A quantitative assessment of the consistency of projections from five mathematical models of the HIV epidemic in South Africa: a model comparison study

Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the robustness of estimates and highlight research gaps. As part of a larger project aiming to determine the optimal allocation of funding for HIV se...

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Published inBMC public health Vol. 23; no. 1; p. 2119
Main Authors Moolla, Haroon, Phillips, Andrew, Ten Brink, Debra, Mudimu, Edinah, Stover, John, Bansi-Matharu, Loveleen, Martin-Hughes, Rowan, Wulan, Nisaa, Cambiano, Valentina, Smith, Jennifer, Bershteyn, Anna, Meyer-Rath, Gesine, Jamieson, Lise, Johnson, Leigh F
Format Journal Article
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Published England BioMed Central Ltd 27.10.2023
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Abstract Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the robustness of estimates and highlight research gaps. As part of a larger project aiming to determine the optimal allocation of funding for HIV services, in this study we compare projections from five mathematical models of the HIV epidemic in South Africa: EMOD-HIV, Goals, HIV-Synthesis, Optima, and Thembisa. The five modelling groups produced estimates of the total population, HIV incidence, HIV prevalence, proportion of people living with HIV who are diagnosed, ART coverage, proportion of those on ART who are virally suppressed, AIDS-related deaths, total deaths, and the proportion of adult males who are circumcised. Estimates were made under a "status quo" scenario for the period 1990 to 2040. For each output variable we assessed the consistency of model estimates by calculating the coefficient of variation and examining the trend over time. For most outputs there was significant inter-model variability between 1990 and 2005, when limited data was available for calibration, good consistency from 2005 to 2025, and increasing variability towards the end of the projection period. Estimates of HIV incidence, deaths in people living with HIV, and total deaths displayed the largest long-term variability, with standard deviations between 35 and 65% of the cross-model means. Despite this variability, all models predicted a gradual decline in HIV incidence in the long-term. Projections related to the UNAIDS 95-95-95 targets were more consistent, with the coefficients of variation below 0.1 for all groups except children. While models produced consistent estimates for several outputs, there are areas of variability that should be investigated. This is important if projections are to be used in subsequent cost-effectiveness studies.
AbstractList Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the robustness of estimates and highlight research gaps. As part of a larger project aiming to determine the optimal allocation of funding for HIV services, in this study we compare projections from five mathematical models of the HIV epidemic in South Africa: EMOD-HIV, Goals, HIV-Synthesis, Optima, and Thembisa. The five modelling groups produced estimates of the total population, HIV incidence, HIV prevalence, proportion of people living with HIV who are diagnosed, ART coverage, proportion of those on ART who are virally suppressed, AIDS-related deaths, total deaths, and the proportion of adult males who are circumcised. Estimates were made under a "status quo" scenario for the period 1990 to 2040. For each output variable we assessed the consistency of model estimates by calculating the coefficient of variation and examining the trend over time. For most outputs there was significant inter-model variability between 1990 and 2005, when limited data was available for calibration, good consistency from 2005 to 2025, and increasing variability towards the end of the projection period. Estimates of HIV incidence, deaths in people living with HIV, and total deaths displayed the largest long-term variability, with standard deviations between 35 and 65% of the cross-model means. Despite this variability, all models predicted a gradual decline in HIV incidence in the long-term. Projections related to the UNAIDS 95-95-95 targets were more consistent, with the coefficients of variation below 0.1 for all groups except children. While models produced consistent estimates for several outputs, there are areas of variability that should be investigated. This is important if projections are to be used in subsequent cost-effectiveness studies.
Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the robustness of estimates and highlight research gaps. As part of a larger project aiming to determine the optimal allocation of funding for HIV services, in this study we compare projections from five mathematical models of the HIV epidemic in South Africa: EMOD-HIV, Goals, HIV-Synthesis, Optima, and Thembisa. The five modelling groups produced estimates of the total population, HIV incidence, HIV prevalence, proportion of people living with HIV who are diagnosed, ART coverage, proportion of those on ART who are virally suppressed, AIDS-related deaths, total deaths, and the proportion of adult males who are circumcised. Estimates were made under a "status quo" scenario for the period 1990 to 2040. For each output variable we assessed the consistency of model estimates by calculating the coefficient of variation and examining the trend over time. For most outputs there was significant inter-model variability between 1990 and 2005, when limited data was available for calibration, good consistency from 2005 to 2025, and increasing variability towards the end of the projection period. Estimates of HIV incidence, deaths in people living with HIV, and total deaths displayed the largest long-term variability, with standard deviations between 35 and 65% of the cross-model means. Despite this variability, all models predicted a gradual decline in HIV incidence in the long-term. Projections related to the UNAIDS 95-95-95 targets were more consistent, with the coefficients of variation below 0.1 for all groups except children. While models produced consistent estimates for several outputs, there are areas of variability that should be investigated. This is important if projections are to be used in subsequent cost-effectiveness studies.
BACKGROUNDMathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the robustness of estimates and highlight research gaps. As part of a larger project aiming to determine the optimal allocation of funding for HIV services, in this study we compare projections from five mathematical models of the HIV epidemic in South Africa: EMOD-HIV, Goals, HIV-Synthesis, Optima, and Thembisa.METHODSThe five modelling groups produced estimates of the total population, HIV incidence, HIV prevalence, proportion of people living with HIV who are diagnosed, ART coverage, proportion of those on ART who are virally suppressed, AIDS-related deaths, total deaths, and the proportion of adult males who are circumcised. Estimates were made under a "status quo" scenario for the period 1990 to 2040. For each output variable we assessed the consistency of model estimates by calculating the coefficient of variation and examining the trend over time.RESULTSFor most outputs there was significant inter-model variability between 1990 and 2005, when limited data was available for calibration, good consistency from 2005 to 2025, and increasing variability towards the end of the projection period. Estimates of HIV incidence, deaths in people living with HIV, and total deaths displayed the largest long-term variability, with standard deviations between 35 and 65% of the cross-model means. Despite this variability, all models predicted a gradual decline in HIV incidence in the long-term. Projections related to the UNAIDS 95-95-95 targets were more consistent, with the coefficients of variation below 0.1 for all groups except children.CONCLUSIONSWhile models produced consistent estimates for several outputs, there are areas of variability that should be investigated. This is important if projections are to be used in subsequent cost-effectiveness studies.
Abstract Background Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the robustness of estimates and highlight research gaps. As part of a larger project aiming to determine the optimal allocation of funding for HIV services, in this study we compare projections from five mathematical models of the HIV epidemic in South Africa: EMOD-HIV, Goals, HIV-Synthesis, Optima, and Thembisa. Methods The five modelling groups produced estimates of the total population, HIV incidence, HIV prevalence, proportion of people living with HIV who are diagnosed, ART coverage, proportion of those on ART who are virally suppressed, AIDS-related deaths, total deaths, and the proportion of adult males who are circumcised. Estimates were made under a “status quo” scenario for the period 1990 to 2040. For each output variable we assessed the consistency of model estimates by calculating the coefficient of variation and examining the trend over time. Results For most outputs there was significant inter-model variability between 1990 and 2005, when limited data was available for calibration, good consistency from 2005 to 2025, and increasing variability towards the end of the projection period. Estimates of HIV incidence, deaths in people living with HIV, and total deaths displayed the largest long-term variability, with standard deviations between 35 and 65% of the cross-model means. Despite this variability, all models predicted a gradual decline in HIV incidence in the long-term. Projections related to the UNAIDS 95–95-95 targets were more consistent, with the coefficients of variation below 0.1 for all groups except children. Conclusions While models produced consistent estimates for several outputs, there are areas of variability that should be investigated. This is important if projections are to be used in subsequent cost-effectiveness studies.
Background Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the robustness of estimates and highlight research gaps. As part of a larger project aiming to determine the optimal allocation of funding for HIV services, in this study we compare projections from five mathematical models of the HIV epidemic in South Africa: EMOD-HIV, Goals, HIV-Synthesis, Optima, and Thembisa. Methods The five modelling groups produced estimates of the total population, HIV incidence, HIV prevalence, proportion of people living with HIV who are diagnosed, ART coverage, proportion of those on ART who are virally suppressed, AIDS-related deaths, total deaths, and the proportion of adult males who are circumcised. Estimates were made under a "status quo" scenario for the period 1990 to 2040. For each output variable we assessed the consistency of model estimates by calculating the coefficient of variation and examining the trend over time. Results For most outputs there was significant inter-model variability between 1990 and 2005, when limited data was available for calibration, good consistency from 2005 to 2025, and increasing variability towards the end of the projection period. Estimates of HIV incidence, deaths in people living with HIV, and total deaths displayed the largest long-term variability, with standard deviations between 35 and 65% of the cross-model means. Despite this variability, all models predicted a gradual decline in HIV incidence in the long-term. Projections related to the UNAIDS 95-95-95 targets were more consistent, with the coefficients of variation below 0.1 for all groups except children. Conclusions While models produced consistent estimates for several outputs, there are areas of variability that should be investigated. This is important if projections are to be used in subsequent cost-effectiveness studies. Keywords: HIV, Mathematical modelling, Epidemic projections, Model comparison, Coefficient of variation
Abstract Background Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the robustness of estimates and highlight research gaps. As part of a larger project aiming to determine the optimal allocation of funding for HIV services, in this study we compare projections from five mathematical models of the HIV epidemic in South Africa: EMOD-HIV, Goals, HIV-Synthesis, Optima, and Thembisa. Methods The five modelling groups produced estimates of the total population, HIV incidence, HIV prevalence, proportion of people living with HIV who are diagnosed, ART coverage, proportion of those on ART who are virally suppressed, AIDS-related deaths, total deaths, and the proportion of adult males who are circumcised. Estimates were made under a “status quo” scenario for the period 1990 to 2040. For each output variable we assessed the consistency of model estimates by calculating the coefficient of variation and examining the trend over time. Results For most outputs there was significant inter-model variability between 1990 and 2005, when limited data was available for calibration, good consistency from 2005 to 2025, and increasing variability towards the end of the projection period. Estimates of HIV incidence, deaths in people living with HIV, and total deaths displayed the largest long-term variability, with standard deviations between 35 and 65% of the cross-model means. Despite this variability, all models predicted a gradual decline in HIV incidence in the long-term. Projections related to the UNAIDS 95–95-95 targets were more consistent, with the coefficients of variation below 0.1 for all groups except children. Conclusions While models produced consistent estimates for several outputs, there are areas of variability that should be investigated. This is important if projections are to be used in subsequent cost-effectiveness studies.
ArticleNumber 2119
Audience Academic
Author Stover, John
Phillips, Andrew
Bershteyn, Anna
Moolla, Haroon
Wulan, Nisaa
Martin-Hughes, Rowan
Johnson, Leigh F
Mudimu, Edinah
Jamieson, Lise
Ten Brink, Debra
Bansi-Matharu, Loveleen
Smith, Jennifer
Cambiano, Valentina
Meyer-Rath, Gesine
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  surname: Johnson
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  organization: Centre for Infectious Disease Epidemiology and Research, Faculty of Health Sciences, University of Cape Town, Anzio Road, Cape Town, 7925, Observatory, South Africa
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Cites_doi 10.1016/j.envres.2019.03.068
10.1371/journal.pmed.1001534
10.1097/QAI.0000000000000605
10.1016/S2352-3018(17)30190-X
10.1371/journal.pone.0111956
10.1016/S2214-109X(13)70172-4
10.1016/S0140-6736(20)30068-4
10.1002/jia2.25776
10.1016/S2214-109X(14)70237-2
10.4102/sajhivmed.v19i1.796
10.1371/journal.pmed.1001245
10.1016/S2214-109X(15)00080-7
10.37623/SJMR.2019.3902
10.1017/CBO9781139062404.012
10.1002/jia2.25097
10.1371/journal.pone.0133255
10.12688/gatesopenres.13220.1
10.2471/BLT.11.086280
10.1016/S2214-109X(22)00310-2
10.7448/IAS.18.1.20628
10.4102/sajhivmed.v18i1.694
10.1016/j.jval.2020.08.001
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Issue 1
Keywords Mathematical modelling
Model comparison
Epidemic projections
HIV
Coefficient of variation
Language English
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References 16995_CR4
16995_CR3
AN Phillips (16995_CR21) 2018; 5
16995_CR2
16995_CR1
JW Eaton (16995_CR26) 2014; 2
RM Stuart (16995_CR6) 2018; 21
JW Eaton (16995_CR10) 2015; 3
H Kustner (16995_CR34) 1991; 18
16995_CR45
16995_CR44
16995_CR43
16995_CR42
cr-split#-16995_CR67.2
16995_CR40
cr-split#-16995_CR67.1
M Jit (16995_CR15) 2014; 2
cr-split#-16995_CR65.2
cr-split#-16995_CR65.1
M Brisson (16995_CR17) 2020; 395
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JA Hontelez (16995_CR13) 2013; 10
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LF Johnson (16995_CR24) 2015; 18
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J Stover (16995_CR19) 2014; 9
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CT Cowie (16995_CR16) 2019; 174
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References_xml – volume: 174
  start-page: 24
  year: 2019
  ident: 16995_CR16
  publication-title: Environ Res
  doi: 10.1016/j.envres.2019.03.068
  contributor:
    fullname: CT Cowie
– volume: 19
  start-page: 80
  year: 1992
  ident: 16995_CR35
  publication-title: Epidemiol Comments
  contributor:
    fullname: R Swanevelder
– ident: #cr-split#-16995_CR67.2
– ident: #cr-split#-16995_CR30.2
– volume: 18
  start-page: 35
  issue: 2
  year: 1991
  ident: 16995_CR34
  publication-title: Epidemiol Comments
  contributor:
    fullname: H Kustner
– ident: #cr-split#-16995_CR68.1
– ident: #cr-split#-16995_CR62.1
– ident: 16995_CR72
– ident: 16995_CR53
– ident: 16995_CR18
– volume: 10
  start-page: e1001534
  issue: 10
  year: 2013
  ident: 16995_CR13
  publication-title: PLoS Med
  doi: 10.1371/journal.pmed.1001534
  contributor:
    fullname: JA Hontelez
– volume: 69
  start-page: 365
  issue: 3
  year: 2015
  ident: 16995_CR20
  publication-title: JAIDS J Acquir Immune Defic Syndr
  doi: 10.1097/QAI.0000000000000605
  contributor:
    fullname: CC Kerr
– ident: 16995_CR2
– ident: 16995_CR47
– ident: 16995_CR28
– ident: 16995_CR43
– volume: 20
  start-page: 35
  issue: 3
  year: 1993
  ident: 16995_CR36
  publication-title: Epidemiol Comments
  contributor:
    fullname: R Swanevelder
– volume: 84
  start-page: 195
  issue: 4
  year: 1994
  ident: 16995_CR37
  publication-title: S Afr Med J
  contributor:
    fullname: HGV Kustner
– volume: 5
  start-page: e146
  issue: 3
  year: 2018
  ident: 16995_CR21
  publication-title: Lancet HIV
  doi: 10.1016/S2352-3018(17)30190-X
  contributor:
    fullname: AN Phillips
– volume: 21
  start-page: 68
  year: 1994
  ident: 16995_CR38
  publication-title: Epidemiol Comments
  contributor:
    fullname: R Swanevelder
– ident: 16995_CR4
– ident: #cr-split#-16995_CR30.1
– ident: #cr-split#-16995_CR65.2
– ident: #cr-split#-16995_CR62.2
– ident: 16995_CR31
– ident: 16995_CR52
– ident: #cr-split#-16995_CR57.2
– ident: 16995_CR56
– ident: 16995_CR1
– volume: 9
  start-page: e111956
  issue: 11
  year: 2014
  ident: 16995_CR19
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0111956
  contributor:
    fullname: J Stover
– ident: 16995_CR63
– volume: 2
  start-page: e23
  issue: 1
  year: 2014
  ident: 16995_CR26
  publication-title: Lancet Glob Health
  doi: 10.1016/S2214-109X(13)70172-4
  contributor:
    fullname: JW Eaton
– volume: 395
  start-page: 575
  issue: 10224
  year: 2020
  ident: 16995_CR17
  publication-title: Lancet
  doi: 10.1016/S0140-6736(20)30068-4
  contributor:
    fullname: M Brisson
– ident: 16995_CR29
– ident: 16995_CR46
– ident: 16995_CR42
– ident: 16995_CR45
– ident: 16995_CR70
– ident: #cr-split#-16995_CR64.2
– volume: 24
  start-page: e25776
  year: 2021
  ident: 16995_CR25
  publication-title: J Int AIDS Soc
  doi: 10.1002/jia2.25776
  contributor:
    fullname: LF Johnson
– volume: 2
  start-page: e406
  issue: 7
  year: 2014
  ident: 16995_CR15
  publication-title: Lancet Glob Health
  doi: 10.1016/S2214-109X(14)70237-2
  contributor:
    fullname: M Jit
– volume-title: ART programme analysis: Reviewing the ART programme from April 2004 to March 2014
  year: 2015
  ident: 16995_CR33
  contributor:
    fullname: Department of Health
– volume: 19
  start-page: 796
  issue: 1
  year: 2018
  ident: 16995_CR5
  publication-title: South Afr J HIV Med
  doi: 10.4102/sajhivmed.v19i1.796
  contributor:
    fullname: KL Hopkins
– ident: 16995_CR51
– ident: #cr-split#-16995_CR57.1
– ident: #cr-split#-16995_CR65.1
– volume: 9
  start-page: e1001245
  issue: 7
  year: 2012
  ident: 16995_CR9
  publication-title: PLoS Med
  doi: 10.1371/journal.pmed.1001245
  contributor:
    fullname: JW Eaton
– ident: 16995_CR55
– ident: #cr-split#-16995_CR66.1
– volume: 3
  start-page: e598
  issue: 10
  year: 2015
  ident: 16995_CR10
  publication-title: Lancet Glob Health
  doi: 10.1016/S2214-109X(15)00080-7
  contributor:
    fullname: JW Eaton
– ident: 16995_CR59
– ident: #cr-split#-16995_CR68.2
  doi: 10.37623/SJMR.2019.3902
– ident: 16995_CR49
– ident: 16995_CR60
– ident: 16995_CR22
– ident: 16995_CR44
– ident: 16995_CR69
– ident: #cr-split#-16995_CR64.1
– start-page: 183
  volume-title: HIV/AIDS in South Africa
  year: 2010
  ident: 16995_CR71
  doi: 10.1017/CBO9781139062404.012
  contributor:
    fullname: L Myer
– ident: #cr-split#-16995_CR67.1
– volume: 21
  start-page: e25097
  issue: 4
  year: 2018
  ident: 16995_CR6
  publication-title: J Int AIDS Soc
  doi: 10.1002/jia2.25097
  contributor:
    fullname: RM Stuart
– volume: 23
  start-page: 4
  year: 1997
  ident: 16995_CR41
  publication-title: Epidemiological Comments
  contributor:
    fullname: Department of Health
– volume: 10
  start-page: e0133255
  issue: 7
  year: 2015
  ident: 16995_CR14
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0133255
  contributor:
    fullname: T Rehle
– volume: 5
  start-page: 15
  year: 2021
  ident: 16995_CR11
  publication-title: Gates Open Res
  doi: 10.12688/gatesopenres.13220.1
  contributor:
    fullname: EL Korenromp
– volume: 89
  start-page: 278
  issue: 4
  year: 2011
  ident: 16995_CR23
  publication-title: Bull World Health Organ
  doi: 10.2471/BLT.11.086280
  contributor:
    fullname: JK Birnbaum
– ident: 16995_CR54
– volume-title: Cost-effectiveness of voluntary male medical circumcision (VMMC) for HIV prevention across sub-Saharan Africa: results from five independent models
  year: 2022
  ident: 16995_CR8
  contributor:
    fullname: L Bansi-Matharu
– ident: 16995_CR50
– ident: #cr-split#-16995_CR66.2
– volume: 10
  start-page: e1298
  issue: 9
  year: 2022
  ident: 16995_CR12
  publication-title: Lancet Glob Health
  doi: 10.1016/S2214-109X(22)00310-2
  contributor:
    fullname: A Bershteyn
– volume: 18
  start-page: 20628
  issue: 1
  year: 2015
  ident: 16995_CR24
  publication-title: J Int AIDS Soc
  doi: 10.7448/IAS.18.1.20628
  contributor:
    fullname: LF Johnson
– ident: 16995_CR58
– ident: 16995_CR3
– volume: 18
  start-page: 1
  issue: 1
  year: 2017
  ident: 16995_CR32
  publication-title: South Afr J HIV Med
  doi: 10.4102/sajhivmed.v18i1.694
  contributor:
    fullname: LF Johnson
– ident: 16995_CR48
– ident: 16995_CR27
– ident: 16995_CR40
– ident: 16995_CR61
– volume: 23
  start-page: 1509
  issue: 11
  year: 2020
  ident: 16995_CR7
  publication-title: Value in Health
  doi: 10.1016/j.jval.2020.08.001
  contributor:
    fullname: AL Avanceña
– volume: 23
  start-page: 3
  year: 1995
  ident: 16995_CR39
  publication-title: Epidemiol Comments
  contributor:
    fullname: Department of Health
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Snippet Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can test the...
Abstract Background Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical...
Background Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can...
BackgroundMathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can...
BACKGROUNDMathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical models can...
Abstract Background Mathematical models are increasingly used to inform HIV policy and planning. Comparing estimates obtained using different mathematical...
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pubmedcentral
proquest
gale
crossref
pubmed
SourceType Open Website
Open Access Repository
Aggregation Database
Index Database
StartPage 2119
SubjectTerms Acquired immune deficiency syndrome
Adult
Adults
AIDS
Antiretroviral therapy
Calibration
Child
Circumcision
Coefficient of variation
Collaboration
Confidence intervals
Consistency
Consortia
Cost analysis
COVID-19
Distribution
Epidemic projections
Epidemics
Estimates
Evaluation
Fatalities
Forecasting
Forecasts and trends
HIV
HIV infection
HIV Infections - epidemiology
Human immunodeficiency virus
Humans
Incidence
Male
Males
Mathematical modelling
Mathematical models
Medical tests
Model comparison
Models, Theoretical
Policy and planning
Public health
Robustness (mathematics)
South Africa
South Africa - epidemiology
Standard deviation
Trends
Variability
Variables
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Title A quantitative assessment of the consistency of projections from five mathematical models of the HIV epidemic in South Africa: a model comparison study
URI https://www.ncbi.nlm.nih.gov/pubmed/37891514
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https://search.proquest.com/docview/2883576353
https://pubmed.ncbi.nlm.nih.gov/PMC10612295
https://doaj.org/article/7cb193ce313b4b999a1376e2170078b1
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