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Development of prediction models to identify hotspots of schistosomiasis in endemic regions to guide mass drug administration

Proceedings of the National Academy of Sciences(2024)10.1073/pnas.2315463120Source: DataRank Database

Development of prediction models to identify hotspots of schistosomiasis in endemic regions to guide mass drug administration is a research paper published in Proceedings of the National Academy of Sciences (2024). On theSindex it has a DataRank of 0. It has been cited 12 times.

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Open Access12 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (4 grants)Impact (FWCI 4.80)OA: hybridTopics (59)IDs (PubMed, PMC, OpenAlex)Annotations (1)SDGs (2)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (6)

Jean T. Coulibaly ORCID,Hailey J. Park,Jason R. Andrews ORCID,Isaac I. Bogoch ORCID,Nathan C. Lo ORCID

Live enrichment

PubMed:38181058 PMC:PMC10786280 OpenAlex:https://openalex.org/W4390604494

UC | UCSF | School of Medicine, University of California, San Francisco

Grant: UCSF Institute for Global Health Sciences Affiliate Faculty Seed Award

University Health Network

Grant: .

HHS | NIH | National Institute of Allergy and Infectious Diseases

Grant: DP2AI170485

National Institutes of Health

Grant: 1DP2AI170485-01

Real-time predictive modeling for public health departments to control infectious diseases

FWCI

4.80

Citation Percentile

1.0%

Citation Trend

2024

2025

2026

hybridLicense: cc-by

journalhttps://doi.org/10.1073/pnas.2315463120

publisherhttps://doi.org/10.1073/pnas.2315463120

publisherhttps://pnas.org/doi/pdf/10.1073/pnas.2315463120

repositoryhttps://pubmed.ncbi.nlm.nih.gov/38181058

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/10786280

Fields of Study

Parasites and Host InteractionsGlobal Maternal and Child HealthZoonotic diseases and public health0301 basic medicine03 medical and health sciences0303 health sciencesHumansAnimalsMass Drug AdministrationSchistosomiasisSchistosomiasis mansoniSchistosoma haematobiumModels, Statistical

MeSH Terms

Mass Drug AdministrationAnimalsHumansSchistosoma haematobiumSchistosomiasisSchistosomiasis mansoniModels, Statistical

Keywords

SchistosomiasisMass drug administrationSchistosoma haematobiumSchistosomaHotspot (geology)Neglected tropical diseasesTropical diseaseMedicineEnvironmental healthSchistosoma mansoniDemographyDiseaseImmunologyInternal medicinePopulationHelminthsPublic HealthMachine LearningHotspotsEmerging Zoonotic Diseases and One Health ApproachGlobal Impact of Helminth Infections and Control StrategiesSociologyHealth SciencesHumansAnimalsGlobal Maternal and Child Health OutcomesImmunology and MicrobiologyModels, StatisticalFOS: Clinical medicinePublic Health, Environmental and Occupational HealthLife SciencesGeologyFOS: Earth and related environmental sciencesBiological SciencesSchistosomiasis mansoniFOS: SociologyGeophysicsPediatrics, Perinatology and Child HealthParasitology

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Good health and well-being

Development of prediction models to identify hotspots of schistosomiasis in endemic regions to guide mass drug administration

FAIR Checklist

Authors (6)

Funding (4 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)