Geographic disparities in COVID-19 case rates are not reflected in seropositivity rates using a neighborhood survey in Chicago

Disproportionate impacts of COVID-19 in a large US city

COVID-19 has disproportionately impacted individuals depending on where they live and work, and based on their race, ethnicity, and socioeconomic status. Studies have documented catastrophic disparities at critical points throughout the pandemic, but have not yet systematically tracked their severity through time. Using anonymized hospitalization data from March 11, 2020 to June 1, 2021 and fine-grain infection hospitalization rates, we estimate the time-varying burden of COVID-19 by age group and ZIP code in Austin, Texas. During this 15-month period, we estimate an overall 23.7% (95% CrI: 22.5-24.8%) infection rate and 29.4% (95% CrI: 28.0-31.0%) case reporting rate. Individuals over 65 were less likely to be infected than younger age groups (11.2% [95% CrI: 10.3-12.0%] vs 25.1% [95% CrI: 23.7-26.4%]), but more likely to be hospitalized (1,965 per 100,000 vs 376 per 100,000) and have their infections reported (53% [95% CrI: 49-57%] vs 28% [95% CrI: 27-30%]). We used a mixed effect poisson regression model to estimate disparities in infection and reporting rates as a function of social vulnerability. We compared ZIP codes ranking in the 75th percentile of vulnerability to those in the 25th percentile, and found that the more vulnerable communities had 2.5 (95% CrI: 2.0-3.0) times the infection rate and only 70% (95% CrI: 60%-82%) the reporting rate compared to the less vulnerable communities. Inequality persisted but declined significantly over the 15-month study period. Our results suggest that further public health efforts are needed to mitigate local COVID-19 disparities and that the CDC's social vulnerability index may serve as a reliable predictor of risk on a local scale when surveillance data are limited.

A neighborhood-level analysis of association between social vulnerability and COVID-19 in ahvaz, Iran

Social vulnerability and society's resilience are two concepts frequently used to examine the capacity of social systems to prepare, absorb, and adapt to environmental hazards and shocks. With the emergence of the COVID-19 pandemic, the role of social vulnerability in dealing with risks has gained renewed attention. Assessing social vulnerability can help managers and planners prioritize budgets, develop prevention programs, and enhance risk preparedness. This study aimed to determine the association between social vulnerability and COVID-19 in the neighborhoods of Ahvaz, Iran. To assess the social vulnerability of Ahvaz neighborhoods, decision-making techniques (best-worst method and weighted aggregated sum product assessment method) and geographic information systems were applied. Moreover, to investigate the relationship between social vulnerability and COVID-19 cases, the Pearson correlation test was used. The results showed that the '20-meteri shahrdari' neighborhood has the highest level of social vulnerability, and the lowest level of social vulnerability among the neighborhoods of Ahvaz belongs to the neighborhood of 'Shahrak Naft'. There is a low inverse association between the integrated index of social vulnerability and the incidence of COVID-19 per 1000 people in Ahvaz. By revealing the most important details at the neighborhood level and levels of vulnerability, the results can inform effective planning actions at the neighborhood level.

Comparison of a Blood Self-Collection System with Routine Phlebotomy for SARS-CoV-2 Antibody Testing

The Coronavirus Disease 2019 (COVID-19) pandemic forced researchers to reconsider in-person assessments due to transmission risk. We conducted a pilot study to evaluate the feasibility of using the Tasso-SST (Tasso, Inc, Seattle, Washington) device for blood self-collection for use in SARS-CoV-2 antibody testing in an ongoing COVID-19 prevalence and immunity research study. 100 participants were recruited between January and March 2021 from a previously identified sub-cohort of the Cabarrus County COVID-19 Prevalence and Immunity (C3PI) Study who were under-going bimonthly COVID-19 antibody testing. Participants were given a Tasso-SST kit and asked to self-collect blood during a scheduled visit where trained laboratory personnel performed routine phlebotomy. All participants completed an after-visit survey about their experience. Overall, 70.0% of participants were able to collect an adequate sample for testing using the device. Among those with an adequate sample, there was a high concordance in results between the Tasso-SST and phlebotomy blood collection methods (Cohen’s kappa coefficient = 0.88, Interclass correlation coefficient 0.98 [0.97, 0.99], p < 0.0001). The device received a high-level (90.0%) of acceptance among all participants. Overall, the Tasso-SST could prove to be a valuable tool for seroprevalence testing. However, future studies in larger, diverse populations over longer periods may provide a better understanding of device usability and acceptance among older participants and those with comorbidities in various use scenarios.

Relationship between Acute-Phase Symptoms and Immunoglobulin G Seropositivity up to Eight Months after COVID-19

Background and Objectives: Given the limited knowledge of antibody responses to COVID-19 and their determinants, we analyzed the relationship between the occurrence of acute-phase symptoms and infection-induced immunoglobulin (Ig) G seropositivity up to 8 months post-symptom onset. Materials and Methods: In this cross-sectional study, 661 middle-aged unvaccinated healthcare workers (HCWs) were interviewed about the presence of symptoms during the acute phase of their previously confirmed COVID-19 and were tested for specific IgG, targeting the spike protein (S1 and S2). The dependence of seropositivity on the symptom occurrence was explored through multiple logistic regression, adjusted for the interval between symptom onset and serology testing, and through classification and regression trees. Results: A total of 551 (83.4%) HCWs showed seropositivity and, inversely, 110 (16.6%) HCWs were seronegative. The chance of IgG seropositivity was increased by dyspnea (odds ratio (OR) 1.48, p < 0.001) and anosmia (OR 1.52, p = 0.021). Fever in HCWs with dyspnea resulted in the highest detected seropositivity rate, and anosmia in HCWs without dyspnea significantly increased the proportion of seropositivity. Conclusion: Clinical manifestation of the acute phase of COVID-19 predisposes to the development of infection-induced antibody responses. The findings can be applied for assessing the long-term protection by IgG, and thus, for creating effective surveillance strategies.

Association of Zip Code Vaccination Rate With COVID-19 Mortality in Chicago, Illinois

Importance

There has been large geographic inequity in vaccination coverage across Chicago, Illinois, with higher vaccination rates in zip codes with residents who predominantly have high incomes and are White.

Objective

To determine the association between inequitable zip code-level vaccination coverage and COVID-19 mortality in Chicago.

Design, Setting, and Participants

This retrospective cohort study used Chicago Department of Public Health vaccination and mortality data and Cook County Medical Examiner mortality data from March 1, 2020, through November 6, 2021, to assess the association of COVID-19 mortality with zip code-level vaccination rates. Data were analyzed from June 1, 2021, to April 13, 2022.

Exposures

Zip code-level first-dose vaccination rates before the Alpha and Delta waves of COVID-19.

Main Outcomes and Measures

The primary outcome was deaths from COVID-19 during the Alpha and Delta waves. The association of a marginal increase in zip code-level vaccination rate with weekly mortality rates was estimated with a mixed-effects Poisson regression model, and the total number of preventable deaths in the least vaccinated quartile of zip codes was estimated with a linear difference-in-difference design.

Results

The study population was 2 686 355 Chicago residents in 52 zip codes (median [IQR] age 34 [32-38] years; 1 378 658 [51%] women; 773 938 Hispanic residents [29%]; 783 916 non-Hispanic Black residents [29%]; 894 555 non-Hispanic White residents [33%]). Among residents in the least vaccinated quartile, 80% were non-Hispanic Black, compared with 8% of residents identifying as non-Hispanic Black in the most vaccinated quartile (P < .001). After controlling for age distribution and recovery from COVID-19, a 10-percentage point increase in zip code-level vaccination 6 weeks before the peak of the Alpha wave was associated with a 39% lower relative risk of death from COVID-19 (incidence rate ratio [IRR], 0.61 [95% CI, 0.52-0.72]). A 10-percentage point increase in zip code vaccination rate 6 weeks before the peak of the Delta wave was associated with a 24% lower relative risk of death (IRR, 0.76 [95% CI, 0.66-0.87]). The difference-in-difference estimate was that 119 Alpha wave deaths (72% [95% CI, 63%-81%]) and 108 Delta wave deaths (75% [95% CI, 66%-84%]) might have been prevented in the least vaccinated quartile of zip codes if it had had the vaccination coverage of the most vaccinated quartile.

Conclusions and Relevance

These findings suggest that low zip code-level vaccination rates in Chicago were associated with more deaths during the Alpha and Delta waves of COVID-19 and that inequitable vaccination coverage exacerbated existing racial and ethnic disparities in COVID-19 deaths.

Predicting COVID-19 future trends for different European countries using Pearson correlation

The ability to accurately forecast the number of COVID-19 cases and future case trends would certainly assist governments and various organisations in strategising and preparing for the newly infected cases well in advance. Many predictions have failed to foresee future COVID-19 cases due to the lack of reliable data; however, such data are now widely available for predicting future trends in COVID-19 after more than one and a half years of the pandemic. Also, various countries are closely monitoring other countries that are experiencing a surge in COVID-19 cases in the expectation of similar scenarios, but this does not always produce correct results, as no research has identified specific correlations between different countries in terms of COVID-19 cases. During the past 18 months, many nations have watched countries whose COVID-19 cases have risen sharply, in anticipation of handling the situation themselves. However, this did not provide accurate results, as no research was conducted that compared countries to determine if their COVID-19 case trends were correlated. As official data on COVID-19 cases has become increasingly available, using the Pearson correlation technique to pinpoint the countries that should be closely monitored will help governments plan and prepare for the number of infections that are expected in the future at an early stage. In this study, a simple and real-time prediction of COVID-19 cases incorporating existing variables of coronavirus variants was used to explore the correlation among different European countries in terms of the number of COVID-19 cases officially recorded on a daily basis. Data from selected countries over the past 76 weeks were analysed using a Pearson correlation technique to determine if there were correlations between case trends and geographical position. The correlation coefficient (r) was employed for identifying whether the different countries in Europe were interrelated, with r > 0.85 indicating they were very strongly correlated, 0.85 > r > 0.8 indicating that they were strongly correlated, 0.8 > r > 0.7 indicating that they were moderately correlated, and r < 0.7 indicating that the examined countries were either weakly correlated or that a correlation did not exist. The results showed that although some neighbouring countries are strongly correlated, other countries that are not geographically close are also correlated. In addition, some countries on opposite sides of Europe (Belgium and Armenia) are also correlated. Other countries (France, Iceland, Israel, Kosovo, San Marino, Spain, Sweden and Turkey) were either weakly correlated or had no relationship at all.