Historical Epidemics Cartography Generated by Spatial Analysis: Mapping the Heterogeneity of Three Medieval "Plagues" in Dijon

Pandemics and socio-economic status. Evidence from the plague of 1630 in northern Italy

This paper investigates the biological, socio-economic, and institutional factors shaping the individual risk of death during a major pre-industrial epidemic. We use a micro-demographic database for an Italian city (Carmagnola) during the 1630 plague to explore in detail the survival dynamics of the population admitted to the isolation hospital (lazzaretto). We develop a theoretical model of admissions to the lazzaretto, for better interpretation of the observational data. We explore how age and sex shaped the individual risk of death, and we provide a one-of-a-kind study of the impact of socio-economic status. We report an inversion of the normal mortality gradient by status for those interned at the lazzaretto. The rich enjoyed a greater ability to make decisions about their hospitalization, but this backfired. Instead, the poor sent to the lazzaretto faced a relatively low risk of death because they enjoyed better conditions than they would have experienced outside the hospital.

Reconstructing historical 3D city models

Historical maps are increasingly used for studying how cities have evolved over time, and their applications are multiple: understanding past outbreaks, urban morphology, economy, etc. However, these maps are usually scans of older paper maps, and they are therefore restricted to two dimensions. We investigate in this paper how historical maps can be 'augmented' with the third dimension so that buildings have heights, volumes, and roof shapes. The resulting 3D city models, also known as digital twins, have several benefits in practice since it is known that some spatial analyses are only possible in 3D: visibility studies, wind flow analyses, population estimation, etc. At this moment, reconstructing historical models is (mostly) a manual and very time-consuming operation, and it is plagued by inaccuracies in the 2D maps. In this paper, we present a new methodology to reconstruct 3D buildings from historical maps, we developed it with the aim of automating the process as much as possible, and we discuss the engineering decisions we made when implementing it. Our methodology uses extra datasets for height extraction, reuses the 3D models of buildings that still exist, and infers other buildings with procedural modelling. We have implemented and tested our methodology with real-world historical maps of European cities for different times between 1700 and 2000.

Mortality and demographic recovery in early post-black death epidemics: Role of recent emigrants in medieval Dijon

Objective and methods

We analyze the influence of population movement on susceptibility to death and resilience during two epidemics occurring in Dijon soon after the Black Death. Using a specific program designed to propose links between entries in annual tax registers, we define tentative heads of household, the elapsed time since their first registration and their ties with other persons within the city.

Results

During the 1400 epidemic heads of household who were registered for 1–3 years die in large numbers, whereas during years without epidemics, their death rate is lower than that of heads of household who were registered longer. Recent registration is an epidemic vulnerability factor only in association with a low taxation status, which, when isolated, does not influence mortality. A lack of familial ties within Dijon is another vulnerability factor among the recently registered. This suggests that poor, recent emigrants are more affected by epidemic mortality. In contrast, the mortality of recently registered heads of household is indistinct during a later epidemic occurring after several years of major famine that may have selected the more resistant emigrants and/or excluded the more miserable of them from our analysis. In contrast to the first one, this second epidemic is followed by rapid demographic recovery. This latter recovery is fully explained by the contribution of poor, newly registered heads of household without ties in Dijon.

Conclusion

Our results outline the interaction between population movement and low socioeconomic status on death susceptibility in historical plagues and show that poor recent emigrants may also be key players in the resilience of the population after an epidemic.

The 'light touch' of the Black Death in the Southern Netherlands: an urban trick?

Although the fanciful notion that the Black Death bypassed the Low Countries has long been rejected, nevertheless a persistent view remains that the Low Countries experienced only a 'light touch' of the plague when placed in a broader European perspective, and recovered quickly and fully. However, in this article an array of dispersed sources for the Southern Netherlands together with a new mortmain accounts database for Hainaut show that the Black Death was severe, perhaps no less severe than other parts of western Europe; that serious plagues continued throughout the fourteenth and fifteenth centuries; and that the Black Death and recurring plagues spread over vast territories-including the countryside. The previous conception of a 'light touch' of plague in the Low Countries was created by the overprivileging of particular urban sources, and a failure to account for the rapid replenishment of cities via inward migration, which obscured demographic decimation. We suggest that the population of the Low Countries may not have recovered faster than other parts of western Europe but instead experienced a greater degree of post-plague rural-urban migration.

A survival analysis of the last great European plagues: The case of Nonantola (Northern Italy) in 1630

This paper develops the first survival analysis of a large-scale mortality crisis caused by plague. For the time-to-event analyses we used the Cox proportional hazards regression model. Our case study is the town of Nonantola during the 1630 plague, which was probably the worst to affect Italy since the Black Death. Individual risk of death did not depend on sex, grew with age (peaking at ages 40-60 and then declining), was not affected by socio-economic status, and was positively associated with household size. We discuss these findings in light of the historical-demographic and palaeo-demographic literature on medieval and early modern plagues. Our results are compatible with the debated idea that ancient plague was able to spread directly from human to human. Our methods could be replicated in other studies of European plagues to nuance and integrate the findings of recent palaeo-biological and palaeo-demographic research on plague.

Dangers of Noncritical Use of Historical Plague Data

Researchers have published several articles using historical data sets on plague epidemics using impressive digital databases that contain thousands of recorded outbreaks across Europe over the past several centuries. Through the digitization of preexisting data sets, scholars have unprecedented access to the historical record of plague occurrences. However, although these databases offer new research opportunities, noncritical use and reproduction of preexisting data sets can also limit our understanding of how infectious diseases evolved. Many scholars have performed investigations using Jean-Noël Biraben’s data, which contains information on mentions of plague from various kinds of sources, many of which were not cited. When scholars fail to apply source criticism or do not reflect on the content of the data they use, the reliability of their results becomes highly questionable. Researchers using these databases going forward need to verify and restrict content spatially and temporally, and historians should be encouraged to compile the work.

Exploring and visualizing multidimensional data in translational research platforms

The unprecedented advances in technology and scientific research over the past few years have provided the scientific community with new and more complex forms of data. Large data sets collected from single groups or cross-institution consortiums containing hundreds of omic and clinical variables corresponding to thousands of patients are becoming increasingly commonplace in the research setting. Before any core analyses are performed, visualization often plays a key role in the initial phases of research, especially for projects where no initial hypotheses are dominant. Proper visualization of data at a high level facilitates researcher's abilities to find trends, identify outliers and perform quality checks. In addition, research has uncovered the important role of visualization in data analysis and its implied benefits facilitating our understanding of disease and ultimately improving patient care. In this work, we present a review of the current landscape of existing tools designed to facilitate the visualization of multidimensional data in translational research platforms. Specifically, we reviewed the biomedical literature for translational platforms allowing the visualization and exploration of clinical and omics data, and identified 11 platforms: cBioPortal, interactive genomics patient stratification explorer, Igloo-Plot, The Georgetown Database of Cancer Plus, tranSMART, an unnamed data-cube-based model supporting heterogeneous data, Papilio, Caleydo Domino, Qlucore Omics, Oracle Health Sciences Translational Research Center and OmicsOffice® powered by TIBCO Spotfire. In a health sector continuously witnessing an increase in data from multifarious sources, visualization tools used to better grasp these data will grow in their importance, and we believe our work will be useful in guiding investigators in similar situations.

The sex-selective impact of the Black Death and recurring plagues in the Southern Netherlands, 1349-1450

Although recent work has begun to establish that early modern plagues had selective mortality effects, it was generally accepted that the initial outbreak of Black Death in 1347-52 was a "universal killer." Recent bioarchaeological work, however, has argued that the Black Death was also selective with regard to age and pre-plague health status. The issue of the Black Death's potential sex selectivity is less clear. Bioarchaeological research hypothesizes that sex-selection in mortality was possible during the initial Black Death outbreak, and we present evidence from historical sources to test this notion.

OBJECTIVE

To determine whether the Black Death and recurring plagues in the period 1349-1450 had a sex-selective mortality effect.

MATERIALS AND METHODS

We present a newly compiled database of mortality information taken from mortmain records in Hainaut, Belgium, in the period 1349-1450, which not only is an important new source of information on medieval mortality, but also allows for sex-disaggregation.

RESULTS

We find that the Black Death period of 1349-51, as well as recurring plagues in the 100 years up to 1450, often had a sex-selective effect-killing more women than in "non-plague years."

DISCUSSION

Although much research tends to suggest that men are more susceptible to a variety of diseases caused by bacteria, viruses and parasites, we cannot assume that the same direction of sex-selection in mortality applied to diseases in the distant past such as Second Pandemic plagues. While the exact reasons for the sex-selective effect of late-medieval plague are unclear in the absence of further data, we suggest that simple inequities between the sexes in exposure to the disease may not have been a key driver.