Epidemiologic Reviews最新文献

Burnout in health care workers is caused by a complex interplay of psychosocial, organizational, and broader environmental factors. Understanding these causes can help us develop coordinated, comprehensive, and effective solutions. Employers must assess the cost of burnout to their institution, acknowledge tradeoffs, communicate with their employees about burnout, and think comprehensively as they develop policy, programs, and environmental supports to mitigate burnout.

COVID-19 has transitioned from a pandemic to an endemic state, but the emergence of novel variants continues to pose significant public health challenges. In this study, the application of spatial and spatiotemporal machine learning (ML) models in understanding the dynamics of COVID-19 was systematically reviewed, as were contextual local-level comprehensive socio-environmental drivers. A systematic search was conducted across the Scopus, Web of Science, PubMed, Emcare (via Ovid), and the World Health Organization COVID-19 databases, and gray literature, adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Data extraction was conducted according to the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies checklist, and study quality was assessed using a validated scoring system. A total of 42 studies met the inclusion criteria. The review Findings indicate that global-scale spatial and spatiotemporal ML models dominate the field. Long-standing standalone factors in the demographic, environmental, and socioeconomic domains are frequently used as local-level drivers. However, the integration of composite indicators, aggregating multiple standalone factors into a single score, is notably lacking. Such composite indicators have the potential to reduce model complexity, improve interpretability, and enhance performance by capturing multidimensional aspects of vulnerability or risk in a more simplified form. This review highlights critical gaps in the current use of spatial and spatiotemporal ML models to understand the spatial epidemiology of COVID-19. Addressing these gaps could significantly enhance the understanding of COVID-19 dynamics and inform the development of effective public health strategies to mitigate future threats.

Although the economic impact of guaranteed income (GI) (recurring, unconditional, and unrestricted cash transfers intended to supplement the income of participants) is well studied, much less is known about how GI may affect health, especially in the context of high-income countries like the United States and Canada. We searched 5 electronic databases for terms related to "guaranteed income" and "cash transfer" through April 23, 2022. Among 5340 records originally identified, 25 met our inclusion criteria and represented 16 unique GI initiatives. Most included studies used a quantitative approach (n = 22; 88%), were published between 2000 and 2022 (n = 21; 84%), and were conducted in the United States (n = 15; 60%). Health outcomes included maternal and child health (eg, preterm births, breastfeeding initiation), healthcare utilization (eg, hospital admissions), mental health (eg, depression), physical health (eg, body mass index), and behavioral health (eg, substance use). Maternal, infant, and child health were the most highly represented health outcomes. Guaranteed-income initiatives generally had significant positive impacts on health outcomes, especially among the most vulnerable recipients. Data were absent on neighborhood-level health outcomes, chronic and infectious diseases, potential unintended consequences, and long-term impacts of GI on health. Studies on the impact of GI on health suggest GI has the potential to positively affect many, but not all, health outcomes. Rigorous assessment of health outcomes is still needed, and additional health outcomes should be considered in the design and evaluation of GI initiatives.

Comparisons between randomized trial analyses and observational analyses that attempt to address similar research questions have generated many controversies in epidemiology and the social sciences. There has been little consensus on when such comparisons are reasonable, what their implications are for the validity of observational analyses, or whether trial and observational analyses can be integrated to address effectiveness questions. Here, we consider methods for using observational analyses to complement trial analyses when assessing treatment effectiveness. First, we review the framework for designing observational analyses that emulate target trials and present an evidence map of its recent applications. We then review approaches for estimating the average treatment effect in the target population underlying the emulation, using observational analyses of the emulation data alone and using transportability analyses to extend inferences from a trial to the target population. We explain how comparing treatment effect estimates from the emulation against those from the trial can provide evidence on whether observational analyses can be trusted to deliver valid estimates of effectiveness-a process we refer to as benchmarking-and, in some cases, allow the joint analysis of the trial and observational data. We illustrate different approaches using a simplified example of a pragmatic trial and its emulation in registry data. We conclude that synthesizing trial and observational data-in transportability, benchmarking, or joint analyses-can leverage their complementary strengths to enhance learning about comparative effectiveness, through a process combining quantitative methods and epidemiologic judgments.

For lethal means safety counseling (LMSC) interventions to reduce population-level suicide rates, interventions must be deployed across many settings and populations. We conducted a systematic search in 6 databases to review the current state of LMSC interventions across study designs, settings, intervention providers, populations, and injury prevention levels (eg, universal). Eligibility criteria were as follows: any individual or group receiving an LMSC intervention involving a human-to-human component aiming to influence adult behaviors related to lethal suicide methods, and outcome assessment of storage behaviors and/or suicidal self-directed violence (SDV). Risk of bias was assessed using the Effective Public Health Practice Project quality assessment tool. A descriptive synthesis approach was used for analysis. Twenty-two studies were included that reported medication- and/or firearm-storage behaviors and/or SDV after LMSC. Of the 19 studies assessing behavioral change, 14 reported a significant improvement in safe storage behaviors, and all studies measuring acceptability reported that participants found the interventions favorable. The quality of evidence was limited. No studies were rated low risk of bias, and 77% were rated high risk of bias. There was substantial heterogeneity in the settings, populations, injury prevention levels, delivery methods, and intervention elements. Many included studies focused on caregivers of pediatric populations, and few studies assessed SDV outcomes. Higher-quality trials conducted across a variety of settings, particularly those focusing on adults at risk of suicide, are needed. This review was preregistered with the International Prospective Register of Systematic Reviews (no. CRD42021230668).

The widespread occurrence of knee injuries in athletes when playing basketball, in particular, damage to the cartilage system of the knee joint is reviewed. Basketball players may develop post-traumatic chondropathy with a subsequent change in the functional state of knee joints, which is inextricably linked with a decrease in the quality of life, the occurrence of pain syndrome, shortening of career duration, an increased risk of surgical interventions, and possible disability, from a long-term perspective. This review was conducted to explore modern ideas about the impact of post-traumatic chondropathy on the functional state of knee joints in athletes during basketball games. Literature databases were searched for relevant studies. Given the character of the basketball game, knee injuries, both acute and chronic, are widespread among athletes of this sport, including cartilaginous defects of the knee joint. The findings of this study are of practical value for sports medicine doctors, physiotherapists, and traumatologists because they present the main mechanisms of knee injuries in athletes when playing basketball and the possible consequences of these injuries in the long term.

Progress toward racial health equity cannot be made if we cannot measure its fundamental driver: structural racism. As in other epidemiologic studies, the first step is to measure the exposure. But how to measure structural racism is an ongoing debate. To characterize the approaches epidemiologists and other health researchers use to quantitatively measure structural racism, highlight methodological innovations, and identify gaps in the literature, we conducted a scoping review of the peer-reviewed and gray literature published during 2019-2021 to accompany the 2018 published work of Groos et al., in which they surveyed the scope of structural racism measurement up to 2017. We identified several themes from the recent literature: the current predominant focus on measuring anti-Black racism; using residential segregation as well as other segregation-driven measures as proxies of structural racism; measuring structural racism as spatial exposures; increasing calls by epidemiologists and other health researchers to measure structural racism as a multidimensional, multilevel determinant of health and related innovations; the development of policy databases; the utility of simulated counterfactual approaches in the understanding of how structural racism drives racial health inequities; and the lack of measures of antiracism and limited work on later life effects. Our findings sketch out several steps to improve the science related to structural racism measurements, which is key to advancing antiracism policies.

People living with HIV can achieve viral suppression through timely HIV care continuum (HCC) engagement (ie, diagnosis, linkage to HIV care, retention in care, and adherence to prescribed treatment regimens). Black populations have poorer viral suppression, suboptimal HCC engagement, and higher levels of racism-related mistrust. The state of the evidence linking suboptimal HCC engagement to racism among US Black populations is assessed in this article. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, 6 English language databases were searched using 3 sets of key terms related to HCC engagement (eg, HIV diagnosis), racism (eg, discrimination), and the population (eg, Black people). To exclude articles, 3 rounds of reviews were conducted and results assessed for interrater reliability (κ = 99.00%; P < 0.00). From 2027 articles initially retrieved, the final set of analyses (n = 32) included clinical and nonclinical samples of people living with or at risk for HIV. Overall, the evidence was conceptually robust but methodologically simple. Studies primarily targeted intrapersonal and interpersonal racism and the late stage of HCC engagement: adherence. Sample-specific prevalence of racism ranged considerably; for example, 20% to 90% of sample members in clinical settings perceived or experienced interpersonal forms of racism. To date, the evidence suggests the relationship between racism and HCC engagement is mixed. Racism is salient among Black people living with or at risk for HIV. It appears not to impede HIV testing, though it may limit retention in HIV care, especially among men who have sex with men.

The incidence of invasive fungal infection (IFI) is increasing, especially among patients diagnosed with hematological malignancies due to their immunocompromised nature. Other risk factors include advanced age, exposure to immunosuppressants, neutropenia, and catheter use. Some of the most common IFI organisms reported are Candida and Aspergillus species, and other fungal species, including Scedosporium, Trichosporon, Cryptococcus, and Fusarium have also increasingly been reported in the past years. However, the epidemiologic data on IFI among patients with hematological malignancies in Asian countries are lacking. Therefore, we investigated published epidemiologic data on such cases from the past 10 years (2011-2021) and discuss the challenges faced in the diagnosis and management of IFIs in Asia.

Racial discrimination is a well-known risk factor of racial disparities in health. Although progress has been made in identifying multiple levels through which racism and racial discrimination influences health, less is known about social factors that may buffer racism's associations with health. We conducted a systematic review of the literature with a specific focus on social connectedness, racism, and health, retrieving studies conducted in the United States and published between January 1, 2012, and July 30, 2022, in peer-reviewed journals. Of the 787 articles screened, 32 were selected for full-text synthesis. Most studies (72%) were at the individual level, cross-sectional, and among community/neighborhood, school, or university samples. Studies had good methodological rigor and low risk of bias. Measures of racism and racial discrimination varied. Discrimination scales included unfair treatment because of race, schedule of racist events, experiences of lifetime discrimination, and everyday discrimination. Measures of social connectedness (or disconnectedness) varied. Social-connectedness constructs included social isolation, loneliness, and social support. Mental health was the most frequently examined outcome (75%). Effect modification was used in 56% of studies and mediation in 34% of studies. In 81% of studies, at least 1 aspect of social connectedness significantly buffered or mediated the associations between racism and health. Negative health associations were often weaker among people with higher social connectedness. Social connectedness is an important buffering mechanism to mitigate the associations between racial discrimination and health. In future studies, harmonizing metrics of social connectedness and racial discrimination can strengthen causal claims to inform interventions.