South Africa

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

Leigh Johnson and Rob Dorrington (University of Cape Town)

Impact of prevention and treatment programmes, demographic impact of HIV, understanding epidemic drivers General population (includes sex workers, but not MSM or PWID) Deterministic, compartmental, cohort component projection models
  • Johnson LF, Dorrington RE. Modelling the demographic impact of HIV/AIDS in South Africa and the likely impact of interventions. Demographic Research. 2006;14:541-574.
Leigh Johnson
BBH (Bärnighausen, Bloom, Humair)

Till Bärnighausen, David Bloom (Harvard School of Public Health) and Salal Humair (unaffiliated)

Impact of HIV-related biomedical and behavioural interventions on population health outcomes, targeted towards investigating resource allocation issues in HIV (e.g., cost-effectiveness of combination interventions, optimal allocation of a fixed budget across different interventions) Heterosexual couples, MSMs, FSWs Deterministic, analytical
  • Bärnighausen, T., D. E. Bloom and S. Humair (2012). "Economics of antiretroviral treatment vs. circumcision for HIV prevention." Proceedings of the National Academy of Sciences 109(52): 21271-21276.

Eaton, Hallett (submitted)

Jeff Eaton, Tim Hallett (Imperial College London)

Impact of biomedical prevention interventions, drivers of epidemics, modelling methodology General population Deterministic population-based model jeffrey.eaton(at)

Olivia Keiser, Janne Estill, Luisa Salazar and Nello Blaser (University of Bern)

Modelling methodology, resource allocation / decision making, optimising treatment and patient management General population Individual based cohort model
  • Estill J, Aubrière C, Egger M, Johnson L, Wood R, Garone D, Gsponer T, Wandeler G, Boulle A, Davies MA, Hallett TB, Keiser O; IeDEA Southern Africa. Viral load monitoring of antiretroviral therapy, cohort viral load and HIV transmission in Southern Africa: a mathematical modelling analysis. AIDS. 2012;26(11):1403-13.
Olivia Keiser and Janne Estill okeiser(at); jestill(at)
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 (

Natasha Martin (University of Bristol), Peter Vickerman (LSHTM) and the Social and Mathematical Epidemiology Group.

Impact of ART on HIV/HCV or HIV/HBV progression and vertical or sexual transmission Individuals coinfected with HIV and hepatitis C virus, individuals coinfected with HIV and hepatitis B virus Coinfection disease progression cohort model with sexual and vertical transmission
ICRC HIV Transmission Model

Roger Ying (University of Washington International Clinical Research Center)

Biomedical interventions - ART as Treatment and as PrEP All ages, heterosexual transmission Compartmental, deterministic
  • Ying R, Celum C, Baeten J, Murnane P, Hong T, Krows M, van Rooyen H, Humphries H, Hughes JP, and Barnabas R. Pre-Exposure Prophylaxis (PrEP) is Estimated to Be a Cost-Effective Addition to Antiretroviral Therapy (ART) For HIV Prevention in a Generalised Epidemic Setting. Sex Transm Infect. 2013;89: A219
Roger Ying - rying1(at)
KZN Model

Íde Cremin, Timothy Hallett (Imperial College London)

Impact of combination HIV prevention Heterosexual transmission, age, sex and risk structured Deterministic, compartmental, age, sex and risk structured
  • Cremin I, Alsallaq R, Dybul M, Piot P, Garnett G, Hallett TB. The new role of antiretrovirals in combination HIV prevention: a mathematical modelling analysis. Aids 2013,27:447-458.
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
PopART (population effects of antiretroviral therapy to reduce HIV transmission)

Christophe Fraser et al (Imperial College London)

Impact of universal testing and universal "test and treat" (delivered in the PopART trial) on the HIV incidence at the community level General population Deterministic compartmental model Christophe Fraser - c.fraser(at)

Jan Hontelez (Department of Public Health, Erasmus MC, Rotterdam, The Netherlands; and Africa Centre for Health and Population Studies, University of KwaZulu-Natal, South Africa)

HIV elimination, epidemiological impact of antiretroviral therapy, population level impact of health systems and cascade of care, cost-effectiveness of different modes of treatment delivery General population; female sex workers and male clients Stochastic microsimulation model
  • Steen R, Hontelez JA, Veraart A, White RG, de Vlas SJ. Looking upstream to prevent HIV transmission: can interventions with sex workers alter the course of HIV epidemics in Africa as they did in Asia? AIDS. 2014; 28: 891-9.
  • Eaton JW, Menzies NA, Stover J, Cambiano V, Chindelevitch L, Cori A, Hontelez JA, (...) Hallett TB. Health benefits, costs, and cost-effectiveness of earlier eligibility for adult antiretroviral therapy and expanded treatment coverage: a combined analysis of 12 mathematical models. Lancet glob health. 2014;2(1) e23-e24

Leigh Johnson, Rob Dorrington (University of Cape Town) and Debbie Bradshaw (South African Medical Research Council)

Understanding epidemic drivers (especially sexual behaviour and the role of other STIs), impact of prevention and treatment programmes, demographic impact of HIV General population (including sex workers) Deterministic, compartmental, cohort component projection models
  • Johnson LF, Dorrington RE, Bradshaw D, Pillay-Van Wyk V, Rehle TM. Sexual behaviour patterns in South Africa and their association with the spread of HIV: insights from a mathematical model. Demographic Research. 2009;21:289-340.

Leigh Johnson and Rob Dorrington (University of Cape Town)

Impact of prevention and treatment programmes, demographic impact of HIV, understanding epidemic drivers General population (including sex workers) Deterministic, compartmental, cohort component projection models
  • Johnson L. THEMBISA version 1.0: A model for evaluating the impact of HIV/AIDS in South Africa. Centre for Infectious Disease Epidemiology and Research, University of Cape Town; 2014.