title: Big city, small world: density, contact rates, and transmission of dengue across Pakistan.
abstract: Macroscopic descriptions of populations commonly assume that encounters between individuals are well mixed; i.e. each individual has an equal chance of coming into contact with any other individual. Relaxing this assumption can be challenging though, due to the difficulty of acquiring detailed knowledge about the non-random nature of encounters. Here, we fitted a mathematical model of dengue virus transmission to spatial time-series data from Pakistan and compared maximum-likelihood estimates of 'mixing parameters' when disaggregating data across an urban-rural gradient. We show that dynamics across this gradient are subject not only to differing transmission intensities but also to differing strengths of nonlinearity due to differences in mixing. Accounting for differences in mobility by incorporating two fine-scale, density-dependent covariate layers eliminates differences in mixing but results in a doubling of the estimated transmission potential of the large urban district of Lahore. We furthermore show that neglecting spatial variation in mixing can lead to substantial underestimates of the level of effort needed to control a pathogen with vaccines or other interventions. We complement this analysis with estimates of the relationships between dengue transmission intensity and other putative environmental drivers thereof.
authors.affiliation: Department of Zoology, University of Oxford, Oxford OX1 3PS, UK moritz.kraemer@zoo.ox.ac.uk.
authors.forename: M U G
authors.initials: MU
authors.lastname: Kraemer
authors.affiliation: Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556, USA Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA.
authors.forename: T A
authors.initials: TA
authors.lastname: Perkins
authors.affiliation: Department of Epidemiology, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, MD 21205, USA.
authors.forename: D A T
authors.initials: DA
authors.lastname: Cummings
authors.affiliation: Department of Public Health, University of Punjab, Lahore 54590, Pakistan.
authors.forename: R
authors.initials: R
authors.lastname: Zakar
authors.affiliation: Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98121, USA.
authors.forename: S I
authors.initials: SI
authors.lastname: Hay
authors.affiliation: Department of Zoology, University of Oxford, Oxford OX1 3PS, UK Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA Sanaria Institute for Global Health and Tropical Medicine, Rockville, MD 20850, USA.
authors.forename: D L
authors.initials: DL
authors.lastname: Smith
authors.affiliation: Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN 47405, USA.
authors.forename: R C
authors.initials: RC
authors.lastname: Reiner
mesh_terms: D002947:Cities; D003140:Communicable Disease Control; D003715:Dengue / Q000453:epidemiology* / Q000635:transmission*; D003716:Dengue Virus; D004196:Disease Outbreaks; D005843:Geography; D006801:Humans; D016013:Likelihood Functions; D008962:Models, Theoretical; D010154:Pakistan / Q000453:epidemiology; D011157:Population Dynamics; D012424:Rural Population; D014505:Urban Population
keywords: dengue; epidemiology; heterogeneity; mixing; spatial accessibility; spatial dynamics