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Impact of inaccurate laboratory test result on the spread of infectious disease: Mathematical modelling approach
Abstract
This study examines the impact of diagnostic inaccuracies on the transmission dynamics of infectious diseases using an extended SEIR model. By incorporating compartments for false-positive and falsenegative cases, the model simulates the effects of faulty testing, no testing, and varying testing rates on disease progression. Simulations reveal that while no testing results in rapid disease spread, introducing a 10% testing rate significantly reduces infections but generates substantial diagnostic errors—1.8 million false positives and 600,000 false negatives within 40 days. These findings underscore the critical role of accurate testing in mitigating false negatives, reducing undetected transmission, and optimizing public health interventions. The model bridges the gap between theoretical epidemiology and practical disease management, offering actionable insights for enhancing testing strategies to improve epidemic control.