About
Titles
Professor Adjunct of Biostatistics
Biography
Professor Peter Diggle is currently an EPSRC Senior Fellow, leading a research programme in Spatial and Longitudinal Data Analysis at the University of Lancaster.
Current methodological themes include: geostatistical analysis; spatial and spatio-temporal point processes; joint modelling of repeated measurement and time-to-event outcomes in longitudinal studies. Current areas of application include: real-time disease surveillance; environmental exposure measurement; tropical disease prevalence mapping.
Diggle is founding co-editor of the journal "Biostatistics" and a trustee for the Biometrika Trust.
Appointments
Biostatistics
Professor AdjunctPrimary
Other Departments & Organizations
- Biostatistics
- Yale School of Public Health
Education & Training
- PhD
- Newcastle University (1977)
- MSc
- Oxford College (1973)
Research
Overview
Medical Subject Headings (MeSH)
Statistics as Topic
ORCID
0000-0003-3521-5020
Research at a Glance
Yale Co-Authors
Frequent collaborators of Peter Diggle's published research.
Publications Timeline
A big-picture view of Peter Diggle's research output by year.
Federico Costa, PhD
Albert Ko, MD
14Publications
18Citations
Publications
2024
Factors associated with differential seropositivity to Leptospira interrogans and Leptospira kirschneri in a high transmission urban setting for leptospirosis in Brazil
de Oliveira D, Khalil H, Palma F, Santana R, Nery N, Quintero-Vélez J, Zeppelini C, do Sacramento G, Cruz J, Lustosa R, Ferreira I, Carvalho-Pereira T, Diggle P, Wunder E, Ko A, Lopez Y, Begon M, Reis M, Costa F. Factors associated with differential seropositivity to Leptospira interrogans and Leptospira kirschneri in a high transmission urban setting for leptospirosis in Brazil. PLOS Neglected Tropical Diseases 2024, 18: e0011292. PMID: 38758957, PMCID: PMC11139309, DOI: 10.1371/journal.pntd.0011292.Peer-Reviewed Original ResearchAltmetricConceptsYears of ageResidents of low-income areasMultinomial logistic regression modelWork-related exposureEpidemiological patternsLow-income areasLogistic regression modelsInformal urban communitiesFactors associated with seropositivityCity of SalvadorPathogenic species of bacteriaUrban settingsUrban communitiesLongitudinal Data Analysis
Diggle P, Taylor-Robinson D. Longitudinal Data Analysis. 2024, 1-34. DOI: 10.1007/978-1-4614-6625-3_75-1.Peer-Reviewed Original ResearchConceptsTime-to-event outcomesBinary responsesTreatment of missing valuesClinical trials of drug therapyJoint modelTrials of drug therapyCystic fibrosis patientsLongitudinal studyLinear modelCross-sectional studySchizophrenia patientsFibrosis patientsLong-term progressionDrug therapyClinical trialsLung functionObservational studyNon-independencePatientsOutcome variablesStatistical methodsImproving the Cost-efficiency of Preventive Chemotherapy: Impact of New Diagnostics on Stopping Decisions for Control of Schistosomiasis
Coffeng L, Graham M, Browning R, Kura K, Diggle P, Denwood M, Medley G, Anderson R, de Vlas S. Improving the Cost-efficiency of Preventive Chemotherapy: Impact of New Diagnostics on Stopping Decisions for Control of Schistosomiasis. Clinical Infectious Diseases 2024, 78: s153-s159. PMID: 38662699, PMCID: PMC11045014, DOI: 10.1093/cid/ciae020.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsHow 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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsMass 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 proportionA 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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsOptimal 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 sanitationIntegrating 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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsPrevalence 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 outbreaksAudio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers
Coppock H, Nicholson G, Kiskin I, Koutra V, Baker K, Budd J, Payne R, Karoune E, Hurley D, Titcomb A, Egglestone S, Tendero Cañadas A, Butler L, Jersakova R, Mellor J, Patel S, Thornley T, Diggle P, Richardson S, Packham J, Schuller B, Pigoli D, Gilmour S, Roberts S, Holmes C. Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. Nature Machine Intelligence 2024, 6: 229-242. DOI: 10.1038/s42256-023-00773-8.Peer-Reviewed Original ResearchCitationsAltmetric
2023
Basic urban services fail to neutralise environmental determinants of ‘rattiness’, a composite metric of rat abundance
Carvalho-Pereira T, Eyre M, Zeppelini C, Espirito Santo V, Santiago D, Santana R, Palma F, Reis M, Lustosa R, Khalil H, Diggle P, Giorgi E, Costa F, Begon M. Basic urban services fail to neutralise environmental determinants of ‘rattiness’, a composite metric of rat abundance. Urban Ecosystems 2023, 27: 757-771. DOI: 10.1007/s11252-023-01481-2.Peer-Reviewed Original ResearchWastewater-based surveillance models for COVID-19: A focused review on spatio-temporal models
Torabi F, Li G, Mole C, Nicholson G, Rowlingson B, Smith C, Jersakova R, Diggle P, Blangiardo M. Wastewater-based surveillance models for COVID-19: A focused review on spatio-temporal models. Heliyon 2023, 9: e21734. PMID: 38053867, PMCID: PMC10694161, DOI: 10.1016/j.heliyon.2023.e21734.Peer-Reviewed Original ResearchCitationsAltmetricConceptsUsing a model-based geostatistical approach to design and analyse the prevalence of schistosomiasis in Kenya
Okoyo C, Minnery M, Orowe I, Owaga C, Wambugu C, Olick N, Hagemann J, Omondi W, Gichuki P, McCracken K, Montresor A, Fronterre C, Diggle P, Mwandawiro C. Using a model-based geostatistical approach to design and analyse the prevalence of schistosomiasis in Kenya. Frontiers In Tropical Diseases 2023, 4: 1240617. DOI: 10.3389/fitd.2023.1240617.Peer-Reviewed Original ResearchAltmetricConceptsTreatment strategy changesSchool-based deworming programmePublic health problemPrevalence of schistosomiasisWorld Health Organization guidelinesCross-sectional surveyHealth Organization guidelinesPredictive probabilitySCH prevalenceDeworming programsSchistosoma haematobiumHealth problemsSchistosoma mansoniOrganization guidelinesStudy designCounties of KenyaPrevalenceSchistosomiasisHighest predictive probabilityParasitic wormsTreatment requirementsTreatmentGuidelinesMorbidityHaematobium
Get In Touch
Contacts
Academic Office Number