# Project

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## Scale up of antiretroviral therapy and transmission of HIV in Southern Africa: Mathematical model

 English title Scale up of antiretroviral therapy and transmission of HIV in Southern Africa: Mathematical model Keiser Olivia 137106 ProDoc Institute of Social and Preventive Medicine University of Bern University of Berne - BE Infectious Diseases 01.10.2011 - 30.06.2015 172'166.00
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### All Disciplines (2)

Discipline
 Infectious Diseases
 Methods of Epidemiology and Preventive Medicine

### Lay Summary (English)

Lay summary

Background: The HIV/AIDS pandemic is a public health emergency in many low-income and middle-income countries. There were an estimated 33.3 million people living with HIV at the end of 2009, with 11.3 million living in Southern Africa. Since 2004 efforts by governments and others have resulted in a massive scale-up of highly active antiretroviral combination therapy (ART): at the end of 2009, 3.9 million people were reported to be receiving antiretroviral therapy in sub-Saharan Africa.
The impact of the scale-up of ART on the incidence of new infections in Africa is hotly debated but unclear at present. We would like to address this question by building a mathematical transmission model based on the International epidemiological Databases in Southern Africa (IeDEA-SA).

Rationale: The concept of ‘treatment as prevention’ or ‘test-and-treat’ is topical and a better understanding of the place of ART in prevention is urgently needed. The 2010 treatment guidelines of the World Health Organization (WHO) recommend earlier initiation of ART (when CD4 cell counts fall to 350 cells/μl or lower, rather than 200 cells/μl), which means that many more people living with HIV have become eligible for ART. Previous models of ART in low-income settings focussed on clinical outcomes without considering its impact on HIV transmission, or on HIV transmission without modelling the scale-up of ART in resource-constrained settings. There is an urgent need for more comprehensive models that consider the realities of ART in sub-Saharan Africa, including the high rate of loss to follow-up, the lack of viral load (VL) monitoring, treatment interruptions and stock outs, and the incidence of treatment failure.

Objectives: We aim to develop an individual-based, comprehensive mathematical model of the impact of ART on HIV transmission in Southern Africa, based on the data from IeDEA-SA. In particular, we will explore the role of routine VL monitoring and study the impact on HIV transmission at the population level of the new WHO guidelines.

Methods: IeDEA-SA is a large collaborative network of HIV treatment sites in Southern Africa, with coordinating centres at the Universities of Bern, Switzerland and Cape Town, South Africa. The current database includes 288,015 adults (251,759 on ART) and 30,470 children (24,277 on ART) in 23 programmes in 6 countries (Botswana, Malawi, Mozambique, South Africa and Zambia, Zimbabwe). All participating clinics collect socio-demographic, clinical, laboratory, and pharmacological data at the individual patient level, using an agreed protocol and database structure. Patients are followed up 3 to 6 monthly. VL is regularly measured in South Africa and Botswana. Outcomes include changes in virological and immunological failure of ART, mortality and loss to follow-up. We will use the IeDEA-SA data to parameterize the model, and review published transmission models and the literature to extract data on sexual behaviour (not collected in IeDEA) and partner change. We will adapt the individual-based ART model developed at ISPM Bern to include components relevant to HIV transmission (pre-ART period, individual VL and CD4 trajectories etc.), integrate the ART model into the transmission model, explore model uncertainty and validate the model, and test pre-specified hypotheses.

Significance: This will be the first HIV transmission model that incorporates detailed information that reflects the realities of ART in Southern Africa. The model will predict the future course of the epidemic in the ART era under different scenarios and aid decision making. Mathematical modelling complements randomized controlled trial and epidemiological research: it is time- and cost-saving and allows testing a wealth of different strategies. The project provides an ideal environment for a PhD student and will strengthen existing collaborations with renowned mathematical modellers in the field of HIV.

 Direct link to Lay Summary Last update: 21.02.2013

### Responsible applicant and co-applicants

Name Institute
 Keiser Olivia Institut de Santé Globale Institute des Etudes Globales Université de Genève
 Egger Matthias Institute of Social and Preventive Medicine University of Bern

Name Institute

### Publications

Publication
Blaser Nello, Zahnd Cindy, Hermans Sabine, Salazar-Vizcaya Luisa, Estill Janne, Morrow Carl, Egger Matthias, Keiser Olivia, Wood Robin (2016), Tuberculosis in Cape Town: An age-structured transmission model, in Epidemics, 14(0), 54-61.
Blaser Nello, Salazar-Vizcaya Luisa, Estill Janne, Zahnd Cindy, Kalesan Bindu, Egger Matthias, Keiser Olivia, Gsponer Thomas (2015), gems: An R Package for Simulating from Disease Progression Models, in Journal of Statistical Software, 64(10), 1-22.
Estill Janne, Salazar-Vizcaya Luisa, Blaser Nello, Egger Matthias, Keiser Olivia (2015), The Cost-Effectiveness of Monitoring Strategies for Antiretroviral Therapy of HIV Infected Patients in Resource-Limited Settings: Software Tool, in PLoS One , 10(3), e0119299.
Keebler Daniel, Revill Paul, Braithwaite Scott, Phillips Andrew, Blaser Nello, et al (2014), How Should HIV Programmes Monitor Adults on ART? A Combined Analysis of Three Mathematical Models, in Lancet Global Health, 2(1), e35-43.
Blaser Nello, Wettstein Celina, Estill Janne, Salazar-Vizcaya Luisa, Wandeler Gilles, Egger Matthias, Keiser Olivia (2014), Impact of viral load and the duration of primary infection on HIV transmission: systematic review and meta-analysis, in AIDS, 28, 1021-1029.
Petersen Maya, Schwab Joshua, Gruber Susan, Blaser Nello, Schomaker Michael, van der Laan Mark (2014), Targeted Maximum Likelihood Estimation for Dynamic and Static Longitudinal Marginal Structural Working Models, in Journal of Causal Inference, 2(2), 147-185.
Estill Janne, Tweya Hannock, Tweya Hannock, Tweya Hannock, Egger Matthias, Egger Matthias, Wandeler Gilles, Wandeler Gilles, Wandeler Gilles, Feldacker Caryl, Feldacker Caryl, Johnson Leigh F., Blaser Nello, Vizcaya Luisa Salazar, Phiri Sam, Keiser Olivia (2014), Tracing of patients lost to follow-up and HIV transmission: Mathematical modeling study based on 2 large ART programs in Malawi, in Journal of Acquired Immune Deficiency Syndromes, 65(5), e179-e186.
Estill Janne, Egger Matthias, Blaser Nello, Salazar Vizcaya Luisa, Garone Daniela, Wood Robin, Campbell Jennifer, Hallett Timothy B., Keiser Olivia (2013), Cost-effectiveness of point-of-care viral load monitoring of antiretroviral therapy in resource-limited settings: mathematical modelling study, in AIDS, 1483.
Salazar-Vizcaya Luisa, Keiser Olivia, Technau Karl, Davies Mary Ann, Haas Andreas D., Blaser Nello, Cox Vivian, Eley Brian, Rabie Helena, Moultrie Harry, Giddy Janet, Wood Robin, Egger Matthias, Egger Matthias, Estill Janne (2013), Viral load versus CD4+ monitoring and 5-year outcomes of antiretroviral therapy in HIV-positive children in Southern Africa: A cohort-based modelling study, in AIDS, 28(16), 2451-2460.
Wettstein Celina, Mugglin Catrina, Egger Matthias, Blaser Nello, Salazar Luisa, Estill Janne, Bender Nicole, Davies Mary-Ann, Wandeler Gilles, Keiser Olivia (2012), Missed Opportunities to Prevent Mother-to-Child-Transmission in sub-Saharan Africa: Systematic Review and Meta-Analysis., in AIDS (London, England), 1-1.
Keiser Olivia, Blaser Nello, Davies Mary-Ann, Wessa Patrick, Eley Brian, Moultrie Harry, Rabie Helena, Technau Karl, Ndirangu James, Garone Daniela, Giddy Janet, Grimwood Ashraf, Gsponer Thomas, Egger Matthias, Growth in Virologically Suppressed HIV Positive Children on Antiretroviral Therapy: Individual and Population-Level References, in The Pediatric Infectious Disease Journal.

### Collaboration

Group / person Country
Types of collaboration
 Dr Tim Hallett: Imperial College, London, UK Great Britain and Northern Ireland (Europe)
 - in-depth/constructive exchanges on approaches, methods or results- Publication
 Prof Robin Wood, University of Cape Town South Africa (Africa)
 - in-depth/constructive exchanges on approaches, methods or results- Publication
 Dr Mary-Ann Davies, Dr L Johnson: School of Public Health, University of Cape Town South Africa (Africa)
 - in-depth/constructive exchanges on approaches, methods or results

### Scientific events

#### Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
 IWHOD Talk given at a conference Age-structure in the TB-HIV co-epidemic in Cape Town: a mathematical modeling study 27.03.2014 Sitges, Spain Blaser Nello;
 IWHOD Talk given at a conference gems: A Flexible, Open Source Simulation Tool for Modeling Antiretroviral Therapy Interventions 11.04.2013 Dubrovnik, Croatia Keiser Olivia; Egger Matthias; Blaser Nello;
 South African Clinicians Society Conference Talk given at a conference Modeling for clinical decision making: two examples 25.11.2012 Cape Town, South Africa Blaser Nello;
 Swiss Meeting for Infectious Disease Dynamics Talk given at a conference Generalized multistate simulation model GEMS to test the effectiveness of health interventions: development and first applications 30.08.2012 St. Gallen, Switzerland Blaser Nello;
 HIV treatment as prevention Poster Infectiousness over time in HIV infected patients – implications for a universal ‘test and treat’ strategy 22.04.2012 Vancouver, Canada Blaser Nello;

### Associated projects

Number Title Start Funding scheme
 150934 Mathematical simulation models to test the impact and cost-effectiveness of health interventions - applications in HIV, tuberculosis, cancer and hepatitis C 01.01.2014 Ambizione
 131629 Long-term antiretroviral therapy of HIV-infected patients in sub-Saharan Africa - insights from causal and mathematical modelling 01.01.2011 Ambizione
 146143 Understanding and Predicting the Hepatitis C Epidemic in HIV-infected Patients 01.05.2013 Project funding (special)

### Abstract

Background: The HIV/AIDS pandemic is a public health emergency in many low-income and middle-income countries. There were an estimated 33.3 million people living with HIV at the end of 2009, with 11.3 million living in Southern Africa. Since 2004 efforts by governments and others have resulted in a massive scale-up of highly active antiretroviral combination therapy (ART): at the end of 2009, 3.9 million people were reported to be receiving antiretroviral therapy in sub-Saharan Africa. The impact of the scale-up of ART on the incidence of new infections in Africa is hotly debated but unclear at present. We would like to address this question by building a mathematical transmission model based on the International epidemiological Databases in Southern Africa (IeDEA-SA). Rationale: The concept of ‘treatment as prevention’ or ‘test-and-treat’ is topical and a better understanding of the place of ART in prevention is urgently needed. The 2010 treatment guidelines of the World Health Organization (WHO) recommend earlier initiation of ART (when CD4 cell counts fall to 350 cells/µl or lower, rather than 200 cells/µl), which means that many more people living with HIV have become eligible for ART. Previous models of ART in low-income settings focussed on clinical outcomes without considering its impact on HIV transmission, or on HIV transmission without modelling the scale-up of ART in resource-constrained settings. There is an urgent need for more comprehensive models that consider the realities of ART in sub-Saharan Africa, including the high rate of loss to follow-up, the lack of viral load (VL) monitoring, treatment interruptions and stock outs, and the incidence of treatment failure.Objectives: We aim to develop an individual-based, comprehensive mathematical model of the impact of ART on HIV transmission in Southern Africa, based on the data from IeDEA-SA. In particular, we will explore the role of routine VL monitoring and study the impact on HIV transmission at the population level of the new WHO guidelines.Methods: IeDEA-SA is a large collaborative network of HIV treatment sites in Southern Africa, with coordinating centres at the Universities of Bern, Switzerland and Cape Town, South Africa. The current database includes 288,015 adults (251,759 on ART) and 30,470 children (24,277 on ART) in 23 programmes in 6 countries (Botswana, Malawi, Mozambique, South Africa and Zambia, Zimbabwe). All participating clinics collect socio-demographic, clinical, laboratory, and pharmacological data at the individual patient level, using an agreed protocol and database structure. Patients are followed up 3 to 6 monthly. VL is regularly measured in South Africa and Botswana. Outcomes include changes in virological and immunological failure of ART, mortality and loss to follow-up. We will use the IeDEA-SA data to parameterize the model, and review published transmission models and the literature to extract data on sexual behaviour (not collected in IeDEA) and partner change. We will adapt the individual-based ART model developed at ISPM Bern to include components relevant to HIV transmission (pre-ART period, individual VL and CD4 trajectories etc.), integrate the ART model into the transmission model, explore model uncertainty and validate the model, and test pre-specified hypotheses.Significance: This will be the first HIV transmission model that incorporates detailed information that reflects the realities of ART in Southern Africa. The model will predict the future course of the epidemic in the ART era under different scenarios and aid decision making. Mathematical modelling complements randomized controlled trial and epidemiological research: it is time- and cost-saving and allows testing a wealth of different strategies. The project provides an ideal environment for a PhD student and will strengthen existing collaborations with renowned mathematical modellers in the field of HIV.
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