Monitoring the reproduction number of COVID-19 in France: estimates compared from 3 datasets

Abstract Background The effective reproduction number (Rt) represents the average number of secondary cases generated by an infected person. During an outbreak, near-real-time monitoring of Rt constitutes a key indicator for detecting changes in disease transmission and assessing the effectiveness of interventions. The estimation of Rt usually requires identifying infected cases in the population which is in practice challenging from available data. The purpose of this study was to compare Rt estimates for COVID-19 surveillance in France based on three data sources of different sensitivity and specificity for identifying infected cases. Methods By applying a statistical method developed by Cori et al., we estimated Rt using (1) confirmed cases identified from positive virological tests among the tested population (2) suspected cases recorded by a national network of emergency departments (3) hospital admissions for COVID-19 recorded by a national administrative system to manage hospital's organization. Results From June 2020 to March 2022, the estimates of Rt in France showed similar temporal trends regardless of the dataset. Estimates based on the daily number of confirmed cases provided an earlier signal that the two other sources, with a lag of 3 and 6 days compared to estimates based on emergency department visits and hospital admissions, respectively. Conclusions The COVID-19 experience has proven that monitoring temporal changes in Rt was a key indicator to help public health authorities controlling the outbreak in real time. Having data on infected people in the population to estimate the Rt is not straightforward in practice. As this study has shown, the opportunity of using more readily available data, provided that it is highly correlated with the spread of infection, gives a practical solution for monitoring the COVID-19 epidemic and any epidemic in general. Key messages • The effective reproduction number (Rt) is a key parameter to monitor transmission during epidemics but its estimation from available data is often a critical issue. • Based on COVID-19 experience, data sufficiently correlated with the spread of infection may be appropriate to estimate Rt and monitor its temporal trend.


Background:
The global population is ageing and the need to promote health and well-being of this generation is essential. Co-creative practices can be solutions to welfare challenges in the health care sector and local policies. However, literature addressing co-creation of activities to promote health and wellbeing is sparse. The review aimed to identify health promotive activities co-created between the public and older people, the influence of co-creative activities on health and well-being of older people, and facilitators and barriers for doing cocreation.

Methods:
We searched for peer-reviewed and grey literature in eight scientific and five non-scientific databases. Two reviewers independently screened publications for eligibility according to inclusion and exclusion criteria and extracted data. An inductive thematic content analysis was applied for the analysis.

Results:
We included nineteen publications. Four themes related to cocreative activities emerged: ''Social activities'', ''Activities to create age-friendly environments'', ''Discussions of healthy ageing'', and ''Physical activities''. The co-creative activities influenced the overall well-being, and promoted active and healthy ageing, physical functioning, and quality of life. Identified facilitators for co-creation were the role of the facilitator, a supportive environment, recognition of competencies, while the main barriers were time and resources, and recruitment of participants.

Conclusions:
Few studies have investigated co-creation of activities to promote health and well-being of older people. The included studies dealt with activities in any form and not merely social and physical activities co-created. Future co-creation of activities with older people should consider the role of facilitators, the environment in which the co-creation takes place and value time, resources, and competencies of participants.

Key messages:
Studies on co-creation of activities to promote health and well-being of older people is sparse and must be explored further. Future research may focus on co-creation of social and physical activities to promote health and well-being of older people and consider known facilitators for co-creation.

Background:
The effective reproduction number (Rt) represents the average number of secondary cases generated by an infected person. During an outbreak, near-real-time monitoring of Rt constitutes a key indicator for detecting changes in disease transmission and assessing the effectiveness of interventions.
The estimation of Rt usually requires identifying infected cases in the population which is in practice challenging from available data. The purpose of this study was to compare Rt estimates for COVID-19 surveillance in France based on three data sources of different sensitivity and specificity for identifying infected cases.

Methods:
By applying a statistical method developed by Cori et al., we estimated Rt using (1) confirmed cases identified from positive virological tests among the tested population (2) suspected cases recorded by a national network of emergency departments (3) hospital admissions for COVID-19 recorded by a national administrative system to manage hospital's organization.

Results:
From June 2020 to March 2022, the estimates of Rt in France showed similar temporal trends regardless of the dataset.
Estimates based on the daily number of confirmed cases provided an earlier signal that the two other sources, with a lag of 3 and 6 days compared to estimates based on emergency department visits and hospital admissions, respectively.

Conclusions:
The COVID-19 experience has proven that monitoring temporal changes in Rt was a key indicator to help public health authorities controlling the outbreak in real time. Having data on infected people in the population to estimate the Rt is not straightforward in practice. As this study has shown, the opportunity of using more readily available data, provided that it is highly correlated with the spread of infection, gives a practical solution for monitoring the COVID-19 epidemic and any epidemic in general.

Key messages:
The effective reproduction number (Rt) is a key parameter to monitor transmission during epidemics but its estimation from available data is often a critical issue. Based on COVID-19 experience, data sufficiently correlated with the spread of infection may be appropriate to estimate Rt and monitor its temporal trend.

Background:
To limit SARS-CoV-2 transmission, proactive closure of schools is often believed by policy-makers and public an effective strategy. While evidence on the role of students in the spread is ongoing, effects of closure on children's well-being are well known. The number of secondary cases per class has been considered one of main driving criteria to mandate for distance learning. We aimed to calculate the rate of secondary infections per classroom and to identify factors associated with the development of school clusters.

Methods:
We conducted a population-based cohort study between October 2020 and November 2021 in the province of Venice, Italy, a catchment area of 600,000 inhabitants. Primary, middle and high-schools were included.

Results:
We identified 1,623 primary cases of SARS-CoV-2 infection in students. Of these, 72.5% did not lead to any secondary case in the school setting, 15.6% to 1, and 11.9% to 2+ contagions. The so-called second wave (Oct-Dec 2020) was associated with a lower occurrence of 2+ contagions (AOR = 0.37; 95%CI: 0.24-0.56) than the fourth (Sep-Nov 2021). Both primary (AOR = 1.74; 95%CI: 1.16-2.63) and middle schools (AOR = 1.76 95%CI: 1,14-2,72) showed higher odds than high schools for cluster generation of 2+ cases. The involvement of 2+ secondary cases was lesser associated with the index case being a student rather than school staff (AOR = 0.42; 95%CI: 0.29-0.60). The number of 2+ cases clusters per week followed a time trend in line with the general population incidence.

Conclusions:
The school environment does not facilitate viral spread, but rather reflects transmission in the community. Appropriate measures (use of airway protection devices, interpersonal distancing, frequent hand and respiratory hygiene) and timely case tracking make school a safe place. Given the documented negative effects of school closures on children's learning and well-being, maintaining school attendance is as essential as it is desirable.

Key messages:
A SARS-CoV-2 positive student at school does not generate secondary infections in 3 out of 4 cases. The risk of cluster generation is lower when the index case is a student rather than school staff. The school environment does not facilitate viral spread, but rather reflects transmission in the community. School attendance is essential considering the effects on children's learning and wellbeing.