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Name of Model Research group Area of research Population Type of model Reference Contact
Goals Model

John Stover, Carel Pretorius, Chaitra Gopalappa, Kyeen Anderson and Lori Bollinger (Futures Institute)

HIV epidemic dynamics, impacts of prevention interventions (both biomedical and behavior change, adults and children), impacts of new prevention technologies, resource allocation General population Deterministic, population-based
  • Schwartlander B, Stover J, Hallett T, Atun R, Avila C, Gouws E, et al. Towards and improved investment approach for an effective response to HV/AIDS. Lancet. 2011;377(9782): 2031-2041.
HIV Synthesis Transmission Model for Sub-Saharan Africa

Andrew Phillips, Valentina Cambiano, Debbie Ford, Fumiyo Nakagawa, Loveleen Bansi (University College London), Alec Miners (LSHTM) and Paul Revill (University of York)

Impact of biomedical prevention interventions, impact of behavioural intervention approaches, impact of combination prevention approaches, Optimization of treatment and patient management (monitoring),Impact of introduction of new diagnostic technologies (e.g. new testing devices, resistance test, POC CD4 and VL), Resistance development and transmission South Africa - General population: aged 15 to 65 years old. Sub Saharan Africa - General population: aged 15 to 65 years old. Zimbabwe - General population: aged 15 to 65 years old. Lesotho - General population: aged 15 to 65 years old. Individual-based dynamic stochastic simulation model including transmission. Model of progression is similar to the other Synthesis models, except features such as drug availability and diagnostic testing.
  • Phillips AN, Pillay D, Garnett G, Bennett D, Vitoria M, Cambiano V, et al. Effect on transmission of HIV-1 resistance of timing of implementation of viral load monitoring to determine switches from first to second-line antiretroviral regimens in resource-limited settings. AIDS. 2011; 25(6):843-850. 
  • Cambiano V, Bertagnolio S, Jordan M, Pillay D, Perriens J, Venter F, et al. Predicted levels of HIV drug resistance: potential impact of expanding diagnosis, retention, and eligibility criteria for antiretroviral therapy initiation. AIDS. 2014, 28 (Suppl 1):S15–S23 
  • Cambiano V, Bertagnolio , Jordan M, et al. Transmission of Drug Resistant HIV and Its Potential Impact on Mortality and Treatment Outcomes in Resource-Limited Settings. J Infect Dis. 2013; 207: S57-62
Andrew Phillips ( Valentina Cambiano (
Menzies TB-HIV

Ted Cohen, Megan Murray, Joshua Salomon, Hsein-ho Lin, Leonid Chindelevitch, and Nick menzies (Harvard School of Public Health)

TB and HIV, and effects (epidemiology, disease burden, resource utilization) of control interventions directed at these diseases General population Deterministic state-transition model
  • Menzies NA, Cohen T, Lin H-H, Murray M, Salomon JA. Population Health Impact and Cost-Effectiveness of Tuberculosis Diagnosis with Xpert MTB/RIF: A Dynamic Simulation and Economic Evaluation. PLoS Med. 2012; 9(11): e1001347.
Nick Menzies - nickmenzies(at)

Wilson group, Kirby Institute, UNSW Australia

Allocative efficiency, impact evaluation, cost-effectiveness, epidemic and financial commitment projections, incidence estimation, cascade evaluation Any risk-based and demographic-based stratifications of populations are included Compartmental population-based model with optimization routines
  • Kerr et al. Optima: a model for HIV epidemic analysis, program prioritization, and resource optimization. J Acquir Immune Defic Syndr. 2015;69(3):365-76
  • Wilson et al. Allocating resources efficiently to address strategic objectives: optimisation of HIV responses. Under review.
  • Fraser et al. Sudan’s HIV response: Value for money in a low-level HIV epidemic; Findings from the HIV allocative efficiency study. Report published by the World Bank and UNSW Australia. 2014
  • Fraser et al. Niger’s HIV response: Targeted investments for a health future. Findings from the HIV allocative efficiency and financial sustainability study. Report published by the World Bank. 2014