Treffer: Forecasting tuberculosis in Ethiopia using deep learning: progress toward sustainable development goal evidence from global burden of disease 1990-2021.
PLoS One. 2017 May 2;12(5):e0176690. (PMID: 28464015)
BMJ Open. 2025 Feb 13;15(2):e093808. (PMID: 39947830)
EClinicalMedicine. 2020 Feb 10;20:100268. (PMID: 32300732)
Pan Afr Med J. 2022 Nov 17;43:146. (PMID: 36785687)
BMC Public Health. 2022 Oct 19;22(1):1938. (PMID: 36261815)
Neural Comput. 1997 Nov 15;9(8):1735-80. (PMID: 9377276)
Int J Environ Res Public Health. 2018 Jul 27;15(8):. (PMID: 30060525)
Lancet. 2024 May 18;403(10440):2133-2161. (PMID: 38642570)
Neural Comput. 2000 Oct;12(10):2451-71. (PMID: 11032042)
J Korean Med Sci. 2023 Feb 06;38(5):e43. (PMID: 36747365)
Euro Surveill. 2019 Mar;24(12):. (PMID: 30914077)
Annu Rev Public Health. 2013;34:271-86. (PMID: 23244049)
BMC Infect Dis. 2018 Dec 18;18(1):676. (PMID: 30563476)
PLoS One. 2018 Mar 27;13(3):e0194889. (PMID: 29584784)
Int J Infect Dis. 2022 Nov;124 Suppl 1:S26-S29. (PMID: 35321845)
PLoS One. 2017 Dec 15;12(12):e0188941. (PMID: 29244814)
Infect Dis Poverty. 2024 Aug 19;13(1):60. (PMID: 39155365)
Infect Drug Resist. 2024 Jul 26;17:3241-3251. (PMID: 39081457)
Lancet Infect Dis. 2018 Mar;18(3):261-284. (PMID: 29223583)
PLoS One. 2015 Jun 15;10(6):e0128907. (PMID: 26075615)
PLOS Glob Public Health. 2023 Oct 23;3(10):e0001271. (PMID: 37870997)
Lancet Infect Dis. 2024 Jul;24(7):698-725. (PMID: 38518787)
IEEE Trans Neural Netw. 1994;5(2):157-66. (PMID: 18267787)
Eur J Med Res. 2022 Feb 12;27(1):24. (PMID: 35151350)
Sci Rep. 2019 Nov 29;9(1):17928. (PMID: 31784625)
Infect Drug Resist. 2019 Jul 26;12:2311-2322. (PMID: 31440067)
BMC Public Health. 2024 Nov 11;24(1):3111. (PMID: 39529028)
PLoS One. 2016 Jul 25;11(7):e0157734. (PMID: 27455108)
Weitere Informationen
Background: Tuberculosis (TB) is a preventable and treatable disease caused by Mycobacterium tuberculosis, which most often affects lungs and remains the second leading cause of death from infectious diseases worldwide. The National End TB Strategy aims to eliminate the TB epidemic by reducing TB-related deaths by 95% and decreasing incident TB cases by 90% by 2030, using 2015 as the baseline. Tuberculosis is the primary cause of morbidity, ranks third in hospital admissions, and is the second leading cause of death in Ethiopia, following malaria. Hence, this analysis aims to forecast and provide evidence that supports the combined intervention to monitor TB incidence in Ethiopia's progress toward the Sustainable Development Goals.
Method: Study employed secondary data analysis from the Global Burden of Disease database (1990-2021) to forecast tuberculosis incidence in Ethiopia. LSTM-based models, including multistep LSTM and hybrid ARIMA + LSTM, were implemented for prediction in TensorFlow frameworks while ARIMA model was built using the statsmodels and pmdarima libraries using the Python programming language. The statistical significance level was set at 0.05 to check data stationarity. Model performance was evaluated using Root Mean Squared Error, Mean Absolute Error, Mean Absolute Percentage Error, and Symmetric Mean Absolute Percentage Error. Finally, the best model was used to forecast the next 9 years from 2021 to 2030.
Result: According to GBD data, the incidence of TB in Ethiopia shows a long-term downward trend, decreasing from 466.93 cases per 100,000 in 1990 to 185.53 by 2021. The analysis result revealed that multistep LSTM model outperformed all achieving MAE: 5.53, RMSE: 6.74, MAPE: 2.72% and sMAPE:2.76%. The incidence of tuberculosis in Ethiopia is projected to decline slightly through 2030, according to a multi-step LSTM model. The forecast estimates that the TB incidence will be 189 cases per 100,000 people by 2025, decreasing further to 179 by 2030.
Conclusion: Overall, the analysis indicates that Ethiopia is still falling short of the national "END TB strategy" goal of 90% reduction in TB incidence cases per 100,000 population by 2030. It highlights the necessity for Ethiopia's TB control strategies to improve access to prevention, early diagnosis, and treatment, focusing on high-risk groups and vulnerable populations.
(© 2025. The Author(s).)
Declarations. Ethics approval and consent to participate: The manuscript used open-access GBD 2021 secondary data from the Institutes of Health Metrics and Evaluation (IHME), University of Washington Health Data portal. Permission for data access is typically confirmed by email. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. Clinical trial number: Not applicable.