Birth Patterns in the Aftermath of the 1918 Influenza Pandemic in India: The Case of Madras City.

This paper examines the timing of one-time fluctuations in births subsequent to the 1918 influenza pandemic in Madras (now Chennai), India. After seasonally decomposing key demographic aggregates, we identified abrupt one-time fluctuations in excess births, deaths, and infant deaths. We found a contemporaneous spike in excess deaths and infant deaths and a 40-week lag between the spike in deaths and a subsequent deficit in births. The results suggest that India experienced the same kind of short-term postpandemic "baby bust" that was observed in the United States and other countries. Identifying the mechanisms underlying this widespread phenomenon remains an open question and an important topic for future research.

Deviation in the Age Structure of Mortality as an Indicator of COVID-19 Pandemic Severity.

Objectives. To test whether distortions in the age distribution of deaths can track pandemic activity. Methods. We compared weekly distributions of all-cause deaths by age during the COVID-19 pandemic in the United States from March to December 2020 with corresponding prepandemic weekly baseline distributions derived from data for 2015 to 2019. We measured distortions via Kolmogorov-Smirnov (K-S) and χ2 goodness-of-fit statistics as well as deaths among individuals aged 65 years or older as a percentage of total deaths (PERC65+). We computed bivariate correlations between these measures and the number of recorded COVID-19 deaths for the corresponding weeks. Results. Elevated COVID-19-associated fatalities were accompanied by greater distortions in the age structure of mortality. Distortions in the age distribution of weekly US COVID-19 deaths in 2020 relative to earlier years were highly correlated with COVID fatalities (K-S: r = 0.71, P < .001; χ2: r = 0.90, P < .001; PERC65+: r = 0.85, P < .001). Conclusions. A population-representative sample of age-at-death data can serve as a useful means of pandemic activity surveillance when precise cause-of-death data are incomplete, inaccurate, or unavailable, as is often the case in low-resource environments. (Am J Public Health. 2022;112(1):165-168. https://doi.org/10.2105/AJPH.2021.306567).

Tracking Pandemic Severity Using Data on the Age Structure of Mortality: Lessons From the 1918 Influenza Pandemic in Michigan.

Objectives. To test whether distortions in the age structure of mortality during the 1918 influenza pandemic in Michigan tracked the severity of the pandemic. Methods. We calculated monthly excess deaths during the period of 1918 to 1920 by using monthly data on all-cause deaths for the period of 1912 to 1920 in Michigan. Next, we measured distortions in the age distribution of deaths by using the Kuiper goodness-of-fit test statistic comparing the monthly distribution of deaths by age in 1918 to 1920 with the baseline distribution for the corresponding month for 1912 to 1917. Results. Monthly distortions in the age distribution of deaths were correlated with excess deaths for the period of 1918 to 1920 in Michigan (r = 0.83; P < .001). Conclusions. Distortions in the age distribution of deaths tracked variations in the severity of the 1918 influenza pandemic. Public Health Implications. It may be possible to track the severity of pandemic activity with age-at-death data by identifying distortions in the age distribution of deaths. Public health authorities should explore the application of this approach to tracking the COVID-19 pandemic in the absence of complete data coverage or accurate cause-of-death data.

Pandemic Reemergence and Four Waves of Excess Mortality Coinciding With the 1918 Influenza Pandemic in Michigan: Insights for COVID-19.

The global influenza pandemic that emerged in 1918 has become the event of reference for a broad spectrum of policymakers seeking to learn from the past. This article sheds light on multiple waves of excess mortality that occurred in the US state of Michigan at the time with insights into how epidemics might evolve and propagate across space and time. We analyzed original monthly data on all-cause deaths by county for the 83 counties of Michigan and interpreted the results in the context of what is known about the pandemic. Counties in Michigan experienced up to four waves of excess mortality over a span of two years, including a severe one in early 1920. Some counties experienced two waves in late 1918 while others had only one. The 1920 wave propagated across the state in a different manner than the fall and winter 1918 waves. The twin waves in late 1918 were likely related to the timing of the statewide imposition of a three-week social distancing order. Michigan's experience holds sobering lessons for those who wish to understand how immunologically naïve populations encounter novel viral pathogens.

Spatiotemporal Patterns and Diffusion of the 1918 Influenza Pandemic in British India.

The factors that drive spatial heterogeneity and diffusion of pandemic influenza remain debated. We characterized the spatiotemporal mortality patterns of the 1918 influenza pandemic in British India and studied the role of demographic factors, environmental variables, and mobility processes on the observed patterns of spread. Fever-related and all-cause excess mortality data across 206 districts in India from January 1916 to December 1920 were analyzed while controlling for variation in seasonality particular to India. Aspects of the 1918 autumn wave in India matched signature features of influenza pandemics, with high disease burden among young adults, (moderate) spatial heterogeneity in burden, and highly synchronized outbreaks across the country deviating from annual seasonality. Importantly, we found population density and rainfall explained the spatial variation in excess mortality, and long-distance travel via railroad was predictive of the observed spatial diffusion of disease. A spatiotemporal analysis of mortality patterns during the 1918 influenza pandemic in India was integrated in this study with data on underlying factors and processes to reveal transmission mechanisms in a large, intensely connected setting with significant climatic variability. The characterization of such heterogeneity during historical pandemics is crucial to prepare for future pandemics.

Short-Term Birth Sequelae of the 1918-1920 Influenza Pandemic in the United States: State-Level Analysis.

This paper examines short-term birth sequelae of the influenza pandemic of 1918-1920 in the United States using monthly data on births and all-cause deaths for 19 US states in conjunction with data on maternal deaths, stillbirths, and premature births. The data on births and all-cause deaths are adjusted for seasonal and trend effects, and the residual components of the 2 time series coinciding with the timing of peak influenza mortality are examined for these sequelae. Notable findings include: 1) a drop in births in the 3 months following peak mortality; 2) a reversion in births to normal levels occurring 5-7 months after peak mortality; and 3) a steep drop in births occurring 9-10 months after peak mortality. Interpreted in the context of parallel data showing elevated premature births, stillbirths, and maternal mortality during times of peak influenza mortality, these findings suggest that the main impacts of the 1918-1920 influenza on reproduction occurred through: 1) impaired conceptions, possibly due to effects on fertility and behavioral changes; 2) an increase in the preterm delivery rate during the peak of the pandemic; and 3) elevated maternal and fetal mortality, resulting in late-term losses in pregnancy.

Exposure to workplace smoking bans and continuity of daily smoking patterns on workdays and weekends.

INTRODUCTION: Individuals may compensate for workplace smoking bans by smoking more before or after work, or escaping bans to smoke, but no studies have conducted a detailed, quantitative analysis of such compensatory behaviors using real-time data. METHODS: 124 daily smokers documented smoking occasions over 3weeks using ecological momentary assessment (EMA), and provided information on real-world exposure to smoking restrictions and type of workplace smoking policy (full, partial, or no bans). Mixed modeling and generalized estimating equations assessed effects of time of day, weekday (vs weekend), and workplace policy on mean cigarettes per hour (CPH) and reports of changing location to smoke. RESULTS: Individuals were most likely to change locations to smoke during business hours, regardless of work policy, and frequency of EMA reports of restrictions at work was associated with increased likelihood of changing locations to smoke (OR=1.11, 95% CI 1.05-1.16; p<0.0001). Workplace smoking policy, time block, and weekday/weekend interacted to predict CPH (p<0.01), such that individuals with partial work bans -but not those with full bans - smoked more at night (9pm - bed) on weekdays compared to weekends. CONCLUSIONS: There was little evidence that full bans interfered with subjects' smoking during business hours across weekdays and weekends. Smokers largely compensate for exposure to workplace smoking bans by escaping restrictions during business hours. Better understanding the effects of smoking bans on smoking behavior may help to improve their effectiveness and yield insights into determinants of smoking in more restrictive environments.

Diverse perspectives are welcome: Reply to Martin (2017).

Martin's (2017) comment on Chandra and Leong (2016) highlighted (a) lack of definitional clarity of the concept of adaptability, (b) conceptual generality of the model, and (c) incomplete citations of the literature on adaptability. In this reply, the authors contend that lack of definitional clarity of adaptability is symptomatic of the multitude of definitions of adaptability by psychologists of diverse persuasions. Conceptual generality of the diversified portfolio model (DPM) stems from the choice of a broad definition of adaptability, which extends beyond the narrower definitions provided by scholars including Martin, as well as the capability of the model to mesh with this broad definition. Incomplete citations result from the choice to use a few well-known conceptualizations of adaptability for the purpose of exposition from among the thousands of extant studies on adaptability. The central point of Chandra and Leong (2016) is that diversification is an important antecedent and determinant of adaptability and imparts greater adaptability however defined or measured. (PsycINFO Database Record

A diversified portfolio model of adaptability.

A new model of adaptability, the diversified portfolio model (DPM) of adaptability, is introduced. In the 1950s, Markowitz developed the financial portfolio model by demonstrating that investors could optimize the ratio of risk and return on their portfolios through risk diversification. The DPM integrates attractive features of a variety of models of adaptability, including Linville's self-complexity model, the risk and resilience model, and Bandura's social cognitive theory. The DPM draws on the concept of portfolio diversification, positing that diversified investment in multiple life experiences, life roles, and relationships promotes positive adaptation to life's challenges. The DPM provides a new integrative model of adaptability across the biopsychosocial levels of functioning. More importantly, the DPM addresses a gap in the literature by illuminating the antecedents of adaptive processes studied in a broad array of psychological models. The DPM is described in relation to the biopsychosocial model and propositions are offered regarding its utility in increasing adaptiveness. Recommendations for future research are also offered. (PsycINFO Database Record

Prehospital care training in a rapidly developing economy: a multi-institutional study.

BACKGROUND: The trauma pandemic is one of the leading causes of death worldwide but especially in rapidly developing economies. Perhaps, a common cause of trauma-related mortality in these settings comes from the rapid expansion of motor vehicle ownership without the corresponding expansion of national prehospital training in developed countries. The resulting road traffic injuries often never make it to the hospital in time for effective treatment, resulting in preventable disability and death. The current article examines the development of a medical first responder training program that has the potential to reduce this unnecessary morbidity and mortality. METHODS: An intensive training workshop has been differentiated into two progressive tiers: acute trauma training (ATT) and broad trauma training (BTT) protocols. These four-hour and two-day protocols, respectively, allow for the mass education of laypersons-such as police officials, fire brigade, and taxi and/or ambulance drivers-who are most likely to interact first with prehospital victims. Over 750 ATT participants and 168 BTT participants were trained across three Indian educational institutions at Jodhpur and Jaipur. Trainees were given didactic and hands-on education in a series of critical trauma topics, in addition to pretraining and post-training self-assessments to rate clinical confidence across curricular topics. Two-sample t-test statistical analyses were performed to compare pretraining and post-training confidence levels. RESULTS: Program development resulted in recruitment of a variety of career backgrounds for enrollment in both our ATT and BTT workshops. The workshops were run by local physicians from a wide spectrum of medical specialties and previously ATT-trained police officials. Statistically significant improvements in clinical confidence across all curricular topics for ATT and BTT protocols were identified (P < 0.0001). In addition, improvement in confidence after BTT training was similar in Jodhpur compared with Jaipur. CONCLUSIONS: These results suggest a promising level of reliability and reproducibility across different geographic areas in rapidly developing settings. Program expansion can offer an exponential growth in the training rate of medical first responders, which can help curb the trauma-related mortality in rapidly developing economies. Future directions will include clinical competency assessments and further progressive differentiation into higher tiers of trauma expertise.

Fertility Decline and the 1918 Influenza Pandemic in Taiwan.

The impact of the 1918 influenza pandemic on human fertility has been subject to significant scholarly debate. The current study characterizes the inter-temporal association between excess deaths during the pandemic and the subsequent birth deficit by identifying the length of time between these two phenomena using cross-correlations of monthly death and birth data from Taiwan from 1906 to 1943. The analysis demonstrates a strong and negative correlation between deaths (d) at time t and births (b) at time t + 9 (r(db)(9) = -0.68, p < .0001). In other words, a significant drop in births was observed nine months after pandemic mortality peaked. The findings suggest that the 1918 influenza pandemic impacted subsequent births primarily through the mechanism of reduced conceptions and embryonic loss during the first month of pregnancy rather than through late-first-trimester embryonic loss.

Do consumers substitute opium for hashish? An economic analysis of simultaneous cannabinoid and opiate consumption in a legal regime.

AIM: To analyze interrelationships in the consumption of opiates and cannabinoids in a legal regime and, specifically, whether consumers of opiates and cannabinoids treat them as substitutes for each other. METHOD: Econometric dynamic panel data models for opium consumption are estimated using the generalized method of moments (GMM). A unique dataset containing information about opiate (opium) consumption from the Punjab province of British India for the years 1907-1918 is analyzed (n=252) as a function of its own price, the prices of two forms of cannabis (the leaf (bhang), and the resin (charas, or hashish)), and wage income. Cross-price elasticities are examined to reveal substitution or complementarity between opium and cannabis. RESULTS: Opium is a substitute for charas (or hashish), with a cross price elasticity (߈3) of 0.14 (p<0.05), but not for bhang (cannabis leaves; cross price elasticity=0.00, p>0.10). Opium consumption (߈1=0.47 to 0.49, p<0.01) shows properties of habit persistence consistent with addiction. The consumption of opium is slightly responsive (inelastic) to changes in its own price (߈2=-0.34 to -0.35, p<0.05 to 0.01) and consumer wages (߈1=0.15, p<0.05). CONCLUSION: Opium and hashish, a form of cannabis, are substitutes. In addition, opium consumption displays properties of habit persistence and slight price and wage income responsiveness (inelasticity) consistent with an addictive substance.

Transnational cocaine and heroin flow networks in western Europe: A comparison.

BACKGROUND: A comparison of the properties of drug flow networks for cocaine and heroin in a group of 17 western European countries is provided with the aim of understanding the implications of their similarities and differences for drug policy. METHODS: Drug flow data for the cocaine and heroin networks were analyzed using the UCINET software package. Country-level characteristics including hub and authority scores, core and periphery membership, and centrality, and network-level characteristics including network density, the results of a triad census, and the final fitness of the core-periphery structure of the network, were computed and compared between the two networks. RESULTS: The cocaine network contains fewer path redundancies and a smaller, more tightly knit core than the heroin network. Authorities, hubs and countries central to the cocaine network tend to have higher hub, authority, and centrality scores than those in the heroin network. The core-periphery and hub-authority structures of the cocaine and heroin networks reflect the west-to-east and east-to-west patterns of flow of cocaine and heroin respectively across Europe. The key nodes in the cocaine and heroin networks are generally distinct from one another. CONCLUSION: The analysis of drug flow networks can reveal important structural features of trafficking networks that can be useful for the allocation of scarce drug control resources. The identification of authorities, hubs, network cores, and network-central nodes can suggest foci for the allocation of these resources. In the case of Europe, while some countries are important to both cocaine and heroin networks, different sets of countries occupy positions of prominence in the two networks. The distinct nature of the cocaine and heroin networks also suggests that a one-size-fits-all supply- and interdiction-focused policy may not work as well as an approach that takes into account the particular characteristics of each network.

The evolution of pandemic influenza: evidence from India, 1918-19.

BACKGROUND: The 1918-19 'Spanish' Influenza was the most devastating pandemic in recent history, with estimates of global mortality ranging from 20 to 50 million. The focal point of the pandemic was India, with an estimated death toll of between 10 and 20 million. We will characterize the pattern of spread, mortality, and evolution of the 1918 influenza across India using spatial or temporal data. METHODS: This study estimates weekly deaths in 213 districts from nine provinces in India. We compute statistical measures of the severity, speed, and duration of the virulent autumn wave of the disease as it evolved and diffused throughout India. These estimates create a clear picture of the spread of the pandemic across India. RESULTS: Analysis of the timing and mortality patterns of the disease reveals a striking pattern of speed deceleration, reduction in peak-week mortality, a prolonging of the epidemic wave, and a decrease in overall virulence of the pandemic over time. CONCLUSIONS: The findings are consistent with a variety of possible causes, including the changing nature of the dominant viral strain and the timing and severity of the monsoon. The results significantly advance our knowledge of this devastating pandemic at its global focal point.

The influenza pandemic of 1918-1919 in Sri Lanka: its demographic cost, timing, and propagation.

BACKGROUND: As an island and a former British colony, Sri Lanka is a case of special interest for the study of 1918-1919 influenza pandemic because of its potential for isolation from as well as integration into the world epidemiologic system. OBJECTIVES: To estimate population loss attributable to the influenza pandemic and weekly district-level excess mortality from the pandemic to analyze its spread across the island. METHODS: To measure population loss, we estimated a population growth model using a panel of 100 district-level observations on population for five consecutive censuses from 1891 to 1931, allowing for a one-time drop in population in 1918-1919. To estimate weekly excess mortality from the pandemic, we estimated a seasonally adjusted weekly time series of district-specific mortality estimates from vital registration records, ranked them, and plotted the ranks on weekly maps to create a picture of the geographic pattern of propagation across Sri Lanka. RESULTS: Total loss of population from the influenza pandemic was 307 000 or approximately 6·7% of the population. The pandemic peaked in two discrete (northern and southern) regions in early October of 1918 and in a third (central) region in early March 1919. CONCLUSIONS: The population loss estimate is significantly higher than earlier estimates of mortality from the pandemic in Sri Lanka, suggesting underreporting of influenza-attributable deaths and a role for influenza-related fertility declines. The spatial pattern of peak mortality indicates the presence of two distinct entry points and three distinct epidemiologic regions, defined by population density and ethnicity, in colonial Sri Lanka.

Deaths associated with influenza pandemic of 1918-19, Japan.

Current estimates of deaths from the influenza pandemic of 1918-19 in Japan are based on vital records and range from 257,000 to 481,000. The resulting crude death rate range of 0.47%-0.88% is considerably lower than parallel and conservative worldwide estimates of 1.66%-2.77%. Because the accuracy of vital registration records for early 20th century Asia is questionable, to calculate the percentage of the population who died from the pandemic, we used alternative prefecture-level population count data for Japan in combination with estimation methods for panel data that were not available to earlier demographers. Our population loss estimates of 1.97-2.02 million are appreciably higher than the standing estimates, and they yield a crude rate of population loss of 3.62%-3.71%. This rate resolves a major puzzle about the pandemic by indicating that the experience of Japan was similar to that of other parts of Asia.

A geographic analysis of population density thresholds in the influenza pandemic of 1918-19.

BACKGROUND: Geographic variables play an important role in the study of epidemics. The role of one such variable, population density, in the spread of influenza is controversial. Prior studies have tested for such a role using arbitrary thresholds for population density above or below which places are hypothesized to have higher or lower mortality. The results of such studies are mixed. The objective of this study is to estimate, rather than assume, a threshold level of population density that separates low-density regions from high-density regions on the basis of population loss during an influenza pandemic. We study the case of the influenza pandemic of 1918-19 in India, where over 15 million people died in the short span of less than one year. METHODS: Using data from six censuses for 199 districts of India (n=1194), the country with the largest number of deaths from the influenza of 1918-19, we use a sample-splitting method embedded within a population growth model that explicitly quantifies population loss from the pandemic to estimate a threshold level of population density that separates low-density districts from high-density districts. RESULTS: The results demonstrate a threshold level of population density of 175 people per square mile. A concurrent finding is that districts on the low side of the threshold experienced rates of population loss (3.72%) that were lower than districts on the high side of the threshold (4.69%). CONCLUSIONS: This paper introduces a useful analytic tool to the health geographic literature. It illustrates an application of the tool to demonstrate that it can be useful for pandemic awareness and preparedness efforts. Specifically, it estimates a level of population density above which policies to socially distance, redistribute or quarantine populations are likely to be more effective than they are for areas with population densities that lie below the threshold.

Mortality from the influenza pandemic of 1918-19 in Indonesia.

The influenza pandemic of 1918-19 was the single most lethal short-term epidemic of the twentieth century. For Indonesia, the world's fourth most populous country, the most widely used estimate of mortality from that pandemic is 1.5 million. We estimated mortality from the influenza pandemic in Java and Madura, home to the majority of Indonesia's population, using panel data methods and data from multiple quinquennial population counts and two decennial censuses. The new estimates suggest that, for Java alone, population loss was in the range of 4.26-4.37 million, or more than twice the established estimate for mortality for all of Indonesia. We conclude that the standing estimates of mortality from influenza in Java and Indonesia need to be revised upward significantly. We also present new findings on geographic patterns of population loss across Java, and pre-pandemic and post-pandemic population growth rates.