Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations.

Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1-4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models' predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models' forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models' past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models' forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models' forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models' forecasts of deaths (N=763 predictions from 20 models). Across a 1-4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. Funding: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 (https://www.nfdi4health.de/task-force-covid-19-2) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).

Nirmatrelvir/ritonavir treatment in SARS-CoV-2 positive kidney transplant recipients - a case series with four patients.

BACKGROUND: Despite vaccination coronavirus disease 2019 (COVID-19)-associated mortality caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains high in kidney transplant recipients. Nirmatrelvir is a protease inhibitor with activity against SARS-CoV-2. Nirmatrelvir reduces the risk for mortality and hospitalization, which is approved for treating adults at risk for severe disease. Nirmatrelvir is metabolized by the cytochrome P-450 (CYP) 3A4 isozyme CYP3A4 and is therefore co-administered with the irreversible CYP3A4 inhibitor ritonavir, which results in a drug interaction with tacrolimus. A limited number of patients with nirmatrelvir/ritonavir and tacrolimus therapy after kidney transplantation have been reported to date. It has been reported that tacrolimus was paused during the five-day nirmatrelvir/ritonavir therapy and subtherapeutic tacrolimus levels were observed after finishing nirmatrelvir/ritonavir in two patients. Therefore, optimization of tacrolimus dosing is urgently needed in transplant recipients receiving nirmatrelvir/ritonavir treatment. CASE PRESENTATION: Here, we present our first-hand experience with four patients receiving tacrolimus therapy following kidney transplantation and nirmatrelvir/ritonavir therapy due to COVID-19. Tacrolimus was paused during nirmatrelvir/ritonavir therapy in all patients, which resulted in stable therapeutic tacrolimus levels. Tacrolimus was continued directly after finishing nirmatrelvir/ritonavir to avoid subtherapeutic levels in the first patient treated. This patient received his usual tacrolimus maintenance dose, which resulted in toxic levels. Based on this observation, tacrolimus therapy was continued 24 h after finishing nirmatrelvir/ritonavir treatment at a reduced dose in the subsequent patients. In these patients, therapeutic to supratherapeutic tacrolimus levels were observed despite the therapeutic break and dose reduction. DISCUSSION AND CONCLUSIONS: Based on altered CYP3A4 metabolism, tacrolimus levels have to be closely monitored after treatment with nirmatrelvir/ritonavir. Our study suggests that tacrolimus treatment should be paused during nirmatrelvir/ritonavir medication and be continued 24 h after completing nirmatrelvir/ritonavir therapy at a reduced dose and under close monitoring. Based on the limited number of patients in this study, results must be interpreted with caution.

Decision-support systems for ambulatory care, including pandemic requirements: using mathematically optimized solutions.

BACKGROUND: The healthcare sector poses many strategic, tactic and operational planning questions. Due to the historically grown structures, planning is often locally confined and much optimization potential is foregone. METHODS: We implemented optimized decision-support systems for ambulatory care for four different real-world case studies that cover a variety of aspects in terms of planning scope and decision support tools. All are based on interactive cartographic representations and are being developed in cooperation with domain experts. The planning problems that we present are the problem of positioning centers for vaccination against Covid-19 (strategical) and emergency doctors (strategical/tactical), the out-of-hours pharmacy planning problem (tactical), and the route planning of patient transport services (operational). For each problem, we describe the planning question, give an overview of the mathematical model and present the implemented decision support application. RESULTS: Mathematical optimization can be used to model and solve these planning problems. However, in order to convince decision-makers of an alternative solution structure, mathematical solutions must be comprehensible and tangible. Appealing and interactive decision-support tools can be used in practice to convince public health experts of the benefits of an alternative solution. The more strategic the problem and the less sensitive the data, the easier it is to put a tool into practice. CONCLUSIONS: Exploring solutions interactively is rarely supported in existing planning tools. However, in order to bring new innovative tools into productive use, many hurdles must be overcome.

Quantifying Covid19-vaccine location strategies for Germany.

BACKGROUND: Vaccines are an important tool to limit the health and economic damage of the Covid-19 pandemic. Several vaccine candidates already provided promising effectiveness data, but it is crucial for an effective vaccination campaign that people are willing and able to get vaccinated as soon as possible. Taking Germany as an example, we provide insights of using a mathematical approach for the planning and location of vaccination sites to optimally administer vaccines against Covid-19. METHODS: We used mathematical programming for computing an optimal selection of vaccination sites out of a given set (i.e., university hospitals, health department related locations and general practices). Different patient-to-facility assignments and doctor-to-facility assignments and different constraints on the number of vaccinees per site or maximum travel time are used. RESULTS: In order to minimize the barriers for people to get vaccinated, i.e., limit the one-way travel journey (airline distance) by around 35 km for 75% of the population (with a maximum of 70 km), around 80 well-positioned facilities can be enough. If only the 38 university hospitals are being used, the 75% distance increases to around 50 km (with a maximum of 145 km). Using all 400 health departments or all 56 000 general practices can decrease the journey length significantly, but comes at the price of more required staff and possibly wastage of only partially used vaccine containers. CONCLUSIONS: In the case of free assignments, the number of required physicians can in most scenarios be limited to 2 000, which is also the minimum with our assumptions. However, when travel distances for the patients are to be minimized, capacities of the facilities must be respected, or administrative assignments are prespecified, an increased number of physicians is unavoidable.

Therapy with lopinavir/ritonavir and hydroxychloroquine is associated with acute kidney injury in COVID-19 patients.

BACKGROUND: Acute kidney injury (AKI) is an independent risk factor for mortality, which affects about 5% of hospitalized coronavirus disease-2019 (COVID-19) patients and up to 25-29% of severely ill COVID-19 patients. Lopinavir/ritonavir and hydroxychloroquine show in vitro activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and have been used for the treatment of COVID-19. Both, lopinavir and hydroxychloroquine are metabolized by cytochrome P450 (CYP) 3A4. The impact of a triple therapy with lopinavir/ritonavir and hydroxychloroquine (triple therapy) on kidney function in COVID-19 is currently not known. METHODS: We retrospectively analyzed both non-ICU and ICU patients with COVID-19 receiving triple therapy for the incidence of AKI. Patients receiving standard therapy served as a control group. All patients were hospitalized at the University Hospital of Freiburg, Germany, between March and April 2020. A matched-pair analysis for the National Early Warning Score (NEWS) 2 was performed to control for the severity of illness among non-intensive care unit (ICU) patients. RESULTS: In non-ICU patients, the incidence of AKI was markedly increased following triple therapy (78.6% vs. 21.4% in controls, p = 0.002), while a high incidence of AKI was observed in both groups of ICU patients (triple therapy: 80.0%, control group: 90.5%). ICU patients treated with triple therapy showed a trend towards more oliguric or anuric kidney injury. We also observed a linear correlation between the duration of the triple therapy and the maximum serum creatinine level (p = 0.004, R2 = 0.276, R = 0.597). CONCLUSION: Triple therapy is associated with an increase in the incidence of AKI in non-ICU COVID-19 patients. The underlying mechanisms may comprise a CYP3A4 enzyme interaction, and may be relevant for any future therapy combining hydroxychloroquine with antiviral agents.

Toward Understanding COVID-19 Recovery: National Institutes of Health Workshop on Postacute COVID-19.

Over the past year, the SARS-CoV-2 pandemic has swept the globe, resulting in an enormous worldwide burden of infection and mortality. However, the additional toll resulting from long-term consequences of the pandemic has yet to be tallied. Heterogeneous disease manifestations and syndromes are now recognized among some persons after their initial recovery from SARS-CoV-2 infection, representing in the broadest sense a failure to return to a baseline state of health after acute SARS-CoV-2 infection. On 3 to 4 December 2020, the National Institute of Allergy and Infectious Diseases, in collaboration with other Institutes and Centers of the National Institutes of Health, convened a virtual workshop to summarize existing knowledge on postacute COVID-19 and to identify key knowledge gaps regarding this condition.

Experiences and Short-Term Outcomes of Kidney Transplantation During the Coronavirus Disease 2019 Pandemic From a Medium-Volume Transplantation and Superregional Coronavirus Disease 2019 Treatment Center.

INTRODUCTION: The coronavirus, which first appeared in 2019, developed into a pandemic during 2020. It remains unclear to what extent the pandemic endangers the safety of kidney transplantation programs. In this study, we evaluated the short-term outcomes of our patients receiving a kidney transplant during the first phase and compared them with patients who received a kidney transplant immediately before the coronavirus pandemic. MATERIALS AND METHODS: Our retrospective study includes 34 kidney transplant recipients between October 1, 2019, and April 30, 2020. Nineteen patients from the phase immediately prior to the first coronavirus wave (pre-corona group), and 15 patients from the phase of the first coronavirus wave (corona group) were studied. We retrospectively evaluated demographic data, postoperative short-term outcomes and complications, immunosuppression regime, coronavirus infection status, and behavior during the first phase of the pandemic. RESULTS: There were no differences between the 2 groups regarding short-term outcomes and postoperative complications or in immunosuppressive medication. After the introduction of intensified hygienic conditions and routine swabs prior to transplantation, no nosocomial SARS-CoV-2 infections occurred. In the outpatient setting, none of the patients developed a SARS-CoV-2 infection. The majority of patients performed voluntary quarantine. CONCLUSIONS: The short-term outcomes after kidney transplantation during the first phase of the coronavirus pandemic were comparable to pre-pandemic patients, and no SARS-CoV-2-associated death or transplant failure occurred in our small cohort. We considered patient compliance with hygiene and self-isolation measures very high. Nevertheless, in further phases of the pandemic, the continuation of the living kidney donation program must be critically evaluated.

Psychosocial emergency care in times of COVID-19: the Essen University Hospital concept for corona-infected patients, their relatives, and medical staff.

Due to the SARS CoV-2-virus (COVID-19), anxiety, distress, and insecurity occur more frequently. In particular, infected individuals, their relatives, and medical staff face an increased risk of high psychological distress as a result of the ongoing pandemic. Thus, structured psychosocial emergency concepts are needed. The University hospital of Essen has taken up this challenge by creating the PEC concept to reduce psychosocial long-term consequences for infected patients, relatives, and medical staff at the university hospital. The concept includes professional medical as well as psychological support to convey constructive coping strategies and the provision of adequate tools such as the low-threshold online training program (CoPE It), which is accessible via the webpage www.cope-corona.de .

Techniques, Methods, and Dissemination of Community-Based Psychological Support Strategies in Times of the COVID-19 Pandemic.

In times of the coronavirus pandemic caused by SARS-CoV-2 psychological support needs to meet certain requirements. Due to the lockdown in many countries of the world, the every-day activities of millions of people are reduced to a minimum. This may cause increased psychosomatic symptoms in persons with pre-existing mental illnesses, and additionally raises new challenges for the general population. As a result of the current contact restrictions, access to psychotherapy is further complicated. To guarantee the best possible care under the given conditions, we developed the CoPE (Coping with Corona: Extended Psychosomatic care in Essen) concept. CoPE is delivered by telephone or video calls as well as online contents. The materials presented at our webpage www.cope-corona.de aim to easily reach citizens affected by symptoms such as worries, depression or anger and let them receive readily understandable expert knowledge and training in basic self-help methods.