Should Patients' Boredom in Locked Inpatient Psychiatric Units Be Considered Iatrogenic Harm?

Patients often report experiencing boredom during inpatient psychiatry stays. Because patients' vulnerabilities and conditions can be exacerbated when they feel bored, this article considers ethical dimensions of inpatient units' designs that limit patients' autonomy or access to activities or interactions with others. This commentary on a case also considers whether and how boredom should be considered an iatrogenic harm and influence discharge planning.

Large Community Outbreak of Legionnaires Disease Potentially Associated with a Cooling Tower - Napa County, California, 2022.

Legionnaires disease is a serious infection acquired by inhalation of water droplets from human-made building water systems that contain Legionella bacteria. On July 11 and 12, 2022, Napa County Public Health (NCPH) in California received reports of three positive urinary antigen tests for Legionella pneumophila serogroup 1 in the town of Napa. By July 21, six Legionnaires disease cases had been confirmed among Napa County residents, compared with a baseline of one or two cases per year. NCPH requested assistance from the California Department of Public Health (CDPH) and CDC to aid in the investigations. Close temporal and geospatial clustering permitted a focused environmental sampling strategy of high-risk facilities which, coupled with whole genome sequencing results from samples and investigation of water system maintenance, facilitated potential linking of the outbreak with an environmental source. NCPH, with technical support from CDC and CDPH, instructed and monitored remediation practices for all environmental locations that tested positive for Legionella. The investigation response to this community outbreak illustrates the importance of interdisciplinary collaboration by public health agencies, laboratory support, timely communication with the public, and cooperation of managers of potentially implicated water systems. Timely identification of possible sources, sampling, and remediation of any facility testing positive for Legionella is crucial to interrupting further transmission.

Some principles for using epidemiologic study results to parameterize transmission models.

Background: Infectious disease models, including individual based models (IBMs), can be used to inform public health response. For these models to be effective, accurate estimates of key parameters describing the natural history of infection and disease are needed. However, obtaining these parameter estimates from epidemiological studies is not always straightforward. We aim to 1) outline challenges to parameter estimation that arise due to common biases found in epidemiologic studies and 2) describe the conditions under which careful consideration in the design and analysis of the study could allow us to obtain a causal estimate of the parameter of interest. In this discussion we do not focus on issues of generalizability and transportability. Methods: Using examples from the COVID-19 pandemic, we first identify different ways of parameterizing IBMs and describe ideal study designs to estimate these parameters. Given real-world limitations, we describe challenges in parameter estimation due to confounding and conditioning on a post-exposure observation. We then describe ideal study designs that can lead to unbiased parameter estimates. We finally discuss additional challenges in estimating progression probabilities and the consequences of these challenges. Results: Causal estimation can only occur if we are able to accurately measure and control for all confounding variables that create non-causal associations between the exposure and outcome of interest, which is sometimes challenging given the nature of the variables we need to measure. In the absence of perfect control, non-causal parameter estimates should still be used, as sometimes they are the best available information we have. Conclusions: Identifying which estimates from epidemiologic studies correspond to the quantities needed to parameterize disease models, and determining whether these parameters have causal interpretations, can inform future study designs and improve inferences from infectious disease models. Understanding the way in which biases can arise in parameter estimation can inform sensitivity analyses or help with interpretation of results if the magnitude and direction of the bias is understood.

Health Care Provider Knowledge and Attitudes Regarding Adult Pneumococcal Conjugate Vaccine Recommendations - United States, September 28-October 10, 2022.

Despite the availability of effective vaccines against pneumococcal disease, pneumococcus is a common bacterial cause of pneumonia, causing approximately 100,000 hospitalizations among U.S. adults per year. In addition, approximately 30,000 invasive pneumococcal disease (IPD) cases and 3,000 IPD deaths occur among U.S. adults each year. Previous health care provider surveys identified gaps in provider knowledge about and understanding of the adult pneumococcal vaccine recommendations, and pneumococcal vaccine coverage remains suboptimal. To assess the feasibility and acceptability domains of the Advisory Committee on Immunization Practices (ACIP) Evidence to Recommendations (EtR) framework, a health care provider knowledge and attitudes survey was conducted during September 28-October 10, 2022, by the Healthcare and Public Perceptions of Immunizations Survey Collaborative before the October 2022 ACIP meeting. Among 751 provider respondents, two thirds agreed or strongly agreed with the policy option under consideration to expand the recommendations for the new 20-valent pneumococcal conjugate vaccine (PCV20) to adults who had only received the previously recommended 13-valent pneumococcal conjugate vaccine (PCV13). Gaps in providers' knowledge and perceived challenges to implementing recommendations were identified and were included in ACIP's EtR framework discussions in late October 2022 when ACIP updated the recommendations for PCV20 use in adults. Currently, use of PCV20 is recommended for certain adults who have previously received PCV13, in addition to those who have never received a pneumococcal conjugate vaccine. The survey findings indicate a need to increase provider awareness and implementation of pneumococcal vaccination recommendations and to provide tools to assist with patient-specific vaccination guidance. Resources available to address the challenges to implementing pneumococcal vaccination recommendations include the PneumoRecs VaxAdvisor mobile app and other CDC-developed tools, including summary documents and overviews of vaccination schedules and CDC's strategic framework to increase confidence in vaccines and reduce vaccine-preventable diseases, Vaccinate with Confidence.

Impact of CoronaVac on Covid-19 outcomes of elderly adults in a large and socially unequal Brazilian city: A target trial emulation study.

BACKGROUND: Although CoronaVac was the only Covid-19 vaccine adopted in the first months of the Brazilian vaccination campaign, randomized clinical trials to evaluate its efficacy in elderly adults were limited. In this study, we use routinely collected surveillance and SARS-CoV-2 vaccination and testing data comprising the population of the fifth largest city of Brazil to evaluate the effectiveness of CoronaVac in adults 60+ years old against severe outcomes. METHODS: Using large observational databases on vaccination and surveillance data from the city of Fortaleza, Brazil, we defined a retrospective cohort including 324,302 eligible adults aged ≥60 years to evaluate the effectiveness of the CoronaVac vaccine. The cohort included individuals vaccinated between January 21, 2021, and August 31, 2021, who were matched with unvaccinated persons at the time of rollout following a 1:1 ratio according to baseline covariates of age, sex, and Human Development Index of the neighborhood of residence. Only Covid-19-related severe outcomes were included in the analysis: hospitalization, ICU admission, and death. Vaccine effectiveness for each outcome was calculated by using the risk ratio between the two groups, with the risk obtained by the Kaplan-Meier estimator. RESULTS: We obtained 62,643 matched pairs for assessing the effectiveness of the two-dose regimen of CoronaVac. The demographic profile of the matched population was statistically representative of the population of Fortaleza. Using the cumulative incidence as the risk associated with each group, starting at day 14 since the receipt of the second dose, we found an 82.3 % (95 % CI 66.3-93.9) effectiveness against Covid-19-related death, 68.4 % (95 % CI 42.3-86.4) against ICU admission, and 55.8 % (95 % CI 42.7-68.3) against hospital admission. CONCLUSIONS: Our results show that, despite critical delays in vaccine delivery and limited evidence in efficacy trial estimates, CoronaVac contributed to preventing deaths and severe morbidity due to Covid-19 in elderly adults.

Geographic Targeting of COVID-19 Testing to Maximize Detection in Los Angeles County.

Background: Many severe acute respiratory syndrome coronavirus 2 infections have not been detected, reported, or isolated. For community testing programs to locate the most cases under limited testing resources, we developed and evaluated quantitative approaches for geographic targeting of increased coronavirus disease 2019 testing efforts. Methods: For every week from December 5, 2021, to July 23, 2022, testing and vaccination data were obtained in ∼340 cities/communities in Los Angeles County, and models were developed to predict which cities/communities would have the highest test positivity 2 weeks ahead. A series of counterfactual scenarios were constructed to explore the additional number of cases that could be detected under targeted testing. Results: The simplest model based on most recent test positivity performed nearly as well as the best model based on most recent test positivity and weekly tests per 100 persons in identifying communities that would maximize the average yield of cases per test in the following 2 weeks and almost as well as the perfect knowledge of the actual positivity 2 weeks ahead. In the counterfactual scenario, increasing testing by 1% 2 weeks ahead and allocating all tests to communities with the top 10% of predicted positivity would yield a 2% increase in detected cases. Conclusions: Simple models based on current test positivity can predict which communities may have the highest positivity 2 weeks ahead and hence could be allocated with more testing resources.

The effectiveness of COVID-19 vaccines in Latin America, 2021: a multicenter regional case-control study.

Background: As of September 2022, nearly 1.3 billion doses of COVID-19 vaccine products have been administered in Latin America and the Caribbean, where 27% of global COVID-19 deaths have occurred. This study aimed to estimate the effectiveness of COVID-19 vaccines against lab-confirmed COVID-19 related hospitalizations and deaths among adults in Argentina, Brazil, Chile, and Colombia. Methods: Using a test-negative case control design, we evaluated the effectiveness of a primary vaccination series considering six COVID-19 vaccine products (Sputnik V, mRNA-1273, CoronaVac, ChAdOx1, BNT162b2, Ad26.COV2.S) against lab-confirmed COVID-19 hospitalizations and deaths among 83,708 hospitalized adults from February-December, 2021. Data from hospitalization records, COVID surveillance, and vaccination registries were used. Vaccine effectiveness was estimated using logistic regression ((1-OR) x 100). Findings: The average age of participants was 56.7 (SD = 17.5), and 45,894 (54.8%) were male. Adjusted VE (aVE) estimates for full vaccination against hospitalization were 82% for mRNA-1273 (95% confidence interval (CI) = -30 to 98%), 76% (71%-81%) for BNT162b2, 65% (61-68%) for ChAdOx1, 57% (10-79%) for Sputnik V, 53% (50-56%) for CoronaVac, and 46% (23-62%) for Ad26.COV2.S. Estimates, particularly for CoronaVac, varied by variant. Decreasing aVE was estimated as age increased, particularly for CoronaVac and ChAdOx1. aVE estimates against death were generally higher, with 100% (CI not estimated) for mRNA-1273, 82% (69-90%) for BNT162b2, 73% (69-77%) for ChAdOx1, 65% (60-67%) for CoronaVac, 38% (-75 to 78%) for Sputnik V, 6% (-58 to 44%) for Ad26.COV2.S. Interpretation: Primary series vaccination with available COVID-19 vaccine products was effective against COVID-19 hospitalization and mortality. Effectiveness varied by product and declined with increasing age. Funding: This study was funded by the Pan-American Health Organization (PAHO, World Health Organization (WHO)). PAHO convened and led the study implementation.

Mass drug administration of azithromycin: an analysis.

BACKGROUND: WHO recommends mass drug administration (MDA) of the antibiotic azithromycin for children aged 1-11 months in areas with high rates of infant and child mortality. Notwithstanding the substantial potential benefits of lowering childhood mortality, MDA raises understandable concerns about exacerbating antibiotic resistance. OBJECTIVES: In this study, we aimed to evaluate the use of MDA using both quantitative and ethical considerations. SOURCES: We performed a series of literature searches between July 2019 and June 2022. CONTENT: We first compared MDA with other uses of antibiotics using the standard metric of 'number needed to treat', and five additional criteria: (1) other widely accepted uses of anti-infectives (2) absolute use (i.e. total number), of antibiotics, (3) risk-benefit trade-off, (4) availability of short-term alternatives, and (5) the precedent for implementing similar interventions. We found that MDA falls well within a justifiable range when compared with widely accepted uses of antibiotics in terms of the number needed to treat. The other five criteria we considered provided further support for the use of MDA to prevent childhood mortality. IMPLICATIONS: Although better data on antibiotic use and resistance are needed, efforts to reduce antibiotic use and resistance should not start with halting MDA of azithromycin in the areas with the highest rates of childhood mortality. Improving data to inform this decision is critical. However, on the basis of the best evidence available, we believe that concerns regarding resistance should not thwart MDA; instead, MDA should be accompanied by robust plans to monitor its efficacy and changes in resistance levels. Similar considerations could be included in a framework for evaluating the benefits of antibiotics against the risk of resistance in other contexts.

Victim Intoxication and Capacity to Consent in Sexual Assault Statutes across the United States.

Alcohol use is common in cases of sexual assault. These cases raise significant questions about a victim's capacity to consent to sexual intercourse. In many United States jurisdictions, intoxicated victims may be considered mentally incapacitated only if they have been administered alcohol or other substances involuntarily. A recent Minnesota Supreme Court case illustrated why reform is necessary in this area of criminal sexual conduct law. We present this case and the results of a review of felony criminal sexual conduct laws in the fifty states of the United States and the District of Columbia. We find that nearly half of the jurisdictions surveyed require that a victim must be involuntarily intoxicated to be considered incapacitated or impaired. We draw on Minnesota's experience with legislative reform of its sexual assault laws as well as judicially mediated reform mechanisms to present a roadmap for overcoming this voluntary intoxication caveat. Finally, we discuss the implications of these laws for victims of sexual assault and for the practice of forensic psychiatry in cases of criminal sexual conduct involving victim intoxication.

Clinical outcomes associated with SARS-CoV-2 Omicron (B.1.1.529) variant and BA.1/BA.1.1 or BA.2 subvariant infection in Southern California.

Epidemiologic surveillance has revealed decoupling of Coronavirus Disease 2019 (COVID-19) hospitalizations and deaths from case counts after emergence of the Omicron (B.1.1.529) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant globally. However, assessment of the relative severity of Omicron variant infections presents challenges because of differential acquired immune protection against Omicron and prior variants and because longer-term changes have occurred in testing and healthcare practices. Here we show that Omicron variant infections were associated with substantially reduced risk of progression to severe clinical outcomes relative to time-matched Delta (B.1.617.2) variant infections within a large, integrated healthcare system in Southern California. Adjusted hazard ratios (aHRs) for any hospital admission, symptomatic hospital admission, intensive care unit admission, mechanical ventilation and death comparing individuals with Omicron versus Delta variant infection were 0.59 (95% confidence interval: 0.51-0.69), 0.59 (0.51-0.68), 0.50 (0.29-0.87), 0.36 (0.18-0.72) and 0.21 (0.10-0.44), respectively. This reduced severity could not be explained by differential history of prior infection among individuals with Omicron or Delta variant infection and was starkest among individuals not previously vaccinated against COVID-19 (aHR = 0.40 (0.33-0.49) for any hospital admission and 0.14 (0.07-0.28) for death). Infections with the Omicron BA.2 subvariant were not associated with differential risk of severe outcomes in comparison to BA.1/BA.1.1 subvariant infections. Lower risk of severe clinical outcomes among individuals with Omicron variant infection should inform public health response amid establishment of the Omicron variant as the dominant SARS-CoV-2 lineage globally.

Modeling the Impact of Vaccination Strategies for Nursing Homes in the Context of Increased Severe Acute Respiratory Syndrome Coronavirus 2 Community Transmission and Variants.

Using an agent-based model, we examined the impact of community prevalence, the Delta variant, staff vaccination coverage, and booster vaccines for residents on outbreak dynamics in nursing homes. Increased staff coverage and high booster vaccine effectiveness leads to fewer infections, but cumulative incidence is highly dependent on community transmission.

Identifying and Alleviating Bias Due to Differential Depletion of Susceptible People in Postmarketing Evaluations of COVID-19 Vaccines.

Recent studies have provided key information about SARS-CoV-2 vaccines' efficacy and effectiveness (VE). One important question that remains is whether the protection conferred by vaccines wanes over time. However, estimates over time are subject to bias from differential depletion of susceptible individuals between vaccinated and unvaccinated groups. We examined the extent to which biases occur under different scenarios and assessed whether serological testing has the potential to correct this bias. By identifying nonvaccine antibodies, these tests could identify individuals with prior infection. We found that in scenarios with high baseline VE, differential depletion of susceptible individuals created minimal bias in VE estimates, suggesting that any observed declines are likely not due to spurious waning alone. However, if baseline VE was lower, the bias for leaky vaccines (which reduce individual probability of infection given contact) was larger and should be corrected for by excluding individuals with past infection if the mechanism is known to be leaky. Conducting analyses both unadjusted and adjusted for past infection could give lower and upper bounds for the true VE. Studies of VE should therefore enroll individuals regardless of prior infection history but also collect information, ideally through serological testing, on this critical variable.

Mathematical Modeling to Inform Vaccination Strategies and Testing Approaches for Coronavirus Disease 2019 (COVID-19) in Nursing Homes.

BACKGROUND: Nursing home residents and staff were included in the first phase of coronavirus disease 2019 vaccination in the United States. Because the primary trial endpoint was vaccine efficacy (VE) against symptomatic disease, there are limited data on the extent to which vaccines protect against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the ability to infect others (infectiousness). Assumptions about VE against infection and infectiousness have implications for changes to infection prevention guidance for vaccinated populations, including testing strategies. METHODS: We use a stochastic agent-based Susceptible-Exposed-Infectious (Asymptomatic/Symptomatic)-Recovered model of a nursing home to simulate SARS-CoV-2 transmission. We model 3 scenarios, varying VE against infection, infectiousness, and symptoms, to understand the expected impact of vaccination in nursing homes, increasing staff vaccination coverage, and different screening testing strategies under each scenario. RESULTS: Increasing vaccination coverage in staff decreases total symptomatic cases in the nursing home (among staff and residents combined) in each VE scenario. In scenarios with 50% and 90% VE against infection and infectiousness, increasing staff coverage reduces symptomatic cases among residents. If vaccination only protects against symptoms, and asymptomatic cases remain infectious, increased staff coverage increases symptomatic cases among residents. However, this is outweighed by the reduction in symptomatic cases among staff. Higher frequency testing-more than once weekly-is needed to reduce total symptomatic cases if the vaccine has lower efficacy against infection and infectiousness, or only protects against symptoms. CONCLUSIONS: Encouraging staff vaccination is not only important for protecting staff, but might also reduce symptomatic cases in residents if a vaccine confers at least some protection against infection or infectiousness.

Reduced COVID-19 hospitalizations among New York City residents following age-based SARS-CoV-2 vaccine eligibility: Evidence from a regression discontinuity design.

BACKGROUND: In clinical trials, several SARS-CoV-2 vaccines were shown to reduce risk of severe COVID-19 illness. Local, population-level, real-world evidence of vaccine effectiveness is accumulating. We assessed vaccine effectiveness for community-dwelling New York City (NYC) residents using a quasi-experimental, regression discontinuity design, leveraging a period (January 12-March 9, 2021) when ≥ 65-year-olds were vaccine-eligible but younger persons, excluding essential workers, were not. METHODS: We constructed segmented, negative binomial regression models of age-specific COVID-19 hospitalization rates among 45-84-year-old NYC residents during a post-vaccination program implementation period (February 21-April 17, 2021), with a discontinuity at age 65 years. The relationship between age and hospitalization rates in an unvaccinated population was incorporated using a pre-implementation period (December 20, 2020-February 13, 2021). We calculated the rate ratio (RR) and 95% confidence interval (CI) for the interaction between implementation period (pre or post) and age-based eligibility (45-64 or 65-84 years). Analyses were stratified by race/ethnicity and borough of residence. Similar analyses were conducted for COVID-19 deaths. RESULTS: Hospitalization rates among 65-84-year-olds decreased from pre- to post-implementation periods (RR 0.85, 95% CI: 0.74-0.97), controlling for trends among 45-64-year-olds. Accordingly, an estimated 721 (95% CI: 126-1,241) hospitalizations were averted. Residents just above the eligibility threshold (65-66-year-olds) had lower hospitalization rates than those below (63-64-year-olds). Racial/ethnic groups and boroughs with higher vaccine coverage generally experienced greater reductions in RR point estimates. Uncertainty was greater for the decrease in COVID-19 death rates (RR 0.85, 95% CI: 0.66-1.10). CONCLUSION: The vaccination program in NYC reduced COVID-19 hospitalizations among the initially age-eligible ≥ 65-year-old population by approximately 15% in the first eight weeks. The real-world evidence of vaccine effectiveness makes it more imperative to improve vaccine access and uptake to reduce inequities in COVID-19 outcomes.

Population impact of SARS-CoV-2 variants with enhanced transmissibility and/or partial immune escape.

SARS-CoV-2 variants of concern exhibit varying degrees of transmissibility and, in some cases, escape from acquired immunity. Much effort has been devoted to measuring these phenotypes, but understanding their impact on the course of the pandemic-especially that of immune escape-has remained a challenge. Here, we use a mathematical model to simulate the dynamics of wild-type and variant strains of SARS-CoV-2 in the context of vaccine rollout and nonpharmaceutical interventions. We show that variants with enhanced transmissibility frequently increase epidemic severity, whereas those with partial immune escape either fail to spread widely or primarily cause reinfections and breakthrough infections. However, when these phenotypes are combined, a variant can continue spreading even as immunity builds up in the population, limiting the impact of vaccination and exacerbating the epidemic. These findings help explain the trajectories of past and present SARS-CoV-2 variants and may inform variant assessment and response in the future.

Correction: Practical considerations for measuring the effective reproductive number, Rt.

[This corrects the article DOI: 10.1371/journal.pcbi.1008409.].