Forecasting for Network Management with Joint Statistical Modelling and Machine Learning

Forecasting is a task of ever increasing importance for the operation of mobile networks, where it supports anticipa tory decisions by network intelligence and enables emerging zero touch service and network management models. While current trends in forecasting for anticipatory networking lean towards the systematic adoption of models that are purely based on deep learning approaches, we pave the way for a different strategy to the design of predictors for mobile network environments. Specifically, following recent advances in time series prediction, we consider a hybrid approach that blends statistical modelling and machine learning by means of a joint training process of the two methods. By tailoring this mixed forecasting engine to the specific requirements of network traffic demands, we develop a Thresholded Exponential Smoothing and Recurrent Neural Network (TES-RNN) model. We experiment with TES RNN in two practical network management use cases, i.e., (i) anticipatory allocation of network resources, and (ii) mobile traffic anomaly prediction. Results obtained with extensive traffic workloads collected in an operational mobile network show that TES-RNN can yield substantial performance gains over current state-of-the-art predictors in both applications consideredThis work is partially supported by the European Union's Horizon 2020 research and innovation programme under grant agreement no.101017109 DAEMON. This work is partially supported by the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union-NextGenerationEU through the UNICO 5G I+D 6GCLARION-OR and AEON-ZERO. The authors would like to thank Dario Bega for his contribution to developing the forecasting use case I, and Slawek Smyl for his feedback on the baseline ES-RNN model

Delayed colorectal cancer care during covid-19 pandemic (decor-19). Global perspective from an international survey

Background The widespread nature of coronavirus disease 2019 (COVID-19) has been unprecedented. We sought to analyze its global impact with a survey on colorectal cancer (CRC) care during the pandemic. Methods The impact of COVID-19 on preoperative assessment, elective surgery, and postoperative management of CRC patients was explored by a 35-item survey, which was distributed worldwide to members of surgical societies with an interest in CRC care. Respondents were divided into two comparator groups: 1) ‘delay’ group: CRC care affected by the pandemic; 2) ‘no delay’ group: unaltered CRC practice. Results A total of 1,051 respondents from 84 countries completed the survey. No substantial differences in demographics were found between the ‘delay’ (745, 70.9%) and ‘no delay’ (306, 29.1%) groups. Suspension of multidisciplinary team meetings, staff members quarantined or relocated to COVID-19 units, units fully dedicated to COVID-19 care, personal protective equipment not readily available were factors significantly associated to delays in endoscopy, radiology, surgery, histopathology and prolonged chemoradiation therapy-to-surgery intervals. In the ‘delay’ group, 48.9% of respondents reported a change in the initial surgical plan and 26.3% reported a shift from elective to urgent operations. Recovery of CRC care was associated with the status of the outbreak. Practicing in COVID-free units, no change in operative slots and staff members not relocated to COVID-19 units were statistically associated with unaltered CRC care in the ‘no delay’ group, while the geographical distribution was not. Conclusions Global changes in diagnostic and therapeutic CRC practices were evident. Changes were associated with differences in health-care delivery systems, hospital’s preparedness, resources availability, and local COVID-19 prevalence rather than geographical factors. Strategic planning is required to optimize CRC care

Preoperative nasopharyngeal swab testing and postoperative pulmonary complications in patients undergoing elective surgery during the SARS-CoV-2 pandemic.

BACKGROUND: Surgical services are preparing to scale up in areas affected by COVID-19. This study aimed to evaluate the association between preoperative SARS-CoV-2 testing and postoperative pulmonary complications in patients undergoing elective cancer surgery. METHODS: This international cohort study included adult patients undergoing elective surgery for cancer in areas affected by SARS-CoV-2 up to 19 April 2020. Patients suspected of SARS-CoV-2 infection before operation were excluded. The primary outcome measure was postoperative pulmonary complications at 30 days after surgery. Preoperative testing strategies were adjusted for confounding using mixed-effects models. RESULTS: Of 8784 patients (432 hospitals, 53 countries), 2303 patients (26.2 per cent) underwent preoperative testing: 1458 (16.6 per cent) had a swab test, 521 (5.9 per cent) CT only, and 324 (3.7 per cent) swab and CT. Pulmonary complications occurred in 3.9 per cent, whereas SARS-CoV-2 infection was confirmed in 2.6 per cent. After risk adjustment, having at least one negative preoperative nasopharyngeal swab test (adjusted odds ratio 0.68, 95 per cent confidence interval 0.68 to 0.98; P = 0.040) was associated with a lower rate of pulmonary complications. Swab testing was beneficial before major surgery and in areas with a high 14-day SARS-CoV-2 case notification rate, but not before minor surgery or in low-risk areas. To prevent one pulmonary complication, the number needed to swab test before major or minor surgery was 18 and 48 respectively in high-risk areas, and 73 and 387 in low-risk areas. CONCLUSION: Preoperative nasopharyngeal swab testing was beneficial before major surgery and in high SARS-CoV-2 risk areas. There was no proven benefit of swab testing before minor surgery in low-risk areas