The 1918 influenza epidemic had a marked and fairly long-lasting effect on the sex differential in mortality in the United States. After 1918 women lost most of their mortality advantage over men and the female/male gap did not regain its pre-epidemic level until the 1930s. An analysis of causes of deaths shows a link with tuberculosis. We conjecture the existence of a selection effect, whereby many 1918 influenza deaths were among tuberculous persons, so that tuberculosis death rates dropped in later years, disproportionately among males. Age- and sex-specific data by cause of death corroborate this hypothesis. Copyright 2000 by The Population Council, Inc..

BackgroundVitamin D is an important micronutrient for health. Hypovitaminosis D is thought to play a role in the seasonality of a number of diseases and adverse health conditions. To refine hypotheses about the links between vitamin D and seasonal diseases, good estimates of the cyclicality of serum vitamin D are necessary.ObjectivesThe objective of this study is to describe quantitatively the cyclicality of 25-hydroxyvitamin D (25OHD) in the United States. We provide a statistical analysis with weekly time resolution, in comparison to the quarterly (winter/spring/summer/fall) estimates already in the literature.MethodsWe analyzed time series data on 25OHD, spanning 287 consecutive weeks. The pooled data set comes from 3.44 million serum samples from the United States. We statistically analyzed the proportion of sera that were vitamin D sufficient, defined as 25OHD ng/mL, as a function of date.ResultsIn the United States, serum 25OHD follows a lagged pattern relative to the astronomical seasons, peaking in late summer (August) and troughing in late winter (February). Airmass, which is a function of solar altitude, fits the 25OHD data very well when lagged by 8 weeks.ConclusionsSerum vitamin D levels can be modeled as a function of date, working through a double-log transformation of minimal solar airmass (easily calculated from solar altitude, retrievable from an online solar altitude/azimuth table).

The effect of the 1918 influenza pandemic on other diseases is a neglected topic in historical epidemiology. This paper takes up the hypothesis that the influenza pandemic affected the long-term decline of tuberculosis though selective mortality, such that many people with tuberculosis were killed in 1918, depressing subsequent tuberculosis mortality and transmission. Regularly-collected vital statistics data on mortality of influenza and tuberculosis in the US are presented and analyzed demographically. The available population-level data fail to contradict the selection hypothesis. More work is needed to understand fully the role of multiple morbidities in the 1918 influenza pandemic.

Using Cox regression, this paper shows a weak association between having tuberculosis and dying from influenza among Union Army veterans in late nineteenth-century America. It has been suggested elsewhere [Noymer, A. and M. Garenne (2000). The 1918 influenza epidemic’s effects on sex differentials in mortality in the United States. Population and Development Review 26(3), 565–581.] that the 1918 influenza pandemic accelerated the decline of tuberculosis, by killing many people with tuberculosis. The question remains whether individuals with tuberculosis were at greater risk of influenza death, or if the 1918/post-1918 phenomenon arose from the sheer number of deaths in the influenza pandemic. The present findings, from microdata, cautiously point toward an explanation of Noymer and Garenne’s selection effect in terms of age-overlap of the 1918 pandemic mortality and tuberculosis morbidity, a phenomenon I term “passive selection”. Another way to think of this is selection at the cohort, as opposed to individual, level.

Recent research suggests racial classification is responsive to social stereotypes, but how this affects racial classification in national vital statistics is unknown. This study examines whether cause of death influences racial classification on death certificates. We analyze the racial classifications from a nationally representative sample of death certificates and subsequent interviews with the decedents' next of kin and find notable discrepancies between the two racial classifications by cause of death. Cirrhosis decedents are more likely to be recorded as American Indian on their death certificates, and homicide victims are more likely to be recorded as Black; these results remain net of controls for followback survey racial classification, indicating that the relationship we reveal is not simply a restatement of the fact that these causes of death are more prevalent among certain groups. Our findings suggest that seemingly non-racial characteristics, such as cause of death, affect how people are racially perceived by others and thus shape U.S. official statistics.

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.

BackgroundIn April 2009, the most recent pandemic of influenza A began. We present the first estimates of pandemic mortality based on the newly-released final data on deaths in 2009 and 2010 in the United States.MethodsWe obtained data on influenza and pneumonia deaths from the National Center for Health Statistics (NCHS). Age- and sex-specific death rates, and age-standardized death rates, were calculated. Using negative binomial Serfling-type methods, excess mortality was calculated separately by sex and age groups.ResultsIn many age groups, observed pneumonia and influenza cause-specific mortality rates in October and November 2009 broke month-specific records since 1959 when the current series of detailed US mortality data began. Compared to the typical pattern of seasonal flu deaths, the 2009 pandemic age-specific mortality, as well as influenza-attributable (excess) mortality, skewed much younger. We estimate 2,634 excess pneumonia and influenza deaths in 2009–10; the excess death rate in 2009 was 0.79 per 100,000.ConclusionsPandemic influenza mortality skews younger than seasonal influenza. This can be explained by a protective effect due to antigenic cycling. When older cohorts have been previously exposed to a similar antigen, immune memory results in lower death rates at older ages. Age-targeted vaccination of younger people should be considered in future pandemics.

This paper describes two related epidemic models of rumor transmission in an age-structured population. Rumors share with communicable disease certain basic aspects, which means that formal models of epidemics may be applied to the transmission of rumors. The results show that rumors may become entrenched very quickly and persist for a long time, even when skeptics are modeled to take an active role in trying to convince others that the rumor is false. This is a macrophenomeon, because individuals eventually cease to believe the rumor, but are replaced by new recruits. This replacement of former believers by new ones is an aspect of all the models, but the approach to stability is quicker, and involves smaller chance of extinction, in the model where skeptics actively try to counter the rumor, as opposed to the model where interest is naturally lost by believers. Skeptics hurt their own cause. The result shows that including age, or a variable for which age is a proxy (e.g. experience), can improve model fidelity and yield important insights.