Spreading of rodent infestations through a city

Abstract

This paper details a network-based analysis of the spreading of rodent infestations through a city under varying conditions. Models of two very different cities, Tulsa, OK, USA and Providence, RI, USA, are created as geometric graphs using publicly available map data. The SIR epidemic model is applied with varying parameters, and the resulting infestation rates are measured. Results indicate that the density of a city, the size of the largest connected component (from the point of view of a rodent migrating to a new location), and the distance and probability of migration all play a role in determining the resulting rate of infestation. Results obtained are consistent with infestation patterns and rates reported by studies of other similarly dense city environments. For Providence a targeted attack simulation is run, which shows that carefully targeted extermination interventions could reduce infestation in the city by approximately 40%.

Network centrality for the identification of biomarkers in respondent-driven sampling datasets

“…Network analysis of spreading has been conducted in many contexts, such as in terms of social contacts [ 18 ] and rodent infestations [ 19 ], among others. Because contacts are generally known and can be traced, network analysis is particularly suited to sexually transmitted diseases, such as gonorrhoea [ 20 ] and chlamydia [ 21 ] in addition to HIV [ 22 ].…”