| Literature DB >> 31781529 |
Lei Zhang1,2,3,4,5, Xia Zou1, Yong Xu1, Nick Medland3, Liwei Deng1, Yin Liu1, Shu Su2, Li Ling1.
Abstract
Objectives: We aimed to conduct a comprehensive evaluation of the population impact of methadone maintenance treatment (MMT) for its future program planning.Entities:
Keywords: economic benefit; hepatitis C; human immunodeficiency virus; mathematical model; methadone maintenance treatment
Year: 2019 PMID: 31781529 PMCID: PMC6861367 DOI: 10.3389/fpubh.2019.00327
Source DB: PubMed Journal: Front Public Health ISSN: 2296-2565
Figure 1Temporal trend of number of MMT clinics and the coverage of MMT (%) in China, 2004–2014 (The number of MMT clinics was sourced from Annual Report on Drug Control in China, 2005–2015, whereas the coverage of MMT was calculated by dividing the number of individuals on MMT by the total number of registered DUs over these years).
Figure 2Comparison of risk behaviors in DUs at MMT enrolment and 12 months after treatment initiation. MMT entrants are regarded as a proxy of community DUs. Its comparison with MMT clients after 12-month treatment provides empirical evidence about how MMT may have changed DUs' risk behaviors. The two sets of parameters were subsequently fed into the model as input parameters to inform the calculation of HIV/HCV transmission probability [Data sources: a published meta-analysis (15) and MMT clinical database of Guangdong province, 2006–2014 (8)].
Figure 3HIV and HCV epidemic trends among DUs and IDUs in the presence of MMT program (status quo) and absence of the program (hypothetical), 2005–2015.
Evaluation of population impacts and cost-effectiveness of the Chinese MMT program during 2004–2015.
| Number of clinics | 34 | 42 | 320 | 503 | 600 | 668 | 700 | 738 | 755 | 763 | 767 | – | 767 | ||
| MMT participants (×1000) | 3.0 | 4.1 | 37.0 | 58.0 | 93.7 | 110.0 | 130.0 | 134.0 | 208.0 | 201.7 | 187.0 | 231.9 | 410.0 | ||
| MMT coverage (%) | 0.3 | 0.4 | 4.6 | 6.1 | 8.3 | 8.2 | 8.4 | 7.5 | 9.9 | 8.2 | 6.3 | – | 6.3 | ||
| MMT spending (USD $m) | 3.5 | 4.5 | 36.7 | 57.7 | 79.4 | 90.9 | 101.7 | 105.9 | 139.1 | 136.9 | 130.7 | 150.2 | 1037.3 | ||
| Mean MMT spending perperson-year ($) | 1173.8 | 1089.5 | 993.0 | 994.5 | 847.9 | 826.5 | 782.1 | 790.0 | 668.7 | 678.5 | 699.2 | 647.9 | 2529.3 | ||
| HIV infections averted (×1000) | – | 0.1 | 0.3 | 0.8 | 1.3 | 1.9 | 2.6 | 3.5 | 4.4 | 5.2 | 5.7 | 6.3 | 29.5 | $35.2 | |
| HCV infections averted (×1000) | – | 0 | 0.1 | 0.1 | 0.2 | 0.4 | 0.6 | 0.8 | 1.1 | 1.3 | 1.6 | 1.9 | 130.6 | $7.9 | |
| Drug-use person-years averted (×1000) | – | 6.3 | 19.1 | 36.6 | 53.2 | 72.4 | 94.3 | 117.7 | 142.1 | 150 | 140.8 | 135.6 | 914.2 | $1.1 | |
| HIV-related deaths averted | – | 12 (12,13) | 55 | 149 | 290 | 459 | 656 | 906 | 1194 | 1510 | 1822 | 2128 | 8305.8 | $124.9 | |
| HCV-related deaths averted | – | 10 (10,10) | 96 | 354 | 849 | 1566 | 2448 | 3470 | 4612 | 5852 | 6997 | 7826 | 793.5 | $1307.2 | $96.2 |
| Harm-related deaths averted | – | 9 (9,9) | 25 (25,26) | 49 (48,49) | 69 | 92 | 117 | 141 | 165 | 165 | 139 | 117 | 1043.3 | $994.2 | |
| HIV-related DALY averted (×1000) | – | 0 | 0.2 | 0.5 | 1 (1,1) | 1.6 | 2.1 | 2.9 | 3.7 | 4.6 | 5.5 | 6.8 | 26.0 | 39.9 | |
| HCV-related DALY averted (×1000) | – | 0.1 | 0.4 | 0.9 | 1.6 | 2.5 | 3.5 | 4.6 | 5.9 | 7.1 | 8 | 8.7 | 30.9 | 33.6 | $3.1 |
| Harm-related DALY averted (×1000) | – | 2.8 | 8.3 | 15.6 | 22.2 | 29.5 | 37.2 | 45 | 52.7 | 54 | 49.1 | 45.6 | 344.1 | 3.0 | |
| Spending on HIV care/ treatment saved ($m) | – | −0.2 | −0.6 | −1.6 | −2.6 | −2.6 | −1.1 | 0.9 | 4.3 | 8.9 | 14.5 | 20.4 | 31.7 | $0.03 | |
| Spending on HCV care /treatment saved ($m) | – | 0.1 | 0.8 | 3.0 | 7.3 | 13.9 | 22.3 | 31.5 | 41.9 | 52.9 | 62.2 | 68.4 | 276.6 | $0.3 | $6.7 |
| Reduction in drug cost ($m) | – | 48.2 | 152 | 298 | 433 | 576.4 | 724.2 | 875.1 | 1024.5 | 1049.5 | 958 | 900.1 | 6683.1 | $6.4 | |