Spatially Explicit Conditions for Waterborne Pathogen Invasion

Abstract

Waterborne pathogens cause many possibly lethal human diseases. We derive the condition for pathogen invasion and subsequent disease outbreak in a territory with specific, space-inhomogeneous characteristics (hydrological, ecological, demographic, and epidemiological). The criterion relies on a spatially explicit model accounting for the density of susceptible and infected individuals and the pathogen concentration in a network of communities linked by human mobility and the water system. Pathogen invasion requires that a dimensionless parameter, the dominant eigenvalue of a generalized reproductive matrix J 0 , be larger than unity. Conditions for invasion are studied while crucial parameters (population density distribution, contact and water contamination rates, pathogen growth rates) and the characteristics of the networks (connectivity, directional transport, water retention times, mobility patterns) are varied. We analyze both simple, prototypical test cases and realistic landscapes, in which optimal channel networks mimic the water systems and gravitational models describe human mobility. Also, we show that the dominant eigenvector of J 0 effectively portrays the geography of epidemic outbreaks, that is, the areas of the studied territory that will be initially affected by an epidemic. This is important for planning an efficient spatial allocation of interventions (e.g., improving sanitation and providing emergency aid and medicines).

Aquatic invasive species: challenges for the future

“…Although controlling contamination and proliferation of potential pathogens in freshwater is extremely challenging (Cabral, 2010), their control could be achieved partly at the level of the host, such as by infection tracking in human populations. For example, Gatto et al (2013) observed that hydrological network, human mobility, and landscape complexity mediate the spread of diarrheal infections from Vibrio cholera that could be potentially modeled to predict which communities will be hit hardest during the epidemic.…”

Evolution and selection of river networks: Statics, dynamics, and complexity

“…Developments and applications of OCNs have appeared recently. For example, OCN arrangements have been used to design laboratory experiments with protist metacommunities where patches (true living ecosystems) are arranged in optimal network shapes to simulate the type of directional biological dispersal one expects in fluvial environments (47,48), or used in spatially explicit models of epidemics of waterborne disease where river networks act as ecological corridors for pathogens (49). The OCN concept of feasible optimality has inspired a number of studies on fractal structures in nature not necessarily related to true equilibrium properties of the system, e.g., a class of nonequilibrium interfaces in random exchanges Ising ferromagnets (50).…”

On the predictive ability of mechanistic models for the Haitian cholera epidemic

“…We argue that spatially disconnected models cannot directly account for the spatial mechanisms of pathogen dissemination (i.e. hydrological transport and human mobility), which play a crucial role in the initial phase of the outbreak, when the infection starts propagating into disease-free regions [13,48]. Conversely, spatial coupling may become less important when looking at longer time horizons, once the epidemic has already spread all across the country.…”