scholarly journals The impact of contact tracing and household bubbles on deconfinement strategies for COVID-19

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lander Willem ◽  
Steven Abrams ◽  
Pieter J. K. Libin ◽  
Pietro Coletti ◽  
Elise Kuylen ◽  
...  
Keyword(s):  
Social Interactions ◽  
Hospital Admissions ◽  
Contact Tracing ◽  
Scenario Analyses ◽  
Social Mixing ◽  
Optimal Deployment ◽  
Mixing Patterns ◽  
Complete Contact ◽  
The Impact ◽  
Different Levels

AbstractThe COVID-19 pandemic caused many governments to impose policies restricting social interactions. A controlled and persistent release of lockdown measures covers many potential strategies and is subject to extensive scenario analyses. Here, we use an individual-based model (STRIDE) to simulate interactions between 11 million inhabitants of Belgium at different levels including extended household settings, i.e., “household bubbles”. The burden of COVID-19 is impacted by both the intensity and frequency of physical contacts, and therefore, household bubbles have the potential to reduce hospital admissions by 90%. In addition, we find that it is crucial to complete contact tracing 4 days after symptom onset. Assumptions on the susceptibility of children affect the impact of school reopening, though we find that business and leisure-related social mixing patterns have more impact on COVID-19 associated disease burden. An optimal deployment of the mitigation policies under study require timely compliance to physical distancing, testing and self-isolation.

scholarly journals The impact of contact tracing and household bubbles on deconfinement strategies for COVID-19: an individual-based modelling study

2020 ◽  
Author(s):  
Lander Willem ◽  
Steven Abrams ◽  
Oana Petrof ◽  
Pietro Coletti ◽  
Elise Kuylen ◽  
...  
Keyword(s):  
Social Interactions ◽  
Hospital Admissions ◽  
Leisure Activities ◽  
Absolute Number ◽  
School Closure ◽  
Contact Tracing ◽  
Lower Probability ◽  
Seroprevalence Data ◽  
The Individual ◽  
The Impact

AbstractBackgroundThe rising COVID-19 pandemic caused many governments to impose policies restricting social interactions. These policies have slowed down the spread of the SARS-CoV-2 virus to the extent that restrictions can be gradually lifted. Models can be useful to assess the consequences of deconfinement strategies with respect to business, school and leisure activities.MethodsWe adapted the individual-based model “STRIDE” to simulate interactions between the 11 million inhabitants of Belgium at the levels of households, workplaces, schools and communities. We calibrated our model to observed hospital incidence and seroprevalence data. STRIDE can explore contact tracing options and account for repetitive leisure contacts in extended household settings (so called “household bubbles”) with varying levels of connectivity.FindingsHousehold bubbles have the potential to reduce the number of COVID-19 hospital admissions by up to 90%. The effectiveness of contact tracing depends on its timing, as it becomes futile more than 4 days after the index case developed symptoms. Assuming that children have a lower level of susceptibility and lower probability to experience symptomatic SARS-CoV-2 infection, (partial) school closure options have relatively little impact on COVID-19 burden.InterpretationNot only the absolute number and intensity of physical contacts drive the transmission dynamics and COVID-19 burden, also their repetitiveness is influential. Contact tracing seems essential for a controlled and persistent release of lockdown measures, but requires timely compliance to testing, reporting and self-isolation. Rapid tracing and testing, and communication ensuring continued involvement of the population are therefore essential.

scholarly journals Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jonatan Almagor ◽  
Stefano Picascia
Keyword(s):  
High Rate ◽  
Contact Tracing ◽  
Agent Based Model ◽  
Agent Based ◽  
The Social ◽  
Behavioural Factors ◽  
The Impact ◽  
Different Levels ◽  
User Rate

AbstractA contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.

scholarly journals Investigating the effectiveness of re-opening policies before vaccination during a pandemic: SD modelling research based on COVID-19 in Wuhan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ying Qian ◽  
Wei Xie ◽  
Jidi Zhao ◽  
Ming Xue ◽  
Shiyong Liu ◽  
...  
Keyword(s):  
Model Simulation ◽  
Control Measures ◽  
World Health ◽  
Contact Tracing ◽  
Infection Prevention And Control ◽  
Real World Data ◽  
Medical Resources ◽  
Health Organization ◽  
The Impact ◽  
Different Levels

Abstract Background Lockdown policies were widely adopted during the coronavirus disease 2019 (COVID-19) pandemic to control the spread of the virus before vaccines became available. These policies had significant economic impacts and caused social disruptions. Early re-opening is preferable, but it introduces the risk of a resurgence of the epidemic. Although the World Health Organization has outlined criteria for re-opening, decisions on re-opening are mainly based on epidemiologic criteria. To date, the effectiveness of re-opening policies remains unclear. Methods A system dynamics COVID-19 model, SEIHR(Q), was constructed by integrating infection prevention and control measures implemented in Wuhan into the classic SEIR epidemiological model and was validated with real-world data. The input data were obtained from official websites and the published literature. Results The simulation results showed that track-and-trace measures had significant effects on the level of risk associated with re-opening. In the case of Wuhan, where comprehensive contact tracing was implemented, there would have been almost no risk associated with re-opening. With partial contact tracing, re-opening would have led to a minor second wave of the epidemic. However, if only limited contact tracing had been implemented, a more severe second outbreak of the epidemic would have occurred, overwhelming the available medical resources. If the ability to implement a track-trace-quarantine policy is fixed, the epidemiological criteria need to be further taken into account. The model simulation revealed different levels of risk associated with re-opening under different levels of track-and-trace ability and various epidemiological criteria. A matrix was developed to evaluate the effectiveness of the re-opening policies. Conclusions The SEIHR(Q) model designed in this study can quantify the impact of various re-opening policies on the spread of COVID-19. Integrating epidemiologic criteria, the contact tracing policy, and medical resources, the model simulation predicts whether the re-opening policy is likely to lead to a further outbreak of the epidemic and provides evidence-based support for decisions regarding safe re-opening during an ongoing epidemic. Keyords COVID-19; Risk of re-opening; Effectiveness of re-opening policies; IPC measures; SD modelling.

scholarly journals Protective impacts of household-based tuberculosis contact tracing are robust across endemic incidence levels and community contact patterns

2021 ◽  
Vol 17 (2) ◽  
pp. e1008713 ◽  
Author(s):  
Joshua Havumaki ◽  
Ted Cohen ◽  
Chengwei Zhai ◽  
Joel C. Miller ◽  
Seth D. Guikema ◽  
...  
Keyword(s):  
Population Level ◽  
Contact Tracing ◽  
Spatially Explicit Model ◽  
Household Transmission ◽  
Contact Patterns ◽  
Social Mixing ◽  
High Incidence ◽  
Community Transmission ◽  
The Impact ◽  
The Relationship

There is an emerging consensus that achieving global tuberculosis control targets will require more proactive case finding approaches than are currently used in high-incidence settings. Household contact tracing (HHCT), for which households of newly diagnosed cases are actively screened for additional infected individuals is a potentially efficient approach to finding new cases of tuberculosis, however randomized trials assessing the population-level effects of such interventions in settings with sustained community transmission have shown mixed results. One potential explanation for this is that household transmission is responsible for a variable proportion of population-level tuberculosis burden between settings. For example, transmission is more likely to occur in households in settings with a lower tuberculosis burden and where individuals mix preferentially in local areas, compared with settings with higher disease burden and more dispersed mixing. To better understand the relationship between endemic incidence levels, social mixing, and the impact of HHCT, we developed a spatially explicit model of coupled household and community transmission. We found that the impact of HHCT was robust across settings of varied incidence and community contact patterns. In contrast, we found that the effects of community contact tracing interventions were sensitive to community contact patterns. Our results suggest that the protective benefits of HHCT are robust and the benefits of this intervention are likely to be maintained across epidemiological settings.

scholarly journals COVID-19 and homelessness in England: a modelling study of the COVID-19 pandemic among people experiencing homelessness, and the impact of a residential intervention to isolate vulnerable people and care for people with symptoms

2020 ◽  
Author(s):  
Dan Lewer ◽  
Isobel Braithwaite ◽  
Miriam Bullock ◽  
Max T Eyre ◽  
Robert W Aldridge ◽  
...  
Keyword(s):  
Critical Care ◽  
Success Factors ◽  
Hospital Admissions ◽  
Markov Chain Model ◽  
Severe Disease ◽  
Sensitivity Analyses ◽  
Homeless Population ◽  
Chain Model ◽  
Scenario Analyses ◽  
The Impact

AbstractBackgroundThere is an ongoing pandemic of the viral respiratory disease COVID-19. People experiencing homelessness are vulnerable to infection and severe disease. Health and housing authorities in England have developed a residential intervention that aims to isolate those vulnerable to severe disease (COVID-PROTECT) and care for people with symptoms (COVID-CARE).MethodsWe used a discrete-time Markov chain model to forecast COVID-19 infections among people experiencing homelessness, given strong containment measures in the general population and some transmission among 35,817 people living in 1,065 hostels, and 11,748 people sleeping rough (the ’do nothing’ scenario). We then estimated demand for beds if those eligible are offered COVID-PROTECT and COVID-CARE. We estimated the reduction in the number of COVID-19 cases, deaths, and hospital admissions that could be achieved by these interventions. We also conducted sensitivity and scenario analyses to identify programme success factors.ResultsIn a ’do nothing’ scenario, we estimate that 34% of the homeless population could get COVID-19 between March and August 2020, with 364 deaths, 4,074 hospital admissions and 572 critical care admissions. In our ’base intervention’ scenario, demand for COVID-PROTECT peaks at 9,934 beds, and demand for COVID-CARE peaks at 1,366 beds. The intervention could reduce transmission by removing symptomatic individuals from the community, and preventing vulnerable individuals from being infected. This could lead to a reduction of 164 deaths, 2,624 hospital admissions, and 248 critical care admissions over this period. Sensitivity analyses showed that the number of deaths is sensitive to transmission of COVID-19 in COVID-PROTECT. If COVID-PROTECT capacity is limited, scenario analyses show the benefit of prioritising people who are vulnerable to severe disease.ConclusionSupportive accommodation can mitigate the impact of the COVID-19 pandemic on the homeless population of England, and reduce the burden on acute hospitals.

scholarly journals The influence of school holiday timing on epidemic impact

2013 ◽  
Vol 142 (9) ◽  
pp. 1963-1971 ◽  
Author(s):  
K. T. D. EAMES
Keyword(s):  
Mathematical Models ◽  
School Closure ◽  
Influenza Epidemic ◽  
Final Size ◽  
Peak Incidence ◽  
Social Mixing ◽  
Mixing Patterns ◽  
The Uk ◽  
The Impact

SUMMARYThe impact of reactive school closure on an epidemic is uncertain, since it is not clear how an unplanned closure will affect social mixing patterns. The effect of school holidays on social mixing patterns is better understood. Here, we use mathematical models to explore the influence of the timing of school holidays on the final size and peak incidence of an influenza-like epidemic. A well-timed holiday can reduce the impact of an epidemic, in particular substantially reducing an epidemic's peak. Final size and peak incidence cannot both be minimized: a later holiday is optimal for minimizing the final size, while an earlier holiday minimizes peak incidence. Using social mixing data from the UK, we estimated that, had the 2009 influenza epidemic not been interrupted by the school summer holidays, the final size would have been about 20% larger and the peak about 170% higher.

scholarly journals Habilidades Sociales y acoso escolar: un estudio en centros de Enseñanza Secundaria de Madrid

2014 ◽  
Vol 20 (1) ◽  
pp. 39
Author(s):  
Mª Luisa Dueñas Buey ◽  
María Senra Varela
Keyword(s):  
Social Skills ◽  
Social Interactions ◽  
Social Exclusion ◽  
Descriptive Study ◽  
Self Esteem ◽  
Global Index ◽  
External Attribution ◽  
Opposite Sex ◽  
The Impact ◽  
Different Levels

RESUMEN Este artículo es el resultado de un estudio de tipo descriptivo con una muestra de adolescentes de eda‐ des comprendidas entre los 13 y 14 años con la finalidad de analizar el fenómeno del acoso escolar, así como la incidencia de ciertas habilidades sociales relevantes en relación con el mismo. Se analiza el acoso escolar a tres niveles diferenciados: bajo, medio y alto en las 9 escalas que componen el instrumento utilizado. También se analizan: • Los niveles de acoso escolar según el sexo. • Las habilidades sociales en función del sexo y, finalmente,• El acoso escolar en función de las habilidades sociales.ABSTRACT The bullying phenomenon is a critically important subject in educational settings as well as in society. The studies conducted in this line show that people with tendency to aggressive behaviour are charac‐ terized by a distinguishable profile: instability, irritability, external attribution, high levels of anxiety, low self‐esteem and tendency to depression. This paper arises from a descriptive study with a sample of adolescents (age from 13 to 14). It is focused on the analysis of the bullying phenomenon and the impact of specific social skills on it. Nine scales of bullying are analysed: harassment, intimidation, threats, coercions, social boycott, social exclusion, social manipulation and aggressions. Likewise, we calculated a global index of bullying, taking three different levels into account: low, medium and high. Social skills measured by the instrument are subsumed by six dimensions: self‐expression in social interactions, defence of the own rights as a consumer, expression of annoyance or disagreement, saying “no” and interrupting social interactions, asking a favour, initiating opposite-sex peer interactions.Furthermore, we performed analysis concerning the following aspects: Levels of bullying by sex. Social skills by sex, and, finally, bullying according to social skills.

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 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.

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