Comparing epidemic tuberculosis in demographically distinct heterogeneous populations

There is wide variation in endemic tuberculosis (TB) levels between countries and we seek to identify possible causes of these differences. In this study we present an epidemiological model of Mycobacterium tuberculosis infection to investigate the effects of host genetics and demographic factors on epidemic TB. We discuss the general framework for this approach and present analytical results to identify important parameters affecting steady-state prevalence and incidence rates of TB disease. We then use numerical simulations of our model to observe the effects of a genetically susceptible subpopulation on TB disease dynamics at the population level. Finally, we simulate infection within a genetically heterogeneous population in two demographic settings: India (a typical population with high TB prevalence) and the USA (a typical population with low TB prevalence). Results show that changes in transmission parameters, the fraction of the population genetically susceptible to infection, and demographic factors strongly affect TB prevalence and incidence rates.     

The status of tuberculosis in European wild mammals

• 1 Tuberculosis (TB) is a chronic disease caused by Mycobacterium bovis and related members of the Mycobacterium tuberculosis complex. Infection affects not only cattle but also other livestock species, companion animals and wild mammals. Humans are also susceptible; hence, zoonotic infection is a driver for disease control in animal hosts. As bovine TB prevalence has been reduced in livestock, the relative epidemiological and socio‐economic importance of wildlife reservoirs has increased, and there is a need for disease management strategies.
• 2 We review the current status of TB in European wild mammals, identifying epidemiological trends and areas for future research and management. TB has a complex epidemiology, which may involve multiple hosts, and is influenced by climate and habitat.
• 3 Consequently, the role of wild and domestic hosts in the epidemiology of TB varies among regions. In Europe, there are three regional examples of M. bovis maintenance hosts: the Eurasian badger Meles meles in Great Britain and Ireland, the Eurasian wild boar Sus scrofa in the Iberian Peninsula and deer belonging to the subfamily Cervinae in several European regions. In other parts of Europe, these species are currently regarded as spillover hosts, although in time their status may change depending on local or regional risk factors. Nevertheless, in most situations, the relative contribution of wild mammals to M. bovis infection in cattle is still a matter of debate. Also, the outcome of management interventions to control disease in wildlife populations may be complex and counter‐intuitive.
• 4 As our knowledge of disease dynamics in wild mammals improves, options for disease control in wildlife reservoirs, such as vaccination, improved biosecurity and population management, are likely to broaden. In order to evaluate our existing control options, we must monitor the effects of interventions on TB occurrence in the affected regions of Europe and share our collective experiences.

     

Nutrition, diabetes and tuberculosis in the epidemiological transition

Background

Diabetes prevalence and body mass index reflect the nutritional profile of populations but have opposing effects on tuberculosis risk. Interactions between diabetes and BMI could help or hinder TB control in growing, aging, urbanizing populations.

Methods and Findings

We compiled data describing temporal changes in BMI, diabetes prevalence and population age structure in rural and urban areas for men and women in countries with high (India) and low (Rep. Korea) TB burdens. Using published data on the risks of TB associated with these factors, we calculated expected changes in TB incidence between 1998 and 2008. In India, TB incidence cases would have increased (28% from 1.7 m to 2.1 m) faster than population size (22%) because of adverse effects of aging, urbanization, changing BMI and rising diabetes prevalence, generating an increase in TB incidence per capita of 5.5% in 10 years. In India, general nutritional improvements were offset by a fall in BMI among the majority of men who live in rural areas. The growing prevalence of diabetes in India increased the annual number of TB cases in people with diabetes by 46% between 1998 and 2008. In Korea, by contrast, the number of TB cases increased more slowly (6.1% from 40,200 to 42,800) than population size (14%) because of positive effects of urbanization, increasing BMI and falling diabetes prevalence. Consequently, TB incidence per capita fell by 7.8% in 10 years. Rapid population aging was the most significant adverse effect in Korea.

Conclusions

Nutritional and demographic changes had stronger adverse effects on TB in high-incidence India than in lower-incidence Korea. The unfavourable effects in both countries can be overcome by early drug treatment but, if left unchecked, could lead to an accelerating rise in TB incidence. The prevention and management of risk factors for TB would reinforce TB control by chemotherapy.     

Efficient targeted learning of heterogeneous treatment effects for multiple subgroups

In biomedical science, analyzing treatment effect heterogeneity plays an essential role in assisting personalized medicine. The main goals of analyzing treatment effect heterogeneity include estimating treatment effects in clinically relevant subgroups and predicting whether a patient subpopulation might benefit from a particular treatment. Conventional approaches often evaluate the subgroup treatment effects via parametric modeling and can thus be susceptible to model mis-specifications. In this paper, we take a model-free semiparametric perspective and aim to efficiently evaluate the heterogeneous treatment effects of multiple subgroups simultaneously under the one-step targeted maximum-likelihood estimation (TMLE) framework. When the number of subgroups is large, we further expand this path of research by looking at a variation of the one-step TMLE that is robust to the presence of small estimated propensity scores in finite samples. From our simulations, our method demonstrates substantial finite sample improvements compared to conventional methods. In a case study, our method unveils the potential treatment effect heterogeneity of rs12916-T allele (a proxy for statin usage) in decreasing Alzheimer's disease risk.     

The efficacy of sampling strategies for estimating scabies prevalence

BackgroundEstimating community level scabies prevalence is crucial for targeting interventions to areas of greatest need. The World Health Organisation recommends sampling at the unit of households or schools, but there is presently no standardised approach to scabies prevalence assessment. Consequently, a wide range of sampling sizes and methods have been used. As both prevalence and drivers of transmission vary across populations, there is a need to understand how sampling strategies for estimating scabies prevalence interact with local epidemiology to affect the accuracy of prevalence estimates.MethodsWe used a simulation-based approach to compare the efficacy of different scabies sampling strategies. First, we generated synthetic populations broadly representative of remote Australian Indigenous communities and assigned a scabies status to individuals to achieve a specified prevalence using different assumptions about scabies epidemiology. Second, we calculated an observed prevalence for different sampling methods and sizes.ResultsThe distribution of prevalence in subpopulation groups can vary substantially when the underlying scabies assignment method changes. Across all of the scabies assignment methods combined, the simple random sampling method produces the narrowest 95% confidence interval for all sample sizes. The household sampling method introduces higher variance compared to simple random sampling when the assignment of scabies includes a household-specific component. The school sampling method overestimates community prevalence when the assignment of scabies includes an age-specific component.DiscussionOur results indicate that there are interactions between transmission assumptions and surveillance strategies, emphasizing the need for understanding scabies transmission dynamics. We suggest using the simple random sampling method for estimating scabies prevalence. Our approach can be adapted to various populations and diseases.     

Independent and competing disease risks: implications for host populations in variable environments

Disease models usually assume disease to act independently of other mortality- and morbidity-causing factors. Alternatively, disease may function as a competing risk factor, for example, killing already moribund hosts. Using tuberculosis (TB) in African buffalo as a model system, we explore consequences of competing or independent disease effects for host population dynamics. We include scenarios with density-dependent and density-independent effects of environmental variation, exemplified by variable food availability (driven by rainfall) and catastrophic droughts, respectively. Independent disease effects reduce population size linearly with prevalence, irrespective of the nature of environmental variation. Competing disease risks alter population size only if density-independent variation is present; then, disease reduces population size nonlinearly. Field data indicate that the net effect of TB on buffalo likely falls between the extremes of total independence and competition with other risk factors: TB increases mortality and decreases fecundity in some prime-aged buffalo, suggesting independent disease risks in these individuals, while similar disease effects in senescent buffalo may act as competing risks. Moreover, increased survival and fecundity of TB-negative buffalo may compensate for some disease-related losses. Model assumptions on independent or competing disease risks and environmental variability should be considered explicitly when assessing disease effects on wildlife populations.     

The role of screening and treatment in the transmission dynamics of HIV/AIDS and tuberculosis co-infection: a mathematical study

In this paper, we present a deterministic non-linear mathematical model for the transmission dynamics of HIV and TB co-infection and analyze it in the presence of screening and treatment. The equilibria of the model are computed and stability of these equilibria is discussed. The basic reproduction numbers corresponding to both HIV and TB are found and we show that the disease-free equilibrium is stable only when the basic reproduction numbers for both the diseases are less than one. When both the reproduction numbers are greater than one, the co-infection equilibrium point may exist. The co-infection equilibrium is found to be locally stable whenever it exists. The TB-only and HIV-only equilibria are locally asymptotically stable under some restriction on parameters. We present numerical simulation results to support the analytical findings. We observe that screening with proper counseling of HIV infectives results in a significant reduction of the number of individuals progressing to HIV. Additionally, the screening of TB reduces the infection prevalence of TB disease. The results reported in this paper clearly indicate that proper screening and counseling can check the spread of HIV and TB diseases and effective control strategies can be formulated around ‘screening with proper counseling’.     

Modeling epidemics of multidrug-resistant M. tuberculosis of heterogeneous fitness

Mathematical models have recently been used to predict the future burden of multidrug-resistant tuberculosis (MDRTB). These models suggest the threat of multidrug resistance to TB control will depend on the relative 'fitness' of MDR strains and imply that if the average fitness of MDR strains is considerably less than that of drug-sensitive strains, the emergence of resistance will not jeopardize the success of tuberculosis control efforts. Multidrug resistance in M. tuberculosis is conferred by the sequential acquisition of a number of different single-locus mutations that have been shown to have heterogeneous phenotypic effects. Here we model the impact of initial fitness estimates on the emergence of MDRTB assuming that the relative fitness of MDR strains is heterogeneous. We find that even when the average relative fitness of MDR strains is low and a well-functioning control program is in place, a small subpopulation of a relatively fit MDR strain may eventually outcompete both the drug-sensitive strains and the less fit MDR strains. These results imply that current epidemiological measures and short-term trends in the burden of MDRTB do not provide evidence that MDRTB strains can be contained in the absence of specific efforts to limit transmission from those with MDR disease.     

Optima TB: A tool to help optimally allocate tuberculosis spending

Approximately 85% of tuberculosis (TB) related deaths occur in low- and middle-income countries where health resources are scarce. Effective priority setting is required to maximise the impact of limited budgets. The Optima TB tool has been developed to support analytical capacity and inform evidence-based priority setting processes for TB health benefits package design. This paper outlines the Optima TB framework and how it was applied in Belarus, an upper-middle income country in Eastern Europe with a relatively high burden of TB. Optima TB is a population-based disease transmission model, with programmatic cost functions and an optimisation algorithm. Modelled populations include age-differentiated general populations and higher-risk populations such as people living with HIV. Populations and prospective interventions are defined in consultation with local stakeholders. In partnership with the latter, demographic, epidemiological, programmatic, as well as cost and spending data for these populations and interventions are then collated. An optimisation analysis of TB spending was conducted in Belarus, using program objectives and constraints defined in collaboration with local stakeholders, which included experts, decision makers, funders and organisations involved in service delivery, support and technical assistance. These analyses show that it is possible to improve health impact by redistributing current TB spending in Belarus. Specifically, shifting funding from inpatient- to outpatient-focused care models, and from mass screening to active case finding strategies, could reduce TB prevalence and mortality by up to 45% and 50%, respectively, by 2035. In addition, an optimised allocation of TB spending could lead to a reduction in drug-resistant TB infections by 40% over this period. This would support progress towards national TB targets without additional financial resources. The case study in Belarus demonstrates how reallocations of spending across existing and new interventions could have a substantial impact on TB outcomes. This highlights the potential for Optima TB and similar modelling tools to support evidence-based priority setting.     

Predicting and controlling the reactivity of immune cell populations against cancer

Heterogeneous cell populations form an interconnected network that determine their collective output. One example of such a heterogeneous immune population is tumor‐infiltrating lymphocytes (TILs), whose output can be measured in terms of its reactivity against tumors. While the degree of reactivity varies considerably between different TILs, ranging from null to a potent response, the underlying network that governs the reactivity is poorly understood. Here, we asked whether one can predict and even control this reactivity. To address this we measured the subpopulation compositions of 91 TILs surgically removed from 27 metastatic melanoma patients. Despite the large number of subpopulations compositions, we were able to computationally extract a simple set of subpopulation‐based rules that accurately predict the degree of reactivity. This raised the conjecture of whether one could control reactivity of TILs by manipulating their subpopulation composition. Remarkably, by rationally enriching and depleting selected subsets of subpopulations, we were able to restore anti‐tumor reactivity to nonreactive TILs. Altogether, this work describes a general framework for predicting and controlling the output of a cell mixture.     

Spatiotemporal Model of Barley and Cereal Yellow Dwarf Virus Transmission Dynamics with Seasonality and Plant Competition

Many generalist pathogens are influenced by the spatial distributions and relative abundances of susceptible host species. The spatial structure of host populations can influence patterns of infection incidence (or disease outbreaks), and the effects of a generalist pathogen on host community dynamics in a spatially heterogeneous community may differ from predictions derived via simple models. In this paper, we model the transmission of a generalist pathogen within a patch framework that incorporates the movement of vectors between discrete host patches to investigate the effects of local host community composition and vector movement rates on disease dynamics.     

Genetics of Nonalcoholic Fatty Liver Disease:An Overview

Nonalcoholic fatty liver disease(NAFLD) is the most common liver disease in the world today.Its incidence in adults and children is rising rapidly due to the ongoing epidemics of obesity and type 2 diabetes.Hence,it has become a global public health issue.Environmental factors have been found to play a major role in the etiology of NAFLD,especially for genetically susceptible populations. Among these,one of the most important factors is junk food,especially the typical "Western-style" diet rich in simple carbohydrates, saturated fat,and highly processed food materials.Genetic predisposition to NAFLD does occur;however,a precise definition of genetic factors responsible for NAFLD is still lacking.Specific variants of different genes have been shown to present a risk for NAFLD.Genetic studies might be helpful in the management of the disease by developing novel treatment strategies based on individual’s genotype.     

Genotype and sex-based host variation in behaviour and susceptibility drives population disease dynamics

Host heterogeneity in pathogen transmission is widespread and presents a major hurdle to predicting and minimizing disease outbreaks. Using Drosophila melanogaster infected with Drosophila C virus as a model system, we integrated experimental measurements of social aggregation, virus shedding, and disease-induced mortality from different genetic lines and sexes into a disease modelling framework. The experimentally measured host heterogeneity produced substantial differences in simulated disease outbreaks, providing evidence for genetic and sex-specific effects on disease dynamics at a population level. While this was true for homogeneous populations of single sex/genetic line, the genetic background or sex of the index case did not alter outbreak dynamics in simulated, heterogeneous populations. Finally, to explore the relative effects of social aggregation, viral shedding and mortality, we compared simulations where we allowed these traits to vary, as measured experimentally, to simulations where we constrained variation in these traits to the population mean. In this context, variation in infectiousness, followed by social aggregation, was the most influential component of transmission. Overall, we show that host heterogeneity in three host traits dramatically affects population-level transmission, but the relative impact of this variation depends on both the susceptible population diversity and the distribution of population-level variation.     

Modelling HIV and MTB Co-Infection Including Combined Treatment Strategies

A new host-pathogen model is described that simulates HIV-MTB co-infection and treatment, with the objective of testing treatment strategies. The model includes CD4+ and CD8+ T cells, resting and activated macrophages, HIV and Mycobacterium tuberculosis (MTB). For TB presentation at various stages of HIV disease in a co-infected individual, combined treatment strategies were tested with different relative timings of treatment for each infection. The stages were early HIV disease, late HIV disease and AIDS. The main strategies were TB treatment followed by anti-retroviral therapy (ART) after delays of 15 days, 2 months and 6 months. ART followed by TB treatment was an additional strategy that was tested. Treatment was simulated with and without drug interaction. Simulation results were that TB treatment first followed by ART after a stage-dependent delay has the best outcome. During early HIV disease a 6 month delay is acceptable. During late HIV disease, a 2 month delay is best. During AIDS it is better to start ART after 15 days. However, drug interaction works against the benefits of early ART. These results agree with expert reviews and clinical trials.     

Tuberculosis and Poverty: Why Are the Poor at Greater Risk in India?

Background

Although poverty is widely recognized as an important risk factor for tuberculosis (TB) disease, the specific proximal risk factors that mediate this association are less clear. The objective of our study was to investigate the mechanisms by which poverty increases the risk of TB.

Methods

Using individual level data from 198,754 people from the 2006 Demographic Health Survey (DHS) for India, we assessed self-reported TB status, TB determinants and household socioeconomic status. We used these data to calculate the population attributable fractions (PAF) for each key TB risk factor based on the prevalence of determinants and estimates of the effect of these risk factors derived from published sources. We conducted a mediation analysis using principal components analysis (PCA) and regression to demonstrate how the association between poverty and TB prevalence is mediated.

Results

The prevalence of self-reported TB in the 2006 DHS for India was 545 per 100,000 and ranged from 201 in the highest quintile to 1100 in the lowest quintile. Among those in the poorest population, the PAFs for low body mass index (BMI) and indoor air pollution were 34.2% and 28.5% respectively. The PCA analysis also showed that low BMI had the strongest mediating effect on the association between poverty and prevalent TB (12%, p = 0.019).

Conclusion

TB control strategies should be targeted to the poorest populations that are most at risk, and should address the most important determinants of disease—specifically low BMI and indoor air pollution.     

Matching strategies for genetic association studies in structured populations

Association studies in populations that are genetically heterogeneous can yield large numbers of spurious associations if population subgroups are unequally represented among cases and controls. This problem is particularly acute for studies involving pooled genotyping of very large numbers of single-nucleotide-polymorphism (SNP) markers, because most methods for analysis of association in structured populations require individual genotyping data. In this study, we present several strategies for matching case and control pools to have similar genetic compositions, based on ancestry information inferred from genotype data for approximately 300 SNPs tiled on an oligonucleotide-based genotyping array. We also discuss methods for measuring the impact of population stratification on an association study. Results for an admixed population and a phenotype strongly confounded with ancestry show that these simple matching strategies can effectively mitigate the impact of population stratification.     

Intensive case finding and isoniazid preventative therapy in HIV infected individuals in Africa: economic model and value of information analysis

BACKGROUND: Tuberculosis (TB) accounts of much of the morbidity and mortality associated with HIV. We evaluate the cost-effectiveness of different strategies to actively screen for TB disease in HIV positive individuals, where isoniazid preventative therapy (IPT) is given to those screening negative, and use value of information analysis (VOI) to identify future research priorities. METHODOLOGY/ PRINCIPAL FINDINGS: We built an individual sampling model to investigate the costs (2010 US Dollars) and consequences of screening for TB, and providing TB treatment or IPT in adults testing HIV positive in Sub-Saharan Africa. A systematic review and meta-analysis was conducted to assess performance of the nine different TB screening strategies evaluated. Probabilistic sensitivity analysis was conducted to incorporate decision uncertainty, and expected value of perfect information for the entire model and for groups of parameters was calculated. Screening all HIV infected individuals with sputum microscopy was the least costly strategy, with other strategies not cost-effective at WHO recommended thresholds. Screening those with TB symptoms with sputum microscopy and CXR would be cost-effective at a threshold ICER of $7,800 per quality-adjusted life year (QALY), but associated with significant uncertainty. VOI analysis suggests further information would be of value. CONCLUSIONS/ SIGNIFICANCE: Resource-constrained countries in sub-Saharan Africa wishing to scale up TB preventative services in their HIV infected populations should consider expanding laboratory facilities to enable increased screening for TB with sputum microscopy, whilst improved estimates of the TB prevalence in the population to be screened are needed, as it may influence the optimal strategy.     

基于醇溶蛋白的20份小麦种质遗传完整性分析

采用醇溶蛋白电泳技术对同一品种不同繁殖年份的20份小麦种质进行遗传完整性分析。结果表明：供试种质中有10份具有一种醇溶蛋白谱带带型的同质性种质;另外10份具有2～4种醇溶蛋白谱带带型的异质性种质,其中6份为地方品种。表明地方品种具有较高的遗传多样性。在10份异质性种质中,两个繁殖年份种质之间的醇溶蛋白带型频率变化差异不显著的有5份,其第一繁殖年份的种质发芽率均高于75％,而另外5份存在显著差异的种质,第一年份的发芽率都低于66％。进一步分析表明,这10份异质性种质在两个繁殖年份之间,其发芽率差值与带型频率差值之间呈极显著正相关,相关系数为0．8665。上速结果表明,小麦更新时较高的发芽率是维持异质性种质遗传完整性的关键因素。