Estimating the long-term effects of mass screening for latent and active tuberculosis in the Marshall Islands

Abstract

Background: Ambitious population-based screening programmes for latent and active tuberculosis (TB) were implemented in the Republic of the Marshall Islands in 2017 and 2018.

Methods: We used a transmission dynamic model of TB informed by local data to capture the Marshall Islands epidemic's historical dynamics. We then used the model to project the future epidemic trajectory following the active screening interventions, as well as considering a counterfactual scenario with no intervention. We also simulated future scenarios including periodic interventions similar to those previously implemented, to assess their ability to reach the End TB Strategy targets and TB pre-elimination in the Marshall Islands.

Results: The screening activities conducted in 2017 and 2018 were estimated to have reduced TB incidence and mortality by around one-third in 2020, and are predicted to achieve the End TB Strategy milestone of 50% incidence reduction by 2025 compared with 2015. Screening interventions had a considerably greater impact when latent TB screening and treatment were included, compared with active case finding alone. Such combined programmes implemented at the national level could achieve TB pre-elimination around 2040 if repeated every 2 years.

Conclusions: Our model suggests that it would be possible to achieve TB pre-elimination by 2040 in the Marshall Islands through frequent repetition of the same interventions as those already implemented in the country. It also highlights the importance of including latent infection testing in active screening activities.

Keywords: Mycobacterium tuberculosis infection; active case-finding; latent tuberculosis infection; mass screening; post-exposure prevention.

Figure 1

Illustration of the model structure. Boxes represent the different compartments types: susceptible (S), early latent (E), late latent (L), infectious (I), on treatment (T) and recovered (R). The subscripts indicate whether compartments are stratified by age (a), geography (g) and form of tuberculosis (f). Blue and orange arrows represent progression flows and transmission flows, respectively. The flows associated with the modelled interventions are shown in purple. ACF, active case finding

Figure 2

Comparison between model outputs and local data for the calibration targets. The black dots represent local empirical data. The model predictions are represented in blue as median (solid line), interquartile credible interval (dark shade) and 95% central credible interval (light blue shade). The effect of the 2017-18 interventions was included in these projections. TB, tuberculosis

Figure 3

Projected effect of the active screening interventions implemented in 2017 and 2018. The solid lines represent the median estimates. The shaded areas show the interquartile credible intervals (dark shade) and 95% credible intervals (light shade) projected in the absence of any intervention (pink) and under a scenario including the interventions implemented in 2017-18 in Majuro and Ebeye (blue). TB, tuberculosis; LTBI, latent tuberculosis infection

Figure 4

Projected effect of periodic community-wide interventions. The solid lines represent the median estimates, and the shaded areas show the interquartile credible intervals. The ‘status-quo’ scenario is represented in blue in all panels. The left column of panels presents scenarios including nationwide active case finding (ACF) repeated every 2 years (purple) or every 5 years (orange) or every 10 years (green). The right column of panels presents nationwide ACF scenarios combined with mass latent infection screening and treatment, repeated every 2 years (purple) or 5 years (red). The light and dark grey dots show the 2025 milestones and the 2035 targets, respectively, according to the End TB Strategy. TB, tuberculosis; ACF, active case finding

Figure 5

Results of the sensitivity analysis considering different rates of latent tuberculosis importation in the future. This analysis considered the ‘status-quo’ scenario including the 2017-18 interventions. We assumed an immigration rate of 300 per year. We used the maximum likelihood estimates obtained during calibration (i.e. the best-fitted run) to inform the parameters used in this analysis. TB, tuberculosis; LTBI, latent tuberculosis infection

Figure 6

Estimated tuberculosis disease episodes and tuberculosis deaths averted by active screening interventions, compared with serious adverse effects induced by preventive treatment. Coloured bars show the median estimates and the thin black bars indicate the 95% credible intervals. Numbers of tuberculosis disease episodes, tuberculosis deaths and serious adverse events were cumulated over the period 2017-50. TB, tuberculosis; LTBI, latent tuberculosis infection