The Arctic, even more so than other parts of the world, has warmed substantially over the past few decades. Temperature and humidity influence the rate of development, survival and reproduction of pathogens and thus the incidence and prevalence of many infectious diseases. Higher temperatures may also allow infected host species to survive winters in larger numbers, increase the population size and expand their habitat range. The impact of these changes on human disease in the Arctic has not been fully evaluated. There is concern that climate change may shift the geographic and temporal distribution of a range of infectious diseases. Many infectious diseases are climate sensitive, where their emergence in a region is dependent on climate-related ecological changes. Most are zoonotic diseases, and can be spread between humans and animals by arthropod vectors, water, soil, wild or domestic animals. Potentially climate-sensitive zoonotic pathogens of circumpolar concern include Brucella spp., Toxoplasma gondii, Trichinella spp., Clostridium botulinum, Francisella tularensis, Borrelia burgdorferi, Bacillus anthracis, Echinococcus spp., Leptospira spp., Giardia spp., Cryptosporida spp., Coxiella burnetti, rabies virus, West Nile virus, Hantaviruses, and tick-borne encephalitis viruses.

Background: Extreme heat is a leading weather-related cause of mortality in the United States, but little guidance is available regarding how temperature variable selection impacts heat–mortality relationships.
Objectives: We examined how the strength of the relationship between daily heat-related mortality and temperature varies as a function of temperature observation time, lag, and calculation method.
Methods: Long time series of daily mortality counts and hourly temperature for seven U.S. cities with different climates were examined using a generalized additive model. The temperature effect was modeled separately for each hour of the day (with up to 3-day lags) along with different methods of calculating daily maximum, minimum, and mean temperature. We estimated the temperature effect on mortality for each variable by comparing the 99th versus 85th temperature percentiles, as determined from the annual time series.

Results: In three northern cities (Boston, MA; Philadelphia, PA; and Seattle, WA) that appeared to have the greatest sensitivity to heat, hourly estimates were consistent with a diurnal pattern in the heat-mortality response, with strongest associations for afternoon or maximum temperature at lag 0 (day of death) or afternoon and evening of lag 1 (day before death). In warmer, southern cities, stronger associations were found with morning temperatures, but overall the relationships were weaker. The strongest temperature–mortality relationships were associated with maximum temperature, although mean temperature results were comparable.

Conclusions: There were systematic and substantial differences in the association between temperature and mortality based on the time and type of temperature observation. Because the strongest hourly temperature–mortality relationships were not always found at times typically associated with daily maximum temperatures, temperature variables should be selected independently for each study location. In general, heat-mortality was more closely coupled to afternoon and maximum temperatures in most cities we examined, particularly those typically prone to heat-related mortality.

Background: Extreme heat is a public health challenge. The scarcity of directly comparable studies on the association of heat with morbidity and mortality and the inconsistent identification of threshold temperatures for severe impacts hampers the development of comprehensive strategies aimed at reducing adverse heat-health events.

Objectives: This quantitative study was designed to link temperature with mortality and morbidity events in Maricopa County, Arizona, USA, with a focus on the summer season.
Methods: Using Poisson regression models that controlled for temporal confounders, we assessed daily temperature–health associations for a suite of mortality and morbidity events, diagnoses, and temperature metrics. Minimum risk temperatures, increasing risk temperatures, and excess risk temperatures were statistically identified to represent different “trigger points” at which heat-health intervention measures might be activated.

Results: We found significant and consistent associations of high environmental temperature with all-cause mortality, cardiovascular mortality, heat-related mortality, and mortality resulting from conditions that are consequences of heat and dehydration. Hospitalizations and emergency department visits due to heat-related conditions and conditions associated with consequences of heat and dehydration were also strongly associated with high temperatures, and there were several times more of those events than there were deaths. For each temperature metric, we observed large contrasts in trigger points (up to 22°C) across multiple health events and diagnoses.

Conclusion: Consideration of multiple health events and diagnoses together with a comprehensive approach to identifying threshold temperatures revealed large differences in trigger points for possible interventions related to heat. Providing an array of heat trigger points applicable for different end-users may improve the public health response to a problem that is projected to worsen in the coming decades.

Background: Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to “adaptation uncertainty” (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios.

Objectives: This study had three aims: a) Compare the range in projected impacts that arises from using different adaptation modeling methods; b) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c) recommend modeling method(s) to use in future impact assessments.

Methods: We estimated impacts for 2070–2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty.

Results: The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty.

Conclusions: Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope.

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.

Background: Extreme heat is a leading weather-related cause of illness and death in many locations across the globe, including subtropical Australia. The possibility of increasingly frequent and severe heat waves warrants continued efforts to reduce this health burden, which could be accomplished by targeting intervention measures toward the most vulnerable communities.

Objectives: We sought to quantify spatial variability in heat-related morbidity in Brisbane, Australia, to highlight regions of the city with the greatest risk. We also aimed to find area-level social and environmental determinants of high risk within Brisbane.

Methods: We used a series of hierarchical Bayesian models to examine city-wide and intracity associations between temperature and morbidity using a 2007–2011 time series of geographically referenced hospital admissions data. The models accounted for long-term time trends, seasonality, and day of week and holiday effects.

Results: On average, a 10°C increase in daily maximum temperature during the summer was associated with a 7.2% increase in hospital admissions (95% CI: 4.7, 9.8%) on the following day. Positive statistically significant relationships between admissions and temperature were found for 16 of the city’s 158 areas; negative relationships were found for 5 areas. High-risk areas were associated with a lack of high income earners and higher population density.

Conclusions: Geographically targeted public health strategies for extreme heat may be effective in Brisbane, because morbidity risk was found to be spatially variable. Emergency responders, health officials, and city planners could focus on short- and long-term intervention measures that reach communities in the city with lower incomes and higher population densities, including reduction of urban heat island effects.

Background: While there is ample evidence for health risks associated with heat and other extreme weather events today, little is known about the impact of weather patterns on population health in preindustrial societies.

Objective: To investigate the impact of weather patterns on population health in Sweden before and during industrialization.

Methods: We obtained records of monthly mortality and of monthly mean temperatures and precipitation for Skellefteå parish, northern Sweden, for the period 1800-1950. The associations between monthly total mortality, as well as monthly mortality due to infectious and cardiovascular diseases, and monthly mean temperature and cumulative precipitation were modelled using a time series approach for three separate periods, 1800−1859, 1860-1909, and 1910-1950.

Results: We found higher temperatures and higher amounts of precipitation to be associated with lower mortality both in the medium term (same month and two-months lag) and in the long run (lag of six months up to a year). Similar patterns were found for mortality due to infectious and cardiovascular diseases. Furthermore, the effect of temperature and precipitation decreased over time.

Conclusions: Higher temperature and precipitation amounts were associated with reduced death counts with a lag of up to 12 months. The decreased effect over time may be due to improvements in nutritional status, decreased infant deaths, and other changes in society that occurred in the course of the demographic and epidemiological transition.

Contribution: The study contributes to a better understanding of the complex relationship between weather and mortality and, in particular, historical weather-related mortality.

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.

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.