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   <ref-type name="Journal Article">17</ref-type>
   <contributors>
    <authors>
     <author>Wang, Haidong</author>
     <author>Wolock, Tim M</author>
     <author>Carter, Austin</author>
    </authors>
   </contributors>
   <titles>
    <title></title>
   </titles>
   <dates>
    <year>2016</year>
    <pub-dates>
     <date>2018-03-01</date>
    </pub-dates>
   </dates>
   <doi>10.1016/S2352-3018(16)30087-X</doi>
   <abstract>Background Timely assessment of the burden of HIV/AIDS is essential for policy setting and programme evaluation.&#13;
In this report from the Global Burden of Disease Study 2015 (GBD 2015), we provide national estimates of levels and&#13;
trends of HIV/AIDS incidence, prevalence, coverage of antiretroviral therapy (ART), and mortality for 195 countries&#13;
and territories from 1980 to 2015.&#13;
Methods For countries without high-quality vital registration data, we estimated prevalence and incidence with data&#13;
from antenatal care clinics and population-based seroprevalence surveys, and with assumptions by age and sex on&#13;
initial CD4 distribution at infection, CD4 progression rates (probability of progression from higher to lower CD4&#13;
cell-count category), on and off antiretroviral therapy (ART) mortality, and mortality from all other causes.&#13;
Our estimation strategy links the GBD 2015 assessment of all-cause mortality and estimation of incidence and&#13;
prevalence so that for each draw from the uncertainty distribution all assumptions used in each step are internally&#13;
consistent. We estimated incidence, prevalence, and death with GBD versions of the Estimation and Projection&#13;
Package (EPP) and Spectrum software originally developed by the Joint United Nations Programme on HIV/AIDS&#13;
(UNAIDS). We used an open-source version of EPP and recoded Spectrum for speed, and used updated assumptions&#13;
from systematic reviews of the literature and GBD demographic data. For countries with high-quality vital registration&#13;
data, we developed the cohort incidence bias adjustment model to estimate HIV incidence and prevalence largely&#13;
from the number of deaths caused by HIV recorded in cause-of-death statistics. We corrected these statistics for&#13;
garbage coding and HIV misclassifi cation.</abstract>
   <urls>
    <web-urls>
     <url>https://repo.bashgmu.ru/publication/1026</url>
    </web-urls>
    <pdf-urls>
     <url>https://repo.bashgmu.ru/files/1170</url>
    </pdf-urls>
   </urls>
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