Background:
Theory suggests that individual behavioral responses impact the spread of flu-like illnesses, but this has been difficult to empirically characterize. Social distancing is an important component of behavioral response, though analyses have been limited by a lack of behavioral data. Our objective is to use media data to characterize social distancing behavior in order to empirically inform explanatory and predictive epidemiological models.

Methods:
We use data on variation in home television viewing as a proxy for variation in time spent in the home and, by extension, contact. This behavioral proxy is imperfect but appealing since information on a rich and representative sample is collected using consistent techniques across time and most major cities. We study the April-May 2009 outbreak of A/H1N1 in Central Mexico and examine the dynamic behavioral response in aggregate and contrast the observed patterns of various demographic subgroups. We develop and calibrate a dynamic behavioral model of disease transmission informed by the proxy data on daily variation in contact rates and compare it to a standard (non-adaptive) model and a fixed effects model that crudely captures behavior.

Results:
We find that after a demonstrable initial behavioral response (consistent with social distancing) at the onset of the outbreak, there was attenuation in the response before the conclusion of the public health intervention. We find substantial differences in the behavioral response across age subgroups and socioeconomic levels. We also find that the dynamic behavioral and fixed effects transmission models better account for variation in new confirmed cases, generate more stable estimates of the baseline rate of transmission over time and predict the number of new cases over a short horizon with substantially less error.

Conclusions:
Results suggest that A/H1N1 had an innate transmission potential greater than previously thought but this was masked by behavioral responses. Observed differences in behavioral response across demographic groups indicate a potential benefit from targeting social distancing outreach efforts.

Society is heavily dependent on a reliable electric supply; all infrastructure systems depend on electricity to operate. When the electric system fails, the impacts can be catastrophic (food spoilage, inoperable medical devices, lack of access to water, etc.). The social impacts, defined as the direct and indirect impacts on people, of power outages must be explored as the likelihood of power outages and blackouts are increasing. However, compared to other hazards, such as heat and flooding, the knowledge base on the impacts of power outages is relatively small. The purpose of this thesis is to identify what is currently known about the social impacts of power outages, identify where gaps in the literature exist, and deploy a survey to explore power outage experiences at the household level. This thesis is comprised of two chapters, a systematic literature review on the current knowledge of the social impacts of power outages and a multi-city survey focused on power outage experiences.

The first chapter comprised of a systematic literature review using a combined search of in Scopus which returned 762 candidate articles were identified that potentially explored the social impacts of power outages. However, after multiple filtering criteria were applied, only 45 articles met all criteria. Four themes were used to classify the literature, not exclusively, including modeling, social, technical, and other. Only papers that were classified as “social” - meaning they observed how people were affected by a power outage - or in combination with other categories were used within the review.

From the literature, populations of concern were identified, including minority demographics - specifically Blacks or African Americans, children, elderly, and rural populations. The most commonly reported health concerns were from those that rely on medical devices for chronic conditions and unsafe generator practices. Criminal activity was also reported to increase during prolonged power outages and can be mitigated by consistent messaging on where to receive assistance and when power will be restored. Providing financial assistance and resources such as food and water can reduce the crime rate temporarily, but the crime rate can be expected to increase once the relief expires. Authorities should expect looting to occur, especially in poorer areas, during prolonged power outages. Gaps in the literature were identified and future directions for research were provided.

The second chapter consists of a multi-city survey that targeted three major cities across the United States (Detroit, MI; Miami, FL; and Phoenix, AZ). The survey was disseminated through Amazon’s Mechanical Turk and hosted by Qualtrics. 896 participants from the three cities qualified to complete the full version of the survey. Three criteria had to be met for participants to complete the full survey including residing in one of the three target cities, living at their primary address for a majority of the year, and indicate they had experienced a power outage within the last five years.

Participants were asked questions regarding the number of outages experienced in the last five years, the length of their most recent and longest outage experienced, if they owned a generator, how they managed their longest power outage, if participants or anyone in their household relies on a medical device, the financial burden their power outage caused, and standard demographic- and income-related questions. Race was a significant variable that influenced the outage duration length but not frequency in Phoenix and Detroit. Income was not a significant variable associated with experiencing greater economic impacts, such as having thrown food away because of an outage and not receiving help during the longest outage. Additional assessments similar to this survey are needed to better understand household power outage experiences.

Findings from this thesis demonstrate traditional metrics used in vulnerability indices were not indicative of who experienced the greatest effects of power outages. Additionally, other factors that are not included in these indices, such as owning adaptive resources including medical devices and generators in Phoenix and Detroit, are factors in reducing negative outcomes. More research is needed on this topic to indicate which populations are more likely to experience factors that can influence positive or negative outage outcomes.

Access to air conditioned space is critical for protecting urban populations from the adverse effects of heat exposure. Yet there remains fairly limited knowledge of penetration of private (home air conditioning) and distribution of public (cooling centers and commercial space) cooled space across cities. Furthermore, the deployment of government-sponsored cooling centers is not based on the location of existing cooling resources (residential air conditioning and air conditioned public space), raising questions of the equitability of access to heat refuges.

Using Los Angeles County, California and Maricopa County, Arizona (whose county seat is Phoenix) we explore the distribution of private and public cooling resources and access inequities at the household level. We do this by evaluating the presence of in-home air conditioning and developing a walking-based accessibility measure to air conditioned public space using a combined cumulative opportunities-gravity approach. We find significant inequities in the distribution of residential air conditioning across both regions which are largely attributable to building age and inter/intra-regional climate differences. There are also regional disparities in walkable access to public cooled space.

At average walking speeds, we find that official cooling centers are only accessible to a small fraction of households (3% in Los Angeles, 2% in Maricopa) while a significantly higher number of households (80% in Los Angeles, 39% in Maricopa) have access to at least one other type of public cooling resource which includes libraries and commercial establishments. Aggregated to a neighborhood level, we find that there are areas within each region where access to cooled space (either public or private) is limited which may increase the health risks associated with heat.

Methicillin resistant Staphylococcus aureus (MRSA) is currently a major cause of skin and soft tissue infections (SSTI) in the United States. Seasonal variation of MRSA infections in hospital settings has been widely observed. However, systematic time-series analysis of incidence data is desirable to understand the seasonality of community acquired (CA)-MRSA infections at the population level. In this paper, using data on monthly SSTI incidence in children aged 0–19 years and enrolled in Medicaid in Maricopa County, Arizona, from January 2005 to December 2008, we carried out time-series and nonlinear regression analysis to determine the periodicity, trend, and peak timing in SSTI incidence in children at different age: 0-4 years, 5-9 years, 10-14 years, and 15-19 years. We also assessed the temporal correlation between SSTI incidence and meteorological variables including average temperature and humidity. Our analysis revealed a strong annual seasonal pattern of SSTI incidence with peak occurring in early September. This pattern was consistent across age groups. Moreover, SSTIs followed a significantly increasing trend over the 4-year study period with annual incidence increasing from 3.36% to 5.55% in our pediatric population of approximately 290,000. We also found a significant correlation between the temporal variation in SSTI incidence and mean temperature and specific humidity. Our findings could have potential implications on prevention and control efforts against CA-MRSA.

Background: Prior research shows that work in agriculture and construction/extraction occupations increases the risk of environmental heat-associated death.

Purpose: To assess the risk of environmental heat-associated death by occupation.

Methods: This was a case-control study. Cases were heat-caused and heat-related deaths occurring from May-October during the period 2002–2009 in Maricopa County, Arizona. Controls were selected at random from non-heat-associated deaths during the same period in Maricopa County. Information on occupation, age, sex, and race-ethnicity was obtained from death certificates. Logistic regression analysis was used to estimate odds ratios for heat-associated death.

Results: There were 444 cases of heat-associated deaths in adults (18+ years) and 925 adult controls. Of heat-associated deaths, 332 (75%) occurred in men; a construction/extraction or agriculture occupation was described on the death certificate in 115 (35%) of these men. In men, the age-adjusted odds ratios for heat-associated death were 2.32 (95% confidence interval 1.55, 3.48) in association with construction/extraction and 3.50 (95% confidence interval 1.94, 6.32) in association with agriculture occupations. The odds ratio for heat-associated death was 10.17 (95% confidence interval 5.38, 19.23) in men with unknown occupation. In women, the age-adjusted odds ratio for heat-associated death was 6.32 (95% confidence interval 1.48, 27.08) in association with unknown occupation. Men age 65 years and older in agriculture occupations were at especially high risk of heat-associated death.

Conclusion: The occurrence of environmental heat-associated death in men in agriculture and construction/extraction occupations in a setting with predictable periods of high summer temperatures presents opportunities for prevention.

In this study we characterized the relationship between temperature and mortality in central Arizona desert cities that have an extremely hot climate. Relationships between daily maximum apparent temperature (AT_max) and mortality for eight condition-specific causes and all-cause deaths were modeled for all residents and separately for males and females ages <65 and ≥65 during the months May-October for years 2000-2008. The most robust relationship was between ATmax on day of death and mortality from direct exposure to high environmental heat. For this condition-specific cause of death, the heat thresholds in all gender and age groups (AT_max = 90–97 °F; 32.2‒36.1 °C) were below local median seasonal temperatures in the study period (AT_max = 99.5 °F; 37.5 °C). Heat threshold was defined as AT_max at which the mortality ratio begins an exponential upward trend. Thresholds were identified in younger and older females for cardiac disease/stroke mortality (AT_max = 106 and 108 °F; 41.1 and 42.2 °C) with a one-day lag. Thresholds were also identified for mortality from respiratory diseases in older people (AT_max = 109 °F; 42.8 °C) and for all-cause mortality in females (AT_max = 107 °F; 41.7 °C) and males <65 years (AT_max = 102 °F; 38.9 °C). Heat-related mortality in a region that has already made some adaptations to predictable periods of extremely high temperatures suggests that more extensive and targeted heat-adaptation plans for climate change are needed in cities worldwide.

Maricopa County is the home of the Phoenix metropolitan area, an expansive city with serious air quality concerns. To ameliorate air quality in the county, the Maricopa County Air Quality Department developed a website and mobile application called "Clean Air Make More" as a means of outreach and engagement. In doing this, the county has found a way to engender a bilateral relationship between individuals and their government agency. This study analyzes the effectiveness of Clean Air Make More in establishing this relationship and engaging the community in efforts to improve air quality. It concludes that the design of the application effectively meets user needs, but marketing efforts should target populations disposed to taking action regarding air quality.

Background:
Environmental heat exposure is a public health concern. The impacts of environmental heat on mortality and morbidity at the population scale are well documented, but little is known about specific exposures that individuals experience.

Objectives:
The first objective of this work was to catalyze discussion of the role of personal heat exposure information in research and risk assessment. The second objective was to provide guidance regarding the operationalization of personal heat exposure research methods.

Discussion:
We define personal heat exposure as realized contact between a person and an indoor or outdoor environment that poses a risk of increases in body core temperature and/or perceived discomfort. Personal heat exposure can be measured directly with wearable monitors or estimated indirectly through the combination of time–activity and meteorological data sets. Complementary information to understand individual-scale drivers of behavior, susceptibility, and health and comfort outcomes can be collected from additional monitors, surveys, interviews, ethnographic approaches, and additional social and health data sets. Personal exposure research can help reveal the extent of exposure misclassification that occurs when individual exposure to heat is estimated using ambient temperature measured at fixed sites and can provide insights for epidemiological risk assessment concerning extreme heat.

Conclusions:
Personal heat exposure research provides more valid and precise insights into how often people encounter heat conditions and when, where, to whom, and why these encounters occur. Published literature on personal heat exposure is limited to date, but existing studies point to opportunities to inform public health practice regarding extreme heat, particularly where fine-scale precision is needed to reduce health consequences of heat exposure.