Evaluating vaccination strategies for tuberculosis in endemic and non-endemic settings

Is neglect of self-clearance biasing TB vaccine impact estimates?

BACKGROUND

Mathematical modelling has been used extensively to estimate the potential impact of new tuberculosis vaccines, with the majority of existing models assuming that individuals with Mycobacterium tuberculosis (Mtb) infection remain at lifelong risk of tuberculosis disease. Recent research provides evidence that self-clearance of Mtb infection may be common, which may affect the potential impact of new vaccines that only take in infected or uninfected individuals. We explored how the inclusion of self-clearance in models of tuberculosis affects the estimates of vaccine impact in China and India.

METHODS

For both countries, we calibrated a tuberculosis model to a scenario without self-clearance and to various scenarios with self-clearance. To account for the current uncertainty in self-clearance properties, we varied the rate of self-clearance, and the level of protection against reinfection in self-cleared individuals. We introduced potential new vaccines in 2025, exploring vaccines that work in uninfected or infected individuals only, or that are effective regardless of infection status, and modelling scenarios with different levels of vaccine efficacy in self-cleared individuals. We then estimated the relative disease incidence reduction in 2050 for each vaccine compared with the no vaccination scenario.

FINDINGS

The inclusion of self-clearance increased the estimated relative reductions in incidence in 2050 for vaccines effective only in uninfected individuals, by a maximum of 12% in China and 8% in India. The inclusion of self-clearance increased the estimated impact of vaccines only effective in infected individuals in some scenarios and decreased it in others, by a maximum of 14% in China and 15% in India. As would be expected, the inclusion of self-clearance had minimal impact on estimated reductions in incidence for vaccines that work regardless of infection status.

INTERPRETATIONS

Our work suggests that the neglect of self-clearance in mathematical models of tuberculosis vaccines does not result in substantially biased estimates of tuberculosis vaccine impact. It may, however, mean that we are slightly underestimating the relative advantages of vaccines that work in uninfected individuals only compared with those that work in infected individuals.

Isoniazid Mono-Resistant Tuberculosis Presenting as Empyema Thoracis With Citrobacter koseri and Morganella morganii Infections: The World's First Reported Case of Its Type

Drug resistance is very common in developing countries. Isolated cases of concomitant infection with Mycobacterium tuberculosis, Citrobacter koseri, and Morganella morganii are rare. Furthermore, there is no report available in the literature of concurrent infection of Citrobacter koseri and Morganella morganii in an isoniazid mono-resistant tuberculosis patient. In this case, we present a concomitant infection with drug-resistant strains of Mycobacterium tuberculosis, Citrobacter koseri, and Morganella morganii in a 40-year-old Indian male who presented with fever, dry cough, and chest pain. He was initiated on an isoniazid mono regimen and a broad-spectrum antibiotic, following the national guidelines.

Is neglect of self-clearance biassing TB vaccine impact estimates?

Background

Mathematical modelling has been used extensively to estimate the potential impact of new tuberculosis vaccines, with the majority of existing models assuming that individuals with Mycobacterium tuberculosis (Mtb) infection remain at lifelong risk of tuberculosis disease. Recent research provides evidence that self-clearance of Mtb infection may be common, which may affect the potential impact of new vaccines that only take in infected or uninfected individuals. We explored how the inclusion of self-clearance in models of tuberculosis affects the estimates of vaccine impact in China and India.

Methods

For both countries, we calibrated a tuberculosis model to a scenario without self-clearance and to various scenarios with self-clearance. To account for the current uncertainty in self-clearance properties, we varied the rate of self-clearance, and the level of protection against reinfection in self-cleared individuals. We introduced potential new vaccines in 2025, exploring vaccines that work in uninfected or infected individuals only, or that are effective regardless of infection status, and modelling scenarios with different levels of vaccine efficacy in self-cleared individuals. We then estimated the relative incidence reduction in 2050 for each vaccine compared to the no vaccination scenario.

Findings

The inclusion of self-clearance increased the estimated relative reductions in incidence in 2050 for vaccines effective only in uninfected individuals, by a maximum of 12% in China and 8% in India. The inclusion of self-clearance increased the estimated impact of vaccines only effective in infected individuals in some scenarios and decreased it in others, by a maximum of 14% in China and 15% in India. As would be expected, the inclusion of self-clearance had minimal impact on estimated reductions in incidence for vaccines that work regardless of infection status.

Interpretations

Our work suggests that the neglect of self-clearance in mathematical models of tuberculosis vaccines does not result in substantially biased estimates of tuberculosis vaccine impact. It may, however, mean that we are slightly underestimating the relative advantages of vaccines that work in uninfected individuals only compared to those that work in infected individuals.

Feasibility of novel adult tuberculosis vaccination in South Africa: a cost-effectiveness and budget impact analysis

Early trials of novel vaccines against tuberculosis (TB) in adults have suggested substantial protection against TB. However, little is known about the feasibility and affordability of rolling out such vaccines in practice. We conducted expert interviews to identify plausible vaccination implementation strategies for the novel M72/AS01E vaccine candidate. The strategies were defined in terms of target population, coverage, vaccination schedule and delivery mode. We modelled these strategies to estimate long-term resource requirements and health benefits arising from vaccination over 2025–2050. We presented these to experts who excluded strategies that were deemed infeasible, and estimated cost-effectiveness and budget impact for each remaining strategy. The four strategies modelled combined target populations: either everyone aged 18–50, or all adults living with HIV, with delivery strategies: either a mass campaign followed by routine vaccination of 18-year olds, or two mass campaigns 10 years apart. Delivering two mass campaigns to all 18–50-year olds was found to be the most cost-effective strategy conferring the greatest net health benefit of 1.2 million DALYs averted having a probability of being cost-effective of 65–70%. This strategy required 38 million vaccine courses to be delivered at a cost of USD 507 million, reducing TB-related costs by USD 184 million while increasing ART costs by USD 79 million. A suitably designed adult TB vaccination programme built around novel TB vaccines is likely to be cost-effective and affordable given the resource and budget constraints in South Africa.

Evaluating Strategies For Tuberculosis to Achieve the Goals of WHO in China: A Seasonal Age-Structured Model Study

Although great progress has been made in the prevention and mitigation of TB in the past 20 years, China is still the third largest contributor to the global burden of new TB cases, accounting for 833,000 new cases in 2019. Improved mitigation strategies, such as vaccines, diagnostics, and treatment, are needed to meet goals of WHO. Given the huge variability in the prevalence of TB across age-groups in China, the vaccination, diagnostic techniques, and treatment for different age-groups may have different effects. Moreover, the statistics data of TB cases show significant seasonal fluctuations in China. In view of the above facts, we propose a non-autonomous differential equation model with age structure and seasonal transmission rate. We derive the basic reproduction number, [Formula: see text], and prove that the unique disease-free periodic solution, [Formula: see text] is globally asymptotically stable when [Formula: see text], while the disease is uniformly persistent and at least one positive periodic solution exists when [Formula: see text]. We estimate that the basic reproduction number [Formula: see text] ([Formula: see text]), which means that TB is uniformly persistent. Our results demonstrate that vaccinating susceptible individuals whose ages are over 65 and between 20 and 24 is much more effective in reducing the prevalence of TB, and each of the improved vaccination strategy, diagnostic strategy, and treatment strategy leads to substantial reductions in the prevalence of TB per 100,000 individuals compared with current approaches, and the combination of the three strategies is more effective. Scenario A (i.e., coverage rate [Formula: see text], diagnosis rate [Formula: see text], relapse rate [Formula: see text]) is the best and can reduce the prevalence of TB per 100,000 individuals by [Formula: see text] and [Formula: see text] in 2035 and 2050, respectively. Although the improved strategies will significantly reduce the incidence rate of TB, it is challenging to achieve the goal of WHO in 2050. Our findings can provide guidance for public health authorities in projecting effective mitigation strategies of TB.

Cost-effectiveness of routine adolescent vaccination with an M72/AS01E-like tuberculosis vaccine in South Africa and India

The M72/AS01_E tuberculosis vaccine showed 50% (95%CI: 2-74%) efficacy in a phase 2B trial in preventing active pulmonary tuberculosis disease, but potential cost-effectiveness of adolescent immunisation is unknown. We estimated the impact and cost-effectiveness of six scenarios of routine adolescent M72/AS01_E-like vaccination in South Africa and India. All scenarios suggested an M72/AS01_E-like vaccine would be highly (94-100%) cost-effective in South Africa compared to a cost-effectiveness threshold of $2480/disability-adjusted life-year (DALY) averted. For India, a prevention of disease vaccine, effective irrespective of recipient's M. tuberculosis infection status at time of administration, was also highly likely (92-100%) cost-effective at a threshold of $264/DALY averted; however, a prevention of disease vaccine, effective only if the recipient was already infected, had 0-6% probability of cost-effectiveness. In both settings, vaccinating 50% of 18 year-olds was similarly cost-effective to vaccinating 80% of 15 year-olds, and more cost-effective than vaccinating 80% of 10 year-olds. Vaccine trials should include adolescents to ensure vaccines can be delivered to this efficient-to-target population.

Structural identifiability analysis of age-structured PDE epidemic models

Computational and mathematical models rely heavily on estimated parameter values for model development. Identifiability analysis determines how well the parameters of a model can be estimated from experimental data. Identifiability analysis is crucial for interpreting and determining confidence in model parameter values and to provide biologically relevant predictions. Structural identifiability analysis, in which one assumes data to be noiseless and arbitrarily fine-grained, has been extensively studied in the context of ordinary differential equation (ODE) models, but has not yet been widely explored for age-structured partial differential equation (PDE) models. These models present additional difficulties due to increased number of variables and partial derivatives as well as the presence of boundary conditions. In this work, we establish a pipeline for structural identifiability analysis of age-structured PDE models using a differential algebra framework and derive identifiability results for specific age-structured models. We use epidemic models to demonstrate this framework because of their wide-spread use in many different diseases and for the corresponding parallel work previously done for ODEs. In our application of the identifiability analysis pipeline, we focus on a Susceptible-Exposed-Infected model for which we compare identifiability results for a PDE and corresponding ODE system and explore effects of age-dependent parameters on identifiability. We also show how practical identifiability analysis can be applied in this example.

Edoardo Maragliano (1849-1940) and the immunogenicity of the tubercle bacillus: the pathway of a great italian physician

Edoardo Maragliano (1849-1940) was an Italian physician; he played a central role in medicine's "renaissance" in Italy and Europe. After beginning his academic career as a professor of pathology, he became full professor of internal medicine in 1881. While he studied all fields of internal medicine, his research focused mainly on tuberculosis. Thanks to his experiments in the medical clinic, Maragliano announced the possibility of immunization against Mycobacterium tuberculosis. Although criticized for using an inactivated vaccine, Maragliano continued to advocate vaccination with any type of vaccine. Maragliano keenly contributed to the still ongoing process of understanding the difficult interaction between Mycobacterium tuberculosis and the infected host.

An SVEIRE Model of Tuberculosis to Assess the Effect of an Imperfect Vaccine and Other Exogenous Factors

This study extends a deterministic mathematical model for the dynamics of tuberculosis transmission to examine the impact of an imperfect vaccine and other exogenous factors, such as re-infection among treated individuals and exogenous re-infection. The qualitative behaviors of the model are investigated, covering many distinct aspects of the transmission of the disease. The proposed model is observed to show a backward bifurcation, even when Rv<1. As such, we assume that diminishing Rv to less than unity is not effective for the elimination of tuberculosis. Furthermore, the results reveal that an imperfect tuberculosis vaccine is always effective at reducing the spread of infectious diseases within the population, though the general effect increases with the increase in effectiveness and coverage. In particular, it is shown that a limited portion of people being vaccinated at steady-state and vaccine efficacy assume a equivalent role in decreasing disease burden. From the numerical simulation, it is shown that using an imperfect vaccine lead to effective control of tuberculosis in a population, provided that the efficacy of the vaccine and its coverage are reasonably high.

New tuberculosis vaccines: advances in clinical development and modelling

Tuberculosis remains a major source of morbidity and mortality worldwide, with 10 million cases and 1.5 million deaths in 2018. Achieving 'End TB' prevention and care goals by 2035 will likely require a new tuberculosis vaccine. The tuberculosis vaccine development pipeline has seen encouraging progress; however, questions around their population impact and implementation remain. Mathematical modelling investigates these questions to inform vaccine development and deployment strategies. We provide an update on the current vaccine development pipeline, and a systematic literature review of mathematical modelling of the epidemiological impact of new tuberculosis vaccines. Fourteen prophylactic tuberculosis vaccine candidates are currently in clinical trials. Two candidates have shown promise in phase II proof-of-concept efficacy trials: M72/AS01_E demonstrated 49.7% (95% CI; 2.1, 74.2) protection against tuberculosis disease, and BCG revaccination demonstrated 45.4% (95% CI; 6.4, 68.1) protection against sustained Mycobacterium tuberculosis infection. Since the last modelling review, new studies have investigated the epidemiological impact of differential vaccine characteristics, age targeting and spatial/risk group targeting. Critical research priorities for M72/AS01_E include completing the currently in-design trial, powered to improve the precision of efficacy estimates, include uninfected populations and further assess safety and immunogenicity in HIV-infected people. For BCG revaccination, the priority is completing the ongoing confirmation of efficacy trial. Critical modelling gaps remain on the full value proposition of vaccines, comparisons with other interventions and more realistic implementation strategies. Using carefully designed trials and modelling, we must prepare for success, to ensure that new vaccines will be promptly received by those most in need.

Potential impact of tuberculosis vaccines in China, South Africa, and India

More effective tuberculosis vaccines are needed to help reach World Health Organization tuberculosis elimination goals. Insufficient evidence exists on the potential impact of future tuberculosis vaccines with varying characteristics and in different epidemiological settings. To inform vaccine development decision making, we modeled the impact of hypothetical tuberculosis vaccines in three high-burden countries. We calibrated Mycobacterium tuberculosis (M.tb) transmission models to age-stratified demographic and epidemiological data from China, South Africa, and India. We varied vaccine efficacy to prevent infection or disease, effective in persons M.tb uninfected or infected, and duration of protection. We modeled routine early-adolescent vaccination and 10-yearly mass campaigns from 2025. We estimated median percentage population-level tuberculosis incidence rate reduction (IRR) in 2050 compared to a no new vaccine scenario. In all settings, results suggested vaccines preventing disease in M.tb-infected populations would have greatest impact by 2050 (10-year, 70% efficacy against disease, IRR 51%, 52%, and 54% in China, South Africa, and India, respectively). Vaccines preventing reinfection delivered lower potential impact (IRR 1, 12, and 17%). Intermediate impact was predicted for vaccines effective only in uninfected populations, if preventing infection (IRR 21, 37, and 50%) or disease (IRR 19, 36, and 51%), with greater impact in higher-transmission settings. Tuberculosis vaccines have the potential to deliver substantial population-level impact. For prioritizing impact by 2050, vaccine development should focus on preventing disease in M.tb-infected populations. Preventing infection or disease in uninfected populations may be useful in higher transmission settings. As vaccine impact depended on epidemiology, different development strategies may be required.

A structured Markov chain model to investigate the effects of pre-exposure vaccines in tuberculosis control

In this paper, the interest is in a structured Markov chain model to describe the transmission dynamics of tuberculosis (TB) in the setting of small communities of hosts sharing confined spaces, and to explore the potential impact of new pre-exposure vaccines on reducing the number of new TB cases during an outbreak of the disease. The model under consideration incorporates endogenous reactivation of latent tubercle bacilli, exogenous reinfection of latently infected TB hosts, loss of effectiveness of the vaccine protection, and death of hosts due to tubercle bacilli and from causes beyond TB. Various probabilistic measures are defined and analytically studied to describe extreme values and the number of vaccinations during an outbreak, and a random version of the basic reproduction number is used to measure the transmission potential during the initial phase of the epidemic. Our numerical experiments allow us to compare different pre-exposure vaccines versus the level of coverage in terms of these probabilistic measures.

A Framework for Network-Based Epidemiological Modeling of Tuberculosis Dynamics Using Synthetic Datasets

We present a framework for discrete network-based modeling of TB epidemiology in US counties using publicly available synthetic datasets. We explore the dynamics of this modeling framework by simulating the hypothetical spread of disease over 2 years resulting from a single active infection in Washtenaw County, MI. We find that for sufficiently large transmission rates that active transmission outweighs reactivation, disease prevalence is sensitive to the contact weight assigned to transmissions between casual contacts (that is, contacts that do not share a household, workplace, school, or group quarter). Workplace and casual contacts contribute most to active disease transmission, while household, school, and group quarter contacts contribute relatively little. Stochastic features of the model result in significant uncertainty in the predicted number of infections over time, leading to challenges in model calibration and interpretation of model-based predictions. Finally, predicted infections were more localized by household location than would be expected if they were randomly distributed. This modeling framework can be refined in later work to study specific county and multi-county TB epidemics in the USA.

Clinical Development of New TB Vaccines: Recent Advances and Next Steps

Mycobacterium tuberculosis (Mtb) kills more people worldwide than any single infectious pathogen, yet the only vaccine licensed against tuberculosis, Bacille Calmette Guerin (BCG) is approaching its centenary. Two recent advances in clinical tuberculosis vaccine development have invigorated the field. BCG revaccination of interferon-gamma release assay (IGRA) negative adolescents provided 45% protection against sustained Mtb infection defined by IGRA conversion; and the protein-subunit vaccine M72/AS01_E provided 50% protection against progression from Mtb infection to tuberculosis disease in IGRA-positive adults. These findings provide encouraging evidence for pre-exposure and post-exposure approaches to vaccination against tuberculosis, both of which may be necessary to rapidly interrupt the cycle of Mtb transmission and sustain long-term impact on global tuberculosis control. New trials are needed to demonstrate efficacy of M72/AS01_E with greater precision, in a wider age range, in diverse epidemic settings, and in populations that include Mtb-uninfected and HIV-infected persons. Modeling the impact of mass campaigns with M72/AS01_E and other fast-follower vaccine candidates will be crucial to make the use case and demonstrate public health value for TB endemic countries. The size and scope of the next generation of efficacy trials, and the need to expand and accelerate the existing clinical development pipeline, will require public and private consortium funding and concerted political will.

Global sensitivity analysis of biological multi-scale models

Mathematical models of biological systems need to both reflect and manage the inherent complexities of biological phenomena. Through their versatility and ability to capture behavior at multiple scales, multi-scale models offer a valuable approach. Due to the typically nonlinear and stochastic nature of multi-scale models as well as unknown parameter values, various types of uncertainty are present; thus, effective assessment and quantification of such uncertainty through sensitivity analysis is important. In this review, we discuss global sensitivity analysis in the context of multi-scale and multi-compartment models and highlight its value in model development and analysis. We present an overview of sensitivity analysis methods, approaches for extending such methods to a multi-scale setting, and examples of how sensitivity analysis can inform model reduction. Through schematics and references to past work, we aim to emphasize the advantages and usefulness of such techniques.