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

Mustanski, Brian; Saber, Rana; Ryan, Daniel T.; Benbow, Nanette; Madkins, Krystal; Hayford, Christina; Newcomb, Michael E.; Schrock, Joshua M.; Vaught, Lauren A.; Reiser, Nina L.; Velez, Matthew P.; Hsieh, Ryan R; Demonbreun, Alexis R.; D’Aquila, Richard T.; McNally, Elizabeth M.; McDade, Thomas W.

doi:10.1016/j.annepidem.2021.10.006

Cited by 11 publications

(9 citation statements)

References 36 publications

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“…Currently, there are limited data regarding the reliability of remote sample collection for SARS-CoV-2 antibody testing. Many seroprevalence studies for COVID-19 have used dried blood spot cards collected remotely [ 20 , 21 , 22 , 23 , 24 , 25 , 26 ], but they can have a non-uniform blood distribution and uncertain collection volume [ 21 , 27 ]. One way to mitigate this issue of non-uniform blood distribution is the use of a volumetric sampling device, such as the Tasso-SST (Tasso, Inc, Seattle, Washington) device for capillary blood self-collection.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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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.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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“…In addition, the research of Sun et al ( 2020 ) predicts that a lockdown may be an effective measure to limit the relationship between COVID-19 spread and geographical location, and the relationship between COVID-19 spread and population density. The findings of Mustanski et al ( 2022 ) also indicate that exposure to SARS-COV2 may be more consistent across neighbourhoods within the city of Chicago (USA) than previously thought based on reported COVID-19 case rates. This suggests that factors other than differential seroprevalence, such as geographical location, may play a role in driving disparities in COVID-19 outcomes.…”

Section: Introductionmentioning

confidence: 77%

“…This suggests that factors other than differential seroprevalence, such as geographical location, may play a role in driving disparities in COVID-19 outcomes. Mustanski et al ( 2022 ) reports that the number of active cases in the United States can potentially be used as a warning sign and true predictor of the future trajectory of the epidemic based on geographical spread.…”

Section: Introductionmentioning

confidence: 99%

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

Muhaidat

Albatayneh

Abdallah

et al. 2022

Euro-Mediterr J Environ Integr

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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.

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“…Despite the development of the COVID-19 pandemic, the occurrence of the most common symptoms of the acute phase remains similar, although certain symptoms may appear more prominent depending on a virus strain, affected population, geographical area, etc. [1,30,31]. The study limitations include a cross-sectional design; however, the regression model was adjusted for the interval between symptom onset and serology testing.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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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.

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

Cited by 11 publications

References 36 publications

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

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

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

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

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