In this work we explore the effects of human mobility on the dispersion of a vector borne disease. We combine an already presented stochastic model for dengue with a simple representation of the daily motion of humans on a schematic city of 20 × 20 blocks with 100 inhabitants in each block. The pattern of motion of the individuals is described in terms of complex networks in which links connect different blocks and the link length distribution is in accordance with recent findings on human mobility. It is shown that human mobility can turn out to be the main driving force of the disease dispersal.

No abstract

We present a stochastic dynamical model for the transmission of dengue that considers the co-evolution of the spatial dynamics of the vectors (Aedes aegypti) and hosts (human population), allowing the simulation of control strategies adapted to the actual evolution of an epidemic outbreak. We observed that imposing restrictions on the movement of infected humans is not a highly effective strategy. In contrast, isolating infected individuals with high levels of compliance by the human population is efficient even when implemented with delays during an ongoing outbreak. We also studied insecticide-spraying strategies assuming different (hypothetical) efficiencies. We observed that highly efficient fumigation strategies seem to be effective during an outbreak. Nevertheless, taking into account the controversial results on the use of spraying as a single control strategy, we suggest that carrying out combined strategies of fumigation and isolation during an epidemic outbreak should account for a suitable strategy for the attenuation of epidemic outbreaks.

We introduce a dengue model (SEIR) where the human individuals are treated on an individual basis (IBM) while the mosquito population, produced by an independent model, is treated by compartments (SEI). We study the spread of epidemics by the sole action of the mosquito. Exponential, deterministic and experimental distributions for the (human) exposed period are considered in two weather scenarios, one corresponding to temperate climate and the other to tropical climate. Virus circulation, final epidemic size and duration of outbreaks are considered showing that the results present little sensitivity to the statistics followed by the exposed period provided the median of the distributions are in coincidence. Only the time between an introduced (imported) case and the appearance of the first symptomatic secondary case is sensitive to this distribution. We finally show that the IBM model introduced is precisely a realization of a compartmental model, and that at least in this case, the choice between compartmental models or IBM is only a matter of convenience.

No abstract