Comparing the effects of non-homogenous mixing patterns on epidemiological outcomes in equine populations: A mathematical modelling study

Abstract

Disease transmission models often assume homogenous mixing. This assumption, however, has the potential to misrepresent the disease dynamics for populations in which contact patterns are non-random. A disease transmission model with an SEIR structure was used to compare the effect of weighted and unweighted empirical equine contact networks to weighted and unweighted theoretical networks generated using random mixing. Equine influenza was used as a case study. Incidence curves generated with the unweighted empirical networks were similar in epidemic duration (5–8 days) and peak incidence (30.8–46.4%). In contrast, the weighted empirical networks resulted in a more pronounced difference between the networks in terms of the epidemic duration (8–15 days) and the peak incidence (5–25%). The incidence curves for the empirical networks were bimodal, while the incidence curves for the theoretical networks were unimodal. The incorporation of vaccination and isolation in the model caused a decrease in the cumulative incidence for each network, however, this effect was only seen at high levels of vaccination and isolation for the complete network. This study highlights the importance of using empirical networks to describe contact patterns within populations that are unlikely to exhibit random mixing such as equine populations.

Equine Influenza Virus: An Old Known Enemy in the Americas

“…Long- and short-term transportation affects physiological, endocrine, and immune responses as soon as 15 min post-transport, implying that horses may be vulnerable to disease during and almost immediately after short-term transport [ 90 ]. In mathematical modeling, mixing vaccinated and unvaccinated animals and the use of isolation could not only reduce disease burden in equine populations but also reduce disease transmission and decrease the cumulative incidence of EIV [ 91 , 92 ]. In 174 thoroughbred foals, the antibody response to primary EIV vaccination was assessed, finding that there is a positive relationship between vaccination doses and EIV antibody titers, which demonstrates the poor response to primary vaccination, in addition to showing the relevance of serological surveillance to evaluate herd immunity and specific EIV antibodies in foals [ 93 ].…”

Spatial and temporal variation in proximity networks of commercial dairy cattle in Great Britain

“…Including empirically-determined contact networks rather than homogeneous mixing in transmission models can alter epidemic predictions. In groups of beef cattle, horses, and dogs, using empirical contact data produced lower estimates of epidemic size and duration, compared to simulating random mixing of individuals ( Duncan et al, 2012 ; Milwid et al, 2019a ; Wilson-Aggarwal et al, 2019 ). Incorporating heterogeneous contact structure into within-farm disease transmission models has enabled the dynamics of other cattle infections, including Mycobacterium avium subsp.…”

Epidemiological Model With Anomalous Kinetics: Early Stages of the COVID-19 Pandemic

“…The latter hypothesis constitutes an oversimplification, particularly for the COVID-19 pandemic, due to strong government intervention (social distancing; lockdown) and underreporting as the number of cases grows beyond testing capacity. Diverse aspects are discussed, assuming homogeneous or nonhomogeneous mixing, in epidemiological models in general [2][3][4], as well as in the current pandemic [5][6][7][8][9][10][11][12][13][14][15].…”