Understanding the impact of covariates on the classification of implementation units for soil-transmitted helminths control: a case study from Kenya
Puranik A, Diggle P, Odiere M, Gass K, Kepha S, Okoyo C, Mwandawiro C, Wakesho F, Omondi W, Sultani H, Giorgi E. Understanding the impact of covariates on the classification of implementation units for soil-transmitted helminths control: a case study from Kenya. BMC Medical Research Methodology 2024, 24: 294. PMID: 39614175, PMCID: PMC11606136, DOI: 10.1186/s12874-024-02420-1.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsChildCross-Sectional StudiesHelminthiasisHelminthsHumansKenyaModels, StatisticalPrevalenceSoilConceptsPredictive inferenceRemotely sensed covariatesSimulation studyModel-based geostatisticsGeostatistical modelImpact of covariatesSpatially referenced covariatesSample sizeModern statistical methodsModel-based geostatistical methodsCross-sectional surveyCovariatesReduced sample sizeClassification of areasPrevalence predictionsInferenceDisease riskMethodsThis studyPrevalenceSub-countyPrevalence levelsA Comparison of Markov and Mechanistic Models for Soil-Transmitted Helminth Prevalence Projections in the Context of Survey Design
Eyre M, Bulstra C, Johnson O, de Vlas S, Diggle P, Fronterrè C, Coffeng L. A Comparison of Markov and Mechanistic Models for Soil-Transmitted Helminth Prevalence Projections in the Context of Survey Design. Clinical Infectious Diseases 2024, 78: s146-s152. PMID: 38662703, PMCID: PMC11045013, DOI: 10.1093/cid/ciae022.Peer-Reviewed Original ResearchConceptsOptimal survey designImpact assessment surveysSurvey designProjected prevalenceGeostatistical methodsPrevalence surveySampling designSchool-aged childrenPreventive chemotherapySoil-transmitted helminthsPrevalence projectionsControl programsWorld Health OrganizationAssessment surveyPrevalence dataSub-Saharan AfricaMechanistic modelTarget of PCSoutheast AsiaHealth OrganizationMechanistic methodsPrevalenceBillion peopleSub-SaharanInadequate sanitationHow Does the Proportion of Never Treatment Influence the Success of Mass Drug Administration Programs for the Elimination of Lymphatic Filariasis?
Kura K, Stolk W, Basáñez M, Collyer B, de Vlas S, Diggle P, Gass K, Graham M, Hollingsworth T, King J, Krentel A, Anderson R, Coffeng L. How Does the Proportion of Never Treatment Influence the Success of Mass Drug Administration Programs for the Elimination of Lymphatic Filariasis? Clinical Infectious Diseases 2024, 78: s93-s100. PMID: 38662701, PMCID: PMC11045024, DOI: 10.1093/cid/ciae021.Peer-Reviewed Original ResearchConceptsMass drug administrationElimination of lymphatic filariasisEfficacious treatment regimensLymphatic filariasisLevels of NTMass drug administration programmesYears of annual treatmentTreatment regimensDrug combinationsTransmission settingsMass drug administration programsDrug AdministrationTreatment coveragePrevalenceTransmission areasMDA coverageBaselineProportion of peopleTreatmentPrevalence thresholdImpact of NTAlbendazoleDiethylcarbamazineHighest infection prevalenceHighest proportionIntegrating wastewater and randomised prevalence survey data for national COVID surveillance
Li G, Diggle P, Blangiardo M. Integrating wastewater and randomised prevalence survey data for national COVID surveillance. Scientific Reports 2024, 14: 5124. PMID: 38429366, PMCID: PMC10907376, DOI: 10.1038/s41598-024-55752-9.Peer-Reviewed Original ResearchConceptsPrevalence dataPrevalence surveySurveillance systemCollection of health dataDisease prevalenceMeasures of prevalenceLocal disease prevalenceWastewaterSpatial resolutionWastewater dataPrevalence survey dataHealth dataReduced scaleDisease metricsCoarser spatial resolutionDisease-agnosticPrevalenceCOVID-19 pandemicSurveillance toolPost-pandemic settingEarly detectionNon-epidemic periodsCost-effective mannerSurveyDetect outbreaks