Evaluation of Testing Frequency and Sampling for Severe Acute Respiratory Syndrome Coronavirus 2 Surveillance Strategies in Long-Term Care Facilities

Delaunay, Charlotte Lanièce; Saeed, Sahar; Nguyên, Quôc Dinh

doi:10.1016/j.jamda.2020.08.022

Cited by 16 publications

(9 citation statements)

References 8 publications

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“…At the beginning of the coronavirus disease 2019 (COVID-19) pandemic, travellers formed a high proportion of total incidence, 1 , 2 leading countries to impose travel restrictions, border closures, quarantining of travellers, temperature screening and, when tests became available, testing protocols. 3 , 4 The virus responsible, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can undergo genomic rearrangement and has structural advantages to spread easily between hosts, 5 thus has facilitated for ongoing widespread community transmission globally. Long-term and sustainable border control is therefore essential in allowing countries to reap the economic benefits of allowing travel while simultaneously minimizing importation risk and avoiding the application of ineffective intervention procedures.…”

Section: Introductionmentioning

confidence: 99%

Determining quarantine length and testing frequency for international border opening during the COVID-19 pandemic

Dickens¹,

Koo

Lim

et al. 2021

Journal of Travel Medicine

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Background The COVID-19 pandemic has resulted in the closure or partial closure of international borders in almost all countries. Here we investigate the efficacy of imported case detection considering quarantine length and different testing measures for travellers on arrival. Methods We examine 8 broad border control strategies from utilising quarantine alone, pretesting, entry and exit testing, and testing during quarantine. In comparing the efficacy of these strategies, we calculate the probability of detecting travellers who have been infected up to 2 weeks pre-departure according to their estimated incubation and infectious period. We estimate the number of undetected infected travelers permitted entry for these strategies across a prevalence range of 0.1%–2% per million travelers. Results At 14-day quarantine, on average 2.2% (Range: 0.5%–8.2%) of imported infections are missed across the strategies, leading to 22 (5–82) imported cases at 0.1% prevalence per million travellers, increasing up to 430 (106–1641) at 2%. The strategy utilising exit testing results in 3.9% (3.1%–4.9%) of imported cases being missed at 7-day quarantine, down to 0.4% (0.3%–0.7%) at 21-day quarantine, and the introduction of daily testing, as the most risk averse strategy, reduces the proportion further to 2.5%–4.2% at day 7 and 0.1–0.2% at day 21 dependent on the tests used. Rapid antigen testing every 3 days in quarantine leads to 3% being missed at 7 days and 0.7% at 14 days, which is comparable to PCR testing with a 24-hour turnaround. Conclusions Mandatory testing, at a minimal of pre-testing and on arrival, is strongly recommended where the length of quarantining should then be determined by the destination country’s level of risk averseness, pandemic preparedness and origin of travellers. Repeated testing during quarantining should also be utilised to mitigate case importation risk and reduce the quarantining duration required.

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Section: Introductionmentioning

confidence: 99%

Determining quarantine length and testing frequency for international border opening during the COVID-19 pandemic

Dickens¹,

Koo

Lim

et al. 2021

Journal of Travel Medicine

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“…Transmission of SARS-CoV-2 in healthcare settings has been associated with features such as limited isolation capacity, sub-optimal individual infection prevention practices (including patient and staff testing strategies 25 ), failure to maintain physical distancing, presenteeism, poor environmental ventilation and contaminated fomites, which can all be linked to particular patient groups 26 . In our training and testing data, patients managed in elderly care, general medicine, renal, and surgical units were significantly over-represented in the HOCI group (Table 3).…”

Section: Discussionmentioning

confidence: 99%

Predicting hospital-onset COVID-19 infections using dynamic networks of patient contacts: an observational study

Myall

Price

Peach

et al. 2021

Preprint

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Background. Real–time prediction is key to prevention and control of healthcare–associated infections. Contacts between individuals drive infections, yet most prediction frameworks fail to capture the dynamics of contact. We develop a real–time machine learning framework that incorporates dynamic patient contact networks to predict patient–level hospital–onset COVID–19 infections (HOCIs), which we test and validate on international multi–site datasets spanning epidemic and endemic periods. Methods. Our framework extracts dynamic contact networks from routinely collected hospital data and combines them with patient clinical attributes and background contextual hospital data to forecast the infection status of individual patients. We train and test the HOCI prediction framework using 51,157 hospital patients admitted to a UK (London) National Health Service (NHS) Trust from 01 April 2020 to 01 April 2021, spanning UK COVID-19 surges 1 and 2. We then validate the framework by applying it to data from a non-UK (Geneva) hospital site during an epidemic surge (40,057 total inpatients) and to data from the same London Trust from a subsequent period post surge 2, when COVID-19 had become endemic (43,375 total inpatients). Findings. Based on the training data (London data spanning surges 1 and 2), the framework achieved high predictive performance using all variables (AUC–ROC 0.89 [0.88–0.90]) but was almost as predictive using only contact network variables (AUC–ROC 0.88 [0.86–0.90]), and more so than using only hospital contextual (AUC–ROC 0.82 [0.80–0.84]) or patient clinical (AUC–ROC 0.64 [0.62–0.66]) variables. The top three risk factors we identified consisted of one hospital contextual variable (background hospital COVID–19 prevalence) and two contact network variables (network closeness, and number of direct contacts to infectious patients), and together achieved AUC–ROC 0.85 [0.82–0.88]. Furthermore, the addition of contact network variables improved performance relative to hospital contextual variables on both the non–UK (AUC–ROC increased from 0.84 [0.82–0.86] to 0.88 [0.86–0.90]) and the UK validation datasets (AUC–ROC increased from 0.52 [0.49–0.53] to 0.68 [0.64–0.70]). Interpretation. Our results suggest that dynamic patient contact networks can be a robust predictor of respiratory viral infections spreading in hospitals. Their integration in clinical care has the potential to enhance individualised infection prevention and early diagnosis.

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“… 107 Modelling suggests that frequent testing with a lower sensitivity test can achieve the same probability of case detection as a higher sensitivity test with less frequent testing. 108 , 109 Additionally, further data suggests that rapid and frequent testing can reduce transmission. 108 , 110 Data suggests that the best lateral flow tests can detect 91% of cases that lead to onward transmission (under laboratory conditions and with the implicit uncertainty and assumptions of the modelling).…”

Section: Diagnosticsmentioning

confidence: 99%

Future developments in the prevention, diagnosis and treatment of COVID-19

Coltart

Collet-Fenson

2021

Best Practice & Research Clinical Obstetrics & Gynaecol

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The impact of the COVID-19 pandemic has been profound and global. Mitigating future waves and overcoming this pandemic is a global public health priority. This review focuses on future developments in prevention, diagnosis and treatment of COVID-19, which may help to address these current challenges. The specific relevance to women’s and maternal health, addressing the vulnerabilities in this group, is considered. The remarkable scientific achievements that have been made with respect to the development and implementation of both vaccines and therapeutics for COVID-19 are highlighted. The speed and processes for the development, approval and implementation of interventions heralds a new way forward for combating emerging infectious diseases. However, it is important to note that this it is a rapidly changing field with a constantly evolving knowledge base.

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Evaluation of Testing Frequency and Sampling for Severe Acute Respiratory Syndrome Coronavirus 2 Surveillance Strategies in Long-Term Care Facilities

Abstract: Brief summary We compared the impact of different SARS-CoV-2 surveillance strategies in long-term care facilities. We recommend weekly testing of at least 50% of staff and residents in order to minimize outbreaks in this priority population.

Cited by 16 publications

References 8 publications

Determining quarantine length and testing frequency for international border opening during the COVID-19 pandemic

Determining quarantine length and testing frequency for international border opening during the COVID-19 pandemic

Predicting hospital-onset COVID-19 infections using dynamic networks of patient contacts: an observational study

Future developments in the prevention, diagnosis and treatment of COVID-19

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