Sandro Galea

Massachusetts Department of Public Health, Boston, Massachusetts, United States

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Publications (758)2287.49 Total impact

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    ABSTRACT: The majority of the world’s population now lives in urban areas. Mental health problems are known to be prevalent in the rapidly urbanizing megacities of low-income countries and range at the third place in the list of the ten leading factors of the burden of disease in low-income countries in a projection for 2030. Urbanization is most pronounced in Asia having the largest number of megacities, that is, cities with more than 10 million inhabitants worldwide. There are several characteristics of rapidly urbanizing megacities of low-income countries that can contribute to poor mental health, including, social segregation, lack of infrastructure, and exposure to ongoing adversity and life stressors. However, there is a paucity of data about the relation between characteristics of urban environments and mental health. Using a spatial epidemiological approach, this paper assessed factors linked to mental well-being in the slums of Dhaka, the second fastest growing megacity in the world, which currently accommodates an estimated population of more than 15 million, including at least 3.4 million slum dwellers. Furthermore, we investigated the spatial variability of mental well-being for different population groups in several slums of Dhaka. Specifically, we hypothesized (i) that socio-ecological environmental characteristics of informal settlements are associated with the mental well-being of slum dwellers after adjusting for personal factors such as age, gender and other diseases. We further investigated the hypotheses (ii) that mental well-being shows a significant spatial pattern (that is, spatial clustering) for different population groups, and (iii) that spatially auto-correlated socio-ecological factors relate to the spatial patterns of mental well-being.
    Spatial Analysis in Health Geography, Edited by Antonio Páez, Eric Delmelle, Pavlos Kanaroglou, 10/2015: chapter 9; Ashgate Publishing, Ltd.., ISBN: 147241621X, 9781472416216
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    ABSTRACT: Posttraumatic stress disorder (PTSD) is comorbid with major depressive disorder (MDD; Kessler et al., 1995) and generalized anxiety disorder (GAD; Brown et al., 2001). We aimed to (1) assess discrete patterns of post-trauma PTSD-depression-GAD symptoms using latent profile analyses (LPAs), and (2) assess covariates (gender, income, education, age) in defining the best fitting class solution. The PTSD Checklist (assessing PTSD symptoms), GAD-7 scale (assessing GAD symptoms), and Patient Health Questionnaire-9 (assessing depression) were administered to 1266 trauma-exposed Ohio National Guard soldiers. Results indicated three discrete subgroups based on symptom patterns with mild (class 1), moderate (class 2) and severe (class 3) levels of symptomatology. Classes differed in symptom severity rather than symptom type. Income and education significantly predicted class 1 versus class 3 membership, and class 2 versus class 3. In conclusion, there is heterogeneity regarding severity of PTSD-depression-GAD symptomatology among trauma-exposed soldiers, with income and education predictive of class membership. Copyright © 2015 Elsevier Ltd. All rights reserved.
    Journal of Psychiatric Research 09/2015; 68:19-26. DOI:10.1016/j.jpsychires.2015.05.014 · 4.09 Impact Factor
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    ABSTRACT: Violence-related post-traumatic stress disorder (PTSD) remains a prevalent and disabling psychiatric disorder in urban areas. However, the most effective allocation of resources into prevention and treatment to reduce this problem is unknown. We contrasted the impact of two interventions on violence-related PTSD: (1) a population-level intervention intended to prevent violence (i.e., hot-spot policing), and (2) an individual-level intervention intended to shorten PTSD duration (i.e., cognitive-behavioral therapy-CBT). We used agent-based modeling to simulate violence and PTSD in New York City under four scenarios: (1) no intervention, (2) targeted policing to hot spots of violence, (3) increased access to CBT for people who suffered from violence-related PTSD, and (4) a combination of the two interventions. Combined prevention and treatment produced the largest decrease in violence-related PTSD prevalence: hot-spot policing plus a 50% increase in CBT for 5 years reduced the annual prevalence of violence-related PTSD from 3.6% (95% confidence interval = 3.5%, 3.6%) to 3.4% (3.3%, 3.5%). It would have been necessary to implement hot-spot policing or to increase CBT by 200% for 10 years for either intervention to achieve the same reduction in isolation. This study provides an empirically informed demonstration that investment in combined strategies that target social determinants of mental illness and provide evidence-based treatment to those affected by psychiatric disorders can produce larger reductions in the population burden from violence-related PTSD than either preventive or treatment interventions alone. However, neither hot-spot policing nor CBT, alone or combined, will produce large shifts in the population prevalence of violence-related PTSD.
    Epidemiology (Cambridge, Mass.) 09/2015; 26(5):681-689. DOI:10.1097/EDE.0000000000000350 · 6.18 Impact Factor
  • Ronald Bayer · Sandro Galea
    New England Journal of Medicine 08/2015; 373(6):499-501. DOI:10.1056/NEJMp1506241 · 54.42 Impact Factor
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    ABSTRACT: We review weighting adjustment methods for panel attrition and suggest approaches for incorporating design variables, such as strata, clusters, and baseline sample weights. Design information can typically be included in attrition analysis using multilevel models or decision tree methods such as the chi-square automatic interaction detection algorithm. We use simulation to show that these weighting approaches can effectively reduce bias in the survey estimates that would occur from omitting the effect of design factors on attrition while keeping the resulted weights stable. We provide a step-by-step illustration on creating weighting adjustments for panel attrition in the Galveston Bay Recovery Study, a survey of residents in a community following a disaster, and provide suggestions to analysts in decision-making about weighting approaches. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
    Statistics in Medicine 08/2015; DOI:10.1002/sim.6618 · 2.04 Impact Factor
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    ABSTRACT: The CHANGE (Cessation of Heroin: A Neighborhood Grounded Exploration) Study aimed to understand factors associated with the initiation and maintenance of sustained heroin cessation from the perspective of users themselves and specifically set out to document the correlates of natural recovery. The CHANGE Study was a case-control study conducted in New York City from 2009 to 2011. Cases were former heroin users, abstinent for 1-5 years in the past 5 years. Controls used heroin at least weekly during the past 5 years and were (1) continuous heroin users without a quit attempt of ≥2 weeks' duration or (2) relapsed heroin users who were currently using and had a quit attempt of ≥2 weeks' duration during the past 5 years. Recruitment and data collection methods are described along with limitations and a brief description of the study sample. In contrast to many studies of drug use and cessation, the CHANGE Study was designed to model success (i.e., initiation and maintenance of heroin cessation) and not failure.
    Journal of Urban Health 07/2015; DOI:10.1007/s11524-015-9973-0 · 1.94 Impact Factor
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    ABSTRACT: Adolescent use of marijuana is associated with adverse later effects, so the identification of factors underlying adolescent use is of substantial public health importance. The relationship between US state laws that permit marijuana for medical purposes and adolescent marijuana use has been controversial. Such laws could convey a message about marijuana acceptability that increases its use soon after passage, even if implementation is delayed or the law narrowly restricts its use. We used 24 years of national data from the USA to examine the relationship between state medical marijuana laws and adolescent use of marijuana. Using a multistage, random-sampling design with replacement, the Monitoring the Future study conducts annual national surveys of 8th, 10th, and 12th-grade students (modal ages 13-14, 15-16, and 17-18 years, respectively), in around 400 schools per year. Students complete self-administered questionnaires that include questions on marijuana use. We analysed data from 1 098 270 adolescents surveyed between 1991 and 2014. The primary outcome of this analysis was any marijuana use in the previous 30 days. We used multilevel regression modelling with adolescents nested within states to examine two questions. The first was whether marijuana use was higher overall in states that ever passed a medical marijuana law up to 2014. The second was whether the risk of marijuana use changed after passage of medical marijuana laws. Control covariates included individual, school, and state-level characteristics. Marijuana use was more prevalent in states that passed a medical marijuana law any time up to 2014 than in other states (adjusted prevalence 15·87% vs 13·27%; adjusted odds ratio [OR] 1·27, 95% CI 1·07-1·51; p=0·0057). However, the risk of marijuana use in states before passing medical marijuana laws did not differ significantly from the risk after medical marijuana laws were passed (adjusted prevalence 16·25% vs 15·45%; adjusted OR 0·92, 95% CI 0·82-1·04; p=0·185). Results were generally robust across sensitivity analyses, including redefining marijuana use as any use in the previous year or frequency of use, and reanalysing medical marijuana laws for delayed effects or for variation in provisions for dispensaries. Our findings, consistent with previous evidence, suggest that passage of state medical marijuana laws does not increase adolescent use of marijuana. However, overall, adolescent use is higher in states that ever passed such a law than in other states. State-level risk factors other than medical marijuana laws could contribute to both marijuana use and the passage of medical marijuana laws, and such factors warrant investigation. US National Institute on Drug Abuse, Columbia University Mailman School of Public Health, New York State Psychiatric Institute. Copyright © 2015 Elsevier Ltd. All rights reserved.
    The Lancet Psychiatry 07/2015; 2(7):601-608. DOI:10.1016/S2215-0366(15)00217-5
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    ABSTRACT: We assessed gun ownership rates in 2013 across the USA and the association between exposure to a social gun culture and gun ownership. We used data from a nationally representative sample of 4000 US adults, from 50 states and District of Columbia, aged >18 years to assess gun ownership and social gun culture performed in October 2013. State-level firearm policy information was obtained from the Brady Law Center and Injury Prevention and Control Center. One-third of Americans reported owning a gun, ranging from 5.2% in Delaware to 61.7% in Alaska. Gun ownership was 2.25-times greater among those reporting social gun culture (PR=2.25, 95% CI 2.02 to 2.52) than those who did not. In conclusion, we found strong association between social gun culture and gun ownership. Gun cultures may need to be considered for public health strategies that aim to change gun ownership in the USA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to
    Injury Prevention 06/2015; DOI:10.1136/injuryprev-2015-041586 · 1.94 Impact Factor
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    Sarah R Lowe · Sandro Galea
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    ABSTRACT: Mass shooting episodes have increased over recent decades and received substantial media coverage. Despite the potentially widespread and increasing mental health impact of mass shootings, no efforts to our knowledge have been made to review the empirical literature on this topic. We identified 49 peer-reviewed articles, comprised of 27 independent samples in the aftermath of 15 mass shooting incidents. Based on our review, we concluded that mass shootings are associated with a variety of adverse psychological outcomes in survivors and members of affected communities. Less is known about the psychological effects of mass shootings on indirectly exposed populations; however, there is evidence that such events lead to at least short-term increases in fears and declines in perceived safety. A variety of risk factors for adverse psychological outcomes have been identified, including demographic and pre-incident characteristics (e.g., female gender and pre-incident psychological symptoms), event exposure (e.g., greater proximity to the attack and acquaintance with the deceased), and fewer psychosocial resources (e.g., emotion regulation difficulties and lower social support). Further research that draws on pre-incident and longitudinal data will yield important insights into the processes that exacerbate or sustain post-incident psychological symptoms over time and provide important information for crisis preparedness and post-incident mental health interventions. © The Author(s) 2015.
    Trauma Violence & Abuse 06/2015; DOI:10.1177/1524838015591572 · 3.27 Impact Factor
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    ABSTRACT: Several studies have suggested strong associations between economic downturns and suicide mortality, but are at risk of bias due to unmeasured confounding. The rationale for our study was to provide more robust evidence by using a quasi- experimental design. We analysed 955 561 suicides occurring in the USA from 1980 to 2010 and used a broad index of economic activity in each US state to measure economic conditions. We used a quasi-experimental, fixed-effects design and we also assessed whether the effects were heterogeneous by demographic group and during periods of official recession. After accounting for secular trends, seasonality and unmeasured fixed characteristics of states, we found that an economic downturn similar in magnitude to the 2007 Great Recession increased suicide mortality by 0.14 deaths per 100 000 population [95% confidence interval (CI) 0.00, 0.28] or around 350 deaths. Effects were stronger for men (0.28, 95% CI 0.07, 0.49) than women and for those with less than 12 years of education (1.22 95% CI 0.83, 1.60) compared with more than 12 years of education. The overall effect did not differ for recessionary (0.11, 95% CI -0.02, 0.25) vs non- recessionary periods (0.15, 95% CI 0.01, 0.29). The main study limitation is the potential for misclassified death certificates and we cannot definitively rule out unmeasured confounding. We found limited evidence of a strong, population-wide detrimental effect of economic downturns on suicide mortality. The overall effect hides considerable heterogeneity by gender, socioeconomic position and time period. © The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.
    International Journal of Epidemiology 06/2015; DOI:10.1093/ije/dyv009 · 9.20 Impact Factor
  • Abdulrahman M El-Sayed · Sandro Galea
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    ABSTRACT: Although obesity continues to challenge the public's health, effective policy solutions are wanting. Borrowing from environmental protection efforts, we explored the potential for a "calorie offset" regulatory mechanism, which is similar to the carbon emission offsets used to curb greenhouse gas emissions, to mitigate the harmful health externalities of unhealthy food production. This approach might have a number of advantages over traditional policy tools, and warrants attention from health policymakers and industry alike. (Am J Public Health. Published online ahead of print June 11, 2015: e1-e3. doi:10.2105/AJPH.2015.302678).
    American Journal of Public Health 06/2015; 105(8):e1-e3. DOI:10.2105/AJPH.2015.302678 · 4.23 Impact Factor
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  • PLoS ONE 06/2015; 10(6):e0129169. DOI:10.1371/journal.pone.0129169 · 3.23 Impact Factor
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    ABSTRACT: Recent epidemiologic studies have shown that nonmedical use of prescription opioids (NMUPO) and major depression frequently co-occur. Comorbid forms of drug use and mental illness such as NMUPO and depression pose a greater disease burden than either condition alone. However, sociodemographic and substance use differences between individuals with either NMUPO or depression and those with comorbid conditions have not yet been fully investigated. Data came from the 2011 and 2012 National Survey on Drug Use and Health (NSDUH). Adolescents and adults were examined independently because of differences in screening for major depressive episodes (MDE). Weighted multinomial logistic regression investigated differences between persons with either past-year NMUPO (4.0%) or MDE (5.5%) and those with comorbid NMUPO and MDE (0.6%), compared to persons with neither condition. Females were more likely than males to report either MDE-alone and comorbid NMUPO and MDE, whereas adult men were marginally more likely to report NMUPO-alone (not significant among adolescents). Polydrug use and alcohol use disorders were more pronounced among those with comorbid NMUPO and MDE than persons with either NMUPO-alone or MDE-alone. Persons with independent and comorbid NMUPO and MDE were more likely to report lower income and unemployment versus employment. This study found that independent and comorbid NMUPO and MDE were disproportionately clustered with burdens of lower socioeconomic position, suggesting that a population-based approach to address NMUPO would target these social determinants of health, whereas a high-risk approach to prevention should be tailored to females experiencing MDE symptoms and polydrug users. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
    Drug and alcohol dependence 05/2015; DOI:10.1016/j.drugalcdep.2015.05.010 · 3.28 Impact Factor
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    ABSTRACT: Several individual-level factors are known to promote psychological resilience in the aftermath of disasters. Far less is known about the role of community-level factors in shaping postdisaster mental health. The purpose of this study was to explore the influence of both individual- and community-level factors on resilience after Hurricane Sandy. A representative sample of household residents ( N = 418) from 293 New York City census tracts that were most heavily affected by the storm completed telephone interviews approximately 13–16 months postdisaster. Multilevel multivariable models explored the independent and interactive contributions of individual- and community-level factors to posttraumatic stress and depression symptoms. At the individual-level, having experienced or witnessed any lifetime traumatic event was significantly associated with higher depression and posttraumatic stress, whereas demographic characteristics (e.g., older age, non-Hispanic Black race) and more disa
    PLoS ONE 05/2015; 10:e0125761. DOI:10.1371/journal.pone.0125761 · 3.23 Impact Factor
  • David S Fink · Sandro Galea
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    ABSTRACT: Traumatic events are ubiquitous exposures that interact with life course events to increase risk of acute psychopathology and alter mental health trajectories. While the majority of persons exposed to trauma experience mild to moderate psychological distress followed by a return to pre-trauma health, many persons exposed to trauma experience substantial distress that lasts for several years. Therefore, in an effort to understand why exposure to trauma can provoke such a range of reactions, we apply a life course approach that considers the complex accumulation and interaction of life experiences that range from social to biological factors, which occur over the life span-from gestation to death and across generations. We present this evidence in three categories: genetics and biology, individual exposures, and community experiences, followed by discussing challenges in existing research and directions for future study.
    Current Psychiatry Reports 05/2015; 17(5):566. DOI:10.1007/s11920-015-0566-0 · 3.05 Impact Factor
  • Bindu Kalesan · Sandro Galea
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    ABSTRACT: Firearm injuries are a major health problem contributing to significant morbidity and mortality. Depression is associated with increased risk of adverse health outcomes in trauma patients and those hospitalized for serious disorders. We examined the relation between preexisting depression and adverse hospital outcomes and related injury severity among adult (>16-years) firearm hospitalizations (FH). Using nationally representative Nationwide Inpatient Sample (2005 to 2011) and survey weighted multinomial logistic regression, we calculated odds ratios (OR) and 95% confidence intervals (95%CI) to determine the risk of care facility discharge and in-hospital mortality by pre-existing depression. Pre-existing depression was associated with a 3-fold risk of discharge to care facility (OR=2.91, 95%CI=2.57-3.30) and a 2-fold risk of in-hospital mortality (OR=2.05, 95%CI=1.69-2.47). ORs for risk of care facility discharge compared to routine discharge associated with depression among assault/legal-FH, unintentional-FH, suicide-FH and undetermined-FH was 2.73 (95%CI=2.23-3.33), 1.90 (95%CI=1.50-2.41), 1.52 (95%CI=1.26-1.83) and 2.42 (95%CI=1.60-3.67), while risk of inhospital mortality was 0.17 (95%CI=0.05-0.54), 0.60 (95%CI=0.28-1.29), 0.79 (95%CI=0.63-0.98) and 0.74 (95%CI=0.36-1.52). Lack of information regarding re-hospitalization due to the cross-sectional data. Persons with depression who were hospitalized due to firearm-related injury were less likely to survive than those without depression, and those discharged alive were at higher risk of discharge to a facility. Depression was associated with greater risk of discharge to facility among all intents, and lower risk of in-hospital mortality among assault- and suicide-FH. These findings are important considering the increasing numbers of non-fatal firearm hospitalizations and the associated increase in healthcare expenditure. Copyright © 2015 Elsevier B.V. All rights reserved.
    Journal of Affective Disorders 05/2015; 183. DOI:10.1016/j.jad.2015.05.010 · 3.71 Impact Factor
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    ABSTRACT: High rates of mental health (MH) problems have been documented among disaster relief workers. However, few workers utilize MH services, and predictors of service use among this group remain unexplored. The purpose of this study was to explore associations between predisposing, illness-related, and enabling factors from Andersen's behavioral model of treatment-seeking and patterns of service use among participants who completed at least one full day of cleanup work after the Deepwater Horizon oil spill and participated in home visits for the NIEHS GuLF STUDY (N = 8931). Workers reported on MH symptoms and whether they had used counseling or medication for MH problems since the oil spill. Hierarchical logistic regression models explored associations between predictors and counseling and medication use in the full sample, and type of use (counseling only, medication only, both) among participants who used either service. Analyses were replicated for subsamples of participants with and without symptom inventory scores suggestive of probable post-disaster mental illness. Having a pre-spill MH diagnosis, pre-spill service use, more severe post-spill MH symptoms, and healthcare coverage were positively associated with counseling and medication use in the full sample. Among participants who used either service, non-Hispanic Black race, pre-spill counseling, lower depression, and not identifying a personal doctor or healthcare provider were predictive of counseling only, whereas older age, female gender and pre-spill medication were predictive of medication only. The results were generally consistent among participants with and without probable post-disaster mental illness. The results suggest variability in which factors within Andersen's behavioral model are predictive of different patterns of service use among disaster relief workers. Copyright © 2015 Elsevier Ltd. All rights reserved.
    Social Science & Medicine 04/2015; 130. DOI:10.1016/j.socscimed.2015.02.009 · 2.56 Impact Factor
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    ABSTRACT: The present study investigated symptom relations between two highly comorbid disorders - posttraumatic stress disorder (PTSD) and generalized anxiety disorder (GAD) - by exploring their underlying dimensions. Based on theory and prior empirical research it was expected that the dysphoria factor of PTSD would be more highly related to GAD. As part of a longitudinal project of mental health among Ohio National Guard Soldiers, 1266 subjects were administered the Posttraumatic Stress Disorder Checklist (PCL) and Generalized Anxiety Disorder-7 scale (GAD-7). Confirmatory factor analyses (CFAs) were conducted to examine two models of PTSD and to determine which PTSD factors were more related to the GAD factor. The results indicate that the GAD factor was significantly more highly correlated with PTSD׳s dysphoria factor than with all other PTSD factors, including PTSD׳s reexperiencing factor, avoidance factor, and hyperarousal factor. Results indicate GAD was not significantly more highly correlated with numbing than most other factors of PTSD. The results are consistent with prior research. Implications of the results are discussed in regards to PTSD in DSM-5, comorbidity and diagnostic specificity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
    04/2015; 228(1). DOI:10.1016/j.psychres.2015.04.034
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    ABSTRACT: Only very few studies have investigated the geographic distribution of psychological resilience and associated mental health outcomes after natural or man made disasters. Such information is crucial for location-based interventions that aim to promote recovery in the aftermath of disasters. The purpose of this study therefore was to investigate geographic variability of (1) posttraumatic stress (PTS) and depression in a Hurricane Sandy affected population in NYC and (2) psychological vulnerability and resilience factors among affected areas in NYC boroughs. Cross-sectional telephone survey data were collected 13 to 16 months post-disaster from household residents (N = 418 adults) in NYC communities that were most heavily affected by the hurricane. The Posttraumatic Stress Checklist for DSM-5 (PCL-5) was applied for measuring posttraumatic stress and the nine-item Patient Health Questionnaire (PHQ-9) was used for measuring depression. We applied spatial autocorrelation and spatial regimes regression analyses, to test for spatial clusters of mental health outcomes and to explore whether associations between vulnerability and resilience factors and mental health differed among New York City's five boroughs. Mental health problems clustered predominantly in neighborhoods that are geographically more exposed towards the ocean indicating a spatial variation of risk within and across the boroughs. We further found significant variation in associations between vulnerability and resilience factors and mental health. Race/ethnicity (being Asian or non-Hispanic black) and disaster-related stressors were vulnerability factors for mental health symptoms in Queens, and being employed and married were resilience factors for these symptoms in Manhattan and Staten Island. In addition, parental status was a vulnerability factor in Brooklyn and a resilience factor in the Bronx. We conclude that explanatory characteristics may manifest as psychological vulnerability and resilience factors differently across different regional contexts. Our spatial epidemiological approach is transferable to other regions around the globe and, in the light of a changing climate, could be used to strengthen the psychosocial resources of demographic groups at greatest risk of adverse outcomes pre-disaster. In the aftermath of a disaster, the approach can be used to identify survivors at greatest risk and to plan for targeted interventions to reach them.
    International Journal of Health Geographics 04/2015; 14(16). DOI:10.1186/s12942-015-0008-6 · 2.62 Impact Factor

Publication Stats

17k Citations
2,287.49 Total Impact Points


  • 2015
    • Massachusetts Department of Public Health
      Boston, Massachusetts, United States
    • Boston University
      Boston, Massachusetts, United States
  • 2012–2015
    • McGill University
      • Department of Epidemiology, Biostatistics and Occupational Health
      Montréal, Quebec, Canada
    • University of Oxford
      • Department of Public Health
      Oxford, ENG, United Kingdom
  • 2002–2015
    • Columbia University
      • • Department of Epidemiology
      • • Teachers College
      New York, New York, United States
    • Harvard Medical School
      Boston, Massachusetts, United States
  • 2014
    • Boston Children's Hospital
      • Division of General Pediatrics
      Boston, Massachusetts, United States
  • 2005–2014
    • CUNY Graduate Center
      New York City, New York, United States
    • City University of New York - Hunter College
      Borough of Manhattan, New York, United States
  • 2004–2013
    • Gracie Square Hospital, New York, NY
      New York City, New York, United States
    • Complutense University of Madrid
      • Facultad de Psicología
      Madrid, Madrid, Spain
    • New York Presbyterian Hospital
      • Department of Emergency Medicine
      New York City, NY, United States
  • 2007–2012
    • Yale University
      • Department of Psychiatry
      New Haven, Connecticut, United States
    • New York State Psychiatric Institute
      New York City, New York, United States
  • 2005–2012
    • University of Michigan
      • Department of Epidemiology
      Ann Arbor, Michigan, United States
    • Concordia University–Ann Arbor
      Ann Arbor, Michigan, United States
  • 2011
    • City University of New York - John Jay College of Criminal Justice
      New York City, New York, United States
    • University of California, San Francisco
      • Division of Hospital Medicine
      San Francisco, CA, United States
    • George Mason University
      • Department of Geography and Geoinformation Science
      페어팩스, Virginia, United States
  • 2010
    • University of Haifa
      • School of Political Sciences
      Haifa, Haifa District, Israel
  • 2009–2010
    • Rush University Medical Center
      • Department of Behavioral Sciences
      Chicago, IL, United States
    • University of Washington Seattle
      • School of Social Work
      Seattle, WA, United States
  • 2001–2010
    • New York Academy of Medicine
      New York City, New York, United States
  • 2006–2009
    • University of California, Berkeley
      • Division of Epidemiology
      Berkeley, California, United States
    • Johns Hopkins University
      Baltimore, Maryland, United States
    • Cornell University
      • Department of Public Health
      Итак, New York, United States
    • San Francisco State University
      • Department of Health Education
      San Francisco, CA, United States
    • Beth Israel Medical Center
      New York City, New York, United States
  • 2003–2009
    • Medical University of South Carolina
      • Department of Psychiatry and Behavioral Sciences
      Charleston, SC, United States
  • 1990–2006
    • University of Toronto
      • Department of Immunology
      Toronto, Ontario, Canada
  • 2003–2005
    • Icahn School of Medicine at Mount Sinai
      • Department of Psychiatry
      Manhattan, New York, United States
    • Weill Cornell Medical College
      • Department of Psychiatry
      New York City, NY, United States