Parasitic Infections in Livestock: Pathophysiology and Immune Response
DOI:
https://doi.org/10.63964/atmj.2025.1.2.4Keywords:
livestock parasites; pathophysiology; immune polarization; oxidative stress; Haemonchus contortus; Fasciola hepatica; anthelmintic resistance; immune evasion; vaccination; systems biologyAbstract
Background: Parasitic infections remain a major constraint on global livestock productivity, contributing to substantial economic losses and compromised food security, particularly in developing regions. The biological complexity of host-parasite interactions — spanning protozoan, helminthic, and ectoparasitic infestations — governs infection outcomes, pathological severity, and therapeutic response through mechanisms that are only partially understood.
Objective: This narrative review critically analyzes the pathophysiology, immune polarization dynamics, oxidative stress mechanisms, and therapeutic landscape of major livestock parasites — including Theileria, Babesia, Trypanosoma, Fasciola, Haemonchus, Trichostrongylus, and Eimeria — with a focus on immune evasion strategies, anthelmintic resistance, and a systems biology perspective.
Key Findings: Protozoan parasites predominantly drive Th1 polarization (IFN-γ, TNF-α), while helminths classically elicit Th2 responses (IL-4, IL-5, IL-13, IgE). Regulatory T cell (Treg) expansion is common to most chronic parasitoses and undermines effector immunity. Oxidative stress — manifested by elevated MDA and depleted SOD, GPx, and GSH — is commonly associated with many major livestock parasitoses, though its magnitude varies considerably by parasite species, infection stage, and host immune status. Anthelmintic resistance represents a critical and escalating global challenge.
Conclusion: Effective management of livestock parasitosis requires integrated approaches combining targeted antiparasitic chemotherapy, resistance management, immunomodulatory nutritional support, host genetic resistance selection, and evidence-based vaccination. Future research must prioritize AI-assisted diagnostics, multi-omics characterization of resistance, and climate-adaptive epidemiological modeling.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License.



