ESTIMATING THE STAGE-SPECIFIC NUMBERS OF HIV-INFECTION USING A MARKOV MODEL AND BACK-CALCULATION

被引:46
|
作者
LONGINI, IM
BYERS, RH
HESSOL, NA
TAN, WY
机构
[1] CTR DIS CONTROL,CTR INFECT DIS,DIV HIV AIDS,ATLANTA,GA 30333
[2] DEPT PUBL HLTH,AIDS OFF,SAN FRANCISCO,CA 94103
[3] MEMPHIS STATE UNIV,DEPT MATH SCI,MEMPHIS,TN 38152
关键词
D O I
10.1002/sim.4780110612
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The back-calculation method has been used to estimate the number of HIV infections from AIDS incidence data in a particular population. We present an extension of back calculation that provides estimates of the numbers of HIV infectives in different stages of infection. We model the staging process with a time-dependent Markov process that partitions the HIV infectious period into the following progressive stages and/or substages: stage 1, infected but antibody negative; substages 2-3; antibody positive but asymptomatic; substages 4-6, pre-AIDS symptoms and/or abnormal haematologic indicator; stage 7, clinical AIDS. We also model an eighth stage, deceased due to AIDS. The model allows for time-dependent treatment effects that slow the rate of progression in substages 4-7. We use the estimated AIDS incubation period distribution from the Markov model in back calculation from AIDS incidence data to estimate the total number of HIV infections and the parameters of the infection probability distribution. We then use these estimates in the Markov model to estimate the stage-specific numbers of HIV infections over the course of the epidemic in the population under study. Example calculations employ data for the HIV epidemic in San Francisco City Clinic Cohort.
引用
收藏
页码:831 / 843
页数:13
相关论文
共 40 条
  • [1] Sources of uncertainty in estimating HIV infection rates by back-calculation: An application to Italian data
    Mariotti, S
    Cascioli, R
    [J]. STATISTICS IN MEDICINE, 1996, 15 (24) : 2669 - 2687
  • [2] A BACK-CALCULATION METHOD TO ESTIMATE THE AGE AND PERIOD HIV-INFECTION INTENSITY, CONSIDERING THE SUSCEPTIBLE POPULATION
    VERDECCHIA, A
    MARIOTTO, AB
    [J]. STATISTICS IN MEDICINE, 1995, 14 (14) : 1513 - 1530
  • [3] Bayesian back-calculation using a multi-state model with application to HIV
    Sweeting, MJ
    De Angelis, D
    Aalen, OO
    [J]. STATISTICS IN MEDICINE, 2005, 24 (24) : 3991 - 4007
  • [4] Estimating cancer incidence using a Bayesian back-calculation approach
    Ventura, Leonardo
    Mezzetti, Maura
    [J]. STATISTICS IN MEDICINE, 2014, 33 (25) : 4453 - 4468
  • [5] Estimating the Transmittable Prevalence of Infectious Diseases Using a Back-Calculation Approach
    Lee, Youngsaeng
    Jang, Hyun Gap
    Kim, Tae Yoon
    Park, Jeong-Soo
    [J]. COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS, 2014, 21 (06) : 487 - 500
  • [6] A HIERARCHICAL BAYESIAN-APPROACH TO THE BACK-CALCULATION OF NUMBERS OF HIV-INFECTED SUBJECTS
    WILD, P
    COMMENGES, D
    ETCHEVERRY, B
    [J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES D-THE STATISTICIAN, 1993, 42 (04) : 405 - 414
  • [7] Extending Bayesian back-calculation to estimate age and time specific HIV incidence
    Brizzi, Francesco
    Birrell, Paul J.
    Plummer, Martyn T.
    Kirwan, Peter
    Brown, Alison E.
    Delpech, Valerie C.
    Gill, O. Noel
    De Angelis, Daniela
    [J]. LIFETIME DATA ANALYSIS, 2019, 25 (04) : 757 - 780
  • [8] Methods for estimating HIV prevalence: A comparison of extrapolation from surveys on infection rate and risk behaviour with back-calculation for the Netherlands
    Houweling, H
    Heisterkamp, SH
    Wiessing, LG
    Coutinho, RA
    van Wijngaarden, JK
    Jager, HJC
    [J]. EUROPEAN JOURNAL OF EPIDEMIOLOGY, 1998, 14 (07) : 645 - 652
  • [9] Methods for estimating HIV prevalence: A comparison of extrapolation from surveys on infection rate and risk behaviour with back-calculation for the Netherlands
    Hans Houweling
    Siem H. Heisterkamp
    Lucas G. Wiessing
    Roel A. Coutinho
    Jan K. van Wijngaarden
    Hans (J.)C. Jager
    [J]. European Journal of Epidemiology, 1998, 14 : 645 - 652
  • [10] Extending Bayesian back-calculation to estimate age and time specific HIV incidence
    Francesco Brizzi
    Paul J. Birrell
    Martyn T. Plummer
    Peter Kirwan
    Alison E. Brown
    Valerie C. Delpech
    O. Noel Gill
    Daniela De Angelis
    [J]. Lifetime Data Analysis, 2019, 25 : 757 - 780