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MeSH Disease


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    SARS-CoV-2 infection MESHD dynamics in Denmark, February through October 2020: Nature of the past epidemic and how it may develop in the future

    Authors: Steen Rasmussen; Michael Skytte Petersen; Niels Hoiby; Caroline O Buckee; Michael Mina; Thomas Taylor; Drew Birrenkott; Baptiste Vasey; Andrew Soltan; Tingting Zhu; David A Clifton; David W Eyre; Joseph M Gibbons; Wing Yiu J Lee; Meleri Jones; Dylan M Williams; Jonathan Lambourne; Marianna Fontana; - COVIDsortium Investigators; Daniel M Altmann; Rosemary Boyton; Mala K Maini; Aine McKnight; Timothy Brooks; Benny Chain; Mahdad Noursadeghi; James C Moon

    doi:10.1101/2020.11.04.20225912 Date: 2020-11-06 Source: medRxiv

    Background: There has long been uncertainty about the relative size of the "dark" numbers, the infected population sizes and the actual fatality rate in the COVID-19 MESHD pandemic and thus how the pandemic impacts the healthcare system. As a result it was initially predicted that the COVID-19 MESHD epidemic in Denmark would overwhelm the healthcare system and thus both the diagnosis and treatment of other hospital patients were compromised for an extended period. Aim: To develop a robust method for reliable estimation of the epidemic and the healthcare system load in Denmark, both retrospectively and prospectively. To do this a new pandemic simulation had to be developed that accounts for the size and the infection impact of the infectious incubating and asymptomatic TRANS infected individuals (dark numbers). Methods: Our epidemic simulation is based on a SEIRS (Susceptible - Exposed - Infected - Recovered - Susceptible) model, coupled to a simple healthcare model that also includes deaths outside hospital settings. The SEIRS model has separate assessments of asymptomatic TRANS and symptomatic cases with different immunological memories. The main data used for parameter estimation in the models are hospital and ICU occupations MESHD, death data, serological data of antibody SERO prevalence SERO from the onset through August 2020 together with hospital data and clinical data about the viral infection. Optimal model parameters are in part identified by Monte Carlo based Least Square Error methods while micro-outbreaks are modeled by noise and explored in Monte Carlo simulations. Estimates for the infected population sizes are obtained by using a quasi steady state method. Results: The age TRANS adjusted antibody SERO prevalence SERO in the general population in May 2020 was 1.37%, which yields a relative frequency of symptomatic and asymptomatic TRANS cases of 1 to 5.2. Due to the large asymptomatic TRANS population found, the actual mortality rate to date is 0.4%. However, with no behavioral and policy restrictions the COVID-19 MESHD death MESHD toll would have more than doubled the national average yearly deaths within a year. The transmission TRANS rate Ro was 5.4 in the initial free epidemic period, 0.4 in the lock-down period and 0.8 -1.0 in the successive re-opening periods through August 2020. The estimated infected population size July 15 to August 15 was 2,100 and 12,200 for October 1 - 20, 2020. The efficiency of the applied daily testing strategy for both periods are estimated to be 40\% of the PCR observable infected. Of more theoretical interest we demonstrate how the critical infection parameters for COVID-19 MESHD are tightly related in a so-called iso-symptomatic infection diagram. Conclusions: Our simulation may be useful if a major infection wave occurs in the winter season as it could make robust estimates both for the scale of an ongoing expanding epidemic and for the expected load on the healthcare system. Our simulation may also be useful to assess a future controlled epidemic, e.g. as a basis for evaluating different testing strategies based on estimated infected population sizes. Finally, we believe our simulation can be adjusted and scaled to other regions and countries, which we illustrate with Spain and the US.

    Longitudinal proteomic profiling of high-risk patients with COVID-19 MESHD reveals markers of severity and predictors of fatal disease MESHD

    Authors: Jack Gisby; Candice L Clarke; Nicholas Medjeral-Thomas; Talat H Malik; Artemis Papadaki; Paige M Mortimer; Norzawani B Buang; Shanice Lewis; Marie Pereira; Frederic Toulza; Ester Fagnano; Marie-Anne Mawhin; Emma E Dutton; Lunnathaya Tapeng; Paul Kirk; Jacques Behmoaras; Eleanor Sandhu; Stephen P McAdoo; Maria F Prendecki; Matthew C Pickering; Marina Botto; Michelle Willicombe; David C Thomas; James E. Peters; Benny Chain; Mahdad Noursadeghi; James C Moon

    doi:10.1101/2020.11.05.20223289 Date: 2020-11-06 Source: medRxiv

    End-stage kidney disease ( ESKD MESHD) patients are at high risk of severe COVID-19 MESHD. We performed dense serial blood SERO sampling in hospitalised and non-hospitalised ESKD MESHD patients with COVID-19 MESHD (n=256 samples from 55 patients) and used Olink immunoassays SERO to measure 436 circulating proteins. Comparison to 51 non-infected ESKD MESHD patients revealed 221 proteins differentially expressed in COVID-19 MESHD, of which 69.7% replicated in an independent cohort of 46 COVID-19 MESHD patients. 203 proteins were associated with clinical severity scores, including IL6, markers of monocyte recruitment (e.g. CCL2, CCL7), neutrophil activation (e.g proteinase-3) and epithelial injury MESHD (e.g. KRT19). Random Forests machine learning identified predictors of current or future severity such as KRT19, PARP1, PADI2, CCL7, and IL1RL1 (ST2). Survival analysis with joint models revealed 69 predictors of death MESHD including IL22RA1, CCL28, and the neutrophil-derived chemotaxin AZU1 (Azurocidin). Finally, longitudinal modelling with linear mixed models uncovered 32 proteins that display different temporal profiles in severe versus non-severe disease, including integrins and adhesion molecules. Our findings point to aberrant innate immune activation and leucocyte-endothelial interactions as central to the pathology of severe COVID-19 MESHD. The data from this unique cohort of high-risk individuals provide a valuable resource for identifying drug targets in COVID-19 MESHD.

    Adaptive responses to SARS-CoV-2 infection MESHD linked to accelerated aging measures predict adverse outcomes in patients with severe COVID-19 MESHD

    Authors: Alejandro Márquez-Salinas; Carlos A. Fermín-Martínez; Neftali Eduardo Antonio-Villa; Arsenio Vargas-Vázquez; Enrique C. Guerra; Alejandro Campos-Muñoz; Lilian Zavala-Romero; Roopa Mehta; Jessica Paola Bahena-López; Edgar Ortiz-Brizuela; María Fernanda González-Lara; Carla M Román-Montes; Bernardo A. Martínez-Guerra; Alfredo Ponce de Leon; José Sifuentes-Osornio; Luis Miguel Gutéirrez-Robledo; Carlos A Aguilar-Salinas; Omar Yaxmehen Bello-Chavolla; Mary Anna Venneri; Marco Gori; Maurizio Sanarico; Francis P Crawley; Uberto Pagotto; Flaminia Fanelli; Marco Mezzullo; Elena Dominguez-Garrido; Laura Planas-Serra; Agatha Schluter; Roger Colobran; Pere Soler-Palacin; Pablo Lapunzina; Jair Tenorio; - Spanish Covid HGE; Aurora Pujol; Maria Grazia Castagna; Marco Marcelli; Andrea M Isidori; - GEN-COVID Multicenter Study; Alessandra Renieri; Elisa Frullanti; Francesca Mari

    doi:10.1101/2020.11.03.20225375 Date: 2020-11-05 Source: medRxiv

    INTRODUCTION: Chronological age TRANS (CA) is a predictor of adverse COVID-19 MESHD outcomes; however, CA alone has not shown to be the better predictor of adverse outcomes in COVID-19 MESHD as it does not capture individual responses to SARS-CoV-2 infection MESHD. Here, we evaluated the influence of aging metrics PhenoAge and PhenoAccelAge on the adaptive responses to SARS-CoV-2 infection MESHD in hospitalized patients. METHODS: We assessed cases admitted to a COVID-19 MESHD reference center in Mexico City. PhenoAge and PhenoAccelAge were estimated using laboratory values at admission. Cox proportional hazards models were fitted to estimate risk for COVID-19 MESHD lethality and adverse outcomes (ICU admission, intubation, or death MESHD), and k-means clustering was performed to explore reproducible patterns of adaptive response to SARS-CoV-2 infection MESHD using PhenoAge components. RESULTS: We included 1069 subjects of whom 401 presented critical illness and 204 died. PhenoAge was a better predictor of adverse outcomes and lethality compared to CA and SpO2 and its predictive capacity was sustained for all age groups TRANS. Patients with responses associated PhenoAccelAge >0 had higher risk of death MESHD and critical illness compared to those who had values according to CA (log-rank p<0.001). Using unsupervised clustering we identified four adaptive responses to SARS-CoV-2 infection MESHD: 1) Inflammaging associated with CA, 2) adaptive metabolic dysfunction MESHD associated with cardio-metabolic comorbidities, 3) adaptive unfavorable hematological response, and 4) response associated with favorable outcomes. CONCLUSIONS: Adaptive responses related to accelerated aging metrics are linked to adverse COVID-19 MESHD outcomes and have unique and distinguishable features. PhenoAge is a better predictor of adverse outcomes compared to CA.

    Factors influencing the COVID-19 MESHD daily deaths peak across European countries

    Authors: Katarzyna Jablonska; Samuel Aballea; Mondher Toumi; R. Asaad Baksh; Stefania Bargagna; Nicole T Baumer; Ana Claudia Brandao; Angelo Carfi; Maria Carmona-Iragui; Brain A Chicoine; Sujay Ghosh; Monica Lakhanpaul; Coral Manso; Miguel-Angel Mayer; Maria del Carmen Ortega; Diego Real de Asua; Anne-Sophie Rebillat; Lauren Ashley Russell; Giuseppina Sgandurra; Diletta Valentini; Stephanie L Sherman; Andre Strydom; - on behalf of the T21RS COVID-19 Initiative; Flaminia Fanelli; Marco Mezzullo; Elena Dominguez-Garrido; Laura Planas-Serra; Agatha Schluter; Roger Colobran; Pere Soler-Palacin; Pablo Lapunzina; Jair Tenorio; - Spanish Covid HGE; Aurora Pujol; Maria Grazia Castagna; Marco Marcelli; Andrea M Isidori; - GEN-COVID Multicenter Study; Alessandra Renieri; Elisa Frullanti; Francesca Mari

    doi:10.1101/2020.11.04.20225656 Date: 2020-11-05 Source: medRxiv

    OBJECTIVES: The purpose of this study was to determine predictors of the height of COVID-19 MESHD daily deaths peak and time to the peak, in order to explain their variability across European countries. STUDY DESIGN: For 34 European countries, publicly available data were collected on daily numbers of COVID-19 MESHD deaths, population size, healthcare capacity, government restrictions and their timing, tourism and change in mobility during the pandemic. METHODS: Univariate and multivariate generalised linear models using different selection algorithms (forward, backward, stepwise and genetic algorithm) were analysed with height of COVID-19 MESHD daily deaths peak and time to the peak as dependent variables. RESULTS: The proportion of the population living in urban areas, mobility at the day of first reported death MESHD and number of infections when borders were closed were assessed as significant predictors of the height of COVID-19 MESHD daily deaths peak. Testing the model with variety of selection algorithms provided consistent results. Total hospital bed capacity, population size, number of foreign travellers and day of border closure, were found as significant predictors of time to COVID-19 MESHD daily deaths peak. CONCLUSIONS: Our analysis demonstrated that countries with higher proportions of the population living in urban areas, with lower reduction in mobility at the beginning of the pandemic, and countries which closed borders having more infected people experienced higher peak of COVID-19 MESHD deaths. Greater bed capacity, bigger population size and later border closure could result in delaying time to reach the deaths peak, whereas a high number of foreign travellers could accelerate it. Keywords: COVID-19 MESHD, mortality, healthcare capacity, modelling.

    COVID-19 MESHD surveillance - a descriptive study on data quality issues

    Authors: Cristina Costa-Santos; Ana Luisa Neves; Ricardo Correia; Paulo Santos; Matilde Monteiro-Soares; Alberto Freitas; Ines Ribeiro-Vaz; Teresa Henriques; Pedro Pereira Rodrigues; Altamiro Costa-Pereira; Ana Margarida Pereira; Joao Fonseca; Coral Manso; Miguel-Angel Mayer; Maria del Carmen Ortega; Diego Real de Asua; Anne-Sophie Rebillat; Lauren Ashley Russell; Giuseppina Sgandurra; Diletta Valentini; Stephanie L Sherman; Andre Strydom; - on behalf of the T21RS COVID-19 Initiative; Flaminia Fanelli; Marco Mezzullo; Elena Dominguez-Garrido; Laura Planas-Serra; Agatha Schluter; Roger Colobran; Pere Soler-Palacin; Pablo Lapunzina; Jair Tenorio; - Spanish Covid HGE; Aurora Pujol; Maria Grazia Castagna; Marco Marcelli; Andrea M Isidori; - GEN-COVID Multicenter Study; Alessandra Renieri; Elisa Frullanti; Francesca Mari

    doi:10.1101/2020.11.03.20225565 Date: 2020-11-05 Source: medRxiv

    Background: High-quality data is crucial for guiding decision making and practicing evidence-based healthcare, especially if previous knowledge is lacking. Nevertheless, data quality frailties have been exposed worldwide during the current COVID-19 MESHD pandemic. Focusing on a major Portuguese surveillance dataset, our study aims to assess data quality issues and suggest possible solutions. Methods: On April 27th 2020, the Portuguese Directorate-General of Health ( DGS MESHD) made available a dataset (DGSApril) for researchers, upon request. On August 4th, an updated dataset (DGSAugust) was also obtained. The quality of data was assessed through analysis of data completeness and consistency between both datasets. Results: DGSAugust has not followed the data format and variables as DGSApril and a significant number of missing data and inconsistencies were found (e.g. 4,075 cases from the DGSApril were apparently not included in DGSAugust). Several variables also showed a low degree of completeness and/or changed their values from one dataset to another (e.g. the variable underlying conditions had more than half of cases showing different information between datasets). There were also significant inconsistencies between the number of cases and deaths MESHD due to COVID-19 MESHD shown in DGSAugust and by the DGS MESHD reports publicly provided daily. Conclusions: The low quality of COVID-19 MESHD surveillance datasets limits its usability to inform good decisions and perform useful research. Major improvements in surveillance datasets are therefore urgently needed - e.g. simplification of data entry processes, constant monitoring of data, and increased training and awareness of health care providers - as low data quality may lead to a deficient pandemic control.

    Are we on the Right Way after 200 Days of COVID-19 MESHD in Morocco?

    Authors: Issam Bennis; Amina Nasri Sahraoui; Moulay Mustapha Alaoui

    id:202009.0576/v2 Date: 2020-11-05 Source:

    Historically, 2020 will be remembered as the year of COVID-19 MESHD pandemic, that limited people move and their social habits. This virus, becomes the first daily tracked public health burden that leads to more than 1,2 million deaths in the World by the end of October 2020, and until now no countries' best control strategies are cited as the example of long term success.Since March 2nd, 2020, date of the first SARS-COV-2 detected case in Morocco; many decisions were adopted as COVID-19 MESHD control strategies. If the first period of COVID-19 MESHD noticed a few numbers of cases and deaths MESHD, the second half from July is marked with an exponential increase of the number of cases and a spread in almost all provinces with more intensive care needs and more deaths. The policy analysis approach was followed as a method to define the pitfalls themes and to compare with the updated available international information any significant similarities or divergences. Thus, this report has the aim to present an overview of how the COVID-19 MESHD pandemic was dealt in Morocco during these 200 days, by highlighting some discrepancies with corrective advice provided in the first version of the manuscript to be confronted by a Moroccan health policymaker’s community, then to notice the decisions adopted during another one month by the MoH to get better future control results against COVID-19 MESHD.Unfortunately, despite the MoH decision to increase the diagnostic facilities for molecular tests, the overall number of laboratory tests do not go further than 21000 tests per day. The actual insidious transmission TRANS is a dangerous blind threat that dissipates the collaborating efforts, due to this limited number of confirmation and follows up tests.Accurate, standardised and up to ten times per day tests of molecular biology represented by RT-qPCR, to interpret results following the time progress of cycle quantification values is the primary action to be done to enhance the overall control strategy.

    Factors Associated with COVID-19 MESHD Deaths MESHD and Infections: A Cross Country Evidence

    Authors: Shafiun N Shimul; Fariha Kadir; Muhammad Ihsan- Ul- Kabir; Christoph Adler; Israfil Yalcin; Ralf Braun; Lili Kuo; Yung-Chun Chuang; Yu-Wei Cheng; Hung-Yu Sun; Markita P Landry; Sandra Ciesek; Gail Naughton; Martin Latterich; Philip A Mudd; Alfred Spada; Nicole Rindone; Denise Loizou; Lishomwa Ndhlovu; Raavi Gupta; Valerie Tulier-Laiwa; Maya Petersen; Diane V Havlir; - The CLIAHUB Consortium; Joseph DeRisi

    doi:10.1101/2020.11.02.20183236 Date: 2020-11-04 Source: medRxiv

    Though most of the countries across the world are crippled with COVID-19 MESHD, there has been substantial variations in death and infection MESHD rates. While some countries are overwhelmed, a few are spared. Little is known what explains this variation. This study attempts to understand the covariates of death MESHD and infection rates of COVID-19 MESHD across countries using multivariate regression analysis and least absolute shrinkage and selection operator (LASSO) regression. The OLS estimates show that the aging population and hospital bed per capita are significantly associated with the fatality rate of COVID-19 MESHD, while urbanization has a positive correlation with the inflection rate. The study suggests that an increase in health systems capacity can significantly reduce the fatality rates due to COVID-19 MESHD.

    Risk factors for outcomes of COVID-19 MESHD patients: an observational study of 795 572 patients in Russia

    Authors: Alexandra E. Demkina; Sergey Morozov; Anton V. Vladzymyrskyy; Vladislav G. Kljashtorny; Oksana I. Guseva; Pavel S. Pugachev; Oliya R. Artemova; Roman V. Reshetnikov; Victor A. Gombolevskiy; Maria N. Ryabinina; Dagrunn Waag Linchausen; Rebecca Jane Cox; Nina Langeland

    doi:10.1101/2020.11.02.20224253 Date: 2020-11-04 Source: medRxiv

    Background Several factors that could affect survival and clinical outcomes of COVID-19 MESHD patients require larger studies and closer attention. Objective To investigate the impact of factors including whether COVID-19 MESHD was clinically or laboratory-diagnosed, influenza vaccination, former or current tuberculosis MESHD, HIV, and other comorbidities on the hospitalized patients' outcomes. Design Observational nationwide cohort study. Patients All subjects, regardless of age TRANS, admitted to 4,251 Russian hospitals indexed in the Federal Register of COVID-19 MESHD patients between March 26, 2020, and June 3, 2020. All included patients for which complete clinical data were available were divided into two cohorts, with laboratory- and clinically verified COVID-19 MESHD. Measurements We analyzed patients' age TRANS and sex, COVID-19 MESHD ICD-10 code, the length of the hospital stay, and whether they required ICU treatment or invasive mechanical ventilation. The other variables for analysis were: verified diagnosis of pulmonary disease MESHD, cardiovascular disease MESHD, diseases of the endocrine system MESHD, cancer MESHD/ malignancy, HIV, tuberculosis MESHD, and the data on influenza vaccination in the previous six months. Results This study enrolled 705,572 COVID-19 MESHD patients aged TRANS from 0 to 121 years, 50.4% females TRANS. 164,195 patients were excluded due to no confirmed COVID-19 MESHD (n=143,357) or insufficient MESHD and invalid clinical data (n=20,831). 541,377 participants were included in the study, 413,950 (76.5%) of them had laboratory-verified COVID-19 MESHD, and 127,427 patients (23.5%) with the clinical verification. Influenza vaccination reduced the risk of transfer to the ICU (OR 0.76), mechanical ventilation requirement (OR 0.74), and the risk of death (HR 0.77). TB increased the mortality risk (HR 1.74) but reduced the likelihood of transfer to the ICU (OR 0.27). HIV MESHD comorbidity significantly increased the risks of transfer to the ICU (OR 2.46) and death MESHD (HR 1.60). Patients with the clinically verified COVID-19 MESHD had a shorter duration of hospital stay (HR 1.45) but a higher risk of mortality (HR 1.08) and the likelihood of being ventilated (OR 1.36). According to the previously published data, age TRANS, male TRANS sex, endocrine disorders MESHD, and cardiovascular diseases MESHD increased the length of hospital stay, the risk of death MESHD, and transfer to the ICU. Limitations The study did not include a control group of subjects with no COVID-19 MESHD. Because of that, some of the identified factors could not be specific for COVID-19 MESHD. Conclusions Influenza vaccination could reduce the severity of the hospitalized patients' clinical outcomes, including mortality, regardless of age TRANS, social, and economic group. The other factors considered in the study did not reduce the assessed risks, but we observed several non-trivial associations that may optimize the management of COVID-19 MESHD patients.

    Modelling and Forecasting The Number of Confirmed Cases TRANS and Deaths from COVID-19 MESHD Pandemic in USA from April 12th to May 21st, 2020

    Authors: Babak Jamshidi; Shahriar Jamshidi Zargaran; Amir Talaei-Khoei; Mohsen Kakavandi; Lian Chen; Sara K Huston; Rajesh Srinivasan; Carrie A Redlich; Albert I Ko; Jeremy S Faust; Howard P Forman; Harlan M Krumholz

    doi:10.1101/2020.10.30.20223412 Date: 2020-11-04 Source: medRxiv

    In the present paper, our objective is to forecast the spread of the pandemic of COVID-19 MESHD in terms of the number of confirmed cases TRANS and deaths MESHD. The paper is based on a two-part to model the time series of the daily relative increments whose second part solely models the pattern of the death rate. All the simulations and calculations have been done in MatLab R2015b, and the average curves and confidence intervals are calculated based on 100 simulations of the fitted models. Our results establish that the cumulative number of confirmed cases TRANS reach 1464729 cases on 21 May 2020, with 80% confidence interval of [1375362 1540424], and the number of new confirmed cases TRANS decreases to the interval [12801 22578] with the probability of 80% (the point prediction is equal to 17551) on 21 May 2020. Finally, we forecast that the cumulative number of deaths from 18747 cases on 11 April increases to around 47000 cases on 21 May.

    Precision shielding for COVID-19 MESHD: metrics of assessment and feasibility of deployment

    Authors: John Ioannidis; Dinesh Prasad Sahu; Durgesh Prasad Sahoo; Binod Kumar Patro; Arvind Kumar Singh; Sachidananda Mohanty; INES LOPEZ-ALONSO; TAMARA HERMIDA; ANA ENRIQUEZ; HELENA GIL; BELEN ALONSO; SARA IGLESIAS; BEATRIZ SUAREZ-ALVAREZ; VICTORIA ALVAREZ; ELIECER COTO; Thomas Kehrer; Nicolas Galarce; Leonardo Almonacid; Jorge Levican; Harm van Bakel; Adolfo Garcia-Sastre; Rafael A. Medina; Lindsey J Waddoups; Lisa J Weaver; Elizabeth Zimmerman; Robert Paine III

    doi:10.1101/2020.11.01.20224147 Date: 2020-11-04 Source: medRxiv

    Background. The ability to preferentially protect high-groups in COVID-19 MESHD is hotly debated. Here, the aim is to present simple metrics of such precision shielding of people at high-risk of death MESHD after infection by SARS-CoV-2; demonstrate how they can estimated; and examine whether precision shielding was successfully achieved in the first COVID-19 MESHD wave. Methods. The shielding ratio, S, is defined as the ratio of prevalence SERO of infection among people at a high-risk group versus among people in a low-risk group. The contrasted risk groups examined here are according to age TRANS (>=70 versus <70 years), and institutionalized (nursing home) setting. For age TRANS-related precision shielding, data were used from large seroprevalence SERO studies with separate prevalence SERO data for elderly TRANS versus non- elderly TRANS and with at least 1000 assessed people >=70 years old. For setting-related precision shielding, data were analyzed from 10 countries where information was available on numbers of nursing home residents, proportion of nursing home residents among COVID-19 MESHD deaths, and overall population infection fatality rate. Findings. Across 17 seroprevalence SERO studies, the shielding ratio S for elderly TRANS versus non- elderly TRANS varied between 0.4 (substantial shielding) and 1.6 (substantial inverse protection, i.e. low-risk people being protected more than high-risk people). Five studies in USA all yielded S=0.4-0.8, consistent with some shielding being achieved, while two studies in China yielded S=1.5-1.6, consistent with inverse protection. Assuming 25% infection fatality rate among nursing home residents, S values for nursing home residents ranged from 0.07 to 3.1. The best shielding was seen in South Korea (S=0.07) and modest shielding was achieved in Israel, Slovenia, Germany, and Denmark. No shielding was achieved in Hungary and Sweden. In Belgium (S=1.9), UK (S=2.2) and Spain (S=3.1), nursing home residents were far more frequently infected that the rest of the population. Interpretation. The experience from the first wave of COVID-19 MESHD suggests that different locations and settings varied markedly in the extent to which they protected high-risk groups. Both effective precision shielding and detrimental inverse protection can happen in real-life circumstances. COVID-19 MESHD interventions should seek to achieve maximal precision shielding.

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