Number Of Secondary Infections Research Articles

Understanding and Modeling the Super-spreading Events of the Middle East Respiratory Syndrome Outbreak in Korea

Understanding and Modeling the Super-spreading Events of the Middle East Respiratory Syndrome Outbreak in Korea

Quantification of parasite shedding and horizontal transmission parameters in Histomonas meleagridis-infected turkeys determined by real-time quantitative PCR

To gain more insight into the within flock transmission of Histomonas meleagridis, the shedding of parasites was quantified by a newly developed real-time quantitative (q)PCR and the basic reproduction number (R0) and the mean number of secondary infections per infectious bird per day in a susceptible population (β) of H. meleagridis in the absence of heterakis were assessed. Forty turkeys were divided into two groups of 10 and 30 birds at 14 days of age. Birds of the first group were inoculated with 200,000 histomonads each, the second group served as a susceptible contact group. Cloacal swabs were taken at −1, 1, 4, 7, 9, 11, 14, 18 and 21 days post inoculation (p.i.) to assess the shedding of the parasite by the qPCR (detection limit 330 histomonads/ml droppings). The experiment ended at 28 days p.i. Mortality was 100% in the inoculated birds and started at day 12 p.i., while in the contacts, it was 83% and started at 16 days p.i. Shedding started 1 day after the inoculation in both groups. The mean shedding levels (and 95% CI) expressed as parasite equivalents per gram cloacal content on a log10 scale in the inoculated, contact birds that died and contact birds alive were 2.0 (1.6–2.4), 1.6 (1.4–1.9) and 1.2 (0.5–2.0), respectively. Birds that died shed histomonas more often and were infectious for 13.4 days; in contrast, those that recovered were infectious for 5.7 days. R0 was estimated to be 8.4 and β 0.70. Simulations made with the parameters obtained were in agreement with the experimental results, confirming their validity.

Within-Host Spatiotemporal Dynamics of Plant Virus Infection at the Cellular Level

A multicellular organism is not a monolayer of cells in a flask; it is a complex, spatially structured environment, offering both challenges and opportunities for viruses to thrive. Whereas virus infection dynamics at the host and within-cell levels have been documented, the intermediate between-cell level remains poorly understood. Here, we used flow cytometry to measure the infection status of thousands of individual cells in virus-infected plants. This approach allowed us to determine accurately the number of cells infected by two virus variants in the same host, over space and time as the virus colonizes the host. We found a low overall frequency of cellular infection (<0.3), and few cells were coinfected by both virus variants (<0.1). We then estimated the cellular contagion rate (R), the number of secondary infections per infected cell per day. R ranged from 2.43 to values not significantly different from zero, and generally decreased over time. Estimates of the cellular multiplicity of infection (MOI), the number of virions infecting a cell, were low (<1.5). Variance of virus-genotype frequencies increased strongly from leaf to cell levels, in agreement with a low MOI. Finally, there were leaf-dependent differences in the ease with which a leaf could be colonized, and the number of virions effectively colonizing a leaf. The modeling of infection patterns suggests that the aggregation of virus-infected cells plays a key role in limiting spread; matching the observation that cell-to-cell movement of plant viruses can result in patches of infection. Our results show that virus expansion at the between-cell level is restricted, probably due to the host environment and virus infection itself.

On the Exact Measure of Disease Spread in Stochastic Epidemic Models

The basic reproduction number, R₀, is probably the most important quantity in epidemiology. It is used to measure the transmission potential during the initial phase of an epidemic. In this paper, we are specifically concerned with the quantification of the spread of a disease modeled by a Markov chain. Due to the occurrence of repeated contacts taking place between a typical infective individual and other individuals already infected before, R₀ overestimates the average number of secondary infections. We present two alternative measures, namely, the exact reproduction number, Re0, and the population transmission number, Rp, that overcome this difficulty and provide valuable insight. The applicability of Re0 and Rp to control of disease spread is also examined.

Bursts of Vertex Activation and Epidemics in Evolving Networks

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, heterogeneous patterns generally cause higher prevalence in comparison to homogeneous scenarios with the same average inter-event interval. We find that is generally higher for heterogeneous patterns, except for sufficiently large infection duration and transmission probability.

Integrating Phylodynamics and Epidemiology to Estimate Transmission Diversity in Viral Epidemics

The epidemiology of chronic viral infections, such as those caused by Hepatitis C Virus (HCV) and Human Immunodeficiency Virus (HIV), is affected by the risk group structure of the infected population. Risk groups are defined by each of their members having acquired infection through a specific behavior. However, risk group definitions say little about the transmission potential of each infected individual. Variation in the number of secondary infections is extremely difficult to estimate for HCV and HIV but crucial in the design of efficient control interventions. Here we describe a novel method that combines epidemiological and population genetic approaches to estimate the variation in transmissibility of rapidly-evolving viral epidemics. We evaluate this method using a nationwide HCV epidemic and for the first time co-estimate viral generation times and superspreading events from a combination of molecular and epidemiological data. We anticipate that this integrated approach will form the basis of powerful tools for describing the transmission dynamics of chronic viral diseases, and for evaluating control strategies directed against them.

HIV/AIDS Dynamics with Three Control Strategies: The Role of Incidence Function

The type of incidence function used in epidemiological models is generally a matter of choice and convenience. Basic deterministic HIV/AIDS models with standard and saturated incidences are developed and extended to include three control measures, namely, public health educational campaigns, condom use, and treatment. The potential impact of these incidence functions on long-term projection of the disease dynamics is theoretically assessed, both qualitatively and quantitatively. Conditions for the stability of the model steady states are provided. The model with saturated incidence yields a higher number of secondary infections compared to the same outcome in the standard incidence formulation.

On estimating the basic reproduction number in distinct stages of a contagious disease spreading

In epidemiology, the basic reproduction number R0 is usually defined as the average number of new infections caused by a single infective individual introduced into a completely susceptible population. According to this definition, R0 is related to the initial stage of the spreading of a contagious disease. However, from epidemiological models based on ordinary differential equations (ODE), R0 is commonly derived from a linear stability analysis and interpreted as a bifurcation parameter: typically, when R0>1, the contagious disease tends to persist in the population because the endemic stationary solution is asymptotically stable; when R0<1, the corresponding pathogen tends to naturally disappear because the disease-free stationary solution is asymptotically stable. Here we intend to answer the following question: Do these two different approaches for calculating R0 give the same numerical values? In other words, is the number of secondary infections caused by a unique sick individual equal to the threshold obtained from stability analysis of steady states of ODE? For finding the answer, we use a susceptible-infective-recovered (SIR) model described in terms of ODE and also in terms of a probabilistic cellular automaton (PCA), where each individual (corresponding to a cell of the PCA lattice) is connected to others by a random network favoring local contacts. The values of R0 obtained from both approaches are compared, showing good agreement.

Heterogeneity in tuberculosis transmission and the role of geographic hotspots in propagating epidemics

The importance of high-incidence "hotspots" to population-level tuberculosis (TB) incidence remains poorly understood. TB incidence varies widely across countries, but within smaller geographic areas (e.g., cities), TB transmission may be more homogeneous than other infectious diseases. We constructed a steady-state compartmental model of TB in Rio de Janeiro, replicating nine epidemiological variables (e.g., TB incidence) within 1% of their observed values. We estimated the proportion of TB transmission originating from a high-incidence hotspot (6.0% of the city's population, 16.5% of TB incidence) and the relative impact of TB control measures targeting the hotspot vs. the general community. If each case of active TB in the hotspot caused 0.5 secondary transmissions in the general community for each within-hotspot transmission, the 6.0% of people living in the hotspot accounted for 35.3% of city-wide TB transmission. Reducing the TB transmission rate (i.e., number of secondary infections per infectious case) in the hotspot to that in the general community reduced city-wide TB incidence by 9.8% in year 5, and 29.7% in year 50-an effect similar to halving time to diagnosis for the remaining 94% of the community. The importance of the hotspot to city-wide TB control depended strongly on the extent of TB transmission from the hotspot to the general community. High-incidence hotspots may play an important role in propagating TB epidemics. Achieving TB control targets in a hotspot containing 6% of a city's population can have similar impact on city-wide TB incidence as achieving the same targets throughout the remaining community.

Vaccination of influenza a virus decreases transmission rates in pigs

Limited information is available on the transmission and spread of influenza virus in pig populations with differing immune statuses. In this study we assessed differences in transmission patterns and quantified the spread of a triple reassortant H1N1 influenza virus in naïve and vaccinated pig populations by estimating the reproduction ratio (R) of infection (i.e. the number of secondary infections caused by an infectious individual) using a deterministic Susceptible-Infectious-Recovered (SIR) model, fitted on experimental data. One hundred and ten pigs were distributed in ten isolated rooms as follows: (i) non-vaccinated (NV), (ii) vaccinated with a heterologous vaccine (HE), and (iii) vaccinated with a homologous inactivated vaccine (HO). The study was run with multiple replicates and for each replicate, an infected non-vaccinated pig was placed with 10 contact pigs for two weeks and transmission of influenza evaluated daily by analyzing individual nasal swabs by RT-PCR. A statistically significant difference between R estimates was observed between vaccinated and non-vaccinated pigs (p < 0.05). A statistically significant reduction in transmission was observed in the vaccinated groups where R (95%CI) was 1 (0.39-2.09) and 0 for the HE and the HO groups respectively, compared to an Ro value of 10.66 (6.57-16.46) in NV pigs (p < 0.05). Transmission in the HE group was delayed and variable when compared to the NV group and transmission could not be detected in the HO group. Results from this study indicate that influenza vaccines can be used to decrease susceptibility to influenza infection and decrease influenza transmission.

Quantifying Transmission of Campylobacter jejuni in Commercial Broiler Flocks

Since meat from poultry colonized with Campylobacter spp. is a major cause of bacterial gastroenteritis, human exposure should be reduced by, among other things, prevention of colonization of broiler flocks. To obtain more insight into possible sources of introduction of Campylobacter into broiler flocks, it is essential to estimate the moment that the first bird in a flock is colonized. If the rate of transmission within a flock were known, such an estimate could be determined from the change in the prevalence of colonized birds in a flock over time. The aim of this study was to determine the rate of transmission of Campylobacter using field data gathered for 5 years for Australian broiler flocks. We used unique sampling data for 42 Campylobacter jejuni-colonized flocks and estimated the transmission rate, which is defined as the number of secondary infections caused by one colonized bird per day. The estimate was 2.37 +/- 0.295 infections per infectious bird per day, which implies that in our study population colonized flocks consisting of 20,000 broilers would have an increase in within-flock prevalence to 95% within 4.4 to 7.2 days after colonization of the first broiler. Using Bayesian analysis, the moment of colonization of the first bird in a flock was estimated to be from 21 days of age onward in all flocks in the study. This study provides an important quantitative estimate of the rate of transmission of Campylobacter in broiler flocks, which could be helpful in future studies on the epidemiology of Campylobacter in the field.

The Impact of Dispersion in the Number of Secondary Infections on the Probability of an Epidemic

Heterogeneity in communities is a key factor to consider when modelling the transmission of an infection or implementing strategies to control its transmission. Heterogeneity in the level of infectiousness of individuals can arise in a number of ways. For example, it can arise through the structure of a community with, say, households, through the nature of a disease that may include superspreaders and others who are hardly infectious (like SARS), or through mixing and behaviour patterns that can be altered by interventions. Lloyd-Smith et al. (Lloyd-Smith, Schreiber, Kopp and Getz (2005)) observed that, under certain specific assumptions, greater heterogeneity, leads to a greater probability of disease elimination. In this paper we explore the impact of heterogeneity on the probability of disease elimination more generally. We show that, for many commonly arising distributions in ecology and epidemiology, an increase in heterogeneity, when the mean is fixed, leads to a reduction in the probability of a local outbreak. This result has important consequences for health care strategies, such as choosing strategies that increase heterogeneity for the same mean level of infectivity thereby delaying, or possibly preventing, an outbreak. However, while broadly true, including for most offspring distributions common to epidemic and ecological situations, the result is not in general true as we show by counter-examples for each of the types of heterogeneity considered. We conjecture a general principle determining when the result holds, but it remains an open question precisely when greater heterogeneity leads to an increase in the probability of extinction.

Adaptation of the Fungal Parasite Zygorhizidium planktonicum During 200 Generations of Growth on Homogeneous and Heterogeneous Populations of Its Host, the Diatom Asterionella formosa1

We followed adaptation of the chytrid parasite Zygorhizidium planktonicum during 200 generations of growth on its host, the freshwater diatom Asterionella formosa, in a serial passage experiment. Evolution of parasite fitness was assessed both on a homogenous and heterogeneous host population, consisting of respectively a single new and ten different new host strains. These 10 host strains were genetically different and also varied in their initial susceptibility to the parasite. Parasite fitness increased significantly and rapidly on the new, genetically homogenous host population, but remained unaltered during 200 generations of growth on the heterogeneous host population. Enhanced parasite fitness was the result of faster and more efficient transmission, resulting in higher values of R0 (number of secondary infections). Consequently, parasites that evolved within the uniclonal host population infected significantly more of these hosts than did their ancestors. We thus provide experimental evidence for the widely held view that host genetic diversity restricts evolution of parasites and moderates their harmful effects. Genetically uniform host populations are not only at increased risk from fungal epidemics because they all share the same susceptibility, but also because new parasite strains are able to adapt quickly to new host environments and to improve their fitness.

Quantification of foot and mouth disease virus excretion and transmission within groups of lambs with and without vaccination

Sheep are well known to be susceptible for foot and mouth disease virus (FMDV), but it is unknown whether the infection can spread and persist in a sheep population. We therefore quantified virus transmission by performing experiments with FMD virus strain O/NET/2001 in groups of lambs. We used six groups of four lambs each, in which half of each group was inoculated and the other half was contact-exposed. To quantify the effectiveness of a single vaccination we also included six groups of four lambs each, vaccinated with O Manisa vaccine, 14 days prior to inoculation. Oropharyngeal fluid was obtained with a swab (OPF-swab), and blood samples were collected daily to determine virus excretion and serological response. We calculated the transmission rate β (the number of new infections per day per infectious animal), and the reproduction ratio R (the number of secondary infections caused by one infectious individual). The mean daily virus excretion and the number of days the lambs excreted virus in the OPF differed significantly between vaccinated and non-vaccinated lambs. The transmission rate β in the unvaccinated groups was 0.105 (95% confidence limit 0.044; 0.253) per day. The duration of the infectious period ( T) was 21.11 (95% confidence limit 10.6; 42.1) days. With the final size of infection we estimated the reproduction ratio R in the non-vaccinated groups to be 1.14 (0.3; 3.3), and in vaccinated groups 0.22 (0.01; 1.78). Virus transmission as quantified by the final size did not differ statistically between the vaccinated and the non-vaccinated groups of lambs. In conclusion, FMDV seems able to persist in a sheep population, although the reproduction ratio was only slightly larger than one. As a consequence, vaccination might only have a small effect on transmission, in spite of the fact that virus excretion and duration of virus excretion is significantly reduced after vaccination.

Quantification of within- and between-pen transmission of Foot-and-Mouth disease virus in pigs

Quantified transmission parameters of Foot-and-Mouth Disease Virus (FMDV) are needed for epidemic models used for control and surveillance. In this study, we quantified the within- and between-pen transmission of FMDV in groups of pigs by estimating the daily transmission rate beta, i.e. the number of secondary infections caused by one infectious pig during one day, using an SIR (susceptible-infectious-removed) model. Within-pen transmission was studied in four groups of ten pigs in which 5 infected and 5 susceptible pigs had direct contact; between-pen transmission was studied in one group of ten pigs in which 5 infected and 5 susceptible pigs had indirect contact. Daily results of virus isolation of oropharyngeal fluid were used to quantify the transmission rate beta, using Generalised Linear Modelling (GLM) and a maximum likelihood method. In addition, we estimated the expected time to infection of the first pig within a pen T(w) and in the indirect-contact pen T(b). The between-pen transmission rate beta(b) was estimated to be 0.59 (0.083-4.18) per day, which was significantly lower than the within-pen transmission rate beta(w) of 6.14 (3.75-10.06). T(w) was 1.6 h, and T(b) was 16 h. Our results show that the transmission rate is influenced by contact structure between pigs.

Modeling the potential impact of rectal microbicides to reduce HIV transmission in bathhouses

We evaluate the potential impact of rectal microbicides for reducing HIV transmission in bathhouses. A new mathematical model describing HIV transmission dynamics among men who have sex with men (MSM) in bathhouses is constructed and analyzed. The model incorporates key features affecting transmission, including sexual role behavior (insertive and receptive anal intercourse acts), biological transmissibility of HIV, frequency and efficacy of condom usage, and, most pertinently, frequency and efficacy of rectal microbicide usage. To evaluate the potential impact of rectal microbicide usage, we quantify the effect of rectal microbicides (ranging in efficacy from 10% to 90%) on reducing the number of HIV infections in the bathhouse. We conduct uncertainty analyses to assess the effect of variability in both biological and behavioral parameters. We find that even moderately effective rectal microbicides (if used in 10% to 50% of the sex acts) would substantially reduce transmission in bathhouses. For example, a 50% effective rectal microbicide (used in 50% of sex acts) would reduce the number of secondary infections by almost 13% at disease invasion. Our modeling analyses show that even moderately effective rectal microbicides could be very effective prevention tools for reducing transmission in bathhouses and also potentially limit the spread of HIV in the community.

Soins aux oiseaux mazoutés : mise à jour depuis le naufrage de l'Erika

The treatment and management of oiled birds is constantly being improved. Since the oil spill following the wreck of the tanker Erika, in December 1999, the wildlife centre of the National Veterinary School of Nantes has received several hundred of oiled birds. The current rescue protocol is described with the improvements made since the Erika oil spill. This protocol, which covers the period from the time the birds arrive up to their release, must be implemented by properly trained staff, so that the birds are treated as quickly and efficiently as possible. Indeed, reducing the duration of the process reduces the stress level for the birds and the number of secondary infections.

Threshold conditions for infection persistence in complex host-vectors interactions

As classically defined by Macdonald in the early 1950s, for the case of diseases with one vector and one host, the Basic Reproduction Number, R 0, is defined as the number of secondary infections caused by a single infective of the same type (vector or host) during its infectiousness period in an entirely susceptible population. In the case of a disease which has one vector and one host, it is easy to show that R 0 coincides with the threshold for the establishment of an endemic state: if R 0>1 <1 , the disease can invade (cannot invade) the host population. In this paper we examine various epidemic situations in which there are more than one vector and/or host. We show that in those more complex systems it is not possible to deduce a single R 0 but rather a threshold for infection persistence which is a composite of several quantities closely related to the classical expression of R 0. Another definition of R 0 given by Diekmann, Heesterbeek and Metz, and denoted in this paper R NGO 0 is discussed and applied as an alternative to calculate the thresholds for infection establishment.

Production of Tumour Necrosis Factor-alpha (TNF-α) and Reactive Nitrogen Intermediates by Ovine Peripheral Blood Leucocytes Stimulated by Ehrlichia (Cytoecetes) phagocytophila

Ehrlichia (Cytoecetes) phagocytophila, the causative agent of tick-borne fever in sheep and pasture fever in cattle, is an immunosuppressive, obligately intracellular rickettsia that invades granulocytes and monocytes of ruminants. Infected animals are known to suffer from a number of secondary infections. The mechanisms of immunosuppression are believed to be associated with physical or functional damage to leucocytes and the release of immunosuppressive substances. In the present study, the effects of E. phagocytophila on the production of tumour necrosis factor-alpha (TNF-α) and reactive nitrogen intermediates by ovine peripheral blood mononuclear cells (PBMCs) were investigatedin vivo and in vitro. The concentration of TNF-α and nitrate in ovine sera were significantly increased during infection with E. phagocytophila, peak concentrations occurring at the peak period of rickettsiaemia. The addition of E. phagocytophila to cell cultures enhanced in-vitro production of TNF-α and nitric oxide by normal ovine PBMCs.

A discrete-time epidemiological model to quantify selection for disease resistance

AbstractA genetic epidemiological model (GEM) for investigating the effect of selection for disease resistance on the epidemiology of infectious diseases is presented and applied to a pig breeding scenario. Fundamental to the model is R0, the basic reproductive ratio. R0 is the expected number of secondary infections caused by a single infection. If R0 is greater than 1, there will be an epidemic. The aim of the model is to quantify the effect of selection on R0 and the consequences this has on disease epidemiology. Two implementations are presented: selection for reduced susceptibility/infectivity to a disease and introgression of a major resistance gene. The results suggest that the effects of selection for reduced susceptibility I infectivity are critically dependent on the infectiousness of the disease. Under the assumptions made in the model, for a disease with a low infection level, it takes approximately 15 years of selection until R0 is less than 1 and the population is safe from epidemics should the infectious agent be present. For a highly infectious disease, this time may be as long as 100 years. For gene introgression, the population is expected to be free from epidemics within 5 years and the time to reduce R0 to less than 1 is largely independent of the disease being considered. With gene introgression, the proportion of the population which needs to be resistant to ensure that R0 is less than one is shown to be a function of the initial R0 for the disease. Although selection, as modelled, results in a linear decline in R0, the reduction in the proportion of animals infected during an epidemic is non-linear. The selection process reduces the amount of infectious material that is in the environment when an infection occurs and this decreases the force of infection on unselected animals. This phenomenon results in a marked interaction between host genotype and disease epidemiology. Thus, the results of the model show that altering the genetics of individual animals affects the epidemiology of the disease at the population level. The model can be applied to any farm structure and any microparasitic infectious disease.