Situating mortality

Quantifying crisis points and periods of stability

Datos Bibliográficos

ID8314877
AutoresLawrence A Sawchuk (Department of Anthropology University of Toronto, Scarborough Toronto ON M1C 1A4, Canada, autor de correspondencia), Lianne Tripp (0000-0003-2168-3958, Department of Anthropology University of Toronto, Scarborough Toronto ON M1C 1A4, Canada), Sotirios Damouras (Department of Computer and Mathematical Sciences University of Toronto, Scarborough Toronto ON M1C 1A4, Canada), Mark DeBono (0000-0002-2246-1110, University of Malta Faculty of Medicine and Surgery (student) Msida, MSD 2080, Malta)
Año2013
Volumen152
Número4
Páginas459-470
Fecha de publicación2013-12-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaAmerican Journal of Physical Anthropology (JOURNAL)
Identificadores de la revistaISSN: 0002-9483 • E-ISSN: 1096-8644
EditorialWiley (PUBLISHER • GB)
DOI10.1002/ajpa.22380
PMID24129905
OpenAlexW2138791427
IdiomaEN
Citas recibidas6
Referencias citadas41

A wide range of stressors can cause a dramatic and sudden rise in the death rate in populations, typically resulting in what is referred to as crisis mortality. Here we present a method to standardize the assessment of identifying moments of crises. A modification of the mortality Z ‐score methodology which is combined with time series analysis was used to investigate mortality events over the course of nearly two centuries for two populations: Gibraltar and Malta. A benefit of this method is that it situates the yearly death rate within the prevailing mortality pattern, and by doing so allows the researcher to assess the relative impact of that event against the norm for the period under investigation. A series of threshold values were established to develop levels of mortality to distinguish moments of lower mortality than expected, background mortality, a crisis, and a catastrophe. Our findings suggested that within defined periods, a limited number of events constituted moments of excessive mortality in the range of a crisis or higher. These included epidemics (yellow fever and influenza in Gibraltar only, and cholera) and casualties associated with World War II. Episodes of lower than expected mortality were only detected (although not significant) in the 20th century in Malta, and at the micro level, the harvesting effect appears to have occurred following cholera epidemics in both locations and influenza in Gibraltar. The analysis demonstrates clearly that the impact of epidemics can be highly variable across time and populations. Am J Phys Anthropol 152:459–470, 2013. © 2013 Wiley Periodicals, Inc

Cholera · Coronavirus disease 2019 (COVID-19) · Disease · Geography · Infectious disease (medical specialty) · Influenza pandemic · Mortality rate · Sociology · Climate Change and Health Impacts · COVID-19 epidemiological studies · Demography · Health and Conflict Studies · Medicine · Virology