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This study aimed to explore the 1-year temporal change in prevalence, variety, and potential risk factors of long COVID symptoms, and to further predict the prognostic trends of long COVID.We searched electronic databases for related studies published from January 2020 to February 2022, and conducted one group meta-analysis and locally weighted regression explore the monthly temporal change in the prevalence of each long COVID symptom in 1-year follow-up period.A total of 137 studies were included in meta-analysis, including 134,093 participants. The temporal change of any long COVID symptom showed a steep decrease initially (from 92% at acute phase to 55% at 1-month follow-up), followed by stabilization at approximately 50% during 1-year follow-up. Six months or more after the acute phase, the odds ratio (OR) of population characteristic factors increased, such as female gender (from 1.62 to 1.82), while the OR value of acute phase-related factors (severe/critical and hospitalization) decreased. As for specific symptoms, about two-thirds of the symptoms did not significantly reduce during the 1-year follow-up, and the neuropsychiatric symptoms showed a higher long-term prevalence (approximately 25%) and longer persistence than physical-symptoms.The temporal changes in the prevalence and characteristics speculate that long COVID may persist longer than expected. In particular, we should pay more attention to neuropsychiatric symptoms and other symptoms for which there is no significant downward trend in prevalence. The influence of acute phase-related factors for long COVID gradually decreases over time, while the influence of population characteristic-related gradually increases.

More than 30 months into the novel coronavirus 2019 (COVID-19) pandemic, efforts to bring this prevalence under control have achieved tentative achievements in China. However, the continuing increase in confirmed cases worldwide and the novel variants imply a severe risk of imported viruses. High-intensity non-pharmaceutical interventions (NPIs) are the mainly used measures of China's early response to COVID-19, which enabled effective control in the first wave of the epidemic. However, their efficiency is relatively low across China at the current stage. Therefore, this study focuses on whether measurable meteorological variables be found through global data to learn more about COVID-19 and explore flexible controls. This study first examines the control measures, such as NPIs and vaccination, on COVID-19 transmission across 189 countries, especially in China. Subsequently, we estimate the association between meteorological factors and time-varying reproduction numbers based on the global data by meta-population epidemic model, eliminating the aforementioned anthropogenic factors. According to this study, we find that the basic reproduction number of COVID-19 transmission varied wildly among Köppen-Geiger climate classifications, which is of great significance for the flexible adjustment of China's control protocols. We obtain that in southeast China, Köppen-Geiger climate sub-classifications, Cwb, Cfa, and Cfb, are more likely to spread COVID-19. In August, the R

We evaluated and compared humoral immune responses after inactivated coronavirus disease 2019 (COVID-19) vaccination among naïve individuals, asymptomatically infected individuals, and recovered patients with varying severity. In this multicenter, prospective cohort study, blood samples from 666 participants were collected before and after 2 doses of inactivated COVID-19 vaccination. Among 392 severe acute respiratory syndrome coronavirus 2-naïve individuals, the seroconversion rate increased significantly from 51.8% (median antispike protein pan-immunoglobulins [S-Igs] titer: 0.8 U/ml) after the first dose to 96% (median S-Igs titer: 79.5 U/ml) after the second dose. Thirty-two percent of naïve individuals had detectable neutralizing antibodies (NAbs) against the original strain but all of them lost neutralizing activity against the Omicron variant. In 274 individuals with natural infection, humoral immunity was significantly improved after a single vaccine dose, with median S-Igs titers of 596.7, 1176, 1086.5, and 1828 U/ml for asymptomatic infections, mild cases, moderate cases, and severe/critical cases, respectively. NAb titers also improved significantly. However, the second dose did not substantially increase antibody levels. Although a booster dose is needed for those without infection, our findings indicate that recovered patients should receive only a single dose of the vaccine, regardless of the clinical severity, until there is sufficient evidence to confirm the benefits of a second dose.

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

Objectives: Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infection in young children. We aimed to analyze the factors affecting the estimation of RSV-related disease burden, and furthermore, to provide evidence to help establish a surveillance system. Methods: We searched for literature published in English or Chinese between 1 January, 2010 and 2 June, 2022. The quality of the included articles was assessed using the Agency for Healthcare Research and Quality scale. Random-effects models were used for data synthesis and subgroup analyses. This review was registered in the Prospective Register of Systematic Reviews (PROSPERO: CRD42022372972). Results: We included 44 studies (149,321,171 participants), all of which were of medium or high quality. The pooled RSV-associated disease incidence, hospitalization rate, in-hospital mortality, and overall mortality rates in children aged 5 years and younger were 9.0% (95% confidence interval [CI]: 7.0–11.0%), 1.68% (95% CI: 1.30–2.05%), 0.45% (95% CI: 0.38–0.52%), and 0.05% (95% CI: 0.04–0.06%), respectively. Age, economics, surveillance types, case definition, and data source were all influencing factors. Conclusions: A standardized and unified RSV surveillance system is required. Case definition and surveillance types should be fully considered for surveillance of different age groups.

Until now, we have no thorough understanding the role of absolute humidity on influenza activity, especially in tropical and subtropical areas. In this study, we investigated the relationship between absolute humidity and influenza activity in seven municipalities/provinces covering different climatic zones in China. Weekly meteorological data and influenza surveillance data in seven provinces/municipalities in China were collected from January 2012 to December 2019. A distributed lag nonlinear model was adopted to investigate the association between absolute humidity (AH) and influenza activity in each study site. Then, seven study sites were grouped into three regions: northern, intermediate, and southernmost regions. A multivariate meta-analysis was applied to estimate the exposure-lag-response associations in three regions. The province-specific or municipality-specific curves appeared to be nonlinear, and the association between influenza activity and AH varied across regions. In Beijing and Tianjin, located in northern China, the cumulative relative risks (RRs) increased as weekly average AHmean fell below 3.41 g/m

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.

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.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.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).Influenza vaccination helps limit SARS-CoV-2 infection and severe outcomes, but further studies are needed.PROSPERO, CRD42022333747.

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.

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

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 outbreaks 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.

This cross-sectional study evaluated the long-term health effects of coronavirus disease 2019 (COVID-19) in Jianghan District (Wuhan, China). The results showed that 61.4% of COVID-19 patients reported at least one symptom and 8.8% had depressive symptoms at the 17-month follow-up. The proportion of patients with chest radiographic abnormalities in Fangcang shelter hospitals and designated COVID-19 hospitals was 31.6% and 41.1%, respectively, and the proportion of patients with impaired pulmonary diffusion capacity in these hospitals was 52.8% and 60.9%, respectively. Female sex (odds ratio [OR] = 1.48, 95% confidence interval [CI]: 1.16–1.88), severe disease (OR = 1.46, 95% CI: 1.01–2.10) and a higher number of initial symptoms (OR = 1.31, 95% CI: 1.23–1.40) were associated with the development of sequelae symptoms at 17 months. This study involving community-dwelling COVID-19 adults may help determine the long-term effects of COVID-19 during the first pandemic wave. Nonetheless, larger follow-up studies are needed to characterize the post-COVID-19 condition.

Background: It is very important to establish more accurate influenza prediction models in megacities. The purpose of this study was to compare the different time series prediction models for influenza from 2010 to 2019 in Beijing, China. Methods: We took the influenza-like illness rate (ILI%), the influenza positive rate and the product of ILI% and influenza positive rate as dependent variables respectively. Subsequently, and model performances of summer point, peak bottom point and peak rising point were analyzed. After selecting the best prediction point, we compared the model performances of different parameters at that point using the SARIMA model. Then, the best model selected by SARIMA was compared with the hybrid LSTM model. Results: Between the 26th week of 2010 and the 25th week of 2019, there were 6,753,116(1.24%) ILI patients, 15,883(16.75%) of which were positive for influenza.The trends and the peak times of ILI%, the influenza positive rate and the product of ILI% and influenza positive rate were roughly the same. The SARIMA model of the peak rising point was better than those of the summer point and peak bottom point. The hybrid LSTM model performed better than the selected best SARIMA model in terms of ILI%, influenza positive rate and the product of ILI% and influenza positive rate. Also, the hybrid LSTM model could maintain a good prediction effect from the 1st to the 26th week.. On the contrary, the prediction effect of the SARIMA model decreased significantly with the extension of the prediction period. Conclusions: Our results suggested that the prediction effect of the hybrid LSTM model was better than the SARIMA model, in terms of ILI%, influenza positive rate and the product of ILI% and influenza positive rate. SARIMA was more suitable for short-term prediction, while the hybrid LSTM model showed obvious advantages in long-term prediction. Our research could help to improve the prediction and early warning of influenza and other respiratory infectious diseases.

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.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.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 PMThis 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.National Natural Science Foundation of China and Chongqing Health Commission Program.

Background COVID-19 can lead to increased psychological symptoms such as post-traumatic stress disorder (PTSD), depression, and anxiety among patients with COVID-19. Based on the previous mindfulness-based interventions proved to be effective, this protocol reports a design of a randomized controlled trial aiming to explore the efficacy and possible mechanism of a mindful living with challenge (MLWC) intervention developed for COVID-19 survivors in alleviating their psychological problems caused by both the disease and the pandemic. Methods In April 2021, more than 1600 eligible participants from Hubei Province of China will be assigned 1:1 to an online MLWC intervention group or a waitlist control group. All participants will be asked to complete online questionnaires at baseline, post-program, and 3-month follow-up. The differences of mental health status (e.g. PTSD) and physical symptoms including fatigue and sleeplessness between the COVID-19 survivors who receiving the online MLWC intervention and the control group will be assessed. In addition, the possible mediators and moderators of the link between the MLWC intervention and target outcomes will be evaluated by related verified scales, such as the Five Facets Mindfulness Questionnaire. Data will be analyzed based on an intention-to-treat approach, and SPSS software will be used to perform statistical analysis. Discussion The efficacy and potential mechanism of MLWC intervention in improving the quality of life and psychological status of COVID-19 survivors in China are expected to be reported. Findings from this study will shed light on a novel and feasible model in improving the psychological well-being of people during such public health emergencies. Trial registration Chinese Clinical Trial Registry (ChiCTR), ChiCTR2000037524; Registered on August 29, 2020, http://www.chictr.org.cn/showproj.aspx?proj=60034.

Coronavirus disease 2019 (COVID-19) was detected in China during the 2019–2020 seasonal influenza epidemic. Non-pharmaceutical interventions (NPIs) and behavioral changes to mitigate COVID-19 could have affected transmission dynamics of influenza and other respiratory diseases. By comparing 2019–2020 seasonal influenza activity through March 29, 2020 with the 2011–2019 seasons, we found that COVID-19 outbreaks and related NPIs may have reduced influenza in Southern and Northern China and the United States by 79.2% (lower and upper bounds: 48.8%–87.2%), 79.4% (44.9%–87.4%) and 67.2% (11.5%–80.5%). Decreases in influenza virus infection were also associated with the timing of NPIs. Without COVID-19 NPIs, influenza activity in China and the United States would likely have remained high during the 2019–2020 season. Our findings provide evidence that NPIs can partially mitigate seasonal and, potentially, pandemic influenza., 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.

Government used mobility restrictions to help contain the first wave of coronavirus disease 2019 (COVID-19) across cities in China. The restrictions were lifted during times of non-zero incidence in response to a return to work order that went into effect on February 10, 2020.The effect of lifting mobility restrictions on COVID-19 death rate and incidence varied by city, with smaller increases or even reductions in cities with low community connectivity and small floating volume, and larger increases in cities with high community connectivity and large floating volume. Effects on recovery rates were similar across cities.City-specific mobility restriction lifting is likely to be beneficial. Two indexes, community connectivity and floating volume, can inform the design of city-specific mobility restriction lifting policies.

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 P P P Conclusions A free influenza vaccination policy and workplace required vaccination are effective in improving influenza vaccination coverage among HCWs. Influenza vaccination coverage of Chinese HCWs remained low and showed a downward trend after the COVID-19 outbreak. Further effective measures, such as advocacy campaigns, free vaccine policies, and on-site vaccination could be implemented to improve influenza vaccination coverage. Graphical abstract

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.

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 aged6 years.

Summary Background Wuhan was the epicentre of the COVID-19 outbreak in China. We aimed to determine the seroprevalence and kinetics of anti-SARS-CoV-2 antibodies at population level in Wuhan to inform the development of vaccination strategies. Methods In this longitudinal cross-sectional study, we used a multistage, population-stratified, cluster random sampling method to systematically select 100 communities from the 13 districts of Wuhan. Households were systematically selected from each community and all family members were invited to community health-care centres to participate. Eligible individuals were those who had lived in Wuhan for at least 14 days since Dec 1, 2019. All eligible participants who consented to participate completed a standardised electronic questionnaire of demographic and clinical questions and self-reported any symptoms associated with COVID-19 or previous diagnosis of COVID-19. A venous blood sample was taken for immunological testing on April 14–15, 2020. 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. We did two successive follow-ups between June 11 and June 13, and between Oct 9 and Dec 5, 2020, at which blood samples were taken. Findings Of 4600 households randomly selected, 3599 families (78·2%) with 9702 individuals attended the baseline visit. 9542 individuals from 3556 families had sufficient samples for analyses. 532 (5·6%) of 9542 participants were positive for pan-immunoglobulins against SARS-CoV-2, with a baseline adjusted seroprevalence of 6·92% (95% CI 6·41–7·43) in the population. 437 (82·1%) of 532 participants who were positive for pan-immunoglobulins were asymptomatic. 69 (13·0%) of 532 individuals were positive for IgM antibodies, 84 (15·8%) were positive for IgA antibodies, 532 (100%) were positive for IgG antibodies, and 212 (39·8%) were positive for neutralising antibodies at baseline. The proportion of individuals who were positive for pan-immunoglobulins who had neutralising antibodies in April remained stable for the two follow-up visits (162 [44·6%] of 363 in June, 2020, and 187 [41·2%] of 454 in October–December, 2020). On the basis of data from 335 individuals who attended all three follow-up visits and who were positive for pan-immunoglobulins, neutralising antibody levels did not significantly decrease over the study period (median 1/5·6 [IQR 1/2·0 to 1/14·0] at baseline vs 1/5·6 [1/4·0 to 1/11·2] at first follow-up [p=1·0] and 1/6·3 [1/2·0 to 1/12·6] at second follow-up [p=0·29]). However, neutralising antibody titres were lower in asymptomatic individuals than in confirmed cases and symptomatic individuals. Although titres of IgG decreased over time, the proportion of individuals who had IgG antibodies did not decrease substantially (from 30 [100%] of 30 at baseline to 26 [89·7%] of 29 at second follow-up among confirmed cases, 65 [100%] of 65 at baseline to 58 [92·1%] of 63 at second follow-up among symptomatic individuals, and 437 [100%] of 437 at baseline to 329 [90·9%] of 362 at second follow-up among asymptomatic individuals). Interpretation 6·92% of a cross-sectional sample of the population of Wuhan developed antibodies against SARS-CoV-2, with 39·8% of this population seroconverting to have neutralising antibodies. Our durability data on humoral responses indicate that mass vaccination is needed to effect herd protection to prevent the resurgence of the epidemic. Funding Chinese Academy of Medical Sciences & Peking Union Medical College, National Natural Science Foundation, and Chinese Ministry of Science and Technology. Translation For the Chinese translation of the abstract see Supplementary Materials section.

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.

Background In 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. Objective The 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. Methods We 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. Results The 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. Conclusions The 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.

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.

Background Between mid‐January and early February, provinces of mainland China outside the epicentre in Hubei province were on high alert for importations and transmission of COVID‐19. Many properties of COVID‐19 infection and transmission were still not yet established. Methods We collated and analysed data on 449 of the earliest COVID‐19 cases detected outside Hubei province to make inferences about transmission dynamics and severity of infection. We analysed 64 clusters to make inferences on serial interval and potential role of pre‐symptomatic transmission. Results We estimated an epidemic doubling time of 5.3 days (95% confidence interval (CI): 4.3, 6.7) and a median incubation period of 4.6 days (95% CI: 4.0, 5.2). We estimated a serial interval distribution with mean 5.7 days (95% CI: 4.7, 6.8) and standard deviation 3.5 days, and effective reproductive number was 1.98 (95% CI: 1.68, 2.35). We estimated that 32/80 (40%) of transmission events were likely to have occurred prior to symptoms onset in primary cases. Secondary cases in clusters had less severe illness on average than cluster primary cases. Conclusions The majority of transmissions are occurring around illness onset in an infected person, and pre‐symptomatic transmission does play a role. Detection of milder infections among the secondary cases may be more reflective of true disease severity.

BackgroundIn 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.MethodsThe 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.ResultsA 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.ConclusionThe results of this study suggested that the outbreak of onychomadesis in Hubei province was probably associated with HFMD epidemic within two months.

Pneumococcal diseases (PDs) pose a serious health threat to children. Vaccination is the most cost-effective intervention to prevent PDs, but pneumococcal vaccines coverage among children is low in China.This study investigated the willingness of children's caregivers to have their children vaccinated with pneumococcal vaccines under an innovative policy to offer 1-dose of the 13-valent pneumococcal conjugate vaccines at no charge to families. The research found that 70.51% of caregivers were willing to have their infants receive pneumococcal vaccines and that reducing the cost of vaccines may increase caregivers' willingness.This is the first evaluation in China of acceptance of pneumococcal vaccines among children under a 1-dose, cost-free policy. The results provide scientific evidence for updating local and national pneumococcal immunization strategies to promote the use of the pneumococcal vaccine.

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.

Untangling lessons from the influenza’s plummeting during the COVID-19 pandemic is critical for mitigating seasonal and pandemic influenza. Here we explored a country-specific inference model to estimate the effects of mask-wearing, mobility changes (international and domestic) and SARS-CoV-2 interference in China, England and the United States. We found that mask wearing had a larger reduction than mobility changes in all the regions. Only in 2019-2020, SARS-CoV-2 interference had an observable effect, with values varying at the timing of the influenza season and the speed of SARS-CoV-2 community transmission. Compared to the epidemics in 2017–2019, longer and blunter rebounds could occur in the incoming 2021–2022 season, but the rebound would be smaller if less stringent mask mandates continued or the international mobility stayed low. Our results bear implications for understanding how influenza evolves under non-pharmaceutical interventions and other respiratory diseases, and will inform designing of tailored public health measures.

Background: Assessing the humoral immunity of patients with underlying diseases after being infected with SARS-CoV-2 is essential for determining effective prevention and control strategies. The purpose of this study is to investigate whether underlying disease is a risk factor for SARS-CoV-2 infection, reveal the seroprevalence of people with underlying disease and the characteristics of dynamic changes in anti-SARS-CoV-2 antibodies, and provide evidence for the scientific formulation of COVID-19 vaccination strategies.Methods: The probability ratio sampling method was adopted to systematically select 100 communities from 13 districts in Wuhan, China, followed by a random selection of households from 100 communities 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. Individuals with other serious diseases besides COVID-19, from whom a sample could not be obtained or refused to participate, were excluded. All eligible subjects signed a written informed consent form and completed a standardized electronic questionnaire before being enrolled in the group. From April 9–13, 2020, venous blood samples were collected from all individuals; from June 11–13, 2020, and from October 9–December 5, 2020, all positive and matched negative families were followed up.Results: The seroprevalence of SARS-CoV-2 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]). Among people with underlying diseases, retirees, health workers, and people who have been exposed to fever or respiratory symptoms since December 2019 were more likely to be infected with SARS-CoV-2. The IgG titer of people with underlying disease decreased significantly over time (P Conclusion: These findings imply that vaccination strategies for people with and without underlying diseases may not require special adjustments.

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 P = 0.032, second follow-up, P = 0.018) in the underlying diseases group. Conclusion Our research focused on the serological changes of people with and without underlying diseases in a state of single natural infection. Regardless of the underlying diseases, the IgG titer decreased significantly over time, while there was no significant difference in the decline rate of IgG between with and without underlying diseases. Moreover, the neutralizing antibody titer remained relatively stable within the 9 months at least.

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.

A systematic review and meta-analysis was conducted to estimate the pooled effect of influenza vaccinations for health workers (HWs). Nine databases were screened to identify randomized clinical trials and comparative observational studies that reported the effect of influenza vaccination among HWs. The risk ratio (RR), standardized mean difference, and 95% confidence interval (CI) were employed to study the effect size using fixed/random-effect models. Subgroup analyses and sensitivity analyses were conducted accordingly. Publication bias was examined. Sixteen studies (involving 7971 HWs from nine countries) were included after a comprehensive literature search. The combined RR regarding the incidence of laboratory-confirmed influenza was 0.36 (95% CI: 0.25 to 0.54), the incidence of influenza-like illness (ILI) was 0.69 (95% CI: 0.45 to 1.06), the absenteeism rate was 0.63 (95% CI: 0.46 to 0.86), and the integrated standardized mean difference of workdays lost was −0.18 (95% CI: −0.28 to −0.07) days/person. The subgroup analysis indicated that vaccination significantly decreases the incidence of laboratory-confirmed influenza in different countries, study populations, and average-age vaccinated groups. Influenza vaccinations could effectively reduce the incidence of laboratory-confirmed influenza, absenteeism rates, and workdays lost among HWs. It is advisable, therefore, to improve the coverage and increase the influenza vaccination count among HWs, which may benefit both workers and medical institutions.

Nationwide prospective surveillance of all-age patients with acute respiratory infections was conducted in China between 2009‒2019. Here we report the etiological and epidemiological features of the 231,107 eligible patients enrolled in this analysis. Children, China operates a national surveillance program for acute respiratory infections and sampled over 200,000 patients between 2009–2019. Here, the authors present results from this program and describe patterns by age, pathogen type, presence of pneumonia, and season.

Worldwide governments have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic, together with the large-scale rollout of vaccines since late 2020. However, the effect of these individual NPI and vaccination measures across space and time has not been sufficiently explored. By the decay ratio in the suppression of COVID-19 infections, we investigated the performance of different NPIs across waves in 133 countries, and their integration with vaccine rollouts in 63 countries as of 25 March 2021. The most effective NPIs were gathering restrictions (contributing 27.83% in the infection rate reductions), facial coverings (16.79%) and school closures (10.08%) in the first wave, and changed to facial coverings (30.04%), gathering restrictions (17.51%) and international travel restrictions (9.22%) in the second wave. The impact of NPIs had obvious spatiotemporal variations across countries by waves before vaccine rollouts, with facial coverings being one of the most effective measures consistently. Vaccinations had gradually contributed to the suppression of COVID-19 transmission, from 0.71% and 0.86% within 15 days and 30 days since Day 12 after vaccination, to 1.23% as of 25 March 2021, while NPIs still dominated the pandemic mitigation. Our findings have important implications for continued tailoring of integrated NPI or NPI-vaccination strategies against future COVID-19 waves or similar infectious diseases.

Governments worldwide have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic. However, the effect of these individual NPI measures across space and time has yet to be sufficiently assessed, especially with the increase of policy fatigue and the urge for NPI relaxation in the vaccination era. Using the decay ratio in the suppression of COVID-19 infections, we investigated the changing performance of different NPIs across waves from global and regional levels (in 133 countries) to national and subnational (in the United States of America [USA]) scales before the implementation of mass vaccination. The synergistic effectiveness of all NPIs for reducing COVID-19 infections declined along waves, from 95.4% in the first wave to 56.0% in the third wave recently at the global level and similarly from 83.3% to 58.7% at the USA national level, while it had fluctuating performance across waves on regional and subnational scales. Regardless of geographical scale, gathering restrictions and facial coverings played significant roles in epidemic mitigation before the vaccine rollout. Our findings have important implications for continued tailoring and implementation of NPI strategies, together with vaccination, to mitigate future COVID-19 waves, caused by new variants, and other emerging respiratory infectious diseases.

Almost 100 years after the 1918 influenza pandemic, China experienced its largest, most widespread epidemic of human infections with avian influenza A (H7N9), the influenza virus with the greatest pandemic potential of all influenza viruses assessed to date by the United States Centers for Disease Control and Prevention’s Influenza Risk Assessment Tool. This historical review describes how China was affected by the 1918, 1958, 1968, and 2009 influenza pandemics, records milestones in China’s capacity to detect and respond to influenza threats, and identifies remaining challenges for pandemic preparedness. This review suggests that past influenza pandemics have improved China’s national capabilities such that China has become a global leader in influenza detection and response. Further enhancing China’s pandemic preparedness to address remaining challenges requires government commitment and increased investment in China’s public health and healthcare systems.