A dynamic model for spread of livestock-associated methicillin-resistant Staphylococcus aureus on a pig farm, incorporating bacterial load and human exposure through air
Abstract
Livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) is widely distributed in the pig population in many countries, where its presence is undesirable, because as an opportunistic human pathogen, it poses a threat to human health. At present, there is a lack of knowledge regarding successful methods for eradication of LA-MRSA on a pig farm, which does not involve emptying the farm and culling all pigs. Some studies have reported an association between levels of LA-MRSA in the barn air and LA-MRSA carriage among humans entering or working in the pig barns. Therefore, interventions that are able to reduce the amount of LA-MRSA carried by the pigs and/or the concentration of LA-MRSA in the barn air, might be highly relevant if aiming for reducing the spread of LA-MRSA into the general human population. In the present study, an existing agent-based simulation model for spread of LA-MRSA within a pig herd was extended to also include LA-MRSA load and spread through air. This makes it possible to use the model 33 for studying the air exposure to LA-MRSA for humans entering the pig barns. The model was used for simulating various types of interventions in contaminated herds. At present quantitative data for nasal carriage of LA-MRSA in pigs are sparse, and many knowledge gaps regarding spread of LA-MRSA remain. Thus, our goal of building this model was not to provide exact values for risk reduction, but to avail a model that can be used for studying the effect of various types of interventions mechanistically, once more relevant data become available. Collection of more data on the influence of load is crucial for getting a better understanding of which possible interventions strategies, that might still have some potential in countries, where LA-MRSA has already spread to the majority of the pig population.
Info
Journal Article, 2020
UN SDG Classification
DK Main Research Area
Science/Technology
