@article{fdi:010064756,
  title = {{E}stimation and short-term prediction of the course of the {HIV} epidemic using demographic and health survey methodology-like data},
  author = {{B}laizot, {S}. and {R}iche, {B}. and {M}aman, {D}. and {M}ukui, {I}. and {K}irubi, {B}. and {E}tard, {J}ean-{F}ran{\c{c}}ois and {E}cochard, {R}.},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground {M}athematical models have played important roles in the understanding of epidemics and in the study of the impacts of various behavioral or medical measures. {H}owever, modeling accurately the future spread of an epidemic requires context-specific parameters that are difficult to estimate because of lack of data. {O}ur objective is to propose a methodology to estimate context-specific parameters using {D}emographic and {H}ealth {S}urvey ({DHS})-like data that can be used in mathematical modeling of short-term {HIV} spreading. {M}ethods and {F}indings {T}he model splits the population according to sex, age, {HIV} status, and antiretroviral treatment status. {T}o estimate context-specific parameters, we used individuals' histories included in {DHS}-like data and a statistical analysis that used decomposition of the {P}oisson likelihood. {T}o predict the course of the {HIV} epidemic, sex-and age-specific differential equations were used. {T}his approach was applied to recent data from {K}enya. {T}he approach allowed the estimation of several key epidemiological parameters. {W}omen had a higher infection rate than men and the highest infection rate in the youngest age groups (15-24 and 25-34 years) whereas men had the highest infection rate in age group 25-34 years. {T}he immunosuppression rates were similar between age groups. {T}he treatment rate was the highest in age group 35-59 years in both sexes. {T}he results showed that, within the 1524 year age group, increasing male circumcision coverage and antiretroviral therapy coverage at {CD}4 <= 350/mm(3) over the current 70% could have short-term impacts. {C}onclusions {T}he study succeeded in estimating the model parameters using {DHS}-like data rather than literature data. {T}he analysis provides a framework for using the same data for estimation and prediction, which can improve the validity of context-specific predictions and help designing {HIV} prevention campaigns.},
  keywords = {{KENYA}},
  booktitle = {},
  journal = {{P}los {O}ne},
  volume = {10},
  numero = {6},
  pages = {e0130387 [14 p.]},
  ISSN = {1932-6203},
  year = {2015},
  DOI = {10.1371/journal.pone.0130387},
  URL = {https://www.documentation.ird.fr/hor/fdi:010064756},
}