Three Essays on Health Economics and Policy Evaluation

This dissertation consists of three essays on the U.S. Health care policy. Each paragraph below refers to the three abstracts for the three chapters in this dissertation, respectively. I provide quantitative evidence on how much Prescription Drug Monitoring Programs (PDMPs) affects the retail opioid prescribing behaviors. Using the American Community Survey (ACS), I retrieve county-level high dimensional panel data set from 2010 to 2017. I employ three separate identification strategies: difference-in-difference, double selection post-LASSO, and spatial difference-in-difference. I compare how the retail opioid prescribing behaviors of counties, that are mandatory for prescribers to check the PDMP before prescribing controlled substances (must-access PDMPs), vary from the counties where such a PDMP check is voluntary. I find must-access PDMP reduces about seven retail opioid prescriptions dispensed per 100 persons per year in each county. But, when I compare must-access PDMPs counties with bordering counties without such law, I find a reduction of three retail opioid prescriptions dispensed per 100 persons per year suggesting the possibility of spillovers of retail opioid prescribing behaviors. As of 2019, all U.S. states, except Missouri, have enacted voluntary Prescription Drug Monitoring Programs (PDMPs). In response to the relatively low uptake of voluntary access, several states have strengthened their PDPMs by requiring providers to access information regarding prescription drug use under certain circumstances. These “must-access” PDPMs require states to view a patient\u27s prescription history to facilitate the detection of suspicious prescription and utilization behaviors. This paper develops causal evidence of the effectiveness of “must-access PDPM laws in reducing prescription opioid overdose death rates relative to voluntary PDMP states. I find that PDMPs are ineffective in reducing prescription opioid overdose deaths overall, but the effects are heterogeneous across states with “must-access” PDMP states. I find that marijuana and naloxone access laws, poverty level, income, and education confound the impact of must-access PDMPs on prescription opioid overdose deaths. The optional provision of Medicaid expansion, through the Affordable Care Act (ACA), has triggered a national debate among diverse stakeholders regarding the impacts of Medicaid coverage on various dimensions of public health, costs, and benefits. Randomized experiments like the Rand Health Insurance Experiment and the Oregon Health Insurance Experiment have generated some credible estimates of the average treatment effects of insurance access. However, identical policy interventions can have heterogeneous effects on different subpopulations. This paper uses data from the Oregon Health Insurance Experiment to estimate the heterogeneous treatment effects of access to Medicaid on health care utilization, preventive care utilization, financial strain, and self-reported physical and mental health. I detect heterogeneous treatment effects using a cluster-robust generalized random forest, a causal machine learning approach. I find that the impact of Medicaid is more pronounced among relatively older non-elderly and poorer households, consistent with standard adverse selection theory. Furthermore, I implement the “efficient policy learning, another machine learning strategy, to identify policy changes that prioritize providing Medicaid coverage to the subgroups that are likely to benefit the most. On average, the proposed reforms would improve the average probability of outpatient visits, preventive care use, overall health outcomes, having a personal doctor and clinic, and happiness by a range of 2% to 9% over a random assignment baseline. These findings help design Medicaid Section 1115 waiver

Linking Illness to Food: Summary of a Workshop on Food Attribution

To identify and prioritize effective food safety interventions, it is critical not only to identify the pathogens responsible for illness, but also to attribute cases of foodborne disease to the specific food vehicle responsible. A wide variety of such “food attribution” approaches and data are used around the world, including the analysis of and extrapolation from outbreak and other surveillance data, case-control studies, microbial subtyping and source-tracking methods, and expert judgment, among others. The Food Safety Research Consortium sponsored the Food Attribution Data Workshop in October 2003 to discuss the virtues and limitations of these approaches and to identify future options for the collection of food attribution data in the United States. This discussion paper summarizes workshop discussions and identifies challenges that affect progress in this critical component of a risk-based approach to improving food safety.foodborne illness, food attribution, outbreaks, case-control studies, microbial fingerprinting, microbial subtyping, FoodNet

Research utility of the National Violent Death Reporting System: a scoping review

Background To better understand and prevent suicide and homicide, the National Center for Injury Prevention and Control of the US Centers for Disease Control and Prevention launched the National Violent Death Reporting System (NVDRS) in six states in 2002. As of 2018, the NVDRS has been expanded to include all 50 states, the District of Columbia and Puerto Rico. The purpose of this review was to assess the research utility of the NVDRS based on studies indexed in major bibliographical databases. Methods We performed a scoping review of published studies that were based on data from the NVDRS, identified by searching six electronic databases: PubMed, EMBASE, Google Scholar, OVID, Scopus, and Web of Science. We examined the time trend of annual NVDRS-based research output, generated a word cloud using the keywords listed in the publications, and mapped the knowledge domains covered by NVDRS-based studies. Results Our review included a total of 150 studies published between 2005 and 2018. There was a marked increase in the annual number of NVDRS-based publications, with 120 (80.0%) of the 150 studies published between 2011 and 2018. Overall, 104 (69.3%) studies focused on suicide and 39 (26.0%) on homicide. Of the included studies, 100 (66.7%) were descriptive epidemiology, 31 (20.7%) were risk factor analyses, 9 (6.0%) were evaluations, 7 (4.7%) were trend analyses, and 4 (2.7%) were data quality assessments. Knowledge domain mapping identified two major clusters of studies, one on suicide and the other on homicide. The cluster on suicide was commonly linked to “circumstance,” “alcohol” and “substance abuse” and the cluster on homicide was commonly linked to “firearm,” “injury,” and “gang.” The two clusters were interlinked to overlapping networks of keywords, such as “firearm” and “mental health problem.” Conclusions Research utility of the NVDRS has increased considerably in recent years. Studies based on data from the NVDRS are clustered in two knowledge domains – suicide and homicide. The vast potential of the NVDRS for violence research and prevention remains to be fully exploited

Modeling Precipitation, Acute Gastrointestinal Illness, and Environmental Factors in North Carolina, USA

Increasing intensity and frequency of extreme weather events due to climate change underscores the importance of understanding the influence of hydroclimatic variability on health. Meteorological drivers affect rates of acute gastrointestinal illness (AGI), but the association between precipitation and AGI, the sensitivity to modeling decisions, and the effects of sociodemographic and environmental risk factors are not well characterized. Furthermore, methodological differences may reduce inter-study comparability and can affect model estimates.In this dissertation, we reviewed the methodologies of recent time series AGI-weather studies, including outcome and exposure variables, data sources, spatiotemporal aggregation, and model specification. To investigate the sensitivity of the association between AGI and precipitation to exposure definitions and effect measure modification (EMM), we used AGI emergency department (ED) visit and weather data (2008-2015) from North Carolina (NC) to develop daily, ZIP code-level quasi-Poisson generalized linear models and distributed lag models. We compared multiple precipitation metrics: absolute (total precipitation), extreme (90th, 95th, and 99th percentiles with and without zero-precipitation days), and antecedent (cumulative wet-dry days; 8-week wet-dry periods). We assessed for potential EMM by physiographic region, the density of hogs in concentrated animal feeding operations (CAFOs), and percent of population on private drinking water wells.Depending on exposure definition, we observed an overall cumulative decrease of 1-18% in AGI ED rates following extreme precipitation events (over 0-7 days), with stronger effects associated with heavier rainfall, and a 2% (95% CI: 1.02, 1.03) increase after antecedent (8-week) wet periods. Inverse statewide results following extreme precipitation—dominated by the demographic weight of urban centers in the Piedmont region—were consistent with dilution effects posited by the concentration-dilution hypothesis but obscured dramatic sub-state variation. While EMM by private wells was inconclusive, region and hog density strongly modified the associations observed, with increased AGI ED rates following 95th percentile precipitation in the mountains (18%), coastal plains (19%), and areas exposed to hog CAFOs (7-15%). Our results reveal the vulnerability of mountainous, coastal, and CAFO-impacted areas in NC to rainfall-exacerbated AGI risk. This dissertation highlights the hazards of data aggregation and importance of precipitation exposure definitions and effect measure modification when modeling climate-health relationships.Doctor of Philosoph

2014 EIS Conference

63rd EIS Conference, April 28-May 1, 2014 at-a-glance schedule -- EIS Alumni Association -- Preface -- Scientific Program Committee -- General Information -- Instructions for Completing Online Conference Evaluations -- 2014 EIS Conference Schedule -- Awards: 2014 Award Committee Members, Awards Presented at the 2013 Conference, Stephen B. Thacker EIS Champion Award, Iain C. Hardy Awards, 1996\ue2\u20ac\u201c2013, Alexander D. Langmuir Prize Manuscripts, 1966\ue2\u20ac\u201c2013, Alexander D. Langmuir Lectures, 1972\ue2\u20ac\u201c2013, Distinguished Friend of EIS Awards, 1984\ue2\u20ac\u201c2013, Donald C. Mackel Memorial Awards, 1987\ue2\u20ac\u201c2013, J. Virgil Peavy Memorial Awards, 2003\ue2\u20ac\u201c2013, Paul C. Schnitker International Health Award, 1995\ue2\u20ac\u201c2013, James H. Steele Veterinary Public Health Award, 1999\ue2\u20ac\u201c2013, Outstanding Poster Presentation Award, 1986\ue2\u20ac\u201c2013, Philip S. Brachman Awards, 1983\ue2\u20ac\u201c2013, Mitch Singal Excellence in Occupational and Environmental Health Award, 2010\ue2\u20ac\u201c2013 -- 2014 Conference Sessions: Session A: Stephen B. Thacker Opening Session, Concurrent Session B1: Antimicrobial Use and Resistance, Concurrent Session B2: Environmental Health, Special Session: Novel Viruses/Pandemic Threats: Influenza and MERS Coronavirus, Poster Symposium I, Concurrent Session C1: Vaccine Preventable Diseases in the U.S., Concurrent Session C2: Chronic Disease Prevention, Concurrent Session D1: Zoonoses, Concurrent Session D2: Tuberculosis, Concurrent Session E1: Injury Prevention, Concurrent Session E2: STDs/HIV, Special Session: Creative Solutions for Outbreak Data Management and Contact Tracing with Epi InfoTM: Viral Hemorrhagic Fever Outbreaks and Beyond, Poster Symposium II, Concurrent Session F1: Foodborne Diseases, Concurrent Session F2: Occupational Safety and Health, Concurrent Session G1: Vectorborne and Parasitic Diseases, Concurrent Session G2: Child and Adolescent Health, Concurrent Session H1: Vaccine Preventable Diseases Worldwide, Concurrent Session H2: Maternal and Child Health, Special Session: EIS\ue2\u20ac\u201dChallenges and Opportunities in Epidemiology Training, Concurrent Session I1: Global Health, Concurrent Session I2: Health Care, Session J, Alexander D. Langmuir Lecture and Reception, Session K, International Night, Session L, Mackel Award Finalists, Session M, Peavy Award Finalists, Special Session: Syria Crisis: Epidemiology of Civil War and Refugee Crisis, Concurrent Session N1: Respiratory Diseases, Concurrent Session N2: Hepatitis, Award Presentations, Session O: Late-Breaking Reports -- EIS Officers, Class of 2012 -- EIS Officers, Class of 2013 -- Incoming EIS Officers, Class of 2014 -- Index of EIS Officer Presenters.Surveillance and InvestigationInfectious Diseas

PREDICTING SELF-HARM AND IDENTIFYING CAUSAL RISK FACTORS AMONG ADOLESCENTS WHO HAVE HAD CONTACT WITH U.S. CHILD PROTECTIVE SERVICES

Purpose: Examine self-harm among adolescents following an investigation by Child Protective Services (CPS) for maltreatment, validate a predictive model, and identify modifiable causal risk factors. Methods: Data came from the second National Survey of Child and Adolescent Well-being cohort – a nationally representative, longitudinal survey. Following multiple imputation of missing data, descriptive statistics and multivariable logistic regression accounting for the complex survey design were used to examine the odds of self-harm. A hold-out random forest was used to predict self-harm based on a large (>1,500) set of variables encompassing individual, family, and environmental information. Among the significant predictors, three were identified as modifiable by CPS: feelings of worthlessness, presence of supportive adults, and parental psychological aggression. For each, propensity score weighting (PSW) was used to control for observed confounders and the average effect of exposure among the exposed (ATT) was estimated using weighted logistic regression. Results: The prevalence among older adolescents (15-17 years) remained stable over time at ~10% while among younger adolescents (11-14 years) it declined from 13% to 6% to 3%; 5% of adolescents reported self-harm at multiple survey waves. Native American and Asian/Pacific Islander youth were more likely to report self-harm at multiple waves: odds ratio 6.88 (2.02-23.5) compared to White non-Hispanic. The final predictive model had an AUC of 0.72. Prior self-harm was the strongest predictor, with internalizing problems, suicidal ideation, depression, and psychiatric medication following. Other predictors included trauma symptoms, parental monitoring and maltreatment, running away from home, and having supportive adults. For parental psychological aggression, the PSW odds ratios comparing low and high aggression to none were 0.93 (0.35-2.45) and 1.25 (0.55-2.82), respectively. For feelings of worthlessness it was 1.73 (0.70-4.27), and for supportive adults 0.58 (0.28-1.19). Due to the weighting the effective sample size was substantially reduced, which may have affected statistical power. Conclusions: Further research should explore why Native American and Asian adolescents experienced more persistent self-harm, and potentially design culturally appropriate interventions. Given the modest prediction accuracy, using a machine learning algorithm to estimate risk for individuals within CPS is not currently recommended. However, fostering supportive and encouraging relationships with adults may play an important part in preventing self-harm among adolescents with CPS contact

All-Male Groups in Asian Elephants: A Novel, Adaptive Social Strategy in Increasingly Anthropogenic Landscapes of Southern India

Male Asian elephants are known to adopt a high-risk high-gain foraging strategy by venturing into agricultural areas and feeding on nutritious crops in order to improve their reproductive fitness. We hypothesised that the high risks to survival posed by increasingly urbanising and often unpredictable production landscapes may necessitate the emergence of behavioural strategies that allow male elephants to persist in such landscapes. Using 1445 photographic records of 248 uniquely identified male Asian elephants over a 23-month period, we show that male Asian elephants display striking emergent behaviour, particularly the formation of stable, long-term all-male groups, typically in non-forested or human-modified and highly fragmented areas. They remained solitary or associated in mixed-sex groups, however, within forested habitats. These novel, large all-male associations, may constitute a unique life history strategy for male elephants in the high-risk but resource-rich production landscapes of southern India. This may be especially true for the adolescent males, which seemed to effectively improve their body condition by increasingly exploiting anthropogenic resources when in all-male groups. This observation further supports our hypothesis that such emergent behaviours are likely to constitute an adaptive strategy for male Asian elephants that may be forced to increasingly confront anthropogenically intrusive environments

Birth, death and taxis: North Atlantic right whales in the twenty-first century

Twenty two years of North Atlantic right whale data were analyzed. Several measures indicate reproduction in North Atlantic right whales is in a decline. Calving intervals have increased from about 3.3 years in the 1980\u27s to over 5 years, and the age of first parturition is estimated to be 11 years. Females may lose calves before they are detected, artificially increasing the apparent age of first parturition and possibly affecting estimates of calving interval. Northern feeding habitat use patterns do not appear to affect reproduction. Right whale mortality data was analyzed by age, sex, and habitat use patterns. A total of 46% of all confirmed mortalities are due to human activities. The characteristics of animals presumed dead from long gaps in sighting histories match known anthropogenic mortalities, but not those attributable to natural mortality. Sighting probabilities vary significantly by age, habitat-use pattern and individual. Tag-recapture models of extremely small populations are vulnerable to such heterogeneity, since animals missing for extended periods can create spurious estimates of survivorship, growth rates, and population viability. An analysis of satellite-tracked movements of two adult female right whales in the Gulf of Maine, one with a calf and one without, examined relationships between whale movements and sea-surface temperature, distance to front, frontal density, depth, and bottom slope. The cow was primarily influenced by sea surface temperature and the non-calving adult female was primarily influenced by the distance to fronts . The movements of the cow may reflect the immature thermoregulatory requirements of her calf. In contrast, the movements of the non-calving female appear to be independent of temperature, and may indicate the use of frontal boundaries for navigation and food-finding. Fishing entanglements and collisions with ships are approximately equally responsible for nearly half of all right whale deaths. There are large gaps in the data that inhibit informed mitigation. Right whales face serious problems, but as a long-lived species, a decadal period crisis does not necessarily spell extinction

Molecular Approaches in the Diagnosis of Diarrhoeal Disease in Children from Rural Gambia

Enteroaggregative Escherichia coli (EAEC) is a genetically diverse enteric pathogen that causes growth faltering among children, acute and chronic diarrhoea among children and adults living in both industrialised and low income countries. The German outbreak of EAEC-Shiga-toxin-E. coli in 2011 resulted in over 4000 confirmed cases of diarrhoea with over 54 fatalities in 14 European countries as well as United State of America and Canada. Several studies conducted in sub-Sahara Africa (SSA), Latin America and Asia countries have identified EAEC more frequently than any other bacterial pathogens. In SSA, case fatality due to EAEC is not well documented but the morbidity rate particularly among younger children is huge. Studies conducted in Senegal, Central-Africa-Republic and Tanzania showed that EAEC were endemic among HIV-positive patients with diarrhoea. Few studies from SSA have reported distribution of antimicrobial resistance pattern of EAEC. The Global Enteric Multisite Study (GEMS), a three-year case-control study conducted in seven African and Asia countries, showed that the prevalence of EAEC was higher among children with no diarrhoea (463/741, 62.5%) compared to children with diarrhoea (278/741, 37.5%). The aim of this retrospective analytical study nested to GEMS is to explore other molecular approaches that identify infectious EAEC and to show the genetic diversity and antimicrobial resistant pattern of EAEC. Study design of the first approach involves unmatched case-control 428 (157 cases and 271 controls) EAEC isolates that were examined by polymerase chain reaction (PCR) for the presence of 21 common EAEC virulence genes. This investigation implicated plasmid-encoded toxin (pet), AAF/1 fimbrial subunit (aggA) and hexosyltransferase homolog (capU) to be associated with diarrhoea in infants. In addition, two other virulence genes; Shigella exracellular protease A (sepA) and EAEC-heat-stable enterotoxin 1 (EAST1) were implicated in the EAEC that cause diarrhoea among children under 5 years old. The second approach utilised qualitative PCR (TaqMan-qPCR) method to assess the use of bacterial load diagnostic tool to diagnose infectious EAEC on selected matched case-control 160 (80 cases and 80 controls) EAEC isolates. Two biomarker genes, aatA and aaiC were the target in this study and both resulted in higher rate of higher bacterial load in controls (58/80 [72.5%]) compared to cases 48/80 [60%]), p – value 0.096. The third approach explored bacterial biofilm formation to diagnose infectious EAEC on 400 unmatched cases (150) and controls (250) EAEC isolates. Infectious EAEC produces biofilm to consolidate its colonisation in the host and damage to the tissue. The result of this study showed higher proportion of biofilm-producing EAEC in controls (61%) compared to cases (39%). However, biofilm-producing EAEC isolates that has aggR gene combined with one or all of the following virulence genes aatA, Aap, Orf3 and Orf61 revealed strong association with diarrhoea. Investigation into the antimicrobial resistant EAEC on the same 400 unmatched EAEC isolates revealed multi-drug resistant (MDR) EAEC infection as a significant problem among infants in the Gambia. MDR EAEC strains are almost equally distributed among cases and controls, and high (>71%) rate of resistant to Ampicillin, Sulphamethoxazole-trimethoprim and Tetracycline, and moderate (25%) rate of resistant to Chloramphenicol among study children. However, over ninety-four percent of the Gambia EAEC strains are susceptible to Cefotaxime, Ceftazidime, Ceftriaxone, Ciprofloxacin, Gentamicin and Amoxicillin-clavulanic acid. Additionally, result of whole genome sequencing (WGS) on 50 randomly selected EAEC isolates showed average 94% concordance of resistance genes with phenotypic disc diffusion method. This thesis provides detailed initial description and exploration of virulence genes associated with EAEC strains circulating in the rural Gambia and has revealed the likely biomarker genes to target in the diagnosis of infectious EAEC that cause diarrhoea in infant