Esta pesquisa visa analisar algumas das principais implicações causadas pelas epidemias nas interações desenvolvidas entre índios Tupi e jesuítas na América Portuguesa entre os anos de 1549 e 1585. Para isto, buscamos, inicialmente, salientar a influência das interpretações elaboradas sobre as origens dos contágios, tanto para a construção de concepções sobre o “outro” formuladas a partir do encontro, quanto para a criação de diferentes soluções e acomodações concebidas com o intuito de mitigar os efeitos provocados por estes fenômenos. Em seguida, destacamos como as implicações acarretadas por estas medidas de proteção, aliadas as transformações ocasionadas pelas abruptas quedas demográficas, repercutiram nas relações que se estabeleceram entre indígenas e inacianos durante estas pouco mais de três décadas. Deste modo, foi possível relacionar a emergência de diferentes epidemias ao desenvolvimento de aproximações e rupturas nestas interações, e, com isto, sublinhar as consequências drásticas destes surtos nas dinâmicas dos primeiros contatos desenvolvidos entre os Tupi e a missão jesuítica no período quinhentista.; This research aims to analyze the impacts of epidemics in the interactions between Tupi and Jesuits in América Portuguesa between the years 1549 and 1585. For this...
Streptococcal inhibitor of complement (Sic) is a secreted protein made predominantly by serotype M1 Group A Streptococcus (GAS), which contributes to persistence in the mammalian upper respiratory tract and epidemics of human disease. Unexpectedly, an isogenic sic-negative mutant adhered to human epithelial cells significantly better than the wild-type parental strain. Purified Sic inhibited the adherence of a sic negative serotype M1 mutant and of non-Sic-producing GAS strains to human epithelial cells. Sic was rapidly internalized by human epithelial cells, inducing cell flattening and loss of microvilli. Ezrin and moesin, human proteins that functionally link the cytoskeleton to the plasma membrane, were identified as Sic-binding proteins by affinity chromatography and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis. Sic colocalized with ezrin inside epithelial cells and bound to the F-actin-binding site region located in the carboxyl terminus of ezrin and moesin. Synthetic peptides corresponding to two regions of Sic had GAS adherence-inhibitory activity equivalent to mature Sic and inhibited binding of Sic to ezrin. In addition, the sic mutant was phagocytosed and killed by human polymorphonuclear leukocytes significantly better than the wild-type strain...
In networks, nodes may preferentially contact other nodes with similar (assortatively mixed) or dissimilar (disassortatively mixed) numbers of contacts. Different patterns of contact support different epidemic dynamics, potentially affecting the efficacy of control measures such as contact tracing, which aims to identify and isolate nodes with infectious contacts. We used stochastic simulations to investigate the effects of mixing patterns on epidemic dynamics and contact-tracing efficacy. For uncontrolled epidemics, outbreaks occur at lower infection rates for more assortatively mixed networks, with faster initial epidemic growth rate and shorter epidemic duration than for disassortatively mixed networks. Contact tracing performs better for assortative mixing where epidemic size is large and tracing rate low, but it performs better for disassortative mixing at higher contact rates. For assortatively mixed networks, disease spreads first to highly connected nodes, but this is balanced by contact tracing quickly identifying these same nodes. The converse is true for disassortative mixing, where both disease and tracing are less likely to target highly connected nodes. For small epidemics, contact tracing is more effective on disassortative networks due to the greater resilience of assortative networks to link removal. Multi-step contact tracing is more effective than single-step tracing for assortative mixing...
Understanding the mechanisms that generate oscillations in the incidence of
childhood infectious diseases has preoccupied epidemiologists and population
ecologists for nearly two centuries. This body of work has generated simple yet
powerful explanations for the epidemics of measles and chickenpox, while the
dynamics of other infectious diseases, such as whooping cough, have proved more
challenging to decipher. A number of authors have, in recent years, proposed
that the noisy and somewhat irregular epidemics of whooping cough may arise due
to stochasticity and its interaction with nonlinearity in transmission and
seasonal variation in contact rates. The reason underlying the susceptibility of
whooping cough dynamics to noise and the precise nature of its transient
dynamics remain poorly understood. Here we use household data on the incubation
period in order to parametrize more realistic distributions of the latent and
infectious periods. We demonstrate that previously reported phenomena result
from transients following the interaction between the stable annual attractor
and unstable multiennial solutions.
Understanding the nature of human contact patterns is crucial for predicting the impact of future pandemics and devising effective control measures. However, few studies provide a quantitative description of the aspects of social interactions that are most relevant to disease transmission. Here, we present the results from a detailed diary-based survey of casual (conversational) and close contact (physical) encounters made by a small peer group of 49 adults who recorded 8661 encounters with 3528 different individuals over 14 non-consecutive days. We find that the stability of interactions depends on the intimacy of contact and social context. Casual contact encounters mostly occur in the workplace and are predominantly irregular, while close contact encounters mostly occur at home or in social situations and tend to be more stable. Simulated epidemics of casual contact transmission involve a large number of non-repeated encounters, and the social network is well captured by a random mixing model. However, the stability of the social network should be taken into account for close contact infections. Our findings have implications for the modelling of human epidemics and planning pandemic control policies based on social distancing methods.
In this study we quantified the rate at which classical swine fever had been transmitted by several different types of inter-herd contact during the 1997-8 epidemic in The Netherlands. During that epidemic 428 CSFV-infected pig herds were detected, 403 of which were include in this study. The estimated rates of transmission were 0.065 per shipment of live pigs, 0.011 per contact by a pig transportation lorry, 0.0068 per person contact, 0.0007 per dose of semen, 0.0065 per contact with a potentially contaminated pig assembly point, 0.027 per week per infected herd within a radius of 500 metres and 0.0078 per week per infected herd at a distance between 500 and 1000 metres. These transmission rates can be used to optimize the strategy to stop future epidemics of CSF in The Netherlands. In addition, the analysis demonstrated in this paper, can be used to quantify CSFV transmission rates from other epidemics.
Containing an epidemic at its origin is the most desirable mitigation. Epidemics have often originated in rural areas, with rural communities among the first affected. Disease dynamics in rural regions have received limited attention, and results of general studies cannot be directly applied since population densities and human mobility factors are very different in rural regions from those in cities. We create a network model of a rural community in Kansas, USA, by collecting data on the contact patterns and computing rates of contact among a sampled population. We model the impact of different mitigation strategies detecting closely connected groups of people and frequently visited locations. Within those groups and locations, we compare the effectiveness of random and targeted vaccinations using a Susceptible-Exposed-Infected-Recovered compartmental model on the contact network. Our simulations show that the targeted vaccinations of only 10% of the sampled population reduced the size of the epidemic by 34.5%. Additionally, if 10% of the population visiting one of the most popular locations is randomly vaccinated, the epidemic size is reduced by 19%. Our results suggest a new implementation of a highly effective strategy for targeted vaccinations through the use of popular locations in rural communities.
Contact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the question whether the structure of the contact network leaves a detectable genetic fingerprint in the pathogen population. To this end we compare phylogenies generated by disease outbreaks in simulated populations with different types of contact networks. We find that the shape of these phylogenies strongly depends on contact structure. In particular, measures of tree imbalance allow us to quantify to what extent the contact structure underlying an epidemic deviates from a null model contact network and illustrate this in the case of random mixing. Using a phylogeny from the Swiss HIV epidemic, we show that this epidemic has a significantly more unbalanced tree than would be expected from random mixing.
The dynamic nature of contact patterns creates diverse temporal structures. In particular, empirical studies have shown that contact patterns follow heterogeneous inter-event time intervals, meaning that periods of high activity are followed by long periods of inactivity. To investigate the impact of these heterogeneities in the spread of infection from a theoretical perspective, we propose a stochastic model to generate temporal networks where vertices make instantaneous contacts following heterogeneous inter-event intervals, and may leave and enter the system. We study how these properties affect the prevalence of an infection and estimate , the number of secondary infections of an infectious individual in a completely susceptible population, by modeling simulated infections (SI and SIR) that co-evolve with the network structure. We find that heterogeneous contact patterns cause earlier and larger epidemics in the SIR model in comparison to homogeneous scenarios for a vast range of parameter values, while smaller epidemics may happen in some combinations of parameters. In the case of SI and heterogeneous patterns, the epidemics develop faster in the earlier stages followed by a slowdown in the asymptotic limit. For increasing vertex turnover rates...
We analyze the impact of birth seasonality (seasonal oscillations in the birth rate) on the dynamics of acute, immunizing childhood infectious diseases. Previous research has explored the effect of human birth seasonality on infectious disease dynamics using parameters appropriate for the developed world. We build on this work by including in our analysis an extended range of baseline birth rates and amplitudes, which correspond to developing world settings. Additionally, our analysis accounts for seasonal forcing both in births and contact rates. We focus in particular on the dynamics of measles. In the absence of seasonal transmission rates or stochastic forcing, for typical measles epidemiological parameters, birth seasonality induces either annual or biennial epidemics. Changes in the magnitude of the birth fluctuations (birth amplitude) can induce significant changes in the size of the epidemic peaks, but have little impact on timing of disease epidemics within the year. In contrast, changes to the birth seasonality phase (location of the peak in birth amplitude within the year) significantly influence the timing of the epidemics. In the presence of seasonality in contact rates, at relatively low birth rates (20 per 1000), birth amplitude has little impact on the dynamics but does have an impact on the magnitude and timing of the epidemics. However...
This paper presents an optimal control problem formulation to minimize the total number of infection cases during the spread of susceptible-infected-recovered SIR epidemics in contact networks. In the new approach, contact weighted are reduced among nodes and a global minimum contact level is preserved in the network. In addition, the infection cost and the cost associated with the contact reduction are linearly combined in a single objective function. Hence, the optimal control formulation addresses the tradeoff between minimization of total infection cases and minimization of contact weights reduction. Using Pontryagin theorem, the obtained solution is a unique candidate representing the dynamical weighted contact network. To find the near-optimal solution in a decentralized way, we propose two heuristics based on Bang-Bang control function and on a piecewise nonlinear control function, respectively. We perform extensive simulations to evaluate the two heuristics on different networks. Our results show that the piecewise nonlinear control function outperforms the well-known Bang-Bang control function in minimizing both the total number of infection cases and the reduction of contact weights. Finally, our results show awareness of the infection level at which the mitigation strategies are effectively applied to the contact weights.
Vibrio harveyi is a marine bacterial pathogen responsible for episodic epidemics generally associated with massive mortalities in many marine organisms, including the European abalone Haliotis tuberculata. The aim of this study was to identify the portal of entry and the dynamics of infection of V. harveyi in the European abalone. The results indicate that the duration of contact between V. harveyi and the European abalone influences the mortality rate and precocity. Immediately after contact, the epithelial and mucosal area situated between the gills and the hypobranchial gland was colonized by V. harveyi. Real-time PCR analyses and culture quantification of a green fluorescent protein-tagged strain of V. harveyi in abalone tissues revealed a high density of bacteria adhering to and then penetrating the whole gill-hypobranchial gland tissue after 1 h of contact. V. harveyi was also detected in the hemolymph of a significant number of European abalones after 3 h of contact. In conclusion, this article shows that a TaqMan real-time PCR assay is a powerful and useful technique for the detection of a marine pathogen such as V. harveyi in mollusk tissue and for the study of its infection dynamics. Thus, we have revealed that the adhesion and then the penetration of V. harveyi in European abalone organs begin in the first hours of contact. We also hypothesize that the portal of entry of V. harveyi in the European abalone is the area situated between the gills and the hypobranchial gland.
A differential equations model is developed for the 2014 Ebola epidemics in Sierra Leone and Liberia. The model describes the dynamic interactions of the susceptible and infected populations of these countries. The model incorporates the principle features of contact tracing, namely, the number of contacts per identified infectious case, the likelihood that a traced contact is infectious, and the efficiency of the contact tracing process. The model is first fitted to current cumulative reported case data in each country. The data fitted simulations are then projected forward in time, with varying parameter regimes corresponding to contact tracing efficiencies. These projections quantify the importance of the identification, isolation, and contact tracing processes for containment of the epidemics.
Rift Valley fever (RVF) is a disease of animals and people that is caused by the RVF virus. During epidemics, humans get RVF through direct contact with animals or through mosquito bites. In East Africa, epidemics occur every 5–15 years following unusually high rainfall. In between epidemics, the transmission of RVF might occur at low level. In an epidemic-free period, we measured whether people in the Kilombero Valley in Tanzania had evidence of past and recent RVF infection in their blood sample, and studied risk factors. Three per cent of people had been infected recently, and 12% had evidence of past infection, with increased risk with age, among milkers and among people eating raw meat. Some people with past or recent infection reported they had not had contact with animals. Households keeping livestock had more members with evidence of past infection. The findings show that people get infected with RVF in between epidemics, and that various types of contact with livestock are important risk factors. There is also evidence that some people get infected with RVFV by mosquitoes in the epidemic free period. Clinicians in the Kilombero Valley should consider RVF in the differential diagnosis of patients with fever.
Previous palaeopathological studies have sought to build up a picture of Australian Aboriginal health before European settlement in 1788 and epidemiological studies of Aboriginal health in the twentieth century are now legion. But, despite a growing body of literature on Aboriginal history set in the intervening colonial period, our knowledge of Aboriginal health following European colonisation remains understudied. This thesis is a contribution to filling that gap through an examination of documentary and skeletal evidence in the changing bio-chemical situation experienced by Aboriginal populations of Southeast Australia from 1788 to 1900.
This thesis examines one of the major biological components of this change – disease that were introduced unto Australian Aboriginal populations during the process of colonisation. The epidemiology, timing, diffusion of diseases are considered with specific attention given to infectious and respiratory diseases that were responsible for causing major epidemics of morbidity and mortality.
The medical model for the contact period in the late 18th and 19th centuries is proposed. This model considers three major stages in the disease environment of Aboriginal populations in Southeast Australia; a pre-contact stage with endemic pathogens causing chronic diseases and limited epidemics...
Chronic wasting disease (CWD) is a fatal disease of deer, elk, and moose transmitted through direct, animal-to-animal contact, and indirectly, via environmental contamination. Considerable attention has been paid to modeling direct transmission, but despite the fact that CWD prions can remain infectious in the environment for years, relatively little information exists about the potential effects of indirect transmission on CWD dynamics. In the present study, we use simulation models to demonstrate how indirect transmission and the duration of environmental prion persistence may affect epidemics of CWD and populations of North American deer. Existing data from Colorado, Wyoming, and Wisconsin's CWD epidemics were used to define plausible short-term outcomes and associated parameter spaces. Resulting long-term outcomes range from relatively low disease prevalence and limited host-population decline to host-population collapse and extinction. Our models suggest that disease prevalence and the severity of population decline is driven by the duration that prions remain infectious in the environment. Despite relatively low epidemic growth rates, the basic reproductive number, R0, may be much larger than expected under the direct-transmission paradigm because the infectious period can vastly exceed the host's life span. High prion persistence is expected to lead to an increasing environmental pool of prions during the early phases (i.e. approximately during the first 50 years) of the epidemic. As a consequence...
A generalization of the standard susceptible-infectious-removed (SIR)
stochastic model for epidemics in sparse random networks is introduced which
incorporates contact tracing in addition to random screening. We propose a
deterministic mean-field description which yields quantitative agreement with
stochastic simulations on random graphs. We also analyze the role of contact
tracing in epidemics control in small-world networks and show that its
effectiveness grows as the rewiring probability is reduced.; Comment: 4 pages, 4 figures, submitted to PRL
A differential equations model is developed for the 2014 Ebola epidemics in
Sierra Leone, Liberia, and Guinea. The model describes the dynamic interactions
of the susceptible and infected populations of these countries. The model
incorporates the principle features of contact tracing, namely, the number of
contacts per identified infectious case, the likelihood that a traced contact
is either incubating or infectious, and the efficiency of the contact tracing
process.The model is first fitted to current cumulative reported case data in
each country. The data fitted simulations are then projected forward in time,
with varying parameter regimes corresponding to contact tracing efficiencies.
These projections quantify the importance of the identification, isolation, and
contact tracing processes for containment of the epidemics.
Contact tracing data collected from disease outbreaks has received relatively
little attention in the epidemic modelling literature because it is thought to
be unreliable: infection sources might be wrongly attributed, or data might be
missing due to resource contraints in the questionnaire exercise. Nevertheless,
these data might provide a rich source of information on disease transmission
rate. This paper presents novel methodology for combining contact tracing data
with rate-based contact network data to improve posterior precision, and
therefore predictive accuracy. We present an advancement in Bayesian inference
for epidemics that assimilates these data, and is robust to partial contact
tracing. Using a simulation study based on the British poultry industry, we
show how the presence of contact tracing data improves posterior predictive
accuracy, and can directly inform a more effective control strategy.; Comment: 40 pages, 9 figures. Submitted to Biostatistics
We consider an age-structured epidemic model with two basic public health
interventions: (i) identifying and isolating symptomatic cases, and (ii)
tracing and quarantine of the contacts of identified infectives. The dynamics
of the infected population are modeled by a nonlinear infection-age-dependent
partial differential equation, which is coupled with an ordinary differential
equation that describes the dynamics of the susceptible population. Theoretical
results about global existence and uniqueness of positive solutions are proved.
We also present two practical applications of our model: (1) we assess public
health guidelines about emergency preparedness and response in the event of a
smallpox bioterrorist attack; (2) we simulate the 2003 SARS outbreak in Taiwan
and estimate the number of cases avoided by contact tracing. Our model can be
applied as a rational basis for decision makers to guide interventions and
deploy public health resources in future epidemics.