AIMC Topic: Ixodes

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Variables for habitat and vertebrate hosts of Ixodes scapularis are the best ecological predictors of the spatial spread of Lyme disease in the United States (2010-2019).

Parasites & vectors
BACKGROUND: Lyme disease (LD) is a major public health concern in North America. The incidence of LD has increased in part due to the rapid expansion of Ixodes scapularis infected with Borrelia burgdorferi sensu lato (Bb), the causative agent of LD. ...

A machine learning framework for estimating the probability of blacklegged tick population establishment in eastern Canada using Earth observation data.

PloS one
Ixodes scapularis ticks are the primary vector of Lyme disease (LD) in North America, and their range has expanded into southeastern and southcentral Canada with climate change. This study presents a comprehensive machine learning (ML) framework to e...

Insights into the contribution of multiple factors on Ixodes ricinus abundance across Europe spanning 20 years using different machine learning algorithms.

Ticks and tick-borne diseases
The interplay of biotic and abiotic factors driving Ixodes ricinus abundance trends are not fully understood. Machine learning (ML) approaches are being increasingly used to explore this and predict future abundance patterns of this species, however,...

Machine learning algorithms for the evaluation of risk by tick-borne pathogens in Europe.

Annals of medicine
BACKGROUND: Tick-borne pathogens pose a major threat to human health worldwide. Understanding the epidemiology of tick-borne diseases to reduce their impact on human health requires models covering large geographic areas and considering both the abio...

Identification of public submitted tick images: A neural network approach.

PloS one
Ticks and tick-borne diseases represent a growing public health threat in North America and Europe. The number of ticks, their geographical distribution, and the incidence of tick-borne diseases, like Lyme disease, are all on the rise. Accurate, real...