21 results on '"Sewalk K"'
Search Results
2. EPICORE: AN INNOVATIVE GLOBAL DISEASE SURVEILLANCE TOOL FOR HUMAN, ANIMAL, AND ENVIRONMENTAL PUBLIC HEALTH EVENTS
- Author
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Schultheiss, M., primary, Sewalk, K., additional, Montero, J., additional, Libel, M., additional, Divi, N., additional, and Brownstein, J., additional
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- 2023
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3. Mask-Wearing and Individual Risk of Respiratory Illness during the COVID-19 Pandemic
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Popp, Z., primary, Gertz, A., additional, Sewalk, K., additional, Brownstein, J., additional, and Rader, B., additional
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- 2022
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4. Assessing the Shift in Reasoning for COVID-19 Vaccine Hesitancy in the United States Using a Six-Month Cross-Sectional Analysis from December 2020 to June 2021
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Gertz, A., primary, Sewalk, K., additional, and Brownstein, J., additional
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- 2022
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5. Flu Near You: Crowdsourcing influenza-like-illness reporting across the United States comparing the 2017–18 and 2018–19 influenza seasons
- Author
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Sewalk, K., primary, Smith, S., additional, Goodwin, L., additional, and Brownstein, J., additional
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- 2020
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6. Flu near you: crowdsourcing influenza-like illness reporting in the United States comparing the 2016-17 and 2017-18 influenza season with participant-reported symptoms
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Sewalk, K., primary, Baltrusaitis, K., additional, Cohn, E., additional, Crawley, A.W., additional, and Brownstein, J., additional
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- 2019
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7. Using EpiCore to Enable Rapid Verification of Potential Health Threats: Illustrated Use Cases and Summary Statistics.
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Divi N, Mantero J, Libel M, Leal Neto O, Schultheiss M, Sewalk K, Brownstein J, and Smolinski M
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- Animals, Humans, Pandemics, Disease Outbreaks prevention & control, Health Personnel
- Abstract
Background: The proliferation of digital disease-detection systems has led to an increase in earlier warning signals, which subsequently have resulted in swifter responses to emerging threats. Such highly sensitive systems can also produce weak signals needing additional information for action. The delays in the response to a genuine health threat are often due to the time it takes to verify a health event. It was the delay in outbreak verification that was the main impetus for creating EpiCore., Objective: This paper describes the potential of crowdsourcing information through EpiCore, a network of voluntary human, animal, and environmental health professionals supporting the verification of early warning signals of potential outbreaks and informing risk assessments by monitoring ongoing threats., Methods: This paper uses summary statistics to assess whether EpiCore is meeting its goal to accelerate the time to verification of identified potential health events for epidemic and pandemic intelligence purposes from around the world. Data from the EpiCore platform from January 2018 to December 2022 were analyzed to capture request for information response rates and verification rates. Illustrated use cases are provided to describe how EpiCore members provide information to facilitate the verification of early warning signals of potential outbreaks and for the monitoring and risk assessment of ongoing threats through EpiCore and its utilities., Results: Since its launch in 2016, EpiCore network membership grew to over 3300 individuals during the first 2 years, consisting of professionals in human, animal, and environmental health, spanning 161 countries. The overall EpiCore response rate to requests for information increased by year between 2018 and 2022 from 65.4% to 68.8% with an initial response typically received within 24 hours (in 2022, 94% of responded requests received a first contribution within 24 h). Five illustrated use cases highlight the various uses of EpiCore., Conclusions: As the global demand for data to facilitate disease prevention and control continues to grow, it will be crucial for traditional and nontraditional methods of disease surveillance to work together to ensure health threats are captured earlier. EpiCore is an innovative approach that can support health authorities in decision-making when used complementarily with official early detection and verification systems. EpiCore can shorten the time to verification by confirming early detection signals, informing risk-assessment activities, and monitoring ongoing events., (©Nomita Divi, Jaś Mantero, Marlo Libel, Onicio Leal Neto, Marinanicole Schultheiss, Kara Sewalk, John Brownstein, Mark Smolinski. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 15.03.2024.)
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- 2024
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8. Decreased Seasonal Influenza Rates Detected in a Crowdsourced Influenza-Like Illness Surveillance System During the COVID-19 Pandemic: Prospective Cohort Study.
- Author
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Gertz A, Rader B, Sewalk K, Varrelman TJ, Smolinski M, and Brownstein JS
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- Humans, Seasons, Pandemics, Prospective Studies, SARS-CoV-2, COVID-19 epidemiology, Influenza, Human epidemiology, Influenza, Human prevention & control, Crowdsourcing, Virus Diseases
- Abstract
Background: Seasonal respiratory viruses had lower incidence during their 2019-2020 and 2020-2021 seasons, which overlapped with the COVID-19 pandemic. The widespread implementation of precautionary measures to prevent transmission of SARS-CoV-2 has been seen to also mitigate transmission of seasonal influenza. The COVID-19 pandemic also led to changes in care seeking and access. Participatory surveillance systems have historically captured mild illnesses that are often missed by surveillance systems that rely on encounters with a health care provider for detection., Objective: This study aimed to assess if a crowdsourced syndromic surveillance system capable of detecting mild influenza-like illness (ILI) also captured the globally observed decrease in ILI in the 2019-2020 and 2020-2021 influenza seasons, concurrent with the COVID-19 pandemic., Methods: Flu Near You (FNY) is a web-based participatory syndromic surveillance system that allows participants in the United States to report their health information using a brief weekly survey. Reminder emails are sent to registered FNY participants to report on their symptoms and the symptoms of household members. Guest participants may also report. ILI was defined as fever and sore throat or fever and cough. ILI rates were determined as the number of ILI reports over the total number of reports and assessed for the 2016-2017, 2017-2018, 2018-2019, 2019-2020, and 2020-2021 influenza seasons. Baseline season (2016-2017, 2017-2018, and 2018-2019) rates were compared to the 2019-2020 and 2020-2021 influenza seasons. Self-reported influenza diagnosis and vaccination status were captured and assessed as the total number of reported events over the total number of reports submitted. CIs for all proportions were calculated via a 1-sample test of proportions., Results: ILI was detected in 3.8% (32,239/848,878) of participants in the baseline seasons (2016-2019), 2.58% (7418/287,909) in the 2019-2020 season, and 0.27% (546/201,079) in the 2020-2021 season. Both influenza seasons that overlapped with the COVID-19 pandemic had lower ILI rates than the baseline seasons. ILI decline was observed during the months with widespread implementation of COVID-19 precautions, starting in February 2020. Self-reported influenza diagnoses decreased from early 2020 through the influenza season. Self-reported influenza positivity among ILI cases varied over the observed time period. Self-reported influenza vaccination rates in FNY were high across all observed seasons., Conclusions: A decrease in ILI was detected in the crowdsourced FNY surveillance system during the 2019-2020 and 2020-2021 influenza seasons, mirroring trends observed in other influenza surveillance systems. Specifically, the months within seasons that overlapped with widespread pandemic precautions showed decreases in ILI and confirmed influenza. Concerns persist regarding respiratory pathogens re-emerging with changes to COVID-19 guidelines. Traditional surveillance is subject to changes in health care behaviors. Systems like FNY are uniquely situated to detect disease across disease severity and care seeking, providing key insights during public health emergencies., (©Autumn Gertz, Benjamin Rader, Kara Sewalk, Tanner J Varrelman, Mark Smolinski, John S Brownstein. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 28.12.2023.)
- Published
- 2023
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9. Retrospective evaluation of real-time estimates of global COVID-19 transmission trends and mortality forecasts.
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Bhatia S, Parag KV, Wardle J, Nash RK, Imai N, Elsland SLV, Lassmann B, Brownstein JS, Desai A, Herringer M, Sewalk K, Loeb SC, Ramatowski J, Cuomo-Dannenburg G, Jauneikaite E, Unwin HJT, Riley S, Ferguson N, Donnelly CA, Cori A, and Nouvellet P
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- Humans, Retrospective Studies, SARS-CoV-2, Time, Forecasting, COVID-19 epidemiology, Epidemics
- Abstract
Since 8th March 2020 up to the time of writing, we have been producing near real-time weekly estimates of SARS-CoV-2 transmissibility and forecasts of deaths due to COVID-19 for all countries with evidence of sustained transmission, shared online. We also developed a novel heuristic to combine weekly estimates of transmissibility to produce forecasts over a 4-week horizon. Here we present a retrospective evaluation of the forecasts produced between 8th March to 29th November 2020 for 81 countries. We evaluated the robustness of the forecasts produced in real-time using relative error, coverage probability, and comparisons with null models. During the 39-week period covered by this study, both the short- and medium-term forecasts captured well the epidemic trajectory across different waves of COVID-19 infections with small relative errors over the forecast horizon. The model was well calibrated with 56.3% and 45.6% of the observations lying in the 50% Credible Interval in 1-week and 4-week ahead forecasts respectively. The retrospective evaluation of our models shows that simple transmission models calibrated using routine disease surveillance data can reliably capture the epidemic trajectory in multiple countries. The medium-term forecasts can be used in conjunction with the short-term forecasts of COVID-19 mortality as a useful planning tool as countries continue to relax public health measures., Competing Interests: AC has received payment from Pfizer for teaching of mathematical modelling of infectious diseases. All other authors have declared that no competing interests exist. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2023 Bhatia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
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- 2023
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10. Dissemination of information in event-based surveillance, a case study of Avian Influenza.
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Valentin S, Boudoua B, Sewalk K, Arınık N, Roche M, Lancelot R, and Arsevska E
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- Animals, Disease Outbreaks, Geography, Group Processes, Information Dissemination, Influenza in Birds
- Abstract
Event-Based Surveillance (EBS) tools, such as HealthMap and PADI-web, monitor online news reports and other unofficial sources, with the primary aim to provide timely information to users from health agencies on disease outbreaks occurring worldwide. In this work, we describe how outbreak-related information disseminates from a primary source, via a secondary source, to a definitive aggregator, an EBS tool, during the 2018/19 avian influenza season. We analysed 337 news items from the PADI-web and 115 news articles from HealthMap EBS tools reporting avian influenza outbreaks in birds worldwide between July 2018 and June 2019. We used the sources cited in the news to trace the path of each outbreak. We built a directed network with nodes representing the sources (characterised by type, specialisation, and geographical focus) and edges representing the flow of information. We calculated the degree as a centrality measure to determine the importance of the nodes in information dissemination. We analysed the role of the sources in early detection (detection of an event before its official notification) to the World Organisation for Animal Health (WOAH) and late detection. A total of 23% and 43% of the avian influenza outbreaks detected by the PADI-web and HealthMap, respectively, were shared on time before their notification. For both tools, national and local veterinary authorities were the primary sources of early detection. The early detection component mainly relied on the dissemination of nationally acknowledged events by online news and press agencies, bypassing international reporting to the WAOH. WOAH was the major secondary source for late detection, occupying a central position between national authorities and disseminator sources, such as online news. PADI-web and HealthMap were highly complementary in terms of detected sources, explaining why 90% of the events were detected by only one of the tools. We show that current EBS tools can provide timely outbreak-related information and priority news sources to improve digital disease surveillance., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Valentin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
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- 2023
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11. Longitudinal Participatory Surveillance Highlights Association Between Mask-Wearing and Lower COVID-19 Risk - United States, 2020.
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Swaciak M, Popp Z, Gertz A, Sewalk K, Schultheiss M, Rader B, and Brownstein JS
- Abstract
What Is Already Known About This Topic?: Numerous ecological and laboratory studies suggest face masks are an effective non-pharmaceutical intervention for reducing the spread of coronavirus disease 2019 (COVID-19), but cannot otherwise assess individual-level effects., What Is Added by This Report?: Using a prospective cohort of individuals enrolled in a participatory, syndromic surveillance tool prior to the first case of COVID-19 in the United States, we present a novel longitudinal assessment of the effectiveness of face masks., What Are the Public Health Implications for Public Health Practice?: Our analysis demonstrates an association between self-reported mask-wearing behavior and lower individual risk of syndromic COVID-19-like illness while adjusting for confounders at the individual level. Our results also highlight the dual utility of participatory syndromic surveillance systems as both disease trend monitors and tools that can aid in understanding the effectiveness of personal protective measures., Competing Interests: No conflicts of interest., (Copyright and License information: Editorial Office of CCDCW, Chinese Center for Disease Control and Prevention 2022.)
- Published
- 2022
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12. Spatial modeling of vaccine deserts as barriers to controlling SARS-CoV-2.
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Rader B, Astley CM, Sewalk K, Delamater PL, Cordiano K, Wronski L, Rivera JM, Hallberg K, Pera MF, Cantor J, Whaley CM, Bravata DM, Lee L, Patel A, and Brownstein JS
- Abstract
Background: COVID-19 vaccine distribution is at risk of further propagating the inequities of COVID-19, which in the United States (US) has disproportionately impacted the elderly, people of color, and the medically vulnerable. We sought to measure if the disparities seen in the geographic distribution of other COVID-19 healthcare resources were also present during the initial rollout of the COVID-19 vaccine., Methods: Using a comprehensive COVID-19 vaccine database (VaccineFinder), we built an empirically parameterized spatial model of access to essential resources that incorporated vaccine supply, time-willing-to-travel for vaccination, and previous vaccination across the US. We then identified vaccine deserts-US Census tracts with localized, geographic barriers to vaccine-associated herd immunity. We link our model results with Census data and two high-resolution surveys to understand the distribution and determinates of spatially accessibility to the COVID-19 vaccine., Results: We find that in early 2021, vaccine deserts were home to over 30 million people, >10% of the US population. Vaccine deserts were concentrated in rural locations and communities with a higher percentage of medically vulnerable populations. We also find that in locations of similar urbanicity, early vaccination distribution disadvantaged neighborhoods with more people of color and older aged residents., Conclusion: Given sufficient vaccine supply, data-driven vaccine distribution to vaccine deserts may improve immunization rates and help control COVID-19., (© 2022. The Author(s).)
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- 2022
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13. Healthcare-Seeking Behavior for Respiratory Illness Among Flu Near You Participants in the United States During the 2015-2016 Through 2018-2019 Influenza Seasons.
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Baltrusaitis K, Reed C, Sewalk K, Brownstein JS, Crawley AW, and Biggerstaff M
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- Male, Humans, United States epidemiology, Female, Seasons, Sentinel Surveillance, Patient Acceptance of Health Care, Health Facilities, Influenza, Human epidemiology, Influenza, Human diagnosis
- Abstract
Background: Flu Near You (FNY) is an online participatory syndromic surveillance system that collects health-related information. In this article, we summarized the healthcare-seeking behavior of FNY participants who reported influenza-like illness (ILI) symptoms., Methods: We applied inverse probability weighting to calculate age-adjusted estimates of the percentage of FNY participants in the United States who sought health care for ILI symptoms during the 2015-2016 through 2018-2019 influenza season and compared seasonal trends across different demographic and regional subgroups, including age group, sex, census region, and place of care using adjusted χ 2 tests., Results: The overall age-adjusted percentage of FNY participants who sought healthcare for ILI symptoms varied by season and ranged from 22.8% to 35.6%. Across all seasons, healthcare seeking was highest for the <18 and 65+ years age groups, women had a greater percentage compared with men, and the South census region had the largest percentage while the West census region had the smallest percentage., Conclusions: The percentage of FNY participants who sought healthcare for ILI symptoms varied by season, geographical region, age group, and sex. FNY compliments existing surveillance systems and informs estimates of influenza-associated illness by adding important real-time insights into healthcare-seeking behavior., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America.)
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- 2022
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14. Tracking the 2022 monkeypox outbreak with epidemiological data in real-time.
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Kraemer MUG, Tegally H, Pigott DM, Dasgupta A, Sheldon J, Wilkinson E, Schultheiss M, Han A, Oglia M, Marks S, Kanner J, O'Brien K, Dandamudi S, Rader B, Sewalk K, Bento AI, Scarpino SV, de Oliveira T, Bogoch II, Katz R, and Brownstein JS
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- Disease Outbreaks, Humans, Monkeypox virus genetics, Mpox (monkeypox) epidemiology
- Abstract
Competing Interests: MUGK and JSB report funding from The Rockefeller Foundation and Google.org. TdO received fees from Illumina as a member of the Infectious Disease Testing Advisory Board and received partial travel support to attend the Nobel Symposium of Medicine in May, 2022. IIB received consulting fees from BlueDot and NHL Players' Association. All other authors declare no competing interests.
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- 2022
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15. Use of At-Home COVID-19 Tests - United States, August 23, 2021-March 12, 2022.
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Rader B, Gertz A, Iuliano AD, Gilmer M, Wronski L, Astley CM, Sewalk K, Varrelman TJ, Cohen J, Parikh R, Reese HE, Reed C, and Brownstein JS
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- Adolescent, Adult, Aged, COVID-19 Testing, Cross-Sectional Studies, Humans, SARS-CoV-2, United States epidemiology, COVID-19 diagnosis, COVID-19 epidemiology, COVID-19 prevention & control
- Abstract
COVID-19 testing provides information regarding exposure and transmission risks, guides preventative measures (e.g., if and when to start and end isolation and quarantine), identifies opportunities for appropriate treatments, and helps assess disease prevalence (1). At-home rapid COVID-19 antigen tests (at-home tests) are a convenient and accessible alternative to laboratory-based diagnostic nucleic acid amplification tests (NAATs) for SARS-CoV-2, the virus that causes COVID-19 (2-4). With the emergence of the SARS-CoV-2 B.1.617.2 (Delta) and B.1.1.529 (Omicron) variants in 2021, demand for at-home tests increased
† (5). At-home tests are commonly used for school- or employer-mandated testing and for confirmation of SARS-CoV-2 infection in a COVID-19-like illness or following exposure (6). Mandated COVID-19 reporting requirements omit at-home tests, and there are no standard processes for test takers or manufacturers to share results with appropriate health officials (2). Therefore, with increased COVID-19 at-home test use, laboratory-based reporting systems might increasingly underreport the actual incidence of infection. Data from a cross-sectional, nonprobability-based online survey (August 23, 2021-March 12, 2022) of U.S. adults aged ≥18 years were used to estimate self-reported at-home test use over time, and by demographic characteristics, geography, symptoms/syndromes, and reasons for testing. From the Delta-predominant period (August 23-December 11, 2021) to the Omicron-predominant period (December 19, 2021-March 12, 2022)§ (7), at-home test use among respondents with self-reported COVID-19-like illness¶ more than tripled from 5.7% to 20.1%. The two most commonly reported reasons for testing among persons who used an at-home test were COVID-19 exposure (39.4%) and COVID-19-like symptoms (28.9%). At-home test use differed by race (e.g., self-identified as White [5.9%] versus self-identified as Black [2.8%]), age (adults aged 30-39 years [6.4%] versus adults aged ≥75 years [3.6%]), household income (>$150,000 [9.5%] versus $50,000-$74,999 [4.7%]), education (postgraduate degree [8.4%] versus high school or less [3.5%]), and geography (New England division [9.6%] versus West South Central division [3.7%]). COVID-19 testing, including at-home tests, along with prevention measures, such as quarantine and isolation when warranted, wearing a well-fitted mask when recommended after a positive test or known exposure, and staying up to date with vaccination,** can help reduce the spread of COVID-19. Further, providing reliable and low-cost or free at-home test kits to underserved populations with otherwise limited access to COVID-19 testing could assist with continued prevention efforts., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. Christina M. Astley reports grants from Flu Lab and from the National Institutes of Health and the National Institute of Diabetes and Digestive and Kidney Diseases during conduct of the study. John S. Brownstein, Autumn Gertz, Benjamin Rader, Kara Sewalk, and Tanner J. Varrelman report grants from Flu Lab during conduct of the study. No other potential conflicts of interest were disclosed.- Published
- 2022
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16. Emerging Socioeconomic Disparities in COVID-19 Vaccine Second-Dose Completion Rates in the United States.
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Gertz A, Rader B, Sewalk K, and Brownstein JS
- Abstract
Although COVID-19 vaccination plans acknowledge a need for equity, disparities in two-dose vaccine initiation have been observed in the United States. We aim to assess if disparity patterns are emerging in COVID-19 vaccination completion. We gathered ( n = 843,985) responses between February and November 2021 from a web survey. Individuals self-reported demographics and COVID-19 vaccination status. Dose initiation and completion rates were calculated incorporating survey weights. A multi-variate logistic regression assessed the association between income and completing vaccination, accounting for other demographics. Overall, 57.4% initiated COVID-19 vaccination, with 84.5% completing vaccination. Initiation varied by income, and we observed disparities in completion by occupation, race, age, and insurance. Accounting for demographics, higher incomes are more likely to complete vaccination than lower incomes. We observe disparities in completion across annual income. Differences in COVID-19 vaccination completion may lead to two tiers of protection in the population, with certain sub-groups being better protected from future infection.
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- 2022
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17. Evaluating an app-guided self-test for influenza: lessons learned for improving the feasibility of study designs to evaluate self-tests for respiratory viruses.
- Author
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Zigman Suchsland ML, Rahmatullah I, Lutz B, Lyon V, Huang S, Kline E, Graham C, Cooper S, Su P, Smedinghoff S, Chu HY, Sewalk K, Brownstein JS, and Thompson MJ
- Subjects
- Adult, Cross-Sectional Studies, Data Accuracy, Enzyme-Linked Immunosorbent Assay methods, Feasibility Studies, Female, Humans, Influenza, Human virology, Male, Middle Aged, Sensitivity and Specificity, Influenza A virus immunology, Influenza B virus immunology, Influenza, Human diagnosis, Mobile Applications, Self-Testing
- Abstract
Background: Seasonal influenza leads to significant morbidity and mortality. Rapid self-tests could improve access to influenza testing in community settings. We aimed to evaluate the diagnostic accuracy of a mobile app-guided influenza rapid self-test for adults with influenza like illness (ILI), and identify optimal methods for conducting accuracy studies for home-based assays for influenza and other respiratory viruses., Methods: This cross-sectional study recruited adults who self-reported ILI online. Participants downloaded a mobile app, which guided them through two low nasal swab self-samples. Participants tested the index swab using a lateral flow assay. Test accuracy results were compared to the reference swab tested in a research laboratory for influenza A/B using a molecular assay., Results: Analysis included 739 participants, 80% were 25-64 years of age, 79% female, and 73% white. Influenza positivity was 5.9% based on the laboratory reference test. Of those who started their test, 92% reported a self-test result. The sensitivity and specificity of participants' interpretation of the test result compared to the laboratory reference standard were 14% (95%CI 5-28%) and 90% (95%CI 87-92%), respectively., Conclusions: A mobile app facilitated study procedures to determine the accuracy of a home based test for influenza, however, test sensitivity was low. Recruiting individuals outside clinical settings who self-report ILI symptoms may lead to lower rates of influenza and/or less severe disease. Earlier identification of study subjects within 48 h of symptom onset through inclusion criteria and rapid shipping of tests or pre-positioning tests is needed to allow self-testing earlier in the course of illness, when viral load is higher.
- Published
- 2021
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18. Geographic access to United States SARS-CoV-2 testing sites highlights healthcare disparities and may bias transmission estimates.
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Rader B, Astley CM, Sy KTL, Sewalk K, Hswen Y, Brownstein JS, and Kraemer MUG
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- Female, Humans, Male, COVID-19 Testing, Linear Models, Pandemics prevention & control, Pandemics statistics & numerical data, Racism, Socioeconomic Factors, Time Factors, United States, Clinical Laboratory Techniques methods, COVID-19, Health Services Accessibility statistics & numerical data, Healthcare Disparities economics, Healthcare Disparities ethnology, Travel
- Published
- 2020
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19. Racial and Ethnic Disparities in Patient Experiences in the United States: 4-Year Content Analysis of Twitter.
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Hswen Y, Hawkins JB, Sewalk K, Tuli G, Williams DR, Viswanath K, Subramanian SV, and Brownstein JS
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- Female, Humans, Male, Time Factors, United States, Delivery of Health Care methods, Ethnicity statistics & numerical data, Racial Groups statistics & numerical data, Social Media standards
- Abstract
Background: Racial and ethnic minority groups often face worse patient experiences compared with the general population, which is directly related to poorer health outcomes within these minority populations. Evaluation of patient experience among racial and ethnic minority groups has been difficult due to lack of representation in traditional health care surveys., Objective: This study aims to assess the feasibility of Twitter for identifying racial and ethnic disparities in patient experience across the United States from 2013 to 2016., Methods: In total, 851,973 patient experience tweets with geographic location information from the United States were collected from 2013 to 2016. Patient experience tweets included discussions related to care received in a hospital, urgent care, or any other health institution. Ordinary least squares multiple regression was used to model patient experience sentiment and racial and ethnic groups over the 2013 to 2016 period and in relation to the implementation of the Patient Protection and Affordable Care Act (ACA) in 2014., Results: Racial and ethnic distribution of users on Twitter was highly correlated with population estimates from the United States Census Bureau's 5-year survey from 2016 (r
2 =0.99; P<.001). From 2013 to 2016, the average patient experience sentiment was highest for White patients, followed by Asian/Pacific Islander, Hispanic/Latino, and American Indian/Alaska Native patients. A reduction in negative patient experience sentiment on Twitter for all racial and ethnic groups was seen from 2013 to 2016. Twitter users who identified as Hispanic/Latino showed the greatest improvement in patient experience, with a 1.5 times greater increase (P<.001) than Twitter users who identified as White. Twitter users who identified as Black had the highest increase in patient experience postimplementation of the ACA (2014-2016) compared with preimplementation of the ACA (2013), and this change was 2.2 times (P<.001) greater than Twitter users who identified as White., Conclusions: The ACA mandated the implementation of the measurement of patient experience of care delivery. Considering that quality assessment of care is required, Twitter may offer the ability to monitor patient experiences across diverse racial and ethnic groups and inform the evaluation of health policies like the ACA., (©Yulin Hswen, Jared B Hawkins, Kara Sewalk, Gaurav Tuli, David R Williams, K Viswanath, S V Subramanian, John S Brownstein. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 21.08.2020.)- Published
- 2020
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20. Use of social media to assess the impact of equitable state policies on LGBTQ patient experiences: An exploratory study.
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Hswen Y, Zhang A, Sewalk K, Tuli G, Brownstein JS, and Hawkins JB
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- Humans, Qualitative Research, Surveys and Questionnaires, Health Policy trends, Sexual and Gender Minorities legislation & jurisprudence, Social Media trends
- Abstract
Limited research has evaluated these equitable policies because of the difficulty of capturing LGBTQ patient experience. Previous studies have shown that LGBTQ persons report increased rates of discrimination across a wide variety of healthcare settings which may prevent them from disclosing their LGBTQ status. The goal of this research was to use a social media big dataset to evaluate the impact of equitable policies on patient experiences for LGBTQ persons., Competing Interests: Declaration of competing interest This study was funded by the Robert Wood Johnson Foundation Grant 73495 (to YH, JBH). Additional support was received from the NIH/National Human Genome Research Institute Grant 5U54HG007963-04 (to JSB, JBH). YH reports receiving funding from the Canadian Institutes of Health Research. The funders played no role in the study design; collection, analysis, or interpretation of data; writing of the manuscript; or decision to submit the manuscript for publication., (Copyright © 2020 Elsevier Inc. All rights reserved.)
- Published
- 2020
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21. Epidemiological data from the COVID-19 outbreak, real-time case information.
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Xu B, Gutierrez B, Mekaru S, Sewalk K, Goodwin L, Loskill A, Cohn EL, Hswen Y, Hill SC, Cobo MM, Zarebski AE, Li S, Wu CH, Hulland E, Morgan JD, Wang L, O'Brien K, Scarpino SV, Brownstein JS, Pybus OG, Pigott DM, and Kraemer MUG
- Subjects
- COVID-19, China, Epidemics, Geographic Mapping, Geography, Humans, Pandemics, Public Health, SARS-CoV-2, Betacoronavirus, Coronavirus Infections epidemiology, Coronavirus Infections virology, Pneumonia, Viral epidemiology, Pneumonia, Viral virology
- Abstract
Cases of a novel coronavirus were first reported in Wuhan, Hubei province, China, in December 2019 and have since spread across the world. Epidemiological studies have indicated human-to-human transmission in China and elsewhere. To aid the analysis and tracking of the COVID-19 epidemic we collected and curated individual-level data from national, provincial, and municipal health reports, as well as additional information from online reports. All data are geo-coded and, where available, include symptoms, key dates (date of onset, admission, and confirmation), and travel history. The generation of detailed, real-time, and robust data for emerging disease outbreaks is important and can help to generate robust evidence that will support and inform public health decision making.
- Published
- 2020
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