期刊
LIFE-BASEL
卷 11, 期 12, 页码 -出版社
MDPI
DOI: 10.3390/life11121336
关键词
COVID-19; test positivity rate; mixed-effects model
The study found a consistent association between COVID-19 positivity rate and hospitalization rates at the county level in California. Demographic factors related to higher hospitalization rates changed over time as the pandemic profile impacted different populations in counties across California.
The rapid spread of the new SARS-CoV-2 virus triggered a global health crisis, disproportionately impacting people with pre-existing health conditions and particular demographic and socioeconomic characteristics. One of the main concerns of governments has been to avoid health systems becoming overwhelmed. For this reason, they have implemented a series of non-pharmaceutical measures to control the spread of the virus, with mass tests being one of the most effective controls. To date, public health officials continue to promote some of these measures, mainly due to delays in mass vaccination and the emergence of new virus strains. In this research, we studied the association between COVID-19 positivity rate and hospitalization rates at the county level in California using a mixed linear model. The analysis was performed in the three waves of confirmed COVID-19 cases registered in the state to September 2021. Our findings suggest that test positivity rate is consistently associated with hospitalization rates at the county level for all study waves. Demographic factors that seem to be related to higher hospitalization rates changed over time, as the profile of the pandemic impacted different fractions of the population in counties across California.
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