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. 2021 Jun;8(6):e363-e375.
doi: 10.1016/S2352-3018(21)00051-5.

Subnational mapping of HIV incidence and mortality among individuals aged 15-49 years in sub-Saharan Africa, 2000-18: a modelling study

Local Burden of Disease HIV Collaborators
Collaborators

Subnational mapping of HIV incidence and mortality among individuals aged 15-49 years in sub-Saharan Africa, 2000-18: a modelling study

Local Burden of Disease HIV Collaborators. Lancet HIV. 2021 Jun.

Abstract

Background: High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa.

Methods: In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15-49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000-18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit.

Findings: The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2·8 (95% uncertainty interval 2·1-3·8) in Mauritania to 1585·9 (1369·4-1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7-0·9) in Mauritania to 676·5 (513·6-888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique, had the highest estimated HIV incidence (4661·7 [2544·8-8120·3]) cases per 100 000 people in 2018 and Inhassunge District, Zambezia Province, Mozambique, had the highest estimated HIV mortality rate (1163·0 [679·0-1866·8]) deaths per 100 000 people. Further, the rate of reduction in HIV incidence and mortality from 2000 to 2018, as well as the ratio of new infections to the number of people living with HIV was highly variable. Although most second-level administrative units had declines in the number of new cases (3316 [81·1%] of 4087 units) and number of deaths (3325 [81·4%]), nearly all appeared well short of the targeted 75% reduction in new cases and deaths between 2010 and 2020.

Interpretation: Our estimates suggest that most second-level administrative units in sub-Saharan Africa are falling short of the targeted 75% reduction in new cases and deaths by 2020, which is further compounded by substantial within-country variability. These estimates will help decision makers and programme implementers expand access to ART and better target health resources to higher burden subnational areas.

Funding: Bill & Melinda Gates Foundation.

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Conflict of interest statement

Declaration of interests R Ancuceanu reports consultancy or speakers' fees from UCB, Sandoz, Abbvie, Zentiva, Teva, Larophram, Cegedim, Angelini, Biessen Pharma, Hofigal, AstraZeneca, and Stada. J W Eaton reports grants from Bill & Melinda Gates Foundation, the US National Institutes of Health, and UNAIDS, during the conduct of the study. J J Jozwiak reports personal fees from Boehringer Ingelheim, Teva, Zentiva, and Amgen, outside the submitted work. K Krishan reports non-financial support from University Grants Commission Centre of Advanced Study, (CAS II), awarded to the Department of Anthropology, Panjab University, Chandigarh, India, outside the submitted work. J F Mosser reports grants from Bill & Melinda Gates Foundation, during the conduct of the study. S R Pandi-Perumal reports non-financial support from Somnogen Canada; and personal feesf rom royalties associated with editing volumes, during the conduct of the study. M J Postma reports grants and personal fees from MSD, GlaxoSmithKline, Pfizer, Boehringer Ingelheim, Novavax, Bristol Myers Squibb, Astra Zeneca, Sanofi, IQVIA, and Seqirus; personal fees from Quintiles, Novartis, and Pharmerit; grants from Bayer, BioMerieux, WHO, EU, Foundation for Innovative New Diagnostics, Antilope, Ministry of Research, Technology and Higher Education of the Republic of Indonesia, Indonesia Endowment Fund for Education, and Budi; stock options in Health-Ecore and PAG; and acting as advisor to Asc Academics, all outside the submitted work. A E Schutte reports personal fees from Servier, Takeda, Abbott, and Novartis, all outside the submitted work. J A Singh reports personal fees from Crealta/Horizon, Medisys, Fidia, Two labs, Adept Field Solutions, Clinical Care Options, Clearview Healthcare Partners, Putnam Associates, Focus forward, Navigant Consulting, Spherix, MedIQ, UBM, Trio Health, Medscape, WebMD, Practice Point Communications, Simply Speaking, the US National Institutes of Health, and the American College of Rheumatology; currently or previously owning stock options in TPT Global Tech, Vaxart Pharmaceuticals, Charlotte's Web Holdings, Amarin, Viking, and Moderna; and membership with OMERACT, an international organisation that develops measures for clinical trials and receives arm's length funding from 12 pharmaceutical companies, the US Food and Drug Administration Arthritis Advisory Committee, the Veterans Affairs Rheumatology Field Advisory Committee, and the University of Alabama at Birmingham Cochrane Musculoskeletal Group Satellite Center on Network Meta-analysis. A C Tsai reports personal fees from Elsevier and the Public Library of Science, outside the submitted work. All other authors declare no competing interests.

Figures

Figure 1
Figure 1
HIV incidence among individuals aged 15–49 years in sub-Saharan Africa in 2018 Incidence among individuals aged 15–49 years by (A) country, (B) first-level administrative unit, and (C) second-level administrative unit. Lakes and areas with fewer than ten people per 1 × 1 km and classified as barren or sparsely vegetated are coloured light grey. Areas in dark grey were not included in the analysis. Estimates in areas that are crossed are based on national, rather than subnational, estimates of antiretroviral therapy coverage only.
Figure 2
Figure 2
HIV mortality among individuals aged 15–49 years in sub-Saharan Africa in 2018 (A) HIV mortality among individuals aged 15–49 years by country, (B) first-level administrative unit, and (C) second-level administrative unit. Lakes and areas with fewer than ten people per 1 × 1 km and classified as barren or sparsely vegetated are coloured light grey. Areas in dark grey were not included in the analysis. Estimates in areas that are crossed are based on national, rather than subnational, estimates of antiretroviral therapy coverage only.
Figure 3
Figure 3
Incident HIV cases and deaths among individuals aged 15–49 years in sub-Saharan Africa in 2018 (A) Number of incident HIV cases and (B) HIV deaths among individuals aged 15–49 years in 2018 by second-level administrative unit. Lakes and areas with fewer than ten people per 1 × 1 km and classified as barren or sparsely vegetated are coloured light grey. Areas in dark grey were not included in the analysis. Estimates in areas that are crossed are based on national, rather than subnational, estimates of antiretroviral therapy coverage only.
Figure 4
Figure 4
Percentage reduction in incident HIV cases in sub-Saharan Africa from 2010 to 2018 (A) Reduction in the number of incident HIV cases (%) between 2010 and 2018 among individuals aged 15–49 years by country, (B) first-level administrative unit, and (C) second-level administrative unit. Lakes and areas with fewer than ten people per 1 × 1 km and classified as barren or sparsely vegetated are coloured light grey. Areas in dark grey were not included in the analysis. Estimates in areas that are crossed are based on national, rather than subnational, estimates of antiretroviral therapy coverage only. A 75% reduction in HIV incidence by 2020 is a UNAIDS fast-track goal. Progress towards this target by country highlighting the best and worst performing subnational units is shown in panel D.
Figure 5
Figure 5
Percentage reduction in HIV deaths in sub-Saharan Africa from 2010 to 2018 (A) Reduction in the number of HIV deaths (%) between 2010 and 2018 among individuals aged 15–49 years by country, (B) first-level administrative unit, and (C)second-level administrative unit. Lakes and areas with fewer than ten people per 1 × 1 km and classified as barren or sparsely vegetated are coloured light grey. Areas in dark grey were not included in the analysis. Estimates in areas that are crossed are based on national, rather than subnational, estimates of antiretroviral therapy coverage only. A 75% reduction in HIV deaths by 2020 is a UNAIDS fast-track goal. Progress towards this target by country highlighting the best and worst performing subnational units is shown in panel D.
Figure 6
Figure 6
HIV incidence to prevalence ratio in sub-Saharan Africa in 2018 Number of new infections among individuals aged 15–49 years divided by the number of individuals living with HIV aged 15–49 years by (A) country, (B) first-level administrative unit, and (C) second-level administrative unit. Lakes and areas with fewer than ten people per 1 × 1 km and classified as barren or sparsely vegetated are coloured light grey. Areas in dark grey were not included in the analysis. Estimates in areas that are crossed are based on national, rather than subnational, estimates of antiretroviral therapy coverage only. Achieving a sustained incidence to prevalence ratio of less than 0·03 by 2020 is a UNAIDS fast-track goal.
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References

    1. Ghys PD, Williams BG, Over M, Hallett TB, Godfrey-Faussett P. Epidemiological metrics and benchmarks for a transition in the HIV epidemic. PLoS Med. 2018;15 - PMC - PubMed
    1. UN General Assembly Political declaration on HIV and AIDS: on the fast track to accelerating the fight against HIV and to ending the AIDS epidemic by 2030. 2016. https://www.unaids.org/sites/default/files/media_asset/2016-political-de...
    1. Anderson S-J, Cherutich P, Kilonzo N. Maximising the effect of combination HIV prevention through prioritisation of the people and places in greatest need: a modelling study. Lancet. 2014;384:249–256. - PubMed
    1. McGillen JB, Anderson S-J, Dybul MR, Hallett TB. Optimum resource allocation to reduce HIV incidence across sub-Saharan Africa: a mathematical modelling study. Lancet HIV. 2016;3:e441–e448. - PubMed
    1. Justman JE, Mugurungi O, El-Sadr WM. HIV population surveys—bringing precision to the global response. N Engl J Med. 2018;378:1859–1861. - PubMed

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