Conflicts and the spread of plagues in pre-industrial Europe

Historians, scientists, and wider society have generally paid little attention to bygone epidemics, with the marked exceptions of the Black Death and the Great Plague of London (Duffy, 1977). This narrow outlook has recently changed due to the coronavirus pandemic and its profound impacts on human health, the global economy and the geography of travel. For instance, the ongoing Covid-19 crisis has sparked renewed interest in Albert Camus' novel "The plague", originally published in 1947. The fascist "plague" that inspired the novel may no longer be a reality, but many other varieties of "pestilence" mean that this theme still has relevance today (Franco-Paredes, 2020). Pandemics are the most dramatic manifestation of the rapid and efficient spread of infectious pathogens, capable of influencing the course of world history. Understanding why, when, and how past epidemics/pandemics spread is therefore key to contextualizing current outbreaks. The 2019/2020 coronavirus (Covid-19) pandemic has sharpened focus on the role of human population movements in rapidly spreading pathogenic microbes from a local hotspot to the global scale (Bedford et al., 2020; Chinazzi et al., 2020). In the past 40 years, outbreaks of infectious diseases have also been underpinned by population exoduses. Scourges have often emerged in forcibly displaced populations, invariably linked to a breakdown of health and social services (Murray et al., 2002). The Office of the United Nations High Commissioner for Refugees (UNHCR) reported that the "global forced displacement population" who have escaped conflict, persecution, or human rights violations totaled ~40 million people at the end of 2016 (The UN Refugee Agency, 2016). In 2018, it is estimated that 25 people were forced to flee unsecure areas every minute (The UN Refugee Agency, 2018). War produces a multitude of opportunities for pathogenic microbes and constitutes an extremely effective way to promote microbial traffic and increase human morbidity and mortality. Migrants can act as vectors for infectious disease, leading to severe epidemics in receiving areas, where displaced populations are often housed in cramped refugee camps (see the Darfur region of Sudan; Degomme and Guha-Sapir, 2010). As early as 1995, the UNHCR stated that measles, diarrheal diseases, acute respiratory infections, and malaria account for between 60% and 80% of reported deaths in refugee camps (The UN Refugee Agency, 1995). The health consequences of wars are nowadays circumvented by basic health care services, which alleviate the spread of epidemics, even in countries engaged in armed conflicts and where interventions are challenging (Spiegel et al., 2010; Leaning and Guha-Sapir, 2013). During the Late Middle Ages to the Early Modern Age, when persistent conflicts marred the European continent, the spread of plague (caused by the bacteria Yersinia pestis) was probably aggravated and enhanced through populations fleeing war zones, increasing the geographical range of epidemics. Fatigue, malnutrition, wounds, and stress are known to lower immune responses in human populations. Furthermore, camp life in crowded and unsanitary conditions favors the spread of contagious diseases and creates ideal ecological niches for both native and imported parasites. It has recently been suggested that there is an urgent need for a quantitative framework for modeling modern conflicts and epidemics (Banerjee, 2019). Within this context, there is potentially much to learn from the past and historical data are key to calibrating models. Here, we quantify the fundamental link between conflicts, plagues, fatalities, and the evolution of world population for the period from the Late Middle Ages to the Early Modern Age (AD 1340-1900). We also analyze how climate deterioration aggravated past epidemics/pandemics.

The paper situates its contribution within several strands of prior research: (i) historical accounts of major pandemics, notably the Black Death and successive plague waves, and their demographic impacts (e.g., Benedictow, 2006; Hays, 2005); (ii) debates on the origins, reservoirs, and transmission pathways of Yersinia pestis during the second pandemic, including hypotheses of repeated reintroductions from Asia versus European reservoirs (Schmid et al., 2015; Carmichael, 2014; Rasmussen et al., 2015); (iii) the role of trade and navigable routes in facilitating plague spread (Yue et al., 2016); (iv) climate’s role—particularly temperature anomalies—on plague dynamics, with mixed findings and ongoing debate (Neukom et al., 2014; Luterbacher et al., 2016; Schmid et al., 2015; Yue and Lee, 2018; Stenseth et al., 2006); and (v) modern public health literature on conflict, displacement, and infectious disease transmission, highlighting refugee settings and service breakdowns (Murray et al., 2002; UNHCR reports; Spiegel et al., 2010). The authors note limitations and biases in widely used historical plague datasets (Biraben, 1976; Rosen and Curtis, 2018) and identify the absence of quantitative assessments linking conflicts to historical plague spread, which their study seeks to address.

Study scope: Europe during the second plague pandemic era and adjacent centuries, focusing on AD 1347–1840, with annually resolved time series for conflicts, plague outbreaks, fatalities (scaled by world population), and climate proxies. Data sources: - Conflicts: P. Brecke Conflict Catalog (compiled since 1998). Events (wars, revolts, civil wars, insurgencies, rebellions, battles) were sorted by date, duration, and participating entities; summed annually to produce a linear time series (AD 1347–1840). Authors note possible omissions; dataset used to detect general trends. - Plague outbreaks: Records of epidemics attributed to Yersinia pestis. Base dataset from Biraben (1976), digitized and extended (Atanasiu et al., 2008; Büntgen et al., 2012; Voigtländer and Voth, 2013), with additions from Russia, Constantinople, and Turkey (Schmid et al., 2015). Recognized biases include overestimation in cities and underrepresentation of towns/villages; used for trend analysis rather than event-level inference (Rosen and Curtis, 2018). - Fatalities: From Brecke Conflict Catalog; summed annually (AD 1347–1840), then converted to fatalities relative to world population. World population estimates from U.S. Census Bureau (2020); transformed to annual resolution and applied log transformation to the fatalities ratio. - Climate: European summer temperature anomalies (Luterbacher et al., 2016), Northern Hemisphere temperature anomalies (Neukom et al., 2014), and Palmer Drought Severity Index for the European Basin (Cook et al., 2015). Analytical procedures: - Smoothing to assess long-term trends using moving averages (9-year and 31-year for overview; commonly 3-year for comparative analyses). - Similarity assessments between time series using Mantel scalograms (Bray–Curtis distance) on smoothed (3-year) series, examining correlation phases and temporal alignments. - Change-point and homogeneity tests applied to smoothed series: Pettitt, Standard Normal Homogeneity Test (SNHT), and Buishand tests to detect shifts; means of identified segments reported as “mu”. - Composite index (CPF): Z-score transform of conflicts, plague incidences, and fatalities summed to form CPF; analyzed with 3-year smoothing and fitted with sinusoidal models (P < 0.001) to characterize long-term periodicities. - Demographic context: Computed 50-year averaged world population growth rates (with standard deviation) from consecutive differences in world population estimates. - Climate–epidemic relationships: Cross-correlations between plague outbreaks and temperature anomaly series; precipitation (PDSI) analyzed as well. Time series sorted by ascending values and modeled with linear and polynomial fits; smoothed curves displayed to examine functional relationships. - Spectral/periodicity analysis: Wavelet transforms (Morlet basis) to detect significant cycles, with cones of influence and 0.05 significance contours. Mantel scalograms used to compare CPF with climate proxies, identifying periods of significant association. - Supplementary analyses: Neighbor-joining clustering used to explore relationships among conflicts, plagues, population density, and fatalities (per Supplementary Fig. 1).

- Temporal coupling of conflicts and plagues: Conflicts increased markedly after AD 1450, with a mean twofold rise during AD 1450–1670, closely followed (c. AD 1465–1470 onward) by increases in plague-affected towns/cities and fatalities. Mantel scalograms identify AD 1450–1670 as the main correlation phase across the series. - Significant correlations across variables: Cross-correlations show positive, statistically significant associations between conflicts and plagues, and between plagues and fatalities (P < 0.001), indicating a chronological link among these variables. - Demographic impact: The composite CPF index peaks align with a plateau in world population. Fifty-year averaged demographic growth slowed from AD 1470–1620, turned negative during AD 1620–1670, and then rose strongly after the late 17th century. - Population density effect: The increasing spread of plagues during AD 1400–1500 likely reflects rising population density, enabling more rapid host-to-host transmission. - Climate associations: Plague outbreaks predominantly coincided with colder periods (pre–Little Ice Age and Little Ice Age conditions). Cross-correlations between plague outbreaks and temperature anomalies (European summer and Northern Hemisphere series) are positive and significant (P < 0.001), with stronger linkage to Northern Hemisphere temperatures. Precipitation anomalies (PDSI) are not a significant explanatory factor for plague incidence. - Shared periodicities: Wavelet analyses reveal statistically significant cycles of approximately 55 and 25 years common to conflicts, plagues, fatalities, and temperature anomalies. Mantel scalograms indicate temperature anomalies correlate with CPF, whereas drought (PDSI) does not. - Historical exemplars: Episodes such as the siege of Caffa (1343–1347), English Civil Wars (1644–1645 outbreaks), and the Great Northern War (1708–1712 plague) illustrate conflict-driven dissemination of disease via military movements and civilian displacement. - Transmission implications: Given rat scarcity in parts of northern Europe and climatic conditions unfavorable to flea vectors during some outbreaks, person-to-person routes (pneumonic transmission and/or human ectoparasites) are posited as important in conflict-linked spreads. - Synthesis: Warfare provided a backdrop for significant microbial opportunity; combined with colder climate-induced malnutrition, crowding, and poor sanitation, this fostered recurrent plague outbreaks and elevated fatalities, yielding a demographic stagnation phase.

The study addresses the question of whether and how armed conflicts influenced the spread of plague in pre-industrial Europe, and how climate modulated these dynamics. The strong temporal alignment and significant correlations among conflicts, plague incidences, and fatalities during AD 1450–1670 support the hypothesis that warfare and the resultant displacement of military and civilian populations substantially amplified plague transmission. This effect likely operated through increased population mixing, movement along primary and secondary routes (beyond major trade corridors), and deterioration of living and sanitary conditions. Climate acted as an enabling factor rather than a primary initiator: colder conditions in the pre–Little Ice Age and Little Ice Age impaired food production, increased malnutrition and stress, and encouraged indoor crowding, all weakening host defenses and facilitating human-to-human transmission pathways. The lack of significant association with drought (PDSI) underscores temperature anomalies as the more relevant climatic dimension in this context. The findings integrate with ongoing debates on plague reservoirs and routes. While reintroduction from Asian reservoirs and European natural reservoirs remain plausible, the conflict-driven displacement mechanism offers an explanation for the spread to peripheral towns and the broader geographic pattern observed. Given rat scarcity and unfavorable vector conditions in parts of Europe, non-rodent transmission routes (pneumonic or human ectoparasites) may have been particularly important during intense conflict periods. Overall, the results illuminate a war–plague–climate nexus that produced substantial excess mortality and a mid-17th-century demographic plateau. This historical perspective underscores the need to consider social disruption and mobility, alongside environmental stressors, in models of infectious disease diffusion.

The study quantitatively demonstrates that in pre-industrial Europe, conflicts, plague outbreaks, and fatalities were significantly correlated, especially during AD 1450–1670, a period marked by a twofold rise in conflicts. This war–plague alliance coincided with a plateau in world population, reflecting slowed (and temporarily negative) demographic growth. Cooler conditions associated with the Little Ice Age likely exacerbated outbreaks by weakening populations through malnutrition, stress, and crowding, while precipitation anomalies were not significant drivers. These insights contribute a missing quantitative link between warfare and historical epidemic spread, informing contemporary models of disease diffusion in conflict settings. The findings reinforce the importance of maintaining healthcare access and sanitary conditions for displaced populations to mitigate epidemic risks. Future research could refine event-level datasets (addressing known biases), integrate higher-resolution mobility and urbanization proxies, test causal inference frameworks, and explore mechanistic transmission models incorporating conflict intensity, logistics, and varying climatic regimes.

- Data completeness and bias: The conflict catalog may omit events; plague records (derived from Biraben and successors) are known to overrepresent cities and underrepresent smaller settlements, reflecting source availability rather than true disease severity or prevalence. The authors therefore focus on trends rather than event-level conclusions. - Measurement and transformation choices: Fatalities were normalized by world population and log-transformed; while appropriate for scaling, such transformations can affect interpretability. - Correlational design: Analyses (smoothing, cross-correlations, Mantel scalograms, sinusoidal fits, wavelets) are primarily correlational and cannot establish causation. Temporal lags and confounders (e.g., trade intensity, governance, sanitation) are not fully disentangled. - Climate proxy limitations: Use of broad regional temperature and drought indices may mask local climatic variability relevant to vector ecology and human subsistence. - Spatial granularity: Annual, pan-European aggregations may obscure heterogeneous regional dynamics and pathways (primary versus secondary routes, urban versus rural transmission). - Transmission inference: Conclusions regarding predominant transmission routes (pneumonic/human ectoparasites) are inferential, based on ecological and historical arguments rather than direct microbiological evidence for each outbreak.