Faculty Bibliography
Searched for:
person:cerdam01 or freids01 or hamill07 or krawcn01
Total Results:
1310
Predicting the Future Course of Opioid Overdose Mortality: An Example from Two US States
BACKGROUND:The rapid growth of opioid abuse and related mortality across the United States has spurred the development of predictive models for the allocation of public health resources. These models should characterize heterogeneous growth across states using a drug epidemic framework that enables assessments of epidemic onset, rates of growth, and limited capacities for epidemic growth. METHODS:We used opioid overdose mortality data for 146 North and South Carolina counties from 2001 through 2014 to compare the retrodictive and predictive performance of a logistic growth model that parameterizes onsets, growth, and carrying capacity within a traditional Bayesian Poisson space-time model. RESULTS:In fitting the models to past data, the performance of the logistic growth model was superior to the standard Bayesian Poisson space-time model (deviance information criterion: 8088 vs. 8256), with reduced spatial and independent errors. Predictively, the logistic model more accurately estimated fatality rates 1, 2, and 3 years in the future (root mean squared error medians were lower for 95.7% of counties from 2012 to 2014). Capacity limits were higher in counties with greater population size, percent population age 45 to 64, and percent white population. Epidemic onset was associated with greater same-year and past-year incidence of overdose hospitalizations. CONCLUSION/CONCLUSIONS:Growth in annual rates of opioid fatalities was capacity limited, heterogeneous across counties, and spatially correlated, requiring spatial epidemic models for the accurate and reliable prediction of future outcomes related to opioid abuse. Indicators of risk are identifiable and can be used to predict future mortality outcomes.
PMID: 33002963
ISSN: 1531-5487
CID: 4617182
Identifying sensitive periods when changes in parenting and peer factors are associated with changes in adolescent alcohol and marijuana use
PURPOSE/OBJECTIVE:There are well-established associations between parental/peer relationships and adolescent substance use, but few longitudinal studies have examined whether adolescents change their substance use in response to changes in their parents' behavior or peer networks. We employ a within-person change approach to address two key questions: Are changes in parenting and peer factors associated with changes in adolescent marijuana and alcohol use? Are there sensitive periods when changes in parenting and peer factors are more strongly associated with changes in adolescent marijuana and alcohol use? METHODS:We analyzed longitudinal data collected annually on 503 boys, ages 13-19, recruited from Pittsburgh public schools. Questionnaires regarding parental supervision, negative parenting practices, parental stress, physical punishment, peer delinquency, and peer drug use were administered to adolescents and their caretakers. Alcohol and marijuana use were assessed by a substance use scale adapted from the National Youth Survey. RESULTS:Reductions in parental supervision and increases in peer drug use and peer delinquency were associated with increases in marijuana frequency, alcohol frequency, and alcohol quantity. Increases in parental stress were associated with increases in marijuana and alcohol frequency. The magnitudes of these relationships were strongest at ages 14-15 and systematically decreased across adolescence. These associations were not due to unmeasured stable confounders or measured time-varying confounders. CONCLUSIONS:Reducing or mitigating changes in parenting and peer risk factors in early adolescence may be particularly important for preventing substance use problems as adolescents transition into young adulthood.
PMID: 32915245
ISSN: 1433-9285
CID: 4589632
Assessment of the impact of implementation of a zero-blood alcohol concentration law in Uruguay on moderate/severe injury and fatal crashes: a quasi-experimental study
BACKGROUND AND AIMS/OBJECTIVE:Debates about lowering the blood alcohol concentration (BAC) limit for drivers are intensifying in the United States and other countries, and the World Health Organization recommends the limit for adults should be 0.05%. In January 2016, Uruguay implemented a law setting zero-BAC limit for all drivers. This aimed to assess the effect of this policy on the frequency of moderate/severe-injury and fatal traffic crashes. DESIGN/METHODS:A quasi experimental study in which a synthetic control model was used with controls consisting of local areas in Chile as the counterfactual for outcomes in Uruguay, matched across population counts and pre-intervention period outcomes. Sensitivity analyses were also conducted. SETTING/METHODS:Uruguay and Chile. CASES/METHODS:Panel data with crash counts by outcome per locality-month (2013-2017). INTERVENTION AND COMPARATOR/UNASSIGNED:A zero-blood alcohol concentration law implemented 9 Jan 2016 in Uruguay, alongside a continued 0.03g/dL BAC threshold in Chile. MEASUREMENTS/METHODS:Per capita moderate/severe injury (i.e., moderate or severe), severe injury, and fatal crashes (2016-2017). FINDINGS/RESULTS:Our base synthetic control model results suggested a reduction in fatal crashes at 12 months (20.9%; p-value=0.018, 95% CI: [-0.340, -0.061]). Moderate-/severe-injury crashes did not decrease significantly (10.2%, p=0.312 [-.282, .075]). The estimated effect at 24 months was smaller and with larger confidence intervals for fatal crashes (14%; p =0.048 [-.246, -.026]) and largely unchanged for moderate/severe-injury crashes (-9.4%, p=.302 [-.248, .075]). Difference-in-differences analyses yielded similar results. As a sensitivity test, a synthetic control model relying on an inferior treatment-control match pre-intervention (measured by mean squared error) yielded similar sized differences that were not statistically significant. CONCLUSIONS:Implementation of a law setting a zero blood-alcohol concentration threshold for all drivers in Uruguay appears to have resulted in a reduction in fatal crashes in the following 12 months and 24 months.
PMID: 32830394
ISSN: 1360-0443
CID: 4575052
COVID-19 During the Opioid Epidemic - Exacerbation of Stigma and Vulnerabilities
PMID: 32277731
ISSN: 1748-0361
CID: 4403182
Features of the Energy Spectrum of Cosmic Rays above 2.5×10^{18} eV Using the Pierre Auger Observatory
We report a measurement of the energy spectrum of cosmic rays above 2.5×10^{18} eV based on 215 030 events. New results are presented: at about 1.3×10^{19} eV, the spectral index changes from 2.51±0.03(stat)±0.05(syst) to 3.05±0.05(stat)±0.10(syst), evolving to 5.1±0.3(stat)±0.1(syst) beyond 5×10^{19} eV, while no significant dependence of spectral features on the declination is seen in the accessible range. These features of the spectrum can be reproduced in models with energy-dependent mass composition. The energy density in cosmic rays above 5×10^{18} eV is [5.66±0.03(stat)±1.40(syst)]×10^{53} erg Mpc^{-3}.
PMID: 33016715
ISSN: 1079-7114
CID: 5910932
Three poems on Covid-19 [Poem]
"As the lockdowns lift" -- "Here where the valley fans the wind" -- "What if, while working"
ORIGINAL:0015182
ISSN: n/a
CID: 4905022
Breaching Trust: A Qualitative Study of Healthcare Experiences of People Who Use Drugs in a Rural Setting
Background: Increased drug use has disproportionately impacted rural areas across the U.S. People who use drugs are at risk of overdose and other medical complications, including infectious diseases. Understanding barriers to healthcare access for this often stigmatized population is key to reducing morbidity and mortality, particularly in rural settings where resources may be limited. Methods: We conducted 20 semi-structured interviews with people who use drugs, including 17 who inject drugs, in rural southern Illinois between June 2018 and February 2019. Interviews were analyzed using a modified grounded theory approach where themes are coded and organized as they emerge from the data. Results: Participants reported breaches of trust by healthcare providers, often involving law enforcement and Emergency Medical Services, that dissuaded them from accessing medical care. Participants described experiences of mistreatment in emergency departments, with one account of forced catheterization. They further recounted disclosures of protected health information by healthcare providers, including communicating drug test results to law enforcement and sharing details of counseling sessions with community members without consent. Participants also described a hesitancy common among people who use drugs to call emergency medical services for an overdose due to fear of arrest. Conclusion: Breaches of trust by healthcare providers in rural communities discouraged people who use drugs from accessing medical care until absolutely necessary, if at all. These experiences may worsen healthcare outcomes and further stigmatize this marginalized community. Structural changes including reforming and clarifying law enforcement's role in Emergency Departments as well as instituting diversion policies during arrests may help rebuild trust in these communities. Other possible areas for intervention include stigma training and harm reduction education for emergency medicine providers, as well as developing and implementing referral systems between Emergency Departments and local harm reduction providers and medically assisted drug treatment programs.
PMCID:8022503
PMID: 33869521
ISSN: 2297-7775
CID: 4848162
Lean and deep models for more accurate filtering of SNP and INDEL variant calls
SUMMARY:We investigate convolutional neural networks (CNNs) for filtering small genomic variants in short-read DNA sequence data. Errors created during sequencing and library preparation make variant calling a difficult task. Encoding the reference genome and aligned reads covering sites of genetic variation as numeric tensors allows us to leverage CNNs for variant filtration. Convolutions over these tensors learn to detect motifs useful for classifying variants. Variant filtering models are trained to classify variants as artifacts or real variation. Visualizing the learned weights of the CNN confirmed it detects familiar DNA motifs known to correlate with real variation, like homopolymers and short tandem repeats (STR). After confirmation of the biological plausibility of the learned features we compared our model to current state-of-the-art filtration methods like Gaussian Mixture Models, Random Forests and CNNs designed for image classification, like DeepVariant. We demonstrate improvements in both sensitivity and precision. The tensor encoding was carefully tailored for processing genomic data, respecting the qualitative differences in structure between DNA and natural images. Ablation tests quantitatively measured the benefits of our tensor encoding strategy. Bayesian hyper-parameter optimization confirmed our notion that architectures designed with DNA data in mind outperform off-the-shelf image classification models. Our cross-generalization analysis identified idiosyncrasies in truth resources pointing to the need for new methods to construct genomic truth data. Our results show that models trained on heterogenous data types and diverse truth resources generalize well to new datasets, negating the need to train separate models for each data type. AVAILABILITY AND IMPLEMENTATION:This work is available in the Genome Analysis Toolkit (GATK) with the tool name CNNScoreVariants (https://github.com/broadinstitute/gatk). SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.
PMID: 31830260
ISSN: 1367-4811
CID: 4841902
Rural risk environments, opioid-related overdose, and infectious diseases: A multidimensional, spatial perspective
BACKGROUND:Much remains unknown in rural risk environments, despite a growing crisis in these areas. We adapt a risk environment framework to characterize rural southern Illinois and describe the relations of risk environments, opioid-related overdose, HIV, Hepatitis C, and sexually transmitted infection rates between 2015 and 2017. METHODS:Over two dozen risk environment variables are summarized across zip-code (n = 128) or county levels (n = 16) based on availability and theoretical relevance. We calculate data attribute associations and characterize spatial and temporal dimensions of longitudinal health outcomes and the rural risk environment. We then use a "regional typology analysis" to generate data-driven risk regions and compare health outcomes. RESULTS:Pervasive risk hotspots were identified in more populated locales with higher rates of overdose and HCV incidence, whereas emerging risk areas were isolated to more rural locales that had experienced an increase in analgesic opiate overdoses and generally lacked harm-reduction resources. At-risk areas were characterized with underlying socioeconomic vulnerability but in differing ways, reflecting a nuanced and shifting structural risk landscape. CONCLUSIONS:Rural risk environment vulnerabilities and associated opioid-related health outcomes are multifaceted and spatially heterogeneous. More research is needed to better understand how refining geographies to more precisely define risk can support intervention efforts and further enrich investigations of the opioid epidemic.
PMID: 32513621
ISSN: 1873-4758
CID: 4841852
Police killings of Black people and rates of sexually transmitted infections: a cross-sectional analysis of 75 large US metropolitan areas, 2016
OBJECTIVES:Emerging literature shows that racialised police brutality, a form of structural racism, significantly affects health and well-being of racial/ethnic minorities in the USA. While public health research suggests that structural racism is a distal determinant of sexually transmitted infections (STIs) among Black people, no studies have empirically linked police violence to STIs. To address this gap, our study measures associations between police killings and rates of STIs among Black residents of US metropolitan statistical areas (MSAs). METHODS:This cross-sectional ecological analysis assessed associations between the number of Black people killed by police in 2015 and rates of primary and secondary syphilis, gonorrhoea and chlamydia per 100 000 Black residents of all ages in 2016 in 75 large MSAs. Multivariable models controlled for MSA-level demographic and socioeconomic characteristics, police expenditures, violent crime, arrest and incarceration rates, insurance rates and healthcare funding. RESULTS:In 2015, the median number of Black people killed by police per MSA was 1.0. In multivariable models, police killings were positively and significantly associated with syphilis and gonorrhoea rates among Black residents. Each additional police killing in 2015 was associated with syphilis rates that were 7.5% higher and gonorrhoea rates that were 4.0% higher in 2016. CONCLUSIONS:Police killings of Black people may increase MSA-level risk of STI infections among Black residents. If future longitudinal analyses support these findings, efforts to reduce STIs among Black people should include reducing police brutality and addressing mechanisms linking this violence to STIs.
PMCID:7377537
PMID: 31444277
ISSN: 1472-3263
CID: 4840622
