Understanding the behavior of populations of drug consumers has been and remains a topic of keen interest. Using a unique dataset on 25 districts from Bengal, India, from 1911 to 1925, we analyze whether populations of consumers treat alcohol, cannabis, and opium as economic substitutes or complements in a legal regime. Additionally, we examine responsiveness to prices and income. Our analysis has three main findings. First, we find evidence of substitution between alcohol and cannabis bud. Second, cannabis leaf is a complement for alcohol but a substitute for cannabis bud. Third, we find negative income elasticity for alcohol, cannabis bud, and opium consumption. These findings on the link between consumption patterns and economic factors can guide harm reduction strategies.

We propose a novel method to measure the spatial extent of cocaine flows in the US using data on the price and purity of cocaine observed in drug seizures or undercover drug purchases. We then compare the cocaine trafficking network extracted using this method to anecdotal knowledge about cocaine flows using network analytic methods. Based on the network analysis, the trafficking networks inferred from price and purity data appear to be more elaborate in their geographic extent than prior anecdotal evidence suggests. The analysis uncovers previously unrecognized flows, notably identifying multiple possible cocaine source points along the US-Canadian border, challenging the traditional and likely incomplete narrative focused on the southern border. This study demonstrates that variation in cocaine purity across space and over time can help detect unconventional patterns of cocaine flows, complementing the conventional understanding of the extent of cocaine flows.

This article applies analytical approaches to map illegal psychostimulant (cocaine and methamphetamine) trafficking networks in the US using purity-adjusted price data from the System to Retrieve Information from Drug Evidence. We use two assumptions to build the network: (i) the purity-adjusted price is lower at the origin than at the destination and (ii) price perturbations are transmitted from origin to destination. We then adopt a two-step analytical approach: we formulate the data aggregation problem as an optimization problem, then construct an inferred network of connected states and examine its properties.We find, first, that the inferred cocaine network created from the optimally aggregated dataset explains 46% of the anecdotal evidence, compared with 28.4% for an over-aggregated and 14.5% for an under-aggregated dataset. Second, our network reveals a number of phenomena, some aligning with what is known and some previously unobserved. To demonstrate the applicability of our method, we compare our cocaine data analysis results with parallel analysis of methamphetamine data. These results likewise align with prior knowledge, but also present new insights. Our findings show that an optimally aggregated dataset can provide a more accurate picture of an illicit drug network than can suboptimally aggregated data.

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.

Abstract: This paper sheds light on spatial determinants of violence in rural areas of Indonesia during the 1965–66 mass killings. To do so, it focuses on the regency of Gunungkidul through the lens of the census. The analysis of census information for the 144 desa and kelurahan (village and urban neighbourhoods) of Gunungkidul reveals that violence was higher near the more urban environs of Wonosari and the adjacent city of Yogyakarta, and in the central-eastern desa of the regency. We attribute these high levels of violence to the proximity of these desa to perpetrator strongholds in Wonosari and Yogyakarta and to their accessibility by road. We also attribute violence in eastern areas of the regency to pre-existing political tensions in this region. Conversely, we find patterns of population gains in the southwest, southeast, and northeast corners of the regency, suggesting that they were sites of refuge: all are remote and difficult to access by road. In the case of the northeast, this region also likely served as a refuge for people fleeing intense violence in neighbouring Klaten to the north. This paper demonstrates that even in areas of high communist party support such as Gunungkidul, the intensity of violence varied significantly due to a combination of factors both internal (political tension and local perpetrators) and external (the armed forces) to the region.

Abstract: The role of civilian allies of the Indonesian Army is an important theme in narratives of the anti-Communist killings of 1965-66 in Indonesia. There is an ongoing debate about the extent to which these organizations were involved in the killings. Spatial analysis can provide clues about the degree to which these organizations may have been involved in different locations. The aim of this paper is to use spatial analytics to answer two questions: first, is there evidence that politico-religious allies of the Indonesian Army in the province of East Java were involved in the killings across the province? And second, if there are indications of variation in the degree to which these two organizations were involved in different parts of the province, what do these variations tell us about the interplay between the military and these organizations in the killings? In order to answer these questions, we use kecamatan-level estimates of population loss associated with the violence of 1965-66 in conjunction with information on the locations of major army command centers and centers of politico-religious organization in East Java to test propositions about whether the degree of population loss is systematically associated with the locations of these centers. While the methods cannot prove involvement of specific individuals or organizations, the results are consistent with much of what is known about key players in the violence. They also identify hot spots for which there are indications of possible involvement by either the military or its civilian allies or both.

Electronic nicotine delivery systems (ENDS) are a potentially lower-risk tobacco product which could help smokers switch completely away from cigarettes. However, the lack of strong evidence to date of a measurable, population-level effect on reducing smoking has generated skepticism about ENDS’ potential benefits. This study examines whether increased US ENDS sales have been associated with reduced cigarette sales. Retail data on weekly per-capita cigarette and ENDS purchases in the USA during 2014–2019 were obtained from a national sample of brick-and-mortar retail outlets. Trends in cigarette sales were modeled before (2014–2016) ENDS had a substantial market share, and, after adjusting for macroeconomic factors, projected into the post-period (2017–2019). Actual cigarette sales were lower than projected sales (by up to 16% across the post-period), indicating a substantial “cigarette shortfall” in the post-period. To explore whether general (i.e., inclusive of potentially many mechanisms) substitution by ENDS can explain the cigarette shortfall, its association with per-capita ENDS volume sales was examined. Higher ENDS sales were significantly associated with a greater cigarette shortfall: for every additional per-capita ENDS unit, cigarette sales were 1.4 packs-per-capita lower than expected ( B = 1.4, p < .0001). Error correction models which account for spurious correlation yielded similar results. These findings support ENDS serving as a substitute for cigarettes (through potentially many mechanisms including cigarette price), causing cigarette consumption to decline. Since ENDS potentially pose lower risk than cigarettes, this general substitution effect suggests that risk-proportionate tobacco regulation could mitigate the tobacco-related health burden.

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).

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.

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.

The goal of this article is to demonstrate the value of a global perspective on pandemics for understanding how global pandemics caused by novel viruses can unfold. Using the example of the 1918 influenza pandemic, two factors that were central to the evolving pattern of global pandemic waves, connectivity and seasonality, are explored. Examples of the influences of these factors on pandemic waves in different locations are presented. Viewing the 1918 pandemic through the lens of compartmental models of infectious diseases, our analysis suggests that connectivity played a dominant role in the initial stages. With the passage of time and the progressive infection and consequent immunization of more and more people, however, the role of seasonality increased in importance, ultimately becoming the driving force behind the emergence of future waves of infection. Implications of these observations for pandemics caused by novel viruses such as the ongoing COVID-19 pandemic are discussed.

The mass killings of 1965-1966 in Indonesia marked a watershed in its history. The consensus estimate of lives lost is 500,000. In this paper, demographic and geographic methods are used to characterize the violence in Central Java, one of the worst-affected provinces. The findings provide a portrait of the violence and its dynamics. This portrait highlights the likely complicity of a diverse array of political opponents of the Indonesian Communist Party (PKI). The findings also provide evidence supporting Clifford Geertz's three-aliran (cultural "stream") model of Javanese society, with the complex interplay of the three aliran and the Indonesian Army in the political realm producing the violent outcomes of 1965-1966. In this manner, this study builds on prior work by Hefner, Jay, Lyon, Mortimer, and Ricklefs on the cultural and social underpinnings of the violence. It also builds on more recent work on the neighboring province of East Java in which the role of two of the three alirans was found to be a significant factor, underlining the importance of the intersection of culture, geography, and politics in understanding this violent episode in Indonesian history.

Glimpses of Indonesia’s 1965 Massacre through the Lens of the Census: The Role of Trucks and Roads in “Crushing” the PKI in East Java Siddharth Chandra (bio) One of the most iconic images associated with the mass killings of 1965–66 in Indonesia features an open truck, its cargo bed filled with seated young men, and armed soldiers overlooking them (see photo, next page). The expressions on the faces of the captives are variously worried, resigned, or faraway—suggesting the different ways in which they are coping with the knowledge of their impending fate. While we will likely never know what became of many of these individuals, the photograph’s original caption tells us that these young people are members of a youth wing of Indonesia’s Communist Party (Partai Komunis Indonesia, PKI) in Jakarta, that the month is October 1965, and that they are being taken to prison. [End Page 1] Click for larger view View full resolution Prisoners (suspected of being members of a PKI youth group) on a truck destined for a Jakarta prison under the watchful eyes of Indonesian soldiers, October 1965. Source: Associated Press file photo, used with permission.1 The use of trucks as illustrated by the photograph is telling. The scale of the killings, estimated at 500,000 in the short span of less than a year, would not have been possible without the mobilization of considerable infrastructure to perpetrate what the Indonesian army and government described variously as the crushing (penumpasan) or destruction (penghancuran) of the PKI.2 In his comprehensive study of the violence, Geoffrey Robinson emphasizes the role of “trucks and other vehicles [that] the army provided for the transport of soldiers, vigilante killers, and their victims.” 3 Citing accounts from Aceh to Flores, he demonstrates that the use of trucks constituted one of the many ways in which the Indonesian army played an instrumental role in the killings: when not directly perpetrating them, by orchestrating them with the provision of infrastructure, training, and weapons.4 [End Page 2] Transportation infrastructure has been implicated in numerous accounts of mass violence and killing. Prominent examples include the role of Nazi Germany’s railway system in the Holocaust and that of the People’s Republic of China in enabling the Chinese Communist Party’s oppressive “grain drain” that contributed to the Great Chinese Famine of 1959–61, resulting in tens of millions of deaths. 5 Details of the Indonesian killings remain scarce in large part due to the vigorous censorship that the Suharto regime imposed on the subject in the three succeeding decades. As a result, knowledge of the role played by transportation infrastructure in the violence is, unfortunately, limited by its anecdotal nature. The overarching aim of this data paper is to explore evidence of a connection between the presence of transportation infrastructure and changes in population across the kecamatan (districts) of East Java that can be associated with the killings. Using data from three Indonesian censuses that were taken prior to or after the killings, but within two decades of them, estimates of population change at the district level attributable to 1965–66 are computed. These estimates are then compared with data on the degree to which the kecamatan had access to a key transportation network, that of the main roads in the province. In pursuit of this broad goal, two questions about the role of transportation infrastructure, and road networks and trucks in particular, in the 1965– 66 killings are explored. The first question is: was the transportation infrastructure simply incidental to the process, or was it instrumental in determining the scale and scope of disappearances, killings, and movements of people? The second question is: how did the means of transportation impact whether people were disappeared, killed, or moved around? Close attention to spatial patterns of transportation infrastructure and its use combined with knowledge about spatial variations in changes in population associated with the killings can be illuminating. The answers to these questions may reveal interesting dimensions to the violence that have not yet been studied systematically. Specifically, they may confirm or refute a population’s vulnerability to the violence based on living near major transportation arteries and...

International cocaine trafficking has been well-studied, but little is known about cocaine flows within Colombia, the largest producer and exporter of cocaine in the world. Using a unique dataset on the monthly wholesale prices of cocaine across 32 municipios in 2016, this paper estimates patterns of flows of cocaine within Colombia. For the 496 possible resulting pairs of municipios, price differentials are used to infer direction of flow, and price correlations are used to infer connectedness. Among the new findings, 38 suspected municipio-to-municipio flows that are new to the literature are identified. Interestingly, cocaine is inferred to flow through two distinct networks: one that originates in Buenaventura and the other in three points in southern and eastern Colombia. These networks may correspond to distinct criminal trafficking systems, a finding that has potential implications for drug control policies and measures.

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.

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.

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.