|BRIEF RESEARCH ARTICLE
|Year : 2020 | Volume
| Issue : 5 | Page : 76-78
Aging of HIV epidemic in India: Insights from HIV estimation modeling under the national aids control programme
Pradeep Kumar1, Damodar Sahu2, Nalini Chandra3, Arvind Kumar4, Shobini Rajan5
1 Consultant, Strategic Information Management Division, National AIDS Control Organization, Ministry of Health and Family Welfare, Government of India, New Delhi, India
2 Scientist F, Department of Epidemiology and Behavioral Sciences, ICMR-National Institute of Medical Statistics, New Delhi, India
3 Advisor, Strategic Information Division, The Joint United Nations Programme on HIV/AIDS (UNAIDS), New Delhi, India
4 Associate Consultant, Strategic Information Management Division, National AIDS Control Organization, Ministry of Health and Family Welfare, Government of India, New Delhi, India
5 Assistant Director General, Strategic Information Management Division, National AIDS Control Organization, Ministry of Health and Family Welfare, Government of India, India
|Date of Submission||19-Nov-2019|
|Date of Decision||28-Feb-2020|
|Date of Acceptance||06-Mar-2020|
|Date of Web Publication||14-Apr-2020|
Dr. Pradeep Kumar
National AIDS Control Organization, Ministry of Health and Family Welfare, Government of India, 36 Janpath Road, New Delhi - 110 001
Source of Support: None, Conflict of Interest: None
| Abstract|| |
People living with HIV are gradually getting older as a result of better survival with increased uptake of antiretroviral treatment in India. We aimed to quantify the aging HIV-infected population in India by undertaking a mathematical model analysis of 2017 rounds of HIV burden estimations under the National AIDS Control Programme. Our analysis projects that the mean age of HIV-infected people will increase from 38.4 years in 2005 to 45.5 years in 2025 with the proportion of HIV-infected people aged 50 years or older increasing from 19% in 2005 to 37% in 2025. This aging HIV epidemic is anticipated to lead to more non-AIDS morbidities, increased treatment complexity, and an inevitable need for multidisciplinary health-care services to ensure continued high-quality survival.
Keywords: Aging, antiretroviral therapy, HIV/AIDS, India, people were living with HIV
|How to cite this article:|
Kumar P, Sahu D, Chandra N, Kumar A, Rajan S. Aging of HIV epidemic in India: Insights from HIV estimation modeling under the national aids control programme. Indian J Public Health 2020;64, Suppl S1:76-8
|How to cite this URL:|
Kumar P, Sahu D, Chandra N, Kumar A, Rajan S. Aging of HIV epidemic in India: Insights from HIV estimation modeling under the national aids control programme. Indian J Public Health [serial online] 2020 [cited 2020 May 29];64, Suppl S1:76-8. Available from: http://www.ijph.in/text.asp?2020/64/5/76/282411
It is estimated that around 37.9 million people were living with HIV (PLHIV)/AIDS globally by the end of 2018. An estimated 23.3 million of the total PLHIV were on treatment, more than three times as many as in 2010. As more and more PLHIV are initiating and continuing on antiretroviral therapy (ART), the demographics of the HIV epidemic is changing. The AIDS-related death declined by around 55% since its peak in 2004 and an increasingly larger proportion of older individuals is being reflected in total PLHIV size., It has been predicted that by 2030, 73% of individuals infected with HIV will be aged 50 years or older.
This aging of HIV epidemic has been accompanied by increasingly affected PLHIV with noncommunicable diseases. Projections have been that by 2030, 78% of the PLHIV aged 50 years or more will be having cardiovascular disease and 17% will have diabetes. The growing body of evidence on the issue led advocates to declare aging as the number 1 problem in HIV today.
India, with an estimated 2.14 million PLHIV, has the third-largest HIV/AIDS epidemic in world. India response to the HIV/AIDS epidemic has been extremely successful with a decline of more than 80% in new HIV infections since its peak in 1995 and 71% in AIDS-related deaths since its peak in 2005. Scale-up of the ART has been a key component of priority under the National AIDS Control Programme (NACP). HIV-infected people are now put on ART as soon as detected HIV positive, and around 1.3 million PLHIV were on ART as on March 2019. However, the impact of ART scale-up and improved survival of PLHIV on the size of the PLHIV aged 50 years or older in India is currently unknown. In view of this, the present investigation quantifies and reports the estimate of the overall age profile as well as HIV prevalence and numbers of HIV- infected people aged 50 or older in India over the years.
India biennially undertakes HIV estimation and projection exercises under the NACP to provide update on the status of HIV epidemic by states/UT for use in planning processes. The exercise is undertaken using UNAIDS recommended “Spectrum” model. The detailed method of HIV estimations using spectrum model has been described elsewhere., In brief, spectrum is a mathematical model where user inputs time trend data on demographics, prevention of mother-to-child transmission (PMTCT) and ART coverage, and HIV prevalence from surveillance and surveys. The projections start with estimate of adult incidence by age and sex. The incidence cases progress over time to lower CD4 counts depending on the ART coverage and are subjected to AIDS-related mortalities. HIV-infected people are also subjected to non-AIDS mortality at the same rate as that of noninfected people. The tool generates the estimates for HIV prevalence, HIV incidence, number of PLHIV, AIDS-related deaths, and need for PMTCT. We used the 2017 round of HIV estimations and projections model under NACP available with the National AIDS Control Organization, Ministry of Health and Family Welfare, Government of India to quantify the aging HIV-infected population in India.
The model estimates that the mean age of HIV- infected people will increase from 38·4 years (male: 38.5 years, female: 38.2 years) in 2005–41.4 years (male: 41.4 years, female: 41.4 years) in 2015–45.5 years (male: 45.3 years, female: 45.8 years) in 2025 [Table 1].
|Table 1: HIV epidemiological parameters/indicators by age and sex as estimated by the spectrum model|
Click here to view
HIV prevalence among the population aged 50+ hovered in the range of 0.26%–0.28% between 2010 and 2019 and then increased to 0.32% in 2025. The HIV prevalence among the population aged 50+ is estimated to be 0.32% in 2005, which came down to 0.26% in 2010 and then will increase to 0.32% in 2025.
The total HIV-infected population aged 50+ increased by 48% from 0.52 million in 2005 to more than 0.76 million in 2025. The proportion of 50+ HIV population in total HIV population increased from 19% in 2005 to 37% in 2025 [Figure 1].
The AIDS-related death among 50+ PLHIV is estimated to decrease from around 69,000 in 2005 to around 12,000 in 2025. Less than 30% of the total AIDS-related deaths in 2005 were among older PLHIV which increased to 45% in 2025.
The profile of PLHIV/AIDS in India is changing. The average age of HIV infected people in India has increased and is expected to further increase with expanding ART uptake and improved survival associated with that. Almost two-fifth of HIV-infected people in 2025 will be 50 years or older. Similar finding have been reported by Negin et al. in sub-Saharan Africa and Smit et al. in the Netherlands. As the population infected with HIV is getting older, it is expected to have implications for health-care services which will require increasing focus of to respond to the issues associated with aging in a population of individuals living with HIV.
Older PLHIV will show slower and more limited immunological responses to ART. Besides, being on ART for a long period is associated with various noncommunicable diseases, including ischemic heart disease, diabetes, and certain cancers., With these, the PLHIV will face pharmacological challenges not only because they will require a greater number of drugs to treat these comorbidities but also will have increased risk for drug interactions exacerbated by reductions in renal and hepatic functioning. Clearly, older PLHIV will require tailored health-care services monitoring the risk factors and offering risk reductions services.
In conclusion, our analyses demonstrate an aging population living with HIV in India. To the best of our knowledge, this is the first attempt in quantifying the aging of HIV epidemic in India, and this providing insights for policymakers and all other stakeholders toward designing a comprehensive package of health-care services needed for a growing geriatric PLHIV population in near future.
The authors would like to thank the State AIDS Control Societies, current and previous national and regional institutes (NIHFW-New Delhi, AIIMS-New Delhi, ICMR-NIMS, New Delhi, ICMR-NARI, Pune, ICMR-NIE, Chennai, ICMR-NICED, Kolkata, PGIMER-Chandigarh and RIMS-Imphal) and sentinel site staff and other UN partners (UNAIDS and WHO) for their support in 2017 rounds of HIV Estimations.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Smit M, Brinkman K, Geerlings S, Smit C, Thyagarajan K, Sighem Av, et al
. Future challenges for clinical care of an ageing population infected with HIV: A modelling study. Lancet Infect Dis 2015;15:810-8.
Vance DE, Cody SL. Predictions of geriatric HIV in 2030. Lancet Infect Dis 2015;15:753-4.
France D. Another Kind of AIDS Crisis. New York: Magazine, 2009.
Government of India. Annual Report 2018-19. New Delhi: Department of Health and Family Welfare, Government of India; 2019.
Stover J, Brown T, Marston M. Updates to the spectrum/estimation and projection package (EPP) model to estimate HIV trends for adults and children. Sex Transm Infect 2012;88 Suppl 2:i11-6.
Negin J, Bärnighausen T, Lundgren JD, Mills EJ. Aging with HIV in Africa: The challenges of living longer. AIDS 2012;26 Suppl 1:S1-5.
Manfredi R, Calza L, Cocchi D, Chiodo F. Antiretroviral treatment and advanced age: Epidemiologic, laboratory, and clinical features in the elderly. J Acquir Immune Defic Syndr 2003;33:112-4.