Timing HIV infection with a simple and accurate population viral dynamics model

Clinical trials for HIV prevention can require knowledge of infection times to subsequently determine protective drug levels. Yet, infection timing is difficult when study visits are sparse. Using population nonlinear mixed-effects (pNLME) statistical inference and viral loads from 46 RV217 study participants, we developed a relatively simple HIV primary infection model that achieved an excellent fit to all data. We also discovered that Aptima assay values from the study strongly correlated with viral loads, enabling imputation of very early viral loads for 28/46 participants. Estimated times between infecting exposures and first positives were generally longer than prior estimates (average of two weeks) and were robust to missing viral upslope data. On simulated data, we found that tighter sampling before diagnosis improved estimation more than tighter sampling after diagnosis. Sampling weekly before and monthly after diagnosis was a pragmatic design for good timing accuracy. Our pNLME timing approach is widely applicable to other infections with existing mathematical models. The present model could be used to simulate future HIV trials and may help estimate protective thresholds from the recently completed antibody-mediated prevention trials.     

Mycobacterium bovis shedding patterns from experimentally infected calves and the effect of concurrent infection with bovine viral diarrhoea virus

Concurrent infection of cattle with bovine viral diarrhoea virus (BVDV) and Mycobacterium bovis is considered to be a possible risk factor for onward transmission of bovine tuberculosis (BTB) in infected cattle and is known to compromise diagnostic tests. A comparison is made here of M. bovis shedding (i.e. release) characteristics from 12 calves, six experimentally co-infected with BVDV and six infected with M. bovis alone, using simple models of bacterial replication. These statistical and mathematical models account for the intermittent or episodic nature of shedding, the dynamics of within-host bacterial proliferation and the sampling distribution from a given shedding episode. We show that while there are distinct differences among the shedding patterns of calves given the same infecting dose, there is no statistically significant difference between the two groups of calves. Such differences as there are, can be explained solely in terms of the shedding frequency, but with all calves potentially excreting the same amount of bacteria in a given shedding episode post-infection. The model can be thought of as a process of the bacteria becoming established in a number of discrete foci of colonization, rather than as a more generalized infection of the respiratory tract. In this case, the variability in the shedding patterns of the infected calves can be explained solely by differences in the number of foci established and shedding being from individual foci over time. Should maximum exposure on a particular occasion be a critical consideration for cattle-to-cattle transmission of BTB, cattle that shed only intermittently may still make an important contribution to the spread and persistence of the disease.     

The effect of changes in condom usage and antiretroviral treatment coverage on human immunodeficiency virus incidence in South Africa: a model-based analysis

This study aims to assess trends in human immunodeficiency virus (HIV) incidence in South Africa, and to assess the extent to which prevention and treatment programmes have reduced HIV incidence. Two models of the South African HIV epidemic, the STI (sexually transmitted infection)–HIV Interaction model and the ASSA2003 AIDS and Demographic model, were adapted. Both models were fitted to age-specific HIV prevalence data from antenatal clinic surveys and household surveys, using a Bayesian approach. Both models suggest that HIV incidence in 15–49 year olds declined significantly between the start of 2000 and the start of 2008: by 27 per cent (95% CI: 21–32%) in the STI–HIV model and by 31 per cent (95% CI: 23–39%) in the ASSA2003 model, when expressed as a percentage of incidence rates in 2000. By 2008, the percentage reduction in incidence owing to increased condom use was 37 per cent (95% CI: 34–41%) in the STI–HIV model and 23 per cent (95% CI: 14–34%) in the ASSA2003 model. Both models also estimated a small reduction in incidence owing to antiretroviral treatment by 2008. Increased condom use therefore appears to be the most significant factor explaining the recent South African HIV incidence decline.     

Effect of the initial dose of foot-and-mouth disease virus on the early viral dynamics within pigs

This paper investigates the early viral dynamics of foot-and-mouth disease (FMD) within infected pigs. Using an existing within-host model, we investigate whether individual variation can be explained by the effect of the initial dose of FMD virus. To do this, we consider the experimental data on the concentration of FMD virus genomes in the blood (viral load). In this experiment, 12 pigs were inoculated with one of three different doses of FMD virus: low; medium; or high. Measurements of the viral load were recorded over a time course of approximately 11 days for every 8 hours. The model is a set of deterministic differential equations with the following variables: viral load; virus in the interstitial space; and the proportion of epithelial cells available for infection, infected and uninfected. The model was fitted to the data for each animal individually and also simultaneously over all animals varying only the initial dose. We show that the general trend in the data can be explained by varying only the initial dose. The higher the initial dose the earlier the development of a detectable viral load.     

Onset of virus systemic infection in plants is determined by speed of cell-to-cell movement and number of primary infection foci

The cornerstone of today''s plant virology consists of deciphering the molecular and mechanistic basis of host–pathogen interactions. Among these interactions, the onset of systemic infection is a fundamental variable in studying both within- and between-host infection dynamics, with implications in epidemiology. Here, we developed a mechanistic model using probabilistic and spatio-temporal concepts to explain dynamic signatures of virus systemic infection. The model dealt with the inherent characteristic of plant viruses to use two different and sequential stages for their within-host propagation: cell-to-cell movement from the initial infected cell and systemic spread by reaching the vascular system. We identified the speed of cell-to-cell movement and the number of primary infection foci in the inoculated leaf as the key factors governing this dynamic process. Our results allowed us to quantitatively understand the timing of the onset of systemic infection, describing this global process as a consequence of local spread of viral populations. Finally, we considered the significance of our predictions for the evolution of plant RNA viruses.     

Infection dynamics in ecosystems: on the interaction between red and grey squirrels,pox virus,pine martens and trees

Ecological and epidemiological processes and interactions influence each other, positively and negatively, directly and indirectly. The invasion potential of pathogens is influenced by the ecosystem context of their host species’ populations. This extends to the capacity of (multiple) host species to maintain their (common) pathogen and the way pathogen dynamics are influenced by changes in ecosystem composition. This paper exemplifies these interactions and consequences in a study of red and grey squirrel dynamics in the UK. Differences and changes in background habitat and trophic levels above and below the squirrel species lead to different dynamic behaviour in many subtle ways. The range of outcomes of the different interactions shows that one has to be careful when drawing conclusions about the mechanisms and processes involved in explaining observed phenomena concerning pathogens in their natural environment. The dynamic behaviour also shows that planning interventions, for example for conservation purposes, benefits from understanding the complexity of interactions beyond the particular pathogen and its threatened host species.     

基于协整理论的沪深300股指期货跨期套利研究

现有的股指期货跨期套利大多是基于持有成本模型进行跨期套利,但由于此模型套利存在固有的缺陷,往往得不到理想的套利效果.统计套利提供了一种新的套利模式,少数利用协整理论进行套利的方法也还存在一些可以改进的地方.利用沪深300股指期货的实际交易数据,借助对现有的协整理论进行改进的套利方法建立模型,可以实施跨期套利.实证分析的结果表明,改进的协整策略可以取得较好的套利效果.     

A combination of differential equations and convolution in understanding the spread of an epidemic

Nonlinear dynamical method of projecting the transmission of an epidemic is accurate if the input parameters and initial value variables are reliable. Here, such a model is proposed for predicting an epidemic. A method to supplement two variables and two parameters for this proposed model is demonstrated through a robust statistical approach. The method described here worked well in case of three continuous distributions. Model predictions could be lower estimates due to under-reporting of disease cases. Anad hoc procedure with a technical note is provided in the appendix An earlier version of this paper was presented at the annual conference of the Indian Society for Mathematical Modelling & Computer Simulation, Bangalore, November 14–15, 2002     

Dissecting the determinants of malaria chronicity: why within-host models struggle to reproduce infection dynamics

The duration of infection is fundamental to the epidemiological behaviour of any infectious disease, but remains one of the most poorly understood aspects of malaria. In endemic areas, the malaria parasite Plasmodium falciparum can cause both acute, severe infections and asymptomatic, chronic infections through its interaction with the host immune system. Frequent superinfection and massive parasite genetic diversity make it extremely difficult to accurately measure the distribution of infection lengths, complicating the estimation of basic epidemiological parameters and the prediction of the impact of interventions. Mathematical models have qualitatively reproduced parasite dynamics early during infection, but reproducing long-lived chronic infections remains much more challenging. Here, we construct a model of infection dynamics to examine the consequences of common biological assumptions for the generation of chronicity and the impact of co-infection. We find that although a combination of host and parasite heterogeneities are capable of generating chronic infections, they do so only under restricted parameter choices. Furthermore, under biologically plausible assumptions, co-infection of parasite genotypes can alter the course of infection of both the resident and co-infecting strain in complex non-intuitive ways. We outline the most important puzzles for within-host models of malaria arising from our analysis, and their implications for malaria epidemiology and control.     

Assessing the impact of adherence to anti-retroviral therapy on treatment failure and resistance evolution in HIV

The adherence of patients to therapy is a crucial factor for successful HIV anti-retroviral therapy. Imperfect adherence may lead to treatment failure, which can cause the emergence of resistance within viral populations. We have developed a stochastic model that incorporates compartments of latently infected cells and virus genotypes with different susceptibilities to three simultaneously used drugs. With this model, we study the impact of several key parameters on the probability of treatment failure, i.e. insufficient viral suppression, and the emergence of resistance. Specifically, we consider the impact of drug dosage, drug half-lives, fitness costs for resistance, different basic reproductive numbers of the virus and the influence of pre-existing mutations under various levels of adherence. Furthermore, we also investigate the influence of different temporal distributions of non-adherent days (drug holidays) during a treatment. Factors that promote resistance evolution include a high reproductive number, extended drug holidays and poor adherence. Pre-existing mutations only have a substantial effect if they confer resistance against more than one drug. Overall, our study highlights the importance of the interactions between imperfect adherence, pharmacodynamics, pharmacokinetics and latently infected cells for our understanding of drug resistance and therapy failure in HIV anti-retroviral therapy.     

Modelling gambiense human African trypanosomiasis infection in villages of the Democratic Republic of Congo using Kolmogorov forward equations

Stochastic methods for modelling disease dynamics enable the direct computation of the probability of elimination of transmission. For the low-prevalence disease of human African trypanosomiasis (gHAT), we develop a new mechanistic model for gHAT infection that determines the full probability distribution of the gHAT infection using Kolmogorov forward equations. The methodology allows the analytical investigation of the probabilities of gHAT elimination in the spatially connected villages of different prevalence health zones of the Democratic Republic of Congo, and captures the uncertainty using exact methods. Our method provides a more realistic approach to scaling the probability of elimination of infection between single villages and much larger regions, and provides results comparable to established models without the requirement of detailed infection structure. The novel flexibility allows the interventions in the model to be implemented specific to each village, and this introduces the framework to consider the possible future strategies of test-and-treat or direct treatment of individuals living in villages where cases have been found, using a new drug.     

A novel approach for predicting risk of vector-borne disease establishment in marginal temperate environments under climate change: West Nile virus in the UK

Vector-borne diseases (VBDs), such as dengue, Zika, West Nile virus (WNV) and tick-borne encephalitis, account for substantial human morbidity worldwide and have expanded their range into temperate regions in recent decades. Climate change has been proposed as a likely driver of past and future expansion, however, the complex ecology of host and vector populations and their interactions with each other, environmental variables and land-use changes makes understanding the likely impacts of climate change on VBDs challenging. We present an environmentally driven, stage-structured, host–vector mathematical modelling framework to address this challenge. We apply our framework to predict the risk of WNV outbreaks in current and future UK climates. WNV is a mosquito-borne arbovirus which has expanded its range in mainland Europe in recent years. We predict that, while risks will remain low in the coming two to three decades, the risk of WNV outbreaks in the UK will increase with projected temperature rises and outbreaks appear plausible in the latter half of this century. This risk will increase substantially if increased temperatures lead to increases in the length of the mosquito biting season or if European strains show higher replication at lower temperatures than North American strains.     

Evaluating the potential impact of enhancing HIV treatment and tuberculosis control programmes on the burden of tuberculosis

HIV has fuelled increasing tuberculosis (TB) incidence in sub-Saharan Africa. Better control of TB in this region may be achieved directly through TB programme improvements and indirectly through expanded use of antiretroviral therapy (ART) among those with HIV. We used a mathematical model of TB and HIV in South Africa to examine the potential epidemiological impact in scenarios involving improvements in three dimensions of TB programmes: coverage, diagnosis and treatment effectiveness, as well as expanded ART use through broadened eligibility. We projected the effect of alternative scenarios on TB prevalence, incidence and TB-related mortality over 20 years. Of the three dimensions of TB programme improvement, expanding coverage would produce the greatest reduction in TB burden. Compared with current performance, combined TB programme improvements were projected to decrease TB incidence by 30% over 5 years and 46% over 20 years, and decrease TB-related mortality by 45% over 5 years and 69% over 20 years. Expanded ART eligibility was projected to decrease TB incidence by 22% over 5 years and 45% over 20 years, and TB-related mortality by 22% over 5 years and 50% over 20 years. We found that over a 20-year horizon, TB-specific and HIV-specific programme changes contribute equally to incidence reductions, whereas the TB-specific changes produce a majority of the mortality benefits. An aggressive expansion of ART alongside traditional TB-specific control measures has the potential to greatly reduce TB burden, with the different elements of a combined approach having a synergistic effect in reducing long-term TB incidence and mortality.     

Effect of data quality on estimates of farm infectiousness trends in the UK 2001 foot-and-mouth disease epidemic

Most of the mathematical models that were developed to study the UK 2001 foot-and-mouth disease epidemic assumed that the infectiousness of infected premises was constant over their infectious periods. However, there is some controversy over whether this assumption is appropriate. Uncertainty about which farm infected which in 2001 means that the only method to determine if there were trends in farm infectiousness is the fitting of mechanistic mathematical models to the epidemic data. The parameter values that are estimated using this technique, however, may be influenced by missing and inaccurate data. In particular to the UK 2001 epidemic, this includes unreported infectives, inaccurate farm infection dates and unknown farm latent periods. Here, we show that such data degradation prevents successful determination of trends in farm infectiousness.     

Modelling the spread of infectious salmon anaemia among salmon farms based on seaway distances between farms and genetic relationships between infectious salmon anaemia virus isolates

Infectious salmon anaemia (ISA) is an important infectious disease in Atlantic salmon farming causing recurrent epidemic outbreaks worldwide. The focus of this paper is on tracing the spread of ISA among Norwegian salmon farms. To trace transmission pathways for the ISA virus (ISAV), we use phylogenetic relationships between virus isolates in combination with space–time data on disease occurrences. The rate of ISA infection of salmon farms is modelled stochastically, where seaway distances between farms and genetic distances between ISAV isolates from infected farms play prominent roles. The model was fitted to data covering all cohorts of farmed salmon and the history of all farms with ISA between 2003 and summer 2009. Both seaway and genetic distances were significantly associated with the rate of ISA infection. The fitted model predicts that the risk of infection from a neighbourhood infectious farm decreases with increasing seaway distance between the two farms. Furthermore, for a given infected farm with a given ISAV genotype, the source of infection is significantly more likely to be ISAV of a small genetic distance than of moderate or large genetic distances. Nearly half of the farms with ISA in the investigated period are predicted to have been infected by an infectious farm in their neighbourhood, whereas the remaining half of the infected farms had unknown sources. For many of the neighbourhood infected farms, it was possible to point out one or a few infectious farms as the most probable sources of infection. This makes it possible to map probable infection pathways.     

Prevalence of transfusion-transmitted virus infection in patients on maintenance hemodialysis from New Delhi, India

Transfusion-transmitted virus (TTV) has been reported from a number of hemodialysis (HD) units from various countries throughout the world. TTV has been associated with liver diseases, viral hepatitis B, and C. Clinical details and information regarding TTV prevalence from India are insufficient. The prevalence and clinical significance of TTV infection were studied in New Delhi, India in HD patients. Serum samples were derived from 75 patients on maintenance HD, and 75 age- and sex-matched voluntary blood donors were examined for TTV viremia by nested polymerase chain reaction (PCR) using primers derived from UTR (A) region of the TTV genome. The prevalence of TTV DNA in patients on HD (83%) was significantly (p<0.05) higher than in blood donors (43%). Clinical background including the mean age, sex, mean duration of HD, and mean alanine aminotransferase (ALT) levels did not differ significantly between TTV DNA-positive and -negative HD patients. Fifty-four (72%) TTV-positive HD patients and 7 (56%) TTV-negative HD patients had blood transfusion histories (p>0.05). Among TTV-positive patients, Hepatitis B virus (HBV) co-infection was present in 14.2% cases while hepatitis C virus (HCV) co-infection was absent. Persistent elevation of ALT levels was observed in 7(9.3%) HD patients; 3 (43%) of them were TTV positive and 4 (57%) were TTV negative (p>0.05). All 3 TTV-positive patients with elevated ALT levels were co-infected with HBV. Patients with TTV infection alone showed normal ALT levels. Prevalence of TTV infection is high in North Indian patients on maintenance HD. Also, none of the exclusively TTV DNA-positive patients had clinical or biochemical signs of liver disease. TTV seems to spread through parenteral routes. More often, TTV seems to be associated with parenterally transmitted virus HBV, indicating a parenteral mode of TTV transmission. The pathogenicity of TTV remains unclear from the present study.     

Spatial dynamics of the 1918 influenza pandemic in England,Wales and the United States

There is still limited understanding of key determinants of spatial spread of influenza. The 1918 pandemic provides an opportunity to elucidate spatial determinants of spread on a large scale.To better characterize the spread of the 1918 major wave, we fitted a range of city-to-city transmission models to mortality data collected for 246 population centres in England and Wales and 47 cities in the US. Using a gravity model for city-to-city contacts, we explored the effect of population size and distance on the spread of disease and tested assumptions regarding density dependence in connectivity between cities. We employed Bayesian Markov Chain Monte Carlo methods to estimate parameters of the model for population, infectivity, distance and density dependence. We inferred the most likely transmission trees for both countries.For England and Wales, a model that estimated the degree of density dependence in connectivity between cities was preferable by deviance information criterion comparison. Early in the major wave, long distance infective interactions predominated, with local infection events more likely as the epidemic became widespread. For the US, with fewer more widely dispersed cities, statistical power was lacking to estimate population size dependence or the degree of density dependence, with the preferred model depending on distance only. We find that parameters estimated from the England and Wales dataset can be applied to the US data with no likelihood penalty.     

Exogenous re-infection and the dynamics of tuberculosis epidemics: local effects in a network model of transmission

Infection with Mycobacterium tuberculosis leads to tuberculosis (TB) disease by one of the three possible routes: primary progression after a recent infection; re-activation of a latent infection; or exogenous re-infection of a previously infected individual. Recent studies show that optimal TB control strategies may vary depending on the predominant route to disease in a specific population. It is therefore important for public health policy makers to understand the relative frequency of each type of TB within specific epidemiological scenarios. Although molecular epidemiologic tools have been used to estimate the relative contribution of recent transmission and re-activation to the burden of TB disease, it is not possible to use these techniques to distinguish between primary disease and re-infection on a population level. Current estimates of the contribution of re-infection therefore rely on mathematical models which identify the parameters most consistent with epidemiological data; these studies find that exogenous re-infection is important only when TB incidence is high. A basic assumption of these models is that people in a population are all equally likely to come into contact with an infectious case. However, theoretical studies demonstrate that the social and spatial structure can strongly influence the dynamics of infectious disease transmission. Here, we use a network model of TB transmission to evaluate the impact of non-homogeneous mixing on the relative contribution of re-infection over realistic epidemic trajectories. In contrast to the findings of previous models, our results suggest that re-infection may be important in communities where the average disease incidence is moderate or low as the force of infection can be unevenly distributed in the population. These results have important implications for the development of TB control strategies.     

鸡贫血病毒VP3基因诱导人肺癌细胞SPC-A1凋亡的作用机制

探索了重组质粒pVVP3对人肺癌细胞SPC-A1的作用及机制.将pVVP3经脂质体介导转染人肺癌细胞SPC-A1,通过MTT方法检测了细胞活力;采用吖啶橙/溴化乙锭(AO/EB)染色分析了肿瘤细胞凋亡;采用罗丹明123和DCFA染色测定了线粒体跨膜电位(△Ψm)和活性氧水平变化;通过底物染色反应检测了Caspase-3活性.检测分析结果表明:重组质粒pVVP3转染人肺癌细胞SPC-A1后,细胞活力明显降低; AO/EB染色可见明显的细胞凋亡形态学变化;与空质粒对照相比,线粒体△Ψm下降(P＜0.01),活性氧水平升高(P＜0.05),Caspase-3活性增强(P＜0.01).以上结果提示,重组质粒pVVP3能够通过上调ROS水平,下调线粒体△Ψm,进而激活Caspase-3,最终诱导人肺癌细胞凋亡.