Lyme disease is a tick-borne infection caused by borrelia bacteria with essential implications for animals, humans, and the environment. This disease is transmitted to humans by infected blood-feeding ticks of the Ixodes genus. The disease is characterized by a red rash on the skin known as erythema migrans (EM) and leads to serious conditions if left untreated. Lyme disease is a chief example of the interconnectedness of animals, humans, and the environment. The rise of Lyme disease as a public health threat emphasizes the need for collaborative One Health approaches for the effective management of diseases. A One Health approach addresses the nature of the disease by considering human health, animal health, and ecological factors. Early detection of disease is a critical component of One Health. The use of advanced technologies such as AI by employing computer vision and a convolutional neural network (CNN) to identify ticks that are carriers of Lyme disease will enhance epidemiological surveillance and disease management strategies. Tick control measures using a One Health approach are crucial in mitigating Lyme disease. Tick control measures include the knowledge of ecological processes that affect tick populations, the development of sustainable interventions, and the promotion of public health awareness through research on ticks' behavior and disease transmission. The role of One Health in controlling Lyme disease cannot be ignored. One Health has the potential to significantly reduce the risk of Lyme disease in affected populations by implementing collaborative efforts such as surveillance, interdisciplinary research, and intervention strategies.
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Mitigating the Impact of Lyme Disease on One Health: A Holistic Approach
Published:
07 March 2025
by MDPI
in The 3rd International Electronic Conference on Animals
session One health: Improve Disease Manifestation and Management in Animals, Humans, and the Environment
Abstract:
Keywords: AI; Ixodes; One Health; Public Health; Rash; Surveillance; Ticks; Vector-borne illness
