About

Jon Wakefield is a professor whose research focuses on statistical methods for public health, epidemiology, and complex survey data analysis. His work includes Bayesian nonparametric methods for complex datasets, spatial-temporal modeling for infectious disease incidence, small area estimation, and disease mapping. Wakefield has supervised numerous graduate students and postdoctoral researchers, contributing to the development of statistical techniques applicable to low- and middle-income countries, health indicators, and disease surveillance. His academic background includes collaborations with institutions such as the University of Washington, Columbia University, and the University of Auckland. Wakefield's research emphasizes the application of Bayesian spatial and temporal methods to public health data, with a particular interest in disease modeling, health metrics estimation, and statistical issues in ecological and survey studies. His contributions extend to methodological advancements in Bayesian modeling, spatial analysis, and the integration of diverse data sources for health research.

Research topics

• Geography
• Demography
• Environmental health
• Medicine

Selected publications

• The WHO estimates of excess mortality associated with the COVID-19 pandemic

  Nature · 2022 · 1029 citations

  Senior authorCorresponding
  • Geography
  • Demography
  • Medicine

  . Reported statistics on COVID-19 mortality are problematic for many countries owing to variations in testing access, differential diagnostic capacity and inconsistent certification of COVID-19 as cause of death. Beyond what is directly attributable to it, the pandemic has caused extensive collateral damage that has led to losses of lives and livelihoods. Here we report a comprehensive and consistent measurement of the impact of the COVID-19 pandemic by estimating excess deaths, by month, for 2020 and 2021. We predict the pandemic period all-cause deaths in locations lacking complete reported data using an overdispersed Poisson count framework that applies Bayesian inference techniques to quantify uncertainty. We estimate 14.83 million excess deaths globally, 2.74 times more deaths than the 5.42 million reported as due to COVID-19 for the period. There are wide variations in the excess death estimates across the six World Health Organization regions. We describe the data and methods used to generate these estimates and highlight the need for better reporting where gaps persist. We discuss various summary measures, and the hazards of ranking countries' epidemic responses.

  DOI

• Global, regional, and national estimates and trends in stillbirths from 2000 to 2019: a systematic assessment

  The Lancet · 2021 · 531 citations

  • Geography

  BACKGROUND: Stillbirths are a major public health issue and a sensitive marker of the quality of care around pregnancy and birth. The UN Global Strategy for Women's, Children's and Adolescents' Health (2016-30) and the Every Newborn Action Plan (led by UNICEF and WHO) call for an end to preventable stillbirths. A first step to prevent stillbirths is obtaining standardised measurement of stillbirth rates across countries. We estimated stillbirth rates and their trends for 195 countries from 2000 to 2019 and assessed progress over time. METHODS: For a systematic assessment, we created a dataset of 2833 country-year datapoints from 171 countries relevant to stillbirth rates, including data from registration and health information systems, household-based surveys, and population-based studies. After data quality assessment and exclusions, we used 1531 datapoints to estimate country-specific stillbirth rates for 195 countries from 2000 to 2019 using a Bayesian hierarchical temporal sparse regression model, according to a definition of stillbirth of at least 28 weeks' gestational age. Our model combined covariates with a temporal smoothing process such that estimates were informed by data for country-periods with high quality data, while being based on covariates for country-periods with little or no data on stillbirth rates. Bias and additional uncertainty associated with observations based on alternative stillbirth definitions and source types, and observations that were subject to non-sampling errors, were included in the model. We compared the estimated stillbirth rates and trends to previously reported mortality estimates in children younger than 5 years. FINDINGS: Globally in 2019, an estimated 2·0 million babies (90% uncertainty interval [UI] 1·9-2·2) were stillborn at 28 weeks or more of gestation, with a global stillbirth rate of 13·9 stillbirths (90% UI 13·5-15·4) per 1000 total births. Stillbirth rates in 2019 varied widely across regions, from 22·8 stillbirths (19·8-27·7) per 1000 total births in west and central Africa to 2·9 (2·7-3·0) in western Europe. After west and central Africa, eastern and southern Africa and south Asia had the second and third highest stillbirth rates in 2019. The global annual rate of reduction in stillbirth rate was estimated at 2·3% (90% UI 1·7-2·7) from 2000 to 2019, which was lower than the 2·9% (2·5-3·2) annual rate of reduction in neonatal mortality rate (for neonates aged <28 days) and the 4·3% (3·8-4·7) annual rate of reduction in mortality rate among children aged 1-59 months during the same period. Based on the lower bound of the 90% UIs, 114 countries had an estimated decrease in stillbirth rate since 2000, with four countries having a decrease of at least 50·0%, 28 having a decrease of 25·0-49·9%, 50 having a decrease of 10·0-24·9%, and 32 having a decrease of less than 10·0%. For the remaining 81 countries, we found no decrease in stillbirth rate since 2000. Of these countries, 34 were in sub-Saharan Africa, 16 were in east Asia and the Pacific, and 15 were in Latin America and the Caribbean. INTERPRETATION: Progress in reducing the rate of stillbirths has been slow compared with decreases in the mortality rate of children younger than 5 years. Accelerated improvements are most needed in the regions and countries with high stillbirth rates, particularly in sub-Saharan Africa. Future prevention of stillbirths needs increased efforts to raise public awareness, improve data collection, assess progress, and understand public health priorities locally, all of which require investment. FUNDING: Bill & Melinda Gates Foundation and the UK Foreign, Commonwealth and Development Office.

  DOI

Recent grants

• SPATIO-TEMPORAL EPIDEMIOLOGY: METHODS AND APPLICATIONS

  NIH · $1.4M · 2005–2019

• SPATIO-TEMPORAL EPIDEMIOLOGY: METHODS AND APPLICATIONS

  NIH · $226k · 2005–2018

Frequent coauthors

• Jon Pedersen

  Aker BP (Norway)

  54 shared

• Jennifer Zeitlin

  Université Paris Cité

  54 shared

• Lucia Hug

  United Nations Children's Fund

  54 shared

• Hannah Blencowe

  London School of Hygiene & Tropical Medicine

  54 shared

• Leontine Alkema

  54 shared

• Danzhen You

  54 shared

• K.S. Joseph

  53 shared

• Miranda J. Fix

  Weyerhaeuser (United States)

  53 shared

Labs

• Jon Wakefield LabPI

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