hospital admissions were 0.08% (n = 571) in the first wave, 0.40% (n = 2.865) in the second, and 0.17% (n = 858) in the third wave. ICU admissions were 0.02% (n = 159) in the first wave, 0.07% (n = 530) in the second, and 0.03% (n = 192) in the third wave. Hospital and ICU admission odds were higher among older individuals, males, lower-educated individuals, those of Moroccan origin, residents with lower income and wealth, poor physical health and those living in low socio-economic neighborhoods. In the third wave, neighborhoods with vaccination coverage below 60% had the highest rates of hospital and ICU admissions. CONCLUSION: This study highlighted that individual and neighborhood factors were associated with a higher risk of COVID-19-related hospital and ICU admissions, with the individual risk factors often concentrated in neighborhoods with low socio-economic status scores. Public health strategies should focus on high-risk individuals and incorporate tailored interventions, while early identification of disadvantaged areas is key for effective resource allocation and reducing disparities during future outbreaks.