Evolving social contact patterns during the COVID-19 crisis in Luxembourg

Social contact patterns following the COVID-19 pandemic: a snapshot of post-pandemic behaviour from the CoMix study

The COVID-19 pandemic led to unprecedented changes in behaviour. To estimate if these persisted, a final round of the CoMix social contact survey was conducted in four countries at a time when all societal restrictions had been lifted for several months. We conducted a survey on a nationally representative sample in the UK, Netherlands (NL), Belgium (BE), and Switzerland (CH). Participants were asked about their contacts and behaviours on the previous day. We calculated contact matrices and compared the contact levels to a pre-pandemic baseline to estimate R0. Data collection occurred from 17 November to 7 December 2022. 7477 participants were recruited. Some were asked to undertake the survey on behalf of their children. Only 14.4 % of all participants reported wearing a facemask on the previous day. Self-reported vaccination rates in adults were similar for each country at around 86 %. Trimmed mean recorded contacts were highest in NL with 9.9 (95 % confidence interval [CI] 9.0-10.8) contacts per person per day and lowest in CH at 6.0 (95 % CI 5.4-6.6). Contacts at work were lowest in the UK (1.4 contacts per person per day) and highest in NL at 2.8 contacts per person per day. Other contacts were also lower in the UK at 1.6 per person per day (95 % CI 1.4-1.9) and highest in NL at 3.4 recorded per person per day (95 % CI 43.0-4.0). The next-generation approach suggests that R0 for a close-contact disease would be roughly half pre-pandemic levels in the UK, 80 % in NL and intermediate in the other two countries. The pandemic appears to have resulted in lasting changes in contact patterns expected to have an impact on the epidemiology of many different pathogens. Further post-pandemic surveys are necessary to confirm this finding.

Social contact patterns during the early COVID-19 pandemic in Norway: insights from a panel study, April to September 2020

BACKGROUND

During the COVID-19 pandemic, many countries adopted social distance measures and lockdowns of varying strictness. Social contact patterns are essential in driving the spread of respiratory infections, and country-specific measurements are needed. This study aimed to gain insights into changes in social contacts and behaviour during the early pandemic phase in Norway.

METHODS

We conducted an online panel study among a nationally representative sample of Norwegian adults by age and gender. The panel study included six data collections waves between April and September 2020, and 2017 survey data from a random sample of the Norwegian population (including children < 18 years old) were used as baseline. The market research company Ipsos was responsible for carrying out the 2020 surveys. We calculated mean daily contacts, and estimated age-stratified contact matrices during the study period employing imputation of child-to-child contacts. We used the next-generation method to assess the relative reduction of R0 and compared the results to reproduction numbers estimated for Norway during the 2020 study period.

RESULTS

Over the six waves in 2020, 5 938 observations/responses were registered from 1 718 individuals who reported data on 22 074 contacts. The mean daily number of contacts among adults varied between 3.2 (95%CI 3.0-3.4) to 3.9 (95%CI 3.6-4.2) across the data collection waves, representing a 67-73% decline compared to pre-pandemic levels (baseline). Fewer contacts in the community setting largely drove the reduction; the drop was most prominent among younger adults. Despite gradual easing of social distance measures during the survey period, the estimated population contact matrices remained relatively stable and displayed more inter-age group mixing than at baseline. Contacts within households and the community outside schools and workplaces contributed most to social encounters. Using the next-generation method R0 was found to be roughly 25% of pre-pandemic levels during the study period, suggesting controlled transmission.

CONCLUSION

Social contacts declined significantly in the months following the March 2020 lockdown, aligning with implementation of stringent social distancing measures. These findings contribute valuable empirical information into the social behaviour in Norway during the early pandemic, which can be used to enhance policy-relevant models for addressing future crises when mitigation measures might be implemented.

Key risk factors associated with fractal dimension based geographical clustering of COVID-19 data in the Flemish and Brussels region, Belgium

Introduction

COVID-19 remains a major concern globally. Therefore, it is important to evaluate COVID-19's rapidly changing trends. The fractal dimension has been proposed as a viable method to characterize COVID-19 curves since epidemic data is often subject to considerable heterogeneity. In this study, we aim to investigate the association between various socio-demographic factors and the complexity of the COVID-19 curve as quantified through its fractal dimension.

Methods

We collected population indicators data (ethnic composition, socioeconomic status, number of inhabitants, population density, the older adult population proportion, vaccination rate, satisfaction, and trust in the government) at the level of the statistical sector in Belgium. We compared these data with fractal dimension indicators of COVID-19 incidence between 1 January - 31 December 2021 using canonical correlation analysis.

Results

Our results showed that these population indicators have a significant association with COVID-19 incidences, with the highest explanatory and predictive power coming from the number of inhabitants, population density, and ethnic composition.

Conclusion

It is important to monitor these population indicators during a pandemic, especially when dealing with targeted interventions for a specific population.

Longitudinal social contact data analysis: insights from 2 years of data collection in Belgium during the COVID-19 pandemic

BACKGROUND

During the COVID-19 pandemic, the CoMix study, a longitudinal behavioral survey, was designed to monitor social contacts and public awareness in multiple countries, including Belgium. As a longitudinal survey, it is vulnerable to participants' "survey fatigue", which may impact inferences.

METHODS

A negative binomial generalized additive model for location, scale, and shape (NBI GAMLSS) was adopted to estimate the number of contacts reported between age groups and to deal with under-reporting due to fatigue within the study. The dropout process was analyzed with first-order auto-regressive logistic regression to identify factors that influence dropout. Using the so-called next generation principle, we calculated the effect of under-reporting due to fatigue on estimating the reproduction number.

RESULTS

Fewer contacts were reported as people participated longer in the survey, which suggests under-reporting due to survey fatigue. Participant dropout is significantly affected by household size and age categories, but not significantly affected by the number of contacts reported in any of the two latest waves. This indicates covariate-dependent missing completely at random (MCAR) in the dropout pattern, when missing at random (MAR) is the alternative. However, we cannot rule out more complex mechanisms such as missing not at random (MNAR). Moreover, under-reporting due to fatigue is found to be consistent over time and implies a 15-30% reduction in both the number of contacts and the reproduction number ([Formula: see text]) ratio between correcting and not correcting for under-reporting. Lastly, we found that correcting for fatigue did not change the pattern of relative incidence between age groups also when considering age-specific heterogeneity in susceptibility and infectivity.

CONCLUSIONS

CoMix data highlights the variability of contact patterns across age groups and time, revealing the mechanisms governing the spread/transmission of COVID-19/airborne diseases in the population. Although such longitudinal contact surveys are prone to the under-reporting due to participant fatigue and drop-out, we showed that these factors can be identified and corrected using NBI GAMLSS. This information can be used to improve the design of similar, future surveys.

Impact of tiered measures on social contact and mixing patterns of in Italy during the second wave of COVID-19

BACKGROUND

Most countries around the world enforced non-pharmaceutical interventions against COVID-19. Italy was one of the first countries to be affected by the pandemic, imposing a hard lockdown, in the first epidemic wave. During the second wave, the country implemented progressively restrictive tiers at the regional level according to weekly epidemiological risk assessments. This paper quantifies the impact of these restrictions on contacts and on the reproduction number.

METHODS

Representative (with respect to age, sex, and region of residence) longitudinal surveys of the Italian population were undertaken during the second epidemic wave. Epidemiologically relevant contact patterns were measured and compared with pre-pandemic levels and according to the level of interventions experienced by the participants. Contact matrices were used to quantify the reduction in the number of contacts by age group and contact setting. The reproduction number was estimated to evaluate the impact of restrictions on the spread of COVID-19.

RESULTS

The comparison with the pre-pandemic baseline shows a significant decrease in the number of contacts, independently from the age group or contact settings. This decrease in the number of contacts significantly depends on the strictness of the non-pharmaceutical interventions. For all levels of strictness considered, the reduction in social mixing results in a reproduction number smaller than one. In particular, the impact of the restriction on the number of contacts decreases with the severity of the interventions.

CONCLUSIONS

The progressive restriction tiers implemented in Italy reduced the reproduction number, with stricter interventions associated with higher reductions. Readily collected contact data can inform the implementation of mitigation measures at the national level in epidemic emergencies to come.

Quantifying social contact patterns in Minnesota during stay-at-home social distancing order

SARS-CoV-2 is primarily transmitted through person-to-person contacts. It is important to collect information on age-specific contact patterns because SARS-CoV-2 susceptibility, transmission, and morbidity vary by age. To reduce the risk of infection, social distancing measures have been implemented. Social contact data, which identify who has contact with whom especially by age and place are needed to identify high-risk groups and serve to inform the design of non-pharmaceutical interventions. We estimated and used negative binomial regression to compare the number of daily contacts during the first round (April-May 2020) of the Minnesota Social Contact Study, based on respondent's age, gender, race/ethnicity, region, and other demographic characteristics. We used information on the age and location of contacts to generate age-structured contact matrices. Finally, we compared the age-structured contact matrices during the stay-at-home order to pre-pandemic matrices. During the state-wide stay-home order, the mean daily number of contacts was 5.7. We found significant variation in contacts by age, gender, race, and region. Adults between 40 and 50 years had the highest number of contacts. The way race/ethnicity was coded influenced patterns between groups. Respondents living in Black households (which includes many White respondents living in inter-racial households with black family members) had 2.7 more contacts than respondents in White households; we did not find this same pattern when we focused on individual's reported race/ethnicity. Asian or Pacific Islander respondents or in API households had approximately the same number of contacts as respondents in White households. Respondents in Hispanic households had approximately two fewer contacts compared to White households, likewise Hispanic respondents had three fewer contacts than White respondents. Most contacts were with other individuals in the same age group. Compared to the pre-pandemic period, the biggest declines occurred in contacts between children, and contacts between those over 60 with those below 60.

Social contact patterns during the COVID-19 pandemic in 21 European countries - evidence from a two-year study

BACKGROUND

Most countries have enacted some restrictions to reduce social contacts to slow down disease transmission during the COVID-19 pandemic. For nearly two years, individuals likely also adopted new behaviours to avoid pathogen exposure based on personal circumstances. We aimed to understand the way in which different factors affect social contacts - a critical step to improving future pandemic responses.

METHODS

The analysis was based on repeated cross-sectional contact survey data collected in a standardized international study from 21 European countries between March 2020 and March 2022. We calculated the mean daily contacts reported using a clustered bootstrap by country and by settings (at home, at work, or in other settings). Where data were available, contact rates during the study period were compared with rates recorded prior to the pandemic. We fitted censored individual-level generalized additive mixed models to examine the effects of various factors on the number of social contacts.

RESULTS

The survey recorded 463,336 observations from 96,456 participants. In all countries where comparison data were available, contact rates over the previous two years were substantially lower than those seen prior to the pandemic (approximately from over 10 to < 5), predominantly due to fewer contacts outside the home. Government restrictions imposed immediate effect on contacts, and these effects lingered after the restrictions were lifted. Across countries, the relationships between national policy, individual perceptions, or personal circumstances determining contacts varied.

CONCLUSIONS

Our study, coordinated at the regional level, provides important insights into the understanding of the factors associated with social contacts to support future infectious disease outbreak responses.

Dynamics of non-household contacts during the COVID-19 pandemic in 2020 and 2021 in the Netherlands

The COVID-19 pandemic was in 2020 and 2021 for a large part mitigated by reducing contacts in the general population. To monitor how these contacts changed over the course of the pandemic in the Netherlands, a longitudinal survey was conducted where participants reported on their at-risk contacts every two weeks, as part of the European CoMix survey. The survey included 1659 participants from April to August 2020 and 2514 participants from December 2020 to September 2021. We categorized the number of unique contacted persons excluding household members, reported per participant per day into six activity levels, defined as 0, 1, 2, 3-4, 5-9 and 10 or more reported contacts. After correcting for age, vaccination status, risk status for severe outcome of infection, and frequency of participation, activity levels increased over time, coinciding with relaxation of COVID-19 control measures.

Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infectious contacts

Mathematical models have been widely used during the ongoing SARS-CoV-2 pandemic for data interpretation, forecasting, and policy making. However, most models are based on officially reported case numbers, which depend on test availability and test strategies. The time dependence of these factors renders interpretation difficult and might even result in estimation biases. Here, we present a computational modelling framework that allows for the integration of reported case numbers with seroprevalence estimates obtained from representative population cohorts. To account for the time dependence of infection and testing rates, we embed flexible splines in an epidemiological model. The parameters of these splines are estimated, along with the other parameters, from the available data using a Bayesian approach. The application of this approach to the official case numbers reported for Munich (Germany) and the seroprevalence reported by the prospective COVID-19 Cohort Munich (KoCo19) provides first estimates for the time dependence of the under-reporting factor. Furthermore, we estimate how the effectiveness of non-pharmaceutical interventions and of the testing strategy evolves over time. Overall, our results show that the integration of temporally highly resolved and representative data is beneficial for accurate epidemiological analyses.

Was it really different? COVID-19-pandemic period in long-term recreation monitoring – A case study from Polish forests

The COVID -19 pandemic posed serious challenge for securing public health worldwide. Public health preparedness and restrictions put in place impacted many aspects of human life, including recreational activities and access to outdoor recreational destinations. Green spaces have become one of the few sources of resilience during the coronavirus crisis due to their restorative effects on psychophysical health and community well-being. The aim of this study is to analyse the impact of the COVID -19 pandemic on forest visitation. The results are based upon long-term visitor data acquired via pyroelectric sensors (Eco-Counter) in three forest districts located in Poland (Browsk, Gdansk & Kozienice Forest Districts). The analysis covers the period between January 01, 2019 and December 31, 2020 and the results confirm changes in recreational use in the studied forest areas during the pandemic compared to the preceding year. However, observed changes in forest visitation vary by pandemic period and study area. The ban on access to forest areas significantly reduced the number of forest visits in all studied areas. The number of visits to sub-urban forests (Gdansk Forest District) and to remote nature-based tourist destinations (Browsk Forest District) increased in the later pandemic periods, especially in the summer months of 2020, while it remained the same in a popular nearby recreation area: Kozienice Forest District. There were only minor temporal shifts in the distribution of weekly and daily visits. The results are important for public health preparedness planning in crisis situations and for provisioning conditions supporting societal health and well-being. Objective data on forest visits are necessary for successful management of forest areas and surrounding amenities. More cross-sector collaboration and public participation would be desirable to create sustainable, resilient, and liveable spaces for the society.

Management Implications

•

Long-term visitation monitoring is crucial for successful management of outdoor recreation destinations and their catchment areas.

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Objective numbers concerning forest visitation from the pre-pandemic and COVID-19 pandemic period allow observing trends and making fact-based management decisions during period of crisis.

•

Changes in the investigated three forest study areas in Poland were not homogenous, which implies the necessity of systematic visitor monitoring in multiple destinations, in order to cover different types of forest areas and also local diversity in recreational use.

•

More intersectoral, interdisciplinary and transdisciplinary exchange would be desirable to better integrate existing on-site visitor monitoring data into decision making processes related to forest management, urban planning, transportation, tourism and public health.

Social mixing patterns in the UK following the relaxation of COVID-19 pandemic restrictions, July-August 2020: a cross-sectional online survey

OBJECTIVES

To quantify and characterise non-household contact and to identify the effect of shielding and isolating on contact patterns.

DESIGN

Cross-sectional study.

SETTING AND PARTICIPANTS

Anyone living in the UK was eligible to take part in the study. We recorded 5143 responses to the online questionnaire between 28 July 2020 and 14 August 2020.

OUTCOME MEASURES

Our primary outcome was the daily non-household contact rate of participants. Secondary outcomes were propensity to leave home over a 7 day period, whether contacts had occurred indoors or outdoors locations visited, the furthest distance travelled from home, ability to socially distance and membership of support bubble.

RESULTS

The mean rate of non-household contacts per person was 2.9 d^-1. Participants attending a workplace (adjusted incidence rate ratio (aIRR) 3.33, 95% CI 3.02 to 3.66), self-employed (aIRR 1.63, 95% CI 1.43 to 1.87) or working in healthcare (aIRR 5.10, 95% CI 4.29 to 6.10) reported significantly higher non-household contact rates than those working from home. Participants self-isolating as a precaution or following Test and Trace instructions had a lower non-household contact rate than those not self-isolating (aIRR 0.58, 95% CI 0.43 to 0.79). We found limited evidence that those shielding had reduced non-household contacts compared with non-shielders.

CONCLUSION

The daily rate of non-household interactions remained lower than prepandemic levels measured by other studies, suggesting continued adherence to social distancing guidelines. Individuals attending a workplace in-person or employed as healthcare professionals were less likely to maintain social distance and had a higher non-household contact rate, possibly increasing their infection risk. Shielding and self-isolating individuals required greater support to enable them to follow the government guidelines and reduce non-household contact and therefore their risk of infection.

Occupation, Worker Vulnerability, and COVID-19 Vaccination Uptake: Analysis of the Virus Watch prospective cohort study

BACKGROUND

Occupational disparities in COVID-19 vaccine uptake can impact the effectiveness of vaccination programmes and introduce particular risk for vulnerable workers and those with high workplace exposure. This study aimed to investigate COVID-19 vaccine uptake by occupation, including for vulnerable groups and by occupational exposure status.

METHODS

We used data from employed or self-employed adults who provided occupational information as part of the Virus Watch prospective cohort study (n = 19,595) and linked this to study-obtained information about vulnerability-relevant characteristics (age, medical conditions, obesity status) and work-related COVID-19 exposure based on the Job Exposure Matrix. Participant vaccination status for the first, second, and third dose of any COVID-19 vaccine was obtained based on linkage to national records and study records. We calculated proportions and Sison-Glaz multinomial 95% confidence intervals for vaccine uptake by occupation overall, by vulnerability-relevant characteristics, and by job exposure.

FINDINGS

Vaccination uptake across occupations ranged from 89-96% for the first dose, 87-94% for the second dose, and 75-86% for the third dose, with transport, trade, service and sales workers persistently demonstrating the lowest uptake. Vulnerable workers tended to demonstrate fewer between-occupational differences in uptake than non-vulnerable workers, although clinically vulnerable transport workers (76%-89% across doses) had lower uptake than several other occupational groups (maximum across doses 86%-96%). Workers with low SARS-CoV-2 exposure risk had higher vaccine uptake (86%-96% across doses) than those with elevated or high risk (81-94% across doses).

INTERPRETATION

Differential vaccination uptake by occupation, particularly amongst vulnerable and highly-exposed workers, is likely to worsen occupational and related socioeconomic inequalities in infection outcomes. Further investigation into occupational and non-occupational factors influencing differential uptake is required to inform relevant interventions for future COVID-19 booster rollouts and similar vaccination programmes.

Changes in structure and function of social networks of independently living middle-aged and older adults in diverse sociodemographic subgroups during the COVID-19 pandemic: a longitudinal study

BACKGROUND

Social networks, i.e., all social relationships that people have, contribute to well-being and health. Governmental measures against COVID-19 were explicitly aimed to decrease physical social contact. We evaluated ego-centric social network structure and function, and changes therein, among various sociodemographic subgroups before and during the COVID-19 pandemic.

METHODS

Independently living Dutch adults aged 40 years and older participating in the SaNAE longitudinal cohort study filled in online questionnaires in 2019 and 2020. Changes in network size (network structure) and social supporters (network function) were assessed. Associations with risk for changes (versus stable) were assessed for sociodemographic subgroups (sex, age, educational level, and urbanization level) using multivariable regression analyses, adjusted for confounders.

RESULTS

Of 3,344 respondents 55% were men with a mean age of 65 years (age range 41-95 in 2020). In all assessed sociodemographic subgroups, decreases were observed in mean network size (total population: 11.4 to 9.8), the number of emotional supporters (7.2 to 6.1), and practical supporters (2.2 to 1.8), and an increase in the number of informational supporters (4.1 to 4.7). In all subgroups, the networks changed to being more family oriented. Some individuals increased their network size or number of supporters; they were more often women, higher-educated, or living in rural areas.

CONCLUSION

The COVID-19 pandemic impacted social networks of people aged 40 years and older, as they increased informational support and reduced the number of their social relationships, mainly in terms of emotional and practical supporters. Notably, some individuals did not show such unfavorable trends and managed to reorganize their networks to attribute social support roles more centrally.

Novel estimates reveal subnational heterogeneities in disease-relevant contact patterns in the United States

Population contact patterns fundamentally determine the spread of directly transmitted airborne pathogens such as SARS-CoV-2 and influenza. Reliable quantitative estimates of contact patterns are therefore critical to modeling and reducing the spread of directly transmitted infectious diseases and to assessing the effectiveness of interventions intended to limit risky contacts. While many countries have used surveys and contact diaries to collect national-level contact data, local-level estimates of age-specific contact patterns remain rare. Yet, these local-level data are critical since disease dynamics and public health policy typically vary by geography. To overcome this challenge, we introduce a flexible model that can estimate age-specific contact patterns at the subnational level by combining national-level interpersonal contact data with other locality-specific data sources using multilevel regression with poststratification (MRP). We estimate daily contact matrices for all 50 US states and Washington DC from April 2020 to May 2021 using national contact data from the US. Our results reveal important state-level heterogeneities in levels and trends of contacts across the US over the course of the COVID-19 pandemic, with implications for the spread of respiratory diseases.

Investigation of turning points in the effectiveness of Covid-19 social distancing

Covid-19 is the first digitally documented pandemic in history, presenting a unique opportunity to learn how to best deal with similar crises in the future. In this study we have carried out a model-based evaluation of the effectiveness of social distancing, using Austria and Slovenia as examples. Whereas the majority of comparable studies have postulated a negative relationship between the stringency of social distancing (reduction in social contacts) and the scale of the epidemic, our model has suggested a varying relationship, with turning points at which the system changes its predominant regime from 'less social distancing-more cumulative deaths and infections' to 'less social distancing-fewer cumulative deaths and infections'. This relationship was found to persist in scenarios with distinct seasonal variation in transmission and limited national intensive care capabilities. In such situations, relaxing social distancing during low transmission seasons (spring and summer) was found to relieve pressure from high transmission seasons (fall and winter) thus reducing the total number of infections and fatalities. Strategies that take into account this relationship could be particularly beneficial in situations where long-term containment is not feasible.

Investigating the relationship between interventions, contact patterns, and SARS-CoV-2 transmissibility

BACKGROUND

After a rapid upsurge of COVID-19 cases in Italy during the fall of 2020, the government introduced a three-tiered restriction system aimed at increasing physical distancing. The Ministry of Health, after periodic epidemiological risk assessments, assigned a tier to each of the 21 Italian regions and autonomous provinces. It is still unclear to what extent these different sets of measures altered the number of daily interactions and the social mixing patterns.

METHODS AND FINDINGS

We conducted a survey between July 2020 and March 2021 to monitor changes in social contact patterns among individuals in the metropolitan city of Milan, Italy, which was hardly hit by the second wave of the COVID-19 pandemic. The number of daily contacts during periods characterized by different levels of restrictions was analyzed through negative binomial regression models and age-specific contact matrices were estimated under the different tiers of restrictions. By relying on the empirically estimated mixing patterns, we quantified relative changes in SARS-CoV-2 transmission potential associated with the different tiers. As tighter restrictions were implemented during the fall of 2020, a progressive reduction in the mean number of daily contacts recorded by study participants was observed: from 15.9 % under mild restrictions (yellow tier), to 41.8 % under strong restrictions (red tier). Higher restrictions levels were also found to increase the relative contribution of contacts occurring within the household. The SARS-CoV-2 reproduction number was estimated to decrease by 17.1 % (95 %CI: 1.5-30.1), 25.1 % (95 %CI: 13.0-36.0) and 44.7 % (95 %CI: 33.9-53.0) under the yellow, orange, and red tiers, respectively.

CONCLUSIONS

Our results give an important quantification of the expected contribution of different restriction levels in shaping social contacts and decreasing the transmission potential of SARS-CoV-2. These estimates can find an operational use in anticipating the effect that the implementation of these tiered restriction can have on SARS-CoV-2 reproduction number under an evolving epidemiological situation.

Cohort profile: the British Columbia COVID-19 Population Mixing Patterns Survey (BC-Mix)

PURPOSE

Several non-pharmaceutical interventions, such as physical distancing, handwashing, self-isolation, and school and business closures, were implemented in British Columbia (BC) following the first laboratory-confirmed case of COVID-19 on 26 January 2020, to minimise in-person contacts that could spread infections. The BC COVID-19 Population Mixing Patterns Survey (BC-Mix) was established as a surveillance system to measure behaviour and contact patterns in BC over time to inform the timing of the easing/re-imposition of control measures. In this paper, we describe the BC-Mix survey design and the demographic characteristics of respondents.

PARTICIPANTS

The ongoing repeated online survey was launched in September 2020. Participants are mainly recruited through social media platforms (including Instagram, Facebook, YouTube, WhatsApp). A follow-up survey is sent to participants 2-4 weeks after completing the baseline survey. Survey responses are weighted to BC's population by age, sex, geography and ethnicity to obtain generalisable estimates. Additional indices such as the Material and Social Deprivation Index, residential instability, economic dependency, and others are generated using census and location data.

FINDINGS TO DATE

As of 26 July 2021, over 61 000 baseline survey responses were received of which 41 375 were eligible for analysis. Of the eligible participants, about 60% consented to follow-up and about 27% provided their personal health numbers for linkage with healthcare databases. Approximately 83.5% of respondents were female, 58.7% were 55 years or older, 87.5% identified as white and 45.9% had at least a university degree. After weighting, approximately 50% were female, 39% were 55 years or older, 65% identified as white and 50% had at least a university degree.

FUTURE PLANS

Multiple papers describing contact patterns, physical distancing measures, regular handwashing and facemask wearing, modelling looking at impact of physical distancing measures and vaccine acceptance, hesitancy and uptake are either in progress or have been published.

Human behaviour, NPI and mobility reduction effects on COVID-19 transmission in different countries of the world

Background

The outbreak of Coronavirus disease, which originated in Wuhan, China in 2019, has affected the lives of billions of people globally. Throughout 2020, the reproduction number of COVID-19 was widely used by decision-makers to explain their strategies to control the pandemic.

Methods

In this work, we deduce and analyze both initial and effective reproduction numbers for 12 diverse world regions between February and December of 2020. We consider mobility reductions, mask wearing and compliance with masks, mask efficacy values alongside other non-pharmaceutical interventions (NPIs) in each region to get further insights in how each of the above factored into each region’s SARS-COV-2 transmission dynamic.

Results

We quantify in each region the following reductions in the observed effective reproduction numbers of the pandemic: i) reduction due to decrease in mobility (as captured in Google mobility reports); ii) reduction due to mask wearing and mask compliance; iii) reduction due to other NPI’s, over and above the ones identified in i) and ii).

Conclusion

In most cases mobility reduction coming from nationwide lockdown measures has helped stave off the initial wave in countries who took these types of measures. Beyond the first waves, mask mandates and compliance, together with social-distancing measures (which we refer to as other NPI’s) have allowed some control of subsequent disease spread. The methodology we propose here is novel and can be applied to other respiratory diseases such as influenza or RSV.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12889-022-13921-3).

SARS-CoV-2 Catalonia contact tracing program: evaluation of key performance indicators

Background

Guidance on SARS-CoV-2 contact tracing indicators have been recently revised by international public health agencies. The aim of the study is to describe and analyse contact tracing indicators based on Catalonia’s (Spain) real data and proposing to update them according to recommendations.

Methods

Retrospective cohort analysis including Catalonia’s contact tracing dataset from 20 May until 31 December 2020. Descriptive statistics are performed including sociodemographic stratification by age, and differences are assessed over the study period.

Results

We analysed 923,072 contacts from 301,522 SARS-CoV-2 cases with identified contacts (67.1% contact tracing coverage). The average number of contacts per case was 4.6 (median 3, range 1–243). A total of 403,377 contacts accepted follow-up through three phone calls over a 14-day quarantine period (84.5% of contacts requiring follow-up). The percentage of new cases declared as contacts 14 days prior to diagnosis evolved from 33.9% in May to 57.9% in November. All indicators significantly improved towards the target over time (p < 0.05 for all four indicators).

Conclusions

Catalonia’s SARS-CoV-2 contact tracing indicators improved over time despite challenging context. The critical revision of the indicator’s framework aims to provide essential information in control policies, new indicators proposed will improve system delay’s follow-up. The study provides information on COVID-19 indicators framework experience from country’s real data, allowing to improve monitoring tools in 2021–2022. With the SARS-CoV-2 pandemic being so harmful to health systems and globally, is important to analyse and share contact tracing data with the scientific community.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13695-8.

Patterns of social mixing in England changed in line with restrictions during the COVID-19 pandemic (September 2020 to April 2022)

Social mixing contributes to the transmission of SARS-CoV-2. We developed a composite measure for risky social mixing, investigating changes during the pandemic and factors associated with risky mixing. Forty-five waves of online cross-sectional surveys were used (n = 78,917 responses; 14 September 2020 to 13 April 2022). We investigated socio-demographic, contextual and psychological factors associated with engaging in highest risk social mixing in England at seven timepoints. Patterns of social mixing varied over time, broadly in line with changes in restrictions. Engaging in highest risk social mixing was associated with being younger, less worried about COVID-19, perceiving a lower risk of COVID-19, perceiving COVID-19 to be a less severe illness, thinking the risks of COVID-19 were being exaggerated, not agreeing that one’s personal behaviour had an impact on how COVID-19 spreads, and not agreeing that information from the UK Government about COVID-19 can be trusted. Our composite measure for risky social mixing varied in line with restrictions in place at the time of data collection, providing some validation of the measure. While messages targeting psychological factors may reduce higher risk social mixing, achieving a large change in risky social mixing in a short space of time may necessitate a reimposition of restrictions.

North Carolina public school teachers' contact patterns and mask use within and outside of school during the prevaccine phase of the COVID-19 pandemic

BACKGROUND

Teachers are central to school-associated transmission networks, but little is known about their behavioral patterns during the COVID-19 pandemic.

METHODS

We conducted a cross-sectional survey of 700 North Carolina public school teachers in 4 districts open to in-person learning in November-December 2020 (pre-COVID-19 vaccines). We assessed indoor and outdoor time spent, numbers of people encountered at <6 feet ("close contacts"), and mask use by teachers and those around them at specific locations on the most recent weekday and weekend day.

RESULTS

Nearly all respondents reported indoor time at home (98%) and school (94%) on the most recent weekday, while 62% reported indoor time at stores, 18% at someone else's home, and 17% at bars/restaurants. Responses were similar for the most recent weekend day, excepting school (where 5% reported indoor time). Most teachers (>94%) reported wearing masks inside school, stores, and salons; intermediate percentages (∼50%-85%) inside places of worship, bars/restaurants, and recreational settings; and few (<25%) in their or others' homes. Approximately half reported daily close contact with students.

CONCLUSIONS

As schools reopened in the COVID-19 pandemic, potential transmission opportunities arose through close contacts within and outside of school, along with suboptimal mask use by teachers and/or those around them. Our granular estimates underscore the importance of multilayered mitigation strategies and can inform interventions and mathematical models addressing school-associated transmission.

Higher education responses to COVID-19 in the United States: Evidence for the impacts of university policy

With a dataset of testing and case counts from over 1,400 institutions of higher education (IHEs) in the United States, we analyze the number of infections and deaths from SARS-CoV-2 in the counties surrounding these IHEs during the Fall 2020 semester (August to December, 2020). We find that counties with IHEs that remained primarily online experienced fewer cases and deaths during the Fall 2020 semester; whereas before and after the semester, these two groups had almost identical COVID-19 incidence. Additionally, we see fewer cases and deaths in counties with IHEs that reported conducting any on-campus testing compared to those that reported none. To perform these two comparisons, we used a matching procedure designed to create well-balanced groups of counties that are aligned as much as possible along age, race, income, population, and urban/rural categories-demographic variables that have been shown to be correlated with COVID-19 outcomes. We conclude with a case study of IHEs in Massachusetts-a state with especially high detail in our dataset-which further highlights the importance of IHE-affiliated testing for the broader community. The results in this work suggest that campus testing can itself be thought of as a mitigation policy and that allocating additional resources to IHEs to support efforts to regularly test students and staff would be beneficial to mitigating the spread of COVID-19 in a pre-vaccine environment.

Time trends in social contacts before and during the COVID-19 pandemic: the CONNECT study

BACKGROUND

Since the beginning of the COVID-19 pandemic, many countries, including Canada, have adopted unprecedented physical distancing measures such as closure of schools and non-essential businesses, and restrictions on gatherings and household visits. We described time trends in social contacts for the pre-pandemic and pandemic periods in Quebec, Canada.

METHODS

CONNECT is a population-based study of social contacts conducted shortly before (2018/2019) and during the COVID-19 pandemic (April 2020 - February 2021), using the same methodology for both periods. We recruited participants by random digit dialing and collected data by self-administered web-based questionnaires. Questionnaires documented socio-demographic characteristics and social contacts for two assigned days. A contact was defined as a two-way conversation at a distance ≤ 2 m or as a physical contact, irrespective of masking. We used weighted generalized linear models with a Poisson distribution and robust variance (taking possible overdispersion into account) to compare the mean number of social contacts over time and by socio-demographic characteristics.

RESULTS

A total of 1291 and 5516 Quebecers completed the study before and during the pandemic, respectively. Contacts significantly decreased from a mean of 8 contacts/day prior to the pandemic to 3 contacts/day during the spring 2020 lockdown. Contacts remained lower than the pre-COVID period thereafter (lowest = 3 contacts/day during the Christmas 2020/2021 holidays, highest = 5 in September 2020). Contacts at work, during leisure activities/in other locations, and at home with visitors showed the greatest decreases since the beginning of the pandemic. All sociodemographic subgroups showed significant decreases of contacts since the beginning of the pandemic. The mixing matrices illustrated the impact of public health measures (e.g. school closure, gathering restrictions) with fewer contacts between children/teenagers and fewer contacts outside of the three main diagonals of contacts between same-age partners/siblings and between children and their parents.

CONCLUSION

Physical distancing measures in Quebec significantly decreased social contacts, which most likely mitigated the spread of COVID-19.

Language and the cultural markers of COVID-19

Despite its universal nature, the impact of COVID-19 has not been geographically homogeneous. While certain countries and regions have been severely affected, registering record infection rates and excess deaths, others experienced only milder outbreaks. We investigate to what extent human factors, in particular cultural origins reflected in different attitudes and behavioural norms, can explain different degrees of exposure to the virus. Motivated by the linguistic relativity hypothesis, we take language as a proxy for cultural origins and exploit the exogenous variation in the language spoken around the border that divides the French- and German-speaking parts of Switzerland to estimate the impact of culture on exposure to COVID-19. The results obtained using a spatial regression discontinuity design reveal, that within 50- and 25- kilometres bandwidth from the language border, the average COVID-19 exposure levels for individuals in French speaking municipalities was higher. In particular, we find that German speaking municipalities were associated with a reduction of around 40% - 50% in the odds of COVID-19 exposure compared to the French speaking municipalities.

Workplace contact patterns in England during the COVID-19 pandemic: Analysis of the Virus Watch prospective cohort study

Background

Workplaces are an important potential source of SARS-CoV-2 exposure; however, investigation into workplace contact patterns is lacking. This study aimed to investigate how workplace attendance and features of contact varied between occupations across the COVID-19 pandemic in England.

Methods

Data were obtained from electronic contact diaries (November 2020-November 2021) submitted by employed/self-employed prospective cohort study participants (n=4,616). We used mixed models to investigate the effects of occupation and time for: workplace attendance, number of people sharing workspace, time spent sharing workspace, number of close contacts, and usage of face coverings.

Findings

Workplace attendance and contact patterns varied across occupations and time. The predicted probability of intense space sharing during the day was highest for healthcare (78% [95% CI: 75-81%]) and education workers (64% [59%-69%]), who also had the highest probabilities for larger numbers of close contacts (36% [32%-40%] and 38% [33%-43%] respectively). Education workers also demonstrated relatively low predicted probability (51% [44%-57%]) of wearing a face covering during close contact. Across all occupational groups, workspace sharing and close contact increased and usage of face coverings decreased during phases of less stringent restrictions.

Interpretation

Major variations in workplace contact patterns and mask use likely contribute to differential COVID-19 risk. Patterns of variation by occupation and restriction phase may inform interventions for future waves of COVID-19 or other respiratory epidemics. Across occupations, increasing workplace contact and reduced face covering usage is concerning given ongoing high levels of community transmission and emergence of variants.

Funding

Medical Research Council; HM Government; Wellcome Trust.

Behavior changes and functional capacity Physical, social, and dietary behavioral changes during the COVID-19 crisis and their effects on functional capacity in older adults

Background

This two-year follow-up study aimed to identify factors associated with unhealthy behaviors during the COVID-19 pandemic and examine their impact on functional capacity in older adults.

Methods

Altogether, 536 adults aged ≥65 years participated in this study. The frequency of going out, exercise habits, face-to-face and non-face-to-face interactions, social participation, and eating habits were examined as behavioral factors before and after the first declaration of a state of emergency in Japan. Functional capacity was assessed using the Tokyo Metropolitan Institute of Gerontology Index of Competence.

Results

Using latent class analysis considering changes in the six behaviors, the participants were divided into healthy (n = 289) and unhealthy (n = 247) behavior groups. The male sex was associated with 2.36 times higher odds, diabetes with 2.19 times higher odds, depressive mood with 1.83 times higher odds, poor subjective economic status with 2.62 times higher odds, and living alone with 44% lower odds of being unhealthy. The unhealthy behavior group showed significantly decreased functional capacity (B =−1.56 [−1.98, −1.14]) than the healthy behavior group. For each behavior, negative changes in going out (B =−0.99 [−1.60, −0.37]), face-to-face interaction (B =−0.65 [−1.16, −0.13]), and non-face-to-face interactions (B =−0.80 [−1.36, −0.25]) were associated with a decline in functional capacity.

Conclusion

Our results showed four factors associated with engaging in unhealthy lifestyle behaviors and how behavioral changes affect functional capacity decline during the COVID-19 pandemic, which will help to develop public health approaches

Longitudinal social contacts among school-aged children during the COVID-19 pandemic: the Bay Area Contacts among Kids (BACK) study

BACKGROUND

The San Francisco Bay Area was the first region in the United States to enact school closures to mitigate SARS-CoV-2 transmission. The effects of closures on contact patterns for schoolchildren and their household members remain poorly understood.

METHODS

We conducted serial cross-sectional surveys (May 2020, September 2020, February 2021) of Bay Area households with children to estimate age-structured daily contact rates for children and their adult household members. We examined changes in contact rates over the course of the COVID-19 pandemic, including after vaccination of household members, and compared contact patterns by household demographics using generalized estimating equations clustered by household.

RESULTS

We captured contact histories for 1,967 households on behalf of 2,674 children, comprising 15,087 non-household contacts over the three waves of data collection. Shortly after the start of shelter-in-place orders in May 2020, daily contact rates were higher among children from Hispanic families (1.52 more contacts per child per day; [95% CI: 1.14-2.04]), households whose parents were unable to work from home (1.82; [1.40-2.40]), and households with income < $150,000 (1.75; [1.33-2.33]), after adjusting for other demographic characteristics and household clustering. Between May and August 2020, non-household contacts of children increased by 145% (ages 5-12) and 172% (ages 13-17), despite few children returning to in-person instruction. Non-household contact rates among children were higher-by 1.75 [1.28-2.40] and 1.42 [0.89-2.24] contacts per child per day in 5-12 and 13-17 age groups, respectively, in households where at least one adult was vaccinated against COVID-19, compared to children's contact rates in unvaccinated households.

CONCLUSIONS

Child contact rates rebounded despite schools remaining closed, as parents obtained childcare, children engaged in contact in non-school settings, and family members were vaccinated. The waning reductions observed in non-household contact rates of schoolchildren and their family members during a prolonged school closure suggests the strategy may be ineffective for long-term SARS-CoV-2 transmission mitigation. Reductions in age-assortative contacts were not as apparent amongst children from lower income households or households where adults could not work from home. Heterogeneous reductions in contact patterns raise concerning racial, ethnic and income-based inequities associated with long-term school closures as a COVID-19 mitigation strategy.

"What should be computed" for supporting post-pandemic recovery policymaking? A life-oriented perspective

The COVID-19 pandemic has caused various impacts on people's lives, while changes in people's lives have shown mixed effects on mitigating the spread of the SARS-CoV-2 virus. Understanding how to capture such two-way interactions is crucial, not only to control the pandemic but also to support post-pandemic urban recovery policies. As suggested by the life-oriented approach, the above interactions exist with respect to a variety of life domains, which form a complex behavior system. Through a review of the literature, this paper first points out inconsistent evidence about behavioral factors affecting the spread of COVID-19, and then argues that existing studies on the impacts of COVID-19 on people's lives have ignored behavioral co-changes in multiple life domains. Furthermore, selected uncertain trends of people's lives for the post-pandemic recovery are described. Finally, this paper concludes with a summary about "what should be computed?" in Computational Urban Science with respect to how to catch up with delays in the SDGs caused by the COVID-19 pandemic, how to address digital divides and dilemmas of e-society, how to capture behavioral co-changes during the post-pandemic recovery process, and how to better manage post-pandemic recovery policymaking processes.

Rapid Review of Social Contact Patterns During the COVID-19 Pandemic

BACKGROUND

Physical distancing measures aim to reduce person-to-person contact, a key driver of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. In response to unprecedented restrictions on human contact during the coronavirus disease 2019 (COVID-19) pandemic, studies measured social contact patterns under the implementation of physical distancing measures. This rapid review synthesizes empirical data on the changing social contact patterns during the COVID-19 pandemic.

METHOD

We conducted a systematic review using PubMed, Medline, Embase, and Google Scholar following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We descriptively compared the distribution of contacts observed during the pandemic to pre-COVID data across countries to explore changes in contact patterns during physical distancing measures.

RESULTS

We identified 12 studies reporting social contact patterns during the COVID-19 pandemic. Eight studies were conducted in European countries and eleven collected data during the initial mitigation period in the spring of 2020 marked by government-declared lockdowns. Some studies collected additional data after relaxation of initial mitigation. Most study settings reported a mean of between 2 and 5 contacts per person per day, a substantial reduction compared to pre-COVID rates, which ranged from 7 to 26 contacts per day. This reduction was pronounced for contacts outside of the home. Consequently, levels of assortative mixing by age substantially declined. After relaxation of initial mitigation, mean contact rates increased but did not return to pre-COVID levels. Increases in contacts post-relaxation were driven by working-age adults.

CONCLUSION

Information on changes in contact patterns during physical distancing measures can guide more realistic representations of contact patterns in mathematical models for SARS-CoV-2 transmission.

Differential impact of physical distancing strategies on social contacts relevant for the spread of SARS-CoV-2: evidence from a cross-national online survey, March-April 2020

OBJECTIVES

We investigate changes in social contact patterns following the gradual introduction of non-pharmaceutical interventions and their implications for infection transmission in the early phase of the pandemic.

DESIGN, SETTING AND PARTICIPANTS

We conducted an online survey based on targeted Facebook advertising campaigns across eight countries (Belgium, France, Germany, Italy, the Netherlands, Spain, UK and USA), achieving a sample of 51 233 questionnaires in the period 13 March-12 April 2020. Poststratification weights based on census information were produced to correct for selection bias.

OUTCOME MEASURES

Participants provided data on social contact numbers, adoption of protective behaviours and perceived level of threat. These data were combined to derive a weekly index of infection transmission, the net reproduction number [Formula: see text] .

RESULTS

Evidence from the USA and UK showed that the number of daily contacts mainly decreased after governments issued the first physical distancing guidelines. In mid-April, daily social contact numbers had decreased between 61% in Germany and 87% in Italy with respect to pre-COVID-19 levels, mostly due to a contraction in contacts outside the home. Such reductions, which were uniform across age groups, were compatible with an [Formula: see text] equal or smaller than one in all countries, except Germany. This indicates lower levels of infection transmission, especially in a period of gradual increase in the adoption rate of the face mask outside the home.

CONCLUSIONS

We provided a comparable set of statistics on social contact patterns during the COVID-19 pandemic for eight high-income countries, disaggregated by week and other demographic factors, which could be leveraged by the scientific community for developing more realistic epidemic models of COVID-19.

Individual social contact data and population mobility data as early markers of SARS-CoV-2 transmission dynamics during the first wave in Germany-an analysis based on the COVIMOD study

BACKGROUND

The effect of contact reduction measures on infectious disease transmission can only be assessed indirectly and with considerable delay. However, individual social contact data and population mobility data can offer near real-time proxy information. The aim of this study is to compare social contact data and population mobility data with respect to their ability to reflect transmission dynamics during the first wave of the SARS-CoV-2 pandemic in Germany.

METHODS

We quantified the change in social contact patterns derived from self-reported contact survey data collected by the German COVIMOD study from 04/2020 to 06/2020 (compared to the pre-pandemic period from previous studies) and estimated the percentage mean reduction over time. We compared these results as well as the percentage mean reduction in population mobility data (corrected for pre-pandemic mobility) with and without the introduction of scaling factors and specific weights for different types of contacts and mobility to the relative reduction in transmission dynamics measured by changes in R values provided by the German Public Health Institute.

RESULTS

We observed the largest reduction in social contacts (90%, compared to pre-pandemic data) in late April corresponding to the strictest contact reduction measures. Thereafter, the reduction in contacts dropped continuously to a minimum of 73% in late June. Relative reduction of infection dynamics derived from contact survey data underestimated the one based on reported R values in the time of strictest contact reduction measures but reflected it well thereafter. Relative reduction of infection dynamics derived from mobility data overestimated the one based on reported R values considerably throughout the study. After the introduction of a scaling factor, specific weights for different types of contacts and mobility reduced the mean absolute percentage error considerably; in all analyses, estimates based on contact data reflected measured R values better than those based on mobility.

CONCLUSIONS

Contact survey data reflected infection dynamics better than population mobility data, indicating that both data sources cover different dimensions of infection dynamics. The use of contact type-specific weights reduced the mean absolute percentage errors to less than 1%. Measuring the changes in mobility alone is not sufficient for understanding the changes in transmission dynamics triggered by public health measures.

Projecting contact matrices in 177 geographical regions: An update and comparison with empirical data for the COVID-19 era

Mathematical models have played a key role in understanding the spread of directly-transmissible infectious diseases such as Coronavirus Disease 2019 (COVID-19), as well as the effectiveness of public health responses. As the risk of contracting directly-transmitted infections depends on who interacts with whom, mathematical models often use contact matrices to characterise the spread of infectious pathogens. These contact matrices are usually generated from diary-based contact surveys. However, the majority of places in the world do not have representative empirical contact studies, so synthetic contact matrices have been constructed using more widely available setting-specific survey data on household, school, classroom, and workplace composition combined with empirical data on contact patterns in Europe. In 2017, the largest set of synthetic contact matrices to date were published for 152 geographical locations. In this study, we update these matrices with the most recent data and extend our analysis to 177 geographical locations. Due to the observed geographic differences within countries, we also quantify contact patterns in rural and urban settings where data is available. Further, we compare both the 2017 and 2020 synthetic matrices to out-of-sample empirically-constructed contact matrices, and explore the effects of using both the empirical and synthetic contact matrices when modelling physical distancing interventions for the COVID-19 pandemic. We found that the synthetic contact matrices show qualitative similarities to the contact patterns in the empirically-constructed contact matrices. Models parameterised with the empirical and synthetic matrices generated similar findings with few differences observed in age groups where the empirical matrices have missing or aggregated age groups. This finding means that synthetic contact matrices may be used in modelling outbreaks in settings for which empirical studies have yet to be conducted.

Projecting contact matrices in 177 geographical regions: An update and comparison with empirical data for the COVID-19 era

Mathematical models have played a key role in understanding the spread of directly-transmissible infectious diseases such as Coronavirus Disease 2019 (COVID-19), as well as the effectiveness of public health responses. As the risk of contracting directly-transmitted infections depends on who interacts with whom, mathematical models often use contact matrices to characterise the spread of infectious pathogens. These contact matrices are usually generated from diary-based contact surveys. However, the majority of places in the world do not have representative empirical contact studies, so synthetic contact matrices have been constructed using more widely available setting-specific survey data on household, school, classroom, and workplace composition combined with empirical data on contact patterns in Europe. In 2017, the largest set of synthetic contact matrices to date were published for 152 geographical locations. In this study, we update these matrices with the most recent data and extend our analysis to 177 geographical locations. Due to the observed geographic differences within countries, we also quantify contact patterns in rural and urban settings where data is available. Further, we compare both the 2017 and 2020 synthetic matrices to out-of-sample empirically-constructed contact matrices, and explore the effects of using both the empirical and synthetic contact matrices when modelling physical distancing interventions for the COVID-19 pandemic. We found that the synthetic contact matrices show qualitative similarities to the contact patterns in the empirically-constructed contact matrices. Models parameterised with the empirical and synthetic matrices generated similar findings with few differences observed in age groups where the empirical matrices have missing or aggregated age groups. This finding means that synthetic contact matrices may be used in modelling outbreaks in settings for which empirical studies have yet to be conducted.

Projecting contact matrices in 177 geographical regions: An update and comparison with empirical data for the COVID-19 era

Mathematical models have played a key role in understanding the spread of directly-transmissible infectious diseases such as Coronavirus Disease 2019 (COVID-19), as well as the effectiveness of public health responses. As the risk of contracting directly-transmitted infections depends on who interacts with whom, mathematical models often use contact matrices to characterise the spread of infectious pathogens. These contact matrices are usually generated from diary-based contact surveys. However, the majority of places in the world do not have representative empirical contact studies, so synthetic contact matrices have been constructed using more widely available setting-specific survey data on household, school, classroom, and workplace composition combined with empirical data on contact patterns in Europe. In 2017, the largest set of synthetic contact matrices to date were published for 152 geographical locations. In this study, we update these matrices with the most recent data and extend our analysis to 177 geographical locations. Due to the observed geographic differences within countries, we also quantify contact patterns in rural and urban settings where data is available. Further, we compare both the 2017 and 2020 synthetic matrices to out-of-sample empirically-constructed contact matrices, and explore the effects of using both the empirical and synthetic contact matrices when modelling physical distancing interventions for the COVID-19 pandemic. We found that the synthetic contact matrices show qualitative similarities to the contact patterns in the empirically-constructed contact matrices. Models parameterised with the empirical and synthetic matrices generated similar findings with few differences observed in age groups where the empirical matrices have missing or aggregated age groups. This finding means that synthetic contact matrices may be used in modelling outbreaks in settings for which empirical studies have yet to be conducted.

A national survey on COVID-19 second-wave lockdowns on older adults' mental wellbeing, health-seeking behaviours and social outcomes across Australia

Background

The impact of severe second lockdown measures on older adults’ wellbeing is unknown. We aimed to (i) identify the impact of the second lockdown that resulted from the second wave of COVID-19 cases on older Australians’ quality of life; (ii) compare the impact of second wave lockdowns in Victoria, Australia’s second most populous State, to those in other States and Territories not in lockdown.

Methods

A national cross-sectional study of community-dwelling older adults completed online questionnaires for quality of life, social networks, healthcare access, and perceived impact of COVID-19 between July to September 2020. Tobit regression was used to measure the relationships of healthcare service access and social networks with quality of life of older adults in Victoria compared to those in the rest of Australia.

Results

A total of 2,990 respondents (mean [SD] age, 67.3 [7.0]; 66.8 % female) participated. At time of data collection, Victoria’s second COVID-19 lockdown had been in force for an average 51.7 days. Median quality of life scores were significantly higher in Victoria compared to the rest of Australia (t_2,827=2.25 p = 0.025). Being female (95 % CI, -0.051–0.020), having lower educational attainment (95 % CI, -0.089–-0.018), receiving government benefits (95 % CI, -0.054–-0.024), having small social networks (95 % CI, 0.006–0.009) and self-reported physical chronic health conditions were all independent predictors of lower quality of life.

Conclusions

Longer-term studies are required to provide more robust evidence of the impact as restrictions lift and normal social conventions return.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02352-1.

SARS-CoV-2 transmission in educational settings during an early summer epidemic wave in Luxembourg, 2020

BACKGROUND

Following a first wave in spring and gradual easing of lockdown, Luxembourg experienced an early second epidemic wave of SARS-CoV-2 before the start of summer school holidays on 15th July. This provided the opportunity to investigate the role of school-age children and school settings for transmission.

METHODS

We compared the incidence of SARS-CoV-2 in school-age children, teachers and the general working population in Luxembourg during two epidemic waves: a spring wave from March-April 2020 corresponding to general lockdown with schools being closed and May-July 2020 corresponding to schools being open. We assessed the number of secondary transmissions occurring in schools between May and July 2020 using routine contact tracing data.

RESULTS

During the first wave in March-April 2020 when schools were closed, the incidence in pupils peaked at 28 per 100,000, while during the second wave in May-July 2020 when schools were open, incidence peaked 100 per 100,000. While incidence of SARS-CoV-2 was higher in adults than in children during the first spring wave, no significant difference was observed during the second wave in early summer. Between May and July 2020, we identified a total of 390 and 34 confirmed COVID-19 cases among 90,150 school-age children and 11,667 teachers, respectively. We further estimate that 179 primary cases caused 49 secondary cases in schools. While some small clusters of mainly student-to-student transmission within the same class were identified, we did not observe any large outbreaks with multiple generations of infection.

CONCLUSIONS

Transmission of SARS-CoV-2 within Luxembourg schools was limited during an early summer epidemic wave in 2020. Precautionary measures including physical distancing as well as easy access to testing, systematic contact tracing appears to have been successful in mitigating transmission within educational settings.

Quantifying population contact patterns in the United States during the COVID-19 pandemic

SARS-CoV-2 is transmitted primarily through close, person-to-person interactions. Physical distancing policies can control the spread of SARS-CoV-2 by reducing the amount of these interactions in a population. Here, we report results from four waves of contact surveys designed to quantify the impact of these policies during the COVID-19 pandemic in the United States. We surveyed 9,743 respondents between March 22 and September 26, 2020. We find that interpersonal contact has been dramatically reduced in the US, with an 82% (95%CI: 80%-83%) reduction in the average number of daily contacts observed during the first wave compared to pre-pandemic levels. However, we find increases in contact rates over the subsequent waves. We also find that certain demographic groups, including people under 45 and males, have significantly higher contact rates than the rest of the population. Tracking these changes can provide rapid assessments of the impact of physical distancing policies and help to identify at-risk populations.

CoMix: comparing mixing patterns in the Belgian population during and after lockdown

The COVID-19 pandemic has shown how a newly emergent communicable disease can lay considerable burden on public health. To avoid system collapse, governments have resorted to several social distancing measures. In Belgium, this included a lockdown and a following period of phased re-opening. A representative sample of Belgian adults was asked about their contact behaviour from mid-April to the beginning of August, during different stages of the intervention measures in Belgium. Use of personal protection equipment (face masks) and compliance to hygienic measures was also reported. We estimated the expected reproduction number computing the ratio of [Formula: see text] with respect to pre-pandemic data. During the first two waves (the first month) of the survey, the reduction in the average number of contacts was around 80% and was quite consistent across all age-classes. The average number of contacts increased over time, particularly for the younger age classes, still remaining significantly lower than pre-pandemic values. From the end of May to the end of July , the estimated reproduction number has a median value larger than one, although with a wide dispersion. Estimated [Formula: see text] fell below one again at the beginning of August. We have shown how a rapidly deployed survey can measure compliance to social distancing and assess its impact on COVID-19 spread. Monitoring the effectiveness of social distancing recommendations is of paramount importance to avoid further waves of COVID-19.

Quantifying the shift in social contact patterns in response to non-pharmaceutical interventions

Social contact mixing plays a critical role in influencing the transmission routes of infectious diseases. Moreover, quantifying social contact mixing patterns and their variations in a rapidly evolving pandemic intervened by changing public health measures is key for retroactive evaluation and proactive assessment of the effectiveness of different age- and setting-specific interventions. Contact mixing patterns have been used to inform COVID-19 pandemic public health decision-making; but a rigorously justified methodology to identify setting-specific contact mixing patterns and their variations in a rapidly developing pandemic, which can be informed by readily available data, is in great demand and has not yet been established. Here we fill in this critical gap by developing and utilizing a novel methodology, integrating social contact patterns derived from empirical data with a disease transmission model, that enables the usage of age-stratified incidence data to infer age-specific susceptibility, daily contact mixing patterns in workplace, household, school and community settings; and transmission acquired in these settings under different physical distancing measures. We demonstrated the utility of this methodology by performing an analysis of the COVID-19 epidemic in Ontario, Canada. We quantified the age- and setting (household, workplace, community, and school)-specific mixing patterns and their evolution during the escalation of public health interventions in Ontario, Canada. We estimated a reduction in the average individual contact rate from 12.27 to 6.58 contacts per day, with an increase in household contacts, following the implementation of control measures. We also estimated increasing trends by age in both the susceptibility to infection by SARS-CoV-2 and the proportion of symptomatic individuals diagnosed. Inferring the age- and setting-specific social contact mixing and key age-stratified epidemiological parameters, in the presence of evolving control measures, is critical to inform decision- and policy-making for the current COVID-19 pandemic.