Modeling plague in Medieval European cities

Early Lunch Talk by Katie Dean

The Black Death pandemic swept through Europe during the
Middle Ages leading to high mortality from plague, caused by the
bacterium Yersinia pestis. How it spread, the transmission of the
disease within and between cities, remains a subject of controversy
among scientists and historians. Prior to the identification of the
bacterium in medieval tooth samples, the nature of the pandemic led to
speculation that the Black Death was not the same disease as
current-day plague. In the classical mode of transmission to humans,
black rats act as an intermediate host and the disease spreads by
infected rat fleas. But in the case of Black Death, alternate modes
have been proposed in which the disease spreads either through
pneumonic transmission of plague or through an intermediate human
ectoparasite vector, such as the human body louse. To understand the
transmission dynamics within cities, we used a spatial metapopulation
model with SIR-dynamics for three transmission scenarios and compared
how the epidemic curve, epidemic duration, and total mortality differ
between each mode and historical data. Here we show that 1) a model of
louse-borne transmission of bubonic plague fits the pattern of plague
transmission within cities during the Black Death with regards to
epidemic duration and the distribution of deaths during an epidemic,
and that 2) primary pneumonic plague can produce large scale
epidemics, but only under conditions highly favorable for this mode of
transmission. These results demonstrate that the louse-borne
transmission of bubonic plague is a viable alternative to resolve the
inconsistencies between plague during the Black Death and plague with
rats. We anticipate that the models and parameters we have presented
can be used in future work for more complex models that combine
multiple transmission routes. For example, a model with both primary
pneumonic and bubonic plague transmission during the same epidemic.
Furthermore, the models can be adapted to explore the impact of
immunity, public health measures, and seasonality on the disease
dynamics.
 
Published June 5, 2015 1:58 PM - Last modified June 5, 2015 1:58 PM