Human mobility is a primary driver of infectious disease spread. However, existing data is limited in availability, coverage, granularity, and timeliness. Datadriven forecasts of disease dynamics are crucial for decisionmaking by health officials and private citizens alike. In this work, we focus on a machinelearned anonymized mobility map (hereon referred to as AMM) aggregated over hundreds of millions of smartphones and evaluate its utility in forecasting epidemics. We factor AMM into a metapopulation model to retrospectively forecast influenza in the USA and Australia. We show that the AMM model performs onpar with those based on commuter surveys, which aremore »
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Abstract 
Free, publiclyaccessible full text available July 1, 2022

Discrete dynamical systems serve as useful formal models to study diffusion phenomena in social networks. Motivated by applications in systems biology, several recent papers have studied algorithmic and complexity aspects of diffusion problems for dynamical systems whose underlying graphs are directed, and may contain directed cycles. Such problems can be regarded as reachability problems in the phase space of the corresponding dynamical system. We show that computational intractability results for reachability problems hold even for dynamical systems on directed acyclic graphs (dags). We also show that for dynamical systems on dags where each local function is monotone, the reachability problemmore »Free, publiclyaccessible full text available May 18, 2022

We study evacuation dynamics in a major urban region (Mi ami, FL) using a combination of a realistic population and social contact network, and an agentbased model of evacuation behavior that takes into account peer influence and concerns of looting. These factors have been shown to be important in prior work, and have been modeled as a thresholdbased network dynamical systems model (2modethreshold), which involves two threshold parameters  for a family's decision to evacuate and to remain in place for looting and crime concerns  based on the fraction of neighbors who have evacuated. The dynamics of such modelsmore »

Data from surveys administered after Hurricane Sandy provide a wealth of information that can be used to develop models of evacuation decisionmaking. We use a model based on survey data for predicting whether or not a family will evacuate. The model uses 26 features for each household including its neighborhood characteristics. We augment a 1.7 million node householdlevel synthetic social network of Miami, Florida with public data for the requisite model features so that our population is consistent with the surveybased model. Results show that household features that drive hurricane evacuations dominate the e ects of specifying large numbers ofmore »

Neighborhood e ects have an important role in evacuation decisionmaking by a family. Owing to peer influence, neighbors evacuating can motivate a family to evacuate. Paradoxically, if a lot of neighbors evacuate, then the likelihood of an individual or family deciding to evacuate decreases, for fear of crime and looting. Such behavior cannot be captured using standard models of contagion spread on networks, e.g., threshold, independent cascade, and linear threshold models. Here, we propose a new thresholdbased graph dynamical system model, 2modethreshold, which captures this dichotomy. We study theoretically the dynamical properties of 2modethreshold in di fferent networks, and fimore »

Webbased interactions enable agents to coordinate and generate collective action. Coordination can facilitate the spread of contagion to large groups within networked populations. In game theoretic contexts, coordination requires that agents share common knowledge about each other. Common knowledge emerges within a group when each member knows the states and the thresholds (preferences) of the other members, and critically, each member knows that everyone else has this information. Hence, these models of common knowledge and coordination on communication networks are fundamentally di fferent from influencebased unilateral contagion models, such as those devised by Granovetter and Centola. Moreover, these models utilizemore »

As the complexity of our food systems increases, they also become susceptible to unanticipated natural and humaninitiated events. Commodity trade networks are a critical component of our food systems in ensuring food availability. We develop a generic datadriven framework to construct realistic agricultural commodity trade networks. Our work is motivated by the need to study food flows in the context of biological invasions. These networks are derived by fusing gridded, administrativelevel, and survey datasets on production, trade, and consumption. Further, they are periodic temporal networks reflecting seasonal variations in production and trade of the crop. We apply this approach tomore »

We consider the simultaneous propagation of two contagions over a social network. We assume a threshold model for the propagation of the two contagions and use the formal framework of discrete dynamical systems. In particular, we study an optimization problem where the goal is to minimize the total number of infected nodes subject to a budget constraint on the total number of nodes that can be vaccinated. While this problem has been considered in the literature for a single contagion, our work considers the simultaneous propagation of two contagions. Since the optimization problem is NPhard, we develop a heuristic basedmore »

We investigate questions related to the time evolution of discrete graph dynamical systems where each node has a state from {0,1}. The configuration of a system at any time instant is a Boolean vector that specifies the state of each node at that instant. We say that two configurations are similar if the Hamming distance between them is small. Also, a predecessor of a configuration B is a configuration A such that B can be reached in one step from A. We study problems related to the similarity of predecessor configurations from which two similar configurations can be reached inmore »