In a recent study posted to the medRxiv* preprint server, researchers estimated the time-varying burden of coronavirus disease 2019 (COVID-19) by ZIP codes and individual age in Austin, Texas.
COVID-19 has profoundly but disproportionately affected individuals depending on their residence and workplace location, socioeconomic status, and ethnicity. Studies have reported catastrophic discrepancies at several time points of the pandemic, the severity of which has not yet been tracked systematically.
Study: Disproportionate impacts of COVID-19 in a large US city. Image Credit: Alexander Lukatskiy / Shutterstock
*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
About the study
In the present study, researchers estimated the spatial age-specific and ZIP code-specific time-varying COVID-19 burden in Texas using anonymized hospital admissions data between 11 March 2020 and 1 June 2021.
ZIP codes ranking in the 25th and 75th percentiles of vulnerability were compared. The daily counts of SARS-CoV-2 infections, stratified by age for every ZIP code in Austin, were estimated. Hospital admission data was provided by three main public health systems of Austin. First, the age-stratified IHRs (infection hospitalization rates) from statewide COVID-19 hospital admission data and data of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) seroprevalence were estimated.
Subsequently, the estimated IHR values were used for inferring SARS-CoV-2 infections by the age of the individuals and ZIP codes with the help of a deconvolution-based technique. To compare the accuracy of the estimates with the true rates of SARS-CoV-2 infections in Travis county, the rates were compared to those reported by the Centers for Disease Control and Prevention (CDC). The CDC SVI (social vulnerability index) values were compared with the ZIP codes based on weighted averages of the residential addresses included under a particular ZIP code falling under one census tract.
Mixed effect-type Poisson regression modeling was used to determine the effects of SVI on the rates of being SARS-CoV-2-infected and reporting the infections. The team assumed that differences in risks between Austin’s 46 different ZIP codes were based on the estimated number of individuals at an increased risk of severe SARS-CoV-2 infections. The high-risk fraction was estimated using ZIP code-level data and state-level data obtained from the CDC PLACES: Local Data for Better Health.
Results
The period of the study preceded the SARS-CoV-2 Delta VOC (variant of concern) emergence, including a pandemic wave during April 2020 and larger subsequent COVID-19 waves in summer (between 1 June 2020 and 1 August 2020) and winter (between 1 December 2020 and 1 February 2021). Among the waves, the summer COVID-19 wave was relatively mild for children. By 1 June 2021, 83,722 cases were reported, including 6,474 and 1,024 hospitalized and deceased COVID-19 patients in the county, from a population of 1.3 million.
The estimated rates of developing SARS-CoV-2 infections and reporting them were 17% and 34%, respectively, in accordance with the officially reported seroprevalence estimates of the CDC. In addition, individuals aged >65 years showed a lower likelihood of being SARS-CoV-2-infected compared to those aged 18 years to 49 years (eight percent versus 19%) but a higher likelihood of being admitted to hospitals (1,381 individuals for every 100,000 individuals versus 319 individuals for every 100,000 individuals) and document their infections (51% versus 33%).
The estimated percentage of documented COVID-19 cases was directly proportional to age, ranging between 23% for individuals aged ≤17 years and 51% for those aged >65. In the county, pediatric individuals aged <17 years were hospitalized the least (50 hospitalizations among every 100,000 individuals). However, the number of documented COVID-19 cases was comparable across ages, ranging between 3,793 individuals among every 100,000 individuals in children and 7,159 individuals among every 100,000 individuals in youngsters.
Six percent of all SARS-CoV-2 infections between 1 March and 1 May 2020 were observed among children, who comprised 20% of the total population, compared to 20% of infections between 1 December 2020 and 1 February of the consecutive year. The number of SARS-CoV-2 infections among individuals aged 18 to 49, who comprised 51% of the total population, reduced from 69% during spring 2020 (between 1 March 2020 and 1 May 2020) to 51% during the 2020-2021 winter COVID-19 wave.
Infection rates were 2.5-times higher among the more vulnerable (higher SVI) community-dwelling individuals, and the reporting rates were only 70% of those compared to individuals residing in less vulnerable community-based settings. Inequalities were found to persist, although they significantly reduced over the study period. Infection rate ratios for communities with high and low social vulnerability reduced in 2020 from 12 (April) to four (August) to three (December).
The burden of SARS-CoV-2 infections significantly varied by ZIP code, dividing Travis county into low-risk and high-risk zones in the Western and Eastern regions, respectively. The risk estimates positively correlated with SVI estimates. The ZIP-code-specific IHRs showed geographical trends opposite to the absolute IHRs. The estimated infection rates (39%) and reporting rates (18%) were the highest and lowest, respectively, for the downtown Austin region (78,701).
Overall, the study findings highlighted the disproportionate impact of COVID-19 in the United States and showed that COVID-19 mitigation efforts taken by the public of Texas were effective to a limited extent. In addition, the CDC SVI could reliably estimate COVID-19 hospitalization risks in local settings.
*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
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