Development and Analysis of Multiscale Models for Tuberculosis: From Molecules to Populations.

Although infectious disease dynamics are often analyzed at the macro-scale, increasing numbers of drug-resistant infections highlight the importance of within-host modeling that simultaneously solves across multiple scales to effectively respond to epidemics. We review multiscale modeling approaches for complex, interconnected biological systems and discuss critical steps involved in building, analyzing, and applying such models within the discipline of model credibility. We also present our two tools: CaliPro, for calibrating multiscale models (MSMs) to datasets, and tunable resolution, for fine- and coarse-graining sub-models while retaining insights. We include as an example our work simulating infection with Mycobacterium tuberculosis to demonstrate modeling choices and how predictions are made to generate new insights and test interventions. We discuss some of the current challenges of incorporating novel datasets, rigorously training computational biologists, and increasing the reach of MSMs. We also offer several promising future research directions of incorporating within-host dynamics into applications ranging from combinatorial treatment to epidemic response.

The Role of HIV Partner Services in the Modern Biomedical HIV Prevention Era: A Network Modeling Study.

BACKGROUND: HIV partner services can accelerate the use of antiretroviral-based HIV prevention tools (antiretroviral therapy [ART] and preexposure prophylaxis [PrEP]), but its population impact on long-term HIV incidence reduction is challenging to quantify with traditional partner services metrics of partner identified or HIV screened. Understanding the role of partner services within the portfolio of HIV prevention interventions, including using it to efficiently deliver antiretrovirals, is needed to achieve HIV prevention targets. METHODS: We used a stochastic network model of HIV/sexually transmitted infection transmission for men who have sex with men, calibrated to surveillance-based estimates in the Atlanta area, a jurisdiction with high HIV burden and suboptimal partner services uptake. Model scenarios varied successful delivery of partner services cascade steps (newly diagnosed "index" patient and partner identification, partner HIV screening, and linkage or reengagement of partners in PrEP or ART care) individually and jointly. RESULTS: At current levels observed in Atlanta, removal of HIV partner services had minimal impact on 10-year cumulative HIV incidence, as did improving a single partner services step while holding the others constant. These changes did not sufficiently impact overall PrEP or ART coverage to reduce HIV transmission. If all index patients and partners were identified, maximizing partner HIV screening, partner PrEP provision, partner ART linkage, and partner ART reengagement would avert 6%, 11%, 5%, and 18% of infections, respectively. Realistic improvements in partner identification and service delivery were estimated to avert 2% to 8% of infections, depending on the combination of improvements. CONCLUSIONS: Achieving optimal HIV prevention with partner services depends on pairing improvements in index patient and partner identification with maximal delivery of HIV screening, ART, and PrEP to partners if indicated. Improving the identification steps without improvement to antiretroviral service delivery steps, or vice versa, is projected to result in negligible population HIV prevention benefit.