Updating age-specific contact structures to match evolving demography in a dynamic mathematical model of tuberculosis vaccination.

We investigated the effects of updating age-specific social contact matrices to match evolving demography on vaccine impact estimates. We used a dynamic transmission model of tuberculosis in India as a case study. We modelled four incremental methods to update contact matrices over time, where each method incorporated its predecessor: fixed contact matrix (M0), preserved contact reciprocity (M1), preserved contact assortativity (M2), and preserved average contacts per individual (M3). We updated the contact matrices of a deterministic compartmental model of tuberculosis transmission, calibrated to epidemiologic data between 2000 and 2019 derived from India. We additionally calibrated the M0, M2, and M3 models to the 2050 TB incidence rate projected by the calibrated M1 model. We stratified age into three groups, children (<15y), adults (≥15y, <65y), and the elderly (≥65y), using World Population Prospects demographic data, between which we applied POLYMOD-derived social contact matrices. We simulated an M72-AS01E-like tuberculosis vaccine delivered from 2027 and estimated the per cent TB incidence rate reduction (IRR) in 2050 under each update method. We found that vaccine impact estimates in all age groups remained relatively stable between the M0-M3 models, irrespective of vaccine-targeting by age group. The maximum difference in impact, observed following adult-targeted vaccination, was 7% in the elderly, in whom we observed IRRs of 19% (uncertainty range 13-32), 20% (UR 13-31), 22% (UR 14-37), and 26% (UR 18-38) following M0, M1, M2 and M3 updates, respectively. We found that model-based TB vaccine impact estimates were relatively insensitive to demography-matched contact matrix updates in an India-like demographic and epidemiologic scenario. Current model-based TB vaccine impact estimates may be reasonably robust to the lack of contact matrix updates, but further research is needed to confirm and generalise this finding.

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.

Affordability of Adult Tuberculosis Vaccination in India and China: A Dynamic Transmission Model-Based Analysis.

New tuberculosis vaccines have made substantial progress in the development pipeline. Previous modelling suggests that adolescent/adult mass vaccination may cost-effectively contribute towards achieving global tuberculosis control goals. These analyses have not considered the budgetary feasibility of vaccine programmes. We estimate the maximum total cost that the public health sectors in India and China should expect to pay to introduce a M72/AS01E-like vaccine deemed cost-effective at country-specific willingness to pay thresholds for cost-effectiveness. To estimate the total disability adjusted life years (DALYs) averted by the vaccination programme, we simulated a 50% efficacy vaccine providing 10-years of protection in post-infection populations between 2027 and 2050 in India and China using a dynamic transmission model of M. tuberculosis. We investigated two mass vaccination strategies, both delivered every 10-years achieving 70% coverage: Vaccinating adults and adolescents (age ≥10y), or only the most efficient 10-year age subgroup (defined as greatest DALYs averted per vaccine given). We used country-specific thresholds for cost-effectiveness to estimate the maximum total cost (Cmax) a government should be willing to pay for each vaccination strategy. Adult/adolescent vaccination resulted in a Cmax of $21 billion (uncertainty interval [UI]: 16-27) in India, and $15B (UI:12-29) in China at willingness to pay thresholds of $264/DALY averted and $3650/DALY averted, respectively. Vaccinating the highest efficiency age group (India: 50-59y; China: 60-69y) resulted in a Cmax of $5B (UI:4-6) in India and $6B (UI:4-7) in China. Mass vaccination against tuberculosis of all adults and adolescents, deemed cost-effective, will likely impose a substantial budgetary burden. Targeted tuberculosis vaccination, deemed cost-effective, may represent a more affordable approach.