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The U.S. highway system is an iconic example of civil infrastructure. Yet it also exemplifies the challenges of infrastructure sustainability. The American Society for Civil Engineers gave the American road infrastructure a grade of "D" since the roads "are often crowded, frequently in poor condition, chronically underfunded, and are becoming more dangerous." In this paper, we seek to understand the intertwined social and technical processes that lead to this unsustainability by examining the U.S. highway system from the perspective of coupled infrastructure systems (CIS), a transdisciplinary framework that aims to analyze governance challenges of shared resources from a dynamic systems perspective. We use highways as a special example of the broader challenge of providing and maintaining the shared infrastructure of all types. Our analysis of historical data concludes that the unsustainability of highways as coupled infrastructure systems can be explained from dysfunctional information feedbacks. [ABSTRACT FROM AUTHOR]

Abstract Background Rainfall variability and associated remote sensing indices for vegetation are central to the development of early warning systems for epidemic malaria in arid regions. The considerable change in land-use practices resulting from increasing irrigation in recent decades raises important questions on concomitant change in malaria dynamics and its coupling to climate forcing. Here, the consequences of irrigation level for malaria epidemics are addressed with extensive time series data for confirmed Plasmodium falciparum monthly cases, spanning over two decades for five districts in north-west India. The work specifically focuses on the response of malaria epidemics to rainfall forcing and how this response is affected by increasing irrigation. Methods and Findings Remote sensing data for the Normalized Difference Vegetation Index (NDVI) are used as an integrated measure of rainfall to examine correlation maps within the districts and at regional scales. The analyses specifically address whether irrigation has decreased the coupling between malaria incidence and climate variability, and whether this reflects (1) a breakdown of NDVI as a useful indicator of risk, (2) a weakening of rainfall forcing and a concomitant decrease in epidemic risk, or (3) an increase in the control of malaria transmission. The predictive power of NDVI is compared against that of rainfall, using simple linear models and wavelet analysis to study the association of NDVI and malaria variability in the time and in the frequency domain respectively. Conclusions The results show that irrigation dampens the influence of climate forcing on the magnitude and frequency of malaria epidemics and, therefore, reduces their predictability. At low irrigation levels, this decoupling reflects a breakdown of local but not regional NDVI as an indicator of rainfall forcing. At higher levels of irrigation, the weakened role of climate variability may be compounded by increased levels of control; nevertheless this leads to no significant decrease in the actual risk of disease. This implies that irrigation can lead to more endemic conditions for malaria, creating the potential for unexpectedly large epidemics in response to excess rainfall if these climatic events coincide with a relaxation of control over time. The implications of our findings for control policies of epidemic malaria in arid regions are discussed.