RESUMO
In the summer of 1630, Milan experienced the most devastating plague epidemic in its history. In this study, addressed to investigate the earliest phases of the epidemic in the autumn of 1629, a set of unpublished and only partially known primary sources produced by the city's Officium Sanitatis was consulted and compared for the first time. Including those of two foreigners who died in the Lazzaretto, it was possible to ascertain a total of 39 cases of plague occurred in Milan between 9 October 1629 and the first weeks of 1630, of which 29 (74.4%) ended in death. Seven deaths presumably occurred at home were not recorded in the Liber Mortuorum, in which at least three other deaths caused by plague were deliberately attributed to a different cause. In particular, the case of the Vicario di Provisione in charge, Alfonso Visconti, probably the first death from plague occurred in Milan that year, was deliberately concealed for political reasons. Nevertheless, the spread of the disease remained limited in autumn 1629 and it was probably stopped until the following spring more by climatic factors than by the interventions of public health officials.
RESUMO
Here, we present a computational protocol to perform a spatiotemporal reconstruction of an epidemic. We describe steps for using epidemiological data to depict how the epidemic changes over time and for employing clustering analysis to group geographical units that exhibit similar temporal epidemic progression. We then detail procedures for analyzing the temporal and spatial dynamics of the epidemic within each cluster. This protocol has been developed to be used on historical data but could also be applied to modern epidemiological data. For complete details on the use and execution of this protocol, please refer to Galli et al. (2023).1.
Assuntos
Análise por ConglomeradosRESUMO
In 1630, a devastating plague epidemic struck Milan, one of the most important Italian cities of that time, deeply affecting its demography and economy for decades. The lack of digitized historical data strongly limits our comprehension of that important event. In this work, we digitized and analyzed the Milan death registers of 1630. The study revealed that the epidemic evolved differently among the areas of the city. Indeed, we were able to group the parishes of the city (comparable with modern neighborhoods) in two groups based on their epidemiological curves. These different epidemiological progressions could reflect socio-economical and/or demographic features specific of the neighborhoods, opening questions about the relationship between these features and the evolution of epidemics in the pre-modern period. The study of historical records, like the one presented here, can help us to better understand European history and pre-modern epidemics.