71 citations · 152 across the 35 of their papers we have counts for
25 papers · 1 filter
BARTSIMP: flexible spatial covariate modeling and prediction using Bayesian additive regression trees
Alex Ziyu Jiang, Jon Wakefield
Prediction is a classic challenge in spatial statistics and the inclusion of spatial covariates can greatly improve predictive performance when incorporated into a model with laten…
Small Area Estimation with Random Forests and the LASSO
Victoire Michal, Jon Wakefield, Alexandra M. Schmidt +3
We consider random forests and LASSO methods for model-based small area estimation when the number of areas with sampled data is a small fraction of the total areas for which estim…
Semi-Parametric Inference for Doubly Stochastic Spatial Point Processes: An Approximate Penalized Poisson Likelihood Approach
Si Cheng, Jon Wakefield, Ali Shojaie
Doubly-stochastic point processes model the occurrence of events over a spatial domain as an inhomogeneous Poisson process conditioned on the realization of a random intensity func…
Modeling Urban/Rural Fractions in Low- and Middle-Income Countries
Yunhan Wu, Jon Wakefield
In low- and middle-income countries, household surveys are the most reliable data source to examine health and demographic indicators at the subnational level, an exercise in small…
Incorporating testing volume into estimation of effective reproduction number dynamics
Isaac H. Goldstein, Jon Wakefield, Volodymyr M. Minin
Branching process inspired models are widely used to estimate the effective reproduction number -- a useful summary statistic describing an infectious disease outbreak -- using cou…
Spatial Aggregation with Respect to a Population Distribution
John Paige, Geir-Arne Fuglstad, Andrea Riebler +1
Spatial aggregation with respect to a population distribution involves estimating aggregate quantities for a population based on an observation of individuals in a subpopulation. I…
A Computationally Efficient Approach to Fully Bayesian Benchmarking
Taylor Okonek, Jon Wakefield
In small area estimation, it is sometimes necessary to use model-based methods to produce estimates in areas with little or no data. In official statistics, we often require that s…
Smoothed Model-Assisted Small Area Estimation
Peter A. Gao, Jon Wakefield
In countries where population census data are limited, generating accurate subnational estimates of health and demographic indicators is challenging. Existing model-based geostatis…
A Bayesian hierarchical small-area population model accounting for data source specific methodologies from American Community Survey, Population Estimates Program, and Decennial Census data
Emily N Peterson, Rachel C Nethery, Tullia Padellini +6
Small area estimates of population are necessary for many epidemiological studies, yet their quality and accuracy are often not assessed. In the United States, small area estimates…
Statistical implications of relaxing the homogeneous mixing assumption in time series Susceptible-Infectious-Removed models
Luis D. J. Martinez Lomeli, Michelle N. Ngo, Jon Wakefield +2
Infectious disease epidemiologists routinely fit stochastic epidemic models to time series data to elucidate infectious disease dynamics, evaluate interventions, and forecast epide…
A Statistical Introduction to Template Model Builder: A Flexible Tool for Spatial Modeling
Aaron Osgood-Zimmerman, Jon Wakefield
The integrated nested Laplace approximation (INLA) is a well-known and popular technique for spatial modeling with a user-friendly interface in the R-INLA package. Unfortunately, o…
The Central Role of the Identifying Assumption in Population Size Estimation
Serge Aleshin-Guendel, Mauricio Sadinle, Jon Wakefield
The problem of estimating the size of a population based on a subset of individuals observed across multiple data sources is often referred to as capture-recapture or multiple-syst…
Estimating Seroprevalence of SARS-CoV-2 in Ohio: A Bayesian Multilevel Poststratification Approach with Multiple Diagnostic Tests
David Kline, Zehang Li, Yue Chu +4
Globally the SARS-CoV-2 coronavirus has infected more than 59 million people and killed more than 1.39 million. Designing and monitoring interventions to slow and stop the spread o…
A Probabilistic Model for Analyzing Summary Birth History Data
Katie Wilson, Jon Wakefield
BACKGROUND There is an increasing demand for high quality subnational estimates of under-five mortality. In low and middle income countries, where the burden of under-five mortalit…
Estimating efficacy of measles supplementary immunization activities via discrete-time modeling of disease incidence time series
Tracy Qi Dong, Jon Wakefield
Measles is a significant source of global disease burden and child mortality. Measles vaccination through routine immunization (RI) programs in high-burden settings remains a chall…
Estimation of Health and Demographic Indicators with Incomplete Geographic Information
Katie Wilson, Jon Wakefield
In low and middle income countries, household surveys are a valuable source of information for a range of health and demographic indicators. Increasingly, subnational estimates are…
Bayesian Multiresolution Modeling Of Georeferenced Data
John Paige, Geir-Arne Fuglstad, Andrea Riebler +1
Current implementations of multiresolution methods are limited in terms of possible types of responses and approaches to inference. We provide a multiresolution approach for spatia…
Harmonizing Child Mortality Data at Disparate Geographic Levels
Neal Marquez, Jon Wakefield
There is an increasing focus on reducing inequalities in health outcomes in developing countries. Subnational variation is of particular interest, with geographic data used to unde…
A linear noise approximation for stochastic epidemic models fit to partially observed incidence counts
Jonathan Fintzi, Jon Wakefield, Vladimir N. Minin
Stochastic epidemic models (SEMs) fit to incidence data are critical to elucidating outbreak dynamics, shaping response strategies, and preparing for future epidemics. SEMs typical…
Design- and Model-Based Approaches to Small-Area Estimation in a Low and Middle Income Country Context: Comparisons and Recommendations
John Paige, Geir-Arne Fuglstad, Andrea Riebler +1
The need for rigorous and timely health and demographic summaries has provided the impetus for an explosion in geographic studies, with a common approach being the production of pi…
Estimating Under Five Mortality in Space and Time in a Developing World Context
Jon Wakefield, Geir-Arne Fuglstad, Andrea Riebler +3
Accurate estimates of the under-5 mortality rate (U5MR) in a developing world context are a key barometer of the health of a nation. This paper describes new models to analyze surv…
Pointless Continuous Spatial Surface Reconstruction
Katherine Wilson, Jon Wakefield
The analysis of area-level aggregated summary data is common in many disciplines including epidemiology and the social sciences. Typically, Markov random field spatial models have…
Spatial Modeling, with Application to Complex Survey Data: Discussion of "Model-based Geostatistics for Prevalence Mapping in Low-Resource Settings", by Diggle and Giorgi
Jon Wakefield, Daniel Simpson, Jessica Godwin
Prevalence mapping in low resource settings is an increasingly important endeavor to guide policy making and to spatially and temporally characterize the burden of disease. We will…
Restricted Covariance Priors with Applications in Spatial Statistics
Theresa R. Smith, Jon Wakefield, Adrian Dobra
We present a Bayesian model for area-level count data that uses Gaussian random effects with a novel type of G-Wishart prior on the inverse variance--covariance matrix. Specificall…