Authors: Denis Valle, James S. Clark, Kaiguang Zhao
DOI: 10.1371/journal.pone.0027462
Abstract Summary
Novel modeling framework combines limited cross-sectional surveys with extensive surveillance data to better understand malaria transmission. Study of 486 individuals in Brazilian Amazon reveals forest proximity and activities as key infection drivers, while longer residence decreases infection risk but increases symptom likelihood when infected.
Why Brain? ðŸ§
Novel statistical model combines multiple malaria datasets to improve disease surveillance, revealing forest proximity as key infection risk factor and identifying optimal strategies for detecting asymptomatic carriers.
The image is AI-generated for illustrative purposes only. Courtesy of Midjourney.
