Geostatistical analysis of geomasked PFAS food contamination data in Veneto Region (Italy)

Giorgia Stoppa¹, Dolores Catelan¹, Michela Zamboni², Giuliano Fin², Naike Scatton², Laura Facciolo², Annibale Biggeri¹, Emanuele Giorgi³

1: Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy; 2: No Pfas Moms committee, Vicenza, Padua, Verona, Italy; 3: Lancaster Medical School, Lancaster University, Lancaster, United Kingdom

Long-term effects of air pollution on adolescents' mental health: A two-stage Bayesian approach including exposure uncertainty

Abi Riley¹, Marta Blangiardo¹, James Kirkbride², Fred Piel¹, Monica Pirani¹

1: Imperial College London, United Kingdom; 2: University College London, United Kingdom

A distributed-lag non-linear model for predictors with interacting effects

Sara Rutten¹, Thomas Neyens^1,2, Elisa Duarte¹, Christel Faes¹

1: I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium; 2: L-BioStat, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium

Measuring geographic access to emergency obstetric care: a comparison of travel time estimates modelled using Google Maps Directions API and AccessMod in three Nigerian conurbations

Peter M Macharia^1,2, Kerry LM Wong³, Lenka Beňová^1,3, Jia Wang⁴, Prestige Tatenda Makanga^5,6, Nicolas Ray^7,8, Aduragbemi Banke-Thomas^3,9,10

1: Institute of Tropical Medicine, Antwerp, Belgium; 2: Population & Health Impact Surveillance Group, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya; 3: Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom; 4: School of Computing & Mathematical Sciences, University of Greenwich, London, UK; 5: Surveying and Geomatics Department, Midlands State University Faculty of Science and Technology, Gweru, Midlands, Zimbabwe; 6: Climate and Health Division, Centre for Sexual Health and HIV/AIDS Research, Harare, Zimbabwe; 7: GeoHealth Group, Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland; 8: Institute for Environmental Sciences, University of Geneva, Geneva, Switzerland; 9: School of Human Sciences, University of Greenwich, London, United Kingdom; 10: Maternal and Reproductive Health Research Collective, Lagos, Nigeria

Spatial distribution of poultry farms using point pattern modelling: a method to address livestock environmental impacts and disease transmission risks

Marie-Cécile Dupas^1,2, Francesco Pinotti³, Chaitanya Joshi⁴, Madhvi Joshi⁴, Damer Blake⁵, Fiona Tomley⁵, Marius Gilbert¹, Guillaume Fournié^5,6

1: Université Libre de Bruxelles, Belgium; 2: Hasselt University, Belgium; 3: University of Oxford, UK; 4: Gujarat Biotechnology Research Centre, India; 5: Royal Veterinary College, UK; 6: INRAE, France

Analyzing urban landscapes through satellite data to predict abundance of Aedes mosquito breeding sites

Claire Teillet¹, Rodolphe Devillers¹, Annelise Tran², Thibault Catry¹, Renaud Marti³, Nadine Dessay¹, Joseph Rwagitinywa⁴, Johana Restrepo⁴, Emmanuel Roux¹

1: ESPACE-DEV, Univ Montpellier, IRD, Univ Guyane, Univ Reunion, Univ Antilles, Univ Avignon Maison de la Télédétection, 500 rue Jean‑François Breton, F‑34093 Montpellier, Cedex, France; 2: CIRAD, UMR TETIS, F-34398 Montpellier TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, Montpellier Maison de la Télédétection, 500 rue Jean‑François Breton, F‑34093 Montpellier, Cedex, France; 3: TETIS, Univ Montpellier, AgroParisTech, CIRAD, CNRS, INRAE, Montpellier INRAE, UMR TETIS, Montpellier Maison de la Télédétection, 500 rue Jean‑François Breton, F‑34093 Montpellier, Cedex, France; 4: Collectivité Territoriale de Guyane (CTG), Direction de la Démoustication 4179 Rte de Montabo, Cayenne 97300, Guyane française

Local distribution of cattle over Guadeloupe archipelago: an adapted method for disaggregating census data

Victor Dufleit¹, Laure Guerrini^2,3, Eric Etter^1,2

1: UMR ASTRE, CRVC, CIRAD, Guadeloupe (France); 2: ASTRE, Univ Montpellier, CIRAD, INRAE, Montpellier, France; 3: CIRAD, UMR ASTRE, Montpellier, France

Promoting healthy urban environments: the importance of integrate data and methods in the urban planning system

Eduarda Marques da Costa

Instituto de Geografia e Ordenamento do Território, Portugal

Addressing methodological challenges of boundary changes in longitudinal spatial epidemiology

Maria de Fatima de Pina^1,2

1: i3S / universidade do Porto, Portugal; 2: Oswaldo Cruz Foundation, Brazil

Capturing the spatiotemporal spread of COVID-19 in 30 EU/EEA countries during 2020 – 2022

Thi Huyen Trang Nguyen¹, Niel Hens^1,2, Christel Faes¹

1: Data Science Institute, Hasselt University, Belgium; 2: Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Belgium

Spatio-temporal dynamic of the COVID-19 epidemic and the impact of imported cases in Rwanda

Muhammed Semakula^1,4, François Niragire.², Sabin Nsanzimana¹, Eric Remera³, Christel Faes⁴

1: Rwanda Ministry of Health, Rwanda; 2: Department of Applied Statistics, University of Rwanda, Kigali; 3: Rwanda Biomedical Centre; 4: University of Hasselt

Social inequalities and the COVID-19 epidemic in France: territorial analyses by epidemic waves and metropolitan areas

Luka Canton¹, Pierre Schalkwijk¹, Jordi Landier¹, Stanislas Rebaudet^1,3, Emilie Mosnier^1,4, Pascal Handschumacher¹, Michelle Kelly Irving⁵, Cyrille Delpierre⁵, Stephanie Vandentorren^6,7, Jean Gaudart^1,2

1: Aix Marseille Univ, IRD, INSERM, SESSTIM, ISSPAM, Marseille, France; 2: AP-HM, Hop. La Timone, BioSTIC, Biostatistics & ICT, Marseille, France; 3: Hopital Europeen, Marseille, France; 4: French Agency for Research on AIDS, Viral Hepatitis and Emerging Infectious Diseases (ANRS-MIE), Phnom Penh, Cambodia; 5: CERPOP-UMR1295, EQUITY research team, Inserm, Université Toulouse III Paul Sabatier, Toulouse, France.; 6: Sante publique France, Saint Maurice France; 7: University of Bordeaux, ISPED, Centre INSERM U1219, Bordeaux Population Health, Bordeaux, France

Multiscale Spatio-temporal Modeling of Covid-19 case incidence and mortality

Andrew Booth Lawson¹, Brian Neelon¹, Gerard Chowell², Sijian Fan³

1: Medical University of South Carolina, United States of America; 2: Georgia State University, United States of America; 3: University of South Carolina, United States of America

Spatial variation in inequality distribution of all-cause and cause-specific premature mortality in Belgium since 2000

Martina Otavova¹, Bruno Masquelier¹, Christel Faes², Brecht Devleesschauwer³, Benjamin-Samuel Schluter⁴

1: Louvain University; 2: Hasselt University; 3: Sciensano; 4: University of Toronto

Socio-economic inequalities and access to healthcare during the COVID-19 pandemic: analyses in rural areas in southern France

Pierre Schalkwijk¹, Luka Canton¹, Jordi Landier¹, Stanislas Rebaudet^1,3, Emilie Mosnier^1,4, Pascal Handschumacher¹, Cyrille Delpierre⁵, Stephanie Vandentorren^6,7, Jean Gaudart^1,2

1: Aix Marseille Univ, IRD, INSERM, SESSTIM, ISSPAM, Marseille, France; 2: AP-HM, Hop. La Timone, BioSTIC, Biostatistics & ICT, Marseille, France; 3: Hopital Europeen, Marseille, France;; 4: French Agency for Research on AIDS, Viral Hepatitis and Emerging Infectious Diseases (ANRS-MIE), Phnom Penh, Cambodia; 5: CERPOP-UMR1295, EQUITY research team, Inserm, Université Toulouse III Paul Sabatier, Toulouse, France; 6: Sante publique France, Saint Maurice France; 7: University of Bordeaux, ISPED, Centre INSERM U1219, Bordeaux Population Health, Bordeaux, France

Model-based disease mapping using primary care registry data

Arne Janssens¹, Bert Vaes¹, Gijs Van Pottelbergh¹, Pieter Libin^1,2,3, Thomas Neyens^1,3

1: KU Leuven, Belgium; 2: Vrije Universiteit Brussel, Belgium; 3: UHasselt, Belgium

On Bayesian disease mapping and pandemic management

Ying MacNab

University of British Columbia, Canada

Demystifying spatial confounding

Emiko Dupont¹, Isa Marques², Thomas Kneib³

1: University of Bath, United Kingdom; 2: University of Glasgow, United Kingdom; 3: University of Gottingen, Germany

Scalable Bayesian disease mapping models with bigDM: a divide-and-conquer approach for analyzing high-dimensional data

Aritz Adin, Erick Orozco-Acosta, María Dolores Ugarte

Public University of Navarre, Spain

Joint outcome modelling of spatial COVID-19 incidence data for the senior population of Ontario, Canada, using a shared component model

Charmaine Dean

University of Waterloo, Canada

Utilisation of wastewater-based epidemiology in the post-pandemic era: a data integration approach

Guangquan Li^1,4, Peter Diggle^2,4, Marta Blangiardo^3,4

1: Northumbria University; 2: Lancaster University; 3: Imperial College London; 4: Turing-RSS Health Data Lab

Estimating sub-national surveillance sensitivity for wild poliovirus in Nigeria to inform declaration of elimination

Emily Nightingale

London School of Hygiene and Tropical Medicine, United Kingdom

Spatial-temporal Modelling Using Wastewater for Norovirus Surveillance

Ella Rose White, Marta Blangiardo, Monica Pirani

Imperial College London, United Kingdom

Spatial modelling of viral loads in wastewater: an evaluation of sampling strategies for comprehensive surveillence programs

James D Munday¹, Julien Riou², Moritz Wagner³, Nico Beerenwinkel¹, Christoph Ort⁵, Tim Julien⁴, Tanja Stadler¹

1: Department of Biosytems Science and Engineering, ETH Zürich, Switzerland; 2: Center for Primary Care and Public Health (Unisanté), University of Lausanne, Switzerlan; 3: Federal Office of Public Health, Switzerland; 4: Department Environmental Microbiology, Swiss Federal Institute of Aquatic Science and Technology (EAWAG), Switzerland; 5: Department Urban Water Management, Swiss Federal Institute of Aquatic Science and Technology (EAWAG), Switzerland

Assessing the impact of neighborhood structures in Bayesian disease mapping

Minh Hanh Nguyen¹, Thomas Neyens^1,2, Andrew B. Lawson^3,4, Christel Faes^1,2

1: Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium; 2: I-BioStat, Katholieke Universiteit Leuven, Leuven, Belgium; 3: Department of Public Health Sciences, Medical University of South Carolina, Charleston, USA; 4: Usher Institute, Population Health Sciences, School of Medicine, University of Edinburgh, UK

Disease mapping: What if Tobler's First Law of Geography doesn't hold?

Robin Muegge¹, Andrew Zammit-Mangion², Eilidh Jack¹, Nema Dean¹, Duncan Lee¹

1: School of Mathematics and Statistics, University of Glasgow, United Kingdom; 2: National Institute for Applied Statistics Research Australia, University of Wollongong, Wollongong, NSW, Australia

Optimizing the use of exceedance probabilities in disease mapping: a simulation study

Cristina Cametti¹, Thomas Neyens^1,2, Christel Faes²

1: KU Leuven, Belgium; 2: UHasselt, Belgium

Analysing time trends for cognitive impairment across the U.S.A states.

Sara Martino¹, Riebler Andrea¹, Anna Zajacova²

1: Norwegian University of Science and Technology, Norway; 2: University of Western Ontario, Canada.

A comparison of statistical and machine learning models for spatio-temporal prediction of ambient air pollutant concentrations in Scotland

Qiangqiang Zhu, Duncan Lee, Oliver Stoner

University of Glasgow, United Kingdom

Source apportionment of PM2.5 species data collected over space and time

Veronica Berrocal¹, Michela Frigeri², Alessandra Guglielmi²

1: University of California, Irvine, United States of America; 2: Politecnico di Milano, Milano, Italy

Estimation of a Proportional Hazards Model with Spatially-Dependent Errors through Presmoothing

Lorenzo Tedesco

University of Bergamo, Italy

Flexible scan statistic with restricted likelihood ratio for optimized COVID-19 surveillance

Ernest Akyereko¹, Alfred Stein¹, Frank Badu Osei¹, Kofi M. Nyarko²

1: University of Twente; 2: University of Environment and Sustainable Development

A novel approach to mapping Japanese encephalitis virus in Asia with convolutional neural networks

Alan Costello¹, Sean M Moore^1,2

1: University of Notre Dame, USA; 2: Eck Institute for Global Health, USA

Use of syndromic surveillance data in the design of climate-driven early warning systems for dengue epidemics: feasibility study in Cambodia

Léa Douchet^1,2, Florian Girond³, Morgan Mangeas², Kosal Sreang³, Heng Seng³, Sovann Ly³, Vincent Herbreteau^1,4

1: ESPACE-DEV, IRD, Univ Montpellier, Univ. Antilles, Univ Guyane, Univ Réunion, Phnom Penh, Cambodia; 2: ENTROPIE, IRD, Univ Reunion, CNRS, IFREMER, Univ Nouvelle Calédonie, Nouméa, New Caledonia; 3: Communicable Disease Control Department, Ministry of Health, Phnom Penh, Cambodia; 4: Institute of Technology of Cambodia, Phnom Penh, Cambodia

Spatiotemporally Explicit Epidemic Model for West Nile Virus Outbreak in Germany

Oliver Mbaoma, Stephanie Thomas, Carl Beierkuhnlein

University of Bayreuth, Germany, Germany

Enhancing Epidemic Intelligence with the MOOD Platform: Integration and Application in Public Health Surveillance

Sarah Houben¹, Tom Matheussen¹, Elena Arsevska², Timothée Dub³, Markus Neteler⁴, Annapaola Rizzoli⁵, Mathieu Roche², Maguelonne Teisseire⁶, Wim Van Bortel⁷, Maria Fernanda Vincenti-Gonzalez⁸, William Wint⁹

1: Avia-GIS, Belgium; 2: CIRAD, Montpellier, France; 3: THL, Helsinki, Finland; 4: Mundialis, Bonn, Germany; 5: Research and Innovation Centre, Edmund Mach Foundation, Trento, Italy; 6: INRAE, Montpellier, France; 7: ITG, Antwerpen, Belgium; 8: SpELL, ULB, Brussels, Belgium; 9: ERGO, Oxford, UK

Geospatial patterns of excess mortality in Belgium: Insights from the first year of the COVID-19 pandemic

Yessika Adelwin Natalia¹, Geert Molenberghs^1,2, Christel Faes¹, Thomas Neyens^1,2

1: I-BioStat, Data Science Institute, Hasselt University, Belgium; 2: I-BioStat, Leuven Biostatistics and Statistical Bioinformatics Centre, KU Leuven, Belgium

Spatial distribution and determinants of tuberculosis incidence in Mozambique: A nationwide Bayesian disease mapping study

Nelson Cuboia^1,2,3, Joana Reis-Pardal^1,2, Isabel Pfumo-Cuboia³, Ivan Manhiça⁴, Cláudia Mutaquiha⁴, Luis Nitrogénio⁵, Pereira Zindonga⁴, Luís Azevedo^1,2

1: Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine, University of Porto, Porto, Portugal; 2: CINTESIS@RISE – Center for Health Technology and Services Research (CINTESIS) & Health Research Network Associated Laboratory (RISE), University of Porto, Porto, Portugal; 3: Hospital Rural de Chicumbane, Limpopo, Mozambique; 4: Ministry of Health, National Tuberculosis Program, Maputo, Mozambique; 5: Gaza Provincial Health Directorate, Tuberculosis Program, Xai–Xai, Mozambique

Detecting Co-Occurring Clusters of Coronary Heart Disease and Depression in New England: A Neighborhood-Level Analysis

Theresa N. Faller^1,3, Michael R. Desjardins^2,3

1: Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, 21205; 2: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, 21205; 3: Spatial Science for Public Health Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, 21205

Geospatial clustering of auto-antibodies against apolipoprotein A-1, heavy metals and cardiovascular diseases in the city of Lausanne, Switzerland

Noé Fellay¹, Stéphane Joost¹, Nicolas Vuilleumier²

1: EPFL, Switzerland; 2: HUG, Switzerland

Design and analysis of randomised trials to estimate spatiotemporally heterogeneous treatment effects

Samuel I Watson¹, Thomas A Smith²

1: University of Birmingham, United Kingdom; 2: Swiss Tropical Research Institute, Basel, Switzerland

Small Area Estimation in Low- and Middle-Income Countries

Jon Wakefield

University of Washington

Leveraging spatial accessibility and catchment areas models to improve disease mapping

Peter M Macharia^1,2,3, Nicolas Ray^4,5, Caroline W. Gitonga², Robert W. Snow^2,6, Emanuele Giorgi³

1: Institute of Tropical Medicine Antwerp, Belgium; 2: Population & Health Impact Surveillance Group, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya; 3: Centre for Health Informatics, Computing, and Statistics, Lancaster Medical School, Lancaster University, Lancaster, UK; 4: GeoHealth group, Institute of Global Health, University of Geneva, Geneva, Switzerland; 5: Institute for Environmental Sciences, University of Geneva, Geneva, Switzerland; 6: Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK

Disentangling the effects of fine-scale mobility on leptospirosis infection using telemetry data

Pablo Ruiz Cuenza¹, Fabio Neves², Federico Costa², Max Eyre³, Jonathan Read¹, Emanuele Giorgi¹

1: Lancaster University, United Kingdom; 2: Instituto de Saúde Coletiva, Universidade Federal da Bahia, Salvador, Brazil; 3: London School of Hygiene and Tropical Medicine, United Kingdom

Spatial modeling in support of measles control and elimination

Katherine Rosenfeld

Bill & Melinda Gates Foundation, United States of America

A Declarative Approach to Metapopulation Modelling

Sebastiaan Weytjens^1,2, Niel Hens¹, Ann Nowé², Pieter Libin²

1: Hasselt University, Belgium; 2: Vrije Universiteit Brussel, Belgium

Uncertainty quantification in the predictions of a Ebola outbreak using Bayesian data assimilation

Tobias Wondwossen¹, Ashok Krishnamurthy¹, Michael Myer¹, Thomas White²

1: Mount Royal University, Canada; 2: University of Exeter, UK

Forecasting the spatial spread of an Ebola epidemic in real-time: comparing predictions of mathematical models and experts

James D Munday^1,2,3, Alicia Rosello^2,3, W. John Edmunds^2,3, Sebastian Funk^2,3

1: Department of Biosytems Science and Engineering, ETH Zürich, Switzerland; 2: Center for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, UK; 3: Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK

Plasma selenium concentrations are associated with spatial variation in maize selenium concentrations in Malawi; implications for assessing dietary selenium adequacy

Lucia Segovia de la Revilla¹, Claire Dooley², Elaine L. Ferguson¹, Edward J.M. Joy^1,3

1: LSHTM, United Kingdom; 2: The Bartlett Centre for Advanced Spatial Analysis, University College London, UK; 3: Rothamsted Research, United Kingdom

Disparities in timely antenatal care initiation in Kenya: A geostatistical modelling approach using Demographic and Health Survey data.

Faith F. Chimbandi¹, Guido Van Hal², Aline Semaan³, Lenka Benova^3,4, Peter M. Macharia^3,5

1: Global Health Institute, Family Medicine and Population Health Department, University of Antwerp, Antwerp, Belgium; 2: Social Epidemiology and Health Policy, Family Medicine and Population Health Department, University of Antwerp, Antwerp, Belgium; 3: Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium; 4: Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK; 5: Population & Health Impact Surveillance Group, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya

Estimating Subnational Under-Five Mortality Rates Using a Spatio-Temporal Age-Period-Cohort Model

Connor Gascoigne¹, Theresa Smith², John Paige³, Jon Wakefield⁴

1: Imperial College London, United Kingdom; 2: University of Bath, United Kingdom; 3: Norwegian University of Science and Technology, Norway; 4: University of Washington, Seattle

CANCELLED Identifying High-Risk areas for Untimely Administration of the Hepatitis B Birth Dose (HepB-BD) in low-income settings.

Jacob Mugoya Gizamba

University of southern California, United States of America

Model validation for small area estimation models using complex survey data

Zehang Richard Li

University of California, Santa Cruz, United States of America

Computationally efficient inference in disease mapping using anisotropic basis functions

Duncan Lee

University of Glasgow, United Kingdom

Trivariate shared Bayesian models to estimate ovarian cancer deaths attributable to asbestos exposure in Lombardy (Italy) in 2000-2018

Dolores Catelan¹, Giorgia Stoppa¹, Carolina Mensi², Lucia Fazzo³, Giada Minelli⁴, Valerio Manno⁴, Alessandro Marinaccio⁵, Dario Consonni², Annibale Biggeri¹

1: Unit of Biostatistics, Epidemiology and Public Health, DCTVPH, University of Padova,Padova, Italy; 2: Occupational Health Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy; 3: Department of Environment and Health, Italian National Institute of Health,Rome, Italy; 4: Statistical Service, Italian National Institute of Health, Rome, Italy; 5: Occupational and Environmental Medicine, Epidemiology and Hygiene Department, Italian Workers' Compensation Authority (INAIL), Rome, Italy

CANCELLED Assessing the Impact of the Modifiable Areal Unit Problem

Renato Assuncao^1,2, Vinícius Riffel², Lauren Bennett¹, Lynne Buie¹, Martha Bass¹, Kevin Butler¹

1: ESRI Inc., United States of America; 2: UFMG, Brazil

Quantifying the heterogeneous effect of mobile health code in containing COVID-19 in China during the pandemic

Zhifeng Cheng¹, Chu He², Samantha Cockings¹, Andrew Tatem¹, Shengjie Lai¹

1: WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, United Kingdom; 2: Department of Health Education, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China

Bayesian Age Decomposition Modeling of Covid-19 Space-time Dynamics

Andrew Booth Lawson^1,2, Yao Xin¹

1: Medical University of South Carolina, United States of America; 2: Usher Institute, University of Edinburgh, UK

The effect of spatial scale in agent-based model epidemiology

Robert Manning Smith¹, Sophie Ayling¹, Claire Dooley¹, Hamish Gibbs², Sarah Wise¹

1: Centre for Advanced Spatial Analysis, University College London, United Kingdom, London, UK; 2: Department of Geography, University College London, London, UK

An extended two-stage modelling framework for multi-location epidemiological studies

Antonio Gasparrini, Pierre Masselot

London School of Hygiene & Tropical Medicine, United Kingdom

Exploring the effects of air pollution on chronic diseases using Intego-network data

Elisa Duarte¹, Gijs Van Pottelbergh², Katrien Tersago³, Christel Faes¹, Thomas Neyens^1,4

1: I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium; 2: Department of Public Health and Primary Care, University of Leuven, Leuven, Belgium; 3: Department Care, Flemish Ministry on Welfare, Public Health and Family Matters, Brussels, Belgium; 4: L-BioStat, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium

Urban dengue hot- and coldspots in Lucknow, India: Unravelling the underlying environmental patterns.

Alan Esteban Juache Villagrana¹, Cedric Marsboom¹, Surender N. Sharma¹, Ritu Srivastava², Smita Dhawan², Bejo J. Raju³, Richa Sharma³, Raf Theunissen⁴, Jente Broeckx⁴, Hafeez Rehman⁴, Poornima Prabhakaran³, Guy Hendrickx¹

1: Avia-GIS, Zoersel, Belgium; 2: Public Health, Lucknow, India; 3: PHFI, Delhi, India; 4: VITO, Mol, Belgium

Heat-related mortality in Flanders (Belgium): combining dose-effect relationships with climate and land use modelling.

Els Verachtert¹, Dirk Lauwaet¹, Leo De Nocker¹, Elisa Duarte², Christel Faes², Koen Schoeters³

1: VITO, Environmental Intelligence Unit, Belgium; 2: Data Science Institute – University of Hasselt, Belgium; 3: Flemish Department of Care, Division Health Prevention Policy, Environmental healthcare

Spatial Insights into potential Health Benefits from Urban Traffic Reduction: Case-study on Car-Free Initiatives in European Capitals and pediatric asthma

Bram Vandeninden^1,2,3, Catherine Bouland¹, Christel Faes³, Eva M De Clercq²

1: ULB, Belgium; 2: Sciensano; 3: Hasselt University

Combining Laplace and VB for fast approximate Bayesian inference

Janet Van Niekerk, Haavard Rue

KAUST, Saudi Arabia

Bayesian modelling for the integration of spatially misaligned health and environmental data

Paula Moraga

KAUST, Saudi Arabia

Multivariate Models to Explore Gender-Based Violence in Areal Data

Lola Ugarte, Gonzalo Vicente, Tomas Goicoa

Universidad Publica de Navarra, Spain

Addressing Positional Anonymisation in Geostatistial Analyses of DHS Data

Geir-Arne Fuglstad, Umut Altay, John Paige, Andrea Riebler

Norwegian University of Science and Technology, Norway

Geostatistical and machine learning techniques for mapping vaccination coverage: A statistical comparison

Chigozie Edson Utazi, Ortis Yankey

University of Southampton, United Kingdom

Specification of space-time interactions for prediction in Bayesian disease mapping

Andrea Riebler, Jostein Aastebøl Aanes

NTNU, Norway

Integrating vulnerability and hazard in malaria risk mapping: the elimination context of Senegal

Camille Morlighem^1,2,3, Chibuzor Christopher Nnanatu^4,5, Catherine Linard^2,3,6

1: Fonds National de la Recherche Scientifique (F.R.S-FNRS), B-1000 Brussels, Belgium; 2: Department of Geography, University of Namur, 5000 Namur, Belgium; 3: ILEE, University of Namur, 5000 Namur, Belgium; 4: WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, SO17 1BJ, UK; 5: Department of Statistics, Nnamdi Azikiwe University, PMB 5025, Awka, Nigeria; 6: NARILIS, University of Namur, 5000 Namur, Belgium

Investigating cross nearest neighbor methods in multitype overlapping point patterns as heterogeneity measures for hepatitis B infected liver sample cell phenotypes

Jari Claes¹, Marjolein Crabbe², Kim Thys², Helena Geys², Simon Verheijden², Hans Wils², Annelies Agten¹, Christel Faes¹

1: Data Science Institute, Hasselt University, Diepenbeek, Belgium; 2: Janssen Research and Development, Janssen Pharmaceutica NV, Beerse, Belgium

Climate vulnerability and nutritional status variability in school-aged children and adolescents across the communities in the Mount Meru Ecosystem (Tanzania)

Monica Pirani

Imperial College London, United Kingdom

Linking spatial data sets with LLMs to enable global nutrition modeling.

Kyle Monahan

Tufts University

Modeling seasonality of malnutrition and effects of extreme weather on global food security.

Aishwarya Venkat

Tufts University

Challenges and opportunities in global spatiotemporal modeling of seasonal and pandemic influenza.

Elena Naumova

Tufts University

Geostatistical methods for efficient safety assessment of Ivermectin in Loa loa endemic areas.

Olatunji Johnson

University of Manchester, United Kingdom

Forecasting dengue incidence over space and time, in Thailand, 2013-2022

Yalda Jafari^1,2, Adam Howes³, Cathal Mills¹, Rory J. Gibb⁴, Kulchada Pongsoipetch², Suwanna Mukem², Sumali Bajaj¹, Joseph L.H. Tsui¹, Simon Busch Moreno¹, Moritz U.G. Kraemer¹, Adun Chayyaphong⁵, Chawarat Rotejanaprasert², Oliver J. Brady⁶, Richard J. Maude^1,2

1: University of Oxford, Oxford, United Kingdom; 2: Mahidol Oxford Tropical Medicine Research Unit, Bangkok, Thailand; 3: Imperial College, London, United Kingdom; 4: University College London, United Kingdom; 5: Bureau of Vector-Borne Diseases, Department of Disease Control, Bangkok, Thailand; 6: London School of Hygiene and Tropical Medicine, London, United Kingdom

Short-term effect of temperature and rainfall on the incidence of West Nile Neuroinvasive Disease in Europe: a multi-country case-crossover analysis.

Giovenale Moirano¹, Jan Semenza², Rachel Lowe¹

1: Barcelona Supercomputing Center, Spain; 2: Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany

Citizen science revolutionizing snail-borne diseases risk understanding in rural Uganda

Noelia del Carmen Valderrama Bhraunxs

KU Leuven / Royal Museum for Central Africa, Belgium

Towards Integrated Spatial Health Surveillance

Peter J Diggle¹, Marta A G Blangiardo², Guangquan Li³

1: Lancaster University, United Kingdom; 2: Imperial College, London, UK; 3: Northumbria University, Newcastle upon Tyne, UK

Joint geostatistical modelling of lymphatic filariasis antigenaemia and microfilariae prevalence

Claudio Fronterre

CHICAS, Lancaster University, United Kingdom

A spatio-temporal latent factor model for sparse multivariate time series in ecology

Maxime Fajgenblat^1,2, Thomas Neyens^1,3

1: Data Science Institute, I-BioStat, Hasselt University, Diepenbeek, Belgium; 2: Laboratory of Freshwater Ecology, Evolution and Conservation, KU Leuven, Leuven, Belgium; 3: Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat), Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium

The effect of spatio-temporal sample imbalance in epidemiologic surveillance using opportunistic samples: A case and simulation study using self-reported COVID-19 Symptoms Data

Alejandro Rozo^1,2, Christel Faes², Thomas Neyens^1,2

1: L-Biostat, KU Leuven, Belgium; 2: DSI, Hasselt University, Belgium