Heterogeneity is essential for contact tracing

Nielsen, Bjarke Frost; Sneppen, Kim; Simonsen, Lone; Mathiesen, Joachim

doi:10.1101/2020.06.05.20123141

Cited by 23 publications

(25 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The early impact of these COVID-19 containment measures on travel patterns and mobility have been studied, mostly based on secondary data, e.g. mobile phone and smart card data [10,16,21,22,24,25,34,38,39,52]. Providing a full review and analysis of these results is beyond the scope of this paper.…”

Section: The Roles Of Telecommuting Online Shopping and Other Digitamentioning

confidence: 99%

The trade-off behaviours between virtual and physical activities during the first wave of the COVID-19 pandemic period

Bin

Andruetto

Susilo

et al. 2021

Eur. Transp. Res. Rev.

View full text Add to dashboard Cite

Introduction The first wave of COVID-19 pandemic period has drastically changed people’s lives all over the world. To cope with the disruption, digital solutions have become more popular. However, the ability to adopt digitalised alternatives is different across socio-economic and socio-demographic groups. Objective This study investigates how individuals have changed their activity-travel patterns and internet usage during the first wave of the COVID-19 pandemicperiod, and which of these changes may be kept. Methods An empirical data collection was deployed through online forms. 781 responses from different countries (Italy, Sweden, India and others) have beencollected, and a series of multivariate analyses was carried out. Two linear regression models are presented, related to the change of travel activities andinternet usage, before and during the pandemic period. Furthermore, a binary regression model is used to examine the likelihood of the respondents to adoptand keep their behaviours beyond the pandemic period. Results The results show that the possibility to change the behaviour matter. External restrictions and personal characteristics are the driving factors of the reductionin ones' daily trips. However, the estimation results do not show a strong correlation between the countries' restriction policy and the respondents' likelihoodto adopt the new and online-based behaviours for any of the activities after the restriction period. Conclusion The acceptance and long-term adoption of the online alternatives for activities are correlated with the respondents' personality and socio-demographicgroup, highlighting the importance of promoting alternatives as a part of longer-term behavioural and lifestyle changes.

show abstract

Section: The Roles Of Telecommuting Online Shopping and Other Digitamentioning

confidence: 99%

The trade-off behaviours between virtual and physical activities during the first wave of the COVID-19 pandemic period

Bin

Andruetto

Susilo

et al. 2021

Eur. Transp. Res. Rev.

View full text Add to dashboard Cite

show abstract

“…As we demonstrate, under certain assumptions, the immunity factor is simply a product of social and biological contributions: λ = λsλ b . In our study, we leverage existing studies of real-life face-to-face contact networks (9,15,33,(36)(37)(38)(39) to estimate the social contribution to heterogeneous susceptibility, and the corresponding immunity factor λs. The biological contribution, λ b , is expected to depend on specific details of each infection.…”

Section: Significance Statementmentioning

confidence: 99%

Persistent heterogeneity not short-term overdispersion determines herd immunity to COVID-19

Tkachenko

Maslov

Elbanna

et al. 2020

Preprint

View full text Add to dashboard Cite

It has become increasingly clear that the COVID-19 epidemic is characterized by overdispersion whereby the majority of the transmission is driven by a minority of infected individuals. Such a strong departure from the homogeneity assumptions of traditional well-mixed compartment model is usually hypothesized to be the result of short-term super-spreader events, such as individual's extreme rate of virus shedding at the peak of infectivity while attending a large gathering without appropriate mitigation. However, heterogeneity can also arise through long-term, or persistent variations in individual susceptibility or infectivity. Here, we show how to incorporate persistent heterogeneity into a wide class of epidemiological models, and derive a non-linear dependence of the effective reproduction number R_e on the susceptible population fraction S. Persistent heterogeneity has three important consequences compared to the effects of overdispersion: (1) It results in a major modification of the early epidemic dynamics; (2) It significantly suppresses the herd immunity threshold; (3) It significantly reduces the final size of the epidemic. We estimate social and biological contributions to persistent heterogeneity using data on real-life face-to-face contact networks and age variation of the incidence rate during the COVID-19 epidemic, and show that empirical data from the COVID-19 epidemic in New York City (NYC) and Chicago and all 50 US states provide a consistent characterization of the level of persistent heterogeneity. Our estimates suggest that the hardest-hit areas, such as NYC, are close to the persistent heterogeneity herd immunity threshold following the first wave of the epidemic, thereby limiting the spread of infection to other regions during a potential second wave of the epidemic. Our work implies that general considerations of persistent heterogeneity in addition to overdispersion act to limit the scale of pandemics.

show abstract

“…These models divide the population into homogeneous groups (compartments) in accordance with the state of the disease (SEIR), and assume disease transmission to occur as the infected group mixes with the susceptible group at certain rates 17 . These models' assumptions do not account for the heterogeneity that exists between individuals within the groups, and simplify the complexity of contact patterns, which take place in social networks that are important to understanding the course of an epidemic 18 .…”

Section: Methods: An Agent-based Model Of Covid-19 Transmission and Mmentioning

confidence: 99%

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

Almagor

Picascia

2020

Sci Rep

View full text Add to dashboard Cite

A 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.

show abstract

Heterogeneity is essential for contact tracing

Cited by 23 publications

References 30 publications

The trade-off behaviours between virtual and physical activities during the first wave of the COVID-19 pandemic period

The trade-off behaviours between virtual and physical activities during the first wave of the COVID-19 pandemic period

Persistent heterogeneity not short-term overdispersion determines herd immunity to COVID-19

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

Contact Info

Product

Resources

About