Molecular surveillance was widely used during the COVID-19 pandemic to detect rapidly emerging variants and monitor the transmission of SARS-CoV-2 within communities. In 2021, the Czech COVID-19 Genomics Consortium (COG-CZ) was set up to coordinate a new SARS-CoV-2 molecular surveillance network. In the Czech Republic, molecular surveillance employed whole genome sequencing (WGS) and variant discrimination polymerase chain reaction (VD-PCR) on samples collected through passive, active and sentinel surveillance. All WGS data was uploaded to GISAID and the PANGO lineages used by GISAID were compared to the main variants determined by VD-PCR. To assess the effectiveness and reliability of the gathered data in adapting pandemic responses, the capabilities and turnaround times of the molecular surveillance methods are evaluated. VD-PCR results were available within 48 h of sample collection for 81.5% of cases during the Delta/Omicron transition. WGS enabled the detection of low-frequency novel variants in infection clusters. WGS surveillance showed there was community spread of AY.20.1, a variant that gained novel mutations within the Czech Republic. Molecular surveillance informed the implementation of public health measures; temporal comparisons of restrictions and outcomes are described. Further areas for improvement have been identified for monitoring and managing future pandemics.

• Keywords
• Czech Republic, Molecular surveillance, SARS-CoV-2 variants, Variant discrimination PCR,
• MeSH
• COVID-19 * epidemiology   virology   MeSH
• Genome, Viral MeSH
• Humans MeSH
• Pandemics MeSH
• SARS-CoV-2 * genetics   isolation & purification   MeSH
• Whole Genome Sequencing MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Czech Republic epidemiology   MeSH

Rotations of schoolchildren were considered as a non-pharmacological intervention in the COVID-19 pandemic. This study investigates the impact of different rotation and testing schedules.We built an agent-based model of interactions among pupils and teachers based on a survey in an elementary school in Prague, Czechia. This model contains 624 schoolchildren and 55 teachers and about 27 thousands social contacts in 10 layers. The layers reflect different types of contacts (classroom, cafeteria, etc.) in the survey. On this multi-graph structure we run a modified SEIR model of covid-19 infection. The parameters of the model are calibrated on data from the outbreak in the Czech Republic in spring 2020. Weekly rotations of in-class and distance learning are an effective preventative measure in schools reducing the spread of covid-19 by 75-81% . Antigen testing twice a week or PCR once a week significantly reduces infections even when using tests with a lower sensitivity. The structure of social contacts between pupils and teachers strongly influences the transmission. While the density of contact graphs for older pupils is 1.5 times higher than for younger pupils, the teachers' network is an order of magnitude denser. Teachers moreover act as bridges between groups of children, responsible for 14-18% of infections in the secondary school compared to 8-11% in the primary school. Weekly rotations with regular testing are a highly effective non-pharmacological intervention for the prevention of covid-19 spread in schools and a way to keep schools open during an epidemic.

• MeSH
• COVID-19 * MeSH
• Child MeSH
• Disease Outbreaks MeSH
• Humans MeSH
• Pandemics prevention & control   MeSH
• Surveys and Questionnaires MeSH
• Schools MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

We present a novel approach to estimate the time-varying ascertainment rate in almost real-time, based on the surveillance of positively tested infectious and hospital admission data. We also address the age dependence of the estimate. The ascertainment rate estimation is based on the Bayes theorem. It can be easily calculated and used (i) as part of a mechanistic model of the disease spread or (ii) to estimate the unreported infections or changes in their proportion in almost real-time as one of the early-warning signals in case of undetected outbreak emergence. The paper also contains a case study of the COVID-19 epidemic in the Czech Republic. The case study demonstrates the usage of the ascertainment rate estimate in retrospective analysis, epidemic monitoring, explanations of differences between waves, usage in the national Anti-epidemic system, and monitoring of the effectiveness of non-pharmaceutical interventions on Czech nationwide surveillance datasets. The Czech data reveal that the probability of hospitalization due to SARS-CoV-2 infection for the senior population was 12 times higher than for the non-senior population in the monitored period from the beginning of March 2020 to the end of May 2021. In a mechanistic model of COVID-19 spread in the Czech Republic, the ascertainment rate enables us to explain the links between all basic compartments, including new cases, hospitalizations, and deaths.

• MeSH
• Bayes Theorem MeSH
• COVID-19 * epidemiology   MeSH
• Hospitalization MeSH
• Communicable Diseases * MeSH
• Humans MeSH
• Retrospective Studies MeSH
• SARS-CoV-2 MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Czech Republic epidemiology   MeSH

BACKGROUND: Contact tracing is one of the most effective non-pharmaceutical interventions in the COVID-19 pandemic. This study uses a multi-agent model to investigate the impact of four types of contact tracing strategies to prevent the spread of COVID-19. METHODS: In order to analyse individual contact tracing in a reasonably realistic setup, we construct an agent-based model of a small municipality with about 60.000 inhabitants (nodes) and about 2.8 million social contacts (edges) in 30 different layers. Those layers reflect demographic, geographic, sociological and other patterns of the TTWA (Travel-to-work-area) Hodonín in Czechia. Various data sources such as census, land register, transport data or data reflecting the shopping behaviour, were employed to meet this purpose. On this multi-graph structure we run a modified SEIR model of the COVID-19 dynamics. The parameters of the model are calibrated on data from the outbreak in the Czech Republic in the period March to June 2020. The simplest type of contact tracing follows just the family, the second tracing version tracks the family and all the work contacts, the third type finds all contacts with the family, work contacts and friends (leisure activities). The last one is a complete (digital) tracing capable of recalling any and all contacts. We evaluate the performance of these contact tracing strategies in four different environments. First, we consider an environment without any contact restrictions (benchmark); second with strict contact restriction (replicating the stringent non-pharmaceutical interventions employed in Czechia in the spring 2020); third environment, where the measures were substantially relaxed, and, finally an environment with weak contact restrictions and superspreader events (replicating the situation in Czechia in the summer 2020). FINDINGS: There are four main findings in our paper. 1. In general, local closures are more effective than any type of tracing. 2. In an environment with strict contact restrictions there are only small differences among the four contact tracing strategies. 3. In an environment with relaxed contact restrictions the effectiveness of the tracing strategies differs substantially. 4. In the presence of superspreader events only complete contact tracing can stop the epidemic. INTERPRETATION: In situations, where many other non-pharmaceutical interventions are in place, the specific extent of contact tracing may not have a large influence on their effectiveness. In a more relaxed setting with few contact restrictions and larger events the effectiveness of contact tracing depends heavily on their extent.

• Keywords
• Agent-based model, Epidemiological model, Network model, Non-pharmaceutical interventions,
• MeSH
• COVID-19 * epidemiology   MeSH
• Disease Outbreaks prevention & control   MeSH
• Humans MeSH
• Pandemics prevention & control   MeSH
• SARS-CoV-2 MeSH
• Contact Tracing MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

This work evaluates the impact of the COVID-19 pandemic on Czech dentistry from March 2020 to March 2021. The assessment was based on questionnaires filled out by 3674 Czech dentists representing 42.6% of practicing dentists in the country. During March-May, 2020 (the first COVID-19 wave), 90.7% of dental practices remained open; however, only 22.8% of the practices continued to operate with no changes, 46.5% had fewer patients, 21.4% treated only acute cases, and 3.8% were closed. During September 2020-May 2021 (the second wave of COVID-19), 96.1% of dental practices remained open, 60.8% operated with no changes, 34.5% had fewer patients, 0.8% treated only acute cases, and 0.5% were closed. The reasons leading to the closure of Czech dental practices during the whole pandemic were a shortage of personal protective equipment (50.5%), a COVID-19 outbreak in the workplace (24.5%), fear of a possible self-infection (24.0%), and quarantine (20.5%). The time range of Czech dental practices closure during the whole pandemic was: 1-2 weeks (49.9%), 2-4 weeks (21.2%), and >1 month (0.8%). The greatest professional difficulties of Czech dentists during the pandemic were crisis operating management (55%), health safety and hygiene concerns (21%), shortage of personal protective equipment (21%), and difficulty working with the protective equipment (15%). In addition, 47.3% of dentists also observed a declining interest in preventive dental care, and 16.9% of them observed worse oral care of patients. These results show that despite the lack of protective equipment, dental care was maintained throughout the pandemic. Additionally, the pandemic negatively affected the patients' approach to dental care, indicating a deterioration in oral health as a possible delayed outcome of the COVID-19 pandemic.

• Keywords
• COVID-19, dentist, dentistry, pandemic, protective equipment,
• MeSH
• COVID-19 * MeSH
• Humans MeSH
• Pandemics * MeSH
• Cross-Sectional Studies MeSH
• SARS-CoV-2 MeSH
• Dentists MeSH
• Dentistry MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Czech Republic epidemiology   MeSH