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Isabel J Jones

Biographic Data

ID6927654
NAMEIsabel J Jones
GIVEN NAMESIsabel J
FAMILY NAMEJones
SIGNATUREJONES I J
AFFILIATIONSPacific University
ORCID0000-0002-5784-885X
VERIFIEDYes
TOTAL WORKS6
TOTAL CITATIONS4
AUTHOR COUNT6
EDITOR COUNT0
FIRST PUBLICATION YEAR2019
LATEST PUBLICATION YEAR2023
H-INDEX1
  • Climatic, land-use and socio-economic factors can predict malaria dynamics at fine spatial scales relevant to local health actors

    Open Access•Julie D Pourtois, Krti Tallam et al.•ARTICLE•PLOS Global Public Health•2023

    While much progress has been achieved over the last decades, malaria surveillance and control remain a challenge in countries with limited health care access and resources. High-resolution predictions of malaria incidence using routine surveillance data could represent a powerful tool to health practitioners by targeting malaria control activities where and when they are most needed. Here, we investigate the predictors of spatio-temporal malaria …

  • Environmental Persistence of the World's Most Burdensome Infectious and Parasitic Diseases

    Open Access•Skylar Hopkins, Skylar R Hopkins et al.•ARTICLE•Frontiers in Public Health•2022

    Humans live in complex socio-ecological systems where we interact with parasites and pathogens that spend time in abiotic and biotic environmental reservoirs (e.g., water, air, soil, other vertebrate hosts, vectors, intermediate hosts). Through a synthesis of published literature, we reviewed the life cycles and environmental persistence of 150 parasites and pathogens tracked by the World Health Organization's Global Burden of Disease study. We u…

  • Three reasons why expanded use of natural enemy solutions may offer sustainable control of human infections

    Open Access•Isabel J Jones, Susanne H Sokolow et al.•ARTICLE•People and Nature•2022

    Many infectious pathogens spend a significant portion of their life cycles in the environment or in animal hosts, where ecological interactions with natural enemies may influence pathogen transmission to people. Yet, our understanding of natural enemy opportunities for human disease control is lacking, despite widespread uptake and success of natural enemy solutions for pest and parasite management in agriculture. Here we explore three reasons wh…

  • Identification of Snails and Schistosoma of Medical Importance via Convolutional Neural Networks

    Open Access•Krti Tallam, Zac Yung-Chun Liu et al.•ARTICLE•Frontiers in Public Health•2021

    In recent decades, computer vision has proven remarkably effective in addressing diverse issues in public health, from determining the diagnosis, prognosis, and treatment of diseases in humans to predicting infectious disease outbreaks. Here, we investigate whether convolutional neural networks (CNNs) can also demonstrate effectiveness in classifying the environmental stages of parasites of public health importance and their invertebrate hosts. W…

  • How to identify win–win interventions that benefit human health and conservation

    Open Access•Skylar Hopkins, Susanne H Sokolow et al.•ARTICLE•Nature Sustainability•2020•Cited by: 4•References: 7

  • Modelled effects of prawn aquaculture on poverty alleviation and schistosomiasis control

    Open Access•Christopher M Hoover, Susanne H Sokolow et al.•ARTICLE•Nature Sustainability•2019

  • How to identify win–win interventions that benefit human health and conservation

    Open Access•Skylar Hopkins, Susanne H Sokolow et al.•ARTICLE•Nature Sustainability•2020•Cited by: 4•References: 7

  • Modelled effects of prawn aquaculture on poverty alleviation and schistosomiasis control

    Open Access•Christopher M Hoover, Susanne H Sokolow et al.•ARTICLE•Nature Sustainability•2019

  • How to identify win–win interventions that benefit human health and conservation

    Open Access•Skylar Hopkins, Susanne H Sokolow et al.•ARTICLE•Nature Sustainability•2020•Cited by: 4•References: 7

  • Identification of Snails and Schistosoma of Medical Importance via Convolutional Neural Networks

    Open Access•Krti Tallam, Zac Yung-Chun Liu et al.•ARTICLE•Frontiers in Public Health•2021

    In recent decades, computer vision has proven remarkably effective in addressing diverse issues in public health, from determining the diagnosis, prognosis, and treatment of diseases in humans to predicting infectious disease outbreaks. Here, we investigate whether convolutional neural networks (CNNs) can also demonstrate effectiveness in classifying the environmental stages of parasites of public health importance and their invertebrate hosts. W…

  • Environmental Persistence of the World's Most Burdensome Infectious and Parasitic Diseases

    Open Access•Skylar Hopkins, Skylar R Hopkins et al.•ARTICLE•Frontiers in Public Health•2022

    Humans live in complex socio-ecological systems where we interact with parasites and pathogens that spend time in abiotic and biotic environmental reservoirs (e.g., water, air, soil, other vertebrate hosts, vectors, intermediate hosts). Through a synthesis of published literature, we reviewed the life cycles and environmental persistence of 150 parasites and pathogens tracked by the World Health Organization's Global Burden of Disease study. We u…

  • Three reasons why expanded use of natural enemy solutions may offer sustainable control of human infections

    Open Access•Isabel J Jones, Susanne H Sokolow et al.•ARTICLE•People and Nature•2022

    Many infectious pathogens spend a significant portion of their life cycles in the environment or in animal hosts, where ecological interactions with natural enemies may influence pathogen transmission to people. Yet, our understanding of natural enemy opportunities for human disease control is lacking, despite widespread uptake and success of natural enemy solutions for pest and parasite management in agriculture. Here we explore three reasons wh…

  • Climatic, land-use and socio-economic factors can predict malaria dynamics at fine spatial scales relevant to local health actors

    Open Access•Julie D Pourtois, Krti Tallam et al.•ARTICLE•PLOS Global Public Health•2023

    While much progress has been achieved over the last decades, malaria surveillance and control remain a challenge in countries with limited health care access and resources. High-resolution predictions of malaria incidence using routine surveillance data could represent a powerful tool to health practitioners by targeting malaria control activities where and when they are most needed. Here, we investigate the predictors of spatio-temporal malaria …

Biology (5 works) · Ecology (5 works) · Environmental resource management (4 works) · Medicine (4 works) · Zoonotic diseases and public health (4 works) · Disease (3 works) · Economics (3 works) · Geography (3 works) · Climate Change and Health Impacts (2 works) · Computer Science (2 works)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae