scholarly journals Inflow restrictions can prevent epidemics when contact tracing efforts are effective but have limited capacity

2020 ◽  
Author(s):  
Hannes Malmberg ◽  
Tom Britton
Keyword(s):  
Mathematical Analysis ◽  
Epidemiological Model ◽  
Contact Tracing ◽  
Community Interventions ◽  
Limited Capacity ◽  
Epidemiological Models ◽  
Travel Restrictions

AbstractWhen a region tries to prevent an outbreak of an epidemic, like that of COVID-19, two broad strategies are initially available: limiting the inflow of infected cases using travel restrictions and quarantines, and reducing the transmissions from inflowing cases using contact tracing and community interventions. A large number of papers have used epidemiological models to argue that inflow restrictions are unlikely to be effective. We conduct a mathematical analysis using a simple epidemiological model and perform simulations which show how this conclusion changes if we relax the assumption of unlimited capacity in containment efforts such as contact tracing. In particular, when contact tracing is effective, but the system is close to being overwhelmed, moderate travel restrictions can have a very large effect on the probability of an epidemic.

scholarly journals Inflow restrictions can prevent epidemics when contact tracing efforts are effective but have limited capacity

2020 ◽  
Vol 17 (170) ◽  
pp. 20200351 ◽  
Author(s):  
Hannes Malmberg ◽  
Tom Britton
Keyword(s):  
Epidemiological Model ◽  
Contact Tracing ◽  
Community Interventions ◽  
Limited Capacity ◽  
Epidemiological Models ◽  
Travel Restrictions ◽  
Imported Cases ◽  
Local Transmission

When a region tries to prevent an outbreak of an epidemic, two broad strategies are available: limiting the inflow of infected cases by using travel restrictions and quarantines or limiting the risk of local transmission from imported cases by using contact tracing and other community interventions. A number of papers have used epidemiological models to argue that inflow restrictions are unlikely to be effective. We simulate a simple epidemiological model to show that this conclusion changes if containment efforts such as contact tracing have limited capacity. In particular, our results show that moderate travel restrictions can lead to large reductions in the probability of an epidemic when contact tracing is effective but the contact tracing system is close to being overwhelmed.

scholarly journals Increasing efficacy of contact-tracing applications by user referrals and stricter quarantining

2020 ◽  
Author(s):  
Leslie Ann Goldberg ◽  
Joost Jorritsma ◽  
Júlia Komjáthy ◽  
John Lapinskas
Keyword(s):  
Mobile Phone ◽  
Random Graphs ◽  
Contact Tracing ◽  
Epidemiological Models ◽  
Agent Based ◽  
Inhomogeneous Random Graphs ◽  
Travel Restrictions ◽  
Geometric Space ◽  
Phone Contact

AbstractWe study the effects of two mechanisms which increase the efficacy of contact-tracing applications (CTAs) such as the mobile phone contact-tracing applications that have been used during the COVID-19 epidemic. The first mechanism is the introduction of user referrals. We compare four scenarios for the uptake of CTAs — (1) the p% of individuals that use the CTA are chosen randomly, (2) a smaller initial set of randomly-chosen users each refer a contact to use the CTA, achieving p% in total, (3) a small initial set of randomly-chosen users each refer around half of their contacts to use the CTA, achieving p% in total, and (4) for comparison, an idealised scenario in which the p% of the population that uses the CTA is the p% with the most contacts. Using agent-based epidemiological models incorporating a geometric space, we find that, even when the uptake percentage p% is small, CTAs are an effective tool for mitigating the spread of the epidemic in all scenarios. Moreover, user referrals significantly improve efficacy. In addition, it turns out that user referrals reduce the yearly quarantine load. The second mechanism for increasing the efficacy of CTAs is tuning the severity of quarantine measures. Our modelling shows that using CTAs with mild quarantine measures is effective in reducing the maximum hospital load and the number of people who become ill, but leads to a relatively high quarantine load, which may cause economic disruption. Fortunately, under stricter quarantine measures, the advantages are maintained but the quarantine load is reduced. Our models incorporate geometric inhomogeneous random graphs to study the effects of the presence of super-spreaders and of the absence of long-distant contacts (e.g., through travel restrictions) on our conclusions.

scholarly journals Increasing efficacy of contact-tracing applications by user referrals and stricter quarantining

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0250435
Author(s):  
Leslie Ann Goldberg ◽  
Joost Jorritsma ◽  
Júlia Komjáthy ◽  
John Lapinskas
Keyword(s):  
Mobile Phone ◽  
Random Graphs ◽  
Contact Tracing ◽  
Epidemiological Models ◽  
Agent Based ◽  
Inhomogeneous Random Graphs ◽  
Travel Restrictions ◽  
Geometric Space ◽  
Phone Contact

We study the effects of two mechanisms which increase the efficacy of contact-tracing applications (CTAs) such as the mobile phone contact-tracing applications that have been used during the COVID-19 epidemic. The first mechanism is the introduction of user referrals. We compare four scenarios for the uptake of CTAs—(1) the p% of individuals that use the CTA are chosen randomly, (2) a smaller initial set of randomly-chosen users each refer a contact to use the CTA, achieving p% in total, (3) a small initial set of randomly-chosen users each refer around half of their contacts to use the CTA, achieving p% in total, and (4) for comparison, an idealised scenario in which the p% of the population that uses the CTA is the p% with the most contacts. Using agent-based epidemiological models incorporating a geometric space, we find that, even when the uptake percentage p% is small, CTAs are an effective tool for mitigating the spread of the epidemic in all scenarios. Moreover, user referrals significantly improve efficacy. In addition, it turns out that user referrals reduce the quarantine load. The second mechanism for increasing the efficacy of CTAs is tuning the severity of quarantine measures. Our modelling shows that using CTAs with mild quarantine measures is effective in reducing the maximum hospital load and the number of people who become ill, but leads to a relatively high quarantine load, which may cause economic disruption. Fortunately, under stricter quarantine measures, the advantages are maintained but the quarantine load is reduced. Our models incorporate geometric inhomogeneous random graphs to study the effects of the presence of super-spreaders and of the absence of long-distant contacts (e.g., through travel restrictions) on our conclusions.

scholarly journals Investigating Dynamics of COVID-19 Spread and Containment with Agent-Based Modeling

2021 ◽  
Vol 11 (12) ◽  
pp. 5367
Author(s):  
Amirarsalan Rajabi ◽  
Alexander V. Mantzaris ◽  
Ece C. Mutlu ◽  
Ozlem O. Garibay
Keyword(s):  
Disease Model ◽  
Agent Based Modeling ◽  
Contact Tracing ◽  
Test Bed ◽  
Policy Makers ◽  
Agent Based ◽  
Contact Behavior ◽  
Epidemic Curve ◽  
Behavioral Adaptations ◽  
Travel Restrictions

Governments, policy makers, and officials around the globe are working to mitigate the effects of the COVID-19 pandemic by making decisions that strive to save the most lives and impose the least economic costs. Making these decisions require comprehensive understanding of the dynamics by which the disease spreads. In traditional epidemiological models, individuals do not adapt their contact behavior during an epidemic, yet adaptive behavior is well documented (i.e., fear-induced social distancing). In this work we revisit Epstein’s “coupled contagion dynamics of fear and disease” model in order to extend and adapt it to explore fear-driven behavioral adaptations and their impact on efforts to combat the COVID-19 pandemic. The inclusion of contact behavior adaptation endows the resulting model with a rich dynamics that under certain conditions reproduce endogenously multiple waves of infection. We show that the model provides an appropriate test bed for different containment strategies such as: testing with contact tracing and travel restrictions. The results show that while both strategies could result in flattening the epidemic curve and a significant reduction of the maximum number of infected individuals; testing should be applied along with tracing previous contacts of the tested individuals to be effective. The results show how the curve is flattened with testing partnered with contact tracing, and the imposition of travel restrictions.

scholarly journals The first 100 days of SARS-CoV-2 control in Vietnam

2020 ◽  
Author(s):  
Thai Quang Pham ◽  
Maia Rabaa ◽  
Luong Huy Duong ◽  
Tan Quang Dang ◽  
Quang Dai Tran ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Severe Disease ◽  
Steering Committee ◽  
International Travel ◽  
Control Measures ◽  
Contact Tracing ◽  
Population Mobility ◽  
Early Introduction ◽  
Mobility Data ◽  
Travel Restrictions

Background: One hundred days after SARS-CoV-2 was first reported in Vietnam on January 23rd, 270 cases have been confirmed, with no deaths. We describe the control measures used and their relationship with imported and domestically-acquired case numbers. Methods: Data on the first 270 SARS-CoV-2 infected cases and the timing and nature of control measures were captured by Vietnam's National Steering Committee for COVID-19 response. Apple and Google mobility data provided population movement proxies. Serial intervals were calculated from 33 infector-infectee pairs and used to estimate the proportion of pre-symptomatic transmission events and time-varying reproduction numbers. Results: After the first confirmed case on January 23rd, the Vietnamese Government initiated mass communications measures, contact tracing, mandatory 14-day quarantine, school and university closures, and progressive flight restrictions. A national lockdown was implemented between April 1st and 22nd. Around 200,000 people were quarantined and 266,122 RT-PCR tests conducted. Population mobility decreased progressively before lockdown. 60% (163/270) of cases were imported; 43% (89/208) of resolved infections were asymptomatic. 21 developed severe disease, with no deaths. The serial interval was 3.24 days, and 27.5% (95% confidence interval, 15.7%-40.0%) of transmissions occurred pre-symptomatically. Limited transmission amounted to a maximum reproduction number of 1.15 (95% confidence interval, 0.37-2.36). No community transmission has been detected since April 15th. Conclusions: Vietnam has controlled SARS-CoV-2 spread through the early introduction of communication, contact-tracing, quarantine, and international travel restrictions. The value of these interventions is supported by the high proportion of asymptomatic cases and imported cases, and evidence for substantial pre-symptomatic transmission.

COVID-19 crisis risks deeper European rifts on privacy

2020 ◽  
Keyword(s):  
Public Health ◽  
Public Participation ◽  
Contact Tracing ◽  
Health Crisis ◽  
Content Type ◽  
Public Health Crisis ◽  
Travel Restrictions ◽  
Digital Strategy ◽  
Mass Surveillance ◽  
The Eu

Subject New privacy guidelines. Significance The EU wants contact tracing apps for tackling COVID-19 to be effective, secure and privacy-compliant. Its efforts have exposed how its existing rules on data are adapting (or not) to the extraordinary public health crisis. Impacts Fear of mass surveillance and data breaches will reduce public participation in tracer apps, casting doubts over their effectiveness. The EU’s digital strategy, notably in terms of reviewing the effectiveness of GDPR, may be rethought in response to the COVID-19 crisis. If tracer apps are not inter-operable across national borders, lifting intra-EU travel restrictions will become harder.

scholarly journals Investigating dynamics of COVID-19 spread and containment with agent-based modeling

2020 ◽  
Author(s):  
Amirarsalan Rajabi ◽  
Alexander V. Mantzaris ◽  
Ece C. Mutlu ◽  
Ivan Garibay
Keyword(s):  
Agent Based Modeling ◽  
Contact Tracing ◽  
Model Description ◽  
Test Bed ◽  
Comprehensive Understanding ◽  
Policy Makers ◽  
Agent Based ◽  
Epidemic Curve ◽  
Travel Restrictions ◽  
Travel Restriction

AbstractGovernments, policy makers and officials around the globe are trying to mitigate the effects and progress of the COVID-19 pandemic by making decisions which will save the most lives and impose the least costs. Making these decisions needs a comprehensive understanding about the dynamics by which the disease spreads. In this work, we propose an epidemic agent-based model that simulates the spread of the disease. We show that the model is able to generate an important aspect of the pandemic: multiple waves of infection. A key point in the model description is the aspect of ’fear’ which can govern how agents behave under different conditions. We also show that the model provides an appropriate test-bed to apply different containment strategies and this work presents the results of applying two such strategies: testing, contact tracing, and travel restriction. The results show that while both strategies could result in flattening the epidemic curve and significantly reduce the maximum number of infected individuals; testing should be applied along with tracing previous contacts of the tested individuals to be effective. The results show how the curve is flattened with testing partnered with contact tracing, and the imposition of travel restrictions.

scholarly journals Temporal Contact Graph Reveals The Evolving Epidemic Situation of COVID-19

2021 ◽  
Author(s):  
Mincheng Wu ◽  
Chao Li ◽  
Zhangchong Shen ◽  
Shibo He ◽  
Lingling Tang ◽  
...  
Keyword(s):  
Participation Rate ◽  
Population Level ◽  
User Participation ◽  
Contact Tracing ◽  
Prevention Measures ◽  
Contact Graph ◽  
Individual Level ◽  
Related Data ◽  
Epidemic Size ◽  
Travel Restrictions

Abstract Digital contact tracing has been recently advocated by China and many countries as part of digital prevention measures on COVID-19. Controversies have been raised about their effectiveness in practice as it remains open how they can be fully utilized to control COVID-19. In this article, we show that an abundance of information can be extracted from digital contact tracing for COVID-19 prevention and control. Specifically, we construct a temporal contact graph that quantifies the daily contacts between infectious and susceptible individuals by exploiting a large volume of location-related data contributed by 10,527,737 smartphone users in Wuhan, China. The temporal contact graph reveals five time-varying indicators can accurately capture actual contact trends at population level, demonstrating that travel restrictions (e.g., city lockdown) in Wuhan played an important role in containing COVID-19. We reveal a strong correlation between the contacts level and the epidemic size, and estimate several significant epidemiological parameters (e.g., serial interval). We also show that user participation rate exerts higher influence on situation evaluation than user upload rate does. At individual level, however, the temporal contact graph plays a limited role, since the behavior distinction between the infected and uninfected contacted individuals are not substantial. The revealed results can tell the effectiveness of digital contact tracing against COVID-19, providing guidelines for governments to implement interventions using information technology.

scholarly journals Counter-intuitive COVID-19 Trajectories - Explanations, Early Warning Indicator and Mitigation Strategies

2021 ◽  
Author(s):  
B Shayak ◽  
Mohit Manoj Sharma
Keyword(s):  
Social Interactions ◽  
Early Warning ◽  
Critical Mass ◽  
Mass Effect ◽  
Mitigation Strategies ◽  
Contact Tracing ◽  
Epidemiological Models ◽  
Early Warning Indicator ◽  
Small Change ◽  
Parameter Values

The COVID-19 trajectories worldwide have shown several surprising features which are outside the purview of classical epidemiological models. These include (a) almost constant and low daily case rates over extended periods of time, (b) sudden waves emerging from the above solution despite no or minimal change in the level of non-pharmaceutical interventions (NPI), and (c) reduction or flattening of case counts following relaxation of NPI. To explain these phenomena, we add contact tracing to our recently developed cluster seeding and transmission (CST) model. We find no fewer than four effects which make prediction of epidemic trajectories uncertain. These are (a) cryptogenic instability, where a small increase in population-averaged contact rate causes a large increase in cases, (b) critical mass effect, where a wave manifests after weeks of quiescence with no change in parameter values, (c) knife-edge effect, where a small change in parameter across a critical value causes a huge change in the response of the system, and (d) hysteresis effect, where the timing and not just the strength of a particular NPI determines the subsequent behaviour. Despite these effects however, some non-obvious conclusions regarding NPI appear to be robust. In particular, (a) narrowing the circle of one's social interactions can be as effective a measure as reducing interactions altogether, and (b) a good contact tracing program can effectively substitute for much more invasive measures. Finally, we propose the contact tracing capacity ratio - a metric of the load to which the tracers are subject - as a reliable early warning indicator of an imminent epidemic wave.

scholarly journals Impact of public health interventions on the COVID-19 epidemic: a stochastic model based on data from an African island

2020 ◽  
Author(s):  
D. C. Nuckchady
Keyword(s):  
Stochastic Model ◽  
Population Surveillance ◽  
Health Interventions ◽  
Contact Tracing ◽  
Point Of Entry ◽  
Highly Sensitive ◽  
Travel Restrictions ◽  
Community Transmission ◽  
The Impact ◽  
Key Interventions

AbstractA stochastic model was created to simulate the impact of various healthcare measures on the COVID-19 epidemic. Travel restrictions and point of entry or exit screening help to delay the onset of the outbreak by a few weeks. Population surveillance is critical to detect the start of community transmission early and to avoid a surge in cases. Contact reduction and contact tracing are key interventions that can help to control the outbreak. To promptly curb the number of new cases, countries should diagnose patients using a highly sensitive test.

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