scholarly journals Augmenting contact matrices with time-use data for fine-grained intervention modelling of disease dynamics: A modelling analysis

2020 ◽  
Author(s):  
Edwin van Leeuwen ◽  
Frank Sandmann ◽  
Keyword(s):  
Time Use ◽  
Large Scale ◽  
Close Contact ◽  
Public Health Intervention ◽  
Social Contact ◽  
Social Activities ◽  
Social Distancing ◽  
Epidemic Curve ◽  
Mixing Patterns ◽  
The Impact

AbstractBackgroundSocial distancing is an important public health intervention to reduce or interrupt the sustained community transmission of emerging infectious pathogens, such as SARS-CoV-2 during the coronavirus disease 2019 (COVID-19) pandemic. We aimed to explore the impact on the epidemic curve of fewer contacts when individuals reduce the time they spend on selected daily activities.MethodsWe combined the large-scale empirical data of a social contact survey and a time-use survey to estimate contact matrices by age group (0-15, 16-24, 25-44, 45-64, 65+) and daily activity (work, schooling, transportation, and four leisure activities: social visits, bar/cafe/restaurant visits, park visits, and non-essential shopping). We assumed that reductions in time are proportional to reductions in contacts. The derived matrices were then applied in an age-structured dynamic-transmission model of COVID-19 to explore the effects.FindingsThe relative reductions in the derived contact matrices were highest when closing schools (in ages 0-14 years), workplaces (15-64 years), and stopping social visits (65+ years). For COVID-19, the closure of workplaces, schools, and stopping social visits had the largest impact on reducing the epidemic curve and delaying its peak, while the predicted impact of fewer contacts in parks, bars/cafes/restaurants, and non-essential shopping were minimal.InterpretationWe successfully augmented contact matrices with time-use data to predict the highest impact of social distancing measures from reduced contacts when spending less time at work, school, and on social visits. Although the predicted impact from other leisure activities with potential for close physical contact were minimal, changes in mixing patterns and time-use immediately after re-allowing social activities may pose increased short-term transmission risks, especially in potentially crowded environments indoors.Research in contextEvidence before this studyWe searched PubMed for mathematical models using social contact matrices and time-use data to explore the impact of reduced social contacts as seen from social distancing measures adopted during the coronavirus disease 2019 (COVID-19) pandemic with the search string ((social OR physical) AND distancing) OR (contact* OR (contact matri*)) AND (time-use) AND (model OR models OR modeling OR modelling) from inception to May 06, 2020, with no language restrictions. We found several studies that used time-use data to re-create contact matrices based on time spent in similar locations or to calculate the length of exposure. We identified no study that augmented social contact matrices with time-use data to estimate the impact on transmission dynamics of reducing selected social activities and lifting these restrictions again, as seen during the COVID-19 pandemic.Added value of this studyOur study combines the empirical data of two large-scale, representative surveys to derive social contact matrices that enrich the frequency of contacts with the duration of exposure for selected social activities, which allows for more fine-grained mixing patterns and infectious disease modelling. We successfully applied the resulting matrices to estimate reductions in contacts from social distancing measures such as adopted during the COVID-19 pandemic, as well as the effect on the epidemic curve from increased social contacts when lifting such restrictions again.Implications of all the available evidenceSocial distancing measures are an important public health intervention to limit the close-contact transmission of emerging infectious pathogens by reducing the social mixing of individuals. Our model findings suggest a higher fraction of close-contact transmission occurs at work, schools, and social visits than from visits to parks, bars/cafes/restaurants, and non-essential shopping. The minimal predicted impact is suggestive of lifting the restrictions on certain activities and excluding them from the list of social distancing measures, unless required to maintain sufficient healthcare capacity. However, potential replacement effects of activities and in mixing patterns remain unclear, particularly immediately after re-allowing social activities again.

scholarly journals Close contact infection dynamics over time: insights from a second large-scale social contact survey in Flanders, Belgium, in 2010-2011

2020 ◽  
Author(s):  
Thang Van Hoang ◽  
Pietro Coletti ◽  
Yimer Wasihun Kiffe ◽  
Kim Van Kerckhove ◽  
Sarah Vercruysse ◽  
...  
Keyword(s):  
Large Scale ◽  
Close Contact ◽  
Social Contact ◽  
Contact Rates ◽  
Contact Patterns ◽  
Time Period ◽  
Social Mixing ◽  
Mixing Patterns ◽  
Contact Survey ◽  
The Impact

AbstractBackgroundIn 2010-2011, we conducted a social contact survey in Flanders, Belgium, aimed at improving and extending the design of the first social contact survey conducted in Belgium in 2006. This second social contact survey aimed to enable, for the first time, the estimation of social mixing patterns for an age range of 0 to 99 years and the investigation of whether contact rates remain stable over this 5-year time period.MethodsDifferent data mining techniques are used to explore the data, and the age-specific number of social contacts and the age-specific contact rates are modelled using a GAMLSS model. We compare different matrices using assortativeness measures. The relative change in the basic reproduction number (R0) and the ratio of relative incidences with 95% bootstrap confidence intervals (BCI) are employed to investigate and quantify the impact on epidemic spread due to differences in gender, day of the week, holiday vs. regular periods and changes in mixing patterns over the 5-year time gap between the 2006 and 2010-2011 surveys. Finally, we compare the fit of the contact matrices in 2006 and 2010-2011 to Varicella serological data.ResultsAll estimated contact patterns featured strong homophily in age and gender, especially for small children and adolescents. A 30% (95% BCI [17%; 37%] ) and 29% (95% BCI [14%; 40%] ) reduction in R0 was observed for weekend versus weekdays and for holiday versus regular periods, respectively. Significantly more interactions between people aged 60+ years and their grandchildren were observed on holiday and weekend days than on regular weekdays. Comparing contact patterns using different methods did not show any substantial differences over the 5-year time period under study.ConclusionsThe second social contact survey in Flanders, Belgium, endorses the findings of its 2006 predecessor and adds important information on the social mixing patterns of people older than 60 years of age. Based on this analysis, the mixing patterns of people older than 60 years exhibit considerable heterogeneity, and overall, the comparison of the two surveys shows that social contact rates can be assumed stable in Flanders over a time span of 5 years.

scholarly journals Augmenting contact matrices with time-use data for fine-grained intervention modelling of disease dynamics: A modelling analysis

2021 ◽  
pp. 096228022110370
Author(s):  
Edwin van Leeuwen ◽  
Frank Sandmann ◽  
Keyword(s):  
Public Health ◽  
Time Use ◽  
Large Scale ◽  
Leisure Activities ◽  
Public Health Intervention ◽  
Social Contact ◽  
Daily Activities ◽  
Transmission Model ◽  
Fine Grained ◽  
The Impact

Social distancing is an important public health intervention to reduce or interrupt the sustained community transmission of emerging infectious pathogens, such as severe acute respiratory syndrome-coronavirus-2 during the coronavirus disease 2019 pandemic. Contact matrices are typically used when evaluating such public health interventions to account for the heterogeneity in social mixing of individuals, but the surveys used to obtain the number of contacts often lack detailed information on the time individuals spend on daily activities. The present work addresses this problem by combining the large-scale empirical data of a social contact survey and a time-use survey to estimate contact matrices by age group (0--15, 16--24, 25–44, 45–64, 65+ years) and daily activity (work, schooling, transportation, and four leisure activities: social visits, bar/cafe/restaurant visits, park visits, and non-essential shopping). This augmentation allows exploring the impact of fewer contacts when individuals reduce the time they spend on selected daily activities as well as when lifting such restrictions again. For illustration, the derived matrices were then applied to an age-structured dynamic-transmission model of coronavirus disease 2019. Findings show how contact matrices can be successfully augmented with time-use data to inform the relative reductions in contacts by activity, which allows for more fine-grained mixing patterns and infectious disease modelling.

scholarly journals State-level needs for social distancing and contact tracing to contain COVID-19 in the United States 

2020 ◽  
Author(s):  
Weihsueh A. Chiu ◽  
Rebecca Fischer ◽  
Martial L. Ndeffo-Mbah
Keyword(s):  
Large Scale ◽  
District Of Columbia ◽  
State Level ◽  
The United States ◽  
Contact Tracing ◽  
Social Distancing ◽  
Epidemic Curve ◽  
Dynamics And Control ◽  
And Control ◽  
The Impact

Abstract Starting in mid-May 2020, many US states began relaxing social distancing measures that were put in place to mitigate the spread of COVID-19. To evaluate the impact of relaxation of restrictions on COVID-19 dynamics and control, we developed a transmission dynamic model and calibrated it to US state-level COVID-19 cases and deaths. We used this model to evaluate the impact of social distancing, testing and contact tracing on the COVID-19 epidemic in each state. As of July 22, 2020, we found only three states were on track to curtail their epidemic curve. Thirty-nine states and the District of Columbia may have to double their testing and/or tracing rates and/or rolling back reopening by 25%, while eight states require an even greater measure of combined testing, tracing, and distancing. Increased testing and contact tracing capacity is paramount for mitigating the recent large-scale increases in U.S. cases and deaths.

scholarly journals State-level impact of social distancing and testing on COVID-19 in the United States

2020 ◽  
Author(s):  
Weihsueh A. Chiu ◽  
Rebecca Fischer ◽  
Martial L. Ndeffo-Mbah
Keyword(s):  
United States ◽  
Large Scale ◽  
Disease Incidence ◽  
State Level ◽  
The United States ◽  
Contact Tracing ◽  
Reproductive Number ◽  
Social Distancing ◽  
Epidemic Curve ◽  
The Impact

Abstract Social distancing measures have been implemented in the United States (US) since March 2020, to mitigate the spread of SARS-CoV-2, the causative agent of COVID-19. However, by mid-May most states began relaxing these measures to support the resumption of economic activity, even as disease incidence continued to increase in many states. To evaluate the impact of relaxing social distancing restrictions on COVID-19 dynamics and control in the US, we developed a transmission dynamic model and calibrated it to US state-level COVID-19 cases and deaths from March to June 20th, 2020, using Bayesian methods. We used this model to evaluate the impact of reopening, social distancing, testing, contact tracing, and case isolation on the COVID-19 epidemic in each state. We found that using stay-at-home orders, most states were able to curtail their COVID-19 epidemic curve by reducing and achieving an effective reproductive number below 1. But by June 20th, 2020, only 19 states and the District of Columbia were on track to curtail their epidemic curve with a 75% confidence, at current levels of reopening. Of the remaining 31 states, 24 may have to double their current testing and/or contact tracing rate to curtail their epidemic curve, and seven need to further restrict social contact by 25% in addition to doubling their testing and contact tracing rates. When social distancing restrictions are being eased, greater state-level testing and contact tracing capacity remains paramount for mitigating the risk of large-scale increases in cases and deaths.

scholarly journals Close contact infection dynamics over time: insights from a second large-scale social contact survey in Flanders, Belgium, in 2010-2011

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Thang Van Hoang ◽  
Pietro Coletti ◽  
Yimer Wasihun Kifle ◽  
Kim Van Kerckhove ◽  
Sarah Vercruysse ◽  
...  
Keyword(s):  
Close Contact ◽  
Social Contact ◽  
Additive Models ◽  
Contact Rates ◽  
Contact Patterns ◽  
Time Period ◽  
Social Mixing ◽  
Mixing Patterns ◽  
Contact Survey ◽  
The Impact

Abstract Background In 2010-2011, we conducted a social contact survey in Flanders, Belgium, aimed at improving and extending the design of the first social contact survey conducted in Belgium in 2006. This second social contact survey aimed to enable, for the first time, the estimation of social mixing patterns for an age range of 0 to 99 years and the investigation of whether contact rates remain stable over this 5-year time period. Methods Different data mining techniques are used to explore the data, and the age-specific number of social contacts and the age-specific contact rates are modelled using a generalized additive models for location, scale and shape (GAMLSS) model. We compare different matrices using assortativeness measures. The relative change in the basic reproduction number (R0) and the ratio of relative incidences with 95% bootstrap confidence intervals (BCI) are employed to investigate and quantify the impact on epidemic spread due to differences in sex, day of the week, holiday vs. regular periods and changes in mixing patterns over the 5-year time gap between the 2006 and 2010-2011 surveys. Finally, we compare the fit of the contact matrices in 2006 and 2010-2011 to Varicella serological data. Results All estimated contact patterns featured strong homophily in age and sex, especially for small children and adolescents. A 30% (95% BCI [17%; 37%]) and 29% (95% BCI [14%; 40%]) reduction in R0 was observed for weekend versus weekdays and for holiday versus regular periods, respectively. Significantly more interactions between people aged 60+ years and their grandchildren were observed on holiday and weekend days than on regular weekdays. Comparing contact patterns using different methods did not show any substantial differences over the 5-year time period under study. Conclusions The second social contact survey in Flanders, Belgium, endorses the findings of its 2006 predecessor and adds important information on the social mixing patterns of people older than 60 years of age. Based on this analysis, the mixing patterns of people older than 60 years exhibit considerable heterogeneity, and overall, the comparison of the two surveys shows that social contact rates can be assumed stable in Flanders over a time span of 5 years.

scholarly journals Modelling the SARS-CoV-2 first epidemic wave in Greece: social contact patterns for impact assessment and an exit strategy from social distancing measures

2020 ◽  
Author(s):  
Vana Sypsa ◽  
Sotirios Roussos ◽  
Dimitrios Paraskevis ◽  
Theodore Lytras ◽  
S Sotirios Tsiodras ◽  
...  
Keyword(s):  
Impact Assessment ◽  
Attack Rate ◽  
Social Contact ◽  
Social Distancing ◽  
Relative Contribution ◽  
Contact Patterns ◽  
Social Mixing ◽  
Mixing Patterns ◽  
The Impact ◽  
Epidemic Wave

AbstractIn Greece, a nationwide lockdown to mitigate the transmission of SARS-CoV-2 was imposed on March 23, 2020. As by the end of April the first epidemic wave is waning, it is important to assess the infection attack rate and quantify the impact of physical distancing. We implemented a survey to assess social mixing patterns before the epidemic and during lockdown. We estimated R0 from surveillance data and assessed its decline as a result of physical distancing based on social contacts data. We applied a Susceptible-Exposed-Infectious-Recovered model to estimate the infection attack rate and the infection fatality ratio (IFR). As multiple social distancing measures were implemented simultaneously (schools/work/leisure), we assessed their overall impact as well as their relative contribution. R0 was estimated 2·38 (95%CI: 2·01,2·80). By April 26th, the infection attack rate was 0·12% (95%CrI: 0·06%,0·26%) and the IFR 1·12% (95%CrI: 0·55%,2·31%). During lockdown, daily contacts were reduced by 86·9% and the effective reproduction number reached 0·46 (95%CrI: 0·35,0·57). The reduction in R0 attributed to lockdown was 81·0% (95%CrI: 71·8%,86·0%) whereas the reduction attributed to each measure separately ranged between 10%-24%. We assessed scenarios with less disruptive social distancing measures as well as scenarios where measures are partially lifted after lockdown. This is the first impact assessment of the first wave of SARS-CoV-2 in a European country. It suggests that only multiple measures implemented simultaneously could reduce R0 below 1. Measuring social mixing patterns can be a tool for real-time monitoring of the epidemic potential.

The complication of cyber manhunt: How cyber manhunt further complicated the ethical conflict between breaching the confidentiality and endangering the society in face of the COVID-19 pandemic (Preprint)

2021 ◽  
Author(s):  
Yen-Chang Chen ◽  
Yen-Yuan Chen
Keyword(s):  
Public Health ◽  
Large Scale ◽  
Health Workers ◽  
Early Stage ◽  
Personal Information ◽  
Public Health Intervention ◽  
Contact Tracing ◽  
Online Activity ◽  
Contact Investigation ◽  
The Impact

UNSTRUCTURED While health care and public health workers are working on measures to mitigate the COVID-19 pandemic, there is an unprecedentedly large number of people spending much more time indoors, and relying heavily on the Internet as their lifeline. What has been overlooked is the influence of the increasing online activities on public health issues. In this article, we pointed out how a large-scale online activity called cyber manhunt may threaten to offset the efficacy of contact tracing investigation, a public health intervention considered highly effective in limiting further transmission in the early stage of a highly contagious disease outbreak such as the COVID-19 pandemic. In the first section, we presented a case to show how personal information obtained from contact investigation and disclosed in part on the media provoked a vehement cyber manhunt. We then discussed the possible reasons why netizens collaborate to reveal anonymized personal information about contact investigation, and specify, from the perspective of public health and public health ethics, four problems of cyber manhunt, including the lack of legitimate public health goals, the concerns about privacy breach, the impact of misinformation, and social inequality. Based on our analysis, we concluded that more moral weight may be given to protecting one's confidentiality, especially in an era with the rapid advance of digital and information technologies.

scholarly journals The influence of risk perceptions on close contact frequency during the SARS-CoV-2 pandemic

2021 ◽  
Author(s):  
James Wambua ◽  
Lisa Hermans ◽  
Pietro Coletti ◽  
Frederik Verelst ◽  
Lander Willem ◽  
...  
Keyword(s):  
Public Health ◽  
Health Communication ◽  
Risk Perceptions ◽  
Close Contact ◽  
Social Contact ◽  
Perceived Severity ◽  
Public Health Communication ◽  
Contact Behaviour ◽  
Contact Frequency ◽  
The Impact

Abstract Human behaviour is known to be crucial in the propagation of infectious diseases through respiratory or close-contact routes like the current SARS-CoV-2 virus. Intervention measures implemented to curb the spread of the virus mainly aim at limiting the number of close contacts, until vaccine roll-out is complete. Our main objective was to assess the relationships between SARS-CoV-2 perceptions and social contact behaviour in Belgium. Understanding these relationships is crucial to maximize interventions' effectiveness, e.g. by tailoring public health communication campaigns. In this study, we surveyed a representative sample of adults in Belgium in two longitudinal surveys (8 waves of survey 1 in April 2020 to August 2020, and 11 waves of survey 2 in November 2020 to April 2021). Generalized linear mixed effects models were used to analyse the two surveys. Participants with low and neutral perceptions on perceived severity made a significantly higher number of social contacts as compared to participants with high levels of perceived severity after controlling for other variables. Furthermore, participants with higher levels of perceived effectiveness of measures and perceived adherence to measures made fewer contacts. However, the differences were small. Our results highlight the key role of perceived severity on social contact behaviour during a pandemic. Nevertheless, additional research is required to investigate the impact of public health communication on severity of COVID-19 in terms of changes in social contact behaviour.

scholarly journals Time and well¬being

2015 ◽  
pp. 1-16
Author(s):  
Robert Levine
Keyword(s):  
Time Use ◽  
Large Scale ◽  
Public Policies ◽  
Well Being ◽  
Temporal Orientation ◽  
New Paradigm ◽  
Event Time ◽  
Country Level ◽  
The Impact ◽  
The Way

This paper examines the impact of temporal experience—time use, conceptions of time and temporal norms—on happiness and well-being and suggests public policies to enhance these experiences. First, it reviews literature concerning the interrelationships of time, money and happiness. Second, it reviews data and issues concerning the use of work and non-work hours around the world. Third, it describes a broader range of temporal issues to be considered in policymaking decisions, e.g. clock versus event time-keeping, monochronic versus polychronic approaches, the definition of wasted time, the pace of life, and temporal orientation. Finally, suggestions are of ered for the formulation of time-use policies intended to increase individual and collective happiness. It is a virtual truism that the way we use our time is the way we live our lives. Our time is our most valuable possession. Much of this time, however, is controlled by others, ranging from our employers to our closest family members. It is also clear that there are profound dif erences-- individual, socio-economic, cultural and national--in the degree to which people hold control over their own time (e.g., LEVINE, 1997; LEE, et al., 2007). It may be argued that public policies are needed to protect the “temporal rights” of individuals, particularly those who are most vulnerable to exploitation. This paper was sparked by an ambitious large-scale project in which I had the opportunity to participate. The project was initiated in the Spring of 2012 following a United Nations resolution, adopted unanimously by the General Assembly, placing “happiness” on the global agenda. The nation of Bhutan was asked to convene an interdisciplinary group of international “experts” to craft recommendations for policies to raise worldwide happiness; more specifically, to develop a “new paradigm for world development.” Bhutan, a small, landlocked, relatively poor Himalayan nation, was chosen for this task because of its pioneering Gross National Happiness (GNH) project. “Progress,” the GNH designers declared, “should be viewed not only through the lens of economics but also from spiritual, social, cultural and ecological perspectives.” Happiness and development, in other words, depend on more than growth and the accumulation of money. England, Canada and other countries and country-level organizations have subsequently followed Bhutan’s lead and established GNH measures of their own (LEVINE, 2013). One of the nine core domains of Bhutan’s GNH index is “time use,” which comprised my section of the report. The present paper draws heavily on that report and the insights that research of ered me. I will address four major sets of issues: I. The inter-relationships of time, money and happiness. Most importantly, what is the relevance of time use to well-being and happiness? II. Time Use: Work hour issues and policies. III. Other temporal factors that need to be considered when formulating policies to increase happiness. IV. Suggestions for policymaking: The call for a “Temporal Bill of Rights.”

scholarly journals Indigenous Australian household structure: a simple data collection tool and implications for close contact transmission of communicable diseases

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3958 ◽  
Author(s):  
Thiripura Vino ◽  
Gurmeet R. Singh ◽  
Belinda Davison ◽  
Patricia T. Campbell ◽  
Michael J. Lydeamore ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Close Contact ◽  
Age Groups ◽  
Social Contact ◽  
Communicable Diseases ◽  
Household Structure ◽  
Indigenous Populations ◽  
Indigenous Australian ◽  
Different Populations ◽  
The Impact

Households are an important location for the transmission of communicable diseases. Social contact between household members is typically more frequent, of greater intensity, and is more likely to involve people of different age groups than contact occurring in the general community. Understanding household structure in different populations is therefore fundamental to explaining patterns of disease transmission in these populations. Indigenous populations in Australia tend to live in larger households than non-Indigenous populations, but limited data are available on the structure of these households, and how they differ between remote and urban communities. We have developed a novel approach to the collection of household structure data, suitable for use in a variety of contexts, which provides a detailed view of age, gender, and room occupancy patterns in remote and urban Australian Indigenous households. Here we report analysis of data collected using this tool, which quantifies the extent of crowding in Indigenous households, particularly in remote areas. We use these data to generate matrices of age-specific contact rates, as used by mathematical models of infectious disease transmission. To demonstrate the impact of household structure, we use a mathematical model to simulate an influenza-like illness in different populations. Our simulations suggest that outbreaks in remote populations are likely to spread more rapidly and to a greater extent than outbreaks in non-Indigenous populations.

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