Zijian Feng’s research while affiliated with The Chinese Medical Association and other places

Background: Several COVID-19 vaccines were developed and approved in China. Of these, the BIBB-CorV and CoronaVac inactivated whole-virion vaccines were widely distributed in China and developing countries. However, the performance of the two vaccines in the real world has not been summarized. Methods: A living systematic review based on findings from ongoing post-licensure studies was conducted, applying standardized algorithms. Articles published between 1 May 2020 and 31 May 2022 in English and Chinese were searched for in Medline, Embase, WanFang Data, medRxiv, bioRxiv, arXiv, SSRN, and Research Square, using SARS-CoV-2, COVID-19, and vaccine as the MeSH terms. Studies with estimates of safety, immunogenicity, and effectiveness from receiving the BIBB-CorV or CoronaVac vaccine that met the predefined screening criteria underwent a full-text review. The Joanna Briggs Institute’s Critical Appraisal Checklist and the Cochrane risk of bias were used for assessment of the quality. A random-effects meta-regression model was applied to identify the potential impact factors on the vaccines’ effectiveness. Results: In total, 32578 articles were identified, of these, 770 studies underwent a full-text review. Eventually, 213 studies were included. The pooled occurrence of solicited and unsolicited adverse events after any dose of either vaccine varied between 10% and 40%. The top five commonly reported rare adverse events were immunization stress-related responses (211 cases, 50.0%), cutaneous responses (43 cases, 10.2%), acute neurological syndrome (39 cases, 9.2%), anaphylaxis (17 cases, 4.0%), and acute stroke (16 cases, 3.8%). The majority (83.3%) recovered or were relieved within several days. The peak neutralization titers against the ancestral strain was found within 1 month after the completion of the primary series of either vaccine, with a GMT (geometric mean titer) of 43.7 (95% CI: 23.2–82.4), followed by a dramatic decrease within 3 months. At Month 12, the GMT was 4.1 (95% CI: 3.8–4.4). Homologous boosting could restore humoral immunity, while heterologous boosting elicited around sixfold higher neutralization titers in comparison with homologous boosting. The effectiveness of receiving either vaccine against death and severe disease was around 85% for both shortly after the primary series. At Month 12, the protection against death did not decline, while the protection against severe disease decreased to ~75%. Conclusions: Both the BIBP-CorV and CoronaVac inactivated vaccines are safe. Sustained vaccine effectiveness against death was determined 12 months after the primary series, although protection against severe disease decreased slightly over time. A booster dose could strengthen the waning effectiveness; however, the duration of the incremental effectiveness and the additional benefit provided by a heterologous booster need to be studied.

What is already known about this topic? Both the decline in immunity over time and the evolution of the virus play a role in the level of protection offered by a prior infection. What is added by this report? Point estimates indicated variations in protection levels based on the initial infecting variant and the reinfecting variant. There was a consistent correlation between real-world protection, antigenic distance, and humoral immunity levels. Specifically, shorter antigenic distances and higher humoral immunity levels corresponded to enhanced real-world protection. What are the implications for public health practice? Our findings suggest that virological and immunological studies could help identify and assess the epidemic risk posed by new variants before they become dominant. Prompt incorporation of the latest variants into the antigen components of the coronavirus disease 2019 (COVID-19) vaccines can significantly contribute to effective epidemic prevention and control measures.

In 2021, China’s domestically produced coronavirus disease 2019 (COVID-19) vaccines received approval from regulatory bodies and were administered worldwide. Due to a low number of infections within China during that period, it became imperative to evaluate the vaccines’ real-world effectiveness through international studies. To facilitate this, China CDC launched the COVID-19 Vaccines Evaluation Program (COVEP). This program formed research collaboration agreements with health institutes across five World Health Organization regions, addressing key questions about vaccine performance through ten cooperative agreements. The findings from COVEP projects reinforced confidence, both domestically and globally, in the effectiveness of the vaccines produced in China. Moreover, the outcomes observed internationally were frequently mirrored by later studies conducted within China. COVEP thus pioneered a novel approach for fostering cross-national research collaborations, addressing significant public health issues and exemplifying a framework for international cooperation. This approach is in line with the strategic objectives and other development efforts of China CDC’s national disease control and prevention initiatives.

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 352.69%, 4.98%, and 3.73%, respectively. The mean absolute percentage error (MAPE) value decreases by 73.7%, 23.46%, and 13.06%, respectively. The root mean square error (RMSE) value decreases by 68.02%, 26.68%, and 23.78%, respectively. The mean absolute error (MAE) value decreases by 70.90%, 23.00%, and 21.80%, respectively. The hybrid SARIMA-NARX and SARIMA-LSTM methods predict syphilis cases more accurately than the basic SARIMA and LSTM methods, so that can be used for governments to develop long-term syphilis prevention and control programs. In addition, the predicted cases still maintain a fairly high level of incidence, so there is an urgent need to develop more comprehensive prevention strategies.

Background Hemorrhagic fever with renal syndrome (HFRS) is a zoonotic infectious disease commonly found in Asia and Europe, characterized by fever, hemorrhage, shock, and renal failure. China is the most severely affected region, necessitating an analysis of the temporal incidence patterns in the country. Methods We employed Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), Nonlinear AutoRegressive with eXogenous inputs (NARX), and a hybrid CNN-LSTM model to model and forecast time series data spanning from January 2009 to November 2023 in the mainland China. By comparing the simulated performance of these models on training and testing sets, we determined the most suitable model. Results Overall, the CNN-LSTM model demonstrated optimal fitting performance (with Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Mean Absolute Error (MAE) of 93.77/270.66, 7.59%/38.96%, and 64.37/189.73 for the training and testing sets, respectively, lower than those of individual CNN or LSTM models). Conclusion The hybrid CNN-LSTM model seamlessly integrates CNN’s data feature extraction and LSTM’s recurrent prediction capabilities, rendering it theoretically applicable for simulating diverse distributed time series data. We recommend that the CNN-LSTM model be considered as a valuable time series analysis tool for disease prediction by policy-makers.

Background Gonorrhea has long been a serious public health problem in mainland China that requires attention, modeling to describe and predict its prevalence patterns can help the government to develop more scientific interventions. Methods Time series (TS) data of the gonorrhea incidence in China from January 2004 to August 2022 were collected, with the incidence data from September 2021 to August 2022 as the validation. The seasonal autoregressive integrated moving average (SARIMA) model, long short-term memory network (LSTM) model, and hybrid SARIMA-LSTM model were used to simulate the data respectively, the model performance were evaluated by calculating the mean absolute percentage error (MAPE), root mean square error (RMSE), and mean absolute error (MAE) of the training and validation sets of the models. Results The Seasonal components after data decomposition showed an approximate bimodal distribution with a period of 12 months. The three models identified were SARIMA(1,1,1) (2,1,2)12, LSTM with 150 hidden units, and SARIMA-LSTM with 150 hidden units, the SARIMA-LSTM model fitted best in the training and validation sets, for the smallest MAPE, RMSE, and MPE. Conclusions The overall incidence trend of gonorrhea in mainland China has been on the decline since 2004, with some periods exhibiting an upward trend. The incidence of gonorrhea displays a seasonal distribution, typically peaking in July and December each year. The SARIMA model, LSTM model, and SARIMA-LSTM model can all fit the monthly incidence time series data of gonorrhea in mainland China. However, in terms of predictive performance, the SARIMA-LSTM model outperforms the SARIMA and LSTM models, with the LSTM model surpassing the SARIMA model. This suggests that the SARIMA-LSTM model can serve as a preferred tool for time series analysis, providing evidence for the government to predict trends in gonorrhea incidence. The model's predictions indicate that the incidence of gonorrhea in mainland China will remain at a high level in 2024, necessitating that policymakers implement public health measures in advance to prevent the spread of the disease.

What is already known about this topic?: Public health workers (PHWs) were listed as a priority group recommended for influenza vaccination during the coronavirus disease 2019 (COVID-19) pandemic. Understanding the drivers of influenza vaccine hesitancy among PHWs can promote influenza vaccination in the COVID-19 pandemic. What is added by this report?: The study found that 10.7% of PHWs were hesitant to get an influenza vaccination. Drivers associated with vaccine hesitancy were assessed based on "3Cs model." The absence of a government or workplace requirement and concerns about vaccine safety were the biggest obstacles for PHWs to recommend influenza vaccination. What are the implications for public health practice?: Interventions are needed to improve PHWs' influenza vaccine coverage to prevent the co-circulation of influenza and COVID-19.

Importance: The Sabin-strain inactivated poliovirus vaccine (IPV) may be a tool for polio outbreak response in certain situations. Objective: To investigate the response to a type 2 vaccine-derived poliovirus (VDPV2) outbreak. Design, setting, and participants: This case series was conducted in China after a VDPV2 was detected in stool specimens from a child with acute flaccid paralysis (AFP) in Sichuan Province in 2019, 3 years after the global withdrawal of live, attenuated type 2 oral poliovirus vaccine (OPV). Investigation followed National Health Commission and World Health Organization guidance and included searching hospitals for unreported AFP cases; testing stool specimens from the child, his contacts, and local children; enhanced environmental surveillance for VDPV2s in wastewater; and measuring vaccination coverage. Sabin-strain IPV campaigns were conducted in a wide geographic area. Main outcomes and measures: Any VDPV2 detection after completion of the supplementary immunization activities. Results: A 28-nucleotide-change VDPV2 was isolated from a young boy. Three VDPV2s were detected in healthy children; 2 were contacts of the original child, and none had paralysis. A search of 31 million hospital records found 10 unreported AFP cases; none were polio. No type 2 polioviruses were found in wastewater. Prior to the event, polio vaccine coverage was 65% among children younger than 5 years. Sabin-strain IPV campaigns reached more than 97% of targeted children, administering 1.4 million doses. No transmission source was identified. More than 1 year of enhanced poliovirus environmental and AFP surveillance detected no additional VDPVs. Conclusions and relevance: These findings suggest that the circulating VPDV2 outbreak in 2019 was associated with low vaccine coverage. An investigation discovered 3 infected but otherwise healthy children and no evidence of the virus in wastewater. Following Sabin-strain IPV-only campaigns expanding from county to prefecture, the poliovirus was not detected, and the outbreak response was considered by an expert panel and the World Health Organization to have been successful. This success suggests that the Sabin-strain IPV may be a useful tool for responding to circulating VDPV2 outbreaks when high-quality supplementary immunization activities can be conducted and carefully monitored in settings with good sanitation.