Forecasting tuberculosis in Ethiopia using deep learning: progress toward sustainable development goal evidence from global burden of disease 1990-2021.

Abstract

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.