Faculty Bibliography

BACKGROUND:The large-scale social distancing efforts to reduce SARS-CoV-2 transmission have dramatically changed human behaviors associated with traumatic injuries. Trauma centers have reported decreases in trauma volume, paralleled by changes in injury mechanisms. We aimed to quantify changes in trauma epidemiology at an urban Level I trauma center in a county that instituted one of the earliest shelter-in-place orders to inform trauma care during future pandemic responses. METHODS:A single-center interrupted time-series analysis was performed to identify associations of shelter-in-place with trauma volume, injury mechanisms, and patient demographics in San Francisco, California. To control for short-term trends in trauma epidemiology, weekly level data were analyzed 6 months before shelter-in-place. To control for long-term trends, monthly level data were analyzed 5 years before shelter-in-place. RESULTS:Trauma volume decreased by 50% in the week following shelter-in-place (p < 0.01), followed by a linear increase each successive week (p < 0.01). Despite this, trauma volume for each month (March-June 2020) remained lower compared with corresponding months for all previous 5 years (2015-2019). Pediatric trauma volume showed similar trends with initial decreases (p = 0.02) followed by steady increases (p = 0.05). Reductions in trauma volumes were due entirely to changes in nonviolent injury mechanisms, while violence-related injury mechanisms remained unchanged (p < 0.01). CONCLUSION:Although the shelter-in-place order was associated with an overall decline in trauma volume, violence-related injuries persisted. Delineating and addressing underlying factors driving persistent violence-related injuries during shelter-in-place orders should be a focus of public health efforts in preparation for future pandemic responses. LEVEL OF EVIDENCE:Epidemiological study, level III.

Background/UNASSIGNED:Latino people in the US are experiencing higher excess deaths during the COVID-19 pandemic than any other racial/ethnic group, but it is unclear which subgroups within this diverse population are most affected. Such information is necessary to target policies that prevent further excess mortality and reduce inequities. Methods/UNASSIGNED:Using death certificate data for January 1, 2016 through February 29, 2020 and time-series models, we estimated the expected weekly deaths among Latino people in California from March 1 through October 3, 2020. We quantified excess mortality as observed minus expected deaths and risk ratios (RR) as the ratio of observed to expected deaths. We considered subgroups defined by age, sex, place of birth, education, occupation, and combinations of these factors. Findings/UNASSIGNED:During the first seven months of the pandemic, Latino deaths in California exceeded expected deaths by 10,316, a 31% increase. Excess death rates were greatest for individuals born in Mexico (RR 1.44; 95% PI, 1.41, 1.48) or Central America (RR 1.49; 95% PI, 1.37, 1.64), with less than a high school degree (RR 1.41; 95% PI, 1.35, 1.46), or in food-and-agriculture (RR 1.60; 95% PI, 1.48, 1.74) or manufacturing occupations (RR 1.59; 95% PI, 1.50, 1.69). Immigrant disadvantages in excess death were magnified among working-age Latinos in essential occupations. Interpretation/UNASSIGNED:The pandemic has disproportionately impacted mortality among Latino immigrants and Latinos in unprotected essential jobs; Interventions to reduce these disparities should include early vaccination, workplace safety enforcement, and expanded access to medical care. Funding/UNASSIGNED:National Institute on Aging; UCSF. RESEARCH IN CONTEXT/UNASSIGNED:

Importance:State cannabis laws are changing rapidly. Research is inconclusive about their association with rates of self-harm and assault. Existing studies have not considered variations in cannabis commercialization across states over time. Objective:To evaluate the association of state medical and recreational cannabis laws with self-harm and assault, overall and by age and sex, while considering varying degrees of commercialization. Design, Setting, and Participants:Using a cohort design with panel fixed-effects analysis, within-state changes in claims for self-harm and assault injuries before and after changes in cannabis laws were quantified in all 50 US states and the District of Columbia. Comprehensive claims data on commercial and Medicare Advantage health plan beneficiaries from January 1, 2003, to December 31, 2017, grouped by state and month, were evaluated. Data analysis was conducted from January 31, 2020, to January 21, 2021. Exposures:Categorical variable that indexed the degree of cannabis legalization in each state and month based on law type (medical or recreational) and operational status of dispensaries (commercialization). Main Outcomes and Measures:Claims for self-harm and assault injuries based on International Classification of Diseases codes. Results:The analysis included 75 395 344 beneficiaries (mean [SD] age, 47 [22] years; 50% female; and median follow-up, 17 months [interquartile range, 8-36 months]). During the study period, 29 states permitted use of medical cannabis and 11 permitted recreational cannabis. Point estimates for populationwide rates of self-harm and assault injuries were higher in states legalizing recreational cannabis compared with states with no cannabis laws, but these results were not statistically significant (adjusted rate ratio [aRR] assault, recreational dispensaries: 1.27; 95% CI, 0.79-2.03;self-harm, recreational dispensaries aRR: 1.15; 95% CI, 0.89-1.50). Results varied by age and sex with no associations found except for states with recreational policies and self-harm among males younger than 40 years (aRR <21 years, recreational without dispensaries: 1.70; 95% CI, 1.11-2.61; aRR aged 21-39 years, recreational dispensaries: 1.46; 95% CI, 1.01-2.12). Medical cannabis was generally not associated with self-harm or assault injuries populationwide or among age and sex subgroups. Conclusions and Relevance:Recreational cannabis legalization appears to be associated with relative increases in rates of claims for self-harm among male health plan beneficiaries younger than 40 years. There was no association between cannabis legalization and self-harm or assault, for any other age and sex group or for medical cannabis. States that legalize but still constrain commercialization may be better positioned to protect younger male populations from unintended harms.

BACKGROUND:Firearm dealer density is correlated with firearm interpersonal violence, but no quasi-experimental studies have assessed whether changes in dealer density lead to changes in firearm self-harm injuries and deaths. We assessed whether openings of firearm dealers are associated with short-term changes in local firearm self-harm injury rates. METHODS:We identified 718 openings of firearm dealers in California using licensing data, 2014-2016. We defined exposure regions based on aggregations of zip codes defined by proximity to firearm dealer openings and matched each opening to four control regions on time and determinants of firearm injury. We applied a differences-in-differences approach to compare rates of firearm self-harm, in the month before and after each opening, in places with and without openings. RESULTS:Firearm dealer openings were not associated with acute, local changes in firearm self-harm relative to places without openings (ratio of rate ratio: 0.90 [95% CI:0.68-1.19]). Results were robust to numerous sensitivity and secondary analyses. CONCLUSION:We found no associations of firearm dealer openings with acute, localized firearm self-harm deaths and injuries. Our focus on acute, local effects; broad availability of dealers and firearms; durability of firearms; or strong confounding-control may explain these null findings.

COVID-19 mortality increases dramatically with age and is also substantially higher among Black, Indigenous, and People of Color (BIPOC) populations in the United States. These two facts can have conflicting implications because BIPOC populations are younger than white populations. In analyses of California and Minnesota--demographically divergent states--we show that COVID vaccination schedules based solely on age benefit the older white populations at the expense of younger BIPOC populations with higher risk of death from COVID-19. We find that strategies that prioritize high-risk geographic areas for vaccination at all ages better target mortality risk than age-based strategies alone, although they do not always perform as well as direct prioritization of high-risk racial/ethnic groups. Vaccination schemas directly implicate equitability of access, both domestically and globally.

California's Mental Health Services Act (MHSA) substantially expanded funding of county mental health services through a state tax, and led to broad prevention efforts and intensive services for individuals experiencing serious mental disorders. We estimated the associations between MHSA and mortality due to suicide, homicide, and acute effects of alcohol. Using annual cause-specific mortality data for each US state and the District of Columbia from 1976-2015, we used a generalization of the quasi-experimental synthetic control method to predict California's mortality rate for each outcome in the absence of MHSA using a weighted combination of comparison states. We calculated the association between MHSA and each outcome as the absolute difference and percentage difference between California's observed and predicted average annual rates over the postintervention years (2007-2015). MHSA was associated with modest decreases in average annual rates of homicide (-0.81/100,000 persons, corresponding to a 13% reduction) and mortality from acute alcohol effects (-0.35/100,000 persons, corresponding to a 12% reduction). Placebo test inference suggested that the associations were unlikely to be due to chance. MHSA was not associated with suicide. Protective associations with mortality due to homicide and acute alcohol effects provide evidence for modest health benefits of MHSA at the population level.

BACKGROUND:Though SARS-CoV-2 outbreaks have been documented in occupational settings and in-person essential work has been suspected as a risk factor for COVID-19, occupational differences in excess mortality have, to date, not been examined. Such information could point to opportunities for intervention, such as vaccine prioritization or regulations to enforce safer work environments. METHODS AND FINDINGS:Using autoregressive integrated moving average models and California Department of Public Health data representing 356,188 decedents 18-65 years of age who died between January 1, 2016 and November 30, 2020, we estimated pandemic-related excess mortality by occupational sector and occupation, with additional stratification of the sector analysis by race/ethnicity. During these first 9 months of the COVID-19 pandemic, working-age adults experienced 11,628 more deaths than expected, corresponding to 22% relative excess and 46 excess deaths per 100,000 living individuals. Sectors with the highest relative and per-capita excess mortality were food/agriculture (39% relative excess; 75 excess deaths per 100,000), transportation/logistics (31%; 91 per 100,000), manufacturing (24%; 61 per 100,000), and facilities (23%; 83 per 100,000). Across racial and ethnic groups, Latino working-age Californians experienced the highest relative excess mortality (37%) with the highest excess mortality among Latino workers in food and agriculture (59%; 97 per 100,000). Black working-age Californians had the highest per-capita excess mortality (110 per 100,000), with relative excess mortality highest among transportation/logistics workers (36%). Asian working-age Californians had lower excess mortality overall, but notable relative excess mortality among health/emergency workers (37%), while White Californians had high per-capita excess deaths among facilities workers (70 per 100,000). CONCLUSIONS:Certain occupational sectors are associated with high excess mortality during the pandemic, particularly among racial and ethnic groups also disproportionately affected by COVID-19. In-person essential work is a likely venue of transmission of coronavirus infection and must be addressed through vaccination and strict enforcement of health orders in workplace settings.

Evidence for Action (E4A), a signature program of the Robert Wood Johnson Foundation, funds investigator-initiated research on the impacts of social programs and policies on population health and health inequities. Across thousands of letters of intent and full proposals E4A has received since 2015, one of the most common methodological challenges faced by applicants is selecting realistic effect sizes to inform calculations of power, sample size, and minimum detectable effect (MDE). E4A prioritizes health studies that are both (1) adequately powered to detect effect sizes that may reasonably be expected for the given intervention and (2) likely to achieve intervention effects sizes that, if demonstrated, correspond to actionable evidence for population health stakeholders. However, little guidance exists to inform the selection of effect sizes for population health research proposals. We draw on examples of five rigorously evaluated population health interventions. These examples illustrate considerations for selecting realistic and actionable effect sizes as inputs to calculations of power, sample size and MDE for research proposals to study population health interventions. We show that plausible effects sizes for population health interventions may be smaller than commonly cited guidelines suggest. Effect sizes achieved with population health interventions depend on the characteristics of the intervention, the target population, and the outcomes studied. Population health impact depends on the proportion of the population receiving the intervention. When adequately powered, even studies of interventions with small effect sizes can offer valuable evidence to inform population health if such interventions can be implemented broadly. Demonstrating the effectiveness of such interventions, however, requires large sample sizes.

Directed acyclic graphs (DAGs), a prominent tool for expressing assumptions in epidemiologic research, are most useful when the hypothetical data generating structure is correctly encoded. Understanding a study's data generating structure and translating that data structure into a DAG can be challenging, but these skills are often glossed over in training. Campbell and Stanley's framework for causal inference has been extraordinarily influential in social science training programs but has received less attention in epidemiology. Their work, along with subsequent revisions and enhancements based on practical experience conducting empirical studies, presents a catalog of 37 threats to validity describing reasons empirical studies may fail to deliver causal effects. We interpret most of these threats to study validity as suggestions for common causal structures. Threats are organized into issues of statistical conclusion validity, internal validity, construct validity, or external validity. To assist epidemiologists in drawing the correct DAG for their application, we map the correspondence between threats to validity and epidemiologic concepts that can be represented with DAGs. Representing these threats as DAGs makes them amenable to formal analysis with d-separation rules and breaks down cross-disciplinary language barriers in communicating methodologic issues.