Quantitative Methods in HIV/AIDS Research provides a comprehensive discussion of modern statistical approaches for the analysis of HIV/AIDS data. The first section focuses on statistical issues in clinical trials and epidemiology that are unique to or particularly challenging in HIV/AIDS research; the second section focuses on the analysis of laboratory data used for immune monitoring, biomarker discovery and vaccine development; the final section focuses on statistical issues in the mathematical modeling of HIV/AIDS pathogenesis, treatment and epidemiology.

This book brings together a broad perspective of new quantitative methods in HIV/AIDS research, contributed by statisticians and mathematicians immersed in HIV research, many of whom are current or previous leaders of CFAR quantitative cores. It is the editors’ hope that the work will inspire more statisticians, mathematicians and computer scientists to collaborate and contribute to the interdisciplinary challenges of understanding and addressing the AIDS pandemic.

Table of Contents

1. Design and analysis of HIV clinical trials with multiple or combined endpoints. 2. Design and

analysis of HIV vaccine clinical trials. 3. Genetic and antigenic variation in HIV vaccine trials. 4. Biomarker development in HIV clinical research. 5. Design and Analysis for assessing perinatal transmission in HIV clinical trials. 6. Design and analysis of early stage HIV studies. 7. Modeling of HIV pathogenesis. 8. Modeling of HIV transmission. 9. Design of animal challenge studies for assessing the effects of HIV. 10. Methods for the statistical evaluation of data quality in large, multi-centered clinical trials. 11. Design and analysis of Phase I and phase II HIV vaccine trials. 12. Design and analysis of immunogenicity studies of HIV vaccine candidates. 13. Personalized medicine for patients with HIV. 14. Analysis of assay data related to cure, immune responses to vaccines, and incidence. 15. Computational biology and bioinformatics for HIV research. 16. Viral phylogenetics. 17. B cell phylogenetics for vaccines. 18. HIV dynamical systems models. 19. Social network analysis. 20. Statistical modeling for social behavioral science approaches. 21. Assay standardization. 22. Single cell Biomarkers. 23. Global Health perspectives


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