Projection of HIV/AIDS Mortality in Adamawa State through the Lee-Carter Model: Strides toward SDG-3
DOI:
https://doi.org/10.59653/ijmars.v3i02.1712Keywords:
Mortality, HIV/AIDS, Lee-Carter, Projection, NigeriaAbstract
Globally, HIV/AIDS remains a significant health concern, with profound impacts in developing nations, including Nigeria. This study aims to project mortality among HIV patients in Adamawa State using the Lee-Carter model to assess progress towards the third Sustainable Development Goal (SDG-3) - terminating AIDS by 2030. Mortality data for 2011-2020 on HIV patients aged 15-59 years receiving antiretroviral therapy (ART) was obtained from Adamawa State AIDS control database. The Lee-Carter model, using the Singular Value decomposition (SVD) for parameter estimation was fitted to estimate age-specific parameters. The time series component was forecast using ARIMA(0,1,0). Mortality data from 2011 to 2020 revealed a substantial 296% reduction in mortality, a testament to government and NGO interventions. The study delineates varied age group responses to improvements in mortality rates, pinpointing ages 55-59 as the most affected, while ages 15-19 exhibit the lowest mortality rates. Furthermore, individuals aged 20-24 show heightened responsiveness to general mortality improvements compared to other age cohorts. This work substantiates that Adamawa State has achieved substantial progress, exceeding the SDG-3 target of a 90% decline in HIV/AIDS patient mortality rate, setting a promising trajectory towards an AIDS-free society by 2030. However targeted strategies are still needed for older patients.
Downloads
References
Assefa, Y. and Gilks, C. F. (2020). Ending the epidemic of HIV/AIDS by 2030: Will there be an endgame to HIV, or an endemic HIV requiring an integrated health systems response in many countries? International Journal of Infectious Diseases, 100: 273-277. https://doi.org/10.1016/j.ijid.2020.09.011
Bergeron-Boucher, M.-P. and Kjærgaard, S. (2022). Mortality forecasting at age 65 and above: an age-specific evaluation of the Lee-Carter model. Scandinavian Actuarial Journal, 2022(1): 64-79. https://doi.org/10.1080/03461238.2021.1928542
Chen, Y. and Khaliq, A. Q. M. (2022). Comparative Study of Mortality Rate Prediction Using Data-Driven Recurrent Neural Networks and the Lee–Carter Model. Big Data and Cognitive Computing, 6(4): 134.
Debón, A., Haberman, S., Montes, F. and Otranto, E. (2021). Do Different Models Induce Changes in Mortality Indicators? That Is a Key Question for Extending the Lee-Carter Model. International Journal of Environmental Research and Public Health, 18(4): 2204.
Fajar, M. and Fajariyanto, E. (2022). Lee-Carter Modeling for Mortality in Indonesia with A Bayesian Approach. BAREKENG: Jurnal Ilmu Matematika dan Terapan, 16(4): 1241-1248. https://doi.org/10.30598/barekengvol16iss4pp1241-1248
Guaraldi, G., Orlando, G., Zona, S., Menozzi, M., Carli, F., Garlassi, E., Berti, A., Rossi, E., Roverato, A. and Palella, F. (2011). Premature Age-Related Comorbidities Among HIV-Infected Persons Compared With the General Population. Clinical Infectious Diseases, 53(11): 1120-1126. https://doi.org/10.1093/cid/cir627
Ibrahim, N. S. M., Lazam, N. M. and Shair, S. N. (2021). Forecasting Malaysian mortality rates using the Lee-Carter model with fitting period variants. Journal of Physics: Conference Series, 1988(1): 012103. https://doi.org/10.1088/1742-6596/1988/1/012103
Jones, J., Sullivan, P. S. and Curran, J. W. (2019). Progress in the HIV epidemic: Identifying goals and measuring success. PLOS Medicine, 16(1): e1002729. https://doi.org/10.1371/journal.pmed.1002729
Liu, Q., Ling, C., Li, D. and Peng, L. (2019). Bias-Corrected Inference for a Modified Lee–Carter Mortality Model. ASTIN Bulletin, 49(2): 433-455. https://doi.org/10.1017/asb.2019.9
Mahy, M. I., Sabin, K. M., Feizzadeh, A. and Wanyeki, I. (2021). Progress towards 2020 global HIV impact and treatment targets. Journal of the International AIDS Society, 24(S5): e25779. https://doi.org/https://doi.org/10.1002/jia2.25779
Mills, E. J., Bakanda, C., Birungi, J., Chan, K., Ford, N., Cooper, C. L., Nachega, J. B., Dybul, M. and Hogg, R. S. (2011). Life expectancy of persons receiving combination antiretroviral therapy in low-income countries: a cohort analysis from Uganda. Annals of Internal Medicine, 155(4): 209-216. https://doi.org/10.7326/0003-4819-155-4-201108160-00358
Nigri, A., Levantesi, S., Marino, M., Scognamiglio, S. and Perla, F. (2019). A Deep Learning Integrated Lee–Carter Model. Risks, 7(1): 33.
Odugbesan, J. A. and Rjoub, H. (2019). Relationship among HIV/AIDS Prevalence, Human Capital, Good Governance, and Sustainable Development: Empirical Evidence from Sub-Saharan Africa. Sustainability, 11(5): 1348.
Odugbesan, J. A. and Rjoub, H. (2020). Evaluating HIV/Aids prevalence and sustainable development in sub-Saharan Africa: the role of health expenditure. African Health Sciences, 20(2): 568-578. https://doi.org/10.4314/ahs.v20i2.4
Peres, R. M. (2022). Modelling Hospital Admission Rates in São Paulo, Brazil: Lee-Carter Model Vs. Neural Networks Universidade de Lisboa (Portugal)].
Rodger, A. J., Lodwick, R., Schechter, M., Deeks, S., Amin, J., Gilson, R., Paredes, R., Bakowska, E., Engsig, F. N., Phillips, A. and for the INSIGHT SMART, E. S. G. (2013). Mortality in well controlled HIV in the continuous antiretroviral therapy arms of the SMART and ESPRIT trials compared with the general population. AIDS, 27(6): 973-979. https://doi.org/10.1097/QAD.0b013e32835cae9c
Safitri, L., Mardiyati, S. and Rahim, H. (2018). Estimation of mortality rate in Indonesia with Lee-Carter model. AIP Conference Proceedings, 2023(1). https://doi.org/10.1063/1.5064207
Safitri, Y. R., Mardiyati, S. and Malik, M. (2019). The Cairns-Blake-Dowd model to forecast Indonesian mortality rates. AIP Conference Proceedings, 2168(1). https://doi.org/10.1063/1.5132466
Smit, M., Brinkman, K., Geerlings, S., Smit, C., Thyagarajan, K., Sighem, A. v., de Wolf, F. and Hallett, T. B. (2015). Future challenges for clinical care of an ageing population infected with HIV: a modelling study. The Lancet Infectious Diseases, 15(7): 810-818. https://doi.org/10.1016/S1473-3099(15)00056-0
Ukaegbu, E., Alibekova, R., Ali, S., Crape, B. and Issanov, A. (2022). Trends of HIV/AIDS knowledge and attitudes among Nigerian women between 2007 and 2017 using Multiple Indicator Cluster Survey data. BMC Public Health, 22(1): 440. https://doi.org/10.1186/s12889-022-12865-y
UNAIDS. (2020). Global HIV & AIDS Statistics — 2020 Fact Sheet. https://www.unaids.org/en/resources/fact-sheet
Zili, A. H. A., Mardiyati, S. and Lestari, D. (2018). Forecasting Indonesian mortality rates using the Lee-Carter model and ARIMA method. AIP Conference Proceedings, 2023(1). https://doi.org/10.1063/1.5064209
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2025 Wasinda Bassi Nuhu, Hyelda Stephen, Usman Almujaddid Abdulkadir, Richard Martins Sirante, Francisca Jugivetje Sirante

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).