Jennifer Dowd
Jennifer Dowd
Deputy Director LCDS and Associate Professor of Demography and Population Health
Jenn Dowd is a quantitative social and health scientist with interdisciplinary training in demography, economics, epidemiology and infectious disease. Her research seeks to understand how social and biological processes interact over the life course and how social factors “get under the skin” to impact health. She has studied how socioeconomic status shapes immune function and risk of infections as well as links between infections and chronic diseases of aging. On-going projects include understanding the social determinants of the human microbiome and the causes of stalling life expectancy in the US and UK. She is currently researching social and demographic factors related to COVID-19, and is also part of an all-female team of PhD health scientists interpreting and curating COVID-19 science for a general audience at Dear Pandemic.
She is a highly cited scholar who has published over 90 articles in journals in interdisciplinary journals such as the Proceedings of National Academies of Sciences, Nature Human Behaviour, the American Journal of Epidemiology, and Social Science and Medicine. She has been Principal Investigator and Co-Investigator on multiple large grants from the U.S. National Institutes of Health on topics including the role of infections and immunity in health inequalities and social and population science approaches to the microbiome. She is currently an elected member of the Population Association of America (PAA) Board of Directors and on the Editorial Board of the flagship journal Demography.
Dr. Dowd received her Ph.D. from Princeton University in 2004 in Demography and Economics from the Office of Population Research. She did postdoctoral training in Epidemiology as a Robert Wood Johnson Health & Society Scholar in the Center for Social Epidemiology and Population Health at the University of Michigan. She has previously held positions in the Department of Global Health and Social Medicine, King's College London, and the CUNY School of Public Health/CUNY Institute for Demographic Research (CIDR), City University of New York.
Research Areas: Population Health, Biodemography, Social Determinants of Health
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Estimating the burden of COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: A population-level analysis
July 2020|Journal article<h4>Background</h4> Deaths directly linked to COVID-19 infection may be misclassified, and the pandemic may have indirectly affected other causes of death. To overcome these measurement challenges, we estimate the impact of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality from week 10, when the first COVID-19 death was registered, to week 47 ending November 20, 2020 in England and Wales through an analysis of excess mortality. <h4>Methods</h4> We estimated age and sex-specific excess mortality risk and deaths above a baseline adjusted for seasonality with a systematic comparison of four different models using data from the Office for National Statistics. We additionally provide estimates of life expectancy at birth and lifespan inequality defined as the standard deviation in age at death. <h4>Results</h4> There have been 57,419 (95% Prediction Interval: 54,197, 60,752) excess deaths in the first 47 weeks of 2020, 55% of which occurred in men. Excess deaths increased sharply with age and men experienced elevated risks of death in all age groups. Life expectancy at birth dropped 0.9 and 1.2 years for females and males relative to the 2019 levels, respectively. Lifespan inequality also fell over the same period by five months for both sexes. <h4>Conclusion</h4> Quantifying excess deaths and their impact on life expectancy at birth provides a more comprehensive picture of the burden of COVID-19 on mortality. Whether mortality will return to -or even fall below-the baseline level remains to be seen as the pandemic continues to unfold and diverse interventions are put in place. <h4>Summary boxes</h4> <h4>What is already known on this topic</h4> COVID-19 related deaths may be misclassified thereby inaccurately estimating the full impact of the pandemic on mortality. The pandemic may also have indirect effects on other causes due to changed behaviours, as well as the social and economic consequences resulting from its management. Excess mortality, the difference between observed deaths and what would have been expected in the absence of the pandemic, is a useful metric to quantify the overall impact of the pandemic on mortality and population health. Life expectancy at birth and lifespan inequality assess the cumulative impact of the pandemic on population health. <h4>What this study adds</h4> We examine death registration data from the Office for National Statistics from 2010 to week 47 (ending on November 20) in 2020 to quantify the impact of the COVID-19 pandemic on mortality in England and Wales thus far. We estimate excess mortality risk by age and sex, and quantify the impact of excess mortality risk on excess deaths, life expectancy and lifespan inequality. During weeks 10 through 47 of 2020, elevated mortality rates resulted in 57,419 additional deaths compared with baseline mortality. Life expectancy at birth for females and males over the 47 weeks of 2020 was 82.6 and 78.7 years, with 0.9 and 1.2 years of life lost relative to the year 2019. Lifespan inequality, a measure of the spread or variation in ages at death, declined due to the increase of mortality at older ages. -
Forecasting spatial, socioeconomic and demographic variation in COVID-19 health care demand in England and Wales.
June 2020|Journal article|BMC medicine<h4>Background</h4>COVID-19 poses one of the most profound public health crises for a hundred years. As of mid-May 2020, across the world, almost 300,000 deaths and over 4 million confirmed cases were registered. Reaching over 30,000 deaths by early May, the UK had the highest number of recorded deaths in Europe, second in the world only to the USA. Hospitalization and death from COVID-19 have been linked to demographic and socioeconomic variation. Since this varies strongly by location, there is an urgent need to analyse the mismatch between health care demand and supply at the local level. As lockdown measures ease, reinfection may vary by area, necessitating a real-time tool for local and regional authorities to anticipate demand.<h4>Methods</h4>Combining census estimates and hospital capacity data from ONS and NHS at the Administrative Region, Ceremonial County (CC), Clinical Commissioning Group (CCG) and Lower Layer Super Output Area (LSOA) level from England and Wales, we calculate the number of individuals at risk of COVID-19 hospitalization. Combining multiple sources, we produce geospatial risk maps on an online dashboard that dynamically illustrate how the pre-crisis health system capacity matches local variations in hospitalization risk related to age, social deprivation, population density and ethnicity, also adjusting for the overall infection rate and hospital capacity.<h4>Results</h4>By providing fine-grained estimates of expected hospitalization, we identify areas that face higher disproportionate health care burdens due to COVID-19, with respect to pre-crisis levels of hospital bed capacity. Including additional risks beyond age-composition of the area such as social deprivation, race/ethnic composition and population density offers a further nuanced identification of areas with disproportionate health care demands.<h4>Conclusions</h4>Areas face disproportionate risks for COVID-19 hospitalization pressures due to their socioeconomic differences and the demographic composition of their populations. Our flexible online dashboard allows policy-makers and health officials to monitor and evaluate potential health care demand at a granular level as the infection rate and hospital capacity changes throughout the course of this pandemic. This agile knowledge is invaluable to tackle the enormous logistical challenges to re-allocate resources and target susceptible areas for aggressive testing and tracing to mitigate transmission.Humans, Pneumonia, Viral, Coronavirus Infections, Hospitalization, Demography, Forecasting, Socioeconomic Factors, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Child, Child, Preschool, Infant, Infant, Newborn, Hospital Bed Capacity, Health Services Needs and Demand, Delivery of Health Care, Europe, England, Wales, Female, Male, Young Adult, Pandemics, Betacoronavirus, COVID-19, SARS-CoV-2 -
Early Signs of Gut Microbiome Aging: Biomarkers of Inflammation, Metabolism, and Macromolecular Damage in Young Adulthood.
June 2020|Journal article|The journals of gerontology. Series A, Biological sciences and medical sciencesEmerging links between gut microbiota and diseases of aging point to possible shared immune, metabolic, and cellular damage mechanisms, operating long before diseases manifest. We conducted 16S rRNA sequencing of fecal samples collected from a subsample (n = 668) of Add Health Wave V, a nationally representative longitudinal study of adults aged 32-42. An overlapping subsample (n = 345) included whole-blood RNA-seq. We examined associations between fecal taxonomic abundances and dried blood spot-based markers of lipid and glucose homeostasis and C-reactive protein (measured in Wave IV), as well as gene expression markers of inflammation, cellular damage, immune cell composition, and transcriptomic age (measured in Wave V), using Bayesian hierarchical models adjusted for potential confounders. We additionally estimated a co-abundance network between inflammation-related genes and bacterial taxa using penalized Gaussian graphical models. Strong and consistent microbiota associations emerged for HbA1c, glucose, C-reactive protein, and principal components of genes upregulated in inflammation, DNA repair, and reactive oxygen species, with Streptococcus infantis, Pseudomonas spp., and Peptoniphilus as major players for each. This pattern was largely echoed (though attenuated) for immunological cell composition gene sets, and only Serratia varied meaningfully by transcriptomic age. Network co-abundance indicated relationships between Prevotella sp., Bacteroides sp., and Ruminococcus sp. and gut immune/metabolic regulatory activity, and Ruminococcus sp, Dialister, and Butyrivibrio crossotus with balance between Th1 and Th2 inflammation. In conclusion, many common associations between microbiota and major physiologic aging mechanisms are evident in early-mid adulthood and suggest avenues for early detection and prevention of accelerated aging. -
Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world
June 2020|Journal article|Nature Human BehaviourFFR, stochastic infection curves, social networks, COVID-19, statistical relational events -
Demographic science aids in understanding the spread and fatality rates of COVID-19.
May 2020|Journal article|Proceedings of the National Academy of Sciences of the United States of AmericaGovernments around the world must rapidly mobilize and make difficult policy decisions to mitigate the coronavirus disease 2019 (COVID-19) pandemic. Because deaths have been concentrated at older ages, we highlight the important role of demography, particularly, how the age structure of a population may help explain differences in fatality rates across countries and how transmission unfolds. We examine the role of age structure in deaths thus far in Italy and South Korea and illustrate how the pandemic could unfold in populations with similar population sizes but different age structures, showing a dramatically higher burden of mortality in countries with older versus younger populations. This powerful interaction of demography and current age-specific mortality for COVID-19 suggests that social distancing and other policies to slow transmission should consider the age composition of local and national contexts as well as intergenerational interactions. We also call for countries to provide case and fatality data disaggregated by age and sex to improve real-time targeted forecasting of hospitalization and critical care needs.Humans, Pneumonia, Viral, Coronavirus Infections, Age Factors, Sex Factors, Adult, Aged, Aged, 80 and over, Middle Aged, Italy, Republic of Korea, Pandemics, Betacoronavirus, COVID-19, SARS-CoV-2 -
A systematic review of the impact of psychosocial factors on immunity: Implications for enhancing BCG response against tuberculosis.
April 2020|Journal article|SSM - population healthBackground:Tuberculosis (TB) remains an urgent global public health priority, causing 1.5 million deaths worldwide in 2018. There is evidence that psychosocial factors modulate immune function; however, how this may influence TB risk or BCG vaccine response, and whether this pathway can be modified through social protection, has not been investigated. This paper aims to: a) systematically review evidence of how psychosocial factors influence the expression of biomarkers of immunity, and b) apply this general evidence to propose plausible TB-specific pathways for future study. Methods:Papers reporting on the impact of psychosocial stressors on immune biomarkers in relation to infectious disease risk were identified through a search of the databases MEDLINE, PsycINFO, Global Health and PsycEXTRA alongside reference list and citation searching of key papers. Data extraction and critical appraisal were carried out using a standardised form. The findings were tabulated and synthesised narratively by infectious disease category, and used to propose plausible mechanisms for how psychosocial exposures might influence immune outcomes relevant to TB and BCG response. Results:27,026 citations were identified, of which 51 met the inclusion criteria. The literature provides evidence of a relationship between psychosocial factors and immune biomarkers. While the direction and strength of associations is heterogenous, some overarching patterns emerged: adverse psychosocial factors (e.g. stress) were generally associated with compromised vaccine response and higher antibody titres to herpesviruses, and vice versa for positive psychosocial factors (e.g. social support). Conclusions:The evidence identifies pathways linking psychosocial factors and immune response: co-viral infection and immune suppression, both of which are potentially relevant to TB and BCG response. However, the heterogeneity in the strength and nature of the impact of psychosocial factors on immune function, and lack of research on the implications of this relationship for TB, underscore the need for TB-specific research.
MSc/MPhil course in Advanced Quantitative Methods (Hilary Term)
Dr. Dowd is available to supervise graduate students, particularly those with interests in social determinants of health and biodemography.