Although the effects of seasonality on syphilis have been discussed previously, no previous study has evaluated the seasonality of syphilis incidence by sex and age group. We examined the seasonality of syphilis incidence by sex and age group in Korea from 2011 to 2019. The incidence of syphilis was calculated on the basis of Korea Diseases Control and Prevention Agency data, and an autoregressive integrated moving average (ARIMA) model and seasonal and trend decomposition using Loess were used to analyze the seasonality of the incidence in relation to epidemiological factors. The annual age-standardized incidence rates of primary, secondary, and congenital syphilis were 21.1, 8.8, and 64.0 cases/million persons, respectively, from 2011 to 2019. The highest incidence rates for primary and secondary syphilis were observed among those aged 20 to 29, 13 to 19, and 30 to 49 years, but not among the lower age groups. In analyses based on the ARIMA model, all univariate time series showed the highest goodness-of-fit results with ARIMA for primary syphilis (1,1,2), secondary syphilis (1,1,1), and congenital syphilis (0,1,2) (2,0,0) models. This study suggests that the incidence of secondary syphilis shows a summer seasonality for males and the highest incidence rate in the 20 to 29-year age group for both males and females in Korea. Public health action is needed to prevent an increase in syphilis incidence associated with sex, age group, and seasonal patterns.
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http://dx.doi.org/10.1097/MD.0000000000036723 | DOI Listing |
Infect Drug Resist
December 2024
Department of Epidemiology and Health Statistics, School of Public Health, Xinxiang Medical University, Xinxiang, Henan Province, 453003, People's Republic of China.
Purpose: This study sets out to explore the forecasting value in syphilis incidence of the Bayesian structural time series (BSTS) model in Jiangsu Province.
Methods: The seasonal autoregressive integrated moving average (ARIMA) and BSTS models were constructed using the series from January 2017 to December 2021, and the prediction accuracy of both models was tested using the series from January 2022 to November 2022.
Results: From January 2017 to November 2022, the total number of syphilis cases in Jiangsu Province was 170629, with an average monthly notification cases of 2403.
Transfusion
September 2024
Department of Transfusion Medicine, NIH Clinical Center, Bethesda, Maryland, USA.
Background: In December 2021, the U.S. Food and Drug Administration published a letter to clinical laboratory staff and healthcare providers detailing a risk of false Rapid Plasma Reagin (RPR) when using the Bio-Rad Laboratories BioPlex 2200 Syphilis Total & RPR kit in people who had received COVID-19 vaccination; Treponema pallidum particle agglutination assays did not appear to be impacted by this issue.
View Article and Find Full Text PDFEpidemiol Infect
May 2024
Chinese Preventive Medicine Association, Beijing, China.
Syphilis remains a serious public health problem in mainland China that requires attention, modelling to describe and predict its prevalence patterns can help the government to develop more scientific interventions. The seasonal autoregressive integrated moving average (SARIMA) model, long short-term memory network (LSTM) model, hybrid SARIMA-LSTM model, and hybrid SARIMA-nonlinear auto-regressive models with exogenous inputs (SARIMA-NARX) model were used to simulate the time series data of the syphilis incidence from January 2004 to November 2023 respectively. Compared to the SARIMA, LSTM, and SARIMA-LSTM models, the median absolute deviation (MAD) value of the SARIMA-NARX model decreases by 352.
View Article and Find Full Text PDFJMIR Public Health Surveill
May 2024
Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia.
Sci Total Environ
June 2024
Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China; UNESCO Chair on Global Health and Education of Peking University, Beijing 100191, China.
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