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Introduction: Chongqing is among the areas with the highest rubella incidence rates in China. This study aimed to analyze the temporal distribution characteristics of rubella and establish a forecasting model in Chongqing, which could provide a tool for decision-making in the early warning system for the health sector., Methodology: The rubella monthly incidence data from 2004 to 2019 were obtained from the Chongqing Center of Disease and Control. The incidence from 2004 to June 2019 was fitted using the seasonal autoregressive integrated moving average (SARIMA) model and the back-propagation neural network (BPNN) model, and the data from July to December 2019 was used for validation., Results: A total of 30,083 rubella cases were reported in this study, with a significantly higher average annual incidence before the nationwide introduction of rubella-containing vaccine (RCV). The peak of rubella notification was from April to June annually. Both SARIMA and BPNN models were capable of predicting the expected incidence of rubella. However, the linear SARIMA model fits and predicts better than the nonlinear BPNN model., Conclusions: Based on the results, rubella incidence in Chongqing has an obvious seasonal trend, and SARIMA (2,1,1) × (1,1,1) 12 model can predict the incidence of rubella well. The SARIMA model is a feasible tool for producing reliable rubella forecasts in Chongqing., Competing Interests: No Conflict of Interest is declared, (Copyright (c) 2022 Qi Chen, Han Zhao, Hongfang Qiu, Qiyin Wang, Dewei Zeng, Mengliang Ye.)

Background: Mumps is classified as a class C infection disease in China, and the Chongqing area has one of the highest incidence rates in the country. We aimed to establish a prediction model for mumps in Chongqing and analyze its seasonality, which is important for risk analysis and allocation of resources in the health sector., Methods: Data on incidence of mumps from January 2004 to December 2018 were obtained from Chongqing Municipal Bureau of Disease Control and Prevention. The incidence of mumps from 2004 to 2017 was fitted using a seasonal autoregressive comprehensive moving average (SARIMA) model. The root mean square error (RMSE) and mean absolute percentage error (MAPE) were used to compare the goodness of fit of the models. The 2018 incidence data were used for validation., Results: From 2004 to 2018, a total of 159,181 cases (93,655 males and 65,526 females) of mumps were reported in Chongqing, with significantly more men than women. The age group of 0-19 years old accounted for 92.41% of all reported cases, and students made up the largest proportion (62.83%), followed by scattered children and children in kindergarten. The SARIMA(2, 1, 1) × (0, 1, 1) 12 was the best fit model, RMSE and MAPE were 0.9950 and 39.8396%, respectively., Conclusion: Based on the study findings, the incidence of mumps in Chongqing has an obvious seasonal trend, and SARIMA(2, 1, 1) × (0, 1, 1) 12 model can also predict the incidence of mumps well. The SARIMA model of time series analysis is a feasible and simple method for predicting mumps in Chongqing.

Objectives: To explore the prevalence and changing trends of HIV, syphilis, hepatitis C virus (HCV) infections and risk behaviours among female sex workers (FSWs) and to provide reference and theoretical basis for formulating targeted interventions., Design: Six consecutive cross-sectional surveys., Setting: Chongqing, China., Participants: FSWs were included if they (1) were aged ≥16 years, (2) provided commercial sex for money or goods during the previous month and (3) were willing to participate in the survey and could provide verbal informed consent. This study included 16 791 of 16 810 participants recruited between 2013 and 2018., Primary and Secondary Outcome Measures: The prevalence of HIV/syphilis/HCV infection., Results: The HIV and HCV prevalence among FSWs in Chongqing was stable during the study period, but the prevalence of syphilis had an increasing trend, particularly among low-tier and middle-tier FSWs. Improvements in HIV-related knowledge, condom use, injecting drug use and participation in HIV-related services were observed. However, no change was found in the prevalence of drug use. HIV infection was correlated with no condom use in the last commercial sex (adjusted OR (aOR) 3.48, 95% CI 1.90 to 6.37) and syphilis infection (aOR 4.88, 95% CI 1.95 to 12.18). Syphilis infection was correlated with inconsistent condom use (aOR 1.30, 95% CI 1.02 to 1.65), HIV infection (aOR 5.88, 95% CI 2.40 to 14.41), HCV infection (aOR 7.68, 95% CI 4.37 to 13.49) and sexually transmitted infection (STI) diagnosis in the past year (aOR 3.81, 95% CI 2.40 to 6.03). HCV infection was associated with injecting drug use (aOR 8.91, 95% CI 4.45 to 17.86) and syphilis infection (aOR 7.88, 95% CI 4.49 to 13.83)., Conclusions: Comprehensive interventions targeting FSWs, particularly low-tier and middle-tier FSWs, should be increasingly implemented to prevent and control HIV, syphilis and other STIs., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Acute haemorrhagic conjunctivitis is a highly contagious eye disease, the prediction of acute haemorrhagic conjunctivitis is very important to prevent and grasp its development trend. We use the exponential smoothing model and the seasonal autoregressive integrated moving average (SARIMA) model to analyse and predict. The monthly incidence data from 2004 to 2017 were used to fit two models, the actual incidence of acute haemorrhagic conjunctivitis in 2018 was used to validate the model. Finally, the prediction effect of exponential smoothing is best, the mean square error and the mean absolute percentage error were 0.0152 and 0.1871, respectively. In addition, the incidence of acute haemorrhagic conjunctivitis in Chongqing had a seasonal trend characteristic, with the peak period from June to September each year.

Although immunization against varicella using vaccines has been proven to be significant and effective in the past decades, varicella remains a major public health concern for many developing countries. Varicella vaccination has not been introduced into routine immunization programs in China, and varicella outbreaks have continued to occur. Taking the city of Chongqing, which has a high prevalence of varicella, as an example, this study explored the spatiotemporal epidemiology of varicella. Based on the reported data of varicella cases from 1 January 2014 to 31 December 2018 in Chongqing, hot spots and space-time clusters of varicella were identified using spatial autocorrelation analysis and scan statistics. Within this period, a total of 112,273 varicella cases were reported in Chongqing (average annual incidence: 73.44 per 100,000), including one death. The incidence of varicella showed an increasing trend with significant seasonal peaks, which occurred during April to July and October to January of the following year. The total ratio of male to female patients affected was 1.10:1. Children under the age of 15 and students accounted for the majority of the patient population. The hotspots detected through local spatial autocorrelation analysis, and the most likely clusters identified by scan analysis, were primarily in the main urban districts of Chongqing. The secondary clusters were mostly detected in northeast and southwest Chongqing. There were obvious spatial dependence and spatiotemporal clustering characteristics of varicella in Chongqing from 2014 to 2018. High-risk districts, populations, and peak periods were found in this study, which could be helpful in implementing varicella prevention and control programs, and in adjusting vaccination strategies for the varicella vaccine based on actual conditions.