EFFECT OF UPADACITINIB ON REDUCING PAIN IN PATIENTS WITH ACTIVE ANKYLOSING SPONDYLITIS AND INADEQUATE RESPONSE TO BIOLOGIC THERAPY

BackgroundPain is a debilitating symptom of ankylosing spondylitis (AS) that negatively affects patients' lives. Upadacitinib (UPA), a Janus kinase inhibitor approved for the treatment of AS and other inflammatory diseases, showed significant efficacy vs placebo (PBO) in the phase 2/3 SELECT-AXIS 1 study in patients with AS who were biologic-naive and in the phase 3 SELECT-AXIS 2 study in patients with active AS who had an inadequate response (IR) to biological therapy [1,2]. Improvement in pain outcomes with UPA was also previously demonstrated in the SELECT-AXIS 1 study [3].ObjectivesThe objective of this post-hoc analysis of SELECT-AXIS 2 was to evaluate the efficacy of UPA vs PBO on multiple pain assessments through 14 weeks in patients with IR to a biologic disease-modifying antirheumatic drug (bDMARD-IR).MethodsSELECT-AXIS 2 (NCT04169373) enrolled adults with active AS with IR to biological therapy, including patients who discontinued biologics due to lack of efficacy or intolerance [1]. Patients were randomized 1:1 to UPA 15 mg once daily (QD) or PBO for 14 weeks. Pain endpoints evaluated here included the proportion of patients achieving ≥30%, ≥50%, and ≥70% reduction from baseline, minimal clinically important difference (MCID, defined as ≥1 point reduction or ≥15% reduction from baseline), and much better improvement (MBI, defined as ≥2 point reduction and ≥33% reduction from baseline) in Patient's Global Assessment (PGA) of pain, total back pain, and nocturnal back pain on a 0–10 numeric rating scale [3,4]. Non-responder imputation incorporating multiple imputation to handle missing data due to COVID-19 was used.ResultsA total of 211 patients received UPA 15 mg QD and 209 patients received PBO. Higher proportions of patients receiving UPA vs PBO achieved ≥30% and ≥50% reductions in PGA of pain, total back pain, and nocturnal back pain as early as week 2 that were sustained at all time points through 14 weeks (nominal P<0.05;Figure 1a-c). Achievement of ≥70% reductions in PGA of pain and nocturnal back pain were higher at week 4 and sustained thereafter (Figures 1a and 1c), and achievement of ≥70% reduction in total back pain was higher at week 2 and week 8, but not week 4, and sustained thereafter (Figure 1b). Results were similar for the proportion of patients achieving MCID and MBI, with improvements in PGA of pain, total back pain, and nocturnal back pain for UPA vs PBO as early as week 1 (MCID) or week 2 (MBI) that were sustained through week 14 (all nominal P<0.001;Table 1).Table 1.Achievement of MCID and MBI in Pain Outcomes at Week 14 (NRI-MI)Responder Rate (95% CI), %Pain OutcomesUPA 15 mgPBONominal P ValuePGA of painMCID81.0 (75.8–86.3)62.7 (56.1–69.2)<0.0001MBI60.7 (54.1–67.3)24.9 (19.0–30.7)<0.0001Total back painMCID80.1 (74.7–85.5)65.1 (58.6–71.5)0.0005MBI58.3 (51.6–64.9)25.4 (19.5–31.3)<0.0001Nocturnal back painMCID82.9 (77.9–88.0)61.3 (54.7–67.9)<0.0001MBI61.6 (55.0–68.2)32.1 (25.7–38.4)<0.0001MBI, much better improvement;MCID, minimal clinically important difference;NRI-MI, non-responder imputation incorporating multiple imputation to handle missing data due to COVID-19;PBO, placebo;PGA, Patient's Global Assessment;UPA, upadacitinib.ConclusionIn patients with active AS who were bDMARD-IR, greater proportions of patients treated with UPA achieved rapid and clinically meaningful reductions in pain vs PBO as early as week 2 that were sustained through 14 weeks across multiple pain assessments.References[1]van der Heijde D, et al. Ann Rheum Dis. 2022;81(11):1515-1523.[2]van der Heijde D, et al. Lancet. 2019;394(10214):2108-2117.[3]McInnes IB, et al. RMD Open. 2022;8(1):doi:10.1136/rmdopen-2021-002049.[4]Salaffi F, et al. Eur J Pain. 2004;8(4):283-291.AcknowledgementsAbbVie funded this study and participated in the study design, research, analysis, data collection, interpretation of data, reviewing, and approval of the publication. All authors had access to relevant data and participated in the drafting, review, and approval of this p blication. No honoraria or payments were made for authorship. Medical writing support was provided by M. Hovenden and J. Matsuura of ICON plc (Blue Bell, PA, USA) and was funded by AbbVie.Disclosure of InterestsXenofon Baraliakos Consultant of: Novartis, Pfizer, AbbVie, Eli Lilly, UCB Pharma, Galapagos, Janssen, Celgene, and Amgen, Grant/research support from: Novartis, Pfizer, AbbVie, Eli Lilly, UCB Pharma, Galapagos, Janssen, Celgene, and Amgen, Marina Magrey Consultant of: UCB, Novartis, Eli Lilly, Pfizer, and Janssen, Grant/research support from: Amgen, AbbVie, BMS, and UCB Pharma, Louis Bessette Speakers bureau: Amgen, BMS, Janssen, UCB, AbbVie, Pfizer, Merck, Celgene, Lilly, Novartis, Organon, and Sanofi, Grant/research support from: Amgen, BMS, Janssen, UCB, AbbVie, Pfizer, Merck, Celgene, Lilly, Novartis, Sanofi, and Gilead, Kurt de Vlam Speakers bureau: Amgen, Celgene, Eli Lilly, Galapagos, Novartis, and UCB, Consultant of: Amgen, AbbVie, Celgene, Eli Lilly, Galapagos, Novartis, and UCB, Grant/research support from: Amgen, UCB, and MSD, Tianming Gao Shareholder of: AbbVie, Employee of: AbbVie, Anna Shmagel Shareholder of: AbbVie, Employee of: AbbVie, Ralph Lippe Shareholder of: AbbVie, Employee of: AbbVie, Ana Biljan Shareholder of: AbbVie, Employee of: AbbVie, Victoria Jasion Shareholder of: AbbVie, Employee of: AbbVie, Peter C. Taylor Speakers bureau: AbbVie, Consultant of: Lilly, AbbVie, Pfizer, Galapagos, Gilead, Janssen, GlaxoSmithKline, Sanofi, Fresenius, Nordic Pharma, UCB, and Biogen, Grant/research support from: Galapagos.

Short-Term State Electricity Load Forecasting Based on Transfer-Informer

The worldwide COVID-19 pandemic has caused an enormous impact on the operation mode of human society. Such sudden events bring sharp fluctuations and data inadequacy in datasets of several areas, which leads to challenges in solving related problems. Traditional deep learning models like CNN have shown relatively poor performance with small datasets during the COVID-19 pandemic. This is because the data insufficiency and fluctuations lead to serious problems in the training process. In our work, an Informer framework combined with Transfer learning methods (Transfer-Informer) is proposed to solve the data insufficiency in emergency situations, as well as to provide a more efficient self-attention mechanism for deep feature mining, with two distinctive advantages: (1) The ProbSpares self-attention mechanisms, which enables the proposed model to highlight dominant information and extract more typical features from time-series datasets. (2) The Transfer learning framework improves the generalization capability of the model, by transferring basic knowledge from normal situations to emergency cases with fewer data. In our experiments, Transfer-Informer is applied to short-term load forecasting, which achieves better predicting accuracy than traditional models. The empirical results indicate that the proposed model has put forward a baseline for short-term load forecasting in emergency situations and provided a feasible method to tackle sudden fluctuations in real problem-solving. © 2022 IEEE.

Short-Term State Electricity Load Forecasting Based on Transfer-Informer

The worldwide COVID-19 pandemic has caused an enormous impact on the operation mode of human society. Such sudden events bring sharp fluctuations and data inadequacy in datasets of several areas, which leads to challenges in solving related problems. Traditional deep learning models like CNN have shown relatively poor performance with small datasets during the COVID-19 pandemic. This is because the data insufficiency and fluctuations lead to serious problems in the training process. In our work, an Informer framework combined with Transfer learning methods (Transfer-Informer) is proposed to solve the data insufficiency in emergency situations, as well as to provide a more efficient self-attention mechanism for deep feature mining, with two distinctive advantages: (1) The ProbSpares self-attention mechanisms, which enables the proposed model to highlight dominant information and extract more typical features from time-series datasets. (2) The Transfer learning framework improves the generalization capability of the model, by transferring basic knowledge from normal situations to emergency cases with fewer data. In our experiments, Transfer-Informer is applied to short-term load forecasting, which achieves better predicting accuracy than traditional models. The empirical results indicate that the proposed model has put forward a baseline for short-term load forecasting in emergency situations and provided a feasible method to tackle sudden fluctuations in real problem-solving. © 2022 IEEE.

The Influence of Disease Avoidance Motive on the Economic Behavior Ethics under the Impact of Pandemic: A Moderated Mediation Model

Objective: As one of the basic social motives, Disease Avoidance Motive is the deep psychological factor behind many social behaviors. Since the emergence of the COVID-19 and its continuous spread across the world at the end of 2019, the ever-changing and recurring COVID-19 pandemic has increased people's fear and rejection of the threat of infectious diseases, and activated people's Disease Avoidance Motive, which has remained at a high level for a long time. This study takes Disease Avoidance Motive as the starting point, introduces COVID Control Regulations as the intermediary, and disease vulnerability as the regulator, to explore the influence of Disease Avoidance Motive on Economic Behavior Ethics. Methods: Regression analysis, SPSS Statistics and Moderated Mediation Model were applied and 524 random respondents were surveyed through Basic Social Motivation Scale, Pandemic Norm Compliance Questionnaire, Economic Behavior Ethics Questionnaire and Scale of Perceived Vulnerability to Disease. Results: (1) Disease Avoidance Motive positively predicts Economic Behavior Ethics;(2) COVID Control Regulations play a mediating role between Disease Avoidance Motive and Economic Behavior Ethics (3) Perceived Vulnerability to Disease positively moderates the direct effect of Disease Avoidance Motive on Economic Behavior Ethics. Conclusion: Under the moderation of Perceived Vulnerability to Disease, Disease Avoidance Motive exerts an influence on the Economic Behavior Ethics through COVID Control Regulations. © 2022 ACM.

Efficacité d'upadacitinib chez des patients atteints de spondyloarthrite axiale non radiographique en fonction des signes objectifs d'inflammation à l'inclusion

L'essai de phase 3 SELECT-AXIS 2 (NCT04169373) a évalué l'efficacité et la tolérance d'upadacitinib (UPA) chez des patients atteints de spondyloarthrite axiale non radiographique (nr-axSpA). Nous présentons ici une analyse en sous-groupes (ss-gpes) en fonction de la valeur de la hsCRP et de l'inflammation des sacro-iliaques (SI) à l'IRM à la sélection. Dans SELECT-AXIS 2 [1] , des patients de ≥ 18 ans ayant un diagnostic clinique de nr-axSpA remplissant les critères de classification de 2009 de l'ASAS, mais sans le critère radiologique des critères de New-York modifiés, et présentant des signes objectifs d'inflammation active à l'IRM selon la définition de l'ASAS (évaluation par 2 lecteurs et un arbitre) et/ou un taux de hsCRP supérieur à la limite supérieure de la normale (LSN, 2,87 mg/L) à la sélection, ont été randomisés selon un ratio 1/1 pour recevoir UPA 15 mg 1x/j ou un placebo (PBO). Le critère principal était la réponse ASAS40 à la semaine (S) 14. Les autres critères incluaient la faible activité de la maladie (LDA) selon l'ASDAS (≤ 2,1), la variation par rapport à l'inclusion du SPARCC-IRM articulations SI, du BASFI et de la douleur rachidienne évaluée par le patient, à S14. Les analyses en ss-gpes préspécifiées (ASAS40) et post-hoc (autres critères) ont été réalisées en fonction du statut inflammatoire à la sélection : taux de hsCRP (> LSN vs ≤ LSN) et inflammation des articulations SI à l'IRM (positive vs négative). L'imputation des non-répondeurs (NRI) avec imputation multiple (MI) pour prendre en compte des données manquantes liées au COVID-19, a été utilisée pour les variables binaires. Un modèle mixte pour mesures répétées sur les données observées (AO) a été utilisé pour les variables continues sauf pour le score SPARCC-IRM pour lequel une analyse de covariance sur les AO a été utilisée. Sur les 312 patients inclus dans l'analyse, 176 (56 %) avaient une hsCRP > LSN et une IRM négative (IRM−), 73 (23 %) une hsCRP > LSN et une IRM positive (IRM+) et 63 (20 %) une hsCRP ≤ LSN et une IRM+. Les caractéristiques démographiques et cliniques à l'inclusion étaient similaires dans les ss-gpes ;cependant, le ss-gpe hsCRP > LSN et IRM+ était plus fréquent chez les patients HLA-B27 positifs et avait un plus faible taux de traitement antérieur par DMARDs biologiques (Tableau 1). À S14, des taux plus élevés de réponse ASAS40 et ASDAS-LDA et une réduction plus importante par rapport à l'inclusion des scores SPARCC-IRM, BASFI et de douleur rachidienne ont été associés à UPA vs PBO pour tous les ss-gpes (Fig. 1). La différence UPA vs PBO était plus importante pour le groupe hsCRP > LSN et IRM+, pour tous les critères. Dans SELECT-AXIS 2, les résultats chez les patients atteints de nr-axSpA ont été améliorés pour UPA versus le PBO pour tous les sous-groupes d'inflammation à l'inclusion ;le bénéfice le plus important a été observé chez les patients ayant à la fois un taux élevé de CRP et des signes d'inflammation à l'IRM à la sélection. (French) [ FROM AUTHOR]

Maternal heart rate collection pre- and post-cardiac screening guideline implementation in an outpatient obstetrics office

Objective: The California Maternal Quality Care Collaborative (CMQCC) proposed an algorithm to reduce maternal mortality by screening for cardiac disease in pregnancy, including use of maternal heart rates. The effect of this guideline was assessed at an outpatient obstetrics office by studying rates of heart rate screening before and after implementation. Study Design: This study reviewed 100 return in-person prenatal visits monthly from January 2019 to November 2021. Maternal heart rate, demographics, and presence of chronic hypertension or cardiac disease were noted. Rates of heart rate collection were compared pre- and post-guideline implementation. Per the CMQCC guideline, a resting heart rate of >= 110 bpm was deemed high enough to warrant further evaluation. Result(s): This retrospective cohort included 3,478 visits (100 visits per month, fewer visits in April and May 2020 due to COVID19 pandemic). Several visits (n=382, 11%) were to patients with chronic hypertension and 159 (4.6%) had underlying cardiac disease. Overall, 1798 (51.7%) visits recorded a maternal heart rate, while 1680 (48.3%) did not. More visits had heart rates recorded post- than pre-guideline (67.6% versus 21.4% of visits, respectively;p < 0.001). Maternal heart rates >= 110 bpm were recorded at 130 visits (3.7%). Pre-guideline, 29.5% of patients with heart disease and/or chronic hypertension had heart rate recorded compared to 20.1% of patients without these conditions (p=0.005). Post-guideline, patients with heart disease and/or chronic hypertension were more likely to have heart rate recorded compared to those without these conditions (78.8% versus 65.8%, p < 0.001). Elevated heart rates >= 110 were recorded at 34 of 308 (11.0%) visits to patients with known hypertension and/or cardiac disease, compared to 96 out of 1490 (6.4%) to patients without these diagnoses (p=0.005). Conclusion(s): Maternal heart rate screening significantly increased after guideline implementation. Patients with underlying cardiac disease and/or chronic hypertension were nearly twice as likely to have a heart rate >= 110 bpm when heart rate was assessed. [Formula presented] [Formula presented] Copyright © 2022

Using Gamified Interactive Experience to Relieve Psychological Pressure in the Post-pandemic Era

The COVID-19 Pandemic brought the whole society to a standstill, which has more significant psychological pressure on children and adolescents. Governments, companies, and social groups are trying to confront COVID-19 and social distancing in a gamified way. However, due to fear of the virus and uncertainty about the future, even after the Pandemic is well controlled in physical space, people are still reluctant to stop and play in public areas and are afraid to engage with others because of their internal sense of alienation. From the perspective of urban renewal and environmental design, creating a series of micro-scale design interventions in public spaces to relieve psychological pressure has urgency and relevant significance. This paper analyzes the symbiotic relationship between public art installations and communities. Then discovers the characteristics of public installations based on emotional healing. Furthermore, create two design prototypes to demonstrate more vividly how gamified interactive experience could relieve the mental pressure of the surrounding residents and help them gradually adapt to the new normal life. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

FCOS-Mask: Fully Convolution Neural Network for Face Mask Detection

Since the end of 2019, the coronavirus disease 2019 (COVID-19) has spread globally, posing enormous challenges to the global society. Wearing a mask has been proven to be the easiest and the most effective way to limit the spread of COVID-19, and it has become the rule in many public areas. This has also led to a growing demand for automatic real-time mask detection services to replace manual reminders. However, current research on mask detection still has limitations, and both the accuracy and speed can be further improved. In this paper, we propose FCOS-Mask, a one-stage anchor-free object detection method for face mask detection. We add a bottom-up feature augmentation path to the model's neck and conduct Mosaic to strengthen the ability to detect objects in an unusual context. Moreover, we adopt CIoU and Soft-NMS to improve the training speed and detection accuracy on occluded faces. FCOS-Mask is tested on the Face Mask Detection dataset and achieves a higher 2.9% mAP compared to baseline with a real-time speed of 20.6 FPS on RTX 2070. © 2022 IEEE.

Autonomous inference of complex network dynamics from incomplete and noisy data

The availability of empirical data that capture the structure and behaviour of complex networked systems has been greatly increased in recent years;however, a versatile computational toolbox for unveiling a complex system’s nodal and interaction dynamics from data remains elusive. Here we develop a two-phase approach for the autonomous inference of complex network dynamics, and its effectiveness is demonstrated by the tests of inferring neuronal, genetic, social and coupled oscillator dynamics on various synthetic and real networks. Importantly, the approach is robust to incompleteness and noises, including low resolution, observational and dynamical noises, missing and spurious links, and dynamical heterogeneity. We apply the two-phase approach to infer the early spreading dynamics of influenza A flu on the worldwide airline network, and the inferred dynamical equation can also capture the spread of severe acute respiratory syndrome and coronavirus disease 2019. These findings together offer an avenue to discover the hidden microscopic mechanisms of a broad array of real networked systems. © 2022, The Author(s), under exclusive licence to Springer Nature America, Inc.

Epidemiological and clinical characteristics of 40 cases of COVID-19 outside Hubei

To explore characteristics of patients with pneumonia infected by 2019 Novel Coronavirus (COVID-19) in 2019 outside Hubei Province, China. 40 patients with pneumonia infected by COVID-19 which were confirmed by COVID-19 nucleic acid test were included. Procalcitonin (PCT), serum amyloid A (SAA), C-reactive protein (CRP) and computed tomography (CT) manifestations were analyzed. 40% of patients had clear contact history with Wuhan or other areas of Hubei Province. 60% of patients were clustered diseases and 40% were imported cases. 75% of patients had initial fever, 7.5% had cough, 5% had sore throat at first. 45% had decreased lymphocyte count, 72.5% and 55% patients had increased levels of SAA and CRP. 72.5% of the patients showed multiple ground glass lesions in one or two lungs on chest CT. 90% of the patients with pneumonia are of the common type, and alpha-interferon atomization inhalation combined with Lopinavir/Ritonavir tablets were given to patients during treatment. 62.5% of the patients were treated with antibiotics, and 15% with hormone. All patients improved after treatment, and 14 patients were cured and discharged. Family cluster infection and asymptomatic infection may be the main way of spreading of COVID-19 pneumonia outside Hubei Province in China.

[Correlation analysis of smell and taste loss with COVID-19 outbreak trend based on big data of internet].

Objective: To analyze the correlation between loss of smell/taste and the number of real confirmed cases of coronavirus disease 2019 (COVID-19) worldwide based on Google Trends data, and to explore the guiding role of smell/taste loss for the COVID-19 prevention and control. Methods: "Loss of smell" and "loss of taste" related keywords were searched in the Google Trends platform, the data were obtained from Jan. 1 2019 to Jul. 11 2021. The daily and newly confirmed COVID-19 case number were collected from World Health Organization (WHO) since Dec. 30 2019. All data were statistically analyzed by SPSS 23.0 software. The correlation was finally tested by Spearman correlation analysis. Results: A total of data from 80 weeks were collected. The retrospective analysis was performed on the new trend of COVID-19 confirmed cases in a total of 186 292 441 cases worldwide. Since the epidemic of COVID-19 was recorded on the WHO website, the relative searches related to loss of smell/taste in the Google Trends platform had been increasing globally. The global relative search volumes of "loss of smell" and "loss of taste" on Google Trends was 10.23±2.58 and 16.33±2.47 before the record of epidemic while 80.25±39.81 and 80.45±40.04 after (t value was 8.67, 14.43, respectively, both P<0.001). In the United States and India, the relative searches for "loss of smell" and "loss of taste" after the record of epidemic were also much higher than before (all P<0.001). The correlation coefficients between the trend of weekly new COVID-19 cases and the Google Trends of "loss of smell" in the global, United States, and India was 0.53, 0.76, and 0.82 respectively (all P<0.001), the correlation coefficients with Google Trends of "loss of taste" was 0.54, 0.78, and 0.82 respectively (all P<0.001). The lowest and highest point of loss of smell/taste search curves of Google Trends in different periods appeared 7 to 14 days earlier than that of the weekly newly COVID-19 confirmed cases curves, respectively. Conclusions: There is a significant positive correlation between the number of newly confirmed cases of COVID-19 worldwide and the amount of keywords, such as "loss of smell" and "loss of taste", retrieved in Google Trends. The trend of big data based on Google Trends might predict the outbreak trend of COVID-19 in advance.

Solutions for Post-pandemic Economic Recovery: The Case of China

The global economy is now under extremely severe pressure from a great variety of political, economic, social, environmental, and public health challenges. The COVID-19 outbreak has rapidly transformed from a medical phenomenon to a threat of disruption to global supply chains and economic recession in most countries of the world. Despite the similarity of problems, the impact of the pandemic on individual countries has appeared to be different in terms of the severity of both human and economic losses. China is the first country that experienced the outbreak in early 2020 and now it is one of the first to recover from it. A set of effective and efficient health security, economic, and social measures allowed China to restart economic activities in the domestic market and restore foreign trade with its counterparts. This paper presents an assessment of major macroeconomic parameters of China in 2020 compared to previous periods, discusses the efficacy of economic, fiscal, and investment solutions made by China’s government during the pandemic, and assesses how these measures have affected China’s recovery in terms of GDP, investment in fixed assets, exports and imports, money supply, and the price index. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Location-specific health impacts of climate change require location-specific responses

Left unmitigated, climate change poses a catastrophic risk to human health, demanding an urgent and concerted response from every country. The 2015 Lancet Commission on Health and Climate Change and The Lancet Countdown: Tracking Progress on Health and Climate Change have been initiated to map out the impacts of climate change and the necessary policy responses. To meet these challenges, Tsinghua University, partnering with the University College London and 17 Chinese and international institutions, has prepared the Chinese Lancet Countdown report, which has a national focus and builds on the work of the global Lancet Countdown: Tracking Progress on Health and Climate Change. Drawing on international methodologies and frameworks, this report aims to deepen the understanding of the links between public health and climate change at the national level and track them with 23 indicators. This work is part of the Lancet's Countdown broader efforts to develop regional expertise on this topic, and coincides with the launch of the Lancet Countdown Regional Centre in Asia, based at Tsinghua University. The data and results of this report are presented at the provincial level, where possible, to facilitate targeted response strategies for local decision-makers. Based on the data and findings of the 2020 Chinese Lancet Countdown report, five recommendations are proposed to key stakeholders in health and climate change in China: (1) Enhance inter-departmental cooperation. Climate change is a challenge that demands an integrated response from all sectors, urgently requiring substantial inter-departmental cooperation among health, environment, energy, economic, financial, and education authorities. (2) Strengthen health emergency preparedness. Knowledge and findings on current and future climate-related health threats still lack the required attention and should be fully integrated into the emergency preparedness and response system. (3) Support research and raise awareness. Additional financial support should be allocated to health and climate change research in China to enhance health system adaptation, mitigation measures, and their health benefits. At the same time, media and academia should be fully motivated to raise the public and politicians' awareness of this topic. (4) Increase climate change mitigation. Speeding up the phasing out of coal is necessary to be consistent with China's pledge to be carbon neutral by 2060 and to continue to reduce air pollution. Fossil fuel subsidies must also be phased out. (5) Ensure the recovery from COVID-19 to protect health now and in the future. China's efforts to recover from COVID-19 will shape public health for years to come. Climate change should be a priority in these interventions. © 2021, Science Press. All right reserved.

A Study on User Experience of COVID-19 Emergency Communication Platform from Cross-cultural Perspective of View

From certain point of view, the emergency communication platform plays an important role in fighting against COVID-19. This research aims to explore the user experience of the COVID-19 emergency communication platform in a cross-cultural background, with the purpose of relevant information promoting strategy under different culture recognition. This study takes China’s Tencent health platform and the UK’s NHS COVID-19 APP as the research objects. We built a user experience model first, then obtained user experience data by collecting 172 valid questionnaires and conducting interviews with 17 users. This research explores the current situation of users’ experience on two different national platforms, compares and analyzes the feedback, found the differences between Chinese and British emergency communication platforms based on cultural theory. Our research shows that the different cultural characteristics of China and Britain make the two platforms variance in terms of sensory, interactive and satisfaction experience. © 2021, Springer Nature Switzerland AG.