Modeling SARS-CoV-2 transmission at a winter destination resort region with high outside visitation

Travel destinations, particularly large resorts in otherwise small communities, risk infectious disease outbreaks from an influx of visitors who may import infections during peak seasons. The COVID-19 pandemic highlighted this risk in the context of global travel and has raised questions about appropriate interventions to curb the potential spread of infectious disease at tourist destinations. In Colorado, the initial outbreaks of SARS-CoV-2 in the state occurred in ski communities, leading to large economic losses from closures and visitor restrictions. In this study, we modeled SARS-CoV-2 transmission during the 2020-21 season in a ski region of Colorado to determine optimal combinations of intervention strategies that would keep the region below a predetermined threshold of SARS-CoV-2 infection density. This analysis used an age-stratified, deterministic SEIR compartmental model of disease transmission, calibrated to cellphone-based mobility data, to simulate infection trajectories during the winter ski season. Under three national infection levels corresponding to high, medium, and low viral importation risk, we estimated the potential impact of interventions including policy and behavior changes, visitor restriction strategies, and case investigation/contact tracing, in order to quantify the relative and absolute impacts of these interventions in the context of the COVID-19 pandemic. Our results suggest that, in the context of low viral importation risk, case investigation/contact tracing and policy and behavior changes may be sufficient to stay below predetermined infection thresholds without visitor restrictions. However, if viral importation risk is high, visitor restrictions and/or screening for infected visitors would be needed to avoid lockdown-like control scenarios and large outbreaks in tourist communities. These findings provide important guidance to tourist destinations for balancing policy impact in future infectious disease outbreaks.

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Ethics of instantaneous contact tracing using mobile phone apps in the control of the COVID-19 pandemic

Journal of Medical Ethics ◽

10.1136/medethics-2020-106314 ◽

2020 ◽

Vol 46 (7) ◽

pp. 427-431 ◽

Cited By ~ 34

Author(s):

Michael J Parker ◽

Christophe Fraser ◽

Lucie Abeler-Dörner ◽

David Bonsall

Keyword(s):

Public Health ◽

Infectious Disease ◽

Mobile Phone ◽

Public Health Practice ◽

Disease Outbreaks ◽

Contact Tracing ◽

Mobile Phone Data ◽

Public Health Response ◽

Infectious Disease Outbreaks ◽

Ethical Implications

In this paper we discuss ethical implications of the use of mobile phone apps in the control of the COVID-19 pandemic. Contact tracing is a well-established feature of public health practice during infectious disease outbreaks and epidemics. However, the high proportion of pre-symptomatic transmission in COVID-19 means that standard contact tracing methods are too slow to stop the progression of infection through the population. To address this problem, many countries around the world have deployed or are developing mobile phone apps capable of supporting instantaneous contact tracing. Informed by the on-going mapping of ‘proximity events’ these apps are intended both to inform public health policy and to provide alerts to individuals who have been in contact with a person with the infection. The proposed use of mobile phone data for ‘intelligent physical distancing’ in such contexts raises a number of important ethical questions. In our paper, we outline some ethical considerations that need to be addressed in any deployment of this kind of approach as part of a multidimensional public health response. We also, briefly, explore the implications for its use in future infectious disease outbreaks.

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Inferring epidemiological links from deep sequencing data: a statistical learning approach for human, animal and plant diseases

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2018.0258 ◽

2019 ◽

Vol 374 (1775) ◽

pp. 20180258 ◽

Cited By ~ 4

Author(s):

M. Alamil ◽

J. Hughes ◽

K. Berthier ◽

C. Desbiez ◽

G. Thébaud ◽

...

Keyword(s):

Infectious Disease ◽

Statistical Learning ◽

Sequence Data ◽

Disease Outbreaks ◽

Plant Diseases ◽

Training Data ◽

Contact Tracing ◽

Sequencing Data ◽

Theme Issue ◽

Infectious Disease Outbreaks

Pathogen sequence data have been exploited to infer who infected whom, by using empirical and model-based approaches. Most of these approaches exploit one pathogen sequence per infected host (e.g. individual, household, field). However, modern sequencing techniques can reveal the polymorphic nature of within-host populations of pathogens. Thus, these techniques provide a subsample of the pathogen variants that were present in the host at the sampling time. Such data are expected to give more insight on epidemiological links than a single sequence per host. In general, a mechanistic viewpoint to transmission and micro-evolution has been followed to infer epidemiological links from these data. Here, we investigate an alternative approach grounded on statistical learning. The idea consists of learning the structure of epidemiological links with a pseudo-evolutionary model applied to training data obtained from contact tracing, for example, and using this initial stage to infer links for the whole dataset. Such an approach has the potential to be particularly valuable in the case of a risk of erroneous mechanistic assumptions, it is sufficiently parsimonious to allow the handling of big datasets in the future, and it is versatile enough to be applied to very different contexts from animal, human and plant epidemiology. This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.

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De-escalation strategies for non-pharmaceutical interventions following infectious disease outbreaks: a rapid review and a proposed dynamic de-escalation framework

Globalization and Health ◽

10.1186/s12992-021-00743-y ◽

2021 ◽

Vol 17 (1) ◽

Author(s):

Charbel El Bcheraoui ◽

Sophie Alice Müller ◽

Eleanor C Vaughan ◽

Andreas Jansen ◽

Robert Cook ◽

...

Keyword(s):

Infectious Disease ◽

Grey Literature ◽

Disease Outbreaks ◽

Final Analysis ◽

Control Measures ◽

System Capacity ◽

Contact Tracing ◽

Rapid Review ◽

Infectious Disease Outbreaks ◽

Pharmaceutical Interventions

Abstract Background The severity of COVID-19, as well as the speed and scale of its spread, has posed a global challenge. Countries around the world have implemented stringent non-pharmaceutical interventions (NPI) to control transmission and prevent health systems from being overwhelmed. These NPI have had profound negative social and economic impacts. With the timeline to worldwide vaccine roll-out being uncertain, governments need to consider to what extent they need to implement and how to de-escalate these NPI. This rapid review collates de-escalation criteria reported in the literature to provide a guide to criteria that could be used as part of de-escalation strategies globally. Methods We reviewed literature published since 2000 relating to pandemics and infectious disease outbreaks. The searches included Embase.com (includes Embase and Medline), LitCovid, grey literature searching, reference harvesting and citation tracking. Over 1,700 documents were reviewed, with 39 documents reporting de-escalation criteria included in the final analysis. Concepts retrieved through a thematic analysis of the included documents were interlinked to build a conceptual dynamic de-escalation framework. Results We identified 52 de-escalation criteria, the most common of which were clustered under surveillance (cited by 43 documents, 10 criteria e.g. ability to actively monitor confirmed cases and contact tracing), health system capacity (cited by 30 documents, 11 criteria, e.g. ability to treat all patients within normal capacity) and epidemiology (cited by 28 documents, 7 criteria, e.g. number or changes in case numbers). De-escalation is a gradual and bi-directional process, and resurgence of infections or emergence of variants of concerns can lead to partial or full re-escalation(s) of response and control measures in place. Hence, it is crucial to rely on a robust public health surveillance system. Conclusions This rapid review focusing on de-escalation within the context of COVID-19 provides a conceptual framework and a guide to criteria that countries can use to formulate de-escalation plans.

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Facilitators and barriers to engagement with contact tracing during infectious disease outbreaks: A rapid review of the evidence

PLoS ONE ◽

10.1371/journal.pone.0241473 ◽

2020 ◽

Vol 15 (10) ◽

pp. e0241473 ◽

Cited By ~ 1

Author(s):

Odette Megnin-Viggars ◽

Patrice Carter ◽

G. J. Melendez-Torres ◽

Dale Weston ◽

G. James Rubin

Keyword(s):

Infectious Disease ◽

Disease Outbreaks ◽

Contact Tracing ◽

Rapid Review ◽

Infectious Disease Outbreaks ◽

Facilitators And Barriers

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Infectious disease outbreaks in the African region: overview of events reported to the World Health Organization in 2018

Epidemiology and Infection ◽

10.1017/s0950268819001912 ◽

2019 ◽

Vol 147 ◽

Cited By ~ 6

Author(s):

F. Mboussou ◽

P. Ndumbi ◽

R. Ngom ◽

Z. Kassamali ◽

O. Ogundiran ◽

...

Keyword(s):

Infectious Disease ◽

Disease Onset ◽

Disease Outbreaks ◽

Case Fatality ◽

World Health ◽

African Region ◽

Regional Office ◽

Member States ◽

Infectious Disease Outbreaks ◽

The World

Abstract The WHO African region is characterised by the largest infectious disease burden in the world. We conducted a retrospective descriptive analysis using records of all infectious disease outbreaks formally reported to the WHO in 2018 by Member States of the African region. We analysed the spatio-temporal distribution, the notification delay as well as the morbidity and mortality associated with these outbreaks. In 2018, 96 new disease outbreaks were reported across 36 of the 47 Member States. The most commonly reported disease outbreak was cholera which accounted for 20.8% (n = 20) of all events, followed by measles (n = 11, 11.5%) and Yellow fever (n = 7, 7.3%). About a quarter of the outbreaks (n = 23) were reported following signals detected through media monitoring conducted at the WHO regional office for Africa. The median delay between the disease onset and WHO notification was 16 days (range: 0–184). A total of 107 167 people were directly affected including 1221 deaths (mean case fatality ratio (CFR): 1.14% (95% confidence interval (CI) 1.07%–1.20%)). The highest CFR was observed for diseases targeted for eradication or elimination: 3.45% (95% CI 0.89%–10.45%). The African region remains prone to outbreaks of infectious diseases. It is therefore critical that Member States improve their capacities to rapidly detect, report and respond to public health events.

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Digital proximity tracing on empirical contact networks for pandemic control

Nature Communications ◽

10.1038/s41467-021-21809-w ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

G. Cencetti ◽

G. Santin ◽

A. Longa ◽

E. Pigani ◽

A. Barrat ◽

...

Keyword(s):

Large Scale ◽

Disease Outbreaks ◽

Physical Distance ◽

Contact Tracing ◽

Reproductive Number ◽

Modeling Framework ◽

Infectious Disease Outbreaks ◽

Contact Patterns ◽

Contact Data ◽

The Impact

AbstractDigital contact tracing is a relevant tool to control infectious disease outbreaks, including the COVID-19 epidemic. Early work evaluating digital contact tracing omitted important features and heterogeneities of real-world contact patterns influencing contagion dynamics. We fill this gap with a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing in the COVID-19 pandemic. We investigate how well contact tracing apps, coupled with the quarantine of identified contacts, can mitigate the spread in real environments. We find that restrictive policies are more effective in containing the epidemic but come at the cost of unnecessary large-scale quarantines. Policy evaluation through their efficiency and cost results in optimized solutions which only consider contacts longer than 15–20 minutes and closer than 2–3 meters to be at risk. Our results show that isolation and tracing can help control re-emerging outbreaks when some conditions are met: (i) a reduction of the reproductive number through masks and physical distance; (ii) a low-delay isolation of infected individuals; (iii) a high compliance. Finally, we observe the inefficacy of a less privacy-preserving tracing involving second order contacts. Our results may inform digital contact tracing efforts currently being implemented across several countries worldwide.

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