About

Andrew Noymer, MSc, PhD, is an associate professor of Population Health & Disease Prevention at the UC Irvine Program in Public Health. He is an epidemiologist and population health scientist specializing in infectious disease mortality. Dr. Noymer has studied prior modern pandemics of influenza, including the 2009, 1968, 1957, and the most severe, 1918, from demographic, epidemiological, and social perspectives. He has foreshadowed the severe outcomes of the coronavirus pandemic and has been a prominent figure in public health awareness regarding COVID-19, being quoted in outlets such as the New York Times, Washington Post, and USA Today. Dr. Noymer holds a PhD from Berkeley, where he was an NIA and NICHD trainee in demography, an MSc from the London School of Hygiene & Tropical Medicine, and an AB from Harvard University. He is a member of the United Nations/World Health Organization Technical Advisory Group on COVID-19 mortality estimation.

Research topics

• Political Science
• Computer Science
• Medicine
• Immunology
• Geography
• Gerontology
• Biology
• Environmental health
• Internal medicine
• Demography

Selected publications

• Review: School Mask Mandates and Student SARS-CoV-2 Infections: Evidence from a Natural Experiment of Neighboring K-12 Districts in North Dakota, USA

  2025-01-31

  peer-review1st authorCorresponding
  PublisherDOI

• Indigenous peoples and pandemics

  Scandinavian Journal of Public Health · 2022 · 25 citations

  • Political Science
  • Geography
  • Political Science

  Keywords 1918 influenza pandemic, 2009 influenza pandemic, COVID-19, pandemic preparedness, mortality, Indigenous peoples, social inequalities, social determinants of health infectious diseases

  PublisherDOI

• Seasonality of human orthopoxvirus infections

  2022-09-29 · 1 citations

  preprintOpen accessSenior author

  Variola infections (smallpox) showed seasonality in temperate climates. This sharp seasonality (peaking in the Winter-Spring) may have important ramifications for control and elimination of human monkeypox (MPX) and should be considered in planning public health response.

  PublisherOA PDFDOI

• Population Health and COVID-19 in Canada: a Demographic Comparative Perspective

  Canadian Studies in Population · 2021-09-01 · 5 citations

  editorialOpen access

  Demographers have been at the forefront of academic research about the burden of new coronavirus disease . Since the early work of This is because the age gradient of COVID-19 mortality is at least as steep as that of all-cause mortality, causing a greater concentration of deaths in old age Sex differentials in COVID-19 mortality are also more pronounced than all-cause mortality: COVID-19 mortality rates of men aged 25-80 have been found to be greater than those of women (Geldseltzer et al.,

  PublisherOA PDFDOI

• Estimated seroprevalence of SARS-CoV-2 antibodies among adults in Orange County, California

  Scientific Reports · 2021 · 54 citations

  • Medicine
  • Demography
  • Environmental health

  Clinic-based estimates of SARS-CoV-2 may considerably underestimate the total number of infections. Access to testing in the US has been heterogeneous and symptoms vary widely in infected persons. Public health surveillance efforts and metrics are therefore hampered by underreporting. We set out to provide a minimally biased estimate of SARS-CoV-2 seroprevalence among adults for a large and diverse county (Orange County, CA, population 3.2 million). We implemented a surveillance study that minimizes response bias by recruiting adults to answer a survey without knowledge of later being offered SARS-CoV-2 test. Several methodologies were used to retrieve a population-representative sample. Participants (n = 2979) visited one of 11 drive-thru test sites from July 10th to August 16th, 2020 (or received an in-home visit) to provide a finger pin-prick sample. We applied a robust SARS-CoV-2 Antigen Microarray technology, which has superior measurement validity relative to FDA-approved tests. Participants include a broad age, gender, racial/ethnic, and income representation. Adjusted seroprevalence of SARS-CoV-2 infection was 11.5% (95% CI: 10.5-12.4%). Formal bias analyses produced similar results. Prevalence was elevated among Hispanics (vs. other non-Hispanic: prevalence ratio [PR] = 1.47, 95% CI 1.22-1.78) and household income < $50,000 (vs. > $100,000: PR = 1.42, 95% CI: 1.14 to 1.79). Results from a diverse population using a highly specific and sensitive microarray indicate a SARS-CoV-2 seroprevalence of ~ 12 percent. This population-based seroprevalence is seven-fold greater than that using official County statistics. In this region, SARS-CoV-2 also disproportionately affects Hispanic and low-income adults.

  PublisherOA PDFDOI

• Estimated Seroprevalence of SARS-CoV-2 Antibodies Among Adults in Orange County, California

  medRxiv · 2020-10-12 · 8 citations

  preprintOpen access

  ABSTRACT Background Clinic-based estimates of SARS-CoV-2 may considerably underestimate the total number of infections. Access to testing in the US has been heterogeneous and symptoms vary widely in infected persons. Public health surveillance efforts and metrics are therefore hampered by underreporting. We set out to provide a minimally biased estimate of SARS-CoV-2 seroprevalence among adults for a large and diverse county (Orange County, CA, population 3.2 million). Methods We implemented a surveillance study that minimizes response bias by recruiting adults to answer a survey without knowledge of later being offered a SARS-CoV-2 test. Several methodologies were used to retrieve a population-representative sample. Participants (n=2,979) visited one of 11 drive-thru test sites from July 10 th to August 16 th , 2020 (or received an in-home visit) to provide a finger pin-prick sample. We applied a robust SARS-CoV-2 Antigen Microarray technology, which has superior measurement validity relative to FDA-approved tests. Findings Participants include a broad age, gender, racial/ethnic, and income representation. Adjusted seroprevalence of SARS-CoV-2 infection was 11.5% (95% CI: 10.5% to 12.4%). Formal bias analyses produced similar results. Prevalence was elevated among Hispanics (vs. other non-Hispanic: prevalence ratio [PR]= 1.47, 95% CI: 1.22 to 1.78) and household income &lt;$50,000 (vs. &gt;$100,000: PR= 1.42, 95% CI: 1.14 to 1.79). Interpretation Results from a diverse population using a highly specific and sensitive microarray indicate a SARS-CoV-2 seroprevalence of ∼12 percent. This population-based seroprevalence is seven-fold greater than that using official County statistics. In this region, SARS-CoV-2 also disproportionately affects Hispanic and low-income adults. Funding Orange County Healthcare Agency

  PublisherOA PDFDOI

• Epidemics and Time

  Routledge eBooks · 2020 · 4 citations

  1st authorCorresponding
  • Computer Science
  • Computer Science

  In this chapter, the author advances the idea that diseases are interrelated and therefore that &quot;plagues&quot; cannot be understood in isolation. The author discusses the effects of a plague need to be judged not only by the characteristic mortality of the outbreak and the long-term trends of the disease in question but also by changes in all diseases in the wake of the plague. The 1918-1919 influenza pandemic, sometimes called the &quot;Spanish flu,&quot; was most deadly outbreak of any disease in the twentieth century. The entire influenza mortality curve in 1918 lies above the 100 per 100,000 line, reflecting the severity of the epidemic. Despite the magnitude of the 1918-1919 flu and its peculiar age-mortality profile, demographers have paid relatively little attention to it. Historical epidemiology is an endeavor that strives to be good historiography as well as good epidemiology.

  PublisherDOI

• Race and life expectancy in the United States in the Great Depression

  2019-08-28

  preprintOpen accessSenior authorCorresponding

  Prior work has highlighted increases in life expectancy in the United States during the Great Depression. This contradicts the tenet that life expectancy is positively correlated with human welfare, but it coheres with recent literature on mortality and recessions. We construct Lee-Carter interval estimates of life expectancy during the Great Depression, based on trends before 1929. In this analysis, all-race life expectancy did not grow unusually during the Great Depression. However, nonwhites did see greater-than-expected increases in life expectancy in 1930-33. We discuss potential explanations. We conclude by urging scholars of mortality during this time period to focus on race whenever the data permit it.

  PublisherDOI

• The geometry of mortality change: Convex hulls for demographic analysis

  Revue Quetelet + Quetelet journal/Revue Quetelet + Quetelet Journal · 2019-07-15 · 1 citations

  articleOpen access

  We introduce convex hulls as a data visualization and analytic tool for demography. Convex hulls are widely used in computer science, and have been applied in fields such as ecology, but are heretofore underutilized in population studies. We briefly discuss convex hulls, then we show how they may profitably be applied to demography. We do this through three examples, drawn from the relationship between child and adult mortality (5q0 and 45q15 in life table notation). The three examples are: (i) sex differences in mortality; (ii) period and cohort differences and (iii) outlier identification. Convex hulls can be useful in robust compilation of demographic databases. Moreover, the gap/lag framework for sex differences or period/cohort differences is more complex when mortality data are arrayed by two components as opposed to a unidimensional measure such as life expectancy. Our examples show how, in certain cases, convex hulls can identify patterns in demographic data more readily than other techniques. The potential applicability of convex hulls in population studies goes beyond mortality.

  PublisherOA PDFDOI

• Data and code for Genus paper

  Figshare · 2019-01-01

  datasetOpen access1st authorCorresponding

  All data and code for 2019 Genus paper (Bruckner, Ima, Nguyen, Noymer). All input data for the paper and all code for the Lee-Carter analysis, including "helper files" (sub-programs, etc.). See the file README for a catalog of what's what.<br>

  PublisherDOI

Frequent coauthors

• Tim A. Bruckner

  UC Irvine Health

  14 shared

• Ashley M. Ima

  ORCID

  10 shared

• Trang T. Nguyen

  University of California, Irvine

  9 shared

• Ann Nguyen

  University of South Florida

  4 shared

• Bruce Albala

  University of California, Irvine

  4 shared

• Michel Garenne

  Université Clermont Auvergne

  3 shared

• Daniel M. Parker

  University of California, Irvine

  2 shared

• Emily Drum

  University of California, Irvine

  2 shared

Education

• Ph.D., Epidemiology

  University of California, Los Angeles

  1995

• M.S., Epidemiology

  University of California, Los Angeles

  1991

• B.A., Biology

  University of California, Los Angeles

  1988

Awards & honors

• Academic Senate Mid-Career Faculty Award for Service (2021)