Highly dynamic animal contact network and implications on disease transmission

Abstract

Contact patterns among hosts are considered as one of the most critical factors contributing to unequal pathogen transmission. Consequently, networks have been widely applied in infectious disease modeling. However most studies assume static network structure due to lack of accurate observation and appropriate analytic tools. In this study we used high temporal and spatial resolution animal position data to construct a high-resolution contact network relevant to infectious disease transmission. The animal contact network aggregated at hourly level was highly variable and dynamic within and between days, for both network structure (network degree distribution) and individual rank of degree distribution in the network (degree order). We integrated network degree distribution and degree order heterogeneities with a commonly used contact-based, directly transmitted disease model to quantify the effect of these two sources of heterogeneity on the infectious disease dynamics. Four conditions were simulated based on the combination of these two heterogeneities. Simulation results indicated that disease dynamics and individual contribution to new infections varied substantially among these four conditions under both parameter settings. Changes in the contact network had a greater effect on disease dynamics for pathogens with smaller basic reproduction number (i.e. R0 < 2).

Figure 1. Observed time series of total degree in the animal contact network.

Total degree is the sum of the degree of all node/individual cattle, which, in this study, is equivalent to the total number of contacts within each hour. Grey area is bracketed by the 1^st and 3^rd quantiles. A clear diurnal cycle of number of contacts exists for all three pens. Such cycle vanishes if aggregated at the daily level.

Figure 2. Observed animal contact networks during 2 AM, 8 AM, 2 PM, and 8 PM.

Showing 21 cattle in Pen #1 on August 11, 2011. Line width is proportional to the number of contacts in that time period, i.e. the thickest line corresponds to the largest number of contacts between two cattle. Thickness of the lines is not directly comparable between different hours.

Figure 3. Mean degree order of animals in observed and hypothetical pens.

The rank of each animal in each hour was recorded and averaged for the entire 192-h period. For comparison, we simulated a hypothetical group of 21 individuals with constant rank (from 1 to 21) through the entire period. Note pen #3 had 27 individuals instead of 21 as in pen #1 and #2.

Figure 4. Time series of mean daily prevalence under four simulated conditions.

C1: no temporal variability nor degree order change; C2: no temporal variability with order change; C3: temporal variability with no order change; and C4: temporal variability with order change. The dynamics of these four conditions vary substantially for both parameter sets. (A) . (B) . The time series data are in hourly resolution, and the figure is shown/labeled at a daily resolution.