| Literature DB >> 28637916 |
Xavier Didelot1, Lilith K Whittles2, Ian Hall3.
Abstract
Bubonic plague has caused three deadly pandemics in human history: from the mid-sixth to mid-eighth century, from the mid-fourteenth to the mid-eighteenth century and from the end of the nineteenth until the mid-twentieth century. Between the second and the third pandemics, plague was causing sporadic outbreaks in only a few countries in the Middle East, including Egypt. Little is known about this historical phase of plague, even though it represents the temporal, geographical and phylogenetic transition between the second and third pandemics. Here we analysed in detail an outbreak of plague that took place in Cairo in 1801, and for which epidemiological data are uniquely available thanks to the presence of medical officers accompanying the Napoleonic expedition into Egypt at that time. We propose a new stochastic model describing how bubonic plague outbreaks unfold in both rat and human populations, and perform Bayesian inference under this model using a particle Markov chain Monte Carlo. Rat carcasses were estimated to be infectious for approximately 4 days after death, which is in good agreement with local observations on the survival of infectious rat fleas. The estimated transmission rate between rats implies a basic reproduction number R0 of approximately 3, causing the collapse of the rat population in approximately 100 days. Simultaneously, the force of infection exerted by each infected rat carcass onto the human population increases progressively by more than an order of magnitude. We also considered human-to-human transmission via pneumonic plague or human specific vectors, but found this route to account for only a small fraction of cases and to be significantly below the threshold required to sustain an outbreak.Entities:
Keywords: Bayesian analysis; bubonic plague; infectious disease model; palaeoepidemiology
Mesh:
Year: 2017 PMID: 28637916 PMCID: PMC5493801 DOI: 10.1098/rsif.2017.0160
Source DB: PubMed Journal: J R Soc Interface ISSN: 1742-5662 Impact factor: 4.118
States of the epidemiological compartmental model.
| rat states | |
|---|---|
| number of susceptible rats | |
| number of infected rats | |
| number of infectious rat carcasses | |
| human states | |
| number of susceptible humans | |
| number of infected humans | |
| number of dead humans |
Notations and parameters used in the epidemiological model.
| rat parameters | ||
|---|---|---|
| number of live rats | ||
| initial size of rat population | 250 000 | |
| proportion of rats initially infected | estimated | |
| transmission rate from rat carcasses to susceptible rats | estimated | |
| rat carcass infectivity range | estimated | |
| death rate of infected rats | 1/18 per day | |
| rate of loss of infectiousness of rat carcasses | estimated | |
| human parameters | ||
| initial human population size | 250 000 | |
| human non-plague death rate | estimated | |
| human birth rate | ||
| transmission rate from rat carcasses to susceptible humans | estimated | |
| interhuman transmission rate | estimated | |
| rate of death of infected humans | 1/18 per day | |
| probability of human survival from plague | 0.1 |
Figure 1.Daily reported number of deaths among men, women and children living in Cairo at the time of the French expedition. (Online version in colour.)
Figure 2.Compartmental model used for analysis. The three rat states are shown at the top and the three human states are shown at the bottom. Solid arrows represent probabilistic flow from one state to another, with rate indicated in the labels directly above. Dotted arrows represent the forces of infection exerted by infectious rat carcasses and infectious humans.
Figure 3.Posterior distributions of the seven estimated parameters, based on four separate pMCMC runs shown in four different colours. (Online version in colour.)
Figure 4.Scatter plots illustrating the relationships between all pairs of estimated parameters. A red background indicates a correlation higher than 0.7, a yellow background indicates a correlation between 0.3 and 0.7 and a white background indicates a correlation lower than 0.3. The scatter plots are based on a thousand samples from the posterior distribution. (Online version in colour.)
Figure 5.Simulation of the model using 1000 values from the posterior sample. Solid lines indicate the mean value across the 1000 simulations, while the dotted lines indicate the range. (Online version in colour.)