OBJECTIVES: To evaluate a method for adjusting estimates of HIV prevalence based on data from a program for the prevention of mother-to-child transmission (PMTCT) of HIV infection for the potential bias attributable to refusal of PMTCT-related testing. METHODS: Age-specific logistic regression models were used to estimate the HIV risk coefficients for 10 predictor variables among women who accepted the PMTCT-related testing (n = 1874) at an antenatal clinic in northern Uganda. These risk coefficients were used to predict the prevalence among women who were not tested (n = 1719) and to adjust the PMTCT-based prevalence for nonparticipation bias. Crude and adjusted PMTCT-based prevalence estimates were compared with the prevalence among women who were anonymously tested as part of routine sentinel surveillance (n = 2225). RESULTS: The PMTCT-based prevalence represented an underestimate compared with that based on anonymous surveillance in 2004 (9.0% vs. 10.5%); in 2005, it constituted an overestimate (11.8% vs. 10.9%). Adjusting the PMTCT-based prevalence reduced the difference attributable to nonparticipation bias by approximately 70% in both years, so that the adjusted prevalence (10.1% in 2004 and 11.2% in 2005) was similar to the surveillance-based prevalence. CONCLUSIONS: The adjustment method was effective in reducing the nonparticipation bias. Further studies are needed to assess the utility of PMTCT program data for HIV surveillance.
OBJECTIVES: To evaluate a method for adjusting estimates of HIV prevalence based on data from a program for the prevention of mother-to-child transmission (PMTCT) of HIV infection for the potential bias attributable to refusal of PMTCT-related testing. METHODS: Age-specific logistic regression models were used to estimate the HIV risk coefficients for 10 predictor variables among women who accepted the PMTCT-related testing (n = 1874) at an antenatal clinic in northern Uganda. These risk coefficients were used to predict the prevalence among women who were not tested (n = 1719) and to adjust the PMTCT-based prevalence for nonparticipation bias. Crude and adjusted PMTCT-based prevalence estimates were compared with the prevalence among women who were anonymously tested as part of routine sentinel surveillance (n = 2225). RESULTS: The PMTCT-based prevalence represented an underestimate compared with that based on anonymous surveillance in 2004 (9.0% vs. 10.5%); in 2005, it constituted an overestimate (11.8% vs. 10.9%). Adjusting the PMTCT-based prevalence reduced the difference attributable to nonparticipation bias by approximately 70% in both years, so that the adjusted prevalence (10.1% in 2004 and 11.2% in 2005) was similar to the surveillance-based prevalence. CONCLUSIONS: The adjustment method was effective in reducing the nonparticipation bias. Further studies are needed to assess the utility of PMTCT program data for HIV surveillance.
Authors: Samuel S Malamba; Herbert Muyinda; Patricia M Spittal; John P Ekwaru; Noah Kiwanuka; Martin D Ogwang; Patrick Odong; Paul K Kitandwe; Achilles Katamba; Kate Jongbloed; Nelson K Sewankambo; Eugene Kinyanda; Alden Blair; Martin T Schechter Journal: BMC Infect Dis Date: 2016-11-21 Impact factor: 3.090
Authors: Eline L Korenromp; S Guy Mahiané; Nico Nagelkerke; Melanie M Taylor; Rebecca Williams; R Matthew Chico; Carel Pretorius; Laith J Abu-Raddad; Jane Rowley Journal: Sci Rep Date: 2018-07-31 Impact factor: 4.379
Authors: Sheetal Patel; Martin T Schechter; Nelson K Sewankambo; Stella Atim; Noah Kiwanuka; Patricia M Spittal Journal: PLoS One Date: 2014-02-28 Impact factor: 3.240