Integrity monitoring (IM) is essential if GNSS positioning technologies are to be fully trusted by future intelligent transport systems. A tighter and conservative stochastic model can shrink protection levels in the position domain and therefore enhance the user-level integrity. In this study, the stochastic models for vehicle-based GNSS positioning are refined in three respects: (1) Gaussian bounds of precise orbit and clock error products from the International GNSS Service are used; (2) a variable standard deviation to characterize the residual tropospheric delay after model correction is adopted; and (3) an elevation-dependent model describing the receiver-related errors is adaptively refined using least-squares variance component estimation. The refined stochastic models are used for positioning and IM under the Advanced Receiver Autonomous Integrity Monitoring (ARAIM) framework, which is considered the basis for multi-constellation GNSS navigation to support air navigation in the future. These refinements are assessed via global simulations and real data experiments. Different schemes are designed and tested to evaluate the corresponding enhancements on ARAIM availability for both aviation and ground vehicle-based positioning applications. One prospective application of ground-based global navigation satellite system (GNSS) positioning is autonomous driving within the context of intelligent transport systems (ITS). To be a key component in these systems, the accuracy, integrity, continuity and availability of GNSS positioning must be maintained at appropriate levels. Although high precision GNSS positioning technologies such as RTK , PPP (precise point positioning), and PPP-RTK can achieve centimeter-level positioning accuracy, GNSS still faces serious challenges when applied to safety-of-life (SoL) applications .Integrity monitoring (IM) should be conducted if GNSS positioning technologies are to be primarily used, and fully trusted, in ITS SoL applications. IM has two tasks . FirstlyOriginating from aviation applications, to satisfy the GNSS positioning accuracy, integrity, continuity and availability during different phases of flight, airborne-based augmentation systems (ABAS), satellite-based augmentation systems (SBAS) and ground-based augmentation systems (GBAS) have been developed since the mid-1990s . ReceiveIn general, IM for aviation is still based on the implementation of the standard GNSS single point positioning (SPP) mode, a snapshot least-squares (LS) procedure that uses pseudorange or carrier-smoothed code observations. In the ARAIM baseline algorithm, broadcast ephemeris, classical tropospheric and ionospheric delay correction/elimination models/methods are specified. As the operational environments are open sky, a mature and fixed stochastic model has been established to successfully compensate for the multipath and pseudorange noises for specific airborne GNSS receivers .(1)Precise satellite orbit and clock error products have been widely used;(2)Advanced atmospheric delay correction models are available;(3)Receiver noises and environment-dominant multipath effects are quite diverse;(4)Multiple undetected pseudorange outliers, cycle slips, and uncalibrated system biases should be monitored in the fault modes;(5)FDE and PL calculation should be conducted during a Kalman filtering (KF) procedure instead of a snapshot LS procedure.However, similar schemes that are used for ground vehicle-based positioning to maintain the required levels of accuracy, integrity, continuity and availability are lacking. Carrier phase-based RAIM (CRAIM) algorithms for RTK and PPP positioning using a Kalman filter have been studied for both float ambiguity or fixed ambiguity positioning modes ,13,14. EAt the first stage, it is anticipated that the user-level integrity would be enhanced if a tighter and conservative stochastic model is applied. In this paper, the authors comprehensively refine the stochastic model and evaluate the potential enhancement of user-level integrity using the ARAIM concept, mainly for vehicle-based GNSS positioning applications. The rest of the paper is organized as follows. Firstly, an overview of the ARAIM concept as it was developed for aviation applications are given. Then, the prospective challenges of IM for vehicle-based GNSS positioning are discussed, with comparisons to aviation applications. Next, the three refinements of the ARAIM stochastic model for vehicle-based GNSS positioning are presented. Experiments and analyses to evaluate the ARAIM performance improvements follow. The concluding remarks of this study are presented last.The ARAIM concept and its baseline algorithm are outlined in the GPS Evolutionary Architecture Study (GEAS) in the GEAS phase II report , which hA brief overview of the ARAIM baseline user algorithm proposed in the  is givenAccording to y is the m × 1 vector of observed minus computed (OMC) values of pseudorange observations, x is the t × 1 vector of unknown parameters and A is the m × t design matrix determined by the satellite-to-receiver geometry. The error vector e contains all unmodeled errors and is modeled as zero-mean normal distributed random variables with a variance of In general, the linearized mathematical model for GNSS positioning contains a functional and a stochastic modelIt is noted that the covariance matrix If dual-frequency observations are available, the ARAIM algorithm will use the ionosphere-free (IF) combination of pseudorange observations for positioning. For each pseudorange OMC value, purposes .For advanced positioning modes such as RTK, PPP, or PPP-RTK, the tropospheric and/or ionospheric-related errors could be considered unknown parameters, and corresponding constraint equations are added to the set of observation equations ,24. In ti’ is the satellite indicator; i, used for integrity as well as for accuracy and continuity, respectively; According to the ARAIM framework, the diagonal (co)variance matrices given by (2){Dee,The first terms in Equation (2) should characterize the signal in space (SIS) user range error (URE), which is dominated by satellite orbits and clock errors . Traditie σURA,i .i, which projects the zenith The second term, deled as (3)σtrop be 0.12 ; and Ei The third term, deled as (4)σuserIn Equations (1) and (2), the all-in-view positions and fault-tolerant positions are obtained via LS estimation, using which the PDE procedure and PL calculation are then performed.Although IM for aviation has been comprehensively investigated and three standard enhancement technologies have been announced by the ICAO, IM faces big challenges in ground-based GNSS positioning applications such as ITS. The different issues that IM should consider are summarized in Firstly, different observations and positioning techniques are used. In aviation, the baseline IM algorithms are defined based on the assumption that a snapshot weighted LS position algorithm is implemented. Usually, differential or corrected pseudorange observations from GPS or GPS/Galileo dual systems are used. On the other hand, for ground-based positioning applications, multi-frequency and multi-constellation carrier phase observations are increasingly implemented using the RTK, PPP or PPP-RTK modes, seeking higher accuracy, integrity, continuity and availability. In such circumstances, positioning and IM should be based on a KF algorithm, which makes use of observations from all previous epochs. In theory, rigorous IM based on a KF algorithm, including the FDE procedure and PL calculation, should consider potential failure threats to both pseudorange and carrier phase observations.Secondly, stochastic models for positioning and IM for ground-based positioning need to be redefined. In aviation, stochastic models only need to characterize the errors of pseudorange observations. As mentioned above, the total error in a raw or corrected pseudorange observation is the sum of satellite-related, atmospheric-related and receiver-related errors. The variances of these error terms have been explicitly defined by specifications under GBAS, SBAS or RAIM/ARAIM frameworks, where broadcast ephemerides, as well as the specific way to correct tropospheric and ionospheric delays, should be implemented. The observations are generated by an airborne receiver that satisfies the requirements of specified accuracy conditions, and should be operated under the assumed interference environment. Therefore, the receiver-related error term is characterized by a fixed and well-defined model. In contrast, for ground-based positioning, a variety of augmentation approaches can be implemented, i.e., using IGS precise satellite orbit and clock error products, eliminating or correcting the tropospheric and ionospheric delays by various advanced models and estimating those residual delays together with the navigation parameters. In addition, both the receiver manufacturers and the operational environments are diverse, so a single fixed model cannot characterize the receiver-related error term.−5 for satellite, and <10−4 for constellation). For ground-based positioning, since both pseudorange and carrier phase observations would be used by various advanced positioning algorithms, modeling and monitoring the satellite-related and atmosphere-related errors becomes increasingly complicated. In addition, the effects caused by different types of receivers and the diversity of near-ground operational environments complicate matters further [Thirdly, fault events and modes that need to be monitored are more complicated for ground-based positioning. Within the RAIM/ARAIM framework, the error in a pseudorange OMC value is divided into two parts: the unmonitored maximum nominal bias in the null hypothesis model for the fault-free mode, and the monitored unknown large bias in each alternative hypothesis model for the fault mode. Only satellite and constellation failures that cause the unknown large bias in position solutions are monitored with an assumed small occurrence rate Gaussian bounds of IGS RTS products are used to consider the satellite effects delicately;(2)A variable standard deviation for characterizing the residual tropospheric delay is adopted to consider the atmosphere effects delicately;(3)An elevation-dependent model describing the receiver-related errors is adaptively refined to consider the receiver effects delicately.Current stochastic models used in ARAIM baseline algorithms are only specified for aviation applications and are overly conservative in order to guarantee security. In this section, the stochastic models for ground vehicle-based GNSS positioning are refined thusly:In this study, the authors discuss these issues for the SPP mode. However, these investigations can also contribute to advanced-mode GNSS positioning, which will be undertaken in future work.For real-time precise positioning and navigation, the satellite precise orbit and clock error products provided by the IGS RTS can be applied. In this subsection, the variance of the satellite-related error term, denoted by It would be inappropriate that By subtracting the RTS orbit and clocks from their post-processing counterparts, error samples for orbit and clock are obtained; these are denoted as It is noted that Equation (6) does not follow the stringent definition of URA and URE in order to ensure the estimation is more conservative. It has been verified that the integrity risk computed using the convolution of the overbounding distributions described above is an upper bound of the integrity risk computed using the convolution of the true distributions. This means the PLs computed by using the overbounding mean and STD values are still conservative and can satisfy the integrity requirement .There are several IGS RTS products that can be received in real time. In this study, the IGC01 products are used. The IGC01 products are firstly generated by individual real-time analysis centers (ACs) and combined by the European Space Agency’s Space Operations Center (ESA/ESOC). In particular, IGC01 is a single-epoch combined product with an update rate of 5 s for both orbit and clock . The IGSAs an example, the The mean and STD values of From The current tropospheric delay correction model used in ARAIM is the one recommended by the Radio Technical Committee for Aeronautics (RTCA) and is described in RTCA’s Minimum Operational Performance Standards (RTCA MOPS). It states that, in terms of STD, the maximum ZPD residuals after model correction is 0.12 m . Howeverrrection .For integrity, ix steps .Step 1: The residual series Step 2: The seasonal variations of Step 3: The annual maximum and minimum of the normalized residual series n being the band indicator.Step 4: To completely overbound the original residuals Step 5: A variable standard deviation, K is the right tail quantile of the PDF of a standard normal distribution at the extreme probability level, corresponding to the preset PHMI.Step 6: The total Two commonly used tropospheric delay correction models, UNB3 and GPT2w, were evaluated. For a worldwide integrity analysis, the grid-wise VMF3 products with a resolution of 1 × 1 degree between 2000 to 2016 were selected as the reference.As an example, considering the zenith hydrostatic delays (ZHD) residuals of GPT2w in the latitude band 41° N–50° N, the original residual series (blue dots) and its upper bounds (red periodic curves) are shown in To further investigate the effectiveness of the upper bounds, the Stanford diagrams of the two models are shown in The variable STDs for the two models, in each latitude band, are plotted in According to the ARAIM framework, the receiver-related error term is characterized by an elevation-dependent model with constant coefficients, as given in Equation (5), which can only represent the errors of an airborne GPS receiver when it operates under a specific interference environment. For ground-based positioning, such a fixed model would be inadequate, if different types of receivers are used under diverse operational environments. In this subsection, the elevation-dependent model to describe the receiver-related errors is adaptively refined using least-squares variance component estimation (LSVCE), with the variances of satellite-related and atmospheric-related errors being considered as known parts.a and b are the model coefficients that need to be estimated. Other variables have been defined in previous section.There are many elevation-dependent models that can be used to characterize receiver-related errors with adaptive coefficients. The authors adopt the conventional one .(11)σusLSVCE is conventionally used to construct a more accurate and adaptive (co)variance matrix based on the LS criterion. According to LSVCE, the functional and stochastic models are processed in a unified manner, and the variance matrix can be customized by users to adapt to different applications.,The (co)variance matrix of the linear Gauss–Markov model (Equation (1)) can be represented as (12)Dee=Combining Equations (1) and (12), the mathematical model of LSVCE contains two groups of unknowns: the original parameter vector Using the law of error propagation, the expectation and (co)variance of the estimate areSubstituting Equation (12) into Equation (14)vh-operator, the matrix observation equation Equation (15) is transformed to the familiar vector–matrix form of the linear observation equationKronecker product; and duplication matrix that satisfies the condition vh-operator, vec-operator and duplication matrix By using the pendix A .Assuming T constructed by the estimated unknown parameter T should follow a centralized t. For GNSS positioning applications, the authors have only used the 3×1 positioning parameter vector for testing.Finally, by checking whether a set of samples matches the assumed PDF, the reliability of the stochastic model can be evaluated . The tesThe GPS dual-frequency IF combination pseudorange observations, from four IGS GNSS continuously operating receiver stations at different latitudes, were used to fit the coefficients and to evaluate the reliability of the stochastic model. The time period of the data was between 5th September 2019 and 4th October 2019.D0, using IGC01 products and GPT2w tropospheric delay corrections. The variances necessary to characterize the receiver-related error term are estimated with LSVCE and are used to fit the model coefficients of Equation (14). The fitting results are listed in a varies between 0.4 and 0.8, and the value of coefficient b varies between 0.02 and 0.15. It should be noted that the two coefficients have the smallest values at the station NYA2, which is located in the Arctic region.For each pseudorange observation, the variances of the first two terms at the right side of Equation (2) are considered the known part T, as given in Equation (19), was calculated. The elevation-dependent model with constant coefficients applied in GAMP [To evaluate the reliability of the adaptive elevation-dependent model, the test statistic  in GAMP  was usedT (blue bars), together with the PDF of the T in general have better consistency with the centralized The upper panels are plots of the results for the four IGS stations before refinement, and the lower panels are plots of the corresponding values after refinement. The upper panels show that the statistics are mainly distributed on the left side of the PDF of −7, and prior probabilities of a satellite or constellation fault were set to be 10−5 and 10−4, respectively. In both applications, improvements on ARAIM availability and PLs were analyzed using different options for stochastic model refinements. As the refinement for the receiver-related error term should rely on real data, the corresponding performance improvements are evaluated using the actual observations collected by the aforementioned IGS stations.In this section, the performance enhancements for aviation and ground-based positioning applications are further investigated. The open-source Matlab Availability Analysis Simulation Tools (MAAST) released by the GPS Lab, Stanford University, are used for the ARAIM evaluation. Only the GPS constellation is considered. To ensure consistency with the values estimated in last section, the broadcast ephemeris and the IGC01 RTS products, over the same time span between 1 September 2019 and 20 September 2020, were used for the integrity analyses. The required integrity is 10Seven schemes are tested to demonstrate the performance improvements brought about by refining the stochastic model of the three error terms for the aviation and ground-based positioning applications.As the fixed model given by Equations 4) and (5) is only specified for avionics receivers, the receiver-related error term should be redefined. Detailed designs for parameters for the seven schemes are given in  and (5) For aviation, the differences among Schemes A–C are:Scheme A—Original design of the baseline algorithm: Scheme B—Refinement using IGS RTS products (IGC01): Scheme C—Refinement using IGS RTS products (IGC01) and spatiotemporal-varying STDs for residual tropospheric delays: Schemes D–F are the counterparts of A–C for the ground-based positioning applications, where the stochastic model of the receiver-related error term is now defined by Equation (20). Scheme G is intended for the evaluation of the ARAIM performance improvement brought about by using a more accurate tropospheric correction model, via a comparison with the results of Scheme F.The global coverage of ARAIM availability satisfying the LPV-200 requirements for aviation under Schemes A, B and C are shown in σZPD in this region has less reduction compared with the constant value of 0.12 m, which is used under Scheme B.The 99.5% VPL maps under the three schemes are further plotted in Similarly, the 99.5% HPL maps under the three schemes are shown in σZPD. Compared with HPLs, the improvement to VPLs is more significant, as the AL for VPL is generally more stringent for aviation.In general, the results and analyses in this section show that worldwide ARAIM availability for aviation can be significantly improved by using the IGS RTS products and a tighter and variable value for One expects similar improvements to be observed for ground-based positioning. Compared with vertical positioning (for aviation applications), horizontal positioning is more crucial for ground-based positioning users. The 99.5% HPL maps for Schemes D–G are given in To further highlight the discrepancies among Scheme E, F and G, the HPL mean values at each user grid point are plotted along with the point number in The above analyses assume that the user is in an open-sky environment, which is a condition that usually cannot be satisfied in ground vehicle-based positioning applications. To demonstrate the performance degradation caused by receiving ambient occlusion, Schemes H, I and J are designed with the cut-off elevation angle being 10, 15 and 20 degrees, while the other parameters are kept the same as those of Scheme G. The 99.5% HPL maps of the three schemes are shown in The receiver-related error term of the stochastic model should characterize the receiver noises and multipath errors, and therefore the model should be able to accommodate different receivers and operational environments. Via LSVCE, receiver-related errors can be optimally modeled by an elevation-dependent function with adaptive coefficients. To evaluate the ARAIM performance improvements via this refinement, the same dataset as that in last section is used. To analyze the impacts of fault detection and exclusion, we simulated 20 m gross errors on two pseudoranges at each station during the 1000th and 2000th epoch. The Stanford diagrams of horizontal positioning errors (HPEs) and HPLs before and after the refinement at the four IGS stations are shown in In There are also significant differences in performance at different stations. At the polar station NYA2, HPEs are obviously smaller than HPEs at the other three stations, and the HPLs reduce to a much lower range of 10 m to 25 m after refinement. The worst performance is at the mid-latitude station DAEJ, where the HPLs before and after refinement are mainly in the range 25 m to 50 m, and 10 m to 40 m, respectively. Slightly better performance is observed at the station REUN, where the HPLs after refinement are reduced to a range of 10 m to 30 m, while the values before refinement are mainly between 20 m and 50 m.In general, the results evaluated via real data shown in According to the ARAIM baseline algorithm, the first order ionospheric delays can be corrected using the dual-frequency IF combination, and the residual tropospheric delays after model correction are usually at the centimeter level. For aviation, the satellite-related error term, mainly caused by the broadcast ephemeris errors, dominates the stochastic model. By replacing the broadcast ephemeris with IGS precise orbit and clock error products, the ARAIM availability can be significantly improved on a global basis. For ground-based positioning, the receiver-related error term is the intractable one that should be adapted to different receivers and operating environments. Usually, an elevation-dependent function is used to characterize the error. With LSVCE via real data at a station, more accurate coefficients can be obtained, thus improving ARAIM availability at that station.In this paper, the authors have proposed refinements to the stochastic model for GNSS ground-based positioning and IM under the ARAIM framework. Refinements to satellite-related, atmosphere-related and receiver-related error terms are presented. Firstly, Gaussian bounds of IGS-precise orbit and clock errors for all GPS satellites are established and used to characterize the satellite-related error term. Secondly, a variable standard deviation is implemented to characterize the residual tropospheric delay after model correction. Thirdly, an elevation-dependent model with adaptive coefficients is used to characterize the receiver-related error term. The corresponding enhancements to ARAIM availability are discussed.These refinements are evaluated via global simulations and real data experiments. Different schemes are proposed and tested to investigate the enhancement of ARAIM availability for both aviation and ground-based positioning applications. Results show that ARAIM availability can be significantly improved when the satellite-related error term is refined with the use of IGS precise orbit and clock products. With LSVCE via real data at a station, coefficients of the elevation-dependent model can be adapted to different receivers and operating environments, so as to further improve the ARAIM availability at the station. In contrast, PL improvements from using a variable standard deviation to characterize the residual tropospheric delay are smaller, usually on the decimeter or centimeter level. Although these produce marginal improvements to ARAIM availability under current schemes, they would become significant if carrier phase observations are used.At the first stage, these refinements are designed and evaluated for the SPP mode with the use of GPS dual-frequency IF combination pseudorange observations. Contributions by these investigations to IM can be further extended when using advanced GNSS positioning modes.


The onset time of VAP, the occurrence of multidrug-resistant microorganisms AP, the length of invasive mechanical ventilation, and hospital mortality were similar in the patients who received and who did not receive SDD. The multivariate analysis adjusted for confounders showed that the use of SDD reduces the occurrence of VAP . Our pre-post observational study indicates that the use of SDD in a structured protocol for VAP prevention seems to reduce the occurrence of VAP without changes in the incidence of multidrug-resistant bacteria in COVID-19 patients.The aim of our study was to evaluate whether the introduction of SDD in a structured protocol for VAP prevention was effective in reducing the occurrence of ventilator-associated pneumonia (VAP) in COVID-19 patients without changes in the microbiological pattern of antibiotic resistance. This observational pre-post study included adult patients requiring invasive mechanical ventilation (IMV) for severe respiratory failure related to SARS-CoV-2 admitted in three COVID-19 intensive care units (ICUs) in an Italian hospital from 22 February 2020 to 8 March 2022. Selective digestive decontamination (SDD) was introduced from the end of April 2021 in the structured protocol for VAP prevention. The SDD consisted of a tobramycin sulfate, colistin sulfate, and amphotericin B suspension applied in the patient’s oropharynx and the stomach via a nasogastric tube. Three-hundred-and-forty-eight patients were included in the study. In the 86 patients (32.9%) who received SDD, the occurrence of VAP decreased by 7.7% ( The occurrence of bacterial pneumonia, mostly ventilator-associated pneumonia (VAP), has been reported as a frequent complication in critically ill COVID-19 with an incidence ranging between 40–60%, which is roughly three times larger than in non-COVID-19 patients ,3. This As experienced in many other centers, even in the three ICUs dedicated to the COVID-19 patients of our hospital, we observed a dramatic increase in the incidence of VAP, moving from 8–10% in non-COVID-19 mechanically ventilated patients in 2019 to 35–40% during the first six months of SARS-CoV2 pandemic. Unfortunately, although specific interventions for reinforcing compliance with the infection control rules and the interventions were included in the internal protocol for VAP prevention , the incThis observational pre-post study aimed to evaluate whether the introduction of SDD in a structured protocol for VAP prevention was effective in reducing the occurrence of VAP in COVID-19 patients without changes in the microbiological pattern of antibiotic resistance.In this observational study, we included all the adult patients requiring invasive mechanical ventilation (MV) for severe respiratory failure related to SARS-CoV-2 infection admitted to the three COVID-19 ICUs of the University Hospital of Modena from February 2020 to March 2022. Patients with an ICU length of stay (LOS) < 24 h and limitation of care or do not resuscitate orders were excluded from the study. The Institutional Ethics Committee of Area Vasta Emilia Nord (EC AVEN) approved the study . Due to the study’s observational nature, written informed consent was not required.2/FiO2 ratio < 150 mmHg for at least seven days of MV [All the patients received standard ICU supportive care and specific COVID-19 therapies according to WHO guidelines  and natiys of MV  and TociPatient demographics, Simplified Acute Physiology Score II (SAPS II), and standard laboratory test results, including the coagulation and inflammatory variables, were collected at ICU admission. In addition, therapy with steroids, tocilizumab , the occurrence of the first bacterial VAP, early onset VAP (EVAP), late-onset VAP (LVAP), the onset time from the start of invasive MV to VAP, the microorganisms causing VAP and their resistance pattern, CMV blood reactivation, and probable invasive pulmonary aspergillosis were collected during the ICU stay. The length of invasive MV and hospital stay and hospital mortality were also recorded. As for the ICU protocol before the pandemic, the patients were microbiologically screened at ICU admission and twice a week with the rectal swab and tracheal aspirate, serum Galactomannan, and quantitative cytomegalovirus DNAemia in the blood. Further microbiological examinations were performed if there was clinical suspicion of infection. According to international guidelines ,18, the p-value < 0.1 at unadjusted analysis to evaluate the independent association of SDD therapy with VAP occurrence censored at day 60. We also performed a secondary analysis by matching patients with and without SDD use (1:1) using a propensity score estimated by a multivariable logistic-regression model that included as covariates the risk factors to be treated with SDD; the nearest-neighbor method was applied to the propensity-score matching analysis.We used a Cox proportional hazards regression model, including variables with 2 tests were used as appropriate for comparing demographic and baseline values and outcomes in patients with and without SDD and VAP. All results were expressed as medians (range) for continuous variables and as frequencies (percentage) for categorical variables. All tests were two-tailed, with a p-value < 0.05 considered significant. SPSS version 22.0 package  was used to perform statistical analysis.Non-parametric and χ2/FiO2 values, and medical history of hypertension than patients who did not receive SDD. In addition, all these patients received steroids compared to around 90% of the patients in the no-SDD group  received SDD during their ICU stay. At ICU admission, the patients who received SDD were younger, with lower SAPS II scores, PaODD group . Bacterial VAP occurred in about 30% of patients with no substantial differences throughout the waves  with an p = 0.192) for VAP compared to those who did not receive SDD (p = 0.259). In the patients who received SDD, we observed a lower rate of Pseudomonas aeruginosa and Klebsiella spp. and a higher rate of Escherichia coli and Serratia marcescens compared to patients who did not receive SDD. The onset time of VAP, the occurrence of multidrug-resistant patterns in microorganisms causing VAP, CMV blood reactivation, and probable invasive pulmonary aspergillosis were similar between the two groups. Similarly, the length of invasive MV and hospital stay and hospital mortality did not differ between patients who received and who did not receive SDD  and adjusted analysis for confounders confirmed this association   . p = 0.133) without changes in antibiotic resistance pattern. This reduction was not associated with reducing invasive MV length and hospital mortality. The 82 pairs of patients matched by propensity score were well balanced for demographics, comorbidities, and characteristics at ICU admission  for the individual propensity to receive SDD showed that the use of SDD provided an 11% absolute risk reduction in VAP development  to 25% in patients (n =170) treated with SDD and systemic antibiotics [The role of SDD in preventing low respiratory tract infection during invasive MV has been extensively investigated over the last 15 years by more than 40 interventional trials enrolling more than ten-thousand patients ,21,22. Aibiotics ,13. The ibiotics ,13 on COibiotics ,24, we dibiotics  using a 2/FiO2 between the patients receiving and not receiving SDD may indicate non-protocolized changes in ICU admission criteria among the different COVID-19 surges. Second, the VAP incidence may be underestimated because, due to the difficulties in clinical diagnosis of secondary pneumonia in COVID-19 patients, only the microbiologically proven VAP has been considered. However, this could have generated minimal bias in comparing groups because the same method has been used in controls and patients with SDD. Third, the lack of systematic screening for MDR bacteria colonization limits the results observed on the effects of SDD use on the selection of MDR strains. Finally, our study showed an increased risk of VAP related to using tocilizumab but not steroids, as demonstrated by others [Compared with previous studies of SDD in COVID-19, the strength of our study is the evaluation of the net effect of adding SDD into a structured protocol for VAP prevention without the interference of other preventive interventions . However, the study has significant limitations. Firstly, the study design and the sample size limit the general applicability of the results observed. For instance, the difference in PaOy others ,6. HowevIn conclusion, according to other experiences, our pre-post observational study in COVID-19 patients suggests an association between the use of SDD in a structured protocol for VAP prevention and the reduction in VAP occurrence, especially late VAP, without any increase in the incidence of VAP sustained from multidrug-resistant bacteria. However, this decrease was not associated with any benefit in survival rate. Due to the study’s limitations, the results should be considered only as generating hypotheses for future trials.


SD = 13.62) derived from the German CORONA HEALTH APP Study to identify subgroups showing similarity of a comprehensive set of 50 risk and protective factors. Next, we investigated the course of quality of life (QoL) as an indicator of subjective well-being grouped by the identified latent classes from July 2020 to July 2021 based on monthly and pandemic phase averaged follow-up survey data by means of Linear Mixed-Effects Regression Modeling. We identified 4 latent classes with distinct indicators and QoL trajectories  similar to previous evidence on responses to stressful life events. About 2 out of 5 people showed a resilient  or recovering pattern  over time. Absence of depressive symptoms, distress, needs or unhealthy behaviors and presence of adaptive coping, openness, good family climate and positive social experience were indicative of a resilient response pattern during the COVID-19 pandemic. The presented results add knowledge on how to adapt and enhance preparedness to future pandemic situations or similar societal crises by promoting adaptive coping, positive thinking and solidary strategies or timely low-threshold support offers.Early investigations of subjective well-being responses to the COVID-19 pandemic indicated average deterioration but also high variability related to vulnerability of population groups and pandemic phase. Thus, we aimed to gain new insights into the characteristics of certain groups and their differences in subjective well-being response patterns over time. First, we performed Latent Class Analyses with baseline survey data of 2,137 adults (mean age = 40.98, The online version contains supplementary material available at 10.1007/s12144-022-03628-4. The ongoing COVID-19 pandemic represents a global crisis with consequences on the everyday lives and well-being of people from various ages, social and economic contexts . In the face of a stressful life event, vulnerabilities can increase the risk of health deterioration and psychopathology  and as compared to others facing a comparable level of adversity  tendency or style as well as a (situation-specific) dynamic process initiated by personally significant experience of harm or threat , problem-focused , meaning-focused  and support-focused  coping , chronic  or delayed  , for instance, after divorce or chronic illness , while others do not  and with some events raising the risk of permanent change  while others do not   and distinct indicators of such a pattern. This information is highly valuable for public health protection, promotion and preparedness in case of the current COVID-19 pandemic and future similar situations. With reference to previous investigations of response patterns in the face of diverse stressful life events . 55%  participated in the longitudinal part, with 2.3 times a month on average (SD = 1.30). The total number of answered questionnaires was n = 9,502 with a monthly average of n = 731 (SD = 291.71). Although the female to male ratio was relatively balanced, the sample was constituted of less old (60 years and older) and low educated (no school leaving certificate or primary education) participants. Table S1 in the Supplementary Materials presents more detailed sample characteristics for all variables under study.The original data base included 2,156 voluntary adult participants. Inspection of the plausibility of answers , careless responding  and extreme outliers  led to the exclusion of 19 participants and a final sample size of 2,137 adults with an age range from 18 to 84 years . As an indicator of situational coping strategy, we used the 28-item Brief-Cope Questionnaire . Stigmatization expectance and experience were assessed by 4 items adopted from the German version of the Inventory of Stigmatizing Experience . Scoring procedures and cut-offs were followed according to the instructions of respective manuals .As a standardized measure of psychopathological symptoms, we used the depression , general anxiety  and short panic module  of the Patient Health Questionnaire  or job constraints , a current COVID-19 infection  and COVID-19-related death of relatives, financial loss, home-office, relevant sociodemographic characteristics , self-reported lifetime diagnosis of mental disorder, current psychotherapy, health behavior , needs  and positive effects .The participant’s age group , sex , and educational level  were included as covariates in the analyses.Table S1 in the Supplementary Materials gives a detailed overview of the variables under study.Latent Class Analyses (LCA) was used to identify unobserved (latent) groups based on similarity of response patterns in observed (manifest) variables under the assumption of statistical independency  with the lmerTest package , followed by the recovering , delayed  and chronic class .In consideration of the four latent trajectories as depicted in Fig. 2008The resilient class is characterized by a low probability of depressive and panic symptoms or distress but moderate levels of anxiety symptoms and COVID-19-related worries. In addition, class members showed a high probability of good physical health and activity, family climate, conscientiousness and openness, meaning- and problem-focused coping, as well as positive experiences such as perceptions of social support and solidarity  to derive recommendations for better preparedness and universal prevention measures.SD = 0.74) vs. 4.08 (SD = 0.49)  vs. 30.88 (SD = 4.59) . By taking also into consideration that a considerable proportion of participants fell into the chronic class with comparatively low QoL and high psychopathological symptoms at the same time, highlight the need of both mental illness prevention and QoL promotion in line with the conceptualization of mental health as a In consideration of moderate anxiety and COVID-19-related worries even in the resilient class suggests that individuals of each of the four classes have to deal with certain risk factors but the resilient class differentiates from the others by showing maintenance of QoL despite comparable level of adversity, as suggested by resilience theory Rutter, . It is tThis study has some limitations that should be considered for interpreting the results. First, the data base was a convenience sample not allowing any generalization of findings to the German population. More precisely, the sample was unbalanced with regard to the educational level and age, comprising a greater amount of people with higher education and from young to middle adulthood. Therefore, the educational level and age were consistently included as covariates in the present analyses. Second, the data collection was undertaken by a smartphone app, thereby limiting the sample to participants who had access and were proficient with smartphones. Third, despite the longitudinal design and advantage of tracing QoL levels over time, this research lacks pre-pandemic QoL levels. Thus, conclusions are limited to the pandemic phase and do not allow continuous pre- to post comparisons. Although the data were collected during the COVID-19 pandemic, recall bias cannot be ruled out either. Furthermore, the interfaces for Android users and iOS users never look the same, which can generally create an information bias.The results highlight the central need of adaptive coping competency, positive social experience such as solidarity as well as low-threshold psychosocial support and prompt easily accessible recommendations on how to maintain well-being during a societal crisis such as the COVID-19 pandemic. Public health measures should be addressed particularly to people showing considerable QoL deterioration without returning to baseline levels (delayed and chronic response pattern) in both a preventive and promotive matter to enhance preparedness and resilience.Below is the link to the electronic supplementary material.Supplementary Material 1


The aims of this study is to assess by an updated meta-analysis the clinical outcomes related to permanent pacemaker implantation (PPI) after transcatheter aortic valve implantation (TAVI) at long-term (≥12 months) follow-up (LTF).P < 0.001] and rehospitalization for heart failure . In contrast, the risks of stroke and myocardial infarction were not affected. Among the 20 studies that reported procedural risk, the association between PPI and all-cause death risk at LTF was statistically significant only in studies enrolling patients with high STS-PROM score , although there was a similar tendency of the results in those at medium and low risk.A comprehensive literature research was performed on PubMed and EMBASE. The primary endpoint was all-cause death. Secondary endpoints were rehospitalization for heart failure, stroke, and myocardial infarction. A subgroup analysis was performed according to the Society of Thoracic Surgeon—Predicted Risk of Mortality (STS-PROM) score. This study is registered with PROSPERO (CRD42021243301). A total of 51 069 patients undergoing TAVI from 31 observational studies were included. The mean duration of follow-up was 22 months. At LTF, PPI post-TAVI was associated with a higher risk of all-cause death [risk ratio (RR) 1.18, 95% confidence interval (CI) 1.10–1.25; Patients necessitating PPI after TAVI have a higher long-term risk of all-cause death and rehospitalization for heart failure as compared to those who do not receive PPI.  What’s new?1 Over the years, TAVI gained the role of treatment of choice in inoperable patients and those at high or intermediate surgical risk.2 More recently, two randomized controlled clinical trials (RCTs) have supported the indication for TAVI even in patients at low surgical risk.4Since the first clinical report in 2002, transcatheter aortic valve implantation (TAVI) has emerged as a worthy, less-invasive, and safe alternative for the therapeutic management of patients with severe aortic stenosis (AS).Transcatheter aortic valve implantation (TAVI), compared with surgery, led to an increased need for post-operative permanent pacemaker implantation (PPI).In this meta-analysis including 51 069 patients across 31 observational studies, PPI post-TAVI was associated with an increased long-term risk of all-cause death and rehospitalization for heart failure.These results help to characterize the prognosis of patients undergoing TAVI.5 An injury to the atrioventricular conduction system during balloon valvuloplasty or prosthesis implantation and ischaemia of the conduction pathways can lead to advanced conduction disorders that often require permanent pacemaker implantation (PPI).6Among different complications that can occur after TAVI, the development of conduction abnormalities is extremely frequent.7The incidence of post-procedural PPI is higher after TAVI compared with surgical aortic valve replacement (SAVR); in particular, a recent RCT showed that PPI occurred in 33% of TAVI and 20% of SAVR patients at 5 years of follow-up.8 However, to date, the prognostic impact of PPI after TAVI is still debated; indeed, recent observational data have reported conflicting results.9–13 Furthermore, previous meta-analyses  have yielded jarring results.14–19The need for PPI in patients undergoing TAVI is known to be influenced by both clinical and technical aspects.On such bases, we performed the present systematic review and meta-analysis to evaluate the impact of PPI on long-term clinical outcomes of patients with AS undergoing TAVI.20 and was registered within the PROSPERO International Prospective Register of Systematic Reviews (CRD42021243301).This meta-analysis was carried out in accordance with the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelinesTable S1.A systematic and comprehensive literature research was performed on PubMed and EMBASE databases, from inception to October 2021, to identify studies that investigated the impact of PPI after TAVI on clinical outcomes. We used a combination of the following keywords and MeSH terms: TAVI, PPI, mortality. The full research strategy is listed in All records retrieved from the research were systematically screened in parallel and independently by two authors (A.Z. and G.P.), according to titles and abstracts; conflicts were resolved by collegial discussion.The following inclusion criteria were used: (i) studies reporting adverse events related to PPI after TAVI in native valves and (ii) studies reporting long-term clinical outcomes (follow-up ≥ 12 months).We excluded studies in which outcomes of interest were not clearly reported or were impossible to extract from the published results, studies that included patients with pacemaker before TAVI, conference abstracts, comments, editorials, case reports, systematic reviews, and meta-analysis.When two or more studies were reported from the same cohort of subjects, the most recent publication or the one with the longest follow-up was included in the analysis.21 and follow-up duration.Data extraction from the studies included was performed independently by two coauthors (A.Z. and G.P.) using a standardized worksheet. If available, the following items were collected: first author’s name, year of publication, study design, region, number of centres where the study was carried out, sample size, incidence of PPI, timing of PPI, baseline demographic and clinical characteristics of the population, valve type implanted, Society of Thoracic Surgeons—Predicted Risk of Mortality (STS-PROM) score,Particularly, the STS-PROM score is a validated risk prediction model based on ∼50 clinical pre-operative variables from the STS National Adult Cardiac Surgery Database such as age, race, cardiovascular risk factors, clinical presentation; it allows to calculate a patient’s risk of mortality for both the most commonly performed cardiac surgeries and TAVI.14Finally, the data necessary for the outcome analysis were also extracted; data at 1-year follow-up that were not directly available were retrieved from another meta-analysis that previously retrieved data from the corresponding author.22 producing a quality score (from 0 to 9) for each study included.Quality assessment of the studies was made independently by two coauthors (A.Z. and G.P.) using the standardized Newcastle–Ottawa Scale (NOS),The primary endpoint of the study was all-cause death at long-term (≥ 12 months) follow-up (LTF). The risk of all-cause death was calculated at 30 days and 1 year to assess the possible impact of follow-up duration.Secondary endpoints were rehospitalization for heart failure, stroke, and myocardial infarction at LTF and 1 year.Q test statistic and Higgins and Thompson I2. According to prespecified cutoffs, low heterogeneity was defined as an I2 <25%, moderate heterogeneity as an I2 between 25% and 75%, and high heterogeneity as an I2 >75%. We visually inspected funnel plots for asymmetry and used Egger’s regression asymmetry test to assess the potential effect of publication bias. Furthermore, we performed a subgroup analysis stratifying studies according to the mortality risk of patients predicted by the STS-PROM score 23 to evaluate whether the impact of PPI after TAVI on all-cause death at LTF was influenced by this variable.Categorical dichotomous data were summarized across treatment arms, compared, and reported as crude risk ratio (RR) with the corresponding 95% confidence interval (CI). As primary analysis, we used DerSimonian and Laird random-effects model. As secondary analyses, we also reported effects estimates as crude odds ratio (OR) with the corresponding 95% CI and computed Mantel–Haenszel fixed-effects model. We evaluated heterogeneity of effects using the Cochran Sensitivity analyses were performed by comparing the results of the primary and secondary analyses. In order to investigate potential sources of heterogeneity for the LTF outcomes, we performed several univariable random-effects meta-regression analyses with the DerSimonian and Laird method according to age, sex category, atrial fibrillation, diabetes mellitus, coronary artery disease (CAD), left ventricular ejection fraction (LVEF), number of self-expanding and balloon-expanding valves implanted, NOS, and duration of follow-up. Secondary and subgroup analyses were not prespecified. Descriptive characteristics were presented as mean ± standard deviation or median (inter-quartile range) for continuous variables and as frequencies and percentages for categorical variables. Statistical analysis was performed using Stata 17 (StataCorp).Table S2), with 51 069 patients undergoing TAVI included in the analysis. The mean follow-up duration was of 22 months (range 12–60 months).The initial search retrieved 2066 records (616 from PubMed and 1450 from EMBASE). 2003 records were excluded because of different study design or topic of interest after the evaluation of titles and abstracts. Then, other 63 records were subsequently excluded after full-text assessment. Finally, 31 records were selected . The heterogeneity between the studies was moderate (I2 = 25.79%) and there was a potential publication bias detected by the Egger regression and funnel plot inspection .Among 51 069 patients undergoing TAVI, the risk of all-cause death at LTF was higher for patients who experienced PPI , but not in those enrolling patients at intermediate  or low risk . It is worth noting, however, that the tendency of the results was similar in all three groups without a significant heterogeneity .In the subgroup analysis performed in the 20 studies reporting the mortality risk of patients predicted by the STS-PROM score, the association between PPI and all-cause death risk at LTF was significant only in studies enrolling patients with high STS-PROM score . There was low heterogeneity between studies (I2 = 8.37%) and a potential publication bias . Conversely, the risk of all-cause death at 30 days, pooled from 40 806 patients, was not different between patients with PPI and without it . The heterogeneity across the studies was low (I2 = 0.00%) and no potential publication bias was detected .In a pooled analysis of 45 270 patients, those with PPI post-TAVI experienced an increased risk of all-cause death at 1 year . The heterogeneity across the studies was moderate (I2 = 40.87%) and no significant asymmetry was detected .The pooled results among 18 095 patients demonstrated that PPI was associated with rehospitalization for heart failure at LTF  among 14 867 patients; the heterogeneity was moderate (I2 = 42.48%), no potential publication bias was disclosed .The same results were detected at 1 year  and myocardial infarction  was observed between patients who required PPI and controls. The heterogeneity between studies was low  and there was not significant publication bias .At 1 year, no difference in risk of stroke .Sensitivity analyses performed comparing primary and secondary analyses obtained similar results ; moreover, this is the first article performing a subgroup analysis according to the preoperative procedural risk.50–52 Furthermore, it might also explain the increased risk of rehospitalization for heart failure and the absence of an impact of PPI on short-term mortality (at 30 days). In this regard, Nadeem et al.42 documented that patients with right ventricular pacing >40% had a higher risk of heart failure compared with those who experienced a lower right ventricular pacing burden.The ventricular dyssynchrony related to the right ventricular pacing could play an important role in increasing the risk of all-cause death among patients with PPI.Unfortunately, the few data and the variable pacing percentage cut-offs adopted in the various studies did not allow to perform a pooled analysis to evaluate the influence of the aforementioned variable on clinical outcomes. By this logic, different types of ventricular pacing (such as cardiac resynchronization therapy or His pacing) or proper device programming, could have a beneficial impact on the prognosis of patients undergoing post-procedural PPI.14Furthermore, higher mortality observed in patients who underwent PPI after TAVI may be related to different causes, both cardiac and non-cardiac, so that PPI could represent only a simple bystander. For instance, worse outcomes related to PPI could also be explained by the mechanical or ischaemic injury to the conduction system that can occur during TAVI. Indeed, new-onset persistent left bundle branch block was found to be associated with an increased risk of all-cause death and rehospitalization for heart failure.Interestingly, the significantly higher risk of all-cause death at LTF associated with PPI was confined to studies enrolling patients at high preoperative risk of mortality , while it was of borderline significance in those enrolling patients at medium or low risk. These findings are probably affected by the greater multimorbidity burden of high-risk patients undergoing TAVI and, therefore, by the relatively short follow-up available; indeed, among patients with a lower multimorbidity burden, a longer follow-up would be needed to establish the association between PPI and long-term mortality. On the other hand, the benefit of TAVI over SAVR regarding procedural risks is probably smaller in the group with STS-PROM score < 8% and so, in these patients, the disadvantage related to the long-term impact of PPI may be larger. Probably, with the extension of the indications for TAVI also in low-risk patients, the recruitment of patients with a lower average age will help to highlight this issue. However, it should be emphasized that the STS-PROM score may not intercept all comorbidities that could impact long-term mortality and this may limit the interpretation of these results.53 in our study PPI was not associated with a higher risk of stroke at 1-year follow-up. This may be caused by the relatively short follow-up of the studies included and the presence of confounding factors  that were not adjusted during the analysis.Although right ventricular pacing is associated with an increased risk of atrial fibrillation,54 Other factors were found to predict a high percentage of long-term pacing in patients who experienced post-TAVI PPI such as high left ventricular outflow tract diameter ratio, high aortic annulus diameter ratio, new onset of left bundle branch block, time to PPI >2 days, and therapy with beta-blockers.55 Consequently, the choice of intervention modality in patients with AS should take into account the factors mentioned above.Recently, several studies have documented the presence of electrical, anatomical, and procedural predictors of PPI after TAVI such as age, pre-existing conduction abnormalities, calcification of the left ventricular outflow tract, the use of self-expanding valve type, balloon valvuloplasty, and valve implantation depth.56 In addition, other specific changes to the TAVI implementation techniques have been proposed.58 Findings from other ongoing trials are needed to strengthen this evidence.In light of the results of this meta-analysis, strategies aimed to reduce the incidence of PPI might have an impact on the long-term outcomes of patients undergoing TAVI. Recently, higher valve implantation showed a reduction in conduction abnormalities and permanent pacemaker requirement, without compromising procedural safety or valve haemodynamic.Our meta-analysis has some limitations. Since systematic reviews and meta-analyses rely on the quality of included studies, we could only use observational studies, many of them with retrospective follow-up. Besides, the lack of pacing frequency data did not allow us to judge the influence of this variable on outcomes. Also, the lack of single patient-level data regarding the mortality outcome has foreclosed subgroup analyses and the possibility of establishing whether the need for PPI is an independent predictor of worse outcomes. Further, indications for PPI were different in the various studies limiting results reproducibility. Finally, over the period time of the present meta-analysis, there have been some important changes and evolution in the design and technique of TAVI procedure.Patients who underwent PPI after TAVI had an increased risk of all-cause death and rehospitalization for heart failure 1 year after the implantation and at the long-term follow-up. On the other hand, PPI did not modify the risk of all-cause death after 30 days, stroke, and myocardial infarction.Europace online.euac008_Supplementary_DataClick here for additional data file.


Long COVID is defined as symptoms and signs related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that are present at least four weeks following acute infection. These symptoms and signs are poorly characterised but may be associated with significant morbidity. We sought to synthesise the evidence on their incidence to guide future research, policy and practice.We searched Medline and Embase for longitudinal cohort studies from January 2020 to July 2021 that investigated adults with long COVID at least four weeks after acute infection. Risk of bias was assessed using the Joanna Briggs Institute checklist for cohort studies. Random-effects meta-analyses were performed with subgroup analysis by follow-up time (4-12 vs more than 12 weeks).19 studies were included, 13 of which included patients hospitalised with COVID-19. The total sample size was 10 643 and the follow-up time ranged from 30 to 340 days. Risk of bias was assessed as high in one study, moderate in two studies and low in the remaining 16 studies. The most common symptoms and signs seen at any time point in long COVID were fatigue  = 23-55), dyspnoea , olfactory dysfunction , myalgia , cough  and gustatory dysfunction . High heterogeneity was seen for all meta-analyses and the presence of some funnel plot asymmetry may indicate reporting bias. No effect of follow-up time was found for any symptom or sign included in the subgroup analysis.We have summarised evidence from longitudinal cohort studies on the most common symptoms and signs associated with long COVID. High heterogeneity seen in the meta-analysis means pooled incidence estimates should be interpreted with caution. This heterogeneity may be attributable to studies including patients from different health care settings and countries. Long COVID is defined as symptoms and signs related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that are present at least four weeks following acute infection . It can SARS-CoV-2 began to circulate in December 2019, was declared a pandemic in March 2020 , and hasWe wanted to identify the incidence of symptoms and signs of long COVID and to investigate if they differed in patients with ongoing symptomatic COVID-19 and post-COVID-19 syndrome. This review differs from others -8 as it A protocol was developed prior to conducting the review based on preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) guidelines   and guided by the PRISMA flow diagram. Potential eligibility was initially assessed based on the title and abstract. Full-text articles were screened to confirm which studies met the inclusion criteria. An additional reviewer (EV) provided guidance when eligibility was unclear and assessed all the included studies to ensure eligibility.Data were extracted from each study by a single reviewer (QH), using a data extraction form designed for this review  assessed the risk of bias in each study using the Joanna Briggs Institute checklist for cohort studies . This liI2 statistics, with values of 25%, 50%, and 75% representing low, moderate, and high heterogeneity, respectively. Due to differing study populations and the heterogeneity found, random-effects meta-analyses were undertaken. Subgroup analysis was carried out by follow-up time: 4-12 vs >12 weeks. Funnel plots were produced by Egger’s method, with the logit transformed proportion against standard error. Binary outcomes were presented as percentages of patients, while continuous outcomes were presented as mean or median throughout.Meta-analyses were performed using the meta package in RStudio (V.1.3.959). Pooled incidence and 95% confidence intervals (CI) were calculated for symptoms and signs reported in at least five studies. The rationale for this was to focus on the most important symptoms and signs rather than rarely reported, potentially incidental findings highlighted in similar reviews -8. The r2384 studies were identified during the initial database search and 2213 unique records remained after deduplication. The title and abstract of each study were screened for eligibility, followed by the full text if the study passed the initial eligibility assessment. 19 of the 66 studies met the inclusion criteria and 16 were included in the meta-analysis. The remaining three studies were excluded from the meta-analysis as their data were presented graphically, without accompanying raw data. One study was assessed as having high risk of bias, two as having moderate risk of bias, and 16 as having low risk of bias. The reasoning for these assessments is summarised in Table S2 in the Forest plots for each symptom reported by at least five studies are presented in Figure S1 in the This review found that the most common symptoms and signs of long COVID were fatigue (37%), dyspnoea (21%), olfactory dysfunction (17%), myalgia (12%), cough (11%), and gustatory dysfunction (11%). Pooled incidence estimates did not differ between ongoing symptomatic COVID-19 and post-COVID-19 syndrome.This review followed PRISMA guidelines, ensuring rigorous methods. However, most stages were carried out by a single reviewer, increasing the risk of inappropriate screening  or improWe appraised the included studies using a well-validated tool and found they generally had low risk of bias. However, confounding by severity may be present due to patient recruitment during hospital admission or attendance in outpatient departments and may lead to overestimation in our pooled incidence data. For example, all patients in three studies ,22,31 haOur findings correspond with those of similar reviews, such as Martimbianco et al. , MicheleIdentification of the most common long COVID symptoms may influence future research and policy. These symptoms could benefit the most from research to understand their pathogeneses and trial treatments. They may also benefit from an increased focus on long COVID clinical pathways, such as increased education of health care workers in long COVID clinics. Furthermore, the identification of limitations in the studies included in this review, such as confounding by severity and misclassification bias, may guide the methodology of future research.This rapid review identified the most common symptoms and signs of long COVID: fatigue, dyspnoea, olfactory dysfunction, myalgia, and cough. The included studies were found to be at an overall low risk of bias, but a high level of heterogeneity arose in the meta-analyses. This may indicate an effect of different study populations on the results. Further primary research is required to confirm the characteristics of long COVID, understand its pathogeneses, and propose treatments.


The pigments and volatiles metabolites in plants fulfill the function of helping with pollination and spreading seeds  Application of omics technologies in the study of biosynthesis and regulation of pigments.b) The correlation between pigments, volatile or other compounds.via the MEP pathway in plants. Most of the genes in the carotenoid biosynthetic pathway have been identified in plants . The SNP deletion of BrWF3 in the white petals of Chinese cabbage caused the protein to non-function. Therefore, the authors deduced that the lost function of BrWF3 results in the failure combination of carotenoid and polar lipids in the white petals of Chinese cabbage.A candidate gene Lycoris flowers' color. Wang N. et al. identified a hub gene LrDFR1 through comparative transcriptome analysis, which possibly plays an important role in the anthocyanin accumulation in the Lycoris flower. Their experiment results suggested that LrDFR1 acts as a positive regulator in anthocyanin biosynthesis. Fu et al. carried out integrated transcriptomics and metabolomics analysis in five C. japonica cultivars with different color petals and they identified CjANS and Cj4CL as key contributors to the diversity of petal color of C. japonica. Except for structural genes, the transcription factors, such as MYB, bHLH, WD, and MADS-box, play important roles in the regulation of anthocyanin biosynthesis  by analysis of transcriptomes, and they identified VbMYBA as the transcriptional activator responsible for anthocyanin accumulation. In addition, they found that VbMYBA could activate strong anthocyanin accumulation in tobacco leaves. Li et al. gave a new sight of anthocyanin biosynthesis in peanuts by interaction joint analysis of multi-omics and miRNA. They suggested that HCT and chalcone biosynthesis-related candidate genes  were the target genes of AhmiR2950, AhmiR398, AhmiR50, and AhmiR51.The anthocyanin biosynthesis pathway has been reported since 1980  and Nicotiana rustica L. (orange) species using UPLC-ESI-MS/MS. A batch of novel metabolic biomarkers including flavonoids  and carotenoids (lutein and β-carotene) for these species were identified.Zheng et al. summarized the underlying mechanism of regulation, metabolism, and genetics of apocarotenoid diversity, particularly focusing on apocarotenoid pigments and volatiles. In addition, they proposed a strategy that combines chromatography-mass spectrometry apocarotenoid profiling with multi-omics  to find new QTLs for apocarotenoid metabolite traits and identify their underlying genes.Carotenoids could be oxidized by enzymatic activities  or non-enzymatically to generate apocarotenoids in plants, including crocins and bixin, which contribute to pigment development, and β-ionone, α-ionone, β-cyclocitral, β-damascenone, 6-methyl-5-hepten-2-one, and safranal, among others, that contribute to fragrance. The review of Bixa orellana seeds. The bixin metabolic pathway was proposed as early as 20 years ago by Bouvier et al.  and in vitro approach. They analyzed the generated products by LC-ESI-QTOF-MS/MS.Bixin is the second most economically important natural apocarotenoid. Bixin has an orange-red color and is produced mainly from r et al. , but it Xi et al. compared the carotenoids and aroma volatile apocarotenoids profiles of fruits of three different colored apricot cultivars. They found the total carotenoid contents were negatively correlated with the transcripts of CCD1 and CCD4 genes, while the aroma volatile apocarotenoid contents (mainly β-ionone) were positively regulated. These results suggested that CCD1 and CCD4 may be the key regulatory points for the profiles of color and aroma in apricot fruits. Therefore, these two genes can potentially be used as the targets for molecular breeding.Yan et al. performed a comprehensive analysis of the MYB-related transcription factor superfamily in sweet osmanthus and provided novel insights into the roles of OfMYB-related genes in sweet osmanthus as regulators of volatile compounds. They found that OfMYB1R114 and OfMYB1R70 members accelerated β-ionone formation. While OfMYB1R201 was involved in decreasing the β-ionone content. The mechanism of how these candidate MYB-related genes involved in the regulation of aroma substances remains to be further studied.β-ionone is also a significant contributor to the fragrance of sweet osmanthus flowers and is mainly determined by the CCD4 enzyme  under UV-B irradiation. They deduced that the increased β-carotene and the decreased volatiles β-ionone were partially caused by the inhibition of PpCCD4 expression level under the UV-B irradiation. These results suggested that some stress factors could affect the carotenoid metabolism and then influence or change the volatile patterns.The metabolism of carotenoids has been studied intensively for decades, while the interaction mechanism between carotenoids and norisoprenoids (β-ionone) under abiotic stress remained unclear in many plants. via the shikimate pathway. However, studies on the underlying mechanism of the relationship between anthocyanins and phenylalanine-derived volatiles are few. Mei, Wan et al. reported a specific tea (Camellia sinensis) variety with purple flowers, which accumulate a high concentration of anthocyanins. Meanwhile, tea flowers contain special volatile benzenoid-phenylpropanoids (BPs), such as 1-phenylethanol (1-PE) and acetophenone (AP). What would happen to the volatile compounds when the flower color mutates naturally from white color to purple color? According to the results, they found the flux to the benzenoid-phenylpropanoids (BPs) was also enhanced along with the anthocyanins accumulation in the flower of the tea plant.Anthocyanins and a variety of aroma compounds  are derived from phenylalanine Huang et al. identified monoterpenes as the main scent components in Phalaenopsis bellina flower, and they found that TPS-b and TPS-e/f enzymes are involved in the monoterpene biosynthesis in the P. bellina floral scent. Interestingly, the P. bellina flower accumulates anthocyanins, but the main aroma released is not phenylalanine-derived volatiles; while this flower could release terpenoid aroma from the MEP pathway, but could not accumulate carotenoids. Therefore, the regulation of different derived volatile compounds is very complex in plants. Ke et al. identified HcMYB1 could activate the structural gene HcBSMT2 involved in methyl benzoate biosynthesis, and HcMYB2 can also activate the structural gene HcTPS5 involved in linalool biosynthesis in H. coronarium flowers. These findings have shed light on the regulation of volatile compounds in plants.In addition to the volatiles generated from the degradation of certain metabolites in plants, such as carotenoids or phenylalanine-derived compounds, volatiles contributing to the aroma of plants are as well directly synthesized, as the case of monoterpenes , which are derived mainly through the MEP pathway. Mei, Lin et al. compared metabolites in fresh and fermented tea (Camellia sinensis) leaves between “Yinghong 9” (green leaves) and “Huangyu” (mutant yellow leaves) cultivars by using targeted metabolomics. Apart from the significant difference in pigments between these two cultivars, they also found alterations in polyphenols and volatiles. Proanthocyanidins are the main pigment substances in brown cotton, and studies have shown that fiber color is negatively correlated with fiber yield and quality. But the underlying mechanism between proanthocyanidins biosynthesis and metabolism in cotton fiber is unclear. Wang Z. et al. investigated the key structure and regulatory genes in the proanthocyanidins biosynthesis of brown cotton by combing with transcriptome co-expression network and metabolome analysis, and thus established the transcriptional regulatory network of proanthocyanidins biosynthesis and flavonoid metabolism in cotton.The changes in plant color could affect not only volatiles but also other metabolism compounds. Taken together, the Frontiers Research Topic presented here documents recent advances in pigments and volatiles biology research. In the present volume, the authors use advanced omics technologies to elucidate the biosynthesis and regulation of pigments and volatile and address the interactions between pigments and their related secondary compounds in plants. These results would give insight into the interaction between pigments and volatile and inspire further advances in the study of plant metabolites interaction.All authors contributed equally to the manuscript and approved it for publication.This work was supported by the project from the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 31902074), the Youth Innovation Promotion Association of Chinese Academy of Sciences (2022351), and the CAS Scholarship. RR-M work was supported by the Consejo Nacional de Ciencia y Tecnología (CONACYT) (Fronteras de la Ciencia No. 2016-01-1716).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Understanding the effects of the COVID-19 pandemic on cause-specific mortality should be a priority, as this metric allows for a detailed analysis of the true burden of the pandemic. The aim of this systematic literature review is to estimate the impact of the pandemic on different causes of death, providing a quantitative and qualitative analysis of the phenomenon.We searched MEDLINE, Scopus, and ProQuest for studies that reported cause-specific mortality during the COVID-19 pandemic, extracting relevant data.n = 16), followed by cancer (n = 14) and diabetes (n = 11). We reported heterogeneous patterns of cause-specific mortality, except for suicide and road accident.A total of 2413 articles were retrieved, and after screening 22 were selected for data extraction. Cause-specific mortality results were reported using different units of measurement. The most frequently analyzed cause of death was cardiovascular diseases (Evidence on non-COVID-19 cause-specific deaths is not exhaustive. Reliable scientific evidence is needed by policymakers to make the best decisions in an unprecedented and extremely uncertain historical period. We advocate for the urgent need to find an international consensus to define reliable methodological approaches to establish the true burden of the COVID-19 pandemic on non-COVID-19 mortality.The online version contains supplementary material available at 10.1007/s10389-022-01755-7. During the SARS-CoV-2 pandemic, a surge in overall deaths has been recorded in many countries, most of them probably attributable to COVID-19  approach .We used the following search string for MEDLINE:2020/01/01:2022/07/31[Date - Publication] AND (("excess"[All Fields] OR "excesses"[All Fields] OR "excessive"[All Fields] OR "excessively"[All Fields]) AND  AND ("sars cov 2"[MeSH Terms] OR "sars cov 2"[All Fields] OR "covid"[All Fields] OR "covid 19"[MeSH Terms] OR "covid 19"[All Fields]) AND )).We used the following search string for Scopus:( excess* ) AND  OR ( deaths ) ) AND ( covid-19 ) AND ( cause AND specific )We used the following search terms for ProQuest:“ AND (COVID-19) AND ” , limiting the search to peer-reviewed articles in academic journals.We adopted the following inclusion criteria: (i) original article, (ii) assessment of at least one cause-specific mortality during the pandemic period, (iii) assessed causes of deaths using the 10th revision of the International Classification of Diseases (ICD-10), (iv) reporting of at least one of the following outcomes: cause-specific mortality estimates or cause-specific excess mortality, and (v) full-length articles. We excluded articles based on the following criteria: (i) preprints of articles, (ii) reviews, and (iii) non-English-language articles.Two independent investigators  evaluated each record to determine eligibility. All disagreements were discussed with an independent arbiter (FS) to reach consensus. The investigators  independently extracted the data. Disagreements were discussed with FS. Relevant data extracted from each article were: publication year, data stratification, territory, country income level  developed by Wells and colleagues  are classified as upper-middle-income by the World Bank classification system, while the others are classified as high-income . The studies included in our review have study settings with heterogeneous granularity. For instance, studies investigate mortality at a city level       , and seven (32%) of the included articles showed a good quality (score = 8). None of the included studies showed high risk of bias.According to the Newcastle–Ottawa Quality Assessment Scale  and above all that the data used originated from national or supranational mortality registries characterized by controls and sufficient data security, the studies’ quality was high (between fair and good). The only substantial difference in the quality of the studies is related to the use of standardized mortality and the choice of controls for the implementation of the statistical models. This highlights how, despite the heterogeneity of the data sources and of the coding of the causes of death, the level of scientific evidence is high.It should be noted that we could neither perform meta-analyses nor direct comparisons between studies due to the heterogeneity of methodologies and approaches. Specifically, authors investigated different time periods, adopted different methodologies for estimating excess mortality, different coding, and classification of causes of death, and, most importantly, they did not always standardize their results and adopted different approaches in the stratification of the results. Furthermore, despite the large body of literature on all-cause mortality, we found a relatively small number of studies focusing on specific causes of death.Most of the studies included in this review reported excess all-cause mortality in the respective study periods, apart from Li et al.  KontopanOverall, there is still an important knowledge gap on cause-specific mortality patterns during the COVID-19 pandemic. In fact, most of the included studies investigated the causes of deaths that determine the greatest burden of disease in high-income countries . For instance, in the six Brazilian capitals analyzed by Brant et al. , the impAlthough mortality patterns for cardiovascular diseases were very heterogeneous, for chronic diseases — such as oncological diseases — this aspect was even more marked. All the articles included in the review reported different results and addressed different aspects. For instance, opposite results were reported by Kontopantelis et al.  on the oWhen investigating mortality from road accidents, we discovered more homogeneous evidence. Most of the included studies  for specific macro-categories of death causes.Reliable scientific evidence is needed by policymakers to make the best decisions in an unprecedented and extremely uncertain historical period, and this is true for the income level of all countries. We advocate for the urgent need to find an international consensus to define uniform conceptual and methodological approaches to establish the true burden of the COVID-19 pandemic on non-COVID-19 mortality.ESM 1(DOCX 186 kb)


This study investigates the asymmetric interdependence between geopolitical risk (GPR) and the stock markets of the top-seven emerging (E7) countries  in the ongoing geopolitical conflict between Russia and Ukraine. With daily datasets covering the period 01-Feb-2022 to 25-July-2022, the squared wavelet coherence (SWC) and wavelet coherence phase difference (WCPD) techniques are employed. The results underscore heterogeneous and asymmetric market-specific coherence and lead-lag patterns regarding E7 stocks' interdependence with geopolitical risk. The findings imply high comovements between Black Swan events like the Russian-Ukrainian conflict and financial markets' volatility, highlighting the essence of alternative assets or asset classes for hedging geopolitical risks in the ongoing military actions. The heterogeneous and asymmetric responses offered by E7 stocks against GPR render emerging markets equities suitable for diversification and downside hedging strategies against GPR-induced shocks. The findings are robust to the time-varying parameter vector autoregression (TVP-VAR) connectedness approach. The results’ implications for portfolio managers, investors, and policymakers are discussed. EMEs yield high risk-adjusted returns on average and have evolving connections with equities from developed markets, making them desirable surrogates for constructing diversified portfolios ,2.Financial markets occasionally experience crises  whether geopolitical risk drives emerging markets’ equities; (ii) whether all EMEs offer equal responses to geopolitical risk; and (iii) whether the relationship between geopolitical risk and EMEs differ across time and frequencies.For these aims, the study focuses on the top-seven emerging markets , which are most vulnerable to market shocks . It is wThe study's contribution to the body of knowledge is threefold. First, based on the existing knowledge, this is the first study to examine the risk reduction role of emerging markets against shocks from geopolitical risk in the Russian-Ukrainian conflict era. Second, unlike the existing works (as highlighted in the literature review) that primarily focus on the time domain, this study takes on analysis across both time and frequency spectrums. The need for time-frequency analysis is justified as follows. In the spirit of the fractal market hypothesis, as espoused by Peters , market Third, in terms of methods, robust and advanced econometric approaches, the squared wavelet coherence (SWC) and the wavelet coherence phase difference (WCPD) under the bi-wavelet framework are employed. The SWC and WCPD allow the assessment of the degree of coherence and the lead-lag dynamics between bi-variate time series across calendar time and frequency domains, which other approaches lack. Providing time-frequency evidence of the impact of geopolitical risk on assets is particularly important in Black Swan period for which the era of the Russian-Ukrainian military conflict is no exception. Time-frequency evidence is necessary to inform the timely rebalancing of portfolios across time and trading horizons. In the context of this study, the use of the time-frequency analysis also helps to ascertain whether or not stock market dynamics are driven by geopolitical risk. Such knowledge is instrumental for the effective regulation of markets in periods of elevated geopolitical risk. Note that when other econometric techniques, such as spillover connectedness  and This study underscores medium-to-high time-frequency coherence between stock returns from E7 countries and the Russian-Ukrainian conflict-induced geopolitical risk (GPR) shocks. The study documents predominantly high comovements between GPR and E7 stocks, implying that there exists high coherence between Black Swan events like the Russian-Ukrainian conflict and financial markets’ volatility. Among the E7 markets, Russian stocks seem to have been more susceptible to GPR, mainly in the early weeks across the weekly to the monthly frequency band only whereas Turkish stocks possess high diversification potential.The rest of the study is outlined as follows. Section 2 reviews related literature; Section 3 presents the data and methodology; Section 4 discusses the findings; Section 5 ascertains the robustness of the findings, and Section 5 concludes the study.2The academic attention towards examining the extreme financial effects of Black Swan events has risen in recent periods because of the COVID-19 pandemic crisis, where various financial markets’ reactions and overall economic recovery have been investigated widely . HoweveThe first strand covers earlier works that use terror and wars to proxy geopolitical risk. Among them, Frey and Kucher ,27 documThe second strand of works commenced when Caldara and Iacoviello  developeThe discussions on GPR's impact on various assets have been rekindled in the era of the Russian-Ukrainian conflict, occasioning the third strand of works. Thus, this strand of literature assesses the impact of the geopolitical shocks occasioned by the Russian-Ukrainian military actions on financial markets. This has seen discussions on currencies , asset tFrom the third strand of works, which is still an emerging strand, three major issues are worth noting. First, the focus of these studies has largely been on global or developed markets. This study extends this emerging literature by focusing specifically on emerging markets equities to examine their potential to hedge against the geopolitical shocks brought about by Russia's evasion of Ukraine. Second, notable assessments of GPR's impact on stock markets by Yousaf et al.  and Sun Third, between GPR and EMEs, the lead-lag dynamics, which are relevant to assessing the driver and responder of market shocks across the spectrums of time and frequencies (trading horizons), are unknown in the era of the Russian-Ukrainian geopolitical conflict. This Black Swan event stands the chance of causing changes to the dynamics of price, returns, and volatility in equity markets. As a result, the need for a timely rebalancing of portfolios, which is key in crisis periods, is strongly motivated and warrants that empirical assessments focus on how EMEs may behave across time and frequency scales.Therefore, in the persistence of the military conflict between Russia and Ukraine, this study extends the literature by testing the ability of EMEs to hedge against geopolitical risk. Findings from this study should influence portfolio rebalancing and effective market regulation on the part of investors and policymakers or regulators, respectively. This study fills the existing gap by employing the wavelet coherence analysis to provide evidence of the lead-lag dynamics between geopolitical risk (GPR) and EMEs across the time-frequency space. The analysis in this study would help to also ascertain whether EMEs offer an equal response to GPR and whether the relationship between GPR and EMEs differs across time and trading horizons.33.1This study investigates the time-frequency-varying comovements between geopolitical risk (GPR) and the stock markets of the top-seven emerging (E7) countries. The daily GPR index developed by Caldara and Iacoviello  is emploThe descriptive summary indicates that all E7 stock markets recorded negative returns on average, with Russia recording the most negative. Except for Mexico, all E7 market returns were negatively skewed over the sample period GPR peaked at 539.58 but had a minimum of 30.21. The trajectories of the return series for each of the E7 markets are suggestive of the volatile nature of EMEs across the sample period.3.2This study makes use of the squared wavelet coherence (SWC) and wavelet coherence phase difference (WCPD) techniques, which are under the bi-wavelet paradigm. The methodological steps used by the study under the bi-wavelet approach are consistent with the basic steps of Torrence and Compo  and TorrIn generating the CWT of two distinct time series, say nd Compo  to generThe CWT permits a differentiation of the portions across time and frequencies, embodied by the coherence between The SWC, which explains the comovements between  Webster  in equatTo gain further insights into the lead-lad dynamics and the coherence patterns between negative .The WCPD can be expressed in equation A set of two data arrays with a null phase difference is an example of a perfectly co-moving time series. A standard visual representation of the data based on heat map panels is adopted to represent both SWC and WCPD. In the SWC heat maps, deep arrows reflect phase connections between any named two series (GPR and any of E7 equities).The data arrays act in either in-phase (positive correlation) or anti-phase (negative correlation) mode, portrayed by the left- and right-oriented arrows, respectively. Arrows pointing upward or downward signify that 4This section presents the empirical results from the SWC and WCPD-based lead-lag relationships between GPR and each of the E7 stock markets. The patterns of comovement from which the lead-lag dynamics could be inferred are presented in scalograms. All horizontal axes display the time and the vertical axes denote the frequency, measured in days. The colour map accompanying each scalogram represents a key for defining the degree of comovement. Hotter (warmer) colours, shown by red and yellow (blue and green), show high (low) coherence between the pair. Graphically, → and ← oriented arrows suggest in-phase and out-phase coherence, respectively. Right and up (↗) or left and down (↙) arrows evidence a leading role for the first variable (GPR). Right and down (↘) or left and up (↖) arrows indicate a leading role for the second variable (the named E7 stock). Emphasis is laid on the phase difference relationships that fall within the cone of influence (COI), which depicts the significant comovement dynamics between the analysed pairs. The COI shows on the scalogram as the faded area. That is, the lead-lag dynamics in (outside) the clear regions are significant (non-significant).4.1At high frequencies (2–4 daily periodicities) towards the end (beginning) of April (May), GPR led Brazilian stocks, which is consistent with what was observed from the onset of the conflict. After 2 months into the conflict, Brazilian stocks were now negatively driving GPR, particularly towards the end of June. The lead-lag dynamics across the weekly and fortnightly (8–16) frequency bands across the period were characterised by high coherence, as depicted by red and green colours from the WCPD plot see -panel B,4.2Towards the end of May (around 5 daily cycles) and June (around 2–3 daily cycles), the scalogram shows left-oriented arrows, suggesting a negative comovement between GPR shocks and stock returns from China and highlighting potential diversification with Chinese stocks. This observation is confirmed by the white contours coloured in blue and turquoise in May and June, respectively see -panel B.4.3It is worth noting that Indian stocks signalled some diversification potentials across 4–6 and 12–24 daily cycles in late (early) March (April). This lends support to the fact that equities from emerging markets tend to yield high risk-adjusted returns on average and have evolving connections with equities from developed markets, rendering them attractive surrogates for diversifying portfolios [4.4The mix of interspersed positioning arrows across 8–12 daily periodicities between mid-March and the beginning of June reveal negative comovements, as confirmed by the blue-coloured contours from the WCPD plot see -panel B,4.5It is worth noting that there existed potential diversification benefits with the left-down-oriented positioning arrow found at the 4-daily frequency band in February. However, given the strength of this Black Swan period, this diversification potential was overturned at all frequency bands in the remaining periods until mid-June and early July, particularly around 14–21 daily (3-weekly) periodicities. The mix of interspersed positioning arrows across the remaining frequency bands reveals positive comovements, as confirmed by the red or green coloured contours from the WCPD plot see -panel B,4.6From the SWC -panel A,4.7Among the E7 stock markets, Turkish stocks reveal more instances of potential diversification in the sample period. This is evidenced by the clouds of ← and ↙ positioning arrows in blue colours surrounded by white contours found across the time-frequency space, particularly between May and July, albeit with a few interspersed red-coloured contours. The alternating position of Turkish stocks confirms the highly volatile character of EMEs during crises.4.8First, GPR significantly drives the pricing- and return-generating dynamics in the E7 stock markets, as indicated by the predominant red colour of the heatmap across the fortnightly scale. This corroborates the observation of Umar et al. , who rep5To ascertain the robustness of the results and conclusions, the overall and net connectedness between E7 markets in the presence of geopolitical risk is examined. The time-varying parameter vector autoregression (TVP-VAR)-based connectedness metric of Antonakakis et al.  is emploThe TVP-VAR spillover matrix that shows the connectedness between the E7 markets in the face of GPR is presented in The results suggest that the overall connectedness between E7 markets, expressed by the total connectedness index, is 32.54%. Therefore, about a third of the variations in one of the E7 markets is explained by the connectedness between all seven markets and GPR. From the spillover matrix, the important results that need to be focused on, per the theme of the current study, are the net spillovers. The last row “NET” shows that Brazil (−7.06%), China (−8.41%), Indonesia (−7.68%), Russia (−6.53%), and Turkey (−6.78%) are all net recipients. The fact that five out of seven markets are net recipients indicates that they offer potential hedging advantages against geopolitical risk-induced shocks. Interestingly, GPR is a (and the greatest) net transmitter of system spillovers, indicating that shock transmission from other markets to E7 markets is championed by the GPR. To analyse this further, we take a look at the overall and net time-varying spillovers in 6This study investigates the time- and frequency-varying comovements between geopolitical risk (GPR) and the stock markets of the top-seven emerging (E7) countries. The daily GPR index developed by Caldara and Iacoviello  is emploThe results underscore predominant medium-to-high time-frequency coherence between stock returns from E7 countries and the Russian-Ukrainian conflict-induced geopolitical risk. The largely high comovements spotted from this study imply that there exist high comovements between Black Swan events like the Russian-Ukrainian conflict and financial markets’ volatility, highlighting the essence of alternative assets or asset classes for hedging geopolitical risks in the ongoing military actions. It is worth noting, however, that the lead-lag and comovement dynamics between GPR and E7 stocks reveal some intervals of mild coherence across the time-frequency spectrum. The intervals of low coherence suggest that based on the time and frequency , E7 stocks create room for diversification, implying that they could be potential safe-havens during Black Swan events, like geopolitical and military conflicts. Furthermore, this study reveals that E7 stocks exhibit market-specific coherence and lead-lag patterns regarding their interdependence with geopolitical risk, communicating heterogeneous and asymmetric market responses. Hence, the findings back the use of emerging markets equities by international investors seeking diversification and downside hedging strategies. Thus, E7 stocks, particularly those from Brazil, China, Russia, Indonesia, and Turkey could be used to hedge against geopolitical risk-induced shocks. Similarly, stocks that propagate shocks during elevated periods of the ongoing geopolitical conflict could be hedged against or diversified using a blend of E7 stocks.The results revealed from this study have notable implications for managers of portfolios, investors, and policymakers. To portfolio managers and investors, the findings guide asset allocation, particularly during Black Swan events. Given that the E7 economies have different geographical backgrounds, albeit a few shared characteristics, they could be employed for cross-regional hedging strategies by monitoring country- or market-specific attributes across different time scales as well as frequencies. In effect, developed market equities, which may be a source of contagion, could be diversified or hedged against by employing assets from emerging markets. To policymakers, the findings from this study should be instrumental in devising policies that mitigate market volatility during intense geopolitical shocks and heightened market uncertainty. Similarly, by monitoring the levels of GPR, policymakers could revise policy actions anytime GPR elevates or drops massively. This is because elevated levels of GPR could increase spillover transmission and contagion. Future works may extend this evidence by employing other econometric techniques and quantifying the portfolio implications for including E7 stocks in international portfolios.Samuel Kwaku Agyei: Conceived and designed the experiments; Performed the experiments; Analysed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.The authors do not have permission to share data.The authors declare no competing interests.