ArticleFrontiers in public health2022
Development and comparison of predictive models for sexually transmitted diseases-AIDS, gonorrhea, and syphilis in China, 2011-2021.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
- Analysis of the spatio-temporal pattern and evolutionary trends of syphilis at township level in Xining City, Qinghai Province, China from 2008 to 2024.Scientific reports · 2026Article
- Optimal testing frequency for sexually transmitted infections among men who have sex with men and transgender women who use HIV pre-exposure prophylaxis in Australia, Brazil and Thailand: a cost-effectiveness analysis.The Lancet regional health. Western Pacific · 2026Article
- Spatiotemporal distribution of syphilis in Mainland China during the 17 years from 2004 to 2020.BMC public health · 2026Article
- Study on the prediction performance of AIDS monthly incidence in Xinjiang based on time series and deep learning models.BMC public health · 2025Article
- Gonorrhoea among China's aging population: a 20-year nationwide analysis of epidemiological trends with 5-year projections.Frontiers in public health · 2025Article
- Spatio-Temporal Distribution Characteristics of Syphilis: on the Scale of Towns (Streets) in Nantong City, Jiangsu Province, China.International journal of public health · 2025Article
- Enhancing HIV/STI decision-making: challenges and opportunities in leveraging predictive models for individuals, healthcare providers, and policymakers.Journal of translational medicine · 2024Review
- Application of an ARFIMA Model to Estimate Hepatitis C Epidemics in Henan, China.The American journal of tropical medicine and hygiene · 2024Article
- Study on Univariate Modeling and Prediction Methods Using Monthly HIV Incidence and Mortality Cases in China.HIV/AIDS (Auckland, N.Z.) · 2024Article
- Comparison of ARIMA and Bayesian Structural Time Series Models for Predicting the Trend of Syphilis Epidemic in Jiangsu Province.Infection and drug resistance · 2024Article
- Time series analysis-based seasonal autoregressive fractionally integrated moving average to estimate hepatitis B and C epidemics in China.World journal of gastroenterology · 2023Article
- Trends in sexually transmitted and blood-borne infections in China from 2005 to 2021: a joinpoint regression model.BMC infectious diseases · 2023Article
- Research of Combined ES-BP Model in Predicting Syphilis Incidence 1982-2020 in Mainland China.Iranian journal of public health · 2023Article
- Analysis and prediction of the incidence and prevalence trends of gonorrhea in China.Human vaccines & immunotherapeutics · 2023Article
- Research on hand, foot and mouth disease incidence forecasting using hybrid model in mainland China.BMC public health · 2023Article
- Comparison of Three Prediction Models for Predicting Chronic Obstructive Pulmonary Disease in China.International journal of chronic obstructive pulmonary disease · 2023Article
- Availability of Laboratory Diagnosis of Gonorrhoea and Its Meaning in Case Reporting in Shandong Province, China.Clinical, cosmetic and investigational dermatology · 2023Article
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6 authors.
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Abstract
Background: Accurate incidence prediction of sexually transmitted diseases (STDs) is critical for early prevention and better government strategic planning. In this paper, four different forecasting models were presented to predict the incidence of AIDS, gonorrhea, and syphilis. Methods: The annual percentage changes in the incidence of AIDS, gonorrhea, and syphilis were estimated by using joinpoint regression. The performance of four methods, namely, the autoregressive integrated moving average (ARIMA) model, Elman neural network (ERNN) model, ARIMA-ERNN hybrid model and long short-term memory (LSTM) model, were assessed and compared. For 1-year prediction, the collected data from 2011 to 2020 were used for modeling to predict the incidence in 2021. For 5-year prediction, the collected data from 2011 to 2016 were used for modeling to predict the incidence from 2017 to 2021. The performance was evaluated based on four indices: mean square error (MSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). Results: The morbidities of AIDS and syphilis are on the rise, and the morbidity of gonorrhea has declined in recent years. The optimal ARIMA models were determined: ARIMA(2,1,2)(0,1,1) Conclusion: The time series predictive models show their powerful performance in forecasting STDs incidence and can be applied by relevant authorities in the prevention and control of STDs.
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