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Review 1: "The Potential Health and Economic Impacts of New Tuberculosis Vaccines under Varying Delivery Strategies in Delhi and Gujarat, India: A Modelling Study"

Overall, reviewers had divided opinions on the strength of this preprint with some concerns about adherence to the CHEER standards. 

Published onNov 06, 2023
Review 1: "The Potential Health and Economic Impacts of New Tuberculosis Vaccines under Varying Delivery Strategies in Delhi and Gujarat, India: A Modelling Study"
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key-enterThis Pub is a Review of
The potential health and economic impacts of new tuberculosis vaccines under varying delivery strategies in Delhi and Gujarat, India: a modelling study
The potential health and economic impacts of new tuberculosis vaccines under varying delivery strategies in Delhi and Gujarat, India: a modelling study

Abstract Background India has the largest tuberculosis burden globally, but this burden varies nationwide. All-age tuberculosis prevalence in 2021 ranged from 747/100,000 in Delhi to 137/100,000 in Gujarat. Previous modelling has demonstrated the benefits and costs of introducing novel tuberculosis vaccines in India overall. However, no studies have compared the potential impact of tuberculosis vaccines in regions within India with differing tuberculosis disease and infection prevalence. We used mathematical modelling to investigate how the health and economic impact of two potential tuberculosis vaccines, M72/AS01E and BCG-revaccination, could differ in Delhi and Gujarat under varying delivery strategies.Methods We applied a compartmental tuberculosis model separately for Delhi (higher disease and infection prevalence) and Gujarat (lower disease and infection prevalence), and projected epidemiological trends to 2050 assuming no new vaccine introduction. We simulated M72/AS01E and BCG-revaccination scenarios varying target ages and vaccine characteristics. We estimated cumulative cases, deaths, and disability-adjusted life years averted between 2025–2050 compared to the no-new-vaccine scenario and compared incremental cost-effectiveness ratios to three cost-effectiveness thresholds.Results M72/AS01E averted a higher proportion of tuberculosis cases than BCG-revaccination in both regions (Delhi: 16.0% vs 8.3%, Gujarat: 8.5% vs 5.1%) and had higher vaccination costs (Delhi: USD$118 million vs USD$27 million, Gujarat: US$366 million vs US$97 million). M72/AS01E in Delhi could be cost-effective, or even cost-saving, for all modelled vaccine characteristics. M72/AS01E could be cost-effective in Gujarat, unless efficacy was assumed only for those with current infection at vaccination. BCG-revaccination could be cost-effective, or cost-saving, in both regions for all modelled vaccine scenarios.Discussion M72/AS01E and BCG-revaccination could be impactful and cost-effective in Delhi and Gujarat. Differences in impact, costs, and cost-effectiveness between vaccines and regions, were determined partly by differences in disease and infection prevalence, and demography. Age-specific regional estimates of infection prevalence could help to inform delivery strategies for vaccines that may only be effective in people with a particular infection status. Evidence on the mechanism of effect of M72/AS01E and its effectiveness in uninfected individuals, which were important drivers of impact and cost-effectiveness, particularly in Gujarat, are also key to improve estimates of population-level impact.

RR:C19 Evidence Scale rating by reviewer:

  • Reliable. The main study claims are generally justified by its methods and data. The results and conclusions are likely to be similar to the hypothetical ideal study. There are some minor caveats or limitations, but they would/do not change the major claims of the study. The study provides sufficient strength of evidence on its own that its main claims should be considered actionable, with some room for future revision.



The authors conducted an important analysis comparing programs for a prospective M72/AS01Evaccine and BCG vaccine in two locations in India that will be a contribution to the literature. Below are three main concerns, and several additional comments.

I’m not familiar with the authors use of the terms infection and disease in tuberculosis (TB) research. People refer to latent TB and active TB. Latent TB does not have symptoms and cannot be spread but could develop into active TB when the immune system weakens due to comorbidity, malnutrition, or other reasons. Active TB requires treatment and can be spread. I encourage the authors to use these terms, if appropriate, or explain why they diverge from the usual definitions. Additionally, what does the term “subclinical” mean in this context?

The terms infection and disease are problematic throughout the manuscript. For example, when the authors refer to prevalence, do they mean latent TB or active TB prevalence? Does the term “case” refer to someone with active TB? When the authors refer to disease progression, does their model have a fixed rate of progression from latent to active TB as opposed to a transition based on a weakened immune system? 

In addition, the authors should consider elaborating on the distinction between efficacy against disease with any infection status, and against disease with current infection in the M72/AS01E scenarios, and efficacy against infection for those with no infection, and any infection in the BCG scenarios. For example, for the Covid 19 vaccine, people are discouraged from being vaccinated when infected, and researchers distinguish between efficacy against infection and efficacy against severe disease. Are the authors proposing a scenario where the M72/AS01E would potentially replace treatment for latent TB (i.e. “efficacy against disease with current infection”)?

It would be helpful to present a comparison between the M72/AS01E and BCG vaccines in Figure 3, which could be readily done by putting results for both vaccines on the same figure. In Delhi, the ICER for the BCG vaccine is lower than the ICER for M72/AS01E in the base case, but not other scenarios. In Gujarat, the ICERs for the BCG vaccine are lower than all the ICERs for M72/AS01E. I would also recommend including a sensitivity analysis with the cost and efficacy at which the ICER for the M72/AS01E vaccine would be below the BCG vaccine in the relevant scenarios.

Many people are dismissive of the BCG vaccine and waiting for new TB vaccines to be available. This preprint’s analysis highlights scenarios in which the BCG vaccine is more cost-effective than the new vaccine candidate and would suggest that the delay is unnecessary. If the authors believe their results, make this point more forcefully in the abstract and discussion. If they don’t believe them, explain why caution is warranted.

Additional comments.

The axes in Figure 3 should be reversed. The cost-effectiveness plane is generally presented with health outcomes on the horizontal axis and cost on the vertical axis, as the authors do in Figure 4. It's an unnecessary burden to the reader to switch back and forth.

The last sentence on Page 3/Data subsection is unclear. Do the authors mean population for each age, location and year with no uncertainty? Does the UN project population by location, or do the authors take the national projections and assume that the growth rate is the same in every age and location?

For the 2nd sentence on Page 3/Model Structure and Calibration section, the authors should explain the term “history matching and emulation”. For the 3rd sentence, the authors should explicitly state which three targets the model was fitted to. The final sentence is also unclear. What prevalence rate is used for Gujarat? 137 for all or 383 for adults and something else for children? Are the prevalence rates in Delhi not age-specific?

Figure 2 repeats the information in Table 2 and is not a good use of the main text. It could be replaced with a table that summarizes the key parameters in the model, which is a standard reporting practice in cost-effectiveness analyses. For example, what are the costs for diagnosis and treatment and their sources. What disability weight was used for active TB? What is the population in Delhi and Gujarati? What are the case fatality rates (deaths per case of active TB)? Are these case fatality rates the same in each location so that the different mortality per person reflects differences in prevalence of active TB?

On page 6, much of the results section repeats information in the tables and figures, when a better use of the text is to explain the results. For example, in the last paragraph, the authors could explain how delivering the BCG vaccine to an older population decreased the number of cases and deaths in Delhi; isn’t the prevalence the same in all age groups? Is the difference due to the age structure of the population?

On page 8/2nd paragraph/1st sentence, the authors should explain what parameters are driving the results that Older Ages and All-Adults BCG vaccination scenarios were dominated by the Base case scenario.

On page 9/2nd paragraph/3rd sentence, the phrase “Therefore those with current infection would have an immediately lower rate of disease progression” makes no sense in the context of TB. Are the authors referring to latent TB cases who would not develop active TB, people with active and unnotified TB, or people with active subclinical TB?

On page 10/last paragraph/2nd sentence, according to the introduction, the prevalence rate in Gujarat (137) is equal to the notification rate (137). Do the authors mean that the uncertainty interval for the prevalence rate is broader than the notification rate? In that case, the prevalence rate would be lower than and greater than the notification rate for some draws.

On page 11/2nd paragraph/1st sentence, do the authors use all available demographic data and projections from just the UN estimates? The authors should note that demographic data and projections are also available from the US Census Bureau International Database, the Wittgenstein Centre for Demography and Human Capital, and the Global Burden of Disease, Injuries and Risk factor study. (Wang H, et al. Lancet 2020; 1160–1203, and Vollset SE et al. Lancet 2020; 1285-1306)

Additionally, on page 11, please consider adding that the analysis does not address multidrug resistant TB as a limitation.

Lastly, the authors should complete the CHEERS checklist and report it in the appendix, if you haven’t done it already. (

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