OBJECTIVE: To explore dynamic characteristics of the HIV mother to child transmission (MTCT) epidemic in China. METHODS: A deterministic dynamic transmission model was used to determine the effect of key parameters on the likely long-term trends of the HIV MTCT epidemic in China. Matlab 7.0 was used to develop the model. RESULTS: The number of the susceptibles (S), the transmission rate (β), and the screening proportion (α) of HIV positive pregnant women have the greatest impact on the HIV MTCT epidemic in China. The growth of the MTCT epidemic in China could not be controlled only by decreasing the MTCT transmission rate. The prevalence of HIV positive women should be reduced and more pregnant women should be tested for HIV. CONCLUSION: Prevention of MTCT (PMTCT) should focus not only on the reduction of HIV transmission rates and incidences of HIV among women but also on the increase of HIV testing for pregnant women. The most cost-effective PMTCT means for China should be investigated in future studies.
OBJECTIVE: To explore dynamic characteristics of the HIV mother to child transmission (MTCT) epidemic in China. METHODS: A deterministic dynamic transmission model was used to determine the effect of key parameters on the likely long-term trends of the HIV MTCT epidemic in China. Matlab 7.0 was used to develop the model. RESULTS: The number of the susceptibles (S), the transmission rate (β), and the screening proportion (α) of HIV positive pregnant women have the greatest impact on the HIV MTCT epidemic in China. The growth of the MTCT epidemic in China could not be controlled only by decreasing the MTCT transmission rate. The prevalence of HIV positive women should be reduced and more pregnant women should be tested for HIV. CONCLUSION: Prevention of MTCT (PMTCT) should focus not only on the reduction of HIV transmission rates and incidences of HIV among women but also on the increase of HIV testing for pregnant women. The most cost-effective PMTCT means for China should be investigated in future studies.
Authors: G B Scott; C Hutto; R W Makuch; M T Mastrucci; T O'Connor; C D Mitchell; E J Trapido; W P Parks Journal: N Engl J Med Date: 1989-12-28 Impact factor: 91.245
Authors: M Lallemant; G Jourdain; S Le Coeur; S Kim; S Koetsawang; A M Comeau; W Phoolcharoen; M Essex; K McIntosh; V Vithayasai Journal: N Engl J Med Date: 2000-10-05 Impact factor: 91.245
Authors: Hoosen M Coovadia; Nigel C Rollins; Ruth M Bland; Kirsty Little; Anna Coutsoudis; Michael L Bennish; Marie-Louise Newell Journal: Lancet Date: 2007-03-31 Impact factor: 79.321
Authors: Kunjal Patel; Miguel A Hernán; Paige L Williams; John D Seeger; Kenneth McIntosh; Russell B Van Dyke; George R Seage Journal: Clin Infect Dis Date: 2008-02-15 Impact factor: 9.079