Abstract
BackgroundMathematical models have played important roles in the understanding of epidemics and in the study of the impacts of various behavioral or medical measures. However, modeling accurately the future spread of an epidemic requires context-specific parameters that are difficult to estimate because of lack of data. Our objective is to propose a methodology to estimate context-specific parameters using Demographic and Health Survey (DHS)-like data that can be used in mathematical modeling of short-term HIV spreading.Methods and FindingsThe model splits the population according to sex, age, HIV status, and antiretroviral treatment status. To estimate context-specific parameters, we used individuals’ histories included in DHS-like data and a statistical analysis that used decomposition of the Poisson likelihood. To predict the course of the HIV epidemic, sex- and age-specific differential equations were used. This approach was applied to recent data from Kenya. The approach allowed the estimation of several key epidemiological parameters. Women 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. The immunosuppression rates were similar between age groups. The treatment rate was the highest in age group 35–59 years in both sexes. The results showed that, within the 15–24 year age group, increasing male circumcision coverage and antiretroviral therapy coverage at CD4 ≤ 350/mm3 over the current 70% could have short-term impacts.ConclusionsThe study succeeded in estimating the model parameters using DHS-like data rather than literature data. The 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.
Highlights
Mathematical models have played important roles in the understanding of epidemics and in the study of the impacts of various behavioral or medical measures [1,2,3]
The results showed that, within the 15– 24 year age group, increasing male circumcision coverage and antiretroviral therapy coverage at CD4 350/mm3 over the current 70% could have short-term impacts
The study succeeded in estimating the model parameters using Demographic and Health Survey (DHS)-like data rather than literature data
Summary
Mathematical models have played important roles in the understanding of epidemics and in the study of the impacts of various behavioral or medical measures [1,2,3]. Numerous models with various complexities and assumptions have been developed to provide long-term predictions of the future courses of the HIV epidemic, especially the impact of various prevention and treatment strategies [4,5,6,7] In these models, the parameters are often taken from studies carried out in other distant countries with different contexts, which may result in biased results and misguided policies. We propose a modeling approach for short-term predictions of the spread of the HIV epidemic This approach includes an estimation of model parameters from survey data conducted with the DHS methodology. Our objective is to propose a methodology to estimate context-specific parameters using Demographic and Health Survey (DHS)-like data that can be used in mathematical modeling of short-term HIV spreading
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
