Changing Flows: Sociotechnical Tinkering for Adaptive Water Management.

The Western United States is experiencing historic drought, increasing pressure on water management systems. Agricultural production that relies on surface water flows is therefore imperiled, requiring new innovations and partnerships in order to adapt and survive. In Arizona, some agriculture continues to rely on historic, low-tech irrigation infrastructure such as hand-dug open ditches that divert river water to flood fields. These ditch systems are managed through both formal ditch companies and informal associations. To address changing water availability and needs, ditch users regularly "tinker" with water infrastructure, experimenting and making changes beyond the original infrastructure plans. Such changes are informed and driven by local social relationships and realities of the physical infrastructure. These dynamics are critical to understanding the adaptive capacity and flexibility of the water system; however, they are challenging to recognize and record. In this paper, we apply the emerging conceptualization of sociotechnical tinkering to examine the adaptive management of irrigation ditches in the Verde Valley of Arizona. We find evidence that water users frequently tinker with their water delivery and monitoring infrastructure to respond to and anticipate changes in water availability. Viewed through the lens of sociotechnical tinkering, these interactions are understood as the material manifestations of situated practice and actor agency within a water management system. This case study contributes to literature on adaptive environmental management and the hydrosocial cycle.

Social Vulnerability to Irrigation Water Loss: Assessing the Effects of Water Policy Change on Farmers in Idaho, USA.

In the Eastern Snake Plain of Idaho, increasing rates of groundwater extraction for irrigation have corresponded with the adoption of more efficient irrigation technologies; higher use and lower incidental recharge have led to increasing groundwater scarcity. This paper assesses farmer vulnerability to a water resource policy that responds to that scarcity by reducing availability of groundwater for irrigation by 4-20%. Using results from a household survey of impacted farmers, we examine vulnerability in two stages, contributing to theorization of farmer vulnerability in a changing climate as well as producing important regional policy insights. The first stage, multimodel selection and inference, analyzes the primary predictors of two forms of vulnerability to groundwater scarcity among this population of farmers. The second stage, a segmentation analysis, highlights policy-relevant variation in adaptive capacity and in vulnerability predictors across the population. Individual-level results indicate that key indicators of vulnerability include several dimensions of adaptive capacity and sensitivity. At the population level, we find that reductions in sensitivity may play an important role in reducing farmer vulnerability. Accelerating global environmental change will require agriculture in arid and semi-arid regions to adapt to shifts in water availability. As water resources shift, institutional contexts and policy landscapes will shift in parallel, as seen with the reduction in groundwater availability in our case study. These institutional shifts may change the face of adaptation and farmer vulnerability in unexpected ways. Our results indicate that such institutional shifts could lean on efforts to enhance farmer adaptive capacity or reduce farmer sensitivity as mechanisms for reducing farmer vulnerability to adaptation policy changes.

Spread of Zika virus in the Americas.

We use a data-driven global stochastic epidemic model to analyze the spread of the Zika virus (ZIKV) in the Americas. The model has high spatial and temporal resolution and integrates real-world demographic, human mobility, socioeconomic, temperature, and vector density data. We estimate that the first introduction of ZIKV to Brazil likely occurred between August 2013 and April 2014 (90% credible interval). We provide simulated epidemic profiles of incident ZIKV infections for several countries in the Americas through February 2017. The ZIKV epidemic is characterized by slow growth and high spatial and seasonal heterogeneity, attributable to the dynamics of the mosquito vector and to the characteristics and mobility of the human populations. We project the expected timing and number of pregnancies infected with ZIKV during the first trimester and provide estimates of microcephaly cases assuming different levels of risk as reported in empirical retrospective studies. Our approach represents a modeling effort aimed at understanding the potential magnitude and timing of the ZIKV epidemic and it can be potentially used as a template for the analysis of future mosquito-borne epidemics.

Climate Change as an Involuntary Exposure: A Comparative Risk Perception Study from Six Countries across the Global Development Gradient.

Climate change has been referred to as an involuntary exposure, meaning people do not voluntarily put themselves at risk for climate-related ill health or reduced standard of living. The purpose of this study is to examine people's risk perceptions and related beliefs regarding (1) the likelihood of different risks occurring at different times and places and (2) collective (government) responsibility and personal efficacy in dealing with climate change, as well as (3) explore the ways in which climate risk may be amplified when posed against individual health and well-being. Previous research on this topic has largely focused on one community or one nation state, and so a unique characteristic of this study is the comparison between six different city (country) sites by their development and national wealth. Here, we collected 401 surveys from Phoenix (USA), Brisbane (Australia), Wellington (New Zealand), Shanghai (China), Viti Levu (Fiji), and Mexico City (Mexico). Results suggest that the hyperopia effect characterized the sample from each study site but was more pronounced in developed sites, suggesting that the more developed sites employ a broader perspective when approaching ways to mitigate their risk against climate-related health and well-being impacts.

Community hygiene norm violators are consistently stigmatized: Evidence from four global sites and implications for sanitation interventions.

Community sanitation interventions increasingly leverage presumed innate human disgust emotions and desire for social acceptance to change hygiene norms. While often effective at reducing open defecation and encouraging handwashing, there are growing indications from ethnographic studies that this strategy might create collateral damage, such as reinforcing stigmatized identities in ways that can drive social or economic marginalization. To test fundamental ethnographic propositions regarding the connections between hygiene norm violations and stigmatized social identities, we conducted 267 interviews in four distinct global sites (in Guatemala, Fiji, New Zealand, USA) between May 2015 and March 2016. Based on 148 initial codes applied to 23,278 interview segments, text-based analyses show that stigmatizing labels and other indices of contempt readily and immediately attach to imagined hygiene violators in these diverse social settings. Moral concerns are much more salient at all sites than disease/contagion ones, and hygiene violators are extended little empathy. Contrary to statistical predictions, however, non-empathetic moral reactions to women hygiene violators are no harsher than those of male violators. This improved evidentiary base illuminates why disgust- and shame-based sanitation interventions can so easily create unintended social damage: hygiene norm violations and stigmatizing social devaluations are consistently cognitively connected.

Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation.

By informing timely targeted treatments, rapid whole-genome sequencing can improve the outcomes of seriously ill children with genetic diseases, particularly infants in neonatal and pediatric intensive care units (ICUs). The need for highly qualified professionals to decipher results, however, precludes widespread implementation. We describe a platform for population-scale, provisional diagnosis of genetic diseases with automated phenotyping and interpretation. Genome sequencing was expedited by bead-based genome library preparation directly from blood samples and sequencing of paired 100-nt reads in 15.5 hours. Clinical natural language processing (CNLP) automatically extracted children's deep phenomes from electronic health records with 80% precision and 93% recall. In 101 children with 105 genetic diseases, a mean of 4.3 CNLP-extracted phenotypic features matched the expected phenotypic features of those diseases, compared with a match of 0.9 phenotypic features used in manual interpretation. We automated provisional diagnosis by combining the ranking of the similarity of a patient's CNLP phenome with respect to the expected phenotypic features of all genetic diseases, together with the ranking of the pathogenicity of all of the patient's genomic variants. Automated, retrospective diagnoses concurred well with expert manual interpretation (97% recall and 99% precision in 95 children with 97 genetic diseases). Prospectively, our platform correctly diagnosed three of seven seriously ill ICU infants (100% precision and recall) with a mean time saving of 22:19 hours. In each case, the diagnosis affected treatment. Genome sequencing with automated phenotyping and interpretation in a median of 20:10 hours may increase adoption in ICUs and, thereby, timely implementation of precise treatments.