71 citations · 152 across the 35 of their papers we have counts for
13 papers · 1 filter
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…
Estimating the Stillbirth Rate for 195 Countries Using A Bayesian Sparse Regression Model with Temporal Smoothing
Zhengfan Wang, Miranda J. Fix, Lucia Hug +5
Estimation of stillbirth rates globally is complicated because of the paucity of reliable data from countries where most stillbirths occur. We compiled data and developed a Bayesia…
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…
Space-time smoothing models for sub-national measles routine immunization coverage estimation with complex survey data
Tracy Qi Dong, Jon Wakefield
Despite substantial advances in global measles vaccination, measles disease burden remains high in many low- and middle-income countries. A key public health strategy for controlin…
Space-Time Smoothing of Survey Outcomes using the R Package SUMMER
Zehang Richard Li, Bryan D Martin, Tracy Qi Dong +5
The increasing availability of complex survey data, and the continued need for estimates of demographic and health indicators at a fine spatial and temporal scale, which leads to i…
Small Area Estimation of Health Outcomes
Jon Wakefield, Taylor Okonek, Jon Pedersen
Small area estimation (SAE) entails estimating characteristics of interest for domains, often geographical areas, in which there may be few or no samples available. SAE has a long…
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…
Modeling and presentation of vaccination coverage estimates using data from household surveys
Tracy Qi Dong, Jon Wakefield
It is becoming increasingly popular to produce high-resolution maps of vaccination coverage by fitting Bayesian geostatistical models to data from household surveys. Often, the sur…
A flexible Bayesian framework to estimate age- and cause-specific child mortality over time from sample registration data
Austin E Schumacher, Tyler H McCormick, Jon Wakefield +5
In order to implement disease-specific interventions in young age groups, policy makers in low- and middle-income countries require timely and accurate estimates of age- and cause-…
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…