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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.

Human perception of risks related to economic damages caused by nearby wildlife can be transmitted through social networks. Understanding how sharing risk information within a human community alters the spatial dynamics of human‐wildlife interactions has important implications for the design and implementation of effective conservation actions. We developed an agent‐based model that simulates farmer livelihood decisions and activities in an agricultural landscape shared with a population of a generic wildlife species (wildlife‐human interactions in shared landscapes [WHISL]). In the model, based on risk perception and economic information, farmers decide how much labor to allocate to farming and whether and where to exclude wildlife from their farms (e.g., through fencing, trenches, or vegetation thinning). In scenarios where the risk perception of farmers was strongly influenced by other farmers, exclusion of wildlife was widespread, resulting in decreased quality of wildlife habitat and frequency of wildlife damages across the landscape. When economic losses from encounters with wildlife were high, perception of risk increased and led to highly synchronous behaviors by farmers in space and time. Interactions between wildlife and farmers sometimes led to a spillover effect of wildlife damage displaced from socially and spatially connected communities to less connected neighboring farms. The WHISL model is a useful conservation‐planning tool because it provides a test bed for theories and predictions about human‐wildlife dynamics across a range of different agricultural landscapes. Article impact statement: Sharing of risk perception in social networks alters spatial patterns of human‐wildlife interactions, sometimes creating spillover effects. [ABSTRACT FROM AUTHOR]

The Amazon is Brazil's greatest natural resource and invaluable to the rest of the world as a buffer against climate change. The recent election of Brazil's president brought disputes over development plans for the region back into the spotlight. Historically, the development model for the Amazon has focused on exploitation of natural resources, resulting in environmental degradation, particularly deforestation. Although considerable attention has focused on the long-term global cost of "losing the Amazon," too little attention has focused on the emergence and reemergence of vector-borne diseases that directly impact the local population, with spillover effects to other neighboring areas. We discuss the impact of Amazon development models on human health, with a focus on vector-borne disease risk. We outline policy actions that could mitigate these negative impacts while creating opportunities for environmentally sensitive economic activities. This Perspective article maintains that a development model for the Amazon must be bold, creative, carefully planned, and sustainable, explicitly acknowledging the importance of public health in reinforcing economic development, environmental protection, and land use change. [ABSTRACT FROM AUTHOR]

Highlights • A cellular automata model synthetizes the transition from the Chilean evergreen forest to savanna. • The patch-size distribution of the forest provides a leading indicator of the transition. • The indicator of the transition suggests a robust criticality before the collapse of the forest. • Indicators of transition can support livestock management in forest landscapes. Abstract Semi-desert areas are sensitive to changes in rainfall and agricultural pressure, prone to abrupt changes and to the collapse of ecological functions. The sclerophyllous evergreen forest of central Chile, known as matorral , has been extensively overgrazed by domestic livestock. As a consequence, the native and endemic species of this forest community have been replaced by a savanna-type environment dominated by the species Acacia caven , known as espinales. It has been hypothesized that the collapse of matorral forest can be abrupt, and the two ecosystems represent two alternative stable states. To understand the ecological dynamics that occur during this transition, their signature in space, and the consequences of livestock management, a cellular automata model that considers the local interaction among forest vegetation, Acacia, and livestock management was developed. By simulating and analyzing the process of fragmentation in space and time, in a gradient of livestock pressure and aridity, the results show that the system exhibits properties of "robust criticality", with a shift of patch-size distributions from models matching power-laws to models matching truncated power-laws as livestock pressure increases nearby the point of collapse. Simulation results in scenarios with rotation of livestock at the tipping point reveal the interaction between resting frequency and forest conservation. These results provide information to design better management strategies in human-modified landscapes in the remaining Chilean matorral. [ABSTRACT FROM AUTHOR]

Dengue is known to transmit between humans and A. aegypti mosquitoes living in neighboring houses. Although transmission is thought to be highly heterogeneous in both space and time, little is known about the patterns and drivers of transmission in groups of houses in endemic settings. We carried out surveys of PCR positivity in children residing in 2-block patches of highly endemic cities of Colombia. We found high levels of heterogeneity in PCR positivity, varying from less than 30% in 8 of the 10 patches to 56 and 96%, with the latter patch containing 22 children simultaneously PCR positive (PCR22) for DEN2. We then used an agent-based model to assess the likely eco-epidemiological context of this observation. Our model, simulating daily dengue dynamics over a 20 year period in a single two block patch, suggests that the observed heterogeneity most likely derived from variation in the density of susceptible people. Two aspects of human adaptive behavior were critical to determining this density: external social relationships favoring viral introduction (by susceptible residents or infectious visitors) and immigration of households from non-endemic areas. External social relationships generating frequent viral introduction constituted a particularly strong constraint on susceptible densities, thereby limiting the potential for explosive outbreaks and dampening the impact of heightened vectorial capacity. Dengue transmission can be highly explosive locally, even in neighborhoods with significant immunity in the human population. Variation among neighborhoods in the density of local social networks and rural-to-urban migration is likely to produce significant fine-scale heterogeneity in dengue dynamics, constraining or amplifying the impacts of changes in mosquito populations and cross immunity between serotypes. [ABSTRACT FROM AUTHOR]

Highlights: [•] The temporal dynamics of unstable malaria control is of relevance to elimination. [•] Control (IRS) increases nonlinearly with previous incidence (API) in arid NW India. [•] This ‘reactive’ policy is investigated with a rainfall-driven mosquito-human model. [•] ‘Reactive’ control can generate transient disease cycles of about ten years. [•] Control based on rainfall variability proves more effective. [ABSTRACT FROM AUTHOR]

Land-use change is the main force behind ecological and social change in many countries around the globe; it is primarily driven by resource needs and external economic incentives. Concomitantly, transformations of the land are the main drivers for the emergence and re-emergence of malaria. An understanding of malaria population dynamics in transforming landscapes is lacking, despite its relevance for developmental and public health policies. We develop a mathematical model that couples malaria epidemiology with the socio-economic and demographic processes that occur in a landscape undergoing land-use change. This allows us to identify different types of malaria dynamics that can arise in early stages of this transformation. In particular, we show that an increase in transmission followed by either a decline, or a further enhancement, of risk is a common outcome. This increase results from the asymmetry between the relatively fast ecological changes in transformed landscapes, and the slower pace of investment in malaria protection. These results underscore the importance of reducing ecological risk, while providing services and economic opportunities to early migrants for longer periods. Consideration of these socio-ecological processes and, more importantly, the temporal scale on which they act, is critical to avoid potential bifurcations that lead to long-lasting endemic malaria.

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.