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Article ; Online: Predicting COVID-19 case status from self-reported symptoms and behaviors using data from a massive online survey

Srivastava, Mashrin / Reinhart, Alex / Mejia, Robin

medRxiv

Abstract: With the varying availability of RT-PCR testing for COVID-19 across time and location, there is a need for alternative methods of predicting COVID-19 case status. In this study, multiple machine learning (ML) models were trained and assessed for their ... ...

Abstract	With the varying availability of RT-PCR testing for COVID-19 across time and location, there is a need for alternative methods of predicting COVID-19 case status. In this study, multiple machine learning (ML) models were trained and assessed for their ability to accurately predict the COVID-19 case status using US COVID-19 Trends and Impact Survey (CTIS) data. The CTIS includes information on testing, symptoms, demographics, behaviors, and vaccination status. The best performing model was XGBoost, which achieved an F1 score of ≈ 94% in predicting whether an individual was COVID-19 positive or negative. This is a notable improvement on existing models for predicting COVID-19 case status and demonstrates the potential for ML methods to provide policy-relevant estimates.
Keywords	covid19
Language	English
Publishing date	2023-02-07
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2023.02.03.23285405
Database	COVID19

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Article ; Online: Bias-Adjusted Predictions of County-Level Vaccination Coverage from the COVID-19 Trends and Impact Survey.

Reitsma, Marissa B / Rose, Sherri / Reinhart, Alex / Goldhaber-Fiebert, Jeremy D / Salomon, Joshua A

Medical decision making : an international journal of the Society for Medical Decision Making

2023 Volume 44, Issue 2, Page(s) 175–188

Abstract: Background: The potential for selection bias in nonrepresentative, large-scale, low-cost survey data can limit their utility for population health measurement and public health decision making. We developed an approach to bias adjust county-level COVID- ... ...

Abstract	Background: The potential for selection bias in nonrepresentative, large-scale, low-cost survey data can limit their utility for population health measurement and public health decision making. We developed an approach to bias adjust county-level COVID-19 vaccination coverage predictions from the large-scale US COVID-19 Trends and Impact Survey. Design: We developed a multistep regression framework to adjust for selection bias in predicted county-level vaccination coverage plateaus. Our approach included poststratification to the American Community Survey, adjusting for differences in observed covariates, and secondary normalization to an unbiased reference indicator. As a case study, we prospectively applied this framework to predict county-level long-run vaccination coverage among children ages 5 to 11 y. We evaluated our approach against an interim observed measure of 3-mo coverage for children ages 5 to 11 y and used long-term coverage estimates to monitor equity in the pace of vaccination scale up. Results: Our predictions suggested a low ceiling on long-term national vaccination coverage (46%), detected substantial geographic heterogeneity (ranging from 11% to 91% across counties in the United States), and highlighted widespread disparities in the pace of scale up in the 3 mo following Emergency Use Authorization of COVID-19 vaccination for 5- to 11-y-olds. Limitations: We relied on historical relationships between vaccination hesitancy and observed coverage, which may not capture rapid changes in the COVID-19 policy and epidemiologic landscape. Conclusions: Our analysis demonstrates an approach to leverage differing strengths of multiple sources of information to produce estimates on the time scale and geographic scale necessary for proactive decision making. Implications: Designing integrated health measurement systems that combine sources with different advantages across the spectrum of timeliness, spatial resolution, and representativeness can maximize the benefits of data collection relative to costs. Highlights: The COVID-19 pandemic catalyzed massive survey data collection efforts that prioritized timeliness and sample size over population representativeness.The potential for selection bias in these large-scale, low-cost, nonrepresentative data has led to questions about their utility for population health measurement.We developed a multistep regression framework to bias adjust county-level vaccination coverage predictions from the largest public health survey conducted in the United States to date: the US COVID-19 Trends and Impact Survey.Our study demonstrates the value of leveraging differing strengths of multiple data sources to generate estimates on the time scale and geographic scale necessary for proactive public health decision making.
MeSH term(s)	Child ; Humans ; United States/epidemiology ; Vaccination Coverage ; COVID-19 Vaccines/therapeutic use ; Pandemics ; COVID-19/epidemiology ; COVID-19/prevention & control ; Surveys and Questionnaires ; Vaccination
Chemical Substances	COVID-19 Vaccines
Language	English
Publishing date	2023-12-30
Publishing country	United States
Document type	Journal Article
ZDB-ID	604497-9
ISSN	1552-681X ; 0272-989X
ISSN (online)	1552-681X
ISSN	0272-989X
DOI	10.1177/0272989X231218024
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book: Statistics done wrong

Reinhart, Alex

the woefully complete guide

2015

Abstract: Discusses how to avoid the most common statistical errors in modern research, and perform more accurate statistical analyses. ...

Author's details	by Alex Reinhart
Abstract	Discusses how to avoid the most common statistical errors in modern research, and perform more accurate statistical analyses.
Keywords	Missing observations (Statistics) ; Statistics/Methodology
Language	English
Size	XVIII, 152 S., Ill., graph. Darst., 23 cm
Publisher	No Starch Press
Publishing place	San Francisco, CA
Document type	Book
Note	Literaturverz. S. [131] - 146
ISBN	1593276206 ; 9781593276201
Database	Federal Institute for Risk Assessment

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Book: Statistics done wrong

Reinhart, Alex

the woefully complete guide

2015

Abstract: Discusses how to avoid the most common statistical errors in modern research, and perform more accurate statistical analyses. ...

Author's details	by Alex Reinhart
Abstract	Discusses how to avoid the most common statistical errors in modern research, and perform more accurate statistical analyses.
Keywords	Missing observations (Statistics) ; Statistics/Methodology
Language	English
Size	XVIII, 152 S., Ill., graph. Darst., 23 cm
Publisher	No Starch Press
Publishing place	San Francisco, Calif
Document type	Book
Note	Literaturverz. S. 131 - 146
ISBN	1593276206 ; 9781593276201
Database	Former special subject collection: coastal and deep sea fishing

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Book: Statistics done wrong

Reinhart, Alex

the woefully complete guide

2015

Abstract: Discusses how to avoid the most common statistical errors in modern research, and perform more accurate statistical analyses"-- ...

Author's details	by Alex Reinhart
Abstract	"Discusses how to avoid the most common statistical errors in modern research, and perform more accurate statistical analyses"--
Keywords	Missing observations (Statistics) ; Statistics/Methodology
Language	English
Size	XVIII, 152 S, Ill, 23 cm
Publisher	No Starch Press
Publishing place	San Francisco
Document type	Book
Note	Includes bibliographical references (pages 131-146) and index
ISBN	1593276206 ; 9781593276201
Database	Library catalogue of the German National Library of Science and Technology (TIB), Hannover

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Article: COVID-19 vaccine hesitancy January-May 2021 among 18-64 year old US adults by employment and occupation.

King, Wendy C / Rubinstein, Max / Reinhart, Alex / Mejia, Robin

Preventive medicine reports

2021 Volume 24, Page(s) 101569

Abstract: COVID-19 vaccine hesitancy threatens pandemic control efforts. We evaluated vaccine hesitancy in the US by employment status and occupation category during the COVID-19 vaccine rollout. US adults 18-64 years completed an online COVID-19 survey 3,179,174 ... ...

Abstract	COVID-19 vaccine hesitancy threatens pandemic control efforts. We evaluated vaccine hesitancy in the US by employment status and occupation category during the COVID-19 vaccine rollout. US adults 18-64 years completed an online COVID-19 survey 3,179,174 times from January 6-May 19, 2021. Data was aggregated by month. Survey weights matched the sample to the US population age, gender, and state profile. Weighted percentages and 95% confidence intervals (CI) were calculated. Changes in vaccine hesitancy from January-May varied widely by employment status (e.g., -7.8% [95%CI, -8.2 - -7.5] among those working outside the home, a 26.6% decrease; -13.3% [95%CI, -13.7 - -13.0] among those not working for pay, a 44.9% decrease), and occupation category (e.g., -15.9% [95%CI, -17.7 - -14.2] in production, a 39.3% decrease; -1.4% [95%CI, -3.8 - -1.0] in construction/extraction, a 3.0% decrease). April 20-May 19, 2021, vaccine hesitancy ranged from 7.3% (95%CI, 6.7 - 7.8) in computer/mathematical professions to 45.2% (95%CI, 43.2-46.8) in construction/extraction. Hesitancy was 9.0% (95%CI, 8.6-9.3) among educators and 14.5% (95%CI, 14.0-15.0) among healthcare practitioners/technicians. While the prevalence of reasons for hesitancy differed by occupation, over half of employed hesitant participants reported concern about side effects (51.7%) and not trusting COVID-19 vaccines (51.3%), whereas only 15.0% didn't like vaccines in general. Over a third didn't believe they needed the vaccine, didn't trust the government, and/or were waiting to see if it was safe. In this massive national survey of adults 18-64 years, vaccine hesitancy varied widely by occupation. Reasons for hesitancy indicate messaging about safety and addressing trust are paramount.
Language	English
Publishing date	2021-09-27
Publishing country	United States
Document type	Journal Article
ZDB-ID	2785569-7
ISSN	2211-3355
ISSN	2211-3355
DOI	10.1016/j.pmedr.2021.101569
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Time trends, factors associated with, and reasons for COVID-19 vaccine hesitancy: A massive online survey of US adults from January-May 2021.

King, Wendy C / Rubinstein, Max / Reinhart, Alex / Mejia, Robin

PloS one

2021 Volume 16, Issue 12, Page(s) e0260731

Abstract: Importance: COVID-19 vaccine hesitancy has become a leading barrier to increasing the US vaccination rate.: Objective: To evaluate time trends in COVID-19 vaccine intent during the US vaccine rollout, and identify key factors related to and self- ... ...

Abstract	Importance: COVID-19 vaccine hesitancy has become a leading barrier to increasing the US vaccination rate. Objective: To evaluate time trends in COVID-19 vaccine intent during the US vaccine rollout, and identify key factors related to and self-reported reasons for COVID-19 vaccine hesitancy in May 2021. Design, participants and setting: A COVID-19 survey was offered to US adult Facebook users in several languages yielding 5,088,772 qualifying responses from January 6 to May 31, 2021. Data was aggregated by month. Survey weights matched the sample to the age, gender, and state profile of the US population. Exposure: Demographics, geographic factors, political/COVID-19 environment, health status, beliefs, and behaviors. Main outcome measures: "If a vaccine to prevent COVID-19 were offered to you today, would you choose to get vaccinated." Hesitant was defined as responding probably or definitely would not choose to get vaccinated (versus probably or definitely would, or already vaccinated). Results: COVID-19 vaccine hesitancy decreased by one-third from 25.4% (95%CI, 25.3, 25.5) in January to 16.6% (95% CI, 16.4, 16.7) in May, with relatively large decreases among participants with Black, Pacific Islander or Hispanic race/ethnicity and ≤high school education. Independent risk factors for vaccine hesitancy in May (N = 525,644) included younger age, non-Asian race, < 4 year college degree, living in a more rural county, living in a county with higher Trump vote share in the 2020 election, lack of worry about COVID-19, working outside the home, never intentionally avoiding contact with others, and no past-year flu vaccine. Differences in hesitancy by race/ethnicity varied by age (e.g., Black adults more hesitant than White adults <35 years old, but less hesitant among adults ≥45 years old). Differences in hesitancy by age varied by race/ethnicity. Almost half of vaccine hesitant respondents reported fear of side effects (49.2% [95%CI, 48.7, 49.7]) and not trusting the COVID-19 vaccine (48.4% [95%CI, 48.0, 48.9]); over one-third reported not trusting the government, not needing the vaccine, and waiting to see if safe. Reasons differed by degree of vaccine intent and by race/ethnicity. Conclusion: COVID-19 vaccine hesitancy varied by demographics, geography, beliefs, and behaviors, indicating a need for a range of messaging and policy options to target high-hesitancy groups.
MeSH term(s)	Adult ; Aged ; COVID-19/psychology ; COVID-19 Vaccines ; Ethnicity/psychology ; Female ; Humans ; Male ; Middle Aged ; SARS-CoV-2/immunology ; SARS-CoV-2/pathogenicity ; Surveys and Questionnaires ; Time Factors ; United States ; Vaccination/trends ; Vaccination Hesitancy/psychology ; Vaccination Hesitancy/trends
Chemical Substances	COVID-19 Vaccines
Language	English
Publishing date	2021-12-21
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S.
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0260731
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: COVID-19 vaccine hesitancy January-May 2021 among 18–64 year old US adults by employment and occupation

Wendy C. King / Max Rubinstein / Alex Reinhart / Robin Mejia

Preventive Medicine Reports, Vol 24, Iss , Pp 101569- (2021)

2021

Abstract: COVID-19 vaccine hesitancy threatens pandemic control efforts. We evaluated vaccine hesitancy in the US by employment status and occupation category during the COVID-19 vaccine rollout. US adults 18–64 years completed an online COVID-19 survey 3,179,174 ... ...

Abstract	COVID-19 vaccine hesitancy threatens pandemic control efforts. We evaluated vaccine hesitancy in the US by employment status and occupation category during the COVID-19 vaccine rollout. US adults 18–64 years completed an online COVID-19 survey 3,179,174 times from January 6-May 19, 2021. Data was aggregated by month. Survey weights matched the sample to the US population age, gender, and state profile. Weighted percentages and 95% confidence intervals (CI) were calculated. Changes in vaccine hesitancy from January-May varied widely by employment status (e.g., −7.8% [95%CI, −8.2 – −7.5] among those working outside the home, a 26.6% decrease; −13.3% [95%CI, −13.7 – −13.0] among those not working for pay, a 44.9% decrease), and occupation category (e.g., −15.9% [95%CI, −17.7 – −14.2] in production, a 39.3% decrease; −1.4% [95%CI, −3.8 – −1.0] in construction/extraction, a 3.0% decrease). April 20-May 19, 2021, vaccine hesitancy ranged from 7.3% (95%CI, 6.7 – 7.8) in computer/mathematical professions to 45.2% (95%CI, 43.2–46.8) in construction/extraction. Hesitancy was 9.0% (95%CI, 8.6–9.3) among educators and 14.5% (95%CI, 14.0–15.0) among healthcare practitioners/technicians. While the prevalence of reasons for hesitancy differed by occupation, over half of employed hesitant participants reported concern about side effects (51.7%) and not trusting COVID-19 vaccines (51.3%), whereas only 15.0% didn’t like vaccines in general. Over a third didn’t believe they needed the vaccine, didn’t trust the government, and/or were waiting to see if it was safe. In this massive national survey of adults 18–64 years, vaccine hesitancy varied widely by occupation. Reasons for hesitancy indicate messaging about safety and addressing trust are paramount.
Keywords	SARS-CoV-2 ; United States ; Workforce ; Profession ; Vaccination ; Medicine ; R
Language	English
Publishing date	2021-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Time trends, factors associated with, and reasons for COVID-19 vaccine hesitancy

Wendy C King / Max Rubinstein / Alex Reinhart / Robin Mejia

PLoS ONE, Vol 16, Iss 12, p e

A massive online survey of US adults from January-May 2021.

2021 Volume 0260731

Abstract: Importance COVID-19 vaccine hesitancy has become a leading barrier to increasing the US vaccination rate. Objective To evaluate time trends in COVID-19 vaccine intent during the US vaccine rollout, and identify key factors related to and self-reported ... ...

Abstract	Importance COVID-19 vaccine hesitancy has become a leading barrier to increasing the US vaccination rate. Objective To evaluate time trends in COVID-19 vaccine intent during the US vaccine rollout, and identify key factors related to and self-reported reasons for COVID-19 vaccine hesitancy in May 2021. Design, participants and setting A COVID-19 survey was offered to US adult Facebook users in several languages yielding 5,088,772 qualifying responses from January 6 to May 31, 2021. Data was aggregated by month. Survey weights matched the sample to the age, gender, and state profile of the US population. Exposure Demographics, geographic factors, political/COVID-19 environment, health status, beliefs, and behaviors. Main outcome measures "If a vaccine to prevent COVID-19 were offered to you today, would you choose to get vaccinated." Hesitant was defined as responding probably or definitely would not choose to get vaccinated (versus probably or definitely would, or already vaccinated). Results COVID-19 vaccine hesitancy decreased by one-third from 25.4% (95%CI, 25.3, 25.5) in January to 16.6% (95% CI, 16.4, 16.7) in May, with relatively large decreases among participants with Black, Pacific Islander or Hispanic race/ethnicity and ≤high school education. Independent risk factors for vaccine hesitancy in May (N = 525,644) included younger age, non-Asian race, < 4 year college degree, living in a more rural county, living in a county with higher Trump vote share in the 2020 election, lack of worry about COVID-19, working outside the home, never intentionally avoiding contact with others, and no past-year flu vaccine. Differences in hesitancy by race/ethnicity varied by age (e.g., Black adults more hesitant than White adults <35 years old, but less hesitant among adults ≥45 years old). Differences in hesitancy by age varied by race/ethnicity. Almost half of vaccine hesitant respondents reported fear of side effects (49.2% [95%CI, 48.7, 49.7]) and not trusting the COVID-19 vaccine (48.4% [95%CI, 48.0, 48.9]); over one-third reported not trusting the government, not needing the vaccine, and waiting to see if safe. Reasons differed by degree of vaccine intent and by race/ethnicity. Conclusion COVID-19 vaccine hesitancy varied by demographics, geography, beliefs, and behaviors, indicating a need for a range of messaging and policy options to target high-hesitancy groups.
Keywords	Medicine ; R ; Science ; Q
Subject code	950
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Dynamic spinal reflex adaptation during locomotor adaptation.

Refy, Omar / Blanchard, Belle / Miller-Peterson, Abigail / Dalrymple, Ashley N / Bedoy, Ernesto H / Zaripova, Amelia / Motaghedi, Nadim / Mo, Owen / Panthangi, Shalini / Reinhart, Alex / Torres-Oviedo, Gelsy / Geyer, Hartmut / Weber, Douglas J

Journal of neurophysiology

2023 Volume 130, Issue 4, Page(s) 1008–1014

Abstract: The dynamics and interaction of spinal and supraspinal centers during locomotor adaptation remain vaguely understood. In this work, we use Hoffmann reflex measurements to investigate changes in spinal reflex gains during split-belt locomotor adaptation. ... ...

Abstract	The dynamics and interaction of spinal and supraspinal centers during locomotor adaptation remain vaguely understood. In this work, we use Hoffmann reflex measurements to investigate changes in spinal reflex gains during split-belt locomotor adaptation. We show that spinal reflex gains are dynamically modulated during split-belt locomotor adaptation. During first exposure to split-belt transitions, modulation occurs mostly on the leg ipsilateral to the speed change and constitutes rapid suppression or facilitation of the reflex gains, followed by slow recovery to baseline. Over repeated exposure, the modulation pattern washes out. We further show that reflex gain modulation strongly correlates with correction of leg asymmetry, and cannot be explained by speed modulation solely. We argue that reflex modulation is likely of supraspinal origins and constitutes an integral part of the neural substrate underlying split-belt locomotor adaptation.
MeSH term(s)	Adult ; Humans ; Electromyography ; Gait ; Reflex ; Spine ; Adaptation, Physiological ; Walking ; Exercise Test
Language	English
Publishing date	2023-09-13
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	80161-6
ISSN	1522-1598 ; 0022-3077
ISSN (online)	1522-1598
ISSN	0022-3077
DOI	10.1152/jn.00248.2023
Database	MEDical Literature Analysis and Retrieval System OnLINE

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