General short-term load forecasting based on multi-task temporal convolutional network in COVID-19

The spread of the global COVID-19 epidemic has resulted in significant shifts in electricity consumption compared to regular days. It is unknown if standard single-task, single-indicator load forecasting algorithms can accurately reflect COVID-19 load patterns. Power practitioners urgently want a simple, efficient, and accurate solution for anticipating reliable load. In this paper, we first propose a unique collaborative TCN-LSTM-MTL short-term load forecasting model based on mobility data, temporal convolutional networks, and multi-task learning. The addition of the parameter sharing layers and the structure with residual convolution improves the data input diversity of the forecasting model and enables the model to obtain a wider time series receptive field. Then, to demonstrate the usefulness of the mobility optimized TCN-LSTM-MTL, tests were conducted in three levels and twelve base regions using 19 different benchmark models. It is capable of controlling predicting mistakes to within 1 % in the majority of tasks. Finally, to rigorously explain the model, the Shapley additive explanations (SHAP) visual model interpretation technology based on game theory is introduced. It examines the TCN-LSTM-MTL model's internal mechanism at various time periods and establishes the validity of the mobility indicators as well as the asynchronous relationship between indicator significance and real contribution.

Lianhua Qingwen combined with conventional western medicine in treatment of COVID-19: An overview of systematic reviews

Objective: Overview the systematic review/Meta analysis of Lianhua Qingwen (连花清瘟) combined with conventional western medicine in the treatment of coronavirus disease 2019 (COVID-19). Methods: Systematic reviews/Meta-analysis of Lianhua Qingwen combined with western conventional in the treatment of COVID-19 from CNKI, Wanfang, CBM, VIP, PubMed, Embase, Cochrane Library, and Web of Sciencewere search, retrieved as of October 1, 2021. Two investigators screened the literature according to the inclusion and exclusion criteria, and determined the final inclusion of the literature. AMSTAR-2 scale, GRADE system, and PRISMA statements were used to evaluate the methodological quality and GRADE the evidence quality. Results: A total of eight systematic reviews/Meta analyses were included, including six in Chinese and four in English. The quality evaluation and evidence quality classification results show that the quality of the literature and the level of evidence were low. Conclusion: The existing evidence shows that Lianhua Qingwen combined with conventional western has a good effectin the treatment of COVID-19. However, due to the low methodological quality and evidence quality level of the systematic review/Meta analysis and the low level of evidence quality, more high-quality researchs are needed to obtain high-quality research results for verification.

A 3D CNN Network with BERT For Automatic COVID-19 Diagnosis From CT-Scan Images

We present an automatic COVID1-19 diagnosis framework from lung CT-scan slice images. In this framework, the slice images of a CT-scan volume are first preprocessed using segmentation techniques to filter out images of closed lung, and to remove the useless background. Then a re-sampling method is used to select a set of fixed number of slice images for training and validation. A 3D CNN network with BERT is used to classify this set of selected slice images. In this network, an embedding feature is also extracted. In cases where there are more than one set of slice images in a volume, the features of all sets are extracted and pooled into a feature vector for the whole CT-scan volume. A simple multiple-layer perceptron (MLP) network is used to further classify the aggregated feature vector. The models are trained and evaluated on the provided training and validation datasets. On the validation dataset, the precision is 0.9278 and the F1 score is 0.9261. On the test dataset, the F1 score is 0.8822. The code will be available at xxx.

A multi-centre service evaluation of the impact of the COVID-19 pandemic on presentation of newly diagnosed cancers and type 1 diabetes in children in the UK

Background The COVID-19 pandemic led to changes in patterns of presentation to Emergency Departments. Child health professionals were concerned that this could contribute to the delayed diagnosis of life-threatening conditions, including childhood cancer (CC) and type 1 diabetes (T1DM). Objectives Our multicentre, UK-based service evaluation assessed diagnostic intervals and disease severity for these conditions. Methods We collected presentation route, timing and disease severity for children with newly diagnosed CC in three principal treatment centres between January-June 2020 and T1DM in four centres between January-July 2020. We compared these to the corresponding period in 2019. The impact of lockdown on total diagnostic interval (TDI), patient interval (PI), system interval (SI) and disease severity were evaluated. Results Children with new diagnosis of CC (n=253) and T1DM (n=187) were included in the analysis. Overall there was a 17% reduction (138 vs 115) in number of incident CC cases and 9% reduction (98 vs 89) in T1DM cases between 2019 and 2020, with some regional variation. No significant differences in gender, ethnic background or age at diagnosis between study periods were observed. The route to diagnosis and severity of illness at presentation were unchanged across all time periods. Median diagnostic interval for CCs during lockdown was comparable to that in 2019 (TDI 4.6, PI 1.1 and SI 2.1 weeks), except for an increased PI during pre-lockdown period Jan-Mar 2020 (2.7 weeks) (table 1). Median diagnostic interval for T1DM during lockdown was similar to that in 2019 (TDI 16 vs 15 and PI 14 vs 14 days), except for an increased PI in pre-lockdown period Jan-Mar 2020 (21 days) (table 2). Conclusions There is no evidence of diagnostic delay or increased illness severity for CC or T1DM during the first lockdown in the participating centres. This provides reassuring data for children and families with these life-changing conditions. Data collection at a more comprehensive national level would provide greater clarity on diagnostic intervals.

Changing patterns of emergency paediatric presentations during the first wave of COVID-19: Learning for the second wave from a UK Tertiary Emergency Department

Background The SARS-CoV2 pandemic and initial public health response led to significant changes in health service delivery, access and utilisation. The SARS-CoV2 illness burden in children and young people (CYP) is significantly lower than in adults. To inform effective child public health interventions we aimed to compare patterns of paediatric emergency department presentations. Objectives Describe the ED attendance pattern of CYP during COVID-19 compared to the same period in 2019. Methods Retrospective review of all attendances (0-18yrs) over the initial pandemic (02/03/20-03/05/20) compared to 2019. Outcome measures included demographics, number of attendances, source of referral, presenting complaint, discharge diagnosis and disposal. Descriptive statistics, with subgroup analysis by age/sex/ethnicity and pandemic time-periods (prelockdown, lockdown weeks 1-3 and lockdown weeks 4-6) were performed. Results 4417 attendances (57% illness;43% injuries) occurred between 02/03/20-03/05/20, compared to 8813 (57% illness;43% injuries), a reduction of 50%, maximal in lockdown week 2 (-73%). Presenting complaints 2529 (57%) attendances were illnesses and 1868 (43%) injuries, compared to 5005 (57%) and 3764 (43%) respectively in 2019. The top five illness complaints were breathing difficulty, fever, abdominal pain, diarrhoea & vomiting and rash, unchanged from 2019. Ranking of top 3 illness presentations changed across the pandemic weeks. Breathing difficulty dropped from 1st (300;25%) to 2nd (117;21%) to 3rd (59;11%);(p<0.001). Abdominal pain rose from 3rd pre-lockdown (87;7%) and lockdown weeks 1-3 (37;7%) to 2nd in weeks 4-6 (62;12%;p=0.004). Fever ranked 2nd (235;19%) pre-lockdown, 1st (134;24%) in week 1-3 and week 4-6 (94;18%;p=0.035). Triage category 88 (2%) attendances were triaged as a category 1 (CAT1) and 544 (12%) attendances as a category 2 (CAT2);this is compared to 146 (2%) and 1134 (13%) in 2019. There was no variation in CAT1 across pre-lockdown (2%), lockdown weeks 1-3 (2%) and lockdown weeks 4-6 (2%) and minimal variation in CAT2 (12%, 13% and 11% respectively across pandemic weeks), indicating no change in severity of presentations. Source of referral (SOR) 3065/4417 attendances (69%) were by self-referral, proportionally the same as in 2019 (6149/8813;70%). Emergency services/urgent care were the second most common SOR for 487 (11%) attendances, similar to 2019 (762/8813;9%). NHS111 referral ranked third (416/4417;8%) and GP ranked 4th (315/4417;7%). This was different to 2019, where GP referral ranked 3rd (755/8813;9%) and NHS111 ranked 4th (734/8813;8%). Disposal 708 (16%) attendances resulted in admission, 3647 (83%) were discharged, 61 (1%) did not wait (DNW) and 1 patient died during the pandemic period. This was compared to 1675 (19%) admissions, 6755 (77%) discharges, 383 (4%) who DNW and no deaths in 2019. Conclusions Despite a 50% reduction in attendances there was no significant change in proportions of illness/injury, acuity of illness, source of referral or disposal. Rank of illness presentations changed, with abdominal pain ranking second, and fever first, an important change which should prompt further research into causes. Clear public health messaging for CYP and collaborative guidance for primary care is required in this second wave to ensure CYP have access to appropriate emergency, routine and mental health services.

Investigation and analysis of the mental pressure of outpatient medical attendants and nurses during the COVID-19 pandemic in china

Certain sicknesses or contaminations influence an enormous number of individuals in a limited capacity to focus time. A neighbourhood endemic illness can flare-up into a scourge influencing the entire populace or district which on occasion reach out to different nations and mainlands and become pandemic. Pandemics brings about death toll just like the economy. Pooled endeavors and assets, compelling sharing of information, equal numerous methodologies just as the physical and mental condition of forefront staff impact the board of pandemics. The COVID illness COVID-19 brought about by SARS-CoV-2 began in Dec 2019 from Wuhan in China, is currently an overall general wellbeing crisis influencing a huge number of people. It influences numerous cutting edge medical care laborers as well. Here, we contemplated mental pressure and proficient personality of Nurses and Staff for potential relationships, assuming any, and break down affecting elements. We utilized a purposive testing method with 415 Nurses and Staff in Nanjing, China through an overall data poll, seen pressure scale, and nursing proficient personality survey. Attendants and Staff' inception, month to month everyday costs, and their insight on plague counteraction and treatment have indicated a critical effect on their mental pressure (P< 0.010). Essentially, Nurse's and Staff's sexual orientation, inception, clinical practices, and information on counteraction and treatment, and whether they effectively learn such information sway altogether on their expert personality (P< 0.010). The general score of mental pressure were (24.470 +/- 07.350) and proficient personality had 72.470 +/- 08.070. The pressure condition showed a negative connection with the level of expert character (P< 0.01, r = -00.457). Expanded mental pressure, had a lower feeling of expert personality. Generally speaking, the examination of information on saw pressure and expert character pandemic proposes that feelings of anxiety are contrarily relative to information in compelling methods of taking care of the pandemic. Attendants and Staff with clinical practice fared better as far as expert character. The examination proposes Nurses and Staff to remain zeroed in on investigations, clinical practice, and directing, whenever required.