Urban heat is a growing problem that impacts public health, water and energy use, and the economy and affects population subgroups differently. Exposure and sensitivity, two key factors in determining vulnerability, have been widely researched. This dissertation focuses on the adaptive capacity component of heat vulnerability at the individual, household, and community scale. Using a mixed methods approach and metropolitan Phoenix as a test site, I explored how vulnerable communities understand and adapt to increasing extreme urban heat to uncover adaptive capacity that is not being operationalized well through current heat vulnerability frameworks. Twenty-three open-ended interviews were conducted where residents were encouraged to tell their stories about past and present extreme heat adaptive capacity behaviors. A community-based participatory research project consisting of three workshops and demonstration projects was piloted in three underserved neighborhoods to address urban heat on a local scale and collaboratively create community heat action plans. Last, a practitioner stakeholder meeting was held to discuss how the heat action plans will be integrated into other community efforts. Using data from the interviews, workshops, and stakeholder meeting, social capital was examined in the context of urban heat. Although social capital has been measured in a multitude of ways to gauge social relationships, trust, and reciprocity within a community, it is situational and reflects a position within the formal and informal aspects of any issue. Three narratives emerged from the interviews illuminating differentiated capacities to cope with urban heat: heat is an inconvenience, heat is a manageable problem, and heat is a catastrophe. For each of these narratives, generic adaptive capacity is impacted differently by specific heat adaptive capacity. The heat action plan workshops generated hyper-local heat solutions that reflected the neighborhoods’ different identities. Community-based organizations were instrumental in the success of this program. Social capital indicators were developed specific to urban heat that rely on heavily on family and personal relationships, attitudes and beliefs, perceived support, network size and community engagement. This research highlights how extreme heat vulnerability may need to be rethought to capture adaptive capacity nuances and the dynamic structure of who is vulnerable under what circumstances.
The City of Phoenix has committed to public transit improvements in the Transportation 2050 plan and has recently adopted a Complete Streets Policy. Proposed changes include mobility improvements and creating a safe and comfortable environment for non-motorized road participants. To understand what kind of improvements would benefit thermal comfort the most, it is necessary to understand heat exposure at finer spatial scales, explore whether current bus shelter designs are adequate in mitigating heat-health effects, and comprehensively assess the impact of design on physical, psychological and behavioral aspects of thermal comfort. A study conducted at bus stops in one Phoenix neighborhood examined grey and green infrastructure types preferred for cooling and found relationships between perception of pleasantness and thermal sensation votes. Walking interviews conducted in another neighborhood event examined the applicability of a framework for walking behavior under the stress of heat, and how differences between the streets affected perceptions of the walkers. The interviews revealed that many of the structural themes from the framework of walking behavior were applicable, however, participants assessed the majority of the elements in their walk from a heat mitigation perspective. Finally, guiding questions for walkability in hot and arid climates were developed based on the literature review and results from the empirical studies. This dissertation contributes to filling the gap between walkability and outdoor thermal comfort, and presents methodology and findings that can be useful to address walkability and outdoor thermal comfort in the world’s hot cities as well as those in temperate climates that may face similar climate challenges in the future as the planet warms.
Environmental hazards and disaster researchers have demonstrated strong associations between sociodemographic indicators, such as age and socio-economic status (SES), and hazard exposures and health outcomes for individuals and in certain communities. At the same time, behavioral health and risk communications research has examined how individual psychology influences adaptive strategies and behaviors in the face of hazards. However, at present, we do not understand the explanatory mechanisms that explain relationships between larger scale social structure, individual psychology, and specific behaviors that may attenuate or amplify risk. Extreme heat presents growing risks in a rapidly warming and urbanizing world. This dissertation examines the social and behavioral mechanisms that may explain inequitable health outcomes from exposure to concurrent extreme heat and electrical power failure in Phoenix, AZ and extreme heat in Detroit, MI. Exploratory analysis of 163 surveys in Phoenix, AZ showed that age, gender, and respondent’s racialized group identity did not relate to thermal discomfort and self-reported heat illness, which were only predicted by SES (StdB = -0.52, p < 0.01). Of the explanatory mechanisms tested in the study, only relative air conditioning intensity and thermal discomfort explained self-reported heat illness. Thermal discomfort was tested as both a mechanism and outcome measure. Content analysis of 40 semi-structured interviews in Phoenix, AZ revealed that social vulnerability was associated with an increase in perceived hazard severity (StdB = 0.44, p < 0.01), a decrease in perceived adaptation efficacy (StdB = -0.38, p = 0.02), and an indirect increase (through adaptive efficacy) in maladaptive intentions (StdB = 0.18, p = 0.01). Structural equation modeling of 244 surveys in Phoenix, AZ and Detroit, MI revealed that relationships between previous heat illness experience, perceived heat risk, and adaptive intentions were significantly moderated by adaptive capacity: high adaptive capacity households were more likely to undertake adaptive behaviors, and those decisions were more heavily influenced by risk perceptions and previous experiences. However, high adaptive capacity households had lower risk perceptions and fewer heat illness experiences than low adaptive capacity households. A better understanding of the mechanisms that produce social vulnerability can facilitate more salient risk messaging and more targeted public health interventions. For example, public health risk messaging that provides information on the efficacy of specific adaptations may be more likely to motivate self-protective action, and ultimately protect populations.
Urban climate conditions are the physical manifestation of formal and informal social forces of design, policy, and urban management. The urban design community (e.g. planners, architects, urban designers, landscape architects, engineers) impacts urban development through influential built projects and design discourse. Their decisions create urban landscapes that impact physiological and mental health for people that live in and around them. Therefore, to understand possible opportunities for decision-making to support healthier urban environments and communities, this dissertation examines the role of neighborhood design on the thermal environment and the effect the thermal environment has on mental health. In situ data collection and numerical modeling are used to assess current and proposed urban design configurations in the Edison Eastlake public housing community in central Phoenix for their efficacy in cooling the thermal environment. A distributed lagged non-linear model is used to investigate the relative risk of hospitalization for schizophrenia in Maricopa County based on atmospheric conditions. The dissertation incorporates both an assessment of design strategies for the cooling of the thermal environment and an analysis of the existing thermal environment’s relationship with mental health. By reframing the urban design of neighborhoods through the lens of urban climate, this research reinforces the importance of incorporating the community into the planning process and highlights some unintended outcomes of prioritizing the thermal environment in urban design.
To address the dearth of knowledge about person-based and trip-level exposure, we developed the Icarus model. Icarus uses mesoscale traffic model—activity-based model—to analyze the heat exposure of regions of interest at an individual level. The goal with Icarus was to design accurate, granular models of population and temperature behavior for a target region, which could be transformed into a heat exposure model by means of simulation and spatial-temporal joining. By combining and implementing the most robust software and data available, Icarus was able to capture person-based exposure with unparalleled detail. Here we describe the model methodology. We use the metropolitan region of Phoenix, Arizona, USA to carry out a case study using Icarus.
Background: Most excess deaths that occur during extreme hot weather events do not have natural heat recorded as an underlying or contributing cause. This study aims to identify the specific individuals who died because of hot weather using only secondary data. A novel approach was developed in which the expected number of deaths was repeatedly sampled from all deaths that occurred during a hot weather event, and compared with deaths during a control period. The deaths were compared with respect to five factors known to be associated with hot weather mortality. Individuals were ranked by their presence in significant models over 100 trials of 10,000 repetitions. Those with the highest rankings were identified as probable excess deaths. Sensitivity analyses were performed on a range of model combinations. These methods were applied to a 2009 hot weather event in greater Vancouver, Canada.
Results: The excess deaths identified were sensitive to differences in model combinations, particularly between univariate and multivariate approaches. One multivariate and one univariate combination were chosen as the best models for further analyses. The individuals identified by multiple combinations suggest that marginalized populations in greater Vancouver are at higher risk of death during hot weather.
Conclusions: This study proposes novel methods for classifying specific deaths as expected or excess during a hot weather event. Further work is needed to evaluate performance of the methods in simulation studies and against clinically identified cases. If confirmed, these methods could be applied to a wide range of populations and events of interest.
Background: While prior studies have quantified the mortality burden of the 1957 H2N2 influenza pandemic at broad geographic regions in the United States, little is known about the pandemic impact at a local level. Here we focus on analyzing the transmissibility and mortality burden of this pandemic in Arizona, a setting where the dry climate was promoted as reducing respiratory illness transmission yet tuberculosis prevalence was high.
Methods: Using archival death certificates from 1954 to 1961, we quantified the age-specific seasonal patterns, excess-mortality rates, and transmissibility patterns of the 1957 H2N2 pandemic in Maricopa County, Arizona. By applying cyclical Serfling linear regression models to weekly mortality rates, the excess-mortality rates due to respiratory and all-causes were estimated for each age group during the pandemic period. The reproduction number was quantified from weekly data using a simple growth rate method and assumed generation intervals of 3 and 4 days. Local newspaper articles published during 1957–1958 were also examined.
Results: Excess-mortality rates varied between waves, age groups, and causes of death, but overall remained low. From October 1959-June 1960, the most severe wave of the pandemic, the absolute excess-mortality rate based on respiratory deaths per 10,000 population was 16.59 in the elderly (≥65 years). All other age groups exhibit very low excess-mortality and the typical U-shaped age-pattern was absent. However, the standardized mortality ratio was greatest (4.06) among children and young adolescents (5–14 years) from October 1957-March 1958, based on mortality rates of respiratory deaths. Transmissibility was greatest during the same 1957–1958 period, when the mean reproduction number was estimated at 1.08–1.11, assuming 3- or 4-day generation intervals with exponential or fixed distributions.
Conclusions: Maricopa County exhibited very low mortality impact associated with the 1957 influenza pandemic. Understanding the relatively low excess-mortality rates and transmissibility in Maricopa County during this historic pandemic may help public health officials prepare for and mitigate future outbreaks of influenza.
Background: On 31 March 2013, the first human infections with the novel influenza A/H7N9 virus were reported in Eastern China. The outbreak expanded rapidly in geographic scope and size, with a total of 132 laboratory-confirmed cases reported by 3 June 2013, in 10 Chinese provinces and Taiwan. The incidence of A/H7N9 cases has stalled in recent weeks, presumably as a consequence of live bird market closures in the most heavily affected areas. Here we compare the transmission potential of influenza A/H7N9 with that of other emerging pathogens and evaluate the impact of intervention measures in an effort to guide pandemic preparedness.
Methods: We used a Bayesian approach combined with a SEIR (Susceptible-Exposed-Infectious-Removed) transmission model fitted to daily case data to assess the reproduction number (R) of A/H7N9 by province and to evaluate the impact of live bird market closures in April and May 2013. Simulation studies helped quantify the performance of our approach in the context of an emerging pathogen, where human-to-human transmission is limited and most cases arise from spillover events. We also used alternative approaches to estimate R based on individual-level information on prior exposure and compared the transmission potential of influenza A/H7N9 with that of other recent zoonoses.
Results: Estimates of R for the A/H7N9 outbreak were below the epidemic threshold required for sustained human-to-human transmission and remained near 0.1 throughout the study period, with broad 95% credible intervals by the Bayesian method (0.01 to 0.49). The Bayesian estimation approach was dominated by the prior distribution, however, due to relatively little information contained in the case data. We observe a statistically significant deceleration in growth rate after 6 April 2013, which is consistent with a reduction in A/H7N9 transmission associated with the preemptive closure of live bird markets. Although confidence intervals are broad, the estimated transmission potential of A/H7N9 appears lower than that of recent zoonotic threats, including avian influenza A/H5N1, swine influenza H3N2sw and Nipah virus.
Conclusion: Although uncertainty remains high in R estimates for H7N9 due to limited epidemiological information, all available evidence points to a low transmission potential. Continued monitoring of the transmission potential of A/H7N9 is critical in the coming months as intervention measures may be relaxed and seasonal factors could promote disease transmission in colder months.
Background: The impact of socio-demographic factors and baseline health on the mortality burden of seasonal and pandemic influenza remains debated. Here we analyzed the spatial-temporal mortality patterns of the 1918 influenza pandemic in Spain, one of the countries of Europe that experienced the highest mortality burden.
Methods: We analyzed monthly death rates from respiratory diseases and all-causes across 49 provinces of Spain, including the Canary and Balearic Islands, during the period January-1915 to June-1919. We estimated the influenza-related excess death rates and risk of death relative to baseline mortality by pandemic wave and province. We then explored the association between pandemic excess mortality rates and health and socio-demographic factors, which included population size and age structure, population density, infant mortality rates, baseline death rates, and urbanization.
Results: Our analysis revealed high geographic heterogeneity in pandemic mortality impact. We identified 3 pandemic waves of varying timing and intensity covering the period from Jan-1918 to Jun-1919, with the highest pandemic-related excess mortality rates occurring during the months of October-November 1918 across all Spanish provinces. Cumulative excess mortality rates followed a south–north gradient after controlling for demographic factors, with the North experiencing highest excess mortality rates. A model that included latitude, population density, and the proportion of children living in provinces explained about 40% of the geographic variability in cumulative excess death rates during 1918–19, but different factors explained mortality variation in each wave.
Conclusions: A substantial fraction of the variability in excess mortality rates across Spanish provinces remained unexplained, which suggests that other unidentified factors such as comorbidities, climate and background immunity may have affected the 1918-19 pandemic mortality rates. Further archeo-epidemiological research should concentrate on identifying settings with combined availability of local historical mortality records and information on the prevalence of underlying risk factors, or patient-level clinical data, to further clarify the drivers of 1918 pandemic influenza mortality.
Background: Elucidating the role of the underlying risk factors for severe outcomes of the 2009 A/H1N1 influenza pandemic could be crucial to define priority risk groups in resource-limited settings in future pandemics.
Methods: We use individual-level clinical data on a large series of ARI (acute respiratory infection) hospitalizations from a prospective surveillance system of the Mexican Social Security medical system to analyze clinical features at presentation, admission delays, selected comorbidities and receipt of seasonal vaccine on the risk of A/H1N1-related death. We considered ARI hospitalizations and inpatient-deaths, and recorded demographic, geographic, and medical information on individual patients during August-December, 2009.
Results: Seasonal influenza vaccination was associated with a reduced risk of death among A/H1N1 inpatients (OR = 0.43 (95% CI: 0.25, 0.74)) after adjustment for age, gender, geography, antiviral treatment, admission delays, comorbidities and medical conditions. However, this result should be interpreted with caution as it could have been affected by factors not directly measured in our study. Moreover, the effect of antiviral treatment against A/H1N1 inpatient death did not reach statistical significance (OR = 0.56 (95% CI: 0.29, 1.10)) probably because only 8.9% of A/H1N1 inpatients received antiviral treatment. Moreover, diabetes (OR = 1.6) and immune suppression (OR = 2.3) were statistically significant risk factors for death whereas asthmatic persons (OR = 0.3) or pregnant women (OR = 0.4) experienced a reduced fatality rate among A/H1N1 inpatients. We also observed an increased risk of death among A/H1N1 inpatients with admission delays >2 days after symptom onset (OR = 2.7). Similar associations were also observed for A/H1N1-negative inpatients.
Conclusions: Geographical variation in identified medical risk factors including prevalence of diabetes and immune suppression may in part explain between-country differences in pandemic mortality burden. Furthermore, access to care including hospitalization without delay and antiviral treatment and are also important factors, as well as vaccination coverage with the 2008–09 trivalent inactivated influenza vaccine.