Advances in Artificial Intelligence for Infectious Disease Surveillance in Livestock in Zambia

Abstract

The global livestock industry grapples with formidable challenges stemming from the escalation and dissemination of infectious diseases. Zambia, an agricultural cornerstone where livestock is pivotal for economic sustenance and food security, confronts the imperative task of effectually surveilling and managing infectious diseases. This study investigates into the possibilities of the application of artificial intelligence (AI) for infectious disease surveillance in the Zambian livestock sector. The study meticulously scrutinizes the prevailing state of infectious disease surveillance, evaluates the latent capabilities of AI technologies, and critically discusses the intricate landscape of challenges and opportunities entailed in their implementation.

In the intricate tapestry of Zambia's economy, livestock farming assumes a central and irreplaceable role, contributing substantially to the well-being and livelihoods of a significant portion of the populace. However, the omnipresent specter of infectious diseases perpetually menaces livestock health, casting a shadow on productivity and economic equilibrium. Conventional methodologies in disease surveillance exhibit inherent shortcomings, characterized by delays in reporting and inherent inaccuracies. This study is an exploration of possibilities of the AI applications designed to fortify infectious disease surveillance within Zambia's livestock domain. The infusion of AI technologies holds the transformative potential to reshape disease monitoring paradigms, enabling early detection and facilitating swift response strategies in the face of emerging threats. The ensuing critical analysis navigates the intricate terrain of the application of AI in the Zambian livestock context, shedding light on its promising prospects, while pragmatically addressing the hurdles that may accompany its incorporation.