What
This study examined migrant-associated tuberculosis (TB) transmission dynamics in highly endemic regions of Taiwan and evaluated the potential impact of multiple control strategies. The investigation focused on three major administrative areas—Taoyuan City, Taichung City, and New Taipei City—where large migrant worker populations overlap with persistent TB burden. Migrant workers, primarily from Vietnam, the Philippines, and Indonesia, increased substantially between 2013 and 2019, with Vietnam and the Philippines accounting for 43% and 28% of migrant workers, respectively, by 2019. Concurrently, TB incidence rates in migrant source countries remained markedly higher than in Taiwan, with the Philippines reporting 554 cases per 100,000 population compared with 37 per 100,000 in Taiwan, highlighting a potential pathway for cross-population transmission.
The study further documented epidemiological trends showing that TB cases among migrant workers rose between 2006 and 2014 and subsequently stabilized at approximately 600–700 confirmed cases annually. Among 6,416 total migrant TB cases reported between 2006 and 2019, Indonesia contributed the largest proportion (47%), followed by the Philippines (25%), Vietnam (18%), and Thailand (9%). These findings underscored the persistent contribution of migrant populations to TB burden in Taiwan and justified modeling efforts that explicitly incorporated migrant-local transmission dynamics. Sensitivity analyses demonstrated that transmission rates within migrant and local populations were key drivers of projected infection trends, with model projections indicating that both migrant and local infectious populations would peak around 2022–2023 in hotspot cities.
Simulation of control strategies revealed that social distancing was the most effective single intervention for reducing the combined population of latently infected and infectious individuals. In five-year projections, high-intensity distancing measures reduced infections by up to approximately 80% in Taoyuan City, 85% in Taichung City, and 97% in New Taipei City. Early screening and directly observed therapy short-course (DOTS) also demonstrated measurable reductions but were consistently less effective when implemented individually. These findings indicated that interventions targeting transmission prevention yielded stronger reductions than those focused solely on detection or treatment.
Combination strategies produced greater reductions in TB burden, particularly when social distancing was paired with early screening or DOTS. Dual strategies achieved reductions of up to approximately 96% in five-year projections, while triple-intervention strategies provided only marginal additional benefit of approximately 1–3%. The authors concluded that dual-intervention approaches offered the optimal balance between effectiveness and resource allocation, suggesting that combined distancing and early screening may provide the most efficient TB control strategy in migrant-dense settings.
How
This study employed a population-based dynamic modeling approach using an enhanced migrant-based susceptible–latent–infectious–recovered (SLTR) transmission framework. The total population was divided into migrant and local subpopulations, each further categorized into susceptible, latently infected, infectious, and recovered compartments. This structure enabled modeling of bidirectional TB transmission between migrant and local populations, incorporating both within-group and cross-group transmission pathways. The model extended previous frameworks by explicitly including transmission from infectious local individuals to migrant populations, thereby capturing more realistic interaction dynamics in high-density urban regions.
Model parameterization relied on a large-scale meta-analysis combined with national surveillance data. Demographic data for migrant workers between 2013 and 2019 were obtained from Taiwan’s Workforce Development Agency, while TB incidence data for Taiwan and migrant source countries were derived from Taiwan Centers for Disease Control and the World Health Organization. Historical TB case data from 2006 to 2019 were also incorporated to calibrate model assumptions and validate projections. These datasets informed transmission rates, reactivation parameters, and population dynamics within the three selected hotspot cities.
Sensitivity analyses were conducted to evaluate the impact of key transmission parameters and reactivation rates on projected TB dynamics. The modeling results demonstrated that transmission rates within migrant and local populations exerted the strongest influence on infection trajectories, while increases in reactivation rates produced gradual growth in infectious populations without significantly affecting susceptible populations. These analyses strengthened the robustness of the model and identified critical parameters influencing TB spread.
The study then simulated three primary interventions—social distancing, early screening, and DOTS—both individually and in combination. Control intensities were varied across short-term (two-year) and long-term (five-year) projections to assess effectiveness. Dual- and triple-intervention strategies were further modeled to evaluate synergistic effects, using predefined control intensities to simplify comparisons. The modeling framework ultimately allowed estimation of percentage reductions in latently infected and infectious populations under multiple policy scenarios, providing evidence-based insights for optimizing TB control strategies in migrant-dense regions.
Source: Chen, S.C., Wang, T.Y., Tsai, H.C., Chen, C.Y., Lu, T.H., Lin, Y.J., You, S.H., Yang, Y.F. and Liao, C.M., 2022. Demographic Control Measure Implications of Tuberculosis Infection for Migrant Workers across Taiwan Regions. International journal of environmental research and public health, 19(16), p.9899.
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