Article

Functional data analysis techniques to improve the generalizability of near-infrared spectral data for monitoring mosquito populations

2020-04-29

Abstract excerpt

Near infrared spectroscopy is increasingly being used as an economical method to monitor mosquito vector populations in support of disease control. Despite this rise in popularity, strong geographical variation in spectra has proven an issue for generalising predictions from one location to another. Here, we use a functional data analysis approach—which models spectra as smooth curves rather than as a discrete set...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 1e9a97ea-6709-5710-9534-4bb7b8a1f5a8
DOI: 10.1101/2020.04.28.058495

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Functional data analysis techniques to improve the generalizability of near-infrared spectral data for monitoring mosquito populationsDOI 10.1101/2020.04.28.058495Read

Rapid age-grading and species identification of natural mosquitoes for malaria surveillanceSemantic proximity Read

Prediction of mosquito species and population age structure using mid-infrared spectroscopy and supervised machine learningSemantic proximity Read

Physiological and behavioural resistance of malaria vectors in rural West-Africa : a data mining study to address their fine-scale spatiotemporal heterogeneity, drivers, and predictabilitySemantic proximity Read

Rapid ageing and species identification of natural mosquitoes for malaria surveillanceSemantic proximity Read

Data-driven and interpretable machine-learning modeling to explore the fine-scale environmental determinants of malaria vectors biting rates in rural Burkina FasoSemantic proximity Read

Detection of Plasmodium falciparum infected Anopheles gambiae using near-infrared spectroscopySemantic proximity Read

Development and implementation of a passive surveillance system for Aedes albopictus in Emilia-Romagna, ItalySemantic proximity Read

embarcadero: Species distribution modelling with Bayesian additive regression trees in RSemantic proximity Read

A global set of Fourier-transformed remotely sensed covariates for the description of abiotic niche in epidemiological studies of tick vector speciesSemantic proximity Read

Using correlative and mechanistic species distribution models to predict vector-borne disease risk for the current and future environmental and climatic change: a case study of West Nile Virus in the UKSemantic proximity Read

Delimiting cryptic morphological variation among human malaria vector species using convolutional neural networksSemantic proximity Read