Newborn Screening in a Pandemic-Lessons Learned.

The COVID-19 pandemic affected many essential aspects of public health, including newborn screening programs (NBS). Centers reported missing cases of inherited metabolic disease as a consequence of decreased diagnostic process quality during the pandemic. A number of problems emerged at the start of the pandemic, but from the beginning, solutions began to be proposed and implemented. Contingency plans were arranged, and these are reviewed and described in this article. Staff shortage emerged as an important issue, and as a result, new work schedules had to be implemented. The importance of personal protective equipment and social distancing also helped avoid disruption. Staff became stressed, and this needed to be addressed. The timeframe for collecting bloodspot samples was adapted in some cases, requiring reference ranges to be modified. A shortage of essential supplies and protective equipment was evident, and laboratories described sharing resources in some situations. The courier system had to be adapted to make timely and safe transport possible. Telemedicine became an essential tool to enable communication with patients, parents, and medical staff. Despite these difficulties, with adaptations and modifications, some centers evaluated candidate conditions, continued developments, or began new NBS. The pandemic can be regarded as a stress test of the NBS under real-world conditions, highlighting critical aspects of this multidisciplinary system and the need for establishing local, national, and global strategies to improve its robustness and reliability in times of shortage and overloaded national healthcare systems.

Protection provided by vaccination, booster doses and previous infection against covid-19 infection, hospitalisation or death over time in Czechia.

Studies demonstrating the waning of post-vaccination and post-infection immunity against covid-19 generally analyzed a limited range of vaccines or subsets of populations. Using Czech national health data from the beginning of the covid-19 pandemic till November 20, 2021 we estimated the risks of reinfection, breakthrough infection, hospitalization and death by a Cox regression adjusted for sex, age, vaccine type and vaccination status. Vaccine effectiveness against infection declined from 87% at 0-2 months after the second dose to 53% at 7-8 months for BNT162b2 vaccine, from 90% at 0-2 months to 65% at 7-8 months for mRNA-1273, and from 83% at 0-2 months to 55% at 5-6 months for the ChAdOx1-S. Effectiveness against hospitalization and deaths declined by about 15% and 10%, respectively, during the first 6-8 months. Boosters (third dose) returned the protection to the levels observed shortly after dose 2. In unvaccinated, previously infected individuals the protection against infection declined from 97% after 2 months to 72% at 18 months. Our results confirm the waning of vaccination-induced immunity against infection and a smaller decline in the protection against hospitalization and death. Boosting restores the original vaccine effectiveness. Post-infection immunity also decreases over time.

Protection by Vaccines and Previous Infection Against the Omicron Variant of Severe Acute Respiratory Syndrome Coronavirus 2.

BACKGROUND: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evades immunity conferred by vaccines and previous infections. METHODS: We used a Cox proportional hazards model and a logistic regression on individual-level population-wide data from the Czech Republic to estimate risks of infection and hospitalization, including severe states. RESULTS: A recent (≤2 months) full vaccination reached vaccine effectiveness (VE) of 43% (95% confidence interval [CI], 42%-44%) against infection by Omicron compared to 73% (95% CI, 72%-74%) against Delta. A recent booster increased VE to 56% (95% CI, 55%-56%) against Omicron infection compared to 90% (95% CI, 90%-91%) for Delta. The VE against Omicron hospitalization of a recent full vaccination was 45% (95% 95% CI, 29%-57%), with a recent booster 87% (95% CI, 84%-88%). The VE against the need for oxygen therapy due to Omicron was 57% (95% CI, 32%-72%) for recent vaccination, 90% (95% CI, 87%-92%) for a recent booster. Postinfection protection against Omicron hospitalization declined from 68% (95% CI, 68%-69%) at ≤6 months to 13% (95% CI, 11%-14%) at >6 months after a previous infection. The odds ratios for Omicron relative to Delta were 0.36 (95% CI, .34-.38) for hospitalization, 0.24 (95% CI, .22-.26) for oxygen, and 0.24 (95% CI, .21-.28) for intensive care unit admission. CONCLUSIONS: Recent vaccination still brings substantial protection against severe outcome for Omicron.

Sharing datasets of the COVID-19 epidemic in the Czech Republic.

At the time of the COVID-19 pandemic, providing access to data (properly optimised regarding personal data protection) plays a crucial role in providing the general public and media with up-to-date information. Open datasets also represent one of the means for evaluation of the pandemic on a global level. The primary aim of this paper is to describe the methodological and technical framework for publishing datasets describing characteristics related to the COVID-19 epidemic in the Czech Republic (epidemiology, hospital-based care, vaccination), including the use of these datasets in practice. Practical aspects and experience with data sharing are discussed. As a reaction to the epidemic situation, a new portal COVID-19: Current Situation in the Czech Republic (https://onemocneni-aktualne.mzcr.cz/covid-19) was developed and launched in March 2020 to provide a fully-fledged and trustworthy source of information for the public and media. The portal also contains a section for the publication of (i) public open datasets available for download in CSV and JSON formats and (ii) authorised-access-only section where the authorised persons can (through an online generated token) safely visualise or download regional datasets with aggregated data at the level of the individual municipalities and regions. The data are also provided to the local open data catalogue (covering only open data on healthcare, provided by the Ministry of Health) and to the National Catalogue of Open Data (covering all open data sets, provided by various authorities/publishers, and harversting all data from local catalogues). The datasets have been published in various authentication regimes and widely used by general public, scientists, public authorities and decision-makers. The total number of API calls since its launch in March 2020 to 15 December 2020 exceeded 13 million. The datasets have been adopted as an official and guaranteed source for outputs of third parties, including public authorities, non-governmental organisations, scientists and online news portals. Datasets currently published as open data meet the 3-star open data requirements, which makes them machine-readable and facilitates their further usage without restrictions. This is essential for making the data more easily understandable and usable for data consumers. In conjunction with the strategy of the MH in the field of data opening, additional datasets meeting the already implemented standards will be also released, both on COVID-19 related and unrelated topics.

Control Centre for Intensive Care as a Tool for Effective Coordination, Real-Time Monitoring, and Strategic Planning During the COVID-19 Pandemic.

In the Czech Republic, the strategic data-based and organizational support for individual regions and for providers of acute care at the nationwide level is coordinated by the Ministry of Health. At the beginning of the COVID-19 pandemic, the country needed to very quickly implement a system for the monitoring, reporting, and overall management of hospital capacities. The aim of this viewpoint is to describe the purpose and basic functions of a web-based application named "Control Centre for Intensive Care," which was developed and made available to meet the needs of systematic online technical support for the management of intensive inpatient care across the Czech Republic during the first wave of the pandemic in spring 2020. Two tools of key importance are described in the context of national methodology: one module for regular online updates and overall monitoring of currently free capacities of intensive care in real time, and a second module for online entering and overall record-keeping of requirements on medications for COVID-19 patients. A total of 134 intensive care providers and 927 users from hospitals across all 14 regions of the Czech Republic were registered in the central Control Centre for Intensive Care database as of March 31, 2021. This web-based application enabled continuous monitoring and decision-making during the mass surge of critical care from autumn 2020 to spring 2021. The Control Center for Intensive Care has become an indispensable part of a set of online tools that are employed on a regular basis for crisis management at the time of the COVID-19 pandemic.

ACE I/D polymorphism in Czech first-wave SARS-CoV-2-positive survivors.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rapidly spread from China in 2019/2020 to all continents. Significant geographical and ethnic differences were described, and host genetic background seems to be important for the resistance to and mortality of COVID-19. Angiotensin-converting enzyme (ACE) insertion/deletion (I/D) polymorphism (rs4646994) is one of the candidates with the potential to affect infection symptoms and mortality. METHODS: In our study, we successfully genotyped 408 SARS-CoV-2-positive COVID-19 survivors (163 asymptomatic and 245 symptomatic) and compared them with a population-based DNA bank of 2,559 subjects. RESULTS: The frequency of ACE I/I homozygotes was significantly increased in COVID-19 patients compared with that in controls (26.2% vs. 21.2%; P = 0.02; OR [95% CI] = 1.55 [1.17-2.05]. Importantly, however, the difference was driven just by the symptomatic subjects (29.0% vs. 21.2% of the I/I homozygotes; P = 0.002; OR [95% CI] = 1.78 [1.22-2.60]). The genotype distribution of the ACE genotypes was almost identical in population controls and asymptomatic SARS-CoV-2-positive patients (P = 0.76). CONCLUSIONS: We conclude that ACE I/D polymorphism could have the potential to predict the severity of COVID-19, with I/I homozygotes being at increased risk of symptomatic COVID-19.

Covidogram as a simple tool for predicting severe course of COVID-19: population-based study.

OBJECTIVES: COVID-19 might either be entirely asymptomatic or manifest itself with a large variability of disease severity. It is beneficial to identify early patients with a high risk of severe course. The aim of the analysis was to develop a prognostic model for the prediction of the severe course of acute respiratory infection. DESIGN: A population-based study. SETTING: Czech Republic. PARTICIPANTS: The first 7455 consecutive patients with COVID-19 who were identified by reverse transcription-PCR testing from 1 March 2020 to 17 May 2020. PRIMARY OUTCOME: Severe course of COVID-19. RESULT: Of a total 6.2% of patients developed a severe course of COVID-19. Age, male sex, chronic kidney disease, chronic obstructive pulmonary disease, recent history of cancer, chronic heart failure, acid-related disorders treated with proton-pump inhibitors and diabetes mellitus were found to be independent negative prognostic factors (Area under the ROC Curve (AUC) was 0.893). The results were visualised by risk heat maps, and we called this diagram a 'covidogram'. Acid-related disorders treated with proton-pump inhibitors might represent a negative prognostic factor. CONCLUSION: We developed a very simple prediction model called 'covidogram', which is based on elementary independent variables (age, male sex and the presence of several chronic diseases) and represents a tool that makes it possible to identify-with a high reliability-patients who are at risk of a severe course of COVID-19. Obtained results open clinically relevant question about the role of acid-related disorders treated by proton-pump inhibitors as predictor for severe course of COVID-19.

Complex Reporting of Coronavirus Disease (COVID-19) Epidemic in the Czech Republic: Use of Interactive Web-Based Application in Practice

BACKGROUND: The beginning of the COVID-19 epidemic dates back to December 31, 2019, when first cases were reported in the People's Republic of China. In the Czech Republic, the first three cases of infection with the novel coronavirus were confirmed on March 1, 2020. The joint effort of state authorities and researchers gave rise to a unique team, which combines methodical knowledge of real-world processes with the know-how needed for effective processing, analysis and online visualization of data. OBJECTIVE: Due to an urgent need for a tool which would make it possible to present important reports, and which would be based on valid data sources only, a team of government experts together with researchers focused on the design and development of a web application intended to provide a regularly updated overview of COVID-19 epidemiology in the Czech Republic to the general public. METHODS: The CRISP-DM (CRoss-Industry Standard Process for Data Mining) standardized methodology for knowledge mining from database structures was chosen for the complex solution of analytical processing and visualization of data, which provides validated information on the COVID-19 epidemic across the Czech Republic. Great emphasis was put on the understanding and a correct implementation of all six steps (business understanding, data understanding, data preparation, modelling, evaluation and deployment) needed in the process, including the infrastructure of a nationwide information system, the methodological setting of communication channels between all involved stakeholders, as well as data collection, processing, analysis, validation and visualization. RESULTS: The web-based overview of the current spread of COVID-19 in the Czech Republic has been developed as an online platform providing a set of outputs in the form of tables, graphs and maps intended for the general public. On March 12, 2020, the first version of the web portal, containing fourteen overviews divided into five topical sections, was released. The web portal's primary objective is to publish a well-arranged visualization and clear explanation of basic information consisting of the overall numbers of performed tests, confirmed cases of COVID-19, and COVID-19-related deaths together with the daily and cumulative overviews of COVID-19-positive persons, performed tests, location and country of infection of COVID-19-positive persons, hospitalizations of COVID-19 patients, and distribution of personal protective equipment. CONCLUSIONS: The online interactive overview of the current spread of COVID-19 in the Czech Republic was launched on March 11, 2020, and has immediately become the primary communication channel employed by the health care sector to present the current situation regarding the COVID-19 epidemic. This complex reporting of the coronavirus disease epidemic in the Czech Republic also shows an effective way how to interconnect knowledge held by various specialists, such as regional and national methodology experts, who report positive cases of the disease on a daily basis, with knowledge held by developers of central registries, analysts, developers of web applications and leadership in the health care sector. CLINICALTRIAL: