Survey of staff and students at the University of Edinburgh related to their participation in a routine, asymptomatic Covid-19 workplace testing pilot. 522 participants completed a pilot survey in April 2021 and 1,750 completed the main survey (November 2021). Surveys explored: the acceptability of regular PCR testing among students and staff, particularly involving an approach that was less invasive than nasopharyngeal swabbing; barriers and facilitators to participating in a regular university testing programme, including in the context of other testing methods being available; and whether participation in such a programme changed adherence to public health guidelines.

Every day, schools, child care centres and licensed home child care agencies report to the Ministry of Education on children, students and staff that have positive cases of COVID-19. If there is a discrepancy between numbers reported here and those reported publicly by a Public Health Unit, please consider the number reported by the Public Health Unit to be the most up-to-date. Schools and school boards report when a school is closed to the Ministry of Education. Data is current as of 2:00 pm the previous day. This dataset is subject to change. Data is only updated on weekdays excluding provincial holidays Effective June 15, 2022, board and school staff will not be expected to report student/staff absences and closures in the Absence Reporting Tool. The ministry will no longer report absence rates or school/child care closures on Ontario.ca for the remainder of the school year. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. ##Summary of school closures This is a summary of school closures in Ontario. Data includes: * Number of schools closed * Total number of schools * Percentage of schools closed ##School Absenteeism This report provides a summary of schools and school boards that have reported staff and student absences. Data includes: * School board * School * City or Town * Percentage of staff and students who are absent ##Summary of cases in schools This report provides a summary of COVID-19 activity in publicly-funded Ontario schools. Data includes: * School-related cases (total) * School-related student cases * School-related staff cases * Current number of schools with a reported case * Current number of schools closed Note: In some instances the type of cases are not identified due to privacy considerations. ##Schools with active COVID-19 cases This report lists schools and school boards that have active cases of COVID-19. Data includes : * School Board * School * Municipality * Confirmed Student Cases * Confirmed Staff Cases * Total Confirmed Cases ##Cases in school board partners This report lists confirmed active cases of COVID-19 for other school board partners (e.g. bus drivers, authorized health professionals etc.) and will group boards if there is a case that overlaps. Data includes : * School Board(s) * School Municipality * Confirmed cases – other school board partners ##Summary of targeted testing conducted in schools This data includes all tests that have been reported to the Ministry of Education since February 1, 2021. School boards and other testing partners will report to the Ministry every Wednesday based on data from the previous seven days. Data includes : * School boards or regions * Number of schools invited to participate in the last seven days * Total number of tests conducted in the last seven days * Cumulative number of tests conducted * Number of new cases identified in the last seven days * Cumulative number of cases identified ##Summary of asymptomatic testing at conducted in pharmacies: This is a summary of COVID-19 rapid antigen testing conducted at participating pharmacies in Ontario since March 27, 2021. * Total number of tests conducted in the last seven days * Cumulative number of tests conducted * Number of new cases identified in the last seven days * Cumulative number of cases identified

BackgroundCOVID-19 testing is critical for identifying cases to prevent transmission. COVID-19 self-testing has the potential to increase diagnostic testing capacity and to expand access to hard-to-reach areas in low-and-middle-income countries. We investigated the feasibility and acceptability of COVID-19 self-sampling and self-testing using SARS-CoV-2 Antigen-Rapid Diagnostic Tests (Ag-RDTs).MethodsFrom July 2021 to February 2022, we conducted a mixed-methods cross-sectional study examining self-sampling and self-testing using Standard Q and Panbio COVID-19 Ag Rapid Test Device in Urban and rural Blantyre, Malawi. Health care workers and adults (18y+) in the general population were non-randomly sampled.ResultsOverall, 1,330 participants were enrolled of whom 674 (56.0%) were female and 656 (54.0%) were male with 664 for self-sampling and 666 for self-testing. Mean age was 30.7y (standard deviation [SD] 9.6). Self-sampling usability threshold for Standard Q was 273/333 (82.0%: 95% CI 77.4% to 86.0%) and 261/331 (78.8%: 95% CI 74.1% to 83.1%) for Panbio. Self-testing threshold was 276/335 (82.4%: 95% CI 77.9% to 86.3%) and 300/332 (90.4%: 95% CI 86.7% to 93.3%) for Standard Q and Panbio, respectively. Agreement between self-sample results and professional test results was 325/325 (100%) and 322/322 (100%) for Standard Q and Panbio, respectively. For self-testing, agreement was 332/333 (99.7%: 95% CI 98.3 to 100%) for Standard Q and 330/330 (100%: 95% CI 99.8 to 100%) for Panbio. Odds of achieving self-sampling threshold increased if the participant was recruited from an urban site (odds ratio [OR] 2.15 95% CI 1.44 to 3.23, P < .01. Compared to participants with primary school education those with secondary and tertiary achieved higher self-testing threshold OR 1.88 (95% CI 1.17 to 3.01), P = .01 and 4.05 (95% CI 1.20 to13.63), P = .02, respectively.ConclusionsOne of the first studies to demonstrate high feasibility and acceptability of self-testing using SARS-CoV-2 Ag-RDTs among general and health-care worker populations in low- and middle-income countries potentially supporting large scale-up. Further research is warranted to provide optimal delivery strategies of self-testing.

The Advancing Education Safely dashboard includes information about COVID-19 testing and confirmed cases for SDP students and staff in 2021-22.

COVID-19 Diagnostic Testing Market Outlook

The COVID-19 diagnostic testing market size was valued at USD 85 billion in 2023, with a forecasted value of USD 75 billion by 2032, growing at a CAGR of -1.3% during the forecast period. The market's decline is primarily driven by the decreasing number of COVID-19 cases and the widespread availability of vaccines. Despite the downward trend, the market is expected to maintain a significant presence due to ongoing testing requirements in various sectors, evolving virus variants, and the need for early detection in future outbreaks.

One of the main growth factors for the COVID-19 diagnostic testing market is the increasing awareness of the importance of early detection and prevention. Governments and health organizations worldwide have emphasized the necessity of mass testing to control the spread of the virus. Investments in healthcare infrastructure and the development of innovative testing methods have also played a crucial role in maintaining the market's momentum. Moreover, the emergence of new variants has underscored the need for continuous testing and monitoring, ensuring that the market remains relevant.

Technological advancements have significantly influenced the growth of the COVID-19 diagnostic testing market. The development of rapid and accurate testing methods, such as molecular and antigen tests, has revolutionized the industry. These technologies have enabled healthcare providers to quickly identify and isolate infected individuals, thereby preventing further transmission. Additionally, advancements in at-home testing kits have made it more convenient for individuals to monitor their health status, leading to increased adoption of these products.

The expanding applications of COVID-19 diagnostic testing beyond healthcare settings have also contributed to market growth. Many industries, including travel, hospitality, and education, have adopted regular testing protocols to ensure the safety of their employees and customers. This widespread adoption has created a sustained demand for diagnostic tests, even as the number of cases fluctuates. Furthermore, the integration of testing with digital health platforms and mobile applications has streamlined the process, making it easier for individuals to access and interpret their results.

Regionally, North America has been a significant market for COVID-19 diagnostic testing, driven by the high number of cases and robust healthcare infrastructure. Europe and Asia Pacific have also exhibited strong growth, supported by government initiatives and increasing awareness about the importance of testing. In contrast, regions like Latin America and the Middle East & Africa have faced challenges due to limited healthcare infrastructure and resources. However, international aid and collaborations have helped to mitigate some of these issues, fostering growth in these markets.

Test Type Analysis

The COVID-19 diagnostic testing market is segmented into molecular tests, antigen tests, and antibody tests. Molecular tests, such as RT-PCR, remain the gold standard due to their high accuracy and reliability. These tests detect the virus's genetic material and are widely used in hospital and laboratory settings. Despite their longer turnaround time, molecular tests are preferred for definitive diagnosis and for confirming cases of COVID-19, especially in symptomatic individuals and high-risk populations.

Antigen tests have gained popularity due to their rapid turnaround time and ease of use. These tests detect specific proteins on the surface of the virus and can provide results within minutes. While they are less accurate than molecular tests, antigen tests are valuable for mass screening and point-of-care testing. Their ability to quickly identify infected individuals makes them crucial in settings where immediate results are needed, such as airports, schools, and workplaces.

Antibody tests, also known as serology tests, detect the presence of antibodies in the blood, indicating a past infection. These tests play a crucial role in understanding the spread of the virus and the population's immunity levels. While not used for diagnosing active infections, antibody tests provide valuable data for epidemiological studies and vaccine efficacy assessments. They have been instrumental in guiding public health strategies and vaccination campaigns.

The implementation of a <a href="https://dataintelo.com/report/global-covid-19-health-code-market" target="_blank"

This dataset presents information on COVID-19 in children and young people of educational age, education staff and educational settings. This includes: * Testing and cases among children and young people of educational age. * Hospital admissions related to COVID-19 among children and young people of educational age. * Information from contact tracing on cases present in an educational setting in the 7-days before symptom onset, and on cases who work in education or childcare. * Information about COVID-19 cases in registered school pupils. This data is also available on the COVID-19 Education Surveillance Dashboard. Additional data sources relating to this topic area are provided in the Links section of the Metadata below. All publications and supporting material to this topic area can be found on the Enhanced Surveillance of COVID-19 in Education settings section of the Public Health Scotland website. From 11/06/2021 data completeness will be up to the previous Wednesday, so weekly data are aggregated from Thursday to Wednesday. Previously data covered periods from Saturday to Friday. This is due to NHS Boards submitting admission data from Monday to Friday and a three day lag for some boards by the time data is processed for COVID-19 hospital admission. From 2nd of July, information on testing and admissions will be extended to include 20-21 years olds, and admissions will also include 18-19 year olds. From 13th of August, information on PCR testing and admissions has been extended to include 0-1 year olds.

This dataset contains daily and cumulative information on positive PCR in students and teachers, as well as quarantined classrooms and centers.

The data corresponds to the day before its publication.

Total active quarantined classrooms refers to the number of currently quarantined classrooms.

At the moment 16,117 classrooms have started the course.

The positive cases detected by PCR through the COVID-College Teams (tests carried out by the prevention services contracted by the Ministry of Education) are counted.

In the new cases, the cases detected on the day are counted.

Cases accumulated since 9 September.

The classrooms and centers communicated in the day are counted. The educational spaces affected are under the criteria established by the Ministry of Health for the educational field.

Centres supported by public funds are counted as quarantined centres.

The fact sheet outlines how parents and school staff can use at-home rapid test kits for COVID-19 and participate in the government K-12 at-home rapid testing program.

Cross-tabulation of risk category and RT-PCR results (n = 1,174).

The study identified the emotional impact of COVID-2019 pandemic among teaching and non-teaching staff in Vocational Enterprises Institutes in Abuja, Nigeria. The research design used for this study was a cross-sectional study. The study was conducted in Abuja, Nigeria. The population of the study was 182 respondents consisting of 91 males and 63 females teaching staff as well as 16 males and 12 females’ non-teaching staff from the six Vocational Enterprises Institutes, one each from the six area councils in Abuja, Nigeria. Total population sampling technique was used to select the whole population of the study. The instruments used for data collection was Pandemic Emotional Impact Scale. Cronbach Alpha statistical method was used to determine the reliability index of the instrument and found to be .90. The study employed the use of weighted mean formula to answer the research questions and z-test to test the null hypotheses using GraphPad online z-test calculator. Findings from the study revealed among others that worried about finances, anxious or ill at ease, difficulty concentrating, being less productive, worried about personal health or safety, being more bored, difficulty sleeping, feeling lonelier or isolated and feeling more down or depressed, worried about getting necessities like medications were emotional impact of COVID-2019 pandemic among teaching and non-teaching staff in Vocational Enterprises Institutes in Abuja, Nigeria. The study recommended among others that, the education secretariat of the Federal Capital Territory, Abuja, Nigeria should develop an emotional intelligence framework for the management of emotional challenges associated with COVID-19 for teaching and non-teaching staff in Vocational Enterprises Institutes in Abuja, Nigeria.

Baseline demographics and socioeconomic characteristics and reach of the CHW support component of the T2C Model.

Factors associated with self-sampling and self-testing accuracy.

Abstract copyright UK Data Service and data collection copyright owner.

The Surrey Communication and Language in Education Study (SCALES) is the first UK population study of language development and disorder at school entry. The study is funded by Wellcome and the ESRC and involves more than 180 schools across Surrey UK.

This longitudinal study was initially established to determine (1) the extent to which 'Specific' Language Impairment (SLI) was prevalent in a population (as opposed to clinically ascertained) sample at school entry, and (2) the impact of language impairment on other aspects of development and how these patterns of development change over time. A second phase of SCALES aimed to test theoretical accounts of the developing relationship between language and social, emotional, and mental health during the transition to secondary school. Unfortunately, the final testing wave coincided with the global Covid-19 pandemic which impacted data collection due to school closures and lockdown.

The Surrey Communication and Language in Education Study: Screening Data, 2012 contains anonymised data from the first phase of the SCALES study. In this phase, Reception class teachers in state-maintained schools in the county of Surrey UK were invited to respond to an on-line questionnaire for each child in their class. The main focus of the study was to identify the prevalence of language difficulties at school entry and document the association between language difficulties, behavioural problems and educational attainment in the first year of school.

Further information about the study can be found on the UCL Literacy, Language and Communication Laboratory SCALES project website.

The main areas of research include:

• teacher rated language competency
• teacher rated social, emotional, behavioural development
• teacher rated educational attainment (reception year)
  

Structural equation model results, standardized coefficients with clustered standard errors included in parentheses.

The over-arching aim of this multi-method study was to investigate the relations between children’s wellbeing and ‘school readiness’. There were four specific objectives: 1. To enrich understanding of the overlap between ‘school readiness’ and child wellbeing. 2. To examine characteristics that shape children’s wellbeing and ‘school readiness’. 3. To examine how family characteristics shape children’s wellbeing and ‘school readiness’. 4. To examine how children’s wellbeing and school readiness impact on caregiver wellbeing. Children and their caregivers in England were recruited to participate in a 12-month longitudinal study while the children were enrolled in Reception Year (i.e., the final year of the Early Years Foundation Stage in England) in Spring/Summer 2021. Children and their primary caregivers were seen on two occasions approximately 12 months apart (Mean Interval = 12.36 months, SD = 1.08 months) using a remote assessment protocol to mitigate the spread of Covid 19. Data collection was timed to take place when children had completed at least one term in Reception Year and then again after completing at least one term in Year 1. At both timepoints, following written consent, caregivers participated in a remote interview lasting approximately 20 minutes and then completed an online questionnaire pack. Children then participated in a remote testing session using videoconference software with a caregiver present. These sessions lasted approximately 45 – 60 minutes. Families received a voucher for participating in each wave of the study. Teachers were invited to complete a short questionnaire about each study child. Sample The initial plan for the current study was to track a pre-existing cohort of 200 children from the United Kingdom across the transition from Reception Year to Year 1 and to recruit an additional 250 children to enrich the sample. Restrictions due to the Covid-19 pandemic in 2020 and 2021 meant that the start date for the project was delayed and the opportunity to collect data from the pre-existing cohort was no longer possible as the cohort children had moved beyond Reception Year. We instead recruited a new sample of children for the current study. Monte Carlo simulations indicated that a sample size of 250 children would provide sufficient (.81 - .85) power to detect moderate-to-strong cross-lagged effects between two latent variables in a longitudinal model of two time points with three covariates. Children and their primary caregivers were recruited from across England in the Spring/Summer 2021 via mailings to primary schools and paid targeted social media advertising. To participate in the study, children were required to be enrolled in the first year of primary school in England (‘Reception’) and have no history of developmental delay. In England, children typically start the reception year of primary school in the September after their 4th birthday. The primary caregiver and participating child had to be able to communicate in English. We sought to recruit 250 children into the longitudinal study. Just under 500 caregivers expressed an interest in learning more about the study (N=494) and 260 of these families agreed to participate (52.6%). Of these 260 families, 5 families did not provide sufficient information to establish eligibility, 1 child was not attending Reception and 2 families planned to leave England before follow-up. At Time 1, 252 children (131 girls) aged 5.40 years (SD = 0.31) and their caregivers (92.7% mothers, M Age = 38.63 years, SD = 4.66) participated in the study. Children were predominantly from two-parent heterosexual households (92.1%). Caregivers were highly educated (83.7% had degree level education). On the subjective ladder of social status, 74.3% of caregivers rated themselves as 6/10 or above on a 10-point scale where 1 indicated the lowest levels of education, income, and status and 10 indicated the highest levels of education, income, and status. According to UK Census ethnic group categories, 80.5% of children were identified as ‘White’, 13.2% as ‘Mixed or multiple ethnicities’, 5.9% as ‘Asian’, 0.4% as ‘Black’. 223 out of 252 families participated at Time 1 and Time 2 (88.5%). Teacher questionnaires were available for 154 out of 223 children at Time 2 (69%) and Caregiver Questionnaires were available for 192 out of 223 children at Time 2 (86%).The over-arching aim of this multi-method study was to investigate the relations between children’s wellbeing and ‘school readiness’. There were four specific objectives: 1. To enrich understanding of the overlap between ‘school readiness’ and child wellbeing. 2. To examine characteristics that shape children’s wellbeing and ‘school readiness’. 3. To examine how family characteristics shape children’s wellbeing and ‘school readiness’. 4. To examine how children’s wellbeing and school readiness impact on caregiver wellbeing. Children and their caregivers in England were recruited to participate in a 12-month longitudinal study while the children were enrolled in Reception Year (i.e., the final year of the Early Years Foundation Stage in England) in Spring/Summer 2021. Children and their primary caregivers were seen on two occasions approximately 12 months apart (Mean Interval = 12.36 months, SD = 1.08 months) using a remote assessment protocol to mitigate the spread of Covid 19. Data collection was timed to take place when children had completed at least one term in Reception Year and then again after completing at least one term in Year 1. At both timepoints, following written consent, caregivers participated in a remote interview lasting approximately 20 minutes and then completed an online questionnaire pack. Children then participated in a remote testing session using videoconference software with a caregiver present. These sessions lasted approximately 45 – 60 minutes. Families received a voucher for participating in each wave of the study. Teachers were invited to complete a short questionnaire about each study child. Data for this study were collected using multiple methods: structured caregiver interviews, standardized self-report questionnaires, structured observations, standardized assessments, structured child interviews. The protocols for the caregiver interviews, child testing sessions, caregiver questionnaires, and teacher questionnaire are included as separate documents.

Demographic details of school management participants.

Univariable analysis for baseline characteristics and surveillance variables (n = 1,174).

On behalf of the Press and Information Office of the Federal Government, the opinion research institute forsa has regularly conducted representative population surveys on the subject of the ´Corona crisis´ (COVID-19) from calendar week 12/2020. The individual question areas were adapted according to the survey period. Credibility of the information provided by the federal government on the Corona crisis; assessment of the current political measures to contain the Corona virus (appropriate, go too far or do not go far enough); extent of the personal restrictions perceived as a result of the Corona crisis and the associated measures; decision by the federal government to gradually withdraw the Corona restrictions in three stages: Self-assessment of being informed about the different stages of relaxation and the regulations that will then apply in each case; expected effects of the gradual withdrawal of Corona restrictions on various areas (social cohesion, relationship between the unvaccinated and the vaccinated, situation of children and adolescents, situation of medical and nursing staff, situation of older people and people with pre-existing conditions); sensible basic measures against the Corona virus after the discontinuation of most protective measures from 20. March (compulsory masks in public transport, compulsory masks in retail, compulsory masks in schools, compulsory testing for visits to hospitals and care facilities, compulsory testing in schools, distance regulations, none of the above-mentioned measures); assessment of the abolition of the home office obligation from the 20th of March; current place of work: almost exclusively at the place of work away from home, mainly at the place of work away from home, mainly at home in the home office, almost exclusively at home in the home office, not at all (e.g. due to lack of orders, short-time work); preferences regarding place of work after the 20th of March. Demography: sex; age (grouped); employment; education; net household income (grouped); party preference in the next general election; voting behaviour in the last general election. Additionally coded: region; federal state; weight. Im Auftrag des Presse- und Informationsamts der Bundesregierung hat das Meinungsforschungsinstitut forsa ab Kalenderwoche 12/2020 regelmäßig repräsentative Bevölkerungsbefragungen zum Thema ´Corona-Krise´ (COVID-19) durchgeführt. Die einzelnen Fragegebiete wurden je nach Befragungszeitraum angepasst. Glaubwürdigkeit der Informationen der Bundesregierung zur Corona-Krise; Bewertung der aktuellen politischen Maßnahmen zur Eindämmung des Corona-Virus (angemessen, gehen zu weit oder gehen nicht weit genug); Ausmaß der empfundenen persönlichen Einschränkungen durch die Corona-Krise und die damit verbundenen Maßnahmen; Beschluss der Bundesregierung zur schrittweise Zurücknahme der Corona- Beschränkungen in drei Stufen: Selbsteinschätzung Informiertheit über die unterschiedlichen Stufen der Lockerungen und die dann jeweils geltenden Regelungen; erwartete Auswirkungen der schrittweisen Zurücknahme der Corona-Beschränkungen auf verschiedene Bereiche (gesellschaftlicher Zusammenhalt, Verhältnis von Ungeimpften und Geimpften, Situation von Kindern und Jugendlichen, Situation von medizinischem und pflegerischem Personal, Situation älterer Menschen und Menschen mit Vorerkrankungen); sinnvolle Basismaßnahmen gegen das Coronavirus nach Wegfall der meisten Schutzmaßnahmen ab 20. März (Maskenpflicht im ÖPNV, Maskenpflicht im Einzelhandel, Maskenpflicht in Schulen, Testpflicht für Besuche in Krankenhäusern und Pflegeeinrichtungen, Testpflicht in Schulen, Abstandsregelungen, keine der genannten Maßnahmen); Bewertung des Wegfalls der Home-Office-Pflicht ab 20. März; aktueller Arbeitsort: fast ausschließlich an der Arbeitsstätte außer Haus, überwiegend an der Arbeitsstätte außer Haus, überwiegend zu Hause im Home Office, fast ausschließlich zu Hause im Home Office, gar nicht (z.B. wegen fehlender Aufträge, Kurzarbeit); Präferenzen im Hinblick auf den Arbeitsort nach dem 20. März. Demographie: Geschlecht; Alter (gruppiert); Erwerbstätigkeit; Schulabschluss; Haushaltsnettoeinkommen (gruppiert); Parteipräferenz bei der nächsten Bundestagswahl; Wahlverhalten bei der letzten Bundestagswahl. Zusätzlich verkodet wurde: Region; Bundesland; Gewicht. Probability: MultistageProbability.Multistage Wahrscheinlichkeitsauswahl: Mehrstufige ZufallsauswahlProbability.Multistage Telephone interview: Computer-assisted (CATI)Interview.Telephone.CATI

Logistic regression model between associated variables and ELISA test results.