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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.
Last Updated on April 07, 2025.
Appointments
Biostatistics
Professor AdjunctPrimary
Other Departments & Organizations
Education & Training
- PhD
- Newcastle University (1977)
- MSc
- Oxford College (1973)
Research
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Overview
Medical Research Interests
Statistics as Topic
Public Health Interests
Modeling
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
Jamie Childs, ScD
Mitermayer Reis, MD
30Publications
175Citations
Publications
2025
Topography and environmental deficiencies are associated with chikungunya virus exposure in urban informal settlements in Salvador, Brazil
Travis C, Argibay H, Pellizzaro M, de Oliveira D, Santana R, Palma F, Lustosa R, Santana J, Souza F, López Y, Reis M, Ko A, Diggle P, Ribeiro G, Begon M, Costa F, Khalil H, Eyre M. Topography and environmental deficiencies are associated with chikungunya virus exposure in urban informal settlements in Salvador, Brazil. PLOS Neglected Tropical Diseases 2025, 19: e0013477. PMID: 40911655, PMCID: PMC12440227, DOI: 10.1371/journal.pntd.0013477.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsConceptsUrban informal settlementsPublic health burdenLow-income communitiesInformal settlementsGlobal public health burdenBinomial mixed-effects modelDegree of urbanisationHealth burdenMixed-effects modelsCHIKV seroprevalenceEnvironmental deficienciesReduced riskAssociated with seropositivityRisk factorsUrban communitiesMale sexBrazilian citiesRiskHouseholdsCommunityCHIKV seropositivityIndividualsEnvironmental factorsExposure patternsDomains individualsUsing Model-Based Geostatistics to Refine Population-Based Estimates of Trachoma Prevalence: Update from a Technical Consultation.
Harte A, Sasanami M, Burgert-Brucker C, Bakhtiari A, Bisanzio D, Jimenez C, Solomon A, Kabona G, Masika M, Ngondi J, Ante-Testard P, Arnold B, Baayenda G, Cuenca P, Diggle P, Edirweera D, Emerson P, Fronterre C, Gass K, Newbury L, Hooper P, Kamau E, Kebede F, Kyomuhangi I, Lietman T, McCracken K, Minnery M, Nash S, Nicholls T, Olobio N, Palmer S, Saeedzai S, Somerville S, Stern C, Stukel D, Szwarcwald C, Talero S, Yevstigneyeva V, Kello A, Harding-Esch E, Giorgi E. Using Model-Based Geostatistics to Refine Population-Based Estimates of Trachoma Prevalence: Update from a Technical Consultation. American Journal Of Tropical Medicine And Hygiene 2025 PMID: 40744002, DOI: 10.4269/ajtmh.25-0023.Peer-Reviewed Original ResearchCitationsConceptsPopulation-based estimatesCentre for Health InformaticsModel-based geostatisticsHealth informaticsTrachoma prevalenceTechnical consultationWHO Collaborating CentreTrachoma elimination programsCollaborating CentreResearch prioritiesProgram managersElimination statusConsultationMeeting presentationsUnited KingdomGeostatistical methodsTrachomaDisease researchKnowledge gapsGeostatisticsDecision-makingProbability thresholdPeter J Diggle’s contribution to the Discussion of ‘Some statistical aspects of the Covid-19 response’ by Wood et al
Diggle P. Peter J Diggle’s contribution to the Discussion of ‘Some statistical aspects of the Covid-19 response’ by Wood et al. Journal Of The Royal Statistical Society Series A (Statistics In Society) 2025, qnaf078. DOI: 10.1093/jrsssa/qnaf078.Peer-Reviewed Original ResearchSpatial Point Pattern
Diggle P. Spatial Point Pattern. 2025, 2387-2391. DOI: 10.1007/978-3-662-69359-9_585.Peer-Reviewed Original ResearchIs multiple sclerosis a length-dependent central axonopathy? Some empirical data from the TONiC study
Mills R, Schlüter D, Diggle P, Tennant A, Young C, Group T. Is multiple sclerosis a length-dependent central axonopathy? Some empirical data from the TONiC study. Multiple Sclerosis And Related Disorders 2025, 101: 106594. PMID: 40570401, DOI: 10.1016/j.msard.2025.106594.Peer-Reviewed Original ResearchVector-borne helminthiases: a road map for current and future research to support control and elimination in sub-Saharan Africa
Kamgno J, Adeleke M, Basáñez M, Coulibaly Y, de Souza D, Debrah L, Debrah A, Diggle P, Nana-Djeunga H, Domché A, Gass K, Hoerauf A, Hopkins A, Klion A, Mackenzie C, Mwingira U, Njenga S, Nutman T, Nwane P, Stolk W, Unnasch T, Kelly-Hope L. Vector-borne helminthiases: a road map for current and future research to support control and elimination in sub-Saharan Africa. The Lancet Infectious Diseases 2025, 25: e555-e604. PMID: 40541223, DOI: 10.1016/s1473-3099(25)00084-2.Peer-Reviewed Original ResearchCitationsAltmetricA systematic review of variables associated with snakebite risk in spatial and temporal analyses
Collinson S, Lamb T, Cardoso I, Diggle P, Lalloo D. A systematic review of variables associated with snakebite risk in spatial and temporal analyses. Transactions Of The Royal Society Of Tropical Medicine And Hygiene 2025, 119: 1084-1099. PMID: 39817354, PMCID: PMC12403204, DOI: 10.1093/trstmh/trae131.Peer-Reviewed Original ResearchCitationsConceptsSystematic reviewJoanna Briggs Institute toolHealth facility reportingRisk estimation accuracyWeb of ScienceNarrative synthesisFacility reportsStudy qualityAd hoc surveyResearch availabilityHigh-risk regionsIncidence dataSub-Saharan AfricaUrban residentsGlobal healthPositive associationSnakebite riskInstitutional toolsRisk variationStatistical associationNegative associationSub-SaharanCase incidenceAssociationRiskCommunity-based snakebite risk mapping for resource prioritisation in Eastern Province, Rwanda
Ediriweera D, Hakizimana D, Diggle P, Schurer J. Community-based snakebite risk mapping for resource prioritisation in Eastern Province, Rwanda. Transactions Of The Royal Society Of Tropical Medicine And Hygiene 2025, 119: 310-316. PMID: 39749566, DOI: 10.1093/trstmh/trae069.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsSnakebite incidenceHealth worker trainingResource prioritisationEvidence-based decisionsEastern ProvinceResource-poor countriesHousehold visitsSnakebite preventionSnakebite eventsSurveillance of peopleSnakebite riskWorker trainingWell-trained personnelMedical emergencyHigh riskLow riskRisk mapsSnakebite envenomingRiskPrediction mapsSnakebitePrioritisationGeostatistical modelSpatial variationLow incidence
2024
Cost-effectiveness of comparative survey designs for helminth control programs: Post-hoc cost analysis and modelling of the Kenyan national school-based deworming program
Minnery M, Okoyo C, Morgan G, Wang A, Johnson O, Fronterre C, Montresor A, Campbell S, Mwandawiro C, Diggle P. Cost-effectiveness of comparative survey designs for helminth control programs: Post-hoc cost analysis and modelling of the Kenyan national school-based deworming program. PLOS Neglected Tropical Diseases 2024, 18: e0011583. PMID: 39621813, PMCID: PMC11666021, DOI: 10.1371/journal.pntd.0011583.Peer-Reviewed Original ResearchAltmetricUnderstanding 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 ResearchCitationsMeSH Keywords and ConceptsConceptsPredictive 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 levels
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