Network theory may explain the vulnerability of medieval human settlements to the Black Death pandemic

Characterizing the connection between swine production sites by personnel movements using a mobile application-based geofencing platform

Biosecurity is critical to productivity and profitability in swine production systems and can be achieved by incorporating external (bioexclusion) and internal (biocontainment) practices. Although increasing threats of foreign animal diseases have justified the need of rigorous external biosecurity plans, their effectiveness highly depend on the compliance of on-farm employees, farm-related personnel, and visitors. In this study, we evaluated the uses of a mobile application-based geofencing platform in two swine production systems for accurately identifying personnel movements between swine production sites and detecting potential biosecurity breaches by violating required downtime between site visits. The geofencing platform accurately recognized 95.2% (379/398) of personnel entries comparing to physical entry logs. Further, among 1861 entries over a period of one month, 19 strongly connected components and 12 potential biosecurity breaches were identified. Personnel with duty in communications and information systems committed 75% of biosecurity breaches. The results reported herein demonstrated the possible uses of geofencing platforms for investigating connections among swine production sites by personnel movements and identifying biosecurity breaches.

The Challenging Future of Pilgrimage after the Pandemic: New Trends in Pilgrimage to Compostela

During the COVID-19 period, many authors observed changes occurring in pilgrimage along the Way of Saint James. Pandemics have appeared many times in the history of this route, causing changes in the behavior of pilgrims and their environment, such as improvements in healthcare. In this paper, we begin by examining the new contributions that the pandemic has made to the contemporary religious experience of the Camino. The pandemic can be read in a twofold manner: as an attempt to “verify” the motives and as an “opportunity” to preserve the essence of pilgrimage; it also seems to be capable of changing the attitudes of the residents living along the Camino towards the pilgrims. Next, we point to several phenomena that appear on the horizon of the post-pandemic Camino, such as the isolationism of pilgrims, the dominance of individualism, the medicalization of pilgrimage and the restrictions on access to religious practices. This opens up the question of new forms of asceticism with which the Camino has been associated and new trends in pilgrimage to Compostela.

The source of the Black Death in fourteenth-century central Eurasia

The origin of the medieval Black Death pandemic (ad 1346–1353) has been a topic of continuous investigation because of the pandemic’s extensive demographic impact and long-lasting consequences^1,2. Until now, the most debated archaeological evidence potentially associated with the pandemic’s initiation derives from cemeteries located near Lake Issyk-Kul of modern-day Kyrgyzstan^1,3–9. These sites are thought to have housed victims of a fourteenth-century epidemic as tombstone inscriptions directly dated to 1338–1339 state ‘pestilence’ as the cause of death for the buried individuals⁹. Here we report ancient DNA data from seven individuals exhumed from two of these cemeteries, Kara-Djigach and Burana. Our synthesis of archaeological, historical and ancient genomic data shows a clear involvement of the plague bacterium Yersinia pestis in this epidemic event. Two reconstructed ancient Y. pestis genomes represent a single strain and are identified as the most recent common ancestor of a major diversification commonly associated with the pandemic’s emergence, here dated to the first half of the fourteenth century. Comparisons with present-day diversity from Y. pestis reservoirs in the extended Tian Shan region support a local emergence of the recovered ancient strain. Through multiple lines of evidence, our data support an early fourteenth-century source of the second plague pandemic in central Eurasia.

Global pandemics, conflict and networks - the dynamics of international instability, infodemics and health care in the 21st century

Background

The COVID-19 global pandemic is a harbinger of a future destabilised world driven by climate change, rapid mass migration, food insecurity, state failures and epidemics. A significant feature fuelling this destabilised world is networked misinformation and disinformation (referred to as an infodemic), particularly in the area of health.

Aims

To describe the interactive dynamic of climate change; mass population movement; famine; state failure and epidemic disease, analyse developments over the year 2020–2021 and discuss their relationship to an infodemic about disease and public health responses and how this should be addressed in the future.

Methods

Using the concept of ‘the Five Horsemen’ of epochal change and network theory to guide a narrative review.

Results

Concepts of epidemiology are reflected in how misinformation is spread around the world. Health care services and personnel face threats as a result that make it more difficult to manage pan global health risks effectively.

Conclusions

Heath care professionals at an individual and organisational level need to counter infodemic networks. Health care professionals who consistently spread misinformation should have their licence to practice withdrawn.

Comparing transmission potential networks based on social network surveys, close contacts and environmental overlap in rural Madagascar

Social and spatial network analysis is an important approach for investigating infectious disease transmission, especially for pathogens transmitted directly between individuals or via environmental reservoirs. Given the diversity of ways to construct networks, however, it remains unclear how well networks constructed from different data types effectively capture transmission potential. We used empirical networks from a population in rural Madagascar to compare social network survey and spatial data-based networks of the same individuals. Close contact and environmental pathogen transmission pathways were modelled with the spatial data. We found that naming social partners during the surveys predicted higher close-contact rates and the proportion of environmental overlap on the spatial data-based networks. The spatial networks captured many strong and weak connections that were missed using social network surveys alone. Across networks, we found weak correlations among centrality measures (a proxy for superspreading potential). We conclude that social network surveys provide important scaffolding for understanding disease transmission pathways but miss contact-specific heterogeneities revealed by spatial data. Our analyses also highlight that the superspreading potential of individuals may vary across transmission modes. We provide detailed methods to construct networks for close-contact transmission pathogens when not all individuals simultaneously wear GPS trackers.

The Management of Psychiatric Emergencies in Situations of Public Calamity

The prevalence of mental health problems in the general population during a public calamity is high. In calamities, the number of patients who present with mental disorder outbreaks or crises may increase, but the necessary support systems to help them may be impaired if they have not been planned for. Although there are several models for addressing psychiatric emergencies, the general rules are the same, especially when it comes to making these services easily available to the affected population. In this article, we seek to review and present recommendations for the management of psychiatric emergencies in situations of public calamity, including disasters, physical and medical catastrophes, epidemics, and pandemics.

A digital reconstruction of the 1630-1631 large plague outbreak in Venice

The plague, an infectious disease caused by the bacterium Yersinia pestis, is widely considered to be responsible for the most devastating and deadly pandemics in human history. Starting with the infamous Black Death, plague outbreaks are estimated to have killed around 100 million people over multiple centuries, with local mortality rates as high as 60%. However, detailed pictures of the disease dynamics of these outbreaks centuries ago remain scarce, mainly due to the lack of high-quality historical data in digital form. Here, we present an analysis of the 1630-1631 plague outbreak in the city of Venice, using newly collected daily death records. We identify the presence of a two-peak pattern, for which we present two possible explanations based on computational models of disease dynamics. Systematically digitized historical records like the ones presented here promise to enrich our understanding of historical phenomena of enduring importance. This work contributes to the recently renewed interdisciplinary foray into the epidemiological and societal impact of pre-modern epidemics.

Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability

OBJECTIVES

The growth of COVID-19 infections in England raises questions about system vulnerability. Several factors that vary across geographies, such as age, existing disease prevalence, medical resource availability and deprivation, can trigger adverse effects on the National Health System during a pandemic. In this paper, we present data on these factors and combine them to create an index to show which areas are more exposed. This technique can help policy makers to moderate the impact of similar pandemics.

DESIGN

We combine several sources of data, which describe specific risk factors linked with the outbreak of a respiratory pathogen, that could leave local areas vulnerable to the harmful consequences of large-scale outbreaks of contagious diseases. We combine these measures to generate an index of community-level vulnerability.

SETTING

91 Clinical Commissioning Groups (CCGs) in England.

MAIN OUTCOME MEASURES

We merge 15 measures spatially to generate an index of community-level vulnerability. These measures cover prevalence rates of high-risk diseases; proxies for the at-risk population density; availability of staff and quality of healthcare facilities.

RESULTS

We find that 80% of CCGs that score in the highest quartile of vulnerability are located in the North of England (24 out of 30). Here, vulnerability stems from a faster rate of population ageing and from the widespread presence of underlying at-risk diseases. These same areas, especially the North-East Coast areas of Lancashire, also appear vulnerable to adverse shocks to healthcare supply due to tighter labour markets for healthcare personnel. Importantly, our index correlates with a measure of social deprivation, indicating that these communities suffer from long-standing lack of economic opportunities and are characterised by low public and private resource endowments.

CONCLUSIONS

Evidence-based policy is crucial to mitigate the health impact of pandemics such as COVID-19. While current attention focuses on curbing rates of contagion, we introduce a vulnerability index combining data that can help policy makers identify the most vulnerable communities. We find that this index is positively correlated with COVID-19 deaths and it can thus be used to guide targeted capacity building. These results suggest that a stronger focus on deprived and vulnerable communities is needed to tackle future threats from emerging and re-emerging infectious disease.

Modeling the Justinianic Plague: Comparing hypothesized transmission routes

The Justinianic Plague, the first part of the earliest of the three plague pandemics, has minimal historical documentation. Based on the limited primary sources, historians have argued both for and against the "maximalist narrative" of plague, i.e. that the Justinianic Plague had universally devastating effects throughout the Mediterranean region during the sixth century CE. Using primary sources of one of the pandemic’s best documented outbreaks that took place in Constantinople during 542 CE, as well as modern findings on plague etiology and epidemiology, we developed a series of dynamic, compartmental models of disease to explore which, if any, transmission routes of plague are feasible. Using expected parameter values, we find that the bubonic and bubonic-pneumonic transmission routes exceed maximalist mortality estimates and are of shorter detectable duration than described by the primary sources. When accounting for parameter uncertainty, several of the bubonic plague model configurations yielded interquartile estimates consistent with the upper end of maximalist estimates of mortality; however, these models had shorter detectable outbreaks than suggested by the primary sources. The pneumonic transmission routes suggest that by itself, pneumonic plague would not cause significant mortality in the city. However, our global sensitivity analysis shows that predicted disease dynamics vary widely for all hypothesized transmission routes, suggesting that regardless of its effects in Constantinople, the Justinianic Plague would have likely had differential effects across urban areas around the Mediterranean. Our work highlights the uncertainty surrounding the details in the primary sources on the Justinianic Plague and calls into question the likelihood that the Justinianic Plague affected all localities in the same way.

Soil salinity and aridity specify plague foci in the United States of America

Plague is a deadly zoonosis that periodically reemerges as small outbreaks in geographically limited foci where the causative agent Yersinia pestis may reside in soil. We analyzed a dataset of 1.005 carefully documented plague cases that were georeferenced over 113 years in peer-reviewed literature in the contiguous United States. Plotting outbreaks by counties defined as plague foci on geographical maps, we observed a significant co-localization of plague outbreaks with high soil salinity measured by an electric conductivity of >4 dS/ m^-1 and aridity measured by an aridity index <0.5. Thus, we identified aridity and soil salinity as significantly associated with ecological risk factors for relapsing plague in the contiguous United States. These results reveal two evolutive parameters that are partially associated with anthropic activities, complicating the epidemiology of plague in the contiguous United States. Exploiting aridity and soil salinity data may help in the surveillance of evolving plague foci in the contiguous United States.

Climate and society in long-term perspective: Opportunities and pitfalls in the use of historical datasets

Recent advances in paleoclimatology and the growing digital availability of large historical datasets on human activity have created new opportunities to investigate long-term interactions between climate and society. However, noncritical use of historical datasets can create pitfalls, resulting in misleading findings that may become entrenched as accepted knowledge. We demonstrate pitfalls in the content, use and interpretation of historical datasets in research into climate and society interaction through a systematic review of recent studies on the link between climate and (a) conflict incidence, (b) plague outbreaks and (c) agricultural productivity changes. We propose three sets of interventions to overcome these pitfalls, which involve a more critical and multidisciplinary collection and construction of historical datasets, increased specificity and transparency about uncertainty or biases, and replacing inductive with deductive approaches to causality. This will improve the validity and robustness of interpretations on the long-term relationship between climate and society. This article is categorized under: Climate, History, Society, Culture > Disciplinary Perspectives.

EpiRank: Modeling Bidirectional Disease Spread in Asymmetric Commuting Networks

Commuting network flows are generally asymmetrical, with commuting behaviors bi-directionally balanced between home and work locations, and with weekday commutes providing many opportunities for the spread of infectious diseases via direct and indirect physical contact. The authors use a Markov chain model and PageRank-like algorithm to construct a novel algorithm called EpiRank to measure infection risk in a spatially confined commuting network on Taiwan island. Data from the country's 2000 census were used to map epidemic risk distribution as a commuting network function. A daytime parameter was used to integrate forward and backward movement in order to analyze daily commuting patterns. EpiRank algorithm results were tested by comparing calculations with actual disease distributions for the 2009 H1N1 influenza outbreak and enterovirus cases between 2000 and 2008. Results suggest that the bidirectional movement model outperformed models that considered forward or backward direction only in terms of capturing spatial epidemic risk distribution. EpiRank also outperformed models based on network indexes such as PageRank and HITS. According to a sensitivity analysis of the daytime parameter, the backward movement effect is more important than the forward movement effect for understanding a commuting network's disease diffusion structure. Our evidence supports the use of EpiRank as an alternative network measure for analyzing disease diffusion in a commuting network.

Spatial constraints on the diffusion of religious innovations: The case of early Christianity in the Roman Empire

Christianity emerged as a small and marginal movement in the first century Palestine and throughout the following three centuries it became highly visible in the whole Mediterranean. Little is known about the mechanisms of spreading innovative ideas in past societies. Here we investigate how well the spread of Christianity can be explained as a diffusive process constrained by physical travel in the Roman Empire. First, we combine a previously established model of the transportation network with city population estimates and evaluate to which extent the spatio-temporal pattern of the spread of Christianity can be explained by static factors. Second, we apply a network-theoretical approach to analyze the spreading process utilizing effective distance. We show that the spread of Christianity in the first two centuries closely follows a gravity-guided diffusion, and is substantially accelerated in the third century. Using the effective distance measure, we are able to suggest the probable path of the spread. Our work demonstrates how the spatio-temporal patterns we observe in the data can be explained using only spatial constraints and urbanization structure of the empire. Our findings also provide a methodological framework to be reused for studying other cultural spreading phenomena.

Its all about connections: hubs and invasion in habitat networks

During the early stages of invasion, the interaction between the features of the invaded landscape, notably its spatial structure, and the internal dynamics of an introduced population has a crucial impact on establishment and spread. By approximating introduction areas as networks of patches linked by dispersal, we characterised their spatial structure with specific metrics and tested their impact on two essential steps of the invasion process: establishment and spread. By combining simulations with experimental introductions of Trichogramma chilonis (Hymenoptera: Trichogrammatidae) in artificial laboratory microcosms, we demonstrated that spread was hindered by clusters and accelerated by hubs but was also affected by small-population mechanisms prevalent for invasions, such as Allee effects. Establishment was also affected by demographic mechanisms, in interaction with network metrics. These results highlight the importance of considering the demography of invaders as well as the structure of the invaded area to predict the outcome of invasions.

Two thousand years of epidemics in Marseille and the Mediterranean Basin

Marseille has been exposed to epidemics for two millennia, including plague, cholera and yellow fever. This long-standing exposure to epidemics has given the people of Marseilles a particular expertise in fighting epidemics. Lazarets and other quarantine measures were implemented as a response to preventing the further spread of the disease in the community. The Institut Hospitalier Universitaire Méditerranée Infection is paving the way today, with its responses built on the region's long history and knowledge of epidemics, infectious diseases and medical microbiology.

A geo-computational algorithm for exploring the structure of diffusion progression in time and space

A diffusion process can be considered as the movement of linked events through space and time. Therefore, space-time locations of events are key to identify any diffusion process. However, previous clustering analysis methods have focused only on space-time proximity characteristics, neglecting the temporal lag of the movement of events. We argue that the temporal lag between events is a key to understand the process of diffusion movement. Using the temporal lag could help to clarify the types of close relationships. This study aims to develop a data exploration algorithm, namely the TrAcking Progression In Time And Space (TaPiTaS) algorithm, for understanding diffusion processes. Based on the spatial distance and temporal interval between cases, TaPiTaS detects sub-clusters, a group of events that have high probability of having common sources, identifies progression links, the relationships between sub-clusters, and tracks progression chains, the connected components of sub-clusters. Dengue Fever cases data was used as an illustrative case study. The location and temporal range of sub-clusters are presented, along with the progression links. TaPiTaS algorithm contributes a more detailed and in-depth understanding of the development of progression chains, namely the geographic diffusion process.