Putting Africa on the Black Death map: Narratives from genetics and history

Green, Monica H.

doi:10.4000/afriques.2125

Cited by 30 publications

(18 citation statements)

References 121 publications

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“…Although its African origin is not universally accepted ( 54 , 58 ), there is robust genetic evidence for the long-standing presence of Y. pestis in Central Africa ( 59 ). One particular Y. pestis strain, today found exclusively in DRC, Zambia, Kenya, and Uganda, has occurred in Central Africa for at least 300 years and is the oldest living strain closely related to the 14th century Black Death lineage ( 59 , 60 ). At present, there is no firm evidence for persistent vector-borne diseases to have afflicted the Congo rainforest communities during the period of population collapse.…”

Section: Discussionmentioning

confidence: 99%

“…At present, there is no firm evidence for persistent vector-borne diseases to have afflicted the Congo rainforest communities during the period of population collapse. However, the modern distribution of Y. pestis strains does suggest that “Africa harbors strains of plague that entered the continent in different historical periods” ( 59 , 60 ). More genetic research would be needed to corroborate our hypothesis that the strong population decline during 400 to 600 CE revealed by our data may have been caused by a vector-borne epidemic.…”

Section: Discussionmentioning

confidence: 99%

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Population collapse in Congo rainforest from 400 CE urges reassessment of the Bantu Expansion

et al. 2021

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The present-day distribution of Bantu languages is commonly thought to reflect the early stages of the Bantu Expansion, the greatest migration event in African prehistory. Using 1149 radiocarbon dates linked to 115 pottery styles recovered from 726 sites throughout the Congo rainforest and adjacent areas, we show that this is not the case. Two periods of more intense human activity, each consisting of an expansion phase with widespread pottery styles and a regionalization phase with many more local pottery styles, are separated by a widespread population collapse between 400 and 600 CE followed by major resettlement centuries later. Coinciding with wetter climatic conditions, the collapse was possibly promoted by a prolonged epidemic. Comparison of our data with genetic and linguistic evidence further supports a spread-over-spread model for the dispersal of Bantu speakers and their languages.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Population collapse in Congo rainforest from 400 CE urges reassessment of the Bantu Expansion

et al. 2021

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“…Mortality at that time was extremely high, due to the lack of medical treatment. Pyle, Walter Lytle states that "The Black Death resulted in the deaths of up to 75-200 million people in Eurasia and North Africa, peaking in Europe from 1347 to 1351 [1]." Because of the black death, famine showed up at Europe, which also contributed to the mortality rate.…”

Section: Methodsmentioning

confidence: 99%

Shared Elements in Destiny between Jewish and Other Ethnic Groups

2020

2020 3rd International Conference on E-Education, E-Business and Information Management (EEIM 2020)

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“…Combining plague data from different sources to fill the spatial and temporal gaps could potentially reduce the problem of spatial and/or temporal representativeness, and improve our understanding of the spatio-temporal spread. Particularly, new data on the plague dissemination in neglected regions such as sub-Saharan Africa [62], Turkey and Southern Asia [62][63][64] could confirm whether the shift of plague activity from Europe to North Africa in the 16 th to 19 th century, and the growing presence of plague in Asia in the 17 th to 19 th century is a real pattern or merely an artefact of missing data in the centuries before. However, consistency in the data definition and collection is crucial.…”

Section: Usage and Limitations Of Geo-referenced Plague Datasetsmentioning

confidence: 99%

Mapping the plague through natural language processing

Krauer

Schmid

2021

Preprint

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Plague has caused three major pandemics with millions of casualties in the past centuries. There is a substantial amount of historical and modern primary and secondary literature about the spatial and temporal extent of epidemics, circumstances of transmission or symptoms and treatments. Many quantitative analyses rely on structured data, but the extraction of specific information such as the time and place of outbreaks is a tedious process. Machine learning algorithms for natural language processing (NLP) can potentially facilitate the establishment of datasets, but their use in plague research has not been explored much yet. We investigated the performance of five pre-trained NLP libraries (Google NLP, Stanford CoreNLP, spaCy, germaNER and Geoparser.io) for the extraction of location data from a German plague treatise published in 1908 compared to the gold standard of manual annotation. Of all tested algorithms, we found that Stanford CoreNLP had the best overall performance but spaCy showed the highest sensitivity. Moreover, we demonstrate how word associations can be extracted and displayed with simple text mining techniques in order to gain a quick insight into salient topics. Finally, we compared our newly digitised plague dataset to a re-digitised version of the famous Biraben plague list and update the spatio-temporal extent of the second pandemic plague mentions. We conclude that all NLP tools have their limitations, but they are potentially useful to accelerate the collection of data and the generation of a global plague outbreak database.

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Putting Africa on the Black Death map: Narratives from genetics and history

Cited by 30 publications

References 121 publications

Population collapse in Congo rainforest from 400 CE urges reassessment of the Bantu Expansion

Population collapse in Congo rainforest from 400 CE urges reassessment of the Bantu Expansion

Shared Elements in Destiny between Jewish and Other Ethnic Groups

Mapping the plague through natural language processing

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