ASU Scholarship Showcase

Intense and enduring psychological distress has been well-documented in numerous studies on bereaved parents including anxious, depressive, and traumatic stress symptoms. A state of poverty is also known to increase the risk of psychological distress in the general population, yet this variable has not yet been sufficiently evaluated in outcomes specifically for bereaved parents. This study is the first to investigate poverty, education, and parental bereavement while examining the relative risk of other variables as informed by the literature. The findings reveal that poverty was the strongest predictor of psychological distress when compared to others factors which have traditionally been considered significant in parental bereavement. Bereaved parents living in poverty may be less likely to seek support and have fewer available resources. Practice and policy implications are discussed.

Background: Zoonotic avian influenza poses a major risk to China, and other parts of the world. H5N1 has remained endemic in China and globally for nearly two decades, and in 2013, a novel zoonotic influenza A subtype H7N9 emerged in China. This study aimed to improve upon our current understanding of the spreading mechanisms of H7N9 and H5N1 by generating spatial risk profiles for each of the two virus subtypes across mainland China.

Methods and Findings: In this study, we (i) developed a refined data set of H5N1 and H7N9 locations with consideration of animal/animal environment case data, as well as spatial accuracy and precision; (ii) used this data set along with environmental variables to build species distribution models (SDMs) for each virus subtype in high resolution spatial units of 1km² cells using Maxent; (iii) developed a risk modelling framework which integrated the results from the SDMs with human and chicken population variables, which was done to quantify the risk of zoonotic transmission; and (iv) identified areas at high risk of H5N1 and H7N9 transmission. We produced high performing SDMs (6 of 8 models with AUC > 0.9) for both H5N1 and H7N9. In all our SDMs, H7N9 consistently showed higher AUC results compared to H5N1, suggesting H7N9 suitability could be better explained by environmental variables. For both subtypes, high risk areas were primarily located in south-eastern China, with H5N1 distributions found to be more diffuse and extending more inland compared to H7N9.

Conclusions: We provide projections of our risk models to public health policy makers so that specific high risk areas can be targeted for control measures. We recommend comparing H5N1 and H7N9 prevalence rates and survivability in the natural environment to better understand the role of animal and environmental transmission in human infections.

The 2014 Ebola virus disease (EVD) outbreak affected several countries worldwide, including six West African countries. It was the largest Ebola epidemic in the history and the first to affect multiple countries simultaneously. Significant national and international delay in response to the epidemic resulted in 28,652 cases and 11,325 deaths. The aim of this study was to develop a risk analysis framework to prioritize rapid response for situations of high risk. Based on findings from the literature, sociodemographic features of the affected countries, and documented epidemic data, a risk scoring framework using 18 criteria was developed. The framework includes measures of socioeconomics, health systems, geographical factors, cultural beliefs, and traditional practices. The three worst affected West African countries (Guinea, Sierra Leone, and Liberia) had the highest risk scores. The scores were much lower in developed countries that experienced Ebola compared to West African countries. A more complex risk analysis framework using 18 measures was compared with a simpler one with 10 measures, and both predicted risk equally well. A simple risk scoring system can incorporate measures of hazard and impact that may otherwise be neglected in prioritizing outbreak response. This framework can be used by public health personnel as a tool to prioritize outbreak investigation and flag outbreaks with potentially catastrophic outcomes for urgent response. Such a tool could mitigate costly delays in epidemic response.

Background: Bacterial colonization of the respiratory tract is commonly described and usually thought to be of no clinical significance. The aim of this study was to examine the presence and significance of bacteria and viruses in the upper respiratory tract of healthcare workers (HCWs), and association with respiratory symptoms.

Methods: A prospective cohort study was conducted in China and 223 HCWs were recruited from fever clinics and respiratory, paediatric, emergency/Intensive medication wards. Participants were followed over 4 weeks (7th May 2015 to 4th June 2015) for development of clinical respiratory illness (CRI). Nasopharyngeal swabs were obtained at baseline and at the end of the study. The primary endpoints were laboratory-confirmed bacterial colonization and viral respiratory infection. Rates of the following infections in symptomatic and asymptomatic participants were compared at the start or end of the study; 1) all bacterial/viral infections, 2) bacterial infection and bacterial-viral co-infections, excluding virus only infections, and 3) only bacterial infections.

Results: Bacterial colonization was identified in 88% (196/223) of participants at the start or end of the study. Among these participants, 66% (148/223) had only bacterial colonization while 22% (48/223) had co-infection with a virus. Bacteria were isolated from 170 (76.2%) participants at baseline and 127 (57%) participants at the end of the study. Laboratory confirmed viral infections were identified in 53 (23.8%) participants - 35 (15.7%) at the baseline and 20 (9.0%) at the end of the study. CRI symptoms were recorded in 12 participants (4.5%) and all had a positive bacterium isolation at baseline (n = 11) or end of the study (n = 1). Among asymptomatic participants, 187 (87%) had bacterial colonization or bacterial/viral co-infection at baseline or end of the study. Viruses were also isolated from 5 (2.4%) asymptomatic cases. Rates of all infection outcomes were higher in symptomatic participants, however differences were not statistically significant.

Conclusion: We isolated high rates of bacteria and viruses in the upper respiratory tract of hospital HCWs, which may reflect greater exposure to respiratory infections in the hospital. Although respiratory infections are mostly symptomatic, the association between bacterial colonization and symptomatic illness is not clear. In the healthcare setting, HCWs may acquire and transmit infection to patients and other HCWs around them. Larger studies are required to explore ongoing occupational risk of respiratory infection in hospitals HCWs.

American Indians are increasingly using social media/social network platforms as a tool to influence policy through social change. The activist group Apache Stronghold represents a case of American Indians utilising social media tools to protect Oak Flat and influence federal Indian policy. Oak Flat is sacred Apache land located in Superior, Arizona. United States legislators transferred Oak Flat to the mining company Resolution Copper as part of the omnibus National Defense Authorization Act of 2015. Qualitative analysis of social media content and advocacy tactics – specifically through use of timeline and digital ethnography – of Apache Stronghold from 2015-2016 reveal the interrelated nature of on-the-ground efforts, online efforts, solidarity efforts, and legislative support efforts. In sum, these efforts express narratives of survivance, healing, and a future orientation, as a unique dimension of social change.

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.

Epidemics and emerging infectious diseases are becoming an increasing threat to global populations - challenging public health practitioners, decision makers and researchers to plan, prepare, identify and respond to outbreaks in near real-timeframes. The aim of this research is to evaluate the range of public domain and freely available software epidemic modelling tools. Twenty freely utilizable software tools underwent assessment of software usability, utility and key functionalities. Stochastic and agent based tools were found to be highly flexible, adaptable, had high utility and many features, but low usability. Deterministic tools were highly usable with average to good levels of utility.

Public health messaging about antimicrobial resistance (AMR) sometimes conveys the problem as an epidemic. We outline why AMR is a serious endemic problem manifested in hospital and community-acquired infections.

AMR is not an epidemic condition, but may complicate epidemics, which are characterized by sudden societal impact due to rapid rise in cases over a short timescale. Influenza, which causes direct viral effects, or secondary bacterial complications is the most likely cause of an epidemic or pandemic where AMR may be a problem. We discuss other possible causes of a pandemic with AMR, and present a risk assessment formula to estimate the impact of AMR during a pandemic. Finally, we flag the potential impact of genetic engineering of pathogens on global risk and how this could radically change the epidemiology of AMR as we know it.

Understanding the epidemiology of AMR is key to successfully addressing the problem. AMR is an endemic condition but can play a role in epidemics or pandemics, and we present a risk analysis method for assessing the impact of AMR in a pandemic.