TY - JOUR
T1 - Timing of tuberculosis transmission and the impact of household contact tracing
T2 - An agent-based simulation model
AU - Kasaie, Parastu
AU - Andrews, Jason R.
AU - Kelton, W. David
AU - Dowdy, David W.
PY - 2014/4/1
Y1 - 2014/4/1
N2 - Rationale: Household contact tracing has recently been endorsed for global tuberculosis (TB) control, but its potential population-level impact remains uncertain. Objectives: To project the maximum impact of household contact tracing for TB in a moderate-burden setting. Methods: We developed a stochastic, agent-based simulation model of a simplified TB epidemic, calibrated to a setting of moderate TB incidence. We used data from the literature to generate "community-driven" and "household-driven" scenarios in which 22 and 50% of TB transmission occurred within the household, respectively. In each scenario, we simulated an intervention in which the household members are screened and treated for TB at the time of an index patient's active TB diagnosis. Measurements and Main Results: By the time of TB diagnosis, 75 to 95% of initial household infections had already occurred, but only 1.5 to 3.0% of contacts had sufficient time to progress to active TB. With 100% sensitive tracing of all contacts for 5 consecutive years, TB incidence declined by 10 to 15%, with a mean year-over-year decline of 2% per year. Effects were sustained for many years after stopping the intervention. Providing preventive therapy with contact tracing nearly doubled this impact (17-27% decline in incidence). Impact was proportional to sensitivity and coverage; thus, if 50% of contacts were screened with a 50% sensitive test, TB incidence declined by only 0.5% per year. Conclusions: Household contact tracing is unlikely to transform TB epidemiology in isolation but has the potential, especially with provision of preventive therapy, to augment a comprehensive package of interventions that could substantially reduce the population-level burden of TB.
AB - Rationale: Household contact tracing has recently been endorsed for global tuberculosis (TB) control, but its potential population-level impact remains uncertain. Objectives: To project the maximum impact of household contact tracing for TB in a moderate-burden setting. Methods: We developed a stochastic, agent-based simulation model of a simplified TB epidemic, calibrated to a setting of moderate TB incidence. We used data from the literature to generate "community-driven" and "household-driven" scenarios in which 22 and 50% of TB transmission occurred within the household, respectively. In each scenario, we simulated an intervention in which the household members are screened and treated for TB at the time of an index patient's active TB diagnosis. Measurements and Main Results: By the time of TB diagnosis, 75 to 95% of initial household infections had already occurred, but only 1.5 to 3.0% of contacts had sufficient time to progress to active TB. With 100% sensitive tracing of all contacts for 5 consecutive years, TB incidence declined by 10 to 15%, with a mean year-over-year decline of 2% per year. Effects were sustained for many years after stopping the intervention. Providing preventive therapy with contact tracing nearly doubled this impact (17-27% decline in incidence). Impact was proportional to sensitivity and coverage; thus, if 50% of contacts were screened with a 50% sensitive test, TB incidence declined by only 0.5% per year. Conclusions: Household contact tracing is unlikely to transform TB epidemiology in isolation but has the potential, especially with provision of preventive therapy, to augment a comprehensive package of interventions that could substantially reduce the population-level burden of TB.
KW - Contact tracing
KW - Epidemiology
KW - Models
KW - Theoretical
KW - Tuberculosis
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U2 - 10.1164/rccm.201310-1846OC
DO - 10.1164/rccm.201310-1846OC
M3 - Article
C2 - 24559425
AN - SCOPUS:84897440540
SN - 1073-449X
VL - 189
SP - 845
EP - 852
JO - American journal of respiratory and critical care medicine
JF - American journal of respiratory and critical care medicine
IS - 7
ER -