An AI-Enhanced Electronic Health Record Could Boost Primary Care Productivity.

This Viewpoint discusses ways that artificial intelligence (AI) may improve the productivity of primary care physicians with easier and more accurate use of AI-enhanced electronic health records.

Incentivizing COVID-19 vaccination among racial/ethnic minority adults in the United States: $209 per dose could convince the hesitant.

BACKGROUND: More than two years into the coronavirus disease (COVID-19) pandemic, it remains unclear whether financial incentives can reduce vaccine hesitancy and improve uptake among key unvaccinated populations. This study estimated the willingness of racial/ethnic minority adults in the United States to accept financial incentives for COVID-19 vaccination and the minimum amount needed to vaccinate a sufficiently high percentage of this population. METHODS: From August through September 2021, we conducted an online survey of 367 Black/African American and Hispanic patients, age ≥ 18 years, from 8 community health centers in Rhode Island. Contingent valuation questions assessed respondents' willingness-to-accept (WTA) incentives for COVID-19 vaccination using random-starting-points and iterative incentive offers of $5 to $50 per dose. Ordered logistic regression models examined associations between respondent characteristics and WTA. Predictive probabilities were modeled using both within-survey range and out-of-survey range incentive offer amounts and compared against vaccination thresholds needed to reach herd immunity. RESULTS: Less than 30% of unvaccinated survey respondents were WTA an incentive of $50/dose for vaccination. Models using out-of-survey incentive offer amounts greater than $50 suggested that 85% of respondents would agree $140/dose (95% CI: $43-$236) could convince other people to accept vaccination, while $209/dose (95% CI: -$91-$509) would be needed for 85% of respondents to accept vaccination themselves. CONCLUSIONS: Findings from this analysis may inform the design of incentive schemes aiming to reduce racial/ethnic disparities in vaccine and booster uptake, which will continue to be important as new variants of SARS-CoV-2 emerge.

Concentric regulatory zones failed to halt surging COVID-19: Brooklyn 2020.

Methods: We relied on reports of confirmed case incidence and test positivity, along with data on the movements of devices with location-tracking software, to evaluate a novel scheme of three concentric regulatory zones introduced by then New York Governor Cuomo to address an outbreak of COVID-19 in South Brooklyn in the fall of 2020. The regulatory scheme imposed differential controls on access to eating places, schools, houses of worship, large gatherings and other businesses within the three zones, but without restrictions on mobility. Results: Within the central red zone, COVID-19 incidence temporarily declined from 131.2 per 100,000 population during the week ending October 3 to 62.5 per 100,000 by the week ending October 31, but then rebounded to 153.6 per 100,000 by the week ending November 28. Within the intermediate orange and peripheral yellow zones combined, incidence steadily rose from 28.8 per 100,000 during the week ending October 3 to 109.9 per 100,000 by the week ending November 28. Data on device visits to pairs of eating establishments straddling the red-orange boundary confirmed compliance with access controls. More general analysis of device movements showed stable patterns of movement between and beyond zones unaffected by the Governor's orders. A geospatial regression model of COVID-19 incidence in relation to device movements across zip code tabulation areas identified a cluster of five high-movement ZCTAs with estimated reproduction number 1.91 (95% confidence interval, 1.27-2.55). Discussion: In the highly populous area of South Brooklyn, controls on access alone, without restrictions on movement, were inadequate to halt an advancing COVID-19 outbreak.

Mobility was a significant determinant of reported COVID-19 incidence during the Omicron Surge in the most populous U.S. Counties.

BACKGROUND: Significant immune escape by the Omicron variant, along with the emergence of widespread worry fatigue, have called into question the robustness of the previously observed relation between population mobility and COVID-19 incidence. METHODS: We employed principal component analysis to construct a one-dimensional summary indicator of six Google mobility categories. We related this mobility indicator to case incidence among 111 of the most populous U.S. counties during the Omicron surge from December 2021 through February 2022. RESULTS: Reported COVID-19 incidence peaked earlier and declined more rapidly among those counties exhibiting more extensive decline in mobility between December 20 and January 3. Based upon a fixed-effects, longitudinal cohort model, we estimated that every 1% decline in mobility between December 20 and January 3 was associated with a 0.63% decline in peak incidence during the week ending January 17 (95% confidence interval, 0.40-0.86%). Based upon a cross-sectional analysis including mean household size and vaccination participation as covariates, we estimated that the same 1% decline in mobility was associated with a 0.36% decline in cumulative reported COVID-19 incidence from January 10 through February 28 (95% CI, 0.18-0.54%). CONCLUSION: Omicron did not simply sweep through the U.S. population until it ran out of susceptible individuals to infect. To the contrary, a significant fraction managed to avoid infection by engaging in risk-mitigating behaviors. More broadly, the behavioral response to perceived risk should be viewed as an intrinsic component of the natural course of epidemics in humans.

Application of Path Analysis and Structural Equation Modeling in Nutrition and Dietetics.

This is one of a series of monographs on research design and analysis. The purpose of this article is to describe a set of statistical procedures or techniques used to develop and test structural models that characterize the relationships and interrelationships between a group of concepts and variables. These procedures include multiple regression, exploratory and confirmatory factor analysis, path analysis, and structural equation modeling. The article describes the purpose of each of these procedures and how they relate to and build on one another. It also covers the different types of variables examined, including the distinction between endogenous, exogenous, and mediating variables, along with the distinction between measured and unmeasured (or latent) variables. Each procedure results in a set of statistical estimates, and the article presents the interpretation of these estimates, including regression coefficients (standardized and unstandardized), path coefficients, factor loadings, and coefficients of determination (or R2 values). The article presents examples of how each procedure has been used in practice, along with additional resources for readers who wish to learn more.

Timely epidemic monitoring in the presence of reporting delays: anticipating the COVID-19 surge in New York City, September 2020.

BACKGROUND: During a fast-moving epidemic, timely monitoring of case counts and other key indicators of disease spread is critical to an effective public policy response. METHODS: We describe a nonparametric statistical method, originally applied to the reporting of AIDS cases in the 1980s, to estimate the distribution of reporting delays of confirmed COVID-19 cases in New York City during the late summer and early fall of 2020. RESULTS: During August 15-September 26, the estimated mean delay in reporting was 3.3 days, with 87% of cases reported by 5 days from diagnosis. Relying upon the estimated reporting-delay distribution, we projected COVID-19 incidence during the most recent 3 weeks as if each case had instead been reported on the same day that the underlying diagnostic test had been performed. Applying our delay-corrected estimates to case counts reported as of September 26, we projected a surge in new diagnoses that had already occurred but had yet to be reported. Our projections were consistent with counts of confirmed cases subsequently reported by November 7. CONCLUSION: The projected estimate of recently diagnosed cases could have had an impact on timely policy decisions to tighten social distancing measures. While the recent advent of widespread rapid antigen testing has changed the diagnostic testing landscape considerably, delays in public reporting of SARS-CoV-2 case counts remain an important barrier to effective public health policy.

The repeated setbacks of HIV vaccine development laid the groundwork for SARS-CoV-2 vaccines.

The decades-long effort to produce a workable HIV vaccine has hardly been a waste of public and private resources. To the contrary, the scientific know-how acquired along the way has served as the critical foundation for the development of vaccines against the novel, pandemic SARS-CoV-2 virus. We retell the real-world story of HIV vaccine research - with all its false leads and missteps - in a way that sheds light on the current state of the art of antiviral vaccines. We find that HIV-related R&D had more than a general spillover effect. In fact, the repeated failures of phase 2 and 3 clinical trials of HIV vaccine candidates have served as a critical stimulus to the development of successful vaccine technologies today. We rebut the counterargument that HIV vaccine development has been no more than a blind alley, and that recently developed vaccines against COVID-19 are really descendants of successful vaccines against Ebola, MERS, and SARS. These successful vaccines likewise owe much to the vicissitudes of HIV vaccine development. We then discuss how the failures of HIV vaccine development have taught us how adapt SARS-CoV-2 vaccines to immune escape from emerging variants. Finally, we inquire whether recent advances in the development of vaccines against SARS-CoV-2 might in turn further the development of an HIV vaccine - what we describe as a reverse spillover effect.

COVID-19 Incidence and hospitalization during the delta surge were inversely related to vaccination coverage among the most populous U.S. Counties.

Objective: We tested whether COVID-19 incidence and hospitalization rates during the Delta surge were inversely related to vaccination coverage among the 112 most populous counties in the United States, comprising 44 percent of the country's total population. Methods: We measured vaccination coverage as the percent of the county population fully vaccinated as of July 15, 2021. We measured COVID-19 incidence as the number of confirmed cases per 100,000 population during the 14-day period ending August 12, 2021 and hospitalization rates as the number of confirmed COVID-19 admissions per 100,000 population during the same 14-day period. Results: In log-linear regression models, a 10-percentage-point increase in vaccination coverage was associated with a 28.3% decrease in COVID-19 incidence (95% confidence interval, 16.8 - 39.7%), a 44.9 percent decrease in the rate of COVID-19 hospitalization (95% CI, 28.8 - 61.0%), and a 16.6% decrease in COVID-19 hospitalizations per 100 cases (95% CI, 8.4 - 24.8%). Inclusion of demographic covariables, as well as county-specific diabetes prevalence, did not weaken the observed inverse relationship with vaccination coverage. A significant inverse relationship between vaccination coverage and COVID-19 deaths per 100,000 during August 20 - September 16 was also observed. The cumulative incidence of COVID-19 through June 30, 2021, a potential indicator of acquired immunity due to past infection, had no significant relation to subsequent case incidence or hospitalization rates in August. Conclusion: Higher vaccination coverage was associated not only with significantly lower COVID-19 incidence during the Delta surge, but also significantly less severe cases of the disease. Public Interest Summary: We tested whether COVID-19 incidence and hospitalization rates during the Delta variant-related surge were inversely related to vaccination coverage among the 112 most populous counties in the United States, together comprising 44 percent of the country's total population. A 10-percentage-point increase in vaccination coverage was associated with a 28.3% decrease in COVID-19 incidence, a 44.9 percent decrease in the rate of COVID-19 hospitalization, and a 16.6% decrease in COVID-19 hospitalizations per 100 cases. Inclusion of demographic covariables, as well as county-specific diabetes prevalence, did not weaken the observed inverse relationship with vaccination coverage. A significant inverse relationship between vaccination coverage and COVID-19 deaths per 100,000 during August 20 - September 16 was also observed. Higher vaccination coverage was associated not only with significantly lower COVID-19 incidence during the Delta surge, but also significantly less severe cases of the disease.

Pointers and Pitfalls in Interpreting Nutrition and Dietetics Research: The Importance of Statistical and Clinical Significance.

This monograph focuses on understanding statistical and clinical significance and is one in a research and statistics series published by the statistical team of the Journal of the Academy of Nutrition and Dietetics. The content covers the research questions, definition of clinical significance, hypothesis testing, P values, effect sizes, sample sizes, CIs, power analyses, minimal clinically important differences, and validity. This monograph concludes with a summary of the importance of clinical and statistical results for credentialed nutrition and dietetics practitioners to consider when assessing statistical and clinical significance. The assessment will help readers make subjective clinical judgments in the application of research findings based on their experience.

Effect of an abrupt change in sexual and reproductive health policy on teen birth rates in Ecuador, 2008-2017.

Several countries have implemented "family-centered" abstinence-only policies for teenagers, as opposed to encouraging utilization and expansion of reproductive health services and education. Little is known, however, about the effects of these more restrictive policies on adolescent birth rates at the national level or their differential effects by race and ethnicity. The extant literature is even scarcer in low- and middle-income countries. We analyze an unexpected policy change in Ecuador that abruptly reversed course and restricted reproductive health services for teenage women in 2014. We use a canton- and time-fixed effects difference-in-differences analysis of Ecuador's 221 cantons with time-varying controls to analyze the impact of the abrupt policy change on the difference of teen (15-19 years) minus young adult (20-24 years) birth rates. In a difference-in-difference-in-differences analysis, the policy change increases birth rates by 8.5 births per 1000 women in cantons with higher indigenous concentration. Results are robust to changes in the comparison population (young adults vs. women in their late 20 s or in their early 30 s), pre-intervention control periods, population weighting, serial correlation, logarithmic model specification, adjustments for intervention year, definition of indigenous concentration, and potential delays in policy implementation.

Critical Role of the Subways in the Initial Spread of SARS-CoV-2 in New York City.

We studied the possible role of the subways in the spread of SARS-CoV-2 in New York City during late February and March 2020. Data on cases and hospitalizations, along with phylogenetic analyses of viral isolates, demonstrate rapid community transmission throughout all five boroughs within days. The near collapse of subway ridership during the second week of March was followed within 1-2 weeks by the flattening of COVID-19 incidence curve. We observed persistently high entry into stations located along the subway line serving a principal hotspot of infection in Queens. We used smartphone tracking data to estimate the volume of subway visits originating from each zip code tabulation area (ZCTA). Across ZCTAs, the estimated volume of subway visits on March 16 was strongly predictive of subsequent COVID-19 incidence during April 1-8. In a spatial analysis, we distinguished between the conventional notion of geographic contiguity and a novel notion of contiguity along subway lines. We found that the March 16 subway-visit volume in subway-contiguous ZCTAs had an increasing effect on COVID-19 incidence during April 1-8 as we enlarged the radius of influence up to 5 connected subway stops. By contrast, the March 31 cumulative incidence of COVID-19 in geographically-contiguous ZCTAs had an increasing effect on subsequent COVID-19 incidence as we expanded the radius up to three connected ZCTAs. The combined evidence points to the initial citywide dissemination of SARS-CoV-2 via a subway-based network, followed by percolation of new infections within local hotspots.

Data from the COVID-19 epidemic in Florida suggest that younger cohorts have been transmitting their infections to less socially mobile older adults.

We analyzed the daily incidence of newly reported COVID-19 cases among adults aged 20-39 years, 40-59 years, and 60 or more years in the sixteen most populous counties of the state of Florida from March 1 through June 27, 2020. In all 16 counties, an increase in reported COVID-19 case incidence was observed in all three age groups soon after the governor-ordered Full Phase 1 reopening went into effect. Trends in social mobility, but not trends in testing, track case incidence. Data on hospitalization do not support the hypothesis that the observed increase in case incidence was merely the result of liberalization of testing criteria. Parameter estimates from a parsimonious two-group heterogeneous SIR model strongly support the hypothesis that younger persons, having first acquired their infections through increasing social contact with their peers, then transmitted their infections to older, less socially mobile individuals. Without such cross-infection, an isolated epidemic among older people in Florida would be unsustainable.

Correction to: Data from the COVID-19 epidemic in Florida suggest that younger cohorts have been transmitting their infections to less socially mobile older adults.

[This corrects the article DOI: 10.1007/s11150-020-09496-w.].

COVID-19, bar crowding, and the Wisconsin Supreme Court: A non-linear tale of two counties.

The Wisconsin Supreme Court's nullification of a carefully crafted, statewide regulatory scheme led to the substitution of a motley collection of asynchronous, uncoordinated local reopening plans that ultimately facilitated a resurgence of COVID-19. The distinct paths of epidemic containment and subsequent resurgence in Wisconsin's two most populous counties, Milwaukee and Dane, can be directly mapped into their respective volumes of bar traffic. A seemingly small relaxation of social distancing rules can result in a relatively large increase in the incidence of new infections. This study relies exclusively on publicly available, aggregate health data that contain no individual identifiers. The author has no competing interests and no funding sources to declare. This article represents to the sole opinion of its author and does not necessarily represent the opinions of the Massachusetts Institute of Technology, the National Bureau of Economic Research, Eisner Health, or any other organization.

The Bayesian Approach to Decision Making and Analysis in Nutrition Research and Practice.

This is part of a series of monographs on research design and analysis. The purpose of this article is to describe the purposes of and approach to conducting Bayesian decision making and analysis. Bayesian decision making involves basing decisions on the probability of a successful outcome, where this probability is informed by both prior information and new evidence the decision maker obtains. The statistical analysis that underlies the calculation of these probabilities is Bayesian analysis. In recent years, the Bayesian approach has been applied more commonly in both nutrition research and clinical decision making, and registered dietitian nutritionists would benefit from gaining a deeper understanding of this approach. This article provides a background of Bayesian decision making and analysis, and then presents applications of the approach in two different areas-medical diagnoses and nutrition policy research. It concludes with a description of how Bayesian decision making may be used in everyday life to allow each of us to appropriately weigh established beliefs and prior knowledge with new data and information in order to make well-informed and wise decisions.

Impact of plain packaging of cigarettes on the risk perception of Uruguayan smokers: an experimental study.

BACKGROUND: Uruguay, a South American country of 3.4 million inhabitants that has already banned tobacco advertising, prohibited such terms as light, mild and low-tar and required graphic warnings covering 80% of cigarette packs, is considering the imposition of plain, standardised packaging. METHODS: We conducted an experimental choice-based conjoint analysis of the impact of alternative cigarette package designs on the risk perceptions of 180 adult current Uruguayan smokers. We compared plain packaging, with a standardised brand description and the dark brown background colour required on Australian cigarette packages, to two controls: the current package design with distinctive brand elements and colours; and a modified package design, with distinctive brand elements and the dark brown background colour. Graphic warnings were also varied. RESULTS: Plain packaging significantly reduced the probability of perceiving the stimulus cigarettes as less harmful in comparison to the current package design (OR 0.398, 95% CI 0.333 to 0.476, p<0.001) and the modified package design (OR 0.729, 95% CI 0.626 to 0.849, p<0.001). CONCLUSIONS: Plain packaging enhanced the perceived risk of cigarette products even in a highly regulated setting such as Uruguay. Both the elimination of distinctive brand elements and the use of Australia's dark brown background colour contributed to the observed effect.

An in vitro evaluation of sagittal alignment in the cervical spine after insertion of supraphysiologic lordotic implants.

PURPOSE: Cervical spine malalignment can develop as a consequence of degenerative disc disease or following spinal surgery. When normal sagittal alignment of the spine is disrupted, further degeneration may occur adjacent to the deformity. The purpose of this study was to investigate changes in lordosis and sagittal alignment in the cervical spine after insertion of supraphysiologic lordotic implants. METHODS: Eight cadaveric cervical spines (Occiput-T1) were tested. The occiput was free to translate horizontally and vertically but constrained from angular rotation. The T1 vertebra was rigidly fixed with a T1 tilt of 23°. Implants with varying degrees of lordosis were inserted starting with single-level constructs (C5-C6), followed by two (C5-C7), and three-level (C4-C7) constructs. Changes in sagittal alignment, Occ-C2 angle, cervical lordosis (C2-7), and segmental lordosis were measured. RESULTS: Increasing cage lordosis led to global increases in cervical lordosis. As implanted segmental lordosis increased, the axial levels compensated by decreasing in lordosis to maintain horizontal gaze. An increase in cage lordosis also corresponded with larger changes in SVA. CONCLUSION: Reciprocal compensation was observed in the axial and sub-axial cervical spine, with the Occ-C2 segment undergoing the largest compensation. Adding more implant lordosis led to larger reciprocal changes and changes in SVA. Implants with supraphysiologic lordosis may allow for additional capabilities in correcting cervical sagittal plane deformity, following further clinical evaluation.

Lower incidence of myocardial infarction after smoke-free legislation enforcement in Chile.

OBJECTIVE: To evaluate the impact of a complete smoking ban in enclosed spaces on the incidence of acute myocardial infarction in Chile. METHODS: The population-based study involved residents of urban areas, where 80% of the Chilean population live, aged 20 years or older who had a myocardial infarction. Monthly myocardial infarction incidence and mortality rates at health-care facilities between January 2011 and December 2014 were derived from admission and mortality databases. Regression discontinuity methods were used to estimate the near-immediate impact on disease incidence of enforcing smoke-free legislation in March 2013. The same analysis was performed for ischaemic stroke, degenerative disc disease and colon cancer. Data on the concentration of fine respirable particulates were included in an additional analysis of myocardial infarction incidence in the Santiago metropolitan area. RESULTS: The enforcement of smoke-free legislation was associated with an abrupt, near-immediate decline of 0.639 cases of myocardial infarction per 100 000 adults per month (95% confidence interval, CI: 0.242 to 1.036; relative decline: 7.8%). Similar declines were observed in men and women and in people aged over and under 70 years. However, enforcement of the legislation was not associated with a significant change in the rate of ischaemic stroke, degenerative disc disease or colon cancer. The abrupt decline in myocardial infarction incidence was also observed when data on fine respirable particulates were included in an analysis for Santiago. CONCLUSION: The enforcement of extensive smoke-free legislation in Chile was associated with an abrupt, near-immediate decline in the incidence of myocardial infarction.