Partitioning Social and Spatial Drivers of Infection Risk

Area of Science:

• Ecology
• Epidemiology
• Wildlife Disease Ecology

Background:

• Disease transmission models often assume homogenous mixing, which may not reflect real-world contact patterns.
• Spatial and social structures significantly influence heterogeneous contact behavior and disease spread.
• Wildlife disease dynamics are often poorly understood due to complex contact networks.

Purpose of the Study:

• To investigate the relationship between social and spatial behavior and disease exposure in Mastomys natalensis.
• To assess the correlation between spatial overlap and actual contact rates using proximity loggers.
• To understand the role of spatial structuring in the transmission of Morogoro virus (MORV).

Main Methods:

• Utilized an extensive capture-mark-recapture dataset of Mastomys natalensis.
• Employed miniaturized proximity loggers to measure direct contact rates.
• Analyzed home range overlap and spatial autocorrelation in relation to Morogoro virus (MORV) exposure.

Main Results:

• Exposure to MORV was strongly linked to home range overlap with exposed individuals.
• Home range overlap with conspecifics (regardless of exposure) showed a negative association with MORV exposure.
• Proximity logger data indicated that spatial overlap can overestimate direct contact, with most contacts involving a few individuals.

Conclusions:

• Spatial structuring and home range overlap are critical factors in understanding disease transmission dynamics in Mastomys natalensis.
• Homogenous mixing assumptions in disease models may be inadequate for wildlife populations with significant spatial structuring.
• Direct contact rates, rather than just spatial overlap, are key to accurately modeling disease spread in this rodent species.