ASU Scholarship Showcase

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: 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.

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.

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.

Objective: To estimate the effects on homicide rates of the gang truce that was brokered in El Salvador in 2012.

Methods: Mathematical models based on municipal-level census, crime and gang-intelligence data were used to estimate the effect of the truce on homicide rates. One model estimated the overall effect after accounting for the linear trend and seasonality in the homicide rate. In a moderated-effect model, we investigated the relationship between the truce effect and the numbers of MS13 (Mara Salvatrucha 13) and Eighteenth-Street gang members imprisoned per 100 000 population. We then ran each of these two models with additional control variables. We compared values before the truce – 1 January 2010 to 29 February 2012 – with those after the truce – 1 March 2012 to 31 December 2013.

Findings: The overall-effect models with and without additional control variables indicated a homicide rate after the truce that was significantly lower than the value before the truce, giving rate ratios of 0.55 (95% confidence interval, CI: 0.49–0.63) and 0.61 (95% CI: 0.54–0.69), respectively. For any given municipality, the effectiveness of the truce appeared to increase as the number of MS13 gang members imprisoned per 100 000 population increased. We did not observe the same significant relationship for imprisoned Eighteenth-Street gang members.

Conclusion: In the 22 months following the establishment of a national gang truce, the homicide rate was about 40% lower than in the preceding 26 months. The truce’s impact appeared particularly strong in municipalities with relatively high numbers of imprisoned MS13 gang members per 100 000 population.

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.

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.

The literature including social media shows that Mexican/Latino immigrants have attracted contempt and have been traditionally objected to as a minority in the U.S. The intent here is to search for historical and other factors that might explain the public antipathy and to identify reasons that could, either in isolation or in combination with others, explain anti-immigrant sentiments among people, many of whom are descendants of immigrants. The perusal of the challenges of Mexican immigrants to the U.S. through the decades will highlight some similarities related to discrimination against waves “peoples of color”, not only in the U.S. but in other parts of the world. The daily treatment within the society of immigrants of color as well as the frequent lower immigration quotas imposed on certain groups, including Mediterranean people, makes the topic quite relevant to today’s concerns.