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The ongoing transmission of mpox in specific countries and regions necessitates urgent action. It is essential to implement targeted containment strategies that concentrate on high-risk populations and critical locations, such as college campuses, to effectively curb the spread of mpox. This study is dedicated to evaluating the performance of various vaccination and quarantine strategies in curbing the spread of mpox and estimating the outbreak risk. To accomplish this, we constructed a stochastic, agent-based, discrete-time susceptible-latent-infectious-recovered (SLIR) model, to examine mpox transmission on a simulated college campus. Our findings reveal that relying solely on PEP is insufficient in containing mpox effectively. To bolster the population immunity and protect the vulnerable, pre-exposure vaccination among high-risk populations prior to an outbreak is imperative. Our study demonstrates that a pre-exposure vaccination rate of 50% in high-risk populations can led to a remarkable 74.2% reduction of infections. This translated to a mere 1.0% cumulative infection incidence in the overall population. In cases where the desired vaccination coverage is not attainable, enhancing case detection and isolation measures can serve as an effective emergency response to contain mpox outbreaks. For pre-exposure vaccination coverage of 20% or lower, a 40% isolation ratio is necessary to keep the cumulative number of infections in check. However, when the coverage exceeds 30%, a reduced isolation ratio of 20% becomes sufficient to manage the outbreak effectively. These insights underscore the importance of strategic pre-exposure vaccination in conjunction with robust surveillance and isolation protocols to safeguard public health and prevent the escalation of mpox outbreaks.

Background: Influenza is an acute respiratory infectious disease with a significant global disease burden. Additionally, the coronavirus disease 2019 pandemic and its related non-pharmaceutical interventions (NPIs) have introduced uncertainty to the spread of influenza. However, comparative studies on the performance of innovative models and approaches used for influenza prediction are limited. Therefore, this study aimed to predict the trend of influenza-like illness (ILI) in settings with diverse climate characteristics in China based on sentinel surveillance data using three approaches and evaluate and compare their predictive performance. Methods: The generalized additive model (GAM), deep learning hybrid model based on Gate Recurrent Unit (GRU), and autoregressive moving average-generalized autoregressive conditional heteroscedasticity (ARMA—GARCH) model were established to predict the trends of ILI 1-, 2-, 3-, and 4-week-ahead in Beijing, Tianjin, Shanxi, Hubei, Chongqing, Guangdong, Hainan, and the Hong Kong Special Administrative Region in China, based on sentinel surveillance data from 2011 to 2019. Three relevant metrics, namely, Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE), and R squared, were calculated to evaluate and compare the goodness of fit and robustness of the three models. Results: Considering the MAPE, RMSE, and R squared values, the ARMA—GARCH model performed best, while the GRU-based deep learning hybrid model exhibited moderate performance and GAM made predictions with the least accuracy in the eight settings in China. Additionally, the models’ predictive performance declined as the weeks ahead increased. Furthermore, blocked cross-validation indicated that all models were robust to changes in data and had low risks of overfitting. Conclusions: Our study suggested that the ARMA—GARCH model exhibited the best accuracy in predicting ILI trends in China compared to the GAM and GRU-based deep learning hybrid model. Therefore, in the future, the ARMA—GARCH model may be used to predict ILI trends in public health practice across diverse climatic zones, thereby contributing to influenza control and prevention efforts.

It was common to see that older adults were reluctant to be vaccinated for coronavirus disease 2019 (COVID-19) in China. There is a lack of practical prediction models to guide COVID-19 vaccination program. A nationwide, self-reported, cross-sectional survey was conducted from September 2022 to November 2022, including people aged 60 years or older. Stratified random sampling was used to divide the dataset into derivation, validation, and test datasets at a ratio of 6:2:2. Least absolute shrinkage and selection operator and multivariable logistic regression were used for variable screening and model construction. Discrimination and calibration were assessed primarily by area under the receiver operating characteristic curve (AUC) and calibration curve. A total of 35057 samples (53.65% males and mean age of 69.64 ± 7.24 years) were finally selected, which constitutes 93.73% of the valid samples. From 33 potential predictors, 19 variables were screened and included in the multivariable logistic regression model. The mean AUC in the validation dataset was 0.802, with sensitivity, specificity, and accuracy of 0.732, 0.718 and 0.729 respectively, which were similar to the parameters in the test dataset of 0.755, 0.715 and 0.720, respectively, and the mean AUC in the test dataset was 0.815. There were no significant differences between the model predicted values and the actual observed values for calibration in these groups. The prediction model based on self-reported characteristics of older adults was developed that could be useful for predicting the willingness for COVID-19 vaccines, as well as providing recommendations in improving vaccine acceptance.

Influenza vaccination is the most cost-effective strategy for influenza prevention. Influenza vaccines have been found to be effective against symptomatic and medically attended outpatient influenza illnesses. However, there is currently a lack of data regarding the effectiveness of inactivated influenza vaccines in Chongqing, China. We conducted a prospective observational test-negative design study. Outpatient and emergency cases presenting with influenza-like illnesses (ILI) and available influenza reverse transcription polymerase chain reaction (RT-PCR) were selected and classified as cases (positive influenza RT-PCR) or controls (negative influenza RT-PCR). A total of 7,307 cases of influenza and 7,905 control subjects were included in this study. The overall adjusted influenza vaccine effectiveness (IVE) was 44.4% (95% confidence interval (CI): 32.5–54.2%). In the age groups of less than 6 years old, 6–18 years old, and 19–59 years old, the adjusted IVE were 32.2% (95% CI: 10.0–48.9%), 48.2% (95% CI: 30.6–61.4%), and 72.0% (95% CI: 43.6–86.1%). The adjusted IVE for H1N1, H3N2 and B (Victoria) were 71.1% (95% CI: 55.4–81.3%), 36.1% (95% CI: 14.6–52.2%) and 33.7% (95% CI: 14.6–48.5%). Influenza vaccination was effective in Chongqing from 2018 to 2022. Evaluating IVE in this area is feasible and should be conducted annually in the future.

To clarify the preferences of employees seeking influenza vaccination, a discrete choice experiment aims to understand the essential factors that close the gap between intention and behavior. A total of 866 employees with vaccination willingness willing to participated in a discrete choice experiment (DCE) between October 31st and December 6th, 2022 in China including the following attributes: price, vaccination setting, appointment mode, and service time. The data was analyzed using mixed logit models. Employees from smaller enterprises were more likely to get vaccinated collectively. For employees willing to get the influenza vaccine, 95.08 % of their choice was dominated by price. Employees’ behavior varied according to their socioeconomic characteristics. Only female employees strongly favored work-site-based vaccination. Price was the primary factor considered by employees for getting the influenza vaccine. DCE would help to develop influenza vaccination intervention targeted at different groups in future studies.

Abstract The World Health Organization (WHO) prioritizes pneumococcal disease as a vaccine-preventable disease and recommends the inclusion of pneumococcal conjugate vaccines (PCV) in national immunization programs worldwide. However, PCV is not included in the National Immunization Program in China and has low vaccination coverage due to its high cost. To address this, Weifang City implemented an innovative strategy for a 13-valent PCV (PCV13) on June 1, 2021. This strategy aimed to provide one dose of PCV13 free of charge for children aged 6 months to 2 years in registered households and to adopt a commercial insurance model with one dose of PCV13 free of charge in 2023 for children over 2 years old. The Health Commission of Weifang and other departments conducted a comprehensive investigation and considered various factors, such as vaccine effectiveness, safety, accessibility, vaccine price, and immunization schedules, for eligible children (under 5 years old). Stakeholder opinions were also solicited before implementing the policy. The Commission negotiated with various vaccine manufacturers to maximize its negotiating power and reduce vaccine prices. The implementation plan was introduced under the Healthy Weifang Strategy. Following the implementation of this strategy, the full course of vaccination coverage increased significantly from 0.67 to 6.59%. However, vaccination coverage is still lower than that in developed countries. Weifang's PCV13 vaccination innovative strategy is the first of its kind in Chinese mainland and is an active pilot of non-immunization program vaccination strategies. To further promote PCV13 vaccination, Weifang City should continue to implement this strategy and explore appropriate financing channels. Regions with higher levels of economic development can innovate the implementation of vaccine programs, broaden financing channels, improve accessibility to vaccination services, and advocate for more localities to incorporate PCV13 into locally expanded immunization programs or people-benefiting projects. A monitoring and evaluation system should also be established to evaluate implementation effects. Graphical Abstract

Surveillance is an essential work on infectious diseases prevention and control. When the pandemic occurred, the inadequacy of traditional surveillance was exposed, but it also provided a valuable opportunity to explore new surveillance methods. This study aimed to estimate the transmission dynamics and epidemic curve of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BF.7 in Beijing under the emergent situation using Baidu index and influenza-like illness (ILI) surveillance. A novel hybrid model (multiattention bidirectional gated recurrent unit (MABG)–susceptible–exposed–infected–removed (SEIR)) was developed, which leveraged a deep learning algorithm (MABG) to scrutinize the past records of ILI occurrences and the Baidu index of diverse symptoms such as fever, pyrexia, cough, sore throat, anti-fever medicine, and runny nose. By considering the current Baidu index and the correlation between ILI cases and coronavirus disease 2019 (COVID-19) cases, a transmission dynamics model (SEIR) was formulated to estimate the transmission dynamics and epidemic curve of SARS-CoV-2. During the COVID-19 pandemic, when conventional surveillance measures have been suspended temporarily, cases of ILI can serve as a useful indicator for estimating the epidemiological trends of COVID-19. In the specific case of Beijing, it has been ascertained that cumulative infection attack rate surpass 80.25% (95% confidence interval (95% CI): 77.51%–82.99%) since December 17, 2022, with the apex of the outbreak projected to transpire on December 12. The culmination of existing patients is expected to occur three days subsequent to this peak. Effective reproduction number (Rt) represents the average number of secondary infections generated from a single infected individual at a specific point in time during an epidemic, remained below 1 since December 17, 2022. The traditional disease surveillance systems should be complemented with information from modern surveillance data such as online data sources with advanced technical support. Modern surveillance channels should be used primarily in emerging infectious and disease outbreaks. Syndrome surveillance on COVID-19 should be established to following on the epidemic, clinical severity, and medical resource demand.

Abstract Background Common air pollutants such as ozone (O3), sulfur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter play significant roles as influential factors in influenza-like illness (ILI). However, evidence regarding the impact of O3 on influenza transmissibility in multi-subtropical regions is limited, and our understanding of the effects of O3 on influenza transmissibility in temperate regions remain unknown. Methods We studied the transmissibility of influenza in eight provinces across both temperate and subtropical regions in China based on 2013 to 2018 provincial-level surveillance data on influenza-like illness (ILI) incidence and viral activity. We estimated influenza transmissibility by using the instantaneous reproduction number ( $${R}_{t}$$ R t ) and examined the relationships between transmissibility and daily O3 concentrations, air temperature, humidity, and school holidays. We developed a multivariable regression model for $${R}_{t}$$ R t to quantify the contribution of O3 to variations in transmissibility. Results Our findings revealed a significant association between O3 and influenza transmissibility. In Beijing, Tianjin, Shanghai and Jiangsu, the association exhibited a U-shaped trend. In Liaoning, Gansu, Hunan, and Guangdong, the association was L-shaped. When aggregating data across all eight provinces, a U-shaped association was emerged. O3 was able to accounted for up to 13% of the variance in $${R}_{t}$$ R t . O3 plus other environmental drivers including mean daily temperature, relative humidity, absolute humidity, and school holidays explained up to 20% of the variance in $${R}_{t}$$ R t . Conclusions O3 was a significant driver of influenza transmissibility, and the association between O3 and influenza transmissibility tended to display a U-shaped pattern.

Background: Influenza vaccination is essential for type 2 diabetes mellitus (T2DM) patients due to their higher risks of severe complications and mortality from influenza. This study investigated the willingness of T2DM patients in Chongqing, China, to receive the influenza vaccination during the 2023/2024 season, using behavioral and social drivers (BeSD) tools to improve vaccination uptake in this high-risk group. Methods: A multi-stage sampling method was used to select participants, and face-to-face surveys were conducted in community health centers between March 1 and May 1, 2023. Binary logistic regression was used to analyze the factors influencing vaccination willingness, and standardized scores identified barriers and drivers. Results: Among 1672 T2DM patients, 11.7% had been vaccinated during the 2022/2023 season, and 59.6% were willing to receive the vaccination in the 2023/2024 season. Higher willingness was associated with ethnic minorities (odds ratio [OR], 3.18, 95% confidence interval [CI]: 1.58–6.39), being unemployed individuals (OR 2.69, 95% CI: 1.60–4.52), higher monthly household income per capita (OR 2.72, 95% CI: 1.65–4.50), having diabetes complications (OR 1.76, 95% CI: 1.23–2.51), sufficient vaccine knowledge (OR 1.87, 95% CI: 1.48–2.37), and previous vaccination (OR 7.75, 95% CI: 4.83–12.44). Concerning BeSDs, fear of infecting friends or family members and trust in vaccine efficacy were the predominant drivers, while high vaccine costs were the greatest barrier. Conclusions: Future strategies should focus on improving vaccine knowledge, supporting healthcare workers and peer recommendations, and enhancing vaccination policies. Key interventions such as health education among high-risk groups, such as unemployed individuals, advocacy campaigns, pay-it-forward strategies, and policies for free vaccination could improve coverage in Chongqing.

Objectives This study aimed to assess the healthcare-seeking behaviour and related factors of people with acute respiratory symptoms in the rural areas of central and western China to estimate the disease burden of influenza more accurately.Design Cross-sectional survey.Settings Fifty-two communities/villages in the Wanzhou District, Chongqing, China, a rural area in southwest China, from May 2022 to July 2022.Participants The participants were those who had been living in Wanzhou District continuously for more than 6 months and consented to participate.Outcome measures A semistructured questionnaire was used to determine the healthcare-seeking behaviour of participants, and the dichotomous response of ‘yes’ or ‘no’ was used to assess whether participants had acute respiratory symptoms and their healthcare-seeking behaviour.Results Only 50.92% (360 of 707) of the patients with acute respiratory infection visited medical and health institutions for treatment, whereas 49.08% (347 of 707) avoided treatment or opted for self-medication. The primary reason for not seeing a doctor was that patients felt their condition was not serious and visiting a medical facility for treatment was unnecessary. Short distance (87.54%) and reasonable charges (49.48%) were ranked as the most important reasons for choosing treatment at primary medical and health facilities (80.27%). The primary reasons for which patients visited secondary and tertiary hospitals (7.78% and 8.61%, respectively) were that doctors in such facilities were better at diagnosis (57.14%) and at treatment (87.10%).Conclusion The findings provided in this study indicated that regular healthcare-seeking behaviour investigations should be conducted. The disease burden of influenza can be calculated more accurately when healthcare-seeking behaviour investigations are combined with surveillance in the hospitals.

The number of coronavirus disease 2019 (COVID-19) cases continues to surge, overwhelming healthcare systems and causing excess mortality in many countries. Testing of infectious populations remains a key strategy to contain the COVID-19 outbreak, delay the exponential spread of the disease, and flatten the epidemic curve. Using the Omicron variant outbreak as a background, this study aimed to evaluate the effectiveness of testing strategies with different test combinations and frequencies, analyze the factors associated with testing effectiveness, and optimize testing strategies based on these influencing factors. We developed a stochastic, agent-based, discrete-time susceptible–latent–infectious–recovered model simulating a community to estimate the association between three levels of testing strategies and COVID-19 transmission. Antigen testing and its combination strategies were more efficient than polymerase chain reaction (PCR)-related strategies. Antigen testing also showed better performance in reducing the demand for hospital beds and intensive care unit beds. The delay in the turnaround time of test results had a more significant impact on the efficiency of the testing strategy compared to the detection limit of viral load and detection-related contacts. The main advantage of antigen testing strategies is the short turnaround time, which is also a critical factor to be optimized to improve PCR strategies. After modifying the turnaround time, the strategies with less frequent testing were comparable to daily testing. The choice of testing strategy requires consideration of containment goals, test efficacy, community prevalence, and economic factors. This study provides evidence for the selection and optimization of testing strategies in the post-pandemic era and provides guidance for optimizing healthcare resources.

Objectives: Global trade and travel have facilitated infectious disease transmission. In 2022, over a short time, cross-border Mpox (monkeypox) outbreaks were reported. Since, most countries are at risk of cross-border Mpox transmissions, in this study, we developed a real-time risk assessment model for the cross-border transmission of Mpox. Methods: This model includes priori indicators related to the source area before the Mpox outbreak and posterior indicators derived from the quantitative data evaluation afterward. Based on transportation, this model can also be used to assess the global import risk of Mpox for specific countries and cities. Results: European risk values displayed high levels between May and July 2022 and gradually decreased after July. After September 2022, risk values elevated in most countries and regions in the Americas. As for China, high importation risk cities were highly exposed to the United States and moderately exposed to Australia and Germany. Some cities were exposed to the potential risks from only one source country. Conclusions: Dynamic surveillance of the cross-border spread of infectious diseases is essential. Importation risks vary widely across cities and regions, and developing risk prevention and control strategies specific to the traffic flow, medical care capabilities, and risk levels in the main source countries are essential.

ABSTRACTThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination service system lacks standardized indicators to assess resource allocation. Moreover, data on specific vaccination-promoting measures is limited. This study aimed to evaluate vaccination accessibility and capacity and investigate convenience-related factors in China during the Omicron variant epidemic. We collected information on SARS-CoV-2 vaccination services among vaccination sites in Beijing. Analysis was performed using nearest neighbor, Ripley’s K, hot spot analysis, and generalized estimating equations. Overall, 299 vaccination sites were included. The demand for the SARS-CoV-2 vaccine increased with the increase in daily new cases, and the number of staff administering vaccines should be increased in urban areas at the beginning of the epidemic. Providing vaccination for both children and adults, extending vaccination service hours, and offering a wider range of vaccine categories significantly increased the doses of vaccines administered (all P

ABSTRACTGovernments must decide which vaccine priority to include in their public health programs. Using the modified Delphi and entropy method, we developed an indicator framework for vaccine inclusion at the national, provincial, municipal, and district/county levels, each containing three dimensions. In total, 4 primary indicators, 17 secondary indicators, and 45 tertiary indicators were selected, covering vaccine-preventable diseases, candidate vaccines, and social drivers of the supply and demand sides. From a subjective perspective, there was no significant weighting difference in the primary and secondary indicators at all administrative levels. “Vaccine-preventable diseases” as a primary indicator had the greatest weight in the peer group, of which “Health burden” had the highest weight among the secondary indicators. From the objective perspective, the social drivers on the supply and demand sides of the primary indicators accounted for 65% and higher. Among the secondary indicators, “the characteristics of the candidate vaccine” and “vaccine-related policies on the supply side” held 8% of weights or more at both national and provincial levels. “Demographic characteristics” held the highest weight at the municipal (13.50) and district/county (15.45) level. This study indicates that China needs different considerations when using WHO-recommended vaccines at the national, provincial, municipal, and district/county levels. In addition, this study highlights that behavioral and social drivers are important indicators that need to be considered for decision-making. This framework provides a tool for policymakers to determine the inclusion priority of candidate vaccines.

BackgroundInfluenza outbreaks pose a significant threat to global public health. Traditional surveillance systems and simple algorithms often struggle to predict influenza outbreaks in an accurate and timely manner. Big data and modern technology have offered new modalities for disease surveillance and prediction. Influenza-like illness can serve as a valuable surveillance tool for emerging respiratory infectious diseases like influenza and COVID-19, especially when reported case data may not fully reflect the actual epidemic curve. ObjectiveThis study aimed to develop a predictive model for influenza outbreaks by combining Baidu search query data with traditional virological surveillance data. The goal was to improve early detection and preparedness for influenza outbreaks in both northern and southern China, providing evidence for supplementing modern intelligence epidemic surveillance methods. MethodsWe collected virological data from the National Influenza Surveillance Network and Baidu search query data from January 2011 to July 2018, totaling 3,691,865 and 1,563,361 respective samples. Relevant search terms related to influenza were identified and analyzed for their correlation with influenza-positive rates using Pearson correlation analysis. A distributed lag nonlinear model was used to assess the lag correlation of the search terms with influenza activity. Subsequently, a predictive model based on the gated recurrent unit and multiple attention mechanisms was developed to forecast the influenza-positive trend. ResultsThis study revealed a high correlation between specific Baidu search terms and influenza-positive rates in both northern and southern China, except for 1 term. The search terms were categorized into 4 groups: essential facts on influenza, influenza symptoms, influenza treatment and medicine, and influenza prevention, all of which showed correlation with the influenza-positive rate. The influenza prevention and influenza symptom groups had a lag correlation of 1.4-3.2 and 5.0-8.0 days, respectively. The Baidu search terms could help predict the influenza-positive rate 14-22 days in advance in southern China but interfered with influenza surveillance in northern China. ConclusionsComplementing traditional disease surveillance systems with information from web-based data sources can aid in detecting warning signs of influenza outbreaks earlier. However, supplementation of modern surveillance with search engine information should be approached cautiously. This approach provides valuable insights for digital epidemiology and has the potential for broader application in respiratory infectious disease surveillance. Further research should explore the optimization and customization of search terms for different regions and languages to improve the accuracy of influenza prediction models.

Seasonal influenza activity typically peaks in the winter months but plummeted globally during the current coronavirus disease 2019 (COVID-19) pandemic. Unraveling lessons from influenza’s unprecedented low profile is critical in informing preparedness for incoming influenza seasons. Here, we explored a country-specific inference model to estimate the effects of mask-wearing, mobility changes (international and domestic), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) interference in China, England, and the United States. We found that a one-week increase in mask-wearing intervention had a percent reduction of 11.3%–35.2% in influenza activity in these areas. The one-week mobility mitigation had smaller effects for the international (1.7%–6.5%) and the domestic community (1.6%–2.8%). In 2020–2021, the mask-wearing intervention alone could decline percent positivity by 13.3–19.8. The mobility change alone could reduce percent positivity by 5.2–14.0, of which 79.8%–98.2% were attributed to the deflected international travel. Only in 2019–2020, SARS-CoV-2 interference had statistically significant effects. There was a reduction in percent positivity of 7.6 (2.4–14.4) and 10.2 (7.2–13.6) in northern China and England, respectively. Our results have implications for understanding how influenza evolves under non-pharmaceutical interventions and other respiratory diseases and will inform health policy and the design of tailored public health measures.

Abstract Background The impact of coronavirus diseases 2019 (COVID-19) related non-pharmaceutical interventions (NPIs) on influenza activity in the presence of other known seasonal driving factors is unclear, especially at the municipal scale. This study aimed to assess the impact of NPIs on outpatient influenza-like illness (ILI) consultations in Beijing and the Hong Kong Special Administrative Region (SAR) of China. Methods We descriptively analyzed the temporal characteristics of the weekly ILI counts, nine NPI indicators, mean temperature, relative humidity, and absolute humidity from 2011 to 2021. Generalized additive models (GAM) using data in 2011–2019 were established to predict the weekly ILI counts under a counterfactual scenario of no COVID-19 interventions in Beijing and the Hong Kong SAR in 2020–2021, respectively. GAM models were further built to evaluate the potential impact of each individual or combined NPIs on weekly ILI counts in the presence of other seasonal driving factors in the above settings in 2020–2021. Results The weekly ILI counts in Beijing and the Hong Kong SAR fluctuated across years and months in 2011–2019, with an obvious winter-spring seasonality in Beijing. During the 2020–2021 season, the observed weekly ILI counts in both Beijing and the Hong Kong SAR were much lower than those of the past 9 flu seasons, with a 47.5% [95% confidence interval (CI): 42.3%, 52.2%) and 60.0% (95% CI: 58.6%, 61.1%) reduction, respectively. The observed numbers for these two cities also accounted for only 40.2% (95% CI: 35.4%, 45.3%) and 58.0% (95% CI: 54.1%, 61.5%) of the GAM model estimates in the absence of COVID-19 NPIs, respectively. Our study revealed that, “Cancelling public events” and “Restrictions on internal travel” measures played an important role in the reduction of ILI in Beijing, while the “restrictions on international travel” was statistically most associated with ILI reductions in the Hong Kong SAR. Conclusions Our study suggests that COVID-19 NPIs had been reducing outpatient ILI consultations in the presence of other seasonal driving factors in Beijing and the Hong Kong SAR from 2020 to 2021. In cities with varying local circumstances, some NPIs with appropriate stringency may be tailored to reduce the burden of ILI caused by severe influenza strains or other respiratory infections in future. Graphical Abstract

The intranasal spray COVID-19 vaccine was made available for the first time in China, it is necessary to understand receivers’ satisfaction and experience toward the vaccine to help optimize vaccination service. A self-administered multicenter cross-sectional questionnaire survey was conducted in Beijing, China, in December 2022. The vaccination experience was evaluated through three dimensions: immediate tolerance, smooth progress, and time-saving. Vaccine acceptability was measured by receivers’ preference for the intranasal spray over intramuscular injection after vaccination and their recommendation willingness. Stepwise multinomial and binary logistic regression models were applied to investigate factors associated with vaccine acceptability. Among 10,452 participants included in the analysis, 92.6% felt no discomfort during the inoculation, 99.8% thought the vaccination process went well, and 89.4% deemed it a time-saving option. For vaccine acceptability, 5566 (53.3%) participants were willing to recommend the vaccine to others, 534 (5.1%) refused, and 4352 (41.6%) had not decided yet; 6142 (58.8%) participants preferred the intranasal spray, 873 (8.4%) preferred the intramuscular injection, and 3437 (32.9%) had no preferences. The most concerned aspects of the intranasal spray vaccine were vaccine effectiveness and safety. Receivers who perceived higher vaccine effectiveness or safety were more likely to recommend it to others (OR, 95%CI: 4.41, 3.24–6.00; 6.11, 4.52–8.27) or prefer it over intramuscular injection after vaccination (OR, 95%CI: 5.94, 4.62–7.65; 8.50, 6.70–10.78). Receivers showed good acceptability and experience toward the intranasal spray COVID-19 vaccine. Vaccine effectiveness and safety were the most concerned aspects, and corresponding publicity and education efforts may help improve vaccine acceptability.

Abstract Background Herpes zoster increases the burden on the elderly in an aging society. Although an effective vaccine licensed by China Food and Drug Administration in 2019 was introduced into the market in June 2020, the willingness and influencing factors of herpes zoster vaccines in Chinese adults ≥ 50-years-old during coronavirus disease-2019 pandemic are yet to be elucidated. Methods An online questionnaire survey was conducted using a simple random sampling method in October 2021 for viewers of the broadcast program. A binary logistic regression and multiple response analysis were conducted for herpes zoster vaccine and vaccination willingness. Pareto’s graphs were plotted to present the multiple-choice questions of influencing factors. Results A total of 3838 eligible participants were included in this study. Among them, 43.02% intended to be vaccinated, including 10.34% self-reported about receiving at least one shot of shingles vaccine, 30.22% declined, and 26.76% were hesitant. This population comprised a large proportion of middle-aged and older people (≥ 50-years-old) who have not experienced an episode of herpes zoster (54.98%) or are unaware of the virus (33.22%). The strongest determinants of vaccine hesitancy among older people were education background of Master’s degree or above compared to senior high or equivalent and below, personal monthly income

Abstract. Background:. World Health Organization recommends that influenza vaccines should benefit as much of the population as possible, especially where resources are limited. Corona virus disease 2019 (COVID-19) has become one of the greatest threats to health systems worldwide. The present study aimed to extend the evidence of the association between influenza vaccination and COVID-19 to promote the former. Methods:. In this systematic review, four electronic databases, including the Cochrane Library, PubMed, Embase, and Web of Science, were searched for related studies published up to May 2022. All odds ratios (ORs) with 95% confidence intervals (CIs) were pooled by meta-analysis. Results:. A total of 36 studies, encompassing 55,996,841 subjects, were included in this study. The meta-analysis for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection provided an OR of 0.80 (95% CI: 0.73–0.87). The statistically significant estimates for clinical outcomes were 0.83 (95% CI: 0.72–0.96) for intensive care unit admission, 0.69 (95% CI: 0.57–0.84) for ventilator support, and 0.69 (95% CI: 0.52–0.93) for fatal infection, while no effect seen in hospitalization with an OR of 0.87 (95% CI: 0.68–1.10). Conclusion:. Influenza vaccination helps limit SARS-CoV-2 infection and severe outcomes, but further studies are needed. Registration:. PROSPERO, CRD42022333747.

Abstract Background Healthcare workers (HCWs) were the priority group for influenza vaccination, in China during the 2020/2021 and 2021/2022 influenza seasons. However, vaccination rates in HCWs have always been low. This study investigated influenza vaccination status among Chinese HCWs and analyzed the factors driving vaccination. Methods We provided electronic questionnaires to HCWs from January 27, 2022 to February 21, 2022, using the WeChat platform "Breath Circles". HCWs who received the link could also forward it to their colleagues. Binary logistic regression models were used to analyze vaccination-associated factors among HCWs. Results Among the 1697 HCWs surveyed, vaccination coverage was 43.7% (741/1697) during the 2020/2021 influenza season, and 35.4% (600/1697) during the 2021/2022 influenza season, as of February 21, 2022. Additionally, 22.7% (385/1697) and 22.1% (358/1697) of HCWs reported that their workplaces implemented a free vaccination policy for all employees during the 2020/2021 and 2021/2022 influenza seasons. HCWs who were required to be vaccinated according to hospital regulations, and whose hospitals implemented the free influenza vaccine policy were more likely to be vaccinated (2020/2021 and 2021/2022; P

Abstract Background Assessing the humoral immunity of patients with underlying diseases after being infected with SARS-CoV-2 is essential for adopting effective prevention and control strategies. The purpose of this study is to analyze the seroprevalence of people with underlying diseases and the dynamic change features of anti-SARS-CoV-2 antibodies. Methods We selected 100 communities in Wuhan using the probability-proportional-to-size sampling method. From these 100 communities, we randomly selected households according to a list provided by the local government. Individuals who have lived in Wuhan for at least 14 days since December 2019 and were ≥ 40 years old were included. From April 9–13, 2020, community staff invited all selected individuals to the community healthcare center in batches by going door-to-door or telephone. All participants completed a standardized electronic questionnaire simultaneously. Finally, 5 ml of venous blood was collected from all participants. Blood samples were tested for the presence of pan-immunoglobulins, IgM, IgA, and IgG antibodies against SARS-CoV-2 nucleocapsid protein and neutralising antibodies were assessed. During the period June 11–13, 2020 and October 9–December 5, 2020, all family members of a positive family and matched negative families were followed up twice. Results The seroprevalence of anti-SARS-CoV-2 antibodies in people with underlying diseases was 6.30% (95% CI [5.09–7.52]), and that of people without underlying diseases was 6.12% (95% CI [5.33–6.91]). A total of 313 people were positive for total antibodies at baseline, of which 97 had underlying disease. At the first follow-up, a total of 212 people were positive for total antibodies, of which 66 had underlying disease. At the second follow-up, a total of 238 people were positive for total antibodies, of which 68 had underlying disease. A total of 219 participants had three consecutive serum samples with positive total antibodies at baseline. The IgG titers decreased significantly with or without underlying diseases (P

BackgroundSeasonal influenza activity showed a sharp decline in activity at the beginning of the emergence of COVID-19. Whether there is an epidemiological correlation between the dynamic of these 2 respiratory infectious diseases and their future trends needs to be explored. ObjectiveWe aimed to assess the correlation between COVID-19 and influenza activity and estimate later epidemiological trends. MethodsWe retrospectively described the dynamics of COVID-19 and influenza in 6 World Health Organization (WHO) regions from January 2020 to March 2023 and used the long short-term memory machine learning model to learn potential patterns in previously observed activity and predict trends for the following 16 weeks. Finally, we used Spearman correlation coefficients to assess the past and future epidemiological correlation between these 2 respiratory infectious diseases. ResultsWith the emergence of the original strain of SARS-CoV-2 and other variants, influenza activity stayed below 10% for more than 1 year in the 6 WHO regions. Subsequently, it gradually rose as Delta activity dropped, but still peaked below Delta. During the Omicron pandemic and the following period, the activity of each disease increased as the other decreased, alternating in dominance more than once, with each alternation lasting for 3 to 4 months. Correlation analysis showed that COVID-19 and influenza activity presented a predominantly negative correlation, with coefficients above –0.3 in WHO regions, especially during the Omicron pandemic and the following estimated period. The diseases had a transient positive correlation in the European region of the WHO and the Western Pacific region of the WHO when multiple dominant strains created a mixed pandemic. ConclusionsInfluenza activity and past seasonal epidemiological patterns were shaken by the COVID-19 pandemic. The activity of these diseases was moderately or greater than moderately inversely correlated, and they suppressed and competed with each other, showing a seesaw effect. In the postpandemic era, this seesaw trend may be more prominent, suggesting the possibility of using one disease as an early warning signal for the other when making future estimates and conducting optimized annual vaccine campaigns.

Due to growing activities of avian influenza, more attention should be paid to avian influenza virus infections. Global summaries or national reports lack data on epidemiological patterns of avian influenza. A descriptive epidemiological analysis of avian influenza outbreaks from 2018 to 2022 was conducted, particularly fowl infections, human infections, and sequence alterations. The number of fowl infection outbreaks in the first half of 2022 was the highest level in the five-year period. Countries or regions could reliably be classified into three clusters according to fowl infection activity scores, with 60.0% of countries or regions in C1 in Europe. Additionally, two host infection patterns of countries were noted, led by the Taiwan (China) region and Germany. Human infections also increased, with 88.1% of cases being in China with an increasing risk of cases in northern China. Sequences that were furin cleavage motif present spread from Asia to Europe and North America over the five-year period. Continuous changes in the global activities of avian influenza highlight the need for sustained global surveillance, including strengthening monitoring capacity for vulnerable population and dynamically detecting new cases or genetic variations of the avian influenza virus under the One Health framework.

BackgroundIn megacities, there is an urgent need to establish more sensitive forecasting and early warning methods for acute respiratory infectious diseases. Existing prediction and early warning models for influenza and other acute respiratory infectious diseases have limitations and therefore there is room for improvement. ObjectiveThe aim of this study was to explore a new and better-performing deep-learning model to predict influenza trends from multisource heterogeneous data in a megacity. MethodsWe collected multisource heterogeneous data from the 26th week of 2012 to the 25th week of 2019, including influenza-like illness (ILI) cases and virological surveillance, data of climate and demography, and search engines data. To avoid collinearity, we selected the best predictor according to the weight and correlation of each factor. We established a new multiattention-long short-term memory (LSTM) deep-learning model (MAL model), which was used to predict the percentage of ILI (ILI%) cases and the product of ILI% and the influenza-positive rate (ILI%×positive%), respectively. We also combined the data in different forms and added several machine-learning and deep-learning models commonly used in the past to predict influenza trends for comparison. The R2 value, explained variance scores, mean absolute error, and mean square error were used to evaluate the quality of the models. ResultsThe highest correlation coefficients were found for the Baidu search data for ILI% and for air quality for ILI%×positive%. We first used the MAL model to calculate the ILI%, and then combined ILI% with climate, demographic, and Baidu data in different forms. The ILI%+climate+demography+Baidu model had the best prediction effect, with the explained variance score reaching 0.78, R2 reaching 0.76, mean absolute error of 0.08, and mean squared error of 0.01. Similarly, we used the MAL model to calculate the ILI%×positive% and combined this prediction with different data forms. The ILI%×positive%+climate+demography+Baidu model had the best prediction effect, with an explained variance score reaching 0.74, R2 reaching 0.70, mean absolute error of 0.02, and mean squared error of 0.02. Comparisons with random forest, extreme gradient boosting, LSTM, and gated current unit models showed that the MAL model had the best prediction effect. ConclusionsThe newly established MAL model outperformed existing models. Natural factors and search engine query data were more helpful in forecasting ILI patterns in megacities. With more timely and effective prediction of influenza and other respiratory infectious diseases and the epidemic intensity, early and better preparedness can be achieved to reduce the health damage to the population.

WHO-recommended vaccines substantially prevent and control vaccine-preventable diseases (VPDs), but their inclusion differs among countries and regions. We reviewed the application for WHO-recommended vaccines in China and described the concerns and obstacles in driving the inclusion of more vaccines into China’s NIP, including immunization strategies, financial barriers, vaccination services, and behavioral and social supply-side and demand-side factors. China has made significant efforts, however, they may not be sufficient until the inclusion of more WHO-recommended vaccines in the National Immunization Program (NIP), ensuring that the vaccination encompasses the whole life course of individuals, establishment of more trustworthy vaccination finance and procurement, increasing vaccine development, optimizing vaccine demand forecasts, improving the accessibility and equity of vaccination services, capturing the key points of behavioral and social drivers of vaccination on the demand side, and establishing holistic prevention and control from a public health perspective.

Summary: Background: Evidence concerning effects of air pollution on influenza-like illness (ILI) from multi-center is limited and little is known about how regional factors might modify this relationship. Methods: In this ecological study, ILI cases defined as outpatients with temperature ≥38 °C, accompanied by cough or sore throat, were collected from National Influenza Surveillance Network in China. We adopted generalized additive model with quasi-Poisson to estimate province-specific association between air pollution and ILI in 30 Chinese provinces during 2015–2019, after adjusting for time trend and meteorological factors. We then pooled province-specific association by using random-effect meta-analysis. Potential effect modifications of season and regional characteristics were explored. Findings: A total of 26, 004, 853 ILI cases and 777, 223, 877 hospital outpatients were collected. In general, effects of air pollutants were acute. An inter-quartile range increase of PM2.5, SO2, PM10, NO2 and CO at lag0, and O3 at lag0-2 was associated with 3.08% (95% CI: 1.91%, 4.27%), 3.00% (1.86%, 4.16%), 6.46% (4.71%, 8.25%), 7.21% (5.73%, 8.71%), 4.37% (3.05%, 5.70%), and −9.26% (−11.32%, −7.14%) change of ILI at national level, respectively. Associations between air pollutants and ILI varied by season and regions, with higher effect estimates in cold season, eastern and central regions and provinces with more humid condition and larger population. Interpretation: This study indicated that most air pollutants increased the risk of ILI in China. Our findings might provide implications for the development of policies to protect public health from air pollution and influenza. Funding: National Natural Science Foundation of China and Chongqing Health Commission Program.

It is important to understand the cognition, willingness, and psychological anxiety state of Chinese guardians toward COVID-19 vaccination for their children to predict the future vaccination rate and to help the design of policies that aim to expand the population with immunity against COVID-19. This study collected data with a professional vaccination registration platform for children named “Xiao Dou Miao” in February 2021. The psychological anxiety state of the guardians was self-evaluated using the psychological anxiety scale. Factors that might influence the willingness of guardians to vaccinate their children were identified using logistic regression analysis. This study included 12,872 questionnaires with 70.9% of guardians showing willingness to vaccinate their children. Guardians who were male, aged 40–49 and from rural area were more willing to vaccinate their children. Fathers, guardians with higher education and income, whose children have a history of adverse vaccine reactions and allergies were less willing to vaccinate their children (p

This study aimed to investigate the changes in the willingness of guardians to administer the COVID-19 vaccine to their children, allow the coadministration of other vaccines, and administer the COVID-19 vaccine booster dose. This was a follow-up study conducted 6 months after a similar previous study. The self-administered questionnaire was distributed through the “Xiao Dou Miao” app and 9424 guardians with access to this app participated in the survey that was conducted from September 15 to October 8, 2021. Of all the participating guardians, 86.68% were willing to vaccinate their children with the COVID-19 vaccine, which was approximately 16% more than those in our previous study. Guardians aged ≥40 years, healthcare workers, and those with children aged ≥3 years were more willing to vaccinate their children. Approximately 77% of the guardians were willing toward the coadministration of COVID-19 and influenza vaccines. Approximately 64% of the guardians were willing toward the coadministration of other nonimmunization program vaccines with the COVID-19 vaccine for their children. The primary reasons for reluctance toward the coadministration of vaccines were concerns about vaccine safety and effectiveness. If necessary, 92% of the guardians were willing to receive a COVID-19 vaccine booster and 82% were willing to vaccinate their children with a COVID-19 vaccine booster. We hope that this research will facilitate the formulation of successful strategies for the implementation of COVID-19 vaccinations, covaccinations, and COVID-19 booster doses, particularly for children aged

BackgroundHealthcare workers play an essential role in improving the public's vaccination uptake, but the full picture of such workers' engagement in vaccination-related behaviors has not been appropriately identified. According to the Integrated Theory of Health Behavior Change, self-directed learning may be a promising intervention for fostering engagement in vaccination-related behaviors, but the association between self-directed learning and such behaviors remains unclear. This study aimed to determine Chinese healthcare workers' level of engagement in behaviors for combatting vaccine-preventable diseases and assess the association between frequency of performing vaccine-focused SDL and engagement in vaccination-related behaviors.Materials and methodsAn online cross-sectional survey was conducted from January 27 to February 21, 2022, using the survey platform “wjx.” Respondents were restricted to healthcare workers aged 18–65 years. A Sankey diagram and bar plots were constructed to determine patterns of engagement in a vaccination-related-behavior chain. Unconditional binary logistic regression models were fitted to determine the association between frequency of performing vaccine-focused self-directed learning and engagement in vaccination-related behaviors.ResultsOf the 2,248 survey respondents, data for 2,065 were analyzed. Participants who had received influenza or pneumococcal vaccination, routinely recommended vaccination to patients, tracked patients' vaccination status, and recommended efficiently accounted for 43.2%, 50.8%, 40.3%, and 36.4% of the total participants, respectively. When only considering those who routinely made such recommendations, the proportion of those who performed tracking and efficient recommendation was 28.8% and 26.2%, respectively. When compared to performing self-directed learning “never to less than once/six months,” performing self-directed learning “more than once/week” was positively associated with being vaccinated (OR, 95% CI: 2.30, 1.74–3.03), routinely recommending vaccination (OR, 95% CI: 4.46, 3.30–6.04), and tracking the status of patients so recommended (OR, 95% CI: 6.18, 4.35–8.76).ConclusionsChinese healthcare workers' pattern of engagement in vaccination-related behaviors must be improved. Higher frequencies of engagement in self-directed learning are associated with more active engagement in vaccination-related behaviors, meaning raising such frequencies could be a promising intervention for fostering behavior changes in this regard and ultimately increasing vaccination coverage.

BackgroundWe aimed to comprehensively analyze awareness, knowledge and attitude toward influenza vaccine and the factors associated to vaccine acceptance among the young and middle-aged general population, healthcare workers, and health-related administrators in China. The factors influencing the promotion of influenza vaccination were also evaluated among healthcare workers and administrators.MethodsThis is a multicenter, cross-sectional study. General population adults, healthcare workers (HCWs), and health administrators were enrolled in seven regions across China during the 2020–2021 flu season. Data were collected via an online questionnaire, which included information request as to awareness, knowledge, and attitude toward influenza vaccination. Statistical significance set at p-values < 0.05.ResultsA total of 3,239 individuals were included in our analyses. There were gaps in consciousness to action, especially between awareness (87.1%) and knowledge (57.7%), and between willingness (57.3%) and vaccination (22.3%). The downward trends were similar in all three groups. HCW group and the health administrator group showed more positive propensity to accept influenza vaccines than the general population group. For the general population group, those with a lower educational level (lower than a bachelor's degree) were less likely to be vaccinated (aOR = 0.66, 95% CI: 0.45–0.96). For the HCW group, practitioners older than 45 years were more reluctant to be vaccinated than those under 25 years (aOR = 0.41, 95% CI: 0.19–0.86). For the health administrator group, personnel aged 26 years and above were less inclined to be vaccinated (aORs = 0.17–0.20). In all groups, people who had received influenza vaccines in the past 5 years (aOR = 1.72, 95% CI: 1.31–2.26 in general population group, 13.05, 95% CI: 7.71–22.10 in HCW group, and 19.30, 95% CI: 9.66–42.63 in health administrator group) were more likely to be vaccinated in future seasons. People who were not covered by the free program or those without awareness of the related programs were less likely to be vaccinated (aORs < 0.63). Most (70.8%) of HCWs showed intention to recommend the influenza vaccine. Clinical doctors, those who had flu shots themselves, and those who had more knowledge, were more like to make recommendations. Health administrators stated that insufficient budget resources and workforce, and low public awareness are main difficulties in the promotion of influenza vaccine.ConclusionThe influencing factors of the attitude toward influenza vaccination vary across populations. Governments need to carry out focused vaccination promotion programs, especially for healthcare workers, to improve the coverage of influenza vaccination.

We estimated the symptomatic, PCR-confirmed secondary attack rate (SAR) for 2,382 close contacts of 476 symptomatic persons with coronavirus disease in Yichang, Hubei Province, China, identified during January 23–February 25, 2020. The SAR among all close contacts was 6.5%; among close contacts who lived with an index case-patient, the SAR was 10.8%; among close-contact spouses of index case-patients, the SAR was 15.9%. The SAR varied by close contact age, from 3.0% for those 60 years of age. Multilevel logistic regression showed that factors significantly associated with increased SAR were living together, being a spouse, and being >60 years of age. Multilevel regression did not support SAR differing significantly by whether the most recent contact occurred before or after the index case-patient’s onset of illness (p = 0.66). The relatively high SAR for coronavirus disease suggests relatively high virus transmissibility.

To understand influenza vaccination and its correlates among health-careworkers (HCWs) during the 2019/2020 season in China, we used a self-administeredelectronic questionnaire to collect information on demographics, occupational characteristics, influenza vaccination status and access to free vaccination on the “Breath Circles”, a Chinese media platform for respiratory medical professionals. The reported influenza vaccine coverage among HCWs during this season was 67%, with more HCWs in a workplace with free vaccination than those with no free vaccination (79% vs.34%,p < .001). The influenza vaccine coverage among HCWs who were required or encouraged to get vaccinated by the workplace was significantly higher than that without any intervention measures (80% & 70 vs.39%,p < .001). The vaccine coverage in the workplaces with free and required vaccination simultaneously was highest compared to that with neither free vaccination nor any intervention measures (OR = 14.86, 95% CI: 10.93–20.20). The influenza vaccination coverage of HCWs in high-riskdepartments was significantly higher than that of other departments (70% vs.58%,p =.023). HCWs’ vaccine coverage was related to personal opinions and attitudes toward influenza or influenza vaccines, as well as other constraints such as availability of influenza vaccines, workplace regulations, and access to free vaccines.

The coronavirus disease 2019 (COVID-19) pandemic is a global crisis, and medical systems in many countries are overwhelmed with supply shortages and increasing demands to treat patients due to the surge in cases and severe illnesses. This study aimed to assess COVID-19-related essential clinical resource demands in China, based on different scenarios involving COVID-19 spreads and interventions. We used a susceptible–exposed–infectious–hospitalized/isolated–removed (SEIHR) transmission dynamics model to estimate the number of COVID-19 infections and hospitalizations with corresponding essential healthcare resources needed. We found that, under strict non-pharmaceutical interventions (NPIs) or mass vaccination of the population, China would be able to contain community transmission and local outbreaks rapidly. However, under scenarios involving a low intensity of implemented NPIs and a small proportion of the population vaccinated, the use of a peacetime–wartime transition model would be needed for medical source stockpiles and preparations to ensure a normal functioning healthcare system. The implementation of COVID-19 vaccines and NPIs in different periods can influence the transmission of COVID-19 and subsequently affect the demand for clinical diagnosis and treatment. An increased proportion of asymptomatic infections in simulations will not reduce the demand for medical resources; however, attention must be paid to the increasing difficulty in containing COVID-19 transmission due to asymptomatic cases. This study provides evidence for emergency preparations and the adjustment of prevention and control strategies during the COVID-19 pandemic. It also provides guidance for essential healthcare investment and resource allocation.

Non-pharmaceutical interventions (NPIs) implemented to interrupt COVID-19 transmission may also impact the spread of other infectious diseases. Here, the authors estimate that influenza activity in China and the United States reduced by up to 80% when NPIs were in place in the 2019–2020 season.

This study aimed to understand the intention and correlation of receiving and recommending influenza vaccine (IV) among healthcare workers (HCWs) in China during the 2022/2023 season using the behavior and social drivers (BeSD) tools. A self-administered electronic survey collected 17,832 participants on a media platform. We investigated the willingness of IV and used multivariate logistic regression analysis to explore its associated factors. The average scores of the 3Cs’ model were compared by multiple comparisons. We also explored the factors that potentially correlated with recommendation willingness by partial regression. The willingness of IV was 74.89% among HCWs, and 82.58% of the participants were likely to recommend it to others during this season. Thinking and feeling was the strongest domain independently associated with willingness. All domains in BeSD were significantly different between the hesitancy and acceptance groups. Central factors in the 3Cs model were significantly different among groups (p < 0.01). HCWs’ willingness to IV recommendation was influenced by their ability to answer related questions (r = 0.187, p < 0.001) after controlling for their IV willingness and perceived risk. HCWs’ attitudes towards IV affect their vaccination and recommendation. The BeSD framework revealed the drivers during the decision-making process. Further study should classify the causes in detail to refine HCWs’ education.

Abstract Background Since 2011, the Global Influenza Hospital Surveillance Network (GIHSN) has used active surveillance to prospectively collect epidemiological and virological data on patients hospitalized with influenza virus infection. Here, we describe influenza virus strain circulation in the GIHSN participant countries during 2017–2018 season and examine factors associated with complicated hospitalization among patients admitted with laboratory-confirmed influenza illness. Methods The study enrolled patients who were hospitalized in a GIHSN hospital in the previous 48 h with acute respiratory symptoms and who had symptoms consistent with influenza within the 7 days before admission. Enrolled patients were tested by reverse transcription-polymerase chain reaction to confirm influenza virus infection. “Complicated hospitalization” was defined as a need for mechanical ventilation, admission to an intensive care unit, or in-hospital death. In each of four age strata (

Abstract Background China has an aging population with an increasing number of adults aged ≥ 60 years. Influenza causes a heavy disease burden in older adults, but can be alleviated by vaccination. We assessed the cost-effectiveness of a potential government-funded seasonal influenza vaccination program in older adults in China. Methods We characterized the health and economic impact of a fully funded influenza vaccination program for older adults using China-specific influenza disease burden, and related cost data, etc. Using a decision tree model, we calculated the incremental costs per quality-adjusted life year (QALY) gained of vaccination from the societal perspective, at a willingness-to-pay threshold equivalent to GDP per capita (US$8840). Moreover, we estimated the threshold vaccination costs, under which the fully funded vaccination program is cost-effective using GDP per capita as the willingness-to-pay threshold. Results Compared to current self-paid vaccination, a fully funded vaccination program is expected to prevent 19,812 (95% uncertainty interval, 7150–35,783) influenza-like-illness outpatient consultations per year, 9418 (3386–17,068) severe acute respiratory infection hospitalizations per year, and 8800 (5300–11,667) respiratory excess deaths due to influenza per year, and gain 70,212 (42,106–93,635) QALYs per year. Nationally, the incremental costs per QALY gained of the vaccination program is US$4832 (3460–8307), with a 98% probability of being cost-effective. The threshold vaccination cost is US$10.19 (6.08–13.65). However, variations exist between geographical regions, with Northeast and Central China having lower probabilities of cost-effectiveness. Conclusions Our results support the implementation of a government fully funded older adult vaccination program in China. The regional analysis provides results across settings that may be relevant to other countries with similar disease burden and economic status, especially for low- and middle-income countries where such analysis is limited.

Influenza vaccination coverage in pregnant women in China remains low. In this review, we first provide an overview of the evidence for the use of influenza vaccination during pregnancy. Second, we discuss influenza vaccination policy and barriers to increased seasonal influenza vaccination coverage in pregnant women in China. Third, we provide case studies of successes and challenges of programs for increasing seasonal influenza vaccination in pregnant women from other parts of Asia with lessons learned for China. Finally, we assess opportunities and challenges for increasing influenza vaccination coverage among pregnant women in China.

To determine the seroprevalence and seroconversion of avian influenza virus (AIV) antibodies in poultry workers, we conducted a seroepidemiologic study in 7 areas of China during December 2014–April 2016. We used viral isolation and reverse transcription PCR to detect AIVs in specimens from live poultry markets. We analyzed 2,124 serum samples obtained from 1,407 poultry workers by using hemagglutination inhibition and microneutralization assays. We noted seroprevalence of AIV antibodies for subtypes H9N2, H7N9, H6N1, H5N1-SC29, H5N6, H5N1-SH199, and H6N6. In serum from participants with longitudinal samples, we noted seroconversion, with >4-fold rise in titers, for H9N2, H7N9, H6N1, H5N1-SC29, H6N6, H5N6, and H5N1-SH199 subtypes. We found no evidence of H10N8 subtype. The distribution of AIV antibodies provided evidence of asymptomatic infection. We found that AIV antibody prevalence in live poultry markets correlated with increased risk for H7N9 and H9N2 infection among poultry workers.

Abstract Background In 2017, an outbreak of onychomadesis occurred in kindergarten H, Hubei province, China. We investigated the field to learn about the magnitude and reason of the outbreak. Methods The case definition was that a child with onychomadesis or transverse ridging (Beau’s line) in fingernails and toenails without previous traumatic or systemic disease in kindergarten H from Sep. 1st to Nov. 30th, 2017. A retrospective cohort study was carried out to analyze the epidemiological relationship between onychomadesis and the hand-foot-mouth disease (HFMD) in Primary Class #2, kindergarten H. We also performed a serological survey for neutralizing antibodies against coxsackie virus A6 (CVA6), coxsackie virus A10 (CVA10) among 15 cases and six healthy children in the kindergarten. Meanwhile, some children were carried out with routine blood, fungal microscopic and microelement tests. Indoor environment examinations had been done for all classes. Results A total of 20 cases were identified in Kindergarten H. Seventy-five percent (15/20) cases occurred in Primary Class #2. Fifty-five percent of the cases (11/20) had suffered from HFMD within two months. The median time between onychomadesis and HFMD was 45 days (ranging from 31 to 58 days). A retrospective cohort study in Primary Class #2 showed the attack rate was 90.0% among 10 children who suffered from HFMD in the past two months compared to 30.0% among 20 children who didn’t (Rate Ratio [RR] =3.0, 95% Confidence Interval [CI] =1.5–6.0). The positive rates of neutralizing antibodies were 66.7% for CVA6 and 26.7% for CVA10 in tested cases. The result of routine blood, fungal microscopic, microelements tests were normal in cases. The indicators of environment were within the normal range. Conclusion The results of this study suggested that the outbreak of onychomadesis in Hubei province was probably associated with HFMD epidemic within two months.

The intensity of influenza epidemics varies significantly from year to year among regions with similar climatic conditions and populations. However, the underlying mechanisms of the temporal and spatial variations remain unclear. We investigated the impact of urbanization and public transportation size on influenza activity. We used 6-year weekly provincial-level surveillance data of influenza-like disease incidence (ILI) and viral activity in northern China. We derived the transmission potential of influenza for each epidemic season using the susceptible–exposed–infectious–removed–susceptible (SEIRS) model and estimated the transmissibility in the peak period via the instantaneous reproduction number (Rt). Public transport was found to explain approximately 28% of the variance in the seasonal transmission potential. Urbanization and public transportation size explained approximately 10% and 21% of the variance in maximum Rt in the peak period, respectively. For the mean Rt during the peak period, urbanization and public transportation accounted for 9% and 16% of the variance in Rt, respectively. Our results indicated that the differences in the intensity of influenza epidemics among the northern provinces of China were partially driven by urbanization and public transport size. These findings are beneficial for predicting influenza intensity and developing preparedness strategies for the early stages of epidemics.

To determine the vaccine hesitancy of pneumococcal conjugate vaccines (PCVs) in a low-resource setting in China and to identify associated factors, a face-to-face questionnaire survey was conducted in the city of Guilin, China, from December 2021 to March 2022, which comprised sociodemographic information, attitudes toward vaccines and pneumonia, and PCV13 vaccination willingness and willingness to pay (WTP). Stepwise logistic regression and Tobit regression models were fitted to identify factors associated with PCV13 vaccination willingness and WTP, respectively. In total, 1254 questionnaires were included, of which 899, 254, and 101 participants showed acceptance, hesitancy, and refusal to vaccinate their children with PCV13, respectively. Only 39.07% of participants knew about PCV13 before this survey. A total of 558 (48.40%) participants accepted the full payment of vaccination, and 477 (41.37%) other participants accepted the partial payment, with a median cost of CNY 920.00. Demographics, social and psychological context, and attitudes toward vaccines were all associated with PCV13 vaccination but varied for hesitators and refusers. There is a substantial local demand for vaccinating children with PCV13 and partial payment is widely accepted. More publicity and educational efforts and a socially supportive environment are required to alleviate vaccine hesitancy.

Abstract Background Vaccine regulation in China meets World Health Organization standards, but China’s vaccine industry and immunization program have some characteristics that differ from other countries. We described the history, classification, supply and prices of vaccines available and used in China, compared with high-and middle-incomes countries to illustrate the development of Chinese vaccine industry and immunization program. Methods Immunization policy documents were obtained from the State Council and the National Health and Family Planning Commission (NHFPC). Numbers of doses of vaccines released in China were obtained from the Biologicals Lot Release Program of the National Institutes for Food and Drug Control (NIFDC). Vaccine prices were obtained from Chinese Central Government Procurement (CCGP). International data were collected from US CDC, Public Health England, European CDC, WHO, and UNICEF. Results Between 2007 and 2015, the annual supply of vaccines in China ranged between 666 million and 1,190 million doses, with most doses produced domestically. The government’s Expanded Program on Immunization (EPI) prevents 12 vaccine preventable diseases (VPD) through routine immunization. China produces vaccines that are in common use globally; however, the number of routinely-prevented diseases is fewer than in high- and middle-income countries. Contract prices for program (EPI) vaccines ranged from 0.1 to 5.7 US dollars per dose - similar to UNICEF prices. Contract prices for private-market vaccines ranged from 2.4 to 102.9 US dollars per dose - often higher than prices for comparable US, European, and UNICEF vaccines. Conclusion China is a well-regulated producer of vaccines, but some vaccines that are important globally are not included in China’s EPI system in China. Sustained and coordinated effort will be required to bring Chinese vaccine industry and EPI into an era of global leadership.

BackgroundInfluenza illness burden is substantial, particularly among young children, older adults, and those with underlying conditions. Initiatives are underway to develop better global estimates for influenza-associated hospitalizations and deaths. Knowledge gaps remain regarding the role of influenza viruses in severe respiratory disease and hospitalizations among adults, particularly in lower-income settings.Methods and findingsWe aggregated published data from a systematic review and unpublished data from surveillance platforms to generate global meta-analytic estimates for the proportion of acute respiratory hospitalizations associated with influenza viruses among adults. We searched 9 online databases (Medline, Embase, CINAHL, Cochrane Library, Scopus, Global Health, LILACS, WHOLIS, and CNKI; 1 January 1996-31 December 2016) to identify observational studies of influenza-associated hospitalizations in adults, and assessed eligible papers for bias using a simplified Newcastle-Ottawa scale for observational data. We applied meta-analytic proportions to global estimates of lower respiratory infections (LRIs) and hospitalizations from the Global Burden of Disease study in adults ≥20 years and by age groups (20-64 years and ≥65 years) to obtain the number of influenza-associated LRI episodes and hospitalizations for 2016. Data from 63 sources showed that influenza was associated with 14.1% (95% CI 12.1%-16.5%) of acute respiratory hospitalizations among all adults, with no significant differences by age group. The 63 data sources represent published observational studies (n = 28) and unpublished surveillance data (n = 35), from all World Health Organization regions (Africa, n = 8; Americas, n = 11; Eastern Mediterranean, n = 7; Europe, n = 8; Southeast Asia, n = 11; Western Pacific, n = 18). Data quality for published data sources was predominantly moderate or high (75%, n = 56/75). We estimate 32,126,000 (95% CI 20,484,000-46,129,000) influenza-associated LRI episodes and 5,678,000 (95% CI 3,205,000-9,432,000) LRI hospitalizations occur each year among adults. While adults ConclusionsIn this meta-analysis, we estimated that influenza viruses are associated with over 5 million hospitalizations worldwide per year. Inclusion of both published and unpublished findings allowed for increased power to generate stratified estimates, and improved representation from lower-income countries. Together, the available data demonstrate the importance of influenza viruses as a cause of severe disease and hospitalizations in younger and older adults worldwide.

BackgroundThe effects of multiple meteorological factors on influenza activity remain unclear in Chongqing, the largest municipality in China. We aimed to fix this gap in this study.MethodsWeekly meteorological data and influenza surveillance data in Chongqing were collected from 2012 to 2019. Distributed lag nonlinear models (DLNMs) were conducted to estimate the effects of multiple meteorological factors on influenza activity.ResultsInverted J-shaped nonlinear associations between mean temperature, absolute humidity, wind speed, sunshine and influenza activity were found. The relative risks (RRs) of influenza activity increased as weekly average mean temperature fell below 18.18°C, average absolute humidity fell below 12.66 g/m3, average wind speed fell below 1.55 m/s and average sunshine fell below 2.36 hours. Taking the median values as the references, lower temperature, lower absolute humidity and windless could significantly increase the risks of influenza activity and last for 4 weeks. A J-shaped nonlinear association was observed between relative humidity and influenza activity; the risk of influenza activity increased with rising relative humidity with 78.26% as the break point. Taking the median value as the reference, high relative humidity could increase the risk of influenza activity and last for 3 weeks. In addition, we found the relationship between aggregate rainfall and influenza activity could be described with a U-shaped curve. Rainfall effect has significantly higher RR than rainless effect.ConclusionsOur study shows that multiple meteorological factors have strong associations with influenza activity in Chongqing, providing evidence for developing a meteorology-based early warning system for influenza to facilitate timely response to upsurge of influenza activity.

We used national sentinel surveillance data in China for 2005–2016 to examine the lineage-specific epidemiology of influenza B. Influenza B viruses circulated every year with relatively lower activity than influenza A. B/Yamagata was more frequently detected in adults than in children.