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Human ectoparasites and the spread of plague in Europe during the Second Pandemic


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Significance Plague is infamous as the cause of the Black Death (1347–1353) and later Second Pandemic (14th to 19th centuries CE), when devastating epidemics occurred throughout Europe, the Middle East, and North Africa. Despite the historical significance of the disease, the mechanisms underlying the spread of plague in Europe are poorly understood. While it is commonly assumed that rats and their fleas spread plague during the Second Pandemic, there is little historical and archaeological support for such a claim. Here, we show that human ectoparasites, like body lice and human fleas, might be more likely than rats to have caused the rapidly developing epidemics in pre-Industrial Europe. Such an alternative transmission route explains many of the notable epidemiological differences between historical and modern plague epidemics.
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Human ectoparasites and the spread of plague in
Europe during the Second Pandemic
Katharine R. Dean
, Fabienne Krauer
, Lars Walløe
, Ole Christian Lingjærde
, Barbara Bramanti
Nils Chr. Stenseth
, and Boris V. Schmid
Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, N-0316 Oslo, Norway;
Department of Physiology,
Institute of Basic Medical Sciences, University of Oslo, N-0317 Oslo, Norway;
Department of Computer Science, University of Oslo, N-0316 Oslo, Norway;
Department of Biomedical and Specialty Surgical Sciences, Faculty of Medicine, Pharmacy and Prevention, University of Ferrara, 35-441221
Ferrara, Italy
Contributed by Nils Chr. Stenseth, December 4, 2017 (sent for review September 4, 2017; reviewed by Xavier Didelot and Kenneth L. Gage)
Plague, caused by the bacterium Yersinia pestis, can spread through
human populations by multiple transmission pathways. Today, most
human plague cases are bubonic, caused by spillover of infected fleas
from rodent epizootics, or pneumonic, caused by inhalation of infec-
tious droplets. However, little is known about the historical spread of
plague in Europe during the Second Pandemic (1419th centuries),
including the Black Death, which led to high mortality and recurrent
epidemics for hundreds of years. Several studies have suggested that
human ectoparasite vectors, such as human fleas (Pulex irritans)or
body lice (Pediculus humanus humanus), caused the rapidly spreading
epidemics. Here, we describe a compartmental model for plague
transmission by a human ectoparasite vector. Using Bayesian infer-
ence, we found that this model fits mortality curves from nine out-
breaks in Europe better than models for pneumonic or rodent
transmission. Our results support that human ectoparasites were pri-
mary vectors for plague during the Second Pandemic, including the
Black Death (13461353), ultimately challenging the assumption that
plague in Europe was predominantly spread by rats.
Yersinia pestis
Black Death
SIR modeling
Bayesian analysis
Carlo Markov chain
Plague, caused by the bacterium Yersinia pestis, has been exten-
sively studied due to its modern and historical significance. In
the past, plague has famously caused at least three pandemics in
human history: the First Pandemic beginning with the Justinianic
Plague (6th to 8th centuries), the Second Pandemic beginning with
the Black Death(14thto19thcenturies),andtheThirdPandemic
(beginning in the 19th century) (1). Today, plague persists primarily
in rodent reservoirs in Asia, Africa, and the Americas, where it
poses a recurrent threat to nearby human settlements (2).
The most common forms of plague infection are bubonic and
pneumonic (2). Bubonic plague occurs when bacteria enter the
skin, usually from the bite of an infected flea vector. The bacteria
are then transported to the lymph nodes, causing characteristic
swelling, or buboes.Bubonic plague is typically transmitted to
humans from wild or commensal rodents (3), but transmission
between people is also thought to occur by human ectoparasites,
such as human fleas (Pulex irritans) or body lice (Pediculus
humanus humanus) (4). Primary pneumonic plague occurs when
aerosolized bacteria enter and infect the lungs. Pneumonic plague
can also arise as a complication of bubonic or septicemic infections
(2), known as secondary pneumonic plague. Individuals with
pneumonic plague can transmit the disease through the respiratory
route, although outbreaks of pneumonic plague are typically small
because infected persons die rapidly without treatment (5). Septi-
cemic plague occurs when bacteria infect the bloodstream, com-
monly from a primary pneumonic or bubonic infection (2).
A central focus of historical plague research has been to un-
derstand the spread and persistence of plague in Europe. Little is
known about the transmission of plague in Europe, the Middle
East, and North Africa during the Second Pandemic, including
the Black Death, when the disease killed an estimated one-third
of the population. Many studies (4, 6, 7) have suggested that human
ectoparasites, like human fleas and body lice, were more likely than
commensal rats to have caused the rapidly spreading epidemics.
Proponents of the human ectoparasite hypothesisargue that
plague epidemics during the Second Pandemic differ from the rat-
associated epidemics that occurred later, during the Third Pan-
demic. Specifically, the geographic spread and total mortality of the
Black Death far exceeds that of modern plague epidemics (8).
While contemporaneous accounts of symptoms during the Second
Pandemic are consistent with thoseofplague(7),therearenode-
scriptions of rat epizootics, or rat falls,that often precede epi-
demics in the Third Pandemic (79). Some have noted that the
climate of northern Europe could not have fostered the widespread
distribution of Rattus rattus (10), a claim that is supported by a
scarcity of rats in the archaeological record (6). Finally, epidemio-
logical characteristics of plague in Europe, such as a high rate of
household transmission (11), are suggestive of a more direct trans-
mission route (12).
Despite support for human ectoparasite transmission, it has
been difficult to assess their historical contribution because their
role in modern plague epidemics appears to be relatively minor.
Today, human ectoparasite diseases have declined in most de-
veloped countries, but they are still associated with poverty and
unhygienic conditions (13). In the past, human ectoparasites
Plague is infamous as the cause of the Black Death (13471353)
and later Second Pandemic (14th to 19th centuries CE), when
devastating epidemics occurred throughout Europe, the Middle
East, and North Africa. Despite the historical significance of the
disease, the mechanisms underlying the spread of plague in
Europe are poorly understood. While it is commonly assumed
that rats and their fleas spread plague during the Second
Pandemic, there is little historical and archaeological support
for such a claim. Here, we show that human ectoparasites, like
body lice and human fleas, might be more likely than rats to
have caused the rapidly developing epidemics in pre-Industrial
Europe. Such an alternative transmission route explains many
of the notable epidemiological differences between historical
and modern plague epidemics.
Author contributions: K.R.D., N.C.S., and B.V.S. designed research; K.R.D. performed re-
search; K.R.D, F.K., and B.V.S. analyzed data; and K.R.D., F.K., L.W., O.C.L., B.B., N.C.S., and
B.V.S. wrote the paper.
Reviewers: X.D., Imperial College London; and K.L.G., Centers for Disease Control
and Prevention.
The authors declare no conflict of interest.
This open access article is distributed under Creative Commons Attribution-NonCommercial-
NoDeriv atives L icense 4.0 ( CC BY-NC- ND).
To whom correspondence may be addressed. Email:, n.c.stenseth@, or
This article contains supporting information online at
1073/pnas.1715640115/-/DCSupplemental. PNAS Early Edition
have been efficient vectors for diseases such as epidemic typhus
(14) and relapsing fever (15). In 1941, plague-infected body lice
and human fleas were found on septicemic patients during an
outbreak in Morocco (16), indicating that humans can transmit
the disease to lice and human fleas. In addition, recent experi-
mental studies have demonstrated that body lice can transmit the
bacteria to naive rabbits (4, 1719). However, the transmission
from body lice and human fleas to humans has not yet been
documented, and thus the importance of human ectoparasite
transmission in current and historic settings remains an open
question. Our theoretical analysis demonstrates that human ec-
toparasites may indeed play such a role.
Mathematical modeling can provide strong insight into mecha-
nisms of plague transmission for past epidemics. Previous epide-
miological models of plague during the Second Pandemic are
focused mainly on modeling the spread of the disease by commensal
rats during a single outbreak (20, 21). In this study, we developed a
susceptibleinfectiousrecovered (SIR) model for plague trans-
mission with a human ectoparasite vector and compared it to
models for pneumonic and ratflea transmission. We applied these
models to nine outbreaks during the Second Pandemic, to gain a
broad understanding of the transmission dynamics of plague in
European epidemics. We identified the best-fitting model for each
outbreak and estimated the basic reproduction number, R
Historical Data. We used data on the daily and weekly disease-induced mortality
for nine plague outbreaks during the Second Pandemic (Table 1). These data
were publicly available in secondary sources including published articles, books,
and government reports. We digitized the epidemic data from printed tables
and graphs, using the entire duration of each outbreak, apart from Eyam,
which had two mortality peaks. The deterministic models we used cannot ac-
count for the stochasticity of infectious disease processes during the early phase
of an epidemic; thus, for the outbreak in Eyam, we removed the first 279 data
points and considered only the second, larger epidemic peak. To validate the
models for pneumonic and rat-associated plague epidemics, we used three
additional mortality curves from epidemics with known transmission routes
during the Third Pandemic (Table S1).
Parameters. The parameter values and initial conditions used in the models
are shown in Table 2 and Table S2. Fixed values were taken from field, ex-
perimental, or epidemiological case studies when available. Unobservable
parameters were estimated using Bayesian inference.
Table 1. Summary of the Second Pandemic mortality data
Location Date (MM/YYYY) Population Recorded mortality Refs.
Givry, France 07/134811/1348 1,500 636 22
Florence, Italy 05/140011/1400 60,000 10,215 23
Barcelona, Spain 04/149009/1490 25,000 3,576 24, 25
London, England 06/156301/1564 80,000 16,886 26
Eyam, England 06/166611/1666 350 197 26
Gdansk, Poland 03/170912/1709 50,000 23,496 27
Stockholm, Sweden 08/171002/1711 55,000 12,252 27
Moscow, Russia 07/177112/1771 300,000 53,642 28
Island of Malta, Malta 04/181311/1813 97,000 4,487 29
The present-day location, date (month/year), preplague population size, and recorded plague deaths, for nine
plague outbreaks during the Second Pandemic.
Table 2. Parameters for three SIR models of plague transmission
Parameter Value Definition Refs.
βlow U(0.001, 0.05) Transmission rate for bubonic plague from mildly infectious humans to body lice
βhigh U(0.001, 1) Transmission rate for bubonic plague from highly infectious humans to body lice
βpU(0.001, 1) Transmission rate for pneumonic plague
βhU(0.001, 0.2) Transmission rate for bubonic plague from rat fleas to humans
σb18.0 (d) Average low infectious period for bubonic plague
γb12.0 (d) Average high infectious period for bubonic plague
γp12.5 (d) Average infectious period for pneumonic plague 5
γh110.0 (d) Average duration of infection for bubonic plague 30
gh0.4 Probability of recovery from bubonic plague 3
Lice (P. humanus humanus)
rl0.11 (per d) Natural lice growth rate 31
Kl15.0 (per person) Lice index at carrying capacity 32, 33
βl0.05 Transmission rate for bubonic plague from body lice to humans
γl13.0 (d) Average infectious period for bubonic plague 17
Rats (R. rattus)
βrU(0.001, 1) Transmission rate for bubonic plague from rat fleas to rats
γr15.2 (d) Average infectious period for bubonic plague 34
gr0.1 Probability of recovery from bubonic plague 34
Fleas (X. cheopis)
rf0.0084 (per d) Natural flea growth rate 35, 36
Kf6.0 Average number of fleas at carrying capacity 37, 38
df15.0 (d) Death rate of fleas 39
a3.0/Srð0ÞSearching efficiency 35, 36
Single numbers are fixed values and distributions (U=uniform) are priors.
| Dean et al.
HumanEctoparasite Model. The transmission of bubonic plague by a human
ectoparasite vector, such as human fleas or body lice, is modeled by seven
differential equations:
dt =βl
dt =βl
dt =ð1ghÞσbIlow γbIhigh,
dt =ghσbIlow,
dt =γbIhigh,
dt =rlSl1Nl
KlβlowIlow +βhigh IhighSl
dt =βlowIlow +βhigh Ihigh Sl
The five compartments for humans that are functions of time t: susceptible
(Sh), infectious with mild bacteremia ðIlow Þ, infectious with high bacteremia
ðIhighÞ, recovered ðRhÞ, and dead ðDhÞ. The total living population is given by
Nh=Sh+Ilow +Ihigh +Rh. The transmission of plague from vectors to humans
occurs at rate βl. The model assumes that humans are mildly infectious for an
average of 8 d (σb1), and transmission is unlikely at rate βlow. Humans with
mild bacteremia may recover at rate gh, which is around 40% for untreated
bubonic plague. Experimental studies have shown that fleas must feed
on hosts with high levels of bacteremia for reliable transmission (40).
Therefore, the model assumes that moribund humans transmit plague at a
high rate to vectors βhigh for an average of 2 d (γb1). Given the short du-
ration of the outbreaks, we did not model natural births and deaths in the
human population.
Human ectoparasite vectors are modeled in two compartments (Sl,Il). The
susceptible vector population grows at the intrinsic growth rate rl. The
growth of the vector population is limited by the carrying capacity Kl, which
is the product of the parasite index and the number of human hosts Nh.
Modern studies show that the rate of body louse infestation and abundance
in affected human populations ranges from 10.5 to 67.7 lice on average per
person (33, 41).
There are a limited number of studies that evaluate human fleas and body
lice as vectors for plague (1719). These studies have shown both vectors
have similar transmission cycles for Y. pestis, and this makes it difficult to
distinguish between the two species with either model structure or pa-
rameter values (1719). Our model uses parameters specific to body lice;
however, the ranges for the lice and flea parameters overlap. The duration
of infection γl1has been shown experimentally for both species, and is on
average 4.5 d for human fleas and 3 d for body lice (1719). The model as-
sumes that infected human fleas and body lice do not recover. The trans-
mission of plague by human fleas is hypothesized to occur through early
phase transmission, an alternative to blocked transmission observed in rat fleas
(Xenopsylla cheopis) that does not require a lengthy extrinsic incubation
period (42).
Pneumonic Plague Model. The direct human-to-human transmission of plague
is modeled by three differential equations:
dt =βp
dt =βp
dt =γpIh.
There are three compartments for humans (Sh,Ih,Dh) and the total human
population is Nh=Sh+Ih. There is no compartment for recovered individuals
because the case fatality rate of untreated pneumonic plague is close to
100% (43). The human-to-human transmission of pneumonic plague occurs
at rate βp. The disease-induced mortality occurs at rate γpper day and is
equal to the inverse of the infectious period, which is a mean of 2.5 d for
pneumonic plague (5).
RatFlea Model. Based on a metapopulation model for bubonic plague by
Keeling and Gilligan (35, 36), the transmission of plague in a rodent
epizootic, and the spillover to humans is modeled by 10 differential
dt =βr
dt =βr
dt =grγrIr,
dt =ð1grÞγrIr,
dt =rfH1H
dt =ð1grÞγrIrHdfF,
dt =βh
dt =βh
dt =ghγhIh,
dt =ð1ghÞγhIh.
There are four compartments for rats (Sr,Ir,Rr,Dr)andthetotalrat
population is Nr=Sr+Ir+Rr. As epidemics within the rat population can
only occur when a large proportion of the rats are susceptible to the
disease, we assumed an initial black rat (Rattus rattus) population that
was entirely susceptible. Although the expected ratio of urban rats to
humans is about 1 rat to every 5 people (44), we allowed the prior in the
model to have a maximum ratio of 1:1 rats to humans. Increasing the rat
population in medieval cities allowed the simulated rat-borne plague out-
breaks to more easily reach the mortality levels observed in humans during the
Second Pandemic.
Rat fleas (X. cheopis) are modeled as the average number of fleas per rat,
H, and the number of free infectious fleas, F. The flea population has a
natural growth rate, rf, that is limited by the carrying capacity Kf.Weas-
sumed that the flea population is limited by the number of rat hosts, be-
cause X. cheopis does not reproduce on humans (45). Plague is transmitted
to rats at rate βrby free infectious fleas searching for a host with searching
efficiency a. We further assumed that fleas can transmit plague in the early
phase (42). Rats die at a rate equal to the inverse of the infectious period
γr1, or recover with probability gr. When an infected rat dies, a number of
free infectious fleas are released into the environment, depending on the
average number of fleas per rat. Free infectious fleas die at rate df. The
model assumes that plague is a rodent disease and that human cases are a
consequence of mortality in the rat population. Therefore, susceptible hu-
mans Shbecome infected by free infectious fleas at rate βh. Humans remain
infected for an average of 10 d (γh1), at which point they either recover at
rate ghor die.
In the model by Keeling and Gilligan (35, 36), it is assumed that the force
of infection from free infectious fleas is divided exclusively between rats and
humans. However, the authors note that the true force of infection to hu-
mans is less because not every flea will find and infect a human (35). For our
model, we sought to establish a range for βhthat would accurately lower the
force of infection to humans. To establish this range, we fitted the model to
observed mortality for both rats and humans in Hong Kong in 1903 (Fig. S1)
and found that the mean estimate for βhwas 0.1 (Table S3). Using simula-
tions, we found that βhshould be less than 0.2 to preserve the characteristic
delay and higher peak mortality of the rat epizootic compared with the
human epidemic. Based on these observations, we constrained the prior for
Dean et al. PNAS Early Edition
the transmission rate to humans βhto 0.00.2, which enabled us to use this
model for outbreaks where only human mortality was available.
Bayesian Inference and Markov Chain Monte Carlo. We fitted the deterministic
models to the observed data using Bayesian inference and estimated un-
observable parameters of interest. The models had a time-step of 1 d and
were fitted to daily mortality or weekly mortality. Denoting the set of model
parameters as Θ=fS0,β,...
g, the probability pof the observed data D1...m
given Θis calculated as the product of a series of Poisson random variables
with mean λTequal to the human mortality in the model at times T1...m:
The parameters that we fitted were the transmission rates for each model
(βlow,βhigh,βp,βr,βh) and the size of the initial primary host population that
was at risk [Sð0Þh,Sð0Þr] or infected [Ið0Þh,Ið0Þr]. We assumed uniformly
distributed priors and obtained posterior distributions using Markov chain
Monte Carlo (MCMC) simulations with an adaptive MetropolisHastings al-
gorithm implemented in PyMC2 (46) (for examples of the implementation,
see We ran the MCMC simulations for
180,000 iterations with a burn-in of 80,000 iterations and a thinning of 10.
We assessed convergence for each model by running three independent
MCMC chains and verifying that the GelmanRubin statistic (47) was
<1.05 for each parameter. We performed model comparison using the
Bayesian information criterion (BIC) from the maximum-likelihood esti-
mates of the model parameters (48). The model with the lowest BIC value
was the unique preferred model if the second-best model had a BIC value
of at least 10 larger (49).
Estimation of the Basic Reproduction Number. We estimated the basic re-
production number in each model for the primary host using the next-
generation matrix method (50).
Reporting Error. We conducted the analysis again considering different levels
of underreporting (10%, 25%, and 50%) for each outbreak. To do so, we
incorporated a constant probability of reporting into the likelihood func tion.
Model Fit and Selection. We used Bayesian MCMC and the
mortality data to fit the three transmission models: human ec-
toparasite plague (EP), pneumonic plague (PP), and rat-borne
plague (RP) (Fig. 1). The posterior means and 95% credible
intervals for the fitted parameters in each model are given in
Table S3. Fig. 1 shows the fit of each model to the observed
mortality. For the smallest outbreaks, Eyam and Givry, it is
difficult to visually distinguish between the models because the
credible intervals are overlapping. In general, the human ecto-
parasite model fit the pattern of the observed data for the Sec-
ond Pandemic outbreaks. However, the model could not account
for irregularities in the observed mortality from Malta and
Moscow, which have two peaks. For the pneumonic plague
model, the mortality curve is right skewed compared with the
observed mortality. Mortality in the rat model tended to grow
slowly while plague spread through the rat population, and
peaked higher than the observed mortality.
Fig. 1. Fit of three models of plague transmission to mortality during Second Pandemic outbreaks. The observed human mortality data (black dots) and the
fit (mean and 95% credible interval) of three models for plague transmission [human ectoparasite (red), pneumonic (blue), and ratflea (green)] for nine
plague outbreaks: (A) Givry, France (1348), (B) Florence, Italy (1400), (C) Barcelona, Spain (1490), (D) London, England (1563), (E) Eyam, England (1665),
(F) Gdansk, Poland (1709), (G) Stockholm, Sweden (1710), (H) Moscow, Russia (1772), and (I) Island of Malta, Malta (1813).
| Dean et al.
We compared the three competing models using the BIC. Our
results (Table 3) show that the human ectoparasite model had the
lowest BIC value for all outbreaks, except Eyam and Givry. For the
remaining outbreaks, the difference in BIC for the human ecto-
parasite model and the other candidate models was greater than
10, which provides strong evidence against the pneumonic and rat
flea models (50). For Eyam and Givry, the difference between the
human ectoparasite model and another model was less than 10;
therefore, neither model could be excluded.
To verify our model comparison method, we fitted the models to
three additional Third Pandemic outbreaks with known transmission
routes (Fig. S2). We found that the model with the lowest BIC
matched the known modes of transmission for the outbreaks in
Hong Kong (rats) and Harbin (pneumonic) (Table S5). However, we
could not distinguish between two of the models for a small outbreak
of rat-associated plague in Sydney, suggesting together with the re-
sults from Eyam and Givry, that our model comparison method is
better suited for sufficiently large outbreaks (>750 deaths).
Basic Reproduction Number R
.By definition, the basic reproduction
number, R
, is the average number of secondary cases produced by
a primary case, given an entirely susceptible population. In practice,
is an important threshold for disease invasion. For each of the
from the posterior estimates of the
fitted parameters (Table 3). For all of the models, R
was greater
than 1, which is above the threshold for disease invasion. Using the
human ectoparasite model, the estimated R
was 1.481.91 for all
pre-Industrial outbreaks.
Reporting Error. We considered the impact of different levels of
constant underreporting of deaths throughout the epidemics on
model selection (Table S6). We found that underreporting of
10% and 25% did not change the results of the model selection;
under these conditions, the human ectoparasite model was the
best fit for all outbreaks in Europe except Eyam and Givry.
Underreporting of 50% changed the best-fitting models of
Gdansk and Givry to pneumonic plague. For these cities, 50%
underreporting resulted in the death of more than 90% of the
population, giving preference to a pneumonic plague model
where all infected individuals die from plague.
Our study supports human ectoparasite transmission of plague
during the Second Pandemic, including the Black Death. Using
recent experimental data on human fleas and body lice as plague
vectors, we have developed a compartmental model that cap-
tures the dynamics of human ectoparasite transmission. We have
shown that, in seven out of nine localities, the human ectopar-
asite model was the preferred model to explain the pattern of
plague mortality during an outbreak, rather than models of
pneumonic and ratflea plague transmission (Table 3). The small
size of the plague outbreaks in Eyam and Givry made it difficult
to distinguish transmission routes based on mortality data. For
Eyam, both the human ectoparasite model and the pneumonic
model produced a similar quality fit for the observed mortality.
This agrees with a previous modeling study of Eyam (1665),
which found that the dominant mode of transmission was an
unspecified route of human-to-human transmission, rather than
rodent transmission (11). Overall, our results suggest that plague
transmission in European epidemics occurred predominantly through
human ectoparasites, rather than commensal rat or pneumonic
The strength of our study is that we compared three plague
transmission models, each representing a known or hypothetical
mode of plague transmission, for nine plague outbreaks across the
spatial and temporal extent of the Second Pandemic in Europe.
Our study thus provides a more general understanding of plague
epidemics in Europe than previous modeling studies that focus on
single outbreaks, or single transmission routes (11, 20, 35, 36, 51).
However, since we considered nine outbreaks over several centu-
ries, we were limited to using simple models that could be applied
systematically. Consequently, these models did not account for local
conditions that can affect disease transmission, like war, famine,
immunity, and public health interventions. Additionally, we did not
model mixed transmission routes, and this makes it difficult to fully
assess the contribution of pneumonic plague, which commonly
occurs during bubonic outbreaks (52). Secondary pneumonic pla-
gue develops in an estimated 20% of bubonic cases, and this creates
potential for primary pneumonic spread, even if it is not the
dominant transmission route (52). Finally, we do not consider
events leading up to the introduction of the disease and our results
cannot be extended to plague transmission between localities,
which may have involved different transmission mechanisms.
Recent studies have found human ectoparasites during plague
outbreaks in the Democratic Republic of Congo (41), Tanzania
(53), and Madagascar (54), but their role in these outbreaks is
not clear. In the absence of modern studies on human ectopar-
asites as vectors for plague, our results yield inferences about the
conditions necessary to produce outbreaks driven by human ec-
toparasite transmission. Our estimated values for R
using the
human ectoparasite model were consistently between 1.5 and
1.9 for all nine cities. The main components of R
in the human
ectoparasite model are the ectoparasite index and the trans-
mission rates (βl,βlow,βhigh). From the fitted models, we obtained
estimates for the transmission rates (βlow,βhigh) from humans to
ectoparasites during the early and late stages of plague infection.
Table 3. Comparison of transmission models and posterior
estimates for the basic reproduction number for different plague
models and outbreaks
Location Model BIC ΔBIC R
Givry (1348) EP 1,287 01.82 [1.82, 1.82]
PP 1,333 46 1.10 [1.10, 1.10]
RP 1,287 01.61 [1.61, 1.61]
Florence (1400) EP 2,662 01.76 [1.76, 1.76]
PP 4,569 1,907 1.09 [1.09, 1.09]
RP 10,157 7,495 2.03 [2.03, 2.03]
Barcelona (1490) EP 1,942 01.91 [1.91, 1.91]
PP 2,410 468 1.09 [1.09, 1.09]
RP 3,392 1,450 2.04 [2.04, 2.04]
London (1563) EP 1,585 01.64 [1.64, 1.64]
PP 4,647 3,062 1.06 [1.06, 1.06]
RP 3,882 2,297 1.52 [1.52, 1.52]
Eyam (1666) EP 1,171 01.48 [1.48, 1.49]
PP 1,174 31.04 [1.04, 1.04]
RP 1,205 34 1.24 [1.24, 1.24]
Gdansk (1709) EP 797 01.64 [1.64, 1.64]
PP 3,841 3,044 1.06 [1.06, 1.06]
RP 2,212 1,415 1.46 [1.46, 1.46]
Stockholm (1710) EP 726 01.75 [1.75, 1.75]
PP 2,118 1,392 1.06 [1.06, 1.06]
RP 1,062 336 1.30 [1.30, 1.30]
Moscow (1771) EP 3,912 01.79 [1.79, 1.79]
PP 6,789 2,877 1.09 [1.09, 1.09]
RP 15,946 12,034 1.76 [1.76, 1.76]
Malta (1813) EP 2,761 01.57 [1.57, 1.57]
PP 3,580 819 1.06 [1.06, 1.06]
RP 6,445 3,684 1.79 [1.79, 1.79]
The models are designated as human ectoparasite (EP), primary pneumonic
plague (PP), and ratflea (RP). Values in bold represent the best-fitting models
that were within 10 points of the lowest BIC. The R
(mean [95% confidence
interval]) was estimated using the next-generation matrix method.
Dean et al. PNAS Early Edition
We found that the majority of ectoparasite infections occurred
during the period of high infectivity in humans, consistent with
experimental evidence (40). Inferences like these not only im-
prove our understanding of human ectoparasites as plague vec-
tors in the past but also have important implications for limiting
the size of plague outbreaks today.
Many studies have sought to clarify the mechanisms un-
derlying the spread and maintenance of plague during the Sec-
ond Pandemic. Mathematical modeling is an important tool to
examine the role of different transmission mechanisms, partic-
ularly in the absence of definitive experimental, historical, and
archaeological information. Here, we demonstrate that human
ectoparasites appear to have been the dominant transmission
mode for plague during the Second Pandemic. This alternative
mode of transmission could account for many of the epidemio-
logical differences between the Second Pandemic and those
caused by rats during the Third Pandemic. Plague is undeniably a
disease of significant scientific, historic, and public interest, and
is still present in many parts of the world today. It is therefore
crucial that we understand the full spectrum of capabilities that
this versatile, pandemic disease has exhibited in the past.
ACKNOWLEDGMENTS. We thank W. Ryan Easterday and Jukka Corander for
their valuable comments. We acknowledge funding from the European Re-
search Council under the FP7-IDEAS-ERC Program (Grant 324249). We also ac-
knowledge funding from the Centre for Ecological and Evolutionary Synthesis.
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| Dean et al.
Supporting Information
Dean et al. 10.1073/pnas.1715640115
Fig. S1. Fit of the ratflea model to observed rodent and human mortality during the 1903 plague outbreak in Hong Kong. The observed rat mortality (black
dots), the observed human mortality (green dots), and fit (mean and 95% credible interval) of the rat model for plague transmission to both the rat (black) and
human (green) mortality. The mortality peak for humans from the model is delayed compared with the observed data. However, the model captures the
dynamics of the rat mortality and the relationship between the epizootic and the epidemic well by showing the characteristic higher rat mortality and the
delay in the onset of the epidemic in humans.
Dean et al. 1of5
Fig. S2. Fit of the pneumonic and ratflea models of plague transmission to mortality during Third Pandemic outbreaks. The observed human mortality data
(black dots) for plague outbreaks and the fit (mean and 95% credible interval) of the relevant model for plague transmission in each plague outbreak:
pneumonic (blue) and ratflea (green). Both the ratflea model of plague transmission and the pneumonic plague transmission are well capable of fitting
observed human mortality patterns for plague outbreaks that these models describe.
Table S1. Summary of the Third Pandemic mortality data
Location Date, MM/YYYY Population Recorded deaths Transmission mode Ref.
Sydney, Australia 02/190008/1900 400,000 103 Ratflea 1
Hong Kong, China 01/190312/1903 250,000 1,308 Ratflea 2
Harbin (Fuchiatien), China 12/191002/1911 25,000 3,223 Pneumonic 3
The present-day location, dates (month/year), preplague population size, and recorded plague deaths, and
known transmission mode for three plague outbreaks during the Third Pandemic.
1. Cumpston JHL, McCallum F (1926) The History of Plague in Australia, 19001925 (H. J. Green Govt Printer for Commonwealth of Australia Dept Health, Melbourne).
2. Hunter W (1904) A Research into Epidemic and Epizootic Plague (Noronha and Company, Hong Kong).
3. Anonymous (1912) Report of the International Plague Conference Held at Mukden, April, 1911, ed Strong RP (Bureau of Printing, Manila, Philippines).
Table S2. Initial conditions for three SIR models of plague transmission
Parameter Value Definition
Human ectoparasite model
Shð0ÞU(0.001, 1)*population size Initial susceptible humans
Ilowð0ÞU(1, 10*Dhð0Þ) Initial infected (low) humans
Ihighð0Þ2*Dhð0ÞInitial infected (high) humans
Rhð0Þ0 Initial recovered humans
Dhð0ÞObserved deaths at T=0 Initial dead humans
Pneumonic plague model
Shð0ÞU(0.001,1)*population size Initial susceptible humans
Ihð0ÞU(1, 10*Dhð0Þ) Initial infected humans
Dhð0ÞObserved deaths at T=0 Initial dead humans
Ratflea model
Srð0ÞU(0.001, 1)*population size Initial susceptible rats
Irð0ÞU(1, 15*Dhð0Þ) Initial infected rats
Rrð0Þ0 Initial recovered rats
Drð0Þ0 Initial dead rats
Shð0ÞSrð0ÞInitial susceptible humans
Ihð0Þ1.5*Dhð0ÞInitial infected humans
Rhð0Þ0 Initial recovered humans
Dhð0ÞObserved deaths at T=0 Initial dead humans
Hð0ÞKfInitial fleas on host
Fð0ÞKf*Dhð0ÞInitial free infected fleas
Single numbers are fixed values and distributions (U=uniform) are priors.
Dean et al. 2of5
Table S3. Initial parameter values and posterior estimates for the ratflea model fitted rat and
human mortality in Hong Kong
Parameter Parameter value/prior distribution
Posterior estimate, mean
[95% highest posterior density interval]
Ihð0Þ5.0 Fixed
Rhð0Þ0 Fixed
Dhð0ÞObserved deaths at T=0 Fixed
βhU(0.001, 1) 0.11 [0.10, 0.12]
Srð0ÞU(0.001, 1)*population size 0.018 [0.017, 0.018] * 250,000
Irð0ÞU(1, 23) 22.8 [22.6, 23]
Rrð0Þ0 Fixed
Drð0ÞObserved deaths at T=0 Fixed
βrU(0.001, 1) 0.053 [0.053, 0.053]
Single numbers are fixed values, and distributions (U=uniform) are priors.
Dean et al. 3of5
Table S4. Posterior means and 95% highest density posterior intervals for estimated parameters in three plague models for Second and
Third Pandemic outbreaks
Location Model Population at risk (proportion) Initial infected [Ilow ð0Þ,Ihð0Þ,Irð0Þ] Transmission rate ðβlow,βhigh ,βp,βr,βhÞ
Givry (1348) EP 0.75 [0.69, 0.81] 2.21 [2, 2.61] 0.04 [0.02, 0.05]
0.39 [0.32, 0.53]
PP 0.42 [0.38, 0.45] 1.85 [1.41, 2.32] 0.44 [0.43, 0.44]
RP 0.73 [0.64, 0.81] 28.81 [26.60, 29.99] 0.06 [0.06, 0.06]
0.19 [0.18, 0.2]
Florence (1400) EP 0.36 [0.35, 0.36] 79.65 [78.99, 80] 0.049 [0.04, 0.05]
0.32 [0.31, 0.38]
PP 0.17 [0.17, 0.17] 79.79 [79.39, 79.99] 0.42 [0.42, 0.42]
RP 0.19 [0.19, 0.19] 119.91 [119.76, 120.0] 0.084 [0.083, 0.085]
0.2 [0.199, 0.2]
Barcelona (1490) EP 0.28 [0.27, 0.28] 8.68 [7.54, 9.97] 0.032 [0.007, 0.05]
0.49 [0.35, 0.67]
PP 0.14 [0.13, 0.14] 9.90 [9.73, 10.0] 0.43 [0.43, 0.43]
RP 0.14 [0.13, 0.14] 14.95 [14.87, 15.0] 0.08 [0.08, 0.08]
0.2 [0.19, 0.2]
London (1563) EP 0.42 [0.41, 0.42] 32.45 [29.68, 35.62] 0.04 [0.04, 0.05]
0.27 [0.26, 0.28]
PP 0.21 [0.20, 0.21] 50.85 [48.81, 52.99] 0.43 [0.43, 0.43]
RP 0.30 [0.30, 0.31] 254.80 [254.43, 255] 0.06 [0.059, 0.06]
0.2 [0.2, 0.2]
Eyam (1666) EP 0.97 [0.92, 1.0] 3.76 [3, 4.97] 0.032 [0.01, 0.05]
0.32 [0.2, 0.5]
PP 0.56 [0.48, 0.63] 3.80 [3, 4.82] 0.41 [0.41, 0.42]
RP 0.96 [0.90, 1.0] 38.08 [29.53, 44.97] 0.04 [0.04, 0.05]
0.19 [0.18, 0.2]
Gdansk (1709) EP 0.93 [0.92, 0.94] 51.3 [49, 54.6] 0.049 [0.046, 0.05]
0.28 [0.26, 0.3]
PP 0.46 [0.46, 0.47] 79.11 [76.56, 81.95] 0.42 [0.42, 0.42]
RP 0.92 [0.90, 0.93] 734.48 [733.36, 735] 0.04 [0.04, 0.05]
0.2 [0.2, 0.2]
Stockholm (1710) EP 0.42 [0.41, 0.42] 159.63 [153.01, 168.35] 0.04 [0.03, 0.05]
0.33 [0.30, 0.38]
PP 0.22 [0.21, 0.22] 145.36 [139.14, 151.28] 0.42 [0.42, 0.42]
RP 0.36 [0.35, 0.36] 2,290.65 [2,282.25, 2,294.99] 0.069 [0.069, 0.069]
0.2 [0.2, 0.2]
Moscow (1771) EP 0.34 [0.34, 0.35] 157.41 [150.41, 164.44] 0.04 [0.04, 0.05]
0.34 [0.32, 0.39]
PP 0.17 [0.17, 0.18] 148.31 [144.46, 152.12] 0.43 [0.43, 0.43]
RP 0.20 [0.20, 0.21] 659.86 [659.57, 660.0] 0.069 [0.069, 0.069]
0.2 [0.2, 0.2]
Malta (1813) EP 0.09 [0.09, 0.09] 18.09 [16.47, 19.9] 0.04 [0.04, 0.05]
0.26 [0.23, 0.31]
PP 0.04 [0.04, 0.04] 9.96 [9.90, 10.0] 0.43 [0.43, 0.43]
RP 0.045 [0.044, 0.046] 14.98 [14.939, 15.0] 0.06 [0.06, 0.06]
0.2 [0.2, 0.2]
Sydney (1900) EP 0.49 [0.003, 0.95] 7.49 [5.48, 9.77] 0.024 [0.0, 0.04]
0.15 [0.0, 0.3]
PP 0.001 [0.0, 0.001] 1.46 [1, 2.06] 0.42 [0.41, 0.42]
RP 0.001 [0.0, 0.001] 13.559 [10.637, 15.0] 0.05 [0.04, 0.05]
0.18 [0.14, 0.2]
Hong Kong (1903) EP 0.011 [0.011, 0.012] 3.05 [3, 3.17] 0.048 [0.044, 0.05]
0.24 [0.22, 0.26]
PP 0.01 [0.01, 0.01] 2.88 [2.41, 3.35] 0.42 [0.42, 0.42]
RP 0.011 [0.009, 0.013] 36.66 [27.63, 44.99] 0.05 [ 0.05, 0.05]
0.16 [0.13, 0.2]
Harbin (1910) EP 0.02 [0.02, 0.021] 33.93 [27.09, 41.58] 0.03 [0.01, 0.05]
0.88 [0.76, 1.]
PP 0.12 [0.12, 0.13] 16.99 [14.9, 18.98] 0.48 [ 0.48, 0.48]
RP 0.11 [ 0.11, 0.11] 119.25 [117.66, 119.99] 0.14 [0.13, 0.14]
0.19 [0.19, 0.2]
Posterior estimates for initial conditions for different plague models and outbreaks. Models are designated as human ectoparasite (EP), primary pneumonic
plague (PP), and rat and ratflea (RP). Posterior estimates (mean [95% highest density posterior interval]) for the proportion of the initial population at risk, the
initial number of infected [Ið0Þ], and the transmission rate (β).
Dean et al. 4of5
Table S5. Comparison of transmission models and estimates for
the basic reproduction number for different plague models and
Third Pandemic outbreaks
Location Model BIC ΔBIC R
Sydney (1900) EP 235 46 0.86 [0.86, 0.87]
PP 196 71.05 [1.05,1.05]
RP 189 01.36 [1.36,1.36]
Hong Kong (1903) EP 611 107 1.52 [1.52, 1.52]
PP 900 396 1.06 [1.06,1.06]
RP 504 01.41 [1.41,1.41]
Harbin (1910) EP 851 31 2.98 [2.98, 2.98]
PP 820 01.21 [1.21,1.21]
RP 1,606 786 3.62 [3.62,3.62]
The models are designated as human ectoparasite (EP), primary pneu-
monic plague (PP), and rat and ratflea (RP). Values in bold represent the
best-fitting models that were within 10 points of the lowest BIC. The R
(mean [95% confidence interval]) was estimated for each model using the
next-generation matrix.
Table S6. Comparison of transmission models with different levels of underreporting
Location Model
10% underreporting 25% underreporting 50% underreporting
Givry (1348) EP 1,288 1,280 1,395
PP 1,333 1,333 1,331
RP 1,292 1,370 1,439
Florence (1400) EP 2,729 2,876 3,392
PP 4,668 4,928 5,877
RP 10,568 11,264 12,752
Barcelona (1490) EP 1,942 1,951 2,121
PP 2,418 2,453 2,610
RP 3,482 3,640 3,991
London (1563) EP 1,582 1,577 1,575
PP 4,630 4,629 4,629
RP 4,256 4,954 6,743
Eyam (1666) EP 1,176 1,175 1,243
PP 1,174 1,174 1,238
RP 1,210 1,228 1,304
Gdansk (1709) EP 825 1,803 No convergence
PP 3,817 3,817 3,817
RP 2,176 4,447 No convergence
Stockholm (1710) EP 718 709 688
PP 2,180 2,109 2,110
RP 1,238 1,612 2,759
Moscow (1771) EP 3,916 3,916 3,931
PP 6,790 6,790 6,790
RP 17,604 22,612 No convergence
Malta (1813) EP 2,760 2,775 2,864
PP 3,653 3,850 4,244
RP 6,632 6,953 7,656
The models are designated as human ectoparasite (EP), primary pneumonic plague (PP), and rat and ratflea
(RP). Values in bold represent the best-fitting models that were within 10 points of the lowest BIC.
Dean et al. 5of5
... Bubonic plague, thought to be the cause of a series of Bombay outbreaks that began in 1896 [79,80], is transmitted to humans through rat fleas [81], but transmission between humans also appears to occur via infected human fleas or body lice [82]. Pneumonic plague, by contrast, is transmitted by direct human-to-human transmission via respiratory droplets and can occur as complication of bubonic plague [83,84]. ...
... So, does our SIR model similarly succeed as a reduced form model but fail as a structural model of the Bombay plague outbreak? Several structural compartmental models of plague transmission have been tested, typically involving separate states and parameters for humans and vectors [78,[84][85][86]. In a rat-flea transmission model for bubonic plague, for example, the structural model contained a separate sub-epidemic module for rats with a distinct basic reproduction number for rat-to-rat transmission [86]. ...
... The copyright holder for this preprint this version posted March 20, 2023. ; doi: medRxiv preprint appeared to have the best fit to nine plague outbreaks during Europe's Second Pandemic from 1348 to 1813 [84]. Our minimalist SIR model has none of these structural features. ...
Full-text available
We describe a novel approach to recovering the underlying parameters of the SIR dynamic epidemic model from observed data on case incidence or deaths. We formulate a discrete-time approximation to the original continuous-time model and search for the parameter vector that minimizes the standard least squares criterion function. We show that the gradient vector and matrix of second-order derivatives of the criterion function with respect to the parameters adhere to their own systems of difference equations and thus can be exactly calculated iteratively. Applying our new approach, we estimate four-parameter SIR models on two types of datasets: (1) daily reported cases of COVID-19 during the SARS-CoV-2 Omicron/BA.1 surges of December 2021 - March 2022 in New York City and Los Angeles County; and (2) weekly deaths from a plague outbreak on the Isle of Bombay during December 1905 - July 1906, originally studied by Kermack and McKendrick in their now-classic 1927 paper. The estimated parameters from the COVID-19 data suggest a duration of persistent infectivity beyond that reported in small-scale clinical studies of mostly symptomatic subjects. The estimated parameters from the plague data suggest that the Bombay outbreak was in fact driven by pulmonic rather than bubonic plague.
... Questioning the importance of rodents and their ectoparasites during past Pandemics in Europe, our study (2) thus contrasts the main factors and processes of plague transmission known from the Third Pandemic in other continents, where wildlife plague reservoirs have been and continue to be essential. Our study also points to the possible importance of human ectoparasites in the interhuman transmission of bacteria (6). ...
... Recently, virulence attenuation of the plague bacterium (5) and the selection of a more robust innate immunity against Y. pestis (9) have been suggested as factors contributing to the end of the First and Second Pandemics in Europe (7). (ii) The evidence is accumulating for the importance of human-to-human transmission mediated by ectoparasites during plague outbreaks in Europe (6). Though the human flea (Pulex irritans) seems not suitable (10), there are other ectoparasites, such as lice, which may have played a critical role. ...
... As for the plague, in addition to the fourteenth century, which remains that with the greatest impact, there have been other periods of pandemic in other centuries. There was a second wave (Dean et al., 2018) and a third wave (Bramanti et al., 2019) as well, with the involvement of other large cities. In the nineteenth century, cholera decimated the populations of London, Paris, Hamburg, New York and Chicago (Florida et al., 2020). ...
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The chapter deals with the issue of globalization of cities and a distinction between them within a grid of emerging and developed countries and their subdivision into income levels. The thesis is that even within a globalization, urban infrastructure differs according to whether the concept of urbanization or urban consolidation is applied or as Brenner defined it at the beginning of this century for western cities: glocalization or interscalar of urban region. The urban infrastructure finds a different meaning or declination when referring to the greenfield phenomenon more consistent with rapid urbanization; or brownfield more connected with the urban consolidation of western cities. The term greenfield or brownfield infrastructure can also be coined, the latter more in keeping with western global cities. The content of the book focuses more on brownfields infrastructure.
... This collapse of the host-species barrier, inherent in vector-borne diseases, has proven catastrophic time and time again. Such predicaments apply mostly to pathogens moving from animals to humans, as were the cases of the plague in the Middle Ages (Dean et al, 2018), of Acquired Immunodeficiency Syndrome (AIDS) onward from the 1980s (Lovgren, 2003), the Mad Cow Disease in the late 1980s (Broussard, 2001) and, of course, the coronavirus disease-2019 in the current historical moment (Holmes et al, 2021), not to forget at least three other viral zoonoses in the 21st Century (Magouras et al, 2020). ...
The coronavirus disease-2019 (COVID-19) pandemic has raised the stakes for planetary health diagnostics. Because pandemics pose enormous burdens on biosurveillance and diagnostics, reduction of the logistical burdens of pandemics and ecological crises is essential. Moreover, the disruptive effects of catastrophic bioevents impact the supply chains in both highly populated urban centers and rural communities. One "upstream" focus of methodological innovation in biosurveillance is the footprint of Nucleic Acid Amplification Test (NAAT)-based assays. We report in this study a water-only DNA extraction, as an initial step in developing future protocols that may require few expendables, and with low environmental footprints, in terms of wet and solid laboratory waste. In the present work, boiling-hot distilled water was used as the main cell lysis agent for direct polymerase chain reactions (PCRs) on crude extracts. After evaluation (1) in blood and mouth swabs for human biomarker genotyping, and (2) in mouth swabs and plant tissue for generic bacterial or fungal detection, and using different combinations of extraction volume, mechanical assistance, and extract dilution, we found the method to be applicable in low-complexity samples, but not in high-complexity ones such as blood and plant tissue. In conclusion, this study examined the doability of a lean approach for template extraction in the case of NAAT-based diagnostics. Testing our approach with different biosamples, PCR settings, and instruments, including portable ones for COVID-19 or dispersed applications, warrant further research. Minimal resources analysis is a concept and practice, vital and timely for biosurveillance, integrative biology, and planetary health in the 21st century.
... Fleas are also the vector for the transmission of Yersinia pestis, the bacterial causal agent of plague. Traditionally, the Oriental rat flea (Xenopsylla cheopis) has been identified as the vector of transmission; however, recent investigations have underscored the potential of the human flea for the human-human transmission (Dean et al., 2018). ...
Parasitology of archaeological remains, known as archaeoparasitology, is an interdisciplinary field that combines parasitology and archaeological methods to investigate specific patterns of ancient parasite infection in relation to environment, diets, behavior, and disease (Reinhard, 1992a; Reinhard & Araujo, 2012; Mitchell, 2015). The multifaceted nature of the discipline is reflected in the wealth of materials analyzed (e.g., ancient feces, burials, or refuse structures, among others), the variety of methods used, and the diverse research applications. Evolution of parasites related to subsistence, pathology, pharmacology, or human-animal interactions are some of the subjects investigated. Since the beginning of the discipline in the early 20th century, there have been two bursts of interest in parasites derived from archaeological sites, and each began with exploration and innovation of methods. In the mid-20th century, research flourished in South America, North America, and Europe. Analytical methods were applied to coprolites, sediments, and mummies and were based on clinical and archaeological approaches. More recently, and especially after 2010, there was a second burst of interest associated with methodological innovation and critical evaluation. Methods for coprolite and mummy study have been critically evaluated in historical context (Camacho et al., 2018) and within sediments (Camacho et al., 2020), while comparative methods addressing taphonomy have been developed for labs with limited facilities (Romera Barbera et al., 2020). This chapter explores a range of methods used to recover and evaluate parasites in archaeological contexts as well as highlights ways in which the analysis of parasites provides insights into disease in the past.
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The pathogenic anaerobic bacteria Yersinia pestis (Y. pestis), which is well known as the plague causative agent, has the ability to escape or inhibit innate immune system responses, which can result in host death even before the activation of adaptive responses. Bites from infected fleas in nature transmit Y. pestis between mammalian hosts causing bubonic plague. It was recognized that a host’s ability to retain iron is essential in fighting invading pathogens. To proliferate during infection, Y. pestis, like most bacteria, has various iron transporters that enable it to acquire iron from its hosts. The siderophore-dependent iron transport system was found to be crucial for the pathogenesis of this bacterium. Siderophores are low-molecular-weight metabolites with a high affinity for Fe3+. These compounds are produced in the surrounding environment to chelate iron. The siderophore secreted by Y. pestis is yersiniabactin (Ybt). Another metallophore produced by this bacterium, yersinopine, is of the opine type and shows similarities with both staphylopine and pseudopaline produced by Staphylococcus aureus and Pseudomonas aeruginosa, respectively. This paper sheds light on the most important aspects of the two Y. pestis metallophores as well as aerobactin a siderophore no longer secreted by this bacterium due to frameshift mutation in its genome.
Parasites have been infecting humans throughout our evolution. When complex societies developed, the greater population density provided new opportunities for parasites to spread. In this interdisciplinary volume, the author brings his expertise in medicine, archaeology and history to explore the contribution of parasites in causing flourishing past civilizations to falter and decline. By using cutting edge methods, Mitchell presents the evidence for parasites that infected the peoples of key ancient civilizations across the world in order to understand their impact upon those populations. This new understanding of the archaeological and historical evidence for intestinal worms, ectoparasites, and protozoa shows how different cultures were burdened by contrasting types of diseases depending upon their geographical location, endemic insects, food preferences and cultural beliefs.
Global Catastrophic Biological Risks (GCBRs) refer to events with biological agents that can result in unprecedented or catastrophic disasters that are beyond the collective response-abilities of nation-states and the existing governance instruments of global governance and international affairs. This article offers a narrative review, with a view to new hypothesis development to rethink GCBRs after coronavirus disease 2019 (COVID-19) so as to better prepare for future pandemics and ecological crises, if not to completely prevent them. To determine GCBRs' spatiotemporal contexts, define causality, impacts, differentiate the risk and the event, would improve theorization of GCBRs compared to the impact-centric current definition. This could in turn lead to improvements in preparedness, response, allocation of resources, and possibly deterrence, while actively discouraging lack of due biosecurity diligence. Critical governance of GCBRs in ways that unpack the political power-related dimensions could be particularly valuable because the future global catastrophic events might be different in quality, scale, and actors. Theorization of GCBRs remains an important task going forward in the 21st century in ways that draw from experiences in the field, while integrating flexibility, versatility, and critically informed responses to GCBRs.
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A sustained relationship between Cairo, Egypt more broadly, and eastern Ethiopia appears to have existed, particularly in the Ayyubid and Mamluk periods. In the general absence of historical sources, it is archaeology that provides primary insight into how and why this relationship was maintained, particularly over the twelfth to thirteenth centuries. This is considered through archaeological data from the trading entrepot of Harlaa with particular reference to coins, glass wares, ceramics, bread/ textile stamps, marine shell, and jewellery moulds. The inferences that can be drawn from these regarding trade routes and markets are assessed. Finally, the Egyptian role in the decline of Harlaa and its replacement by Harar in the late fifteenth century are considered.
Ancient deoxyribonucleic acid (DNA) may be thousands of years old with significant degradation from environmental exposure, as is typical for DNA from archaeological samples, or it may be only a few years old yet fragmented and damaged, such as found in formalin‐fixed paraffin embedded medical samples. In the archaeological record, there are two primary sources of microbiome data: dental calculus preserves DNA of the oral microbiome, while coprolites and latrine sediments provide a window into the gut microbiome. Some pathogens, including those causing the mycobacterial diseases tuberculosis (TB) and Hansen's disease, as well as treponemal diseases such as yaws, bejel, and syphilis, can result in characteristic changes to the skeleton in those with chronic disease. The recovery and analysis of ancient TB DNA are facilitated by focusing on such individuals, but can be challenging because of the many species of environmental mycobacteria found in soil and water that can contaminate samples.
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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.
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Plague caused by Yersinia pestis is a zoonotic infection, i.e., it is maintained in wildlife by animal reservoirs and on occasion spills over into human populations, causing outbreaks of different entities. Large epidemics of plague, which have had significant demographic, social, and economic consequences, have been recorded in Western European historical documents since the sixth century. Plague has remained in Europe for over 1400 years, intermittently disappearing, yet it is not clear if there were reservoirs for Y. pestis in Western Europe or if the pathogen was rather reimported on different occasions from Asian reservoirs by human agency. The latter hypothesis thus far seems to be the most plausible one, as it is sustained by both ecological and climatological evidence, helping to interpret the phylogeny of this bacterium.
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Plague, caused by the bacterium Yersinia pestis, is one of the deadliest infectious diseases in human history, and still causes worrying outbreaks in Africa and South America. Despite the historical and current importance of plague, several questions remain unanswered concerning its transmission routes and infection risk factors. The plague outbreak that started in September 1665 in the Derbyshire village of Eyam claimed 257 lives over 14 months, wiping out entire families. Since previous attempts at modelling the Eyam plague, new data have been unearthed from parish records revealing a much more complete record of the disease. Using a stochastic compartmental model and Bayesian analytical methods, we found that both rodent-to-human and human-to-human transmission played an important role in spreading the infection, and that they accounted, respectively, for a quarter and three-quarters of all infections, with a statistically significant seasonality effect. We also found that the force of infection was stronger for infectious individuals living in the same household compared with the rest of the village. Poverty significantly increased the risk of disease, whereas adulthood decreased the risk. These results on the Eyam outbreak contribute to the current debate on the relative importance of plague transmission routes.
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Unblocked fleas can transmit Yersinia pestis, the bacterium that causes plague, shortly (≤4 d) after taking an infectious bloodmeal. Investigators have measured so-called early-phase transmission (EPT) efficiency in various fleas following infection with highly bacteremic blood (≥10(8 )cfu/ml). To date, no one has determined the lower limit of bacteremia required for fleas to acquire and transmit infection by EPT, though knowing this threshold is central to determining the length of time a host may be infectious to feeding fleas. Here, we evaluate the ability of Oropsylla montana (Baker) to acquire and transmit Y. pestis after feeding on blood containing 10(3) to 10(9 )cfu/ml. We evaluated the resulting infection prevalence, bacterial loads, and transmission efficiency within the early-phase time period at 1 d postinfection. Fleas acquired infection from bacteremic blood across a wide range of concentrations, but transmission was observed only when fleas ingested highly bacteremic blood.
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bnlearn is an R package which includes several algorithms for learning the structure of Bayesian networks with either discrete or continuous variables. Both constraint-based and score-based algorithms are implemented, and can use the functionality provided by the snow package to improve their performance via parallel computing. Several network scores and conditional independence algorithms are available for both the learning algorithms and independent use. Advanced plotting options are provided by the Rgraphviz package.
Down the ages, war epidemics have decimated the fighting strength of armies, caused the suspension and cancellation of military operations, and have brought havoc to the civil populations of belligerent and non-belligerent states alike. This book examines the historical occurrence and geographical spread of infectious diseases in association with past wars. It addresses an intrinsically geographical question: how are the spatial dynamics of epidemics influenced by military operations and the directives of war? The term historical geography in the title indicates the authors' primary concern with qualitative analyses of archival source materials over a 150-year time period from 1850, and this is combined with quantitative analyses less frequently associated with historical studies.