Mycobacterial ecology as a modulator of tuberculosis vaccine success

Dynamics and optimal control of tuberculosis model with the combined effects of vaccination, treatment and contaminated environments

Tuberculosis has affected human beings for thousands of years, and until today, tuberculosis still ranks third among 29 infectious diseases in China. However, most of the existing mathematical models consider a single factor, which is not conducive to the study of tuberculosis transmission dynamics. Therefore, this study considers the combined effects of vaccination, treatment, and contaminated environments on tuberculosis, and builds a new model with seven compartments of $ SVEITRW $ based on China's tuberculosis data. The study shows that when the basic reproduction number $ R_{0} $ is less than 1, the disease will eventually disappear, but when $ R_{0} $ is greater than 1, the disease may persist. In the numerical analysis part, we use Markov-chain Monte-Carlo method to obtain the optimal parameters of the model. Through the next generation matrix theory, we calculate that the $ R_{0} $ value of tuberculosis in China is $ 2.1102 $, that is, if not controlled, tuberculosis in China will not disappear over time. At the same time, through partial rank correlation coefficients, we find the most sensitive parameter to the basic reproduction number $ R_{0} $. On this basis, we combine the actual prevalence of tuberculosis in China, apply Pontryagin's maximum principle, and perform cost-effectiveness analysis to obtain the conditions required for optimal control. The analysis shows that four control strategies could effectively reduce the prevalence of TB, and simultaneously controlling $ u_{2}, u_{3}, u_{4} $ is the most cost-effective control strategy.

The prevention and control of tuberculosis: an analysis based on a tuberculosis dynamic model derived from the cases of Americans

Background

Tuberculosis (TB), a preventable and curable disease, is claimed as the second largest number of fatalities, and there are 9,025 cases reported in the United States in 2018. Many researchers have done a lot of research and achieved remarkable results, but TB is still a severe problem for human beings. The study is a further exploration of the prevention and control of tuberculosis.

Methods

In the paper, we propose a new dynamic model to study the transmission dynamics of TB, and then use global differential evolution and local sequential quadratic programming (DESQP) optimization algorithm to estimate parameters of the model. Finally, we use Latin hypercube sampling (LHS) and partial rank correlation coefficients (PRCC) to analyze the influence of parameters on the basic reproduction number (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\mathcal R_{0}$\end{document}R0) and the total infectious (including the diagnosed, undiagnosed and incomplete treatment infectious), respectively.

Results

According to the research, the basic reproduction number is computed as 2.3597 from 1984 to 2018, which means TB is also an epidemic in the US. The diagnosed rate is 0.6082, which means the undiagnosed will be diagnosed after 1.6442 years. The diagnosed will recover after an average of 1.9912 years. Moreover, some diagnosed will end the treatment after 1.7550 years for some reason. From the study, it’s shown that 2.40% of the recovered will be reactivated, and 13.88% of the newborn will be vaccinated. However, the immune system will be lost after about 19.6078 years.

Conclusion

Through the results of this study, we give some suggestions to help prevent and control the TB epidemic in the United States, such as prolonging the protection period of the vaccine by developing new and more effective vaccines to prevent TB; using the Chemoprophylaxis for incubation patients to prevent their conversion into active TB; raising people’s awareness of the prevention and control of TB and treatment after illness; isolating the infected to reduce the spread of TB. According to the latest report in the announcement that came at the first WHO Global Ministerial Conference on Ending tuberculosis in the Sustainable Development Era, we predict that it is challenging to control TB by 2030.

On the impact of masking and blocking hypotheses for measuring the efficacy of new tuberculosis vaccines

Over the past 60 years, the Mycobacterium bovis bacille Calmette–Guérin (BCG) has been used worldwide to prevent tuberculosis (TB). However, BCG has shown a very variable efficacy in different trials, offering a wide range of protection in adults against pulmonary TB. One of the most accepted hypotheses to explain these inconsistencies points to the existence of a pre-existing immune response to antigens that are common to environmental sources of mycobacterial antigens and Mycobacterium tuberculosis. Specifically, two different mechanisms have been hypothesized to explain this phenomenon: the masking and the blocking effects. According to masking hypothesis, previous sensitization confers some level of protection against TB that masks vaccine’s effects. In turn, the blocking hypothesis postulates that previous immune response prevents vaccine taking of a new TB vaccine. In this work we introduce a series of models to discriminate between masking and blocking mechanisms and address their relative likelihood. We apply our methodology to the data reported by BCG-REVAC clinical trials, which were specifically designed for studying BCG efficacy variability. Our results yield estimates that are consistent with high levels of blocking (41% in Manaus -95% CI [14–68]- and 96% in Salvador -95% CI [52–100]-). Moreover, we also show that masking does not play any relevant role in modifying vaccine’s efficacy either alone or in addition to blocking. The quantification of these effects around a plausible model constitutes a relevant step towards impact evaluation of novel anti-tuberculosis vaccines, which are susceptible of being affected by similar effects, especially if applied on individuals previously exposed to mycobacterial antigens.

Rhesus immune responses to SIV Gag expressed by recombinant BCG vectors are independent from pre-existing mycobacterial immunity

BACKGROUND

A recombinant Mycobacterium bovis BCG (rBCG) vector expressing HIV transgenes is an attractive candidate as a dual vaccine against HIV and TB. However, pre-existing immune responses to mycobacteria may influence immune responses to rBCG. We analyzed data from a rhesus rBCG trial to determine the effect of pre-existing mycobacterial immune responses on the vaccine-induced responses to the vector and expressed transgene.

METHODS

Indian-origin rhesus macaques were primed with rBCG expressing simian immunodeficiency virus (SIV) Gag and boosted with attenuated vaccinia NYVAC gag-pol. Mycobacteria responses were measured by Mycobacterium tuberculosis (Mtb) purified protein derivative (PPD) interferon-γ ELISpot and Mtb whole cell lysate (WCL) ELISA. SIV Gag responses were measured by SIV Gag ELISpot and by p11C tetramer binding.

RESULTS

Baseline Mtb PPD ELISpot responses and Mtb WCL antibody responses in rhesus macaques overlapped those in human populations. Cellular and antibody responses boosted sharply 4 weeks after rBCG vaccination. Mtb WCL antibody titers at 4 weeks correlated with baseline titers. Primates vaccinated with rBCG developed strong SIV Gag ELISpot and p11C tetramer responses after rBCG prime and NYVAC boost. There were no correlations between the pre-existing mycobacterial immune responses and the SIV Gag T cell responses after vaccination.

CONCLUSIONS

Rhesus immune responses to SIV Gag expressed by rBCG vectors were independent from pre-existing anti-mycobacterial immunity. Rhesus macaques may serve as a surrogate for investigations of pre-existing anti-mycobacterial immunity in humans.