Perspectives on the role of mobility, behavior, and time scales in the spread of diseases

Abstract

The dynamics, control, and evolution of communicable and vectorborne diseases are intimately connected to the joint dynamics of epidemiological, behavioral, and mobility processes that operate across multiple spatial, temporal, and organizational scales. The identification of a theoretical explanatory framework that accounts for the pattern regularity exhibited by a large number of host-parasite systems, including those sustained by host-vector epidemiological dynamics, is but one of the challenges facing the coevolving fields of computational, evolutionary, and theoretical epidemiology. Host-parasite epidemiological patterns, including epidemic outbreaks and endemic recurrent dynamics, are characteristic to well-identified regions of the world; the result of processes and constraints such as strain competition, host and vector mobility, and population structure operating over multiple scales in response to recurrent disturbances (like El Niño) and climatological and environmental perturbations over thousands of years. It is therefore important to identify and quantify the processes responsible for observed epidemiological macroscopic patterns: the result of individual interactions in changing social and ecological landscapes. In this perspective, we touch on some of the issues calling for the identification of an encompassing theoretical explanatory framework by identifying some of the limitations of existing theory, in the context of particular epidemiological systems. Fostering the reenergizing of research that aims at disentangling the role of epidemiological and socioeconomic forces on disease dynamics, better understood as complex adaptive systems, is a key aim of this perspective.infectious disease | risk | complex adaptive systems | mobility | behavior

Dynamics of disease spread. Effect of the characteristic times

“…It becomes irregular as the probability (ϕ) increases. In the model of Watts and Strogatz [14], the rewired short-cuts made the network composed of local clusters, whereas that of Newman and Watts [21] is a single local cluster.…”

“…Small World Network and Scale Free models have been used extensively to study human disease and other spreads (computer virus, rumor, etc.) [15][16][17][18][19][20][21][22][23][24]. Zekri and Clerc found that infection grows exponentially [25] above the percolation threshold [26].…”

“…However, this model [25] neglected some realistic parameters like the characteristic times of disease (latency and infection times), and the force of infection. Further models including various effects such as vaccination and strategies for disease eradication [15,18], connection length [19][20][21][22][23][24]27], fluctuations and correlations [24], and cost control of epidemics [15,19] have been proposed. Recently a distribution of Latency time was used to study the global stability of spread dynamics [28].…”

Human–environment interactions in population and ecosystem health

“…The focus of several papers in this issue was predictive modeling, particularly how the interrelated dynamics of disease transmission and human behavior influence the ecology, evolution, and control of infectious diseases (29) across spatial, temporal, and organizational scales. Using a model of intrapatch disease spread and interpatch mobility, Castillo-Chavez et al (33) illustrate the limitations of existing theoretical frameworks with respect to modeling such complex adaptive systems. The authors call for the formulation of improved theoretical frameworks that can encompass such processes and disentangle the role of epidemiological and socio-economic forces.…”

Source-sink dynamics could sustain HIV epidemics in rural communities in sub-Saharan Africa: the case of Malawi

“…We define a sink to be a community where transmission is not self-sustaining [16]; in this community, ℛ " < 1. To model mobility/travel, we use a generalized Lagrangian approach proposed by Castillo-Chavez and colleagues [17][18][19]. This modeling approach allows individuals to remain identifiable as residents of their home community when they are in other communities.…”