Establishment and validation of a clinical risk scoring model to predict fatal risk in SFTS hospitalized patients.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infection with a high case fatality rate. Significant gaps remain in studies analyzing the clinical characteristics of fatal cases. METHODS: From January 2017 to June 2023, 427 SFTS cases were included in this study. A total of 67 variables about their demographic, clinical, and laboratory data were collected. Univariate logistic regression and the least absolute shrinkage and selection operator (LASSO) method was used to screen predictors from the cohort. Multivariate logistic regression was used to identify independent predictors and nomograms were developed. Calibration, decision curves and area under the curve (AUC) were used to assess model performance. RESULTS: The multivariate logistic regression analysis screened out the four most significant factors, including age > 70 years (p = 0.001, OR = 2.516, 95% CI 1.452-4.360), elevated serum PT (p < 0.001, OR = 1.383, 95% CI 1.143-1.673), high viral load (p < 0. 001, OR = 1.496, 95% CI 1.290-1.735) and high level of serum urea (> 8.0 µmol/L) (p < 0.001, OR = 4.433, 95% CI 1.888-10.409). The AUC of the nomogram based on these four factors was 0.813 (95% CI, 0.758-0.868). The bootstrap resampling internal validation model performed well, and decision curve analysis indicated a high net benefit. CONCLUSIONS: The nomogram based on age, elevated PT, high serum urea level, and high viral load can be used to help early identification of SFTS patients at risk of fatality.

Estimate the number of lives saved by a SARS-CoV-2 vaccination campaign in six states in the United States with a simple model.

Objectives: Vaccination and the emergence of the highly transmissible Omicron variant changed the fate of the COVID-19 pandemic. It is very challenging to estimate the number of lives saved by vaccination given the multiple doses of vaccination, the time-varying nature of transmissibility, the waning of immunity, and the presence of immune evasion. Methods: We established a S-SV-E-I-T-D-R model to simulate the number of lives saved by vaccination in six states in the United States (U.S.) from March 5, 2020, to March 23, 2023. The cumulative number of deaths were estimated under three vaccination scenarios based on two assumptions. Additionally, immune evasion by the Omicron and loss of protection afforded by vaccination or infection were considered. Results: The number of deaths averted by COVID-19 vaccinations (including three doses) ranged from 0.154-0.295% of the total population across six states. The number of deaths averted by the third dose ranged from 0.008-0.017% of the total population. Conclusions: Our estimate of death averted by COVID-19 vaccination in the U.S. was largely in line with an official estimate (at a level of 0.15-0.20% of the total population). We found that the additional contribution of the third dose was small but significant.

Studying the impacts of variant evolution for a generalized age-group transmission model.

The differences of SARS-CoV-2 variants brought the changes of transmission characteristics and clinical manifestations during the prevalence of COVID-19. In order to explore the evolution mechanisms of SARS-CoV-2 variants and the impacts of variant evolution, the classic SIR (Susceptible-Infected-Recovered) compartment model was modified to a generalized SVEIR (Susceptible-Vaccinated-Exposed-Infected-Recovered) compartment model with age-group and varying variants in this study. By using of the SVEIR model and least squares method, the optimal fittings against the surveillance data from Fujian Provincial Center for Disease Control and Prevention were performed for the five epidemics of Fujian Province. The main epidemiological characteristics such as basic reproduction number, effective reproduction number, sensitivity analysis, and cross-variant scenario investigations were extensively investigated during dynamic zero-COVID policy. The study results showed that the infectivities of the variants became fast from wild strain to the Delta variant, further to the Omicron variant. Meanwhile, the cross-variant investigations showed that the average incubation periods were shortened, and that the infection scales quickly enhanced. Further, the risk estimations with the new variants were performed without implements of the non-pharmaceutical interventions, based on the dominant variants XBB.1.9.1 and EG.5. The results of the risk estimations suggested that non-pharmaceutical interventions were necessary on the Chinese mainland for controlling severe infections and deaths, and also that the regular variant monitors were still workable against the aggressive variant evolution and the emergency of new transmission risks in the future.

Exploring the seasonality and optimal control strategy of HIV/AIDS epidemic in China: The impact of seasonal testing.

In this work, we investigate how the seasonal variation in the number of individuals who are tested for an HIV antibody in outpatient clinics affects the HIV transmission patterns in China, which has not been well studied. Based on the characteristics of outpatient testing data and reported cases, we establish a periodic infectious disease model to study the impact of seasonal testing on HIV transmission. The results indicate that the seasonal testing is a driving factor for the seasonality of new cases. We demonstrate the feasibility of ending the HIV/AIDS epidemic. We find that the diagnostic rates related to testing play a crucial role in controlling the size of the epidemic. Specifically, when considering minimizing both infected individuals and diagnostic rates, the level of attention paid to undiagnosed infected individuals is always positively correlated with the optimal diagnostic rates, while the optimal diagnostic rates are negatively correlated with the size of the epidemic at the terminal time.

Association between ambient temperature and influenza prevalence: A nationwide time-series analysis in 201 Chinese cities from 2013 to 2018.

BACKGROUND: Temperature affects influenza transmission; however, currently, limited evidence exists about its effect in China at the national and city levels as well as how temperature can be integrated into influenza interventions. METHODS: Meteorological, pollutant, and influenza data from 201 cities in mainland China between 2013 and 2018 were analyzed at both the city and national levels to investigate the relationship between temperature and influenza prevalence. We examined the impact of temperature on the time-varying reproduction number (Rt) using generalized additive quasi-Poisson regression models combined with the distributed lag nonlinear model. Threshold temperatures were determined for seven regions based on the early warning threshold of serious influenza outbreaks, set at Rt = 1.2. A multivariate random-effects meta-analysis was employed to assess region-specific associations. The excess risk (ER) index was defined to investigate the correlation between Rt and temperature, modified based on seasonal and regional characteristics. RESULTS: At the national level and in the central, northern, northwestern, and southern regions, temperature was found to be negatively correlated with relative risk, whereas the shapes of the data curves for the eastern, southwestern, and northeastern regions were not well defined. Low temperatures had an observable effect on influenza prevalence; however, the effects of high temperatures were not obvious. At an Rt of 1.2, the threshold temperatures for reaching a warning for serious influenza outbreaks were - 24.3 °C in the northeastern region, 16.6 °C in the northwestern region, and between 1℃ and 10 °C in other regions. CONCLUSION: The study findings revealed that temperature had a varying effect on influenza transmission trends (Rt) across different regions in China. By identifying region-specific temperature thresholds at Rt = 1.2, more effective early warning systems for influenza outbreaks could be tailored. These findings emphasize the significance of the region-specific adaptation of influenza prevention and control measures.

Relative effectiveness of a heterologous booster dose with adenovirus type 5 vectored COVID-19 vaccine versus three doses of inactivated COVID-19 vaccine in adults during a nationwide outbreak of omicron predominance, in China: a retrospective, individually matched cohort-control study.

Effectiveness of heterologous booster regimes with ad5 vectored COVID-19 vaccine in a large, diverse population during the national-scale outbreak of SARS-CoV-2 omicron predominance in China has not been reported, yet. We conducted a large-scale cohort-control study in six provinces in China, and did a retrospective survey on the COVID-19 attack risk during this outbreak. Participant aged ≥18 years in five previous trials who were primed with 1 to 3 doses of ICV received heterologous booster with either intramuscular or orally inhaled ad5 vectored COVID-19 vaccine were included in the heterologous-trial cohort. We performed propensity score-matching at a ratio of 1:4 to match participants in the heterologous-trial cohort individually with the community individuals who received three-dose of ICV as a control (ICV-community cohort). From February 4 to April 10, 2023, 41504 (74.5%) of 55710 individuals completed the survey. The median time since the most recent vaccination to the onset of the symptoms of COVID-19 was 303.0 days (IQR 293.0-322.0). The attack rate of COVID-19 in the heterologous-trial cohort was 55.8%, while that in the ICV-community cohort was 64.6%, resulting in a relative effectiveness of 13.7% (95% CI 11.9 to 15.3). In addition, a higher relative effectiveness against COVID-19 associated outpatient visits, and admission to hospital was demonstrated, which was 25.1% (95% CI 18.9 to 30.9), and 48.9% (95% CI 27.0 to 64.2), respectively. The heterologous booster with ad5 vectored COVID-19 vaccine still offered some additional protection in preventing COVID-19 breakthrough infection versus homologous three-dose regimen with ICV, 10 months after vaccination.

Global analysis of an age-structured tuberculosis model with an application to Jiangsu, China.

Diagnostic delay for TB infected individuals and the lack of TB vaccines for adults are the main challenges to achieve the goals of WHO by 2050. In order to evaluate the impacts of diagnostic delay and vaccination for adults on prevalence of TB, we propose an age-structured model with latent age and infection age, and we incorporate Mycobacterium TB in the environment and vaccination into the model. Diagnostic delay is indicated by the age of infection before receiving treatment. The threshold dynamics are established in terms of the basic reproduction number R 0 . When R 0 < 1 , the disease-free equilibrium is globally asymptotically stable, which means that TB epidemic will die out; When R 0 = 1 , the disease-free equilibrium is globally attractive; there exists a unique endemic equilibrium and the endemic equilibrium is globally attractive when R 0 > 1 . We estimate that the basic reproduction number R 0 = 0.5320 (95% CI (0.3060, 0.7556)) in Jiangsu Province, which means that TB epidemic will die out. However, we find that the annual number of new TB cases by 2050 is 1,151 (95%CI: (138, 8,014)), which means that it is challenging to achieve the goal of WHO by 2050. To this end, we evaluate the possibility of achieving the goals of WHO if we start vaccinating adults and reduce diagnostic delay in 2025. Our results demonstrate that when the diagnostic delay is reduced from longer than four months to four months, or 20% adults are vaccinated, the goal of WHO in 2050 can be achieved, and 73,137 (95%CI: (23,906, 234,086)) and 54,828 (95%CI: (15,811, 206,468)) individuals will be prevented from being infected from 2025 to 2050, respectively. The modeling approaches and simulation results used in this work can help policymakers design control measures to reduce the prevalence of TB.

The relationship between compartment models and their stochastic counterparts: A comparative study with examples of the COVID-19 epidemic modeling.

Deterministic compartment models (CMs) and stochastic models, including stochastic CMs and agent-based models, are widely utilized in epidemic modeling. However, the relationship between CMs and their corresponding stochastic models is not well understood. The present study aimed to address this gap by conducting a comparative study using the susceptible, exposed, infectious, and recovered (SEIR) model and its extended CMs from the coronavirus disease 2019 modeling literature. We demonstrated the equivalence of the numerical solution of CMs using the Euler scheme and their stochastic counterparts through theoretical analysis and simulations. Based on this equivalence, we proposed an efficient model calibration method that could replicate the exact solution of CMs in the corresponding stochastic models through parameter adjustment. The advancement in calibration techniques enhanced the accuracy of stochastic modeling in capturing the dynamics of epidemics. However, it should be noted that discrete-time stochastic models cannot perfectly reproduce the exact solution of continuous-time CMs. Additionally, we proposed a new stochastic compartment and agent mixed model as an alternative to agent-based models for large-scale population simulations with a limited number of agents. This model offered a balance between computational efficiency and accuracy. The results of this research contributed to the comparison and unification of deterministic CMs and stochastic models in epidemic modeling. Furthermore, the results had implications for the development of hybrid models that integrated the strengths of both frameworks. Overall, the present study has provided valuable epidemic modeling techniques and their practical applications for understanding and controlling the spread of infectious diseases.

Modelling the preventive treatment under media impact on tuberculosis: A comparison in four regions of China.

Preventive treatment for people with latent Tuberculosis infection (LTBI) has aroused our great interest. In this paper, we propose and analyze a novel mathematical model of TB considering preventive treatment with media impact. The basic reproduction number R0 is defined by the next generation matrix method. In the case without media impact, we prove that the disease-free equilibrium is globally asymptotically stable (unstable) if R0<1(R0>1). Furthermore, we obtain that a unique endemic equilibrium exists when R0>1, which is globally asymptotically stable in the case of permanent immunity and no media impact. We fit the model to the newly reported TB cases data from 2009 to 2019 of four regions in China and estimate the parameters. And we estimated R0=0.5013<1 in Hubei indicating that TB in Hubei will be eliminated in the future. However, the estimated R0=1.015>1 in Henan, R0=1.282>1 in Jiangxi and R0=1.930>1 in Xinjiang imply that TB will continue to persist in these three regions without further prevention and control measures. Besides, sensitivity analysis is carried out to illustrate the role of model parameters for TB control. Our finding reveals that appropriately improving the rate of timely treatment for actively infected people and increasing the rate of individuals with LTBI seeking preventive treatment could achieve the goal of TB elimination. In addition, another interesting finding shows that media impact can only reduce the number of active infections to a limited extent, but cannot change the prevalence of TB.

Environmental Contamination of SARS-CoV-2 Delta VOC by COVID-19 Patients Staying in the Hospital for More Than Two Weeks.

Background: Patients infected with SARS-CoV-2 Delta VOC have a longer course of disease. We detected the air, surfaces, and patient's personal items in the wards of the second hospital of Nanjing during the outbreak of the COVID-19 Delta Variant to identify the environmental contamination, which provides a theoretical basis for the prevention and control of COVID-19 variation beads in the future. Methods: In the cross-sectional study, we collected and analyzed clinical features, demographic and epidemiological data, laboratory and swab test results, and surface and air samples of 144 COVID-19 cases. Results: The time from symptom onset to surface sampling was 25 days (IQR, 21 to 33 days). Positive throat swabs were detected in 52(36.1%) patients, of which only 8(5.6%) patients had N or ORF1a/b genes Ct value <35 on the surface sampling day. Among the 692 environmental surface and air specimens collected from 144 COVID-19 cases, 3 specimens (3/692, 0.4%) related to 5 cases (3.5%, 5/144) were detected positive on RT-PCR. Overall, bedside tables (2/144, 1.4%) were most likely to be contaminated, followed by toilet seats (1/81, 1.2%). Conclusion: The environmental contamination by SARS-CoV-2 Delta VOC-infected cases with disease duration of more than two weeks is limited.

Annual incidence and fatality rates of notifiable infectious diseases in southeast China from 1950 to 2022 and relationship to socioeconomic development.

Background: Over the past 70 years, China has advanced significantly in the prevention and treatment of infectious diseases while simultaneously undergoing a socioeconomic transformation, making it a useful source of data for analysing relationships between public health policy and the control of infectious diseases. Methods: We collected data on the incidence of notifiable infectious diseases and associated fatalities in Jiangsu province in southeast China from the Provincial Center for Disease Control and Prevention, Provincial Institute of Parasitic Diseases, and the Nationwide Notifiable Infectious Diseases Reporting Information System. We compared data from different historical periods using descriptive statistical methods, joinpoint regression, and correlation analysis. Results: During 1950-2022, 75 754 008 cases of 46 notifiable infectious diseases were reported in Jiangsu, with an average annual incidence was 1679.49 per 100 000 population and a fatality rate of 1.82 per 1000 persons. The incidence of classes A-B decreased (average annual percent change (AAPC) = -2.1) during the entire study period, while the incidence of class C increased (AAPC = 10.8) after 2004. The incidence of intestinal diseases (AAPC = -4.4) and vector-borne and zoonotic diseases (AAPC = -8.1) decreased rapidly, while the incidence of sexually transmitted and blood-borne diseases (AAPC = 1.8) increased. The number of medical and health institutions and the per capita gross domestic product correlated negatively with the annual incidence of diseases in classes A-B, but not with fatality rates. Conclusions: Although the annual incidence of many severe infectious diseases has decreased in Jiangsu since 1950, the incidence of sexually transmitted and blood-borne diseases increased. Socioeconomic growth and sustainable investment in health systems are associated with better control of infectious diseases.

COVID-19 transmission driven by age-group mathematical model in Shijiazhuang City of China.

Background: A COVID-19 outbreak in the rural areas of Shijiazhuang City was attributed to the complex interactions among vaccination, host, and non-pharmaceutical interventions (NPIs). Herein, we investigated the epidemiological characteristics of all reported symptomatic cases by picking Shijiazhuang City, Hebei Province in Northern China as research objective. In addition, we established a with age-group mathematical model to perform the optimal fitting and to investigate the dynamical profiles under three scenarios. Methods: All reported symptomatic cases of Shijiazhuang epidemic (January 2-February 3, 2021) were investigated in our study. The cases were classified by gender, age group and location, the distributions were analyzed by epidemiological characteristics. Furthermore, the reported data from Health Commission of Hebei Province was also analyzed by using an age-group mathematical model by two phases and three scenarios. Results: Shijiazhuang epidemic caused by SARS-CoV-2 wild strain was recorded with the peak 84 cases out of 868 reported symptomatic cases on January 11, 2021, which was implemented with strong NPIs by local government and referred as baseline situation in this study. The research results showed that R0 under baseline situation ranged from 4.47 to 7.72, and Rt of Gaocheng Distinct took 3.72 with 95% confidence interval from 3.23 to 4.35 on January 9, the declining tendencies of Rt under baseline situation were kept till February 3, the value of Rt reached below 1 on January 19 and remained low value up to February 3 for Gaocheng District and Shijiazhuang City during Shijiazhuang epidemic. This indicated Shijiazhuang epidemic was under control on January 19. However, if the strong NPIs were kept, but remote isolation operated on January 11 was not implemented as of February 9, then the scale of Shijiazhuang epidemic reached 9482 cases from age group who were 60 years old and over out of 31,017 symptomatic cases. The investigation also revealed that Shijiazhuang epidemic reached 132,648 symptomatic cases for age group who were 60 years old and over (short for G2) under risk-based strategies (Scenario A), 58,048 symptomatic cases for G2 under late quarantine strategies (Scenario B) and 207,124 symptomatic cases for G2 under late quarantine double risk strategies (Scenario C), and that the corresponding transmission tendencies of Rt for three scenarios were consistently controlled on Jan 29, 2021. Compared with baseline situation, the dates for controlling Rt below 1 under three scenarios were delayed 10 days. Conclusions: Shijiazhuang epidemic was the first COVID-19 outbreak in the rural areas in Hebei Province of Northern China. The targeted interventions adopted in early 2021 were effective to halt the transmission due to the implementation of a strict and village-wide closure. However we found that age group profile and NPIs played critical rules to successfully contain Shijiazhuang epidemic, which should be considered by public health policies in rural areas of mainland China during the dynamic zero-COVID policy.

Dynamic modeling and data fitting of climatic and environmental factors and people's behavior factors on hand, foot, and mouth disease (HFMD) in Shanghai, China.

Background: Hand, foot, and mouth disease (HFMD) appear to be a multi-wave outbreak with unknown mechanisms. We investigate the effects of climatic and environmental factors and changes in people's behavior factors that may be caused by external factors: temperature, relative humidity, and school opening and closing. Methods: Distributed lag nonlinear model (DLNM) and dynamic model are used to research multi-wave outbreaks of HFMD. Climatic and environmental factors impact on transmission rate ß(t) is modeled through DLNM and then substituted into this relationship to establish the dynamic model with reported case data to test for validity. Results: Relative risk (RR) of HFMD infection increases with increasing temperature. The RR of infection first increases and then decreases with the increase of relative humidity. For the model fitting HFMD dynamic, time average basic reproduction number [R0] of Stage I (without vaccine) and Stage II (with EV71 vaccine) are 1.9362 and 1.5478, respectively. Temperature has the highest explanatory power, followed by school opening and closing, and relative humidity. Conclusion: We obtain three conclusions about the prevention and control of HFMD. 1) According to the temperature, relative humidity and school start time, the outbreak peak of HFMD should be warned and targeted prevention and control measures should be taken. 2) Reduce high indoor temperature when more than 31.5 oC, and increase low relative humidity when less than 77.5% by opening the window for ventilation, adding houseplants, using air conditioners and humidifiers, reducing the incidence of HFMD and the number of infections. 3) The risk of HFMD transmission during winter vacations is higher than during summer vacations. It is necessary to strengthen the publicity of HFMD prevention knowledge before winter vacations and strengthen the disinfection control measures during winter vacations in children's hospitals, school classrooms, and other places where children gather to reduce the frequency of staff turnover during winter vacations.

Effects and interaction of temperature and relative humidity on the trend of influenza prevalence: A multi-central study based on 30 provinces in mainland China from 2013 to 2018.

Background: Evidence is inefficient about how meteorological factors influence the trends of influenza transmission in different regions of China. Methods: We estimated the time-varying reproduction number (Rt) of influenza and explored the impact of temperature and relative humidity on Rt using generalized additive quasi-Poisson regression models combined with the distribution lag non-linear model (DLNM). The effect of temperature and humidity interaction on Rt of influenza was explored. The multiple random-meta analysis was used to evaluate region-specific association. The excess risk (ER) index was defined to investigate the correlation between Rt and each meteorological factor with the modification of seasonal and regional characteristics. Results: Low temperature and low relative humidity contributed to influenza epidemics on the national level, while shapes of merged cumulative effect plots were different across regions. Compared to that of median temperature, the merged RR (95%CI) of low temperature in northern and southern regions were 1.40(1.24,1.45) and 1.20 (1.14,1.27), respectively, while those of high temperature were 1.10(1.03,1.17) and 1.00 (0.95,1.04), respectively. There were negative interactions between temperature and relative humidity on national (SI = 0.59, 95%CI: 0.57-0.61), southern (SI = 0.49, 95%CI: 0.17-0.80), and northern regions (SI = 0.59, 95%CI: 0.56,0.62). In general, with the increase of the change of the two meteorological factors, the ER of Rt also gradually increased. Conclusions: Temperature and relative humidity have an effect on the influenza epidemics in China, and there is an interaction between the two meteorological factors, but the effect of each factor is heterogeneous among regions. Meteorological factors may be considered to predict the trend of influenza epidemic.

Safety, immunogenicity and protection of heterologous boost with an aerosolised Ad5-nCoV after two-dose inactivated COVID-19 vaccines in adults: a multicentre, open-label phase 3 trial.

BACKGROUND: Aerosolised Ad5-nCoV is one of the first licensed mucosal respiratory vaccine against SARS-CoV-2 in the world; however, the safety profile of this vaccine has not been reported in a large population yet. METHODS: This multicentre, open-label phase 3 trial, done in 15 centres in six provinces (Jiangsu, Hunan, Anhui, Chongqing, Yunnan, Shandong) in China, aimed to evaluate the safety and immunogenicity of aerosolised Ad5-nCoV in healthy adults (members of the general population with no acute febrile disorders, infectious disease, serious cardiovascular diseases, serious chronic diseases or progressive diseases that cannot be controlled) at least 18 years old, who had received two doses of inactivated COVID-19 vaccine as their primary regimen. This study contained a non-randomly assigned safety cohort and a centrally randomly assigned (1:1) immunogenicity subcohort. The patients in the immunogenicity subcohort received aerosolised Ad5-nCov (aerosolised Ad5-nCoV group) or inactivated vaccine (inactivated COVID-19 group) The primary endpoints were the incidence of adverse reactions within 28 days following the booster vaccination with aerosolised Ad5-nCoV in the safety population (collected through a daily record of any solicited or unsolicited adverse events filled by each participant) and the geometric mean titre of neutralising antibodies at day 28 after the booster dose in the immunogenicity subcohort (measured with a pseudovirus neutralisation test). This study was registered with ClinicalTrials.gov, NCT05204589. FINDINGS: Between Jan 22, 2022, and March 12, 2022, we recruited 11 410 participants who were screened for eligibility, of whom 10 267 (99·8%) participants (5738 [55·9%] men, 4529 [44·1%] women; median age 53 years [18-92]) received the study drugs: 9847 (95·9%) participants in the open-label cohort to receive aerosolised Ad5-nCoV, and 420 (4·1%) in the immunogenicity subcohort (212 in the aerosolised Ad5-nCoV group and 208 in the inactivated vaccine group). Adverse reactions were reported by 1299 (13%) of 10 059 participants within 28 days after receiving the booster vaccination with aerosolised Ad5-nCoV, but most of the adverse reactions reported were mild to moderate in severity. Participants in the aerosolised Ad5-nCoV group had a significantly higher level of the neutralising antibodies against omicron BA.4/5 (GMT 107·7 [95% CI 88·8-130·7]) than did those in the inactivated vaccine group (17·2 [16·3-18·2]) at day 28. INTERPRETATION: The heterologous booster regimen with aerosolised Ad5-nCoV is safe and highly immunogenic, boosting both systemic and mucosal immunity against omicron subvariants. FUNDING: National Natural Science Foundation of China, Jiangsu Provincial Science Fund for Distinguished Young Scholars, and Jiangsu Provincial Key Project of Science and Technology Plan. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Impact of antibody-level on viral shedding in B.1.617.2 (Delta) variant-infected patients analyzed using a joint model of longitudinal and time-to-event data.

Knowledge of viral shedding remains limited. Repeated measurement data have been rarely used to explore the influencing factors. In this study, a joint model was developed to explore and validate the factors influencing the duration of viral shedding based on longitudinal data and survival data. We divided 361 patients infected with Delta variant hospitalized in Nanjing Second Hospital into two groups (≤ 21 days group and > 21 days group) according to the duration of viral shedding, and compared their baseline characteristics. Correlation analysis was performed to identify the factors influencing the duration of viral shedding. Further, a joint model was established based on longitudinal data and survival data, and the Markov chain Monte Carlo algorithm was used to explain the influencing factors. In correlation analysis, patients having received vaccination had a higher antibody level at admission than unvaccinated patients, and with the increase of antibody level, the duration of viral shedding shortened. The linear mixed-effects model showed the longitudinal variation of logSARS-COV-2 IgM sample/cutoff (S/CO) values, with a parameter estimate of 0.193 and a standard error of 0.017. Considering gender as an influencing factor, the parameter estimate of the Cox model and their standard error were 0.205 and 0.1093 (P = 0.608), the corresponding OR value was 1.228. The joint model output showed that SARS-COV-2 IgM (S/CO) level was strongly associated with the risk of a composite event at the 95% confidence level, and a doubling of SARS-COV-2 IgM (S/CO) level was associated with a 1.38-fold (95% CI: [1.16, 1.72]) increase in the risk of viral non-shedding. A higher antibody level in vaccinated patients, as well as the presence of IgM antibodies in serum, can accelerate shedding of the mutant virus. This study provides some evidence support for vaccine prevention and control of COVID-19 variants.

Study on the COVID-19 epidemic in mainland China between November 2022 and January 2023, with prediction of its tendency.

The prediction system EpiSIX was used to study the COVID-19 epidemic in mainland China between November 2022 and January 2023, based on reported data from December 9, 2022, to January 30, 2023, released by The Chinese Center for Disease Control and Prevention on February 1, 2023. Three kinds of reported data were used for model fitting: the daily numbers of positive nucleic acid tests and deaths, and the daily number of hospital beds taken by COVID-19 patients. It was estimated that the overall infection rate was 87.54% and the overall case fatality rate was 0.078%-0.116% (median 0.100%). Assuming that a new COVID-19 epidemic outbreak would start in March or April of 2023, induced by a slightly more infectious mutant strain, we predicted a possible large rebound between September and October 2023, with a peak demand of between 800,000 and 900,000 inpatient beds. If no such new outbreak was induced by other variants, then the current COVID-19 epidemic course in mainland China would remain under control until the end of 2023. However, it is suggested that the necessary medical resources be prepared to manage possible COVID-19 epidemic emergencies in the near future, especially for the period between September and October 2023.

Impact of inactivated COVID-19 vaccines on lung injury in B.1.617.2 (Delta) variant-infected patients.

BACKGROUND: Chest computerized tomography (CT) scan is an important strategy that quantifies the severity of COVID-19 pneumonia. To what extent inactivated COVID-19 vaccines could impact the COVID-19 pneumonia on chest CT is not clear. METHODS: This study recruited 357 SARS-COV-2 B.1.617.2 (Delta) variant-infected patients admitted to the Second Hospital of Nanjing from July to August 2021. An artificial intelligence-assisted CT imaging system was used to quantify the severity of COVID-19 pneumonia. We compared the volume of infection (VOI), percentage of infection (POI) and chest CT scores among patients with different vaccination statuses. RESULTS: Of the 357 Delta variant-infected patients included for analysis, 105 were unvaccinated, 72 were partially vaccinated and 180 were fully vaccinated. Fully vaccination had the least lung injuries when quantified by VOI (median VOI of 222.4 cm3, 126.6 cm3 and 39.9 cm3 in unvaccinated, partially vaccinated and fully vaccinated, respectively; p < 0.001), POI (median POI of 7.60%, 3.55% and 1.20% in unvaccinated, partially vaccinated and fully vaccinated, respectively; p < 0.001) and chest CT scores (median CT score of 8.00, 6.00 and 4.00 in unvaccinated, partially vaccinated and fully vaccinated, respectively; p < 0.001). After adjustment for age, sex, comorbidity, time from illness onset to hospitalization and viral load, fully vaccination but not partial vaccination was significantly associated with less lung injuries quantified by VOI {adjust coefficient[95%CI] for "full vaccination": - 106.10(- 167.30,44.89); p < 0.001}, POI {adjust coefficient[95%CI] for "full vaccination": - 3.88(- 5.96, - 1.79); p = 0.001} and chest CT scores {adjust coefficient[95%CI] for "full vaccination": - 1.81(- 2.72, - 0.91); p < 0.001}. The extent of reduction of pulmonary injuries was more profound in fully vaccinated patients with older age, having underlying diseases, and being female sex, as demonstrated by relatively larger absolute values of adjusted coefficients. Finally, even within the non-severe COVID-19 population, fully vaccinated patients were found to have less lung injuries. CONCLUSION: Fully vaccination but not partially vaccination could significantly protect lung injury manifested on chest CT. Our study provides additional evidence to encourage a full course of vaccination.

Association of Endocrine-Disrupting Chemicals with All-Cause and Cause-Specific Mortality in the U.S.: A Prospective Cohort Study.

Wide exposure to endocrine-disrupting chemicals (EDCs) poses a great risk on human health. However, few large-scale cohort studies have comprehensively estimated the association between EDCs exposure and mortality risk. This study aimed to investigate the association of urinary EDCs exposure with mortality risk and quantify attributable mortality and economic loss. Multivariable Cox proportional hazards regression models were performed to investigate the association of 38 representative EDCs exposure with mortality risk in the National Health and Nutrition Examination Survey (NHANES). During a median follow-up of 7.7 years, 47,279 individuals were enrolled. All-cause mortality was positively associated with 1-hydroxynaphthalene, 2-hydroxynaphthalene, cadmium, antimony, cobalt, and monobenzyl phthalate. Cancer mortality was positively associated with cadmium. Cardiovascular disease (CVD) mortality was positively associated with 1-hydroxynaphthalene, 2-hydroxynaphthalene, and 2-hydroxyfluorene. Nonlinear U-shaped relationships were found between all-cause mortality and cadmium and cobalt, which was also identified between 2-hydroxyfluorene and CVD mortality. J-shaped association of cadmium exposure with cancer mortality was also determined. EDCs exposure may cause 56.52% of total deaths (1,528,500 deaths) and around 1,897 billion USD in economic costs. Exposure to certain phthalates, polycyclic aromatic hydrocarbons, phytoestrogens, or toxic metals, even at substantially low levels, is significantly associated with mortality and induces high economic costs.