ASU Scholarship Showcase

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.

The evolution of cooperation is a fundamental problem in biology, especially for non-relatives, where indirect fitness benefits cannot counter within-group inequalities. Multilevel selection models show how cooperation can evolve if it generates a group-level advantage, even when cooperators are disadvantaged within their group. This allows the possibility of group selection, but few examples have been described in nature. Here we show that group selection can explain the evolution of cooperative nest founding in the harvester ant Pogonomyrmex californicus. Through most of this species’ range, colonies are founded by single queens, but in some populations nests are instead founded by cooperative groups of unrelated queens. In mixed groups of cooperative and single-founding queens, we found that aggressive individuals had a survival advantage within their nest, but foundress groups with such non-cooperators died out more often than those with only cooperative members. An agent-based model shows that the between-group advantage of the cooperative phenotype drives it to fixation, despite its within-group disadvantage, but only when population density is high enough to make between-group competition intense. Field data show higher nest density in a population where cooperative founding is common, consistent with greater density driving the evolution of cooperative foundation through group selection.

Human societies are unique in the level of cooperation among non-kin. Evolutionary models explaining this behavior typically assume pure strategies of cooperation and defection. Behavioral experiments, however, demonstrate that humans are typically conditional co-operators who have other-regarding preferences. Building on existing models on the evolution of cooperation and costly punishment, we use a utilitarian formulation of agent decision making to explore conditions that support the emergence of cooperative behavior. Our results indicate that cooperation levels are significantly lower for larger groups in contrast to the original pure strategy model. Here, defection behavior not only diminishes the public good, but also affects the expectations of group members leading conditional co-operators to change their strategies. Hence defection has a more damaging effect when decisions are based on expectations and not only pure strategies.

The threat of West Nile virus (WNV) epidemics with increasingly severe neuroinvasive infections demands the development and licensing of effective vaccines. To date, vaccine candidates based on inactivated, live-attenuated, or chimeric virus, and viral DNA and WNV protein subunits have been developed. Some have been approved for veterinary use or are under clinical investigation, yet no vaccine has been licensed for human use. Reaching the milestone of a commercialized human vaccine, however, may largely depend on the economics of vaccine production. Analysis suggests that currently only novel low-cost production technologies would allow vaccination to outcompete the cost of surveillance and clinical treatment. Here, we review progress using plants to address the economic challenges of WNV vaccine production. The advantages of plants as hosts for vaccine production in cost, speed and scalability, especially those of viral vector-based transient expression systems, are discussed. The progress in developing WNV subunit vaccines in plants is reviewed within the context of their expression, characterization, downstream processing, and immunogenicity in animal models. The development of vaccines based on enveloped and non-enveloped virus-like particles is also discussed. These advancements suggest that plants may provide a production platform that offers potent, safe and affordable human vaccines against WNV.

On-going efforts to understand the dynamics of coupled social-ecological (or more broadly, coupled infrastructure) systems and common pool resources have led to the generation of numerous datasets based on a large number of case studies. This data has facilitated the identification of important factors and fundamental principles which increase our understanding of such complex systems. However, the data at our disposal are often not easily comparable, have limited scope and scale, and are based on disparate underlying frameworks inhibiting synthesis, meta-analysis, and the validation of findings. Research efforts are further hampered when case inclusion criteria, variable definitions, coding schema, and inter-coder reliability testing are not made explicit in the presentation of research and shared among the research community. This paper first outlines challenges experienced by researchers engaged in a large-scale coding project; then highlights valuable lessons learned; and finally discusses opportunities for further research on comparative case study analysis focusing on social-ecological systems and common pool resources. Includes supplemental materials and appendices published in the International Journal of the Commons 2016 Special Issue. Volume 10 - Issue 2 - 2016.

Governing common pool resources (CPR) in the face of disturbances such as globalization and climate change is challenging. The outcome of any CPR governance regime is the influenced by local combinations of social, institutional, and biophysical factors, as well as cross-scale interdependencies. In this study, we take a step towards understanding multiple-causation of CPR outcomes by analyzing 1) the co-occurrence of Design Principles (DP) by activity (irrigation, fishery and forestry), and 2) the combination(s) of DPs leading to social and ecological success. We analyzed 69 cases pertaining to three different activities: irrigation, fishery, and forestry. We find that the importance of the design principles is dependent upon the natural and hard human made infrastructure (i.e. canals, equipment, vessels etc.). For example, clearly defined social boundaries are important when the natural infrastructure is highly mobile (i.e. tuna fish), while monitoring is more important when the natural infrastructure is more static (i.e. forests or water contained within an irrigation system). However, we also find that congruence between local conditions and rules and proportionality between investment and extraction are key for CPR success independent from the natural and human hard made infrastructure. We further provide new visualization techniques for co-occurrence patterns and add to qualitative comparative analysis by introducing a reliability metric to deal with a large meta-analysis dataset on secondary data where information is missing or uncertain.

Includes supplemental materials and appendices publications in International Journal of the Commons 2016 Special Issue. Volume 10 - Issue 2 - 2016

Background: Increasing our understanding of the factors affecting the severity of the 2009 A/H1N1 influenza pandemic in different regions of the world could lead to improved clinical practice and mitigation strategies for future influenza pandemics. Even though a number of studies have shed light into the risk factors associated with severe outcomes of 2009 A/H1N1 influenza infections in different populations (e.g., [1-5]), analyses of the determinants of mortality risk spanning multiple pandemic waves and geographic regions are scarce. Between-country differences in the mortality burden of the 2009 pandemic could be linked to differences in influenza case management, underlying population health, or intrinsic differences in disease transmission [6]. Additional studies elucidating the determinants of disease severity globally are warranted to guide prevention efforts in future influenza pandemics.

In Mexico, the 2009 A/H1N1 influenza pandemic was characterized by a three-wave pattern occurring in the spring, summer, and fall of 2009 with substantial geographical heterogeneity [7]. A recent study suggests that Mexico experienced high excess mortality burden during the 2009 A/H1N1 influenza pandemic relative to other countries [6]. However, an assessment of potential factors that contributed to the relatively high pandemic death toll in Mexico are lacking. Here, we fill this gap by analyzing a large series of laboratory-confirmed A/H1N1 influenza cases, hospitalizations, and deaths monitored by the Mexican Social Security medical system during April 1 through December 31, 2009 in Mexico. In particular, we quantify the association between disease severity, hospital admission delays, and neuraminidase inhibitor use by demographic characteristics, pandemic wave, and geographic regions of Mexico.

Methods: We analyzed a large series of laboratory-confirmed pandemic A/H1N1 influenza cases from a prospective surveillance system maintained by the Mexican Social Security system, April-December 2009. We considered a spectrum of disease severity encompassing outpatient visits, hospitalizations, and deaths, and recorded demographic and geographic information on individual patients. We assessed the impact of neuraminidase inhibitor treatment and hospital admission delay (≤ > 2 days after disease onset) on the risk of death by multivariate logistic regression.

Results: Approximately 50% of all A/H1N1-positive patients received antiviral medication during the Spring and Summer 2009 pandemic waves in Mexico while only 9% of A/H1N1 cases received antiviral medications during the fall wave (P < 0.0001). After adjustment for age, gender, and geography, antiviral treatment significantly reduced the risk of death (OR = 0.52 (95% CI: 0.30, 0.90)) while longer hospital admission delays increased the risk of death by 2.8-fold (95% CI: 2.25, 3.41).

Conclusions: Our findings underscore the potential impact of decreasing admission delays and increasing antiviral use to mitigate the mortality burden of future influenza pandemics.

Research has shown that construction projects in Saudi Arabia have exhibited poor performance for the past three decades. The traditional risk management practices have been ineffective at helping contractors deliver projects on time and within budget while meeting quality expectations. Studies have identified that client decision making is one of the main causes of risks that occur on projects in Saudi Arabia. This paper proposes a new risk management model that can minimize client decision making, and enable the client to utilize expertise, thereby improving project quality and performance. The model is derived from the Information Measurement Theory (IMT) and Performance Information Procurement System (PIPS), both developed at Arizona State University in the United States (U.S.). The model has been tested over 1800 times in both construction and non-construction projects, showing a decrease in required management by owner by up to 80% and an increase in efficiency up to 40%.

Brazil has had issues in efficiently providing the required amount of electricity to its citizens at a low cost. One of the main causes to the decreasing performance of energy is due to reoccurring droughts that decrease the power generated by hydroelectric facilities. To compensate for the decrease, Brazil brought into use thermal power plants. The power plants being on average 23.7% more expensive than hydroelectric. Wind energy is potentially an alternative source of energy to compensate for the energy decrease during droughts. Brazil has invested in wind farms recently, but, due to issues with the delivery method, only 34% of wind farms are operational. This paper reviews the potential benefit Brazil could receive from investing more resources into developing and operating wind farms. It also proposes that utilization of the best value approach in delivering wind farms could produce operational wind farms quicker and more efficiently than previously experienced.

Delays are a major cause for concern in the construction industry in Saudi Arabia. This paper identifies the main causes of delay in infrastructure projects in Mecca, Saudi Arabia, and compares these with projects around the country and other Gulf countries. Data was obtained from 49 infrastructure projects undertaken by the owner and were analyzed quantitatively to understand the severity and causes of delay. 10 risk factors were identified and were grouped into four categories. Average delay in infrastructure projects in Mecca was found to be 39%. The most severe cause of delay was found to be the land acquisition factor. This highlights the critical land ownership and acquisition issues that are prevailing in the city. Additionally, other factors that contribute to delay include contractors’ lack of expertise, re-designing, and haphazard underground utilities (line services). It is concluded that the majority of project delays were caused from the owner's side as compared to contractors, consultants, and other project's stakeholders. This finding matched with the research findings of the Gulf Countries Construction (GCC) Industry's literature. This study fills an important practice and research gap for improving the efficiency in delivering infrastructure projects in the holy city of Mecca and Gulf countries at large.