A one-year follow-up study of systematic impact of long COVID symptoms among patients post SARS-CoV-2 omicron variants infection in Shanghai, China.

Long COVID hinders people from normal life and work, posing significant medical and economic challenges. Nevertheless, comprehensive studies assessing its impact on large populations in Asia are still lacking. We tracked over 20,000 patients infected with COVID-19 for the first time during the Omicron BA.2 outbreak in Shanghai from March-June 2022 for one year. Of the 21,799 COVID-19 patients who participated in the 6-month telephone follow-up, 1939 (8.89%) had self-reported long COVID symptoms. 450 long COVID patients participated in the 6-month outpatient follow-up. Participants underwent healthy physical examinations and questionnaires focused on long-COVID-related symptoms and mental health. Mobility problem (P < 0.001), personal care problem (P = 0.003), usual activity problem (P < 0.001), pain/discomfort (P < 0.001), anxiety/depression (P = 0.001) and PTSD (P = 0.001) were more prevalent in long COVID patients than in healthy individuals, but no significant differences were found between the two groups on chest CT and laboratory examinations. Of the 856 long COVID patients who participated in the 12-month follow-up, 587 (68.5%) had their symptoms resolved. In the multivariable logistic analysis, females (P < 0.001), youth (age <40 years) (P < 0.001), ≥ 2 comorbidities (P = 0.009), and severe infection in the acute phase (P = 0.006) were risk factors for developing long COVID. Middle age (40-60 years) was a risk factor for persistent long COVID one year after hospital discharge (P = 0.013). The study found that long COVID mainly manifested as subjective symptoms and impacts partial patients' quality of life and mental status. After one year, most (68.5%) of the patients recovered from long COVID with no impairment of organ function observed.

Vaccination effects on post-infection outcomes in the Omicron BA.2 outbreak in Shanghai.

Omicron and its sublineages are currently predominant and have triggered epidemiological waves of SARS-CoV-2 around the world due to their high transmissibility and strong immune escape ability. Vaccines are key measures to control the COVID-19 burden. Omicron BA.2 caused a large-scale outbreak in Shanghai since March 2022 and resulted in over 0.6 million laboratory-confirmed infections. The vaccine coverage of primary immunization among residents aged 3 years and older in Shanghai exceeded 90%, and inactivated COVID-19 vaccines were mainly delivered. In the context of high vaccine coverage, we conducted a cohort study to assess vaccine effects on reducing the probability of developing symptoms or severity of disease in infections or nonsevere cases. A total of 48,243 eligible participants were included in this study, the majority of whom had asymptomatic infections (31.0%) and mild-to-moderate illness (67.9%). Domestically developed COVID-19 vaccines provide limited protection to prevent asymptomatic infection from developing into mild-to-moderate illness and durable protection to prevent nonsevere illness from progressing to severe illness caused by Omicron BA.2. Partial vaccination fails to provide effective protection in any situation. The level of vaccine effects on disease progression in the elderly over 80 years old was relatively lower compared with other age groups. Our study results added robust evidence for the vaccine performance against Omicron infection and could improve vaccine confidence.

A diagnostic accuracy study comparing RNA LAMP, direct LAMP, and rapid antigen testing from nasopharyngeal swabs.

Introduction: During the coronavirus disease 2019 (COVID-19) pandemic, the early detection and isolation of individuals infected with severe acute respiratory syndrome coronavirus disease 2 (SARS-CoV-2) through mass testing can effectively prevent disease transmission. SARS-CoV-2 nucleic acid rapid detection based on loop-mediated isothermal amplification (LAMP) may be appropriate to include in testing procedures. Methods: We used 860 nasopharyngeal specimens from healthcare workers of Huashan Hospital and COVID-19 patients collected from April 7th to 21st, 2022, to assess the clinical diagnostic performance of the LAMP assay marketed by Shanghai GeneSc Biotech and compared it to the result of a rapid antigen test (RAT) head-to-head. Results: Overall, the diagnostic performance of LAMP assay and RAT were as follows. The LAMP assay represented higher sensitivity and specificity than RAT, especially in the extracted RNA samples. The sensitivity was 70.92% and 92.91% for direct LAMP and RNA-LAMP assay, respectively, while the specificity was 99.86% and 98.33%. The LAMP assay had overall better diagnostic performance on the specimens with relatively lower C t values or collected in the early phase (≤7 days) of COVID-19. The combination of LAMP assay and RAT improved diagnostic efficiency, providing new strategies for rapidly detecting SARS-CoV-2. Conclusion: The LAMP assay are suitable for mass screenings of SARS-CoV-2 infections in the general population.

New Surveillance Metrics for Alerting Community-Acquired Outbreaks of Emerging SARS-CoV-2 Variants Using Imported Case Data: Bayesian Markov Chain Monte Carlo Approach.

BACKGROUND: Global transmission from imported cases to domestic cluster infections is often the origin of local community-acquired outbreaks when facing emerging SARS-CoV-2 variants. OBJECTIVE: We aimed to develop new surveillance metrics for alerting emerging community-acquired outbreaks arising from new strains by monitoring the risk of small domestic cluster infections originating from few imported cases of emerging variants. METHODS: We used Taiwanese COVID-19 weekly data on imported cases, domestic cluster infections, and community-acquired outbreaks. The study period included the D614G strain in February 2020, the Alpha and Delta variants of concern (VOCs) in 2021, and the Omicron BA.1 and BA.2 VOCs in April 2022. The number of cases arising from domestic cluster infection caused by imported cases (Dci/Imc) per week was used as the SARS-CoV-2 strain-dependent surveillance metric for alerting local community-acquired outbreaks. Its upper 95% credible interval was used as the alert threshold for guiding the rapid preparedness of containment measures, including nonpharmaceutical interventions (NPIs), testing, and vaccination. The 2 metrics were estimated by using the Bayesian Monte Carlo Markov Chain method underpinning the directed acyclic graphic diagram constructed by the extra-Poisson (random-effect) regression model. The proposed model was also used to assess the most likely week lag of imported cases prior to the current week of domestic cluster infections. RESULTS: A 1-week lag of imported cases prior to the current week of domestic cluster infections was considered optimal. Both metrics of Dci/Imc and the alert threshold varied with SARS-CoV-2 variants and available containment measures. The estimates were 9.54% and 12.59%, respectively, for D614G and increased to 14.14% and 25.10%, respectively, for the Alpha VOC when only NPIs and testing were available. The corresponding figures were 10.01% and 13.32% for the Delta VOC, but reduced to 4.29% and 5.19% for the Omicron VOC when NPIs, testing, and vaccination were available. The rapid preparedness of containment measures guided by the estimated metrics accounted for the lack of community-acquired outbreaks during the D614G period, the early Alpha VOC period, the Delta VOC period, and the Omicron VOC period between BA.1 and BA.2. In contrast, community-acquired outbreaks of the Alpha VOC in mid-May 2021, Omicron BA.1 VOC in January 2022, and Omicron BA.2 VOC from April 2022 onwards, were indicative of the failure to prepare containment measures guided by the alert threshold. CONCLUSIONS: We developed new surveillance metrics for estimating the risk of domestic cluster infections with increasing imported cases and its alert threshold for community-acquired infections varying with emerging SARS-CoV-2 strains and the availability of containment measures. The use of new surveillance metrics is important in the rapid preparedness of containment measures for averting large-scale community-acquired outbreaks arising from emerging imported SARS-CoV-2 variants.

Identification of CKD, bedridden history and cancer as higher-risk comorbidities and their impact on prognosis of hospitalized Omicron patients: a multi-centre cohort study.

To further describe the effect of the "fragile population" and their "higher-risk" comorbidities on prognosis among hospitalized Omicron patients, this observational cohort study enrolled hospitalized patients confirmed with SARS-CoV-2 during the 2022 Omicron wave in Shanghai, China. The primary outcome was progression to severe or critical cases. The secondary outcome was viral shedding time from the first positive SARS-CoV-2 detection. A total of 847 participants were enrolled, most of whom featured as advanced age (>70 years old: 30.34%), not fully vaccinated (55.84%), combined with at least 1 comorbidity (65.41%). Multivariate cox regression suggested age >70 years old (aHR[95%CI] 0.78[0.61-0.99]), chronic kidney disease (CKD) stage 4-5 (aHR[95%CI] 0.61[0.46-0.80]), heart conditions (aHR[95%CI] 0.76[0.60-0.97]) would elongate viral shedding time and fully/booster vaccination (aHR[95%CI] 1.4 [1.14-1.72]) would shorten this duration. Multivariate logistic regression suggested CKD stage 4-5 (aHR[95%CI] 3.21[1.45-7.27]), cancer (aHR[95%CI] 9.52[4.19-22.61]), and long-term bedridden status (aHR[95%CI] 4.94[2.36-10.44]) were the "higher" risk factor compared with the elderly, heart conditions, metabolic disorders, isolated hypertension, etc. for severity while female (aHR[95%CI] 0.34[0.16-0.68]) and fully/booster Vaccination (aHR[95%CI] 0.35[0.12-0.87]) could provide protection from illness progression. CKD stage 4-5, cancer and long-term bedridden history were "higher-risk" factors among hospitalized Omicron patients for severity progression while full vaccination could provide protection from illness progression.

Uncertainty Estimation With Neural Processes for Meta-Continual Learning.

The ability to evaluate uncertainties in evolving data streams has become equally, if not more, crucial than building a static predictor. For instance, during the pandemic, a model should consider possible uncertainties such as governmental policies, meteorological features, and vaccination schedules. Neural process families (NPFs) have recently shone a light on predicting such uncertainties by bridging Gaussian processes (GPs) and neural networks (NNs). Their abilities to output average predictions and the acceptable variances, i.e., uncertainties, made them suitable for predictions with insufficient data, such as meta-learning or few-shot learning. However, existing models have not addressed continual learning which imposes a stricter constraint on the data access. Regarding this, we introduce a member meta-continual learning with neural process (MCLNP) for uncertainty estimation. We enable two levels of uncertainty estimations: the local uncertainty on certain points and the global uncertainty p(z) that represents the function evolution in dynamic environments. To facilitate continual learning, we hypothesize that the previous knowledge can be applied to the current task, hence adopt a coreset as a memory buffer to alleviate catastrophic forgetting. The relationships between the degree of global uncertainties with the intratask diversity and model complexity are discussed. We have estimated prediction uncertainties with multiple evolving types including abrupt/gradual/recurrent shifts. The applications encompass meta-continual learning in the 1-D, 2-D datasets, and a novel spatial-temporal COVID dataset. The results show that our method outperforms the baselines on the likelihood and can rebound quickly even for heavily evolved data streams.

Design of UVC Surface Disinfection Robot with Coverage Path Planning Using Map-Based Approach At-The-Edge

In response to the issue of virus contamination in the cold-chain warehouse or hospital environment under the influence of the COVID-19, we propose the design work of a disinfection robot based on the UVC radiation mechanism using the low-computational path optimization at-the-edge. To build a surface disinfection robot with less computing power to generate a collision-free path with shorter total distance in studies, a 2D map is used as a graph-based approach to automatically generate a closed-loop disinfection path to cover all the accessible surfaces. The discrete disinfection points from the map are extracted with effective disinfection distances and sorted by a nearest-neighbor (NN) search over historical trajectory data and improved A * algorithm to obtain an efficient coverage path to all accessible boundaries of the entire area. The purpose of improved A * algorithm with NN is not to find the optimal path solution but to optimize one with reasonable computing power. The proposed algorithm enhances the path-finding efficiency by a dynamically weighted heuristic function and reduces the path turning angles, which improves the path smoothness significantly requiring less computing power. The Gazebo simulation is conducted, and the prototype disinfection robot has been built and tested in a real lab environment. Compared with the classic A * algorithm, the improved A * algorithm with NN has improved the path-finding efficiency and reduced the path length while covering the same area. Both the simulation and experimental results show that this approach can provide the design to balance the tradeoffs among the path-finding efficiency, smoothness, disinfection coverage, and computation resources.

Geriatric risk and protective factors for serious COVID-19 outcomes among older adults in Shanghai Omicron wave.

Shanghai has been experiencing the Omicron wave since March 2022. Though several studies have evaluated the risk factors of severe infections, the analyses of BA.2 infection risk and protective factors among geriatric people were much limited. This multicentre cohort study described clinical characteristics, and assessed risk and protective factors for geriatric Omicron severe infections. A total of 1377 patients older than 60 were enrolled, with 75.96% having comorbidities. The median viral shedding time and hospitalization time were nine and eight days, respectively. Severe and critical were associated with longer virus clearance time (aOR [95%CI]:0.706 (0.533-0.935), P = .015), while fully vaccinated/booster and paxlovid use shortened viral shedding time (1.229 [1.076-1.402], P = .002; 1.140 [0.019-1.274], P = .022, respectively). Older age (>80), cerebrovascular disease, and chronic kidney disease were risk factors of severe/critical. Fully vaccination was a significant protective factor against severe infections (0.237 [0.071-0.793], P = .019). We found patients with more than two comorbidities were more likely to get serious outcomes. These findings demonstrated that in the elderly older than 60 years old, older age (aged over 80), cerebrovascular disease, and chronic kidney disease were risk factors for severe infection. Patients with more than two comorbidities were more likely to get serious outcomes. Fully vaccinated/booster patients were less likely to be severe and vaccinations could shorten viral shedding time. The limitation of lacking an overall spectrum of COVID-19 infections among elders could be compensated in other larger-scale studies in the future.

Early identification and severity prediction of acute respiratory infection (ESAR): a study protocol for a randomized controlled trial.

BACKGROUND: The outbreak of SARS-CoV-2 at the end of 2019 sounded the alarm for early inspection on acute respiratory infection (ARI). However, diagnosis pathway of ARI has still not reached a consensus and its impact on prognosis needs to be further explored. METHODS: ESAR is a multicenter, open-label, randomized controlled, non-inferiority clinical trial on evaluating the diagnosis performance and its impact on prognosis of ARI between mNGS and multiplex PCR. Enrolled patients will be divided into two groups with a ratio of 1:1. Group I will be directly tested by mNGS. Group II will firstly receive multiplex PCR, then mNGS in patients with severe infection if multiplex PCR is negative or inconsistent with clinical manifestations. All patients will be followed up every 7 days for 28 days. The primary endpoint is time to initiate targeted treatment. Secondary endpoints include incidence of significant events (oxygen inhalation, mechanical ventilation, etc.), clinical remission rate, and hospitalization length. A total of 440 participants will be enrolled in both groups. DISCUSSION: ESAR compares the efficacy of different diagnostic strategies and their impact on treatment outcomes in ARI, which is of great significance to make precise diagnosis, balance clinical resources and demands, and ultimately optimize clinical diagnosis pathways and treatment strategies. Trial registration Clinicaltrial.gov, NCT04955756, Registered on July 9th 2021.

Impact of COVID-19 pandemic on accessibility of Taiwanese medical care.

OBJECTIVES: Whether and how the COVID-19 pandemic affected utilization of routine medical care in areas with low infection risk, such as Taiwan, has not been widely addressed. We aimed to evaluate the impact of the COVID-19 pandemic on access to medical care. STUDY DESIGN: Before and after exposure (COVID-19 pandemic) design with a historical control group for comparison of clinical visits based on a retrospective cohort of 6722 customary patients of a community hospital in Zhunan, Taiwan. METHODS: Repeated measurements of medical utilization in 4-month periods (January to April) of 2019 and 2020 in light of the emerging COVID-19 pandemic were collected. Access to medical care was defined as the mean frequencies of clinical visits. The impacts of the COVID-19 pandemic on access in the overall and specific groups were quantified with a multivariable Poisson regression model. RESULTS: The overall outpatient visits per month declined by 39% (rate ratio [RR], 0.61; P < .0001) after adjusting for demographics. A notable reduction in visits was observed in foreign patients (RR, 0.50; P < .0001). The visits of the elderly (≥ 80 years) were the most frequent before the COVID-19 pandemic but were reduced by 44% (RR, 0.56; P < .0001) after it began. Most disease categories revealed a declining trend, but the size of reduction varied by International Classification of Diseases codes. CONCLUSIONS: The COVID-19 pandemic prevented some individuals from keeping regular medical appointments even in an area with a low infection risk. Our findings imply that more research is required to mitigate the effects of delayed medical care for patients who infrequently utilized medical care during and after the long-lasting pandemic period.

Research progress on potential drug interactions of anti-Coronavirus disease 2019 drugs

From the December 2019, coronavirus disease 2019 (COVID-19) was outbreak at home and abroad. Besides antiviral therapy, patients should be treated for complications, therefore a combination of drugs for treatment in Clinic need to be taken. Although recently published guidelines have repeatedly highlighted the drug interactions between the anti-COVID-l 9 medicines, it has not been detailed. The potential drug - drug interactions were reviewed 0f the anti-COVID-19 drugs, and in order to provide references for the clinical safety and rational use of the anti-COVID-19 drugs.