Mitigation of a Coronavirus Disease 2019 Outbreak in a Nursing Home Through Serial Testing of Residents and Staff

Escobar, Daniel; Lanzi, Maria; Saberi, Pouné; Love, Ruby; Linkin, Darren R.; Kelly, John; Jhala, Darshana; Amorosa, Valerianna; Hofmann, Mary T.; Doyon, Jeffrey B.

doi:10.1093/cid/ciaa1021

Cited by 38 publications

(61 citation statements)

References 9 publications

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“…This is consistent with reported transmission dynamics of SARS-CoV-2; for instance, modelling studies have estimated that 30-57% of secondary infections among identified transmission pairs resulted from pre-symptomatic transmission [49], and that, early on in COVID-19 outbreaks in Singapore and Tianjin, pre-symptomatic transmission accounted for at least 65% of all transmission events [19]. Findings are also consistent with high proportions of asymptomatic infection, and important roles for presymptomatic and asymptomatic transmission reported in various LTCF outbreaks [5,16,21,[26][27][28][29]. The often silent nature of SARS-CoV-2 transmission highlights epidemiological challenges associated with screening for emerging outbreaks using symptoms alone.…”

Section: Discussionsupporting

confidence: 56%

“…Insufficient surveillance systems, including those lacking testing capacity or relying only on symptoms as indications for testing, have been identified as aggravating factors for COVID-19 outbreaks in LTCFs [8,16,[24][25][26][27]. Various surveillance strategies have been proposed to optimize testing while accounting for the particular transmission dynamics of SARS-CoV-2, including randomly testing HCWs, testing all patients upon admission, and universal or serial testing [28][29][30]. Yet COVID-19 surveillance is limited in practice by available testing capacity and health-economic resources, particularly for institutions in low-and middle-income settings [31,32].…”

Section: Introductionmentioning

confidence: 99%

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Optimizing COVID-19 surveillance in long-term care facilities: a modelling study

Duval

Pouwels

et al. 2020

BMC Med

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Background Long-term care facilities (LTCFs) are vulnerable to outbreaks of coronavirus disease 2019 (COVID-19). Timely epidemiological surveillance is essential for outbreak response, but is complicated by a high proportion of silent (non-symptomatic) infections and limited testing resources. Methods We used a stochastic, individual-based model to simulate transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) along detailed inter-individual contact networks describing patient-staff interactions in a real LTCF setting. We simulated distribution of nasopharyngeal swabs and reverse transcriptase polymerase chain reaction (RT-PCR) tests using clinical and demographic indications and evaluated the efficacy and resource-efficiency of a range of surveillance strategies, including group testing (sample pooling) and testing cascades, which couple (i) testing for multiple indications (symptoms, admission) with (ii) random daily testing. Results In the baseline scenario, randomly introducing a silent SARS-CoV-2 infection into a 170-bed LTCF led to large outbreaks, with a cumulative 86 (95% uncertainty interval 6–224) infections after 3 weeks of unmitigated transmission. Efficacy of symptom-based screening was limited by lags to symptom onset and silent asymptomatic and pre-symptomatic transmission. Across scenarios, testing upon admission detected just 34–66% of patients infected upon LTCF entry, and also missed potential introductions from staff. Random daily testing was more effective when targeting patients than staff, but was overall an inefficient use of limited resources. At high testing capacity (> 10 tests/100 beds/day), cascades were most effective, with a 19–36% probability of detecting outbreaks prior to any nosocomial transmission, and 26–46% prior to first onset of COVID-19 symptoms. Conversely, at low capacity (< 2 tests/100 beds/day), group testing strategies detected outbreaks earliest. Pooling randomly selected patients in a daily group test was most likely to detect outbreaks prior to first symptom onset (16–27%), while pooling patients and staff expressing any COVID-like symptoms was the most efficient means to improve surveillance given resource limitations, compared to the reference requiring only 6–9 additional tests and 11–28 additional swabs to detect outbreaks 1–6 days earlier, prior to an additional 11–22 infections. Conclusions COVID-19 surveillance is challenged by delayed or absent clinical symptoms and imperfect diagnostic sensitivity of standard RT-PCR tests. In our analysis, group testing was the most effective and efficient COVID-19 surveillance strategy for resource-limited LTCFs. Testing cascades were even more effective given ample testing resources. Increasing testing capacity and updating surveillance protocols accordingly could facilitate earlier detection of emerging outbreaks, informing a need for urgent intervention in settings with ongoing nosocomial transmission.

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Section: Discussionsupporting

confidence: 56%

Section: Introductionmentioning

confidence: 99%

Optimizing COVID-19 surveillance in long-term care facilities: a modelling study

Duval

Pouwels

et al. 2020

BMC Med

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“…The driving reason for the extreme interventions necessary for outbreak prevention is the overwhelming force of infection on a high-density setting like a cruise ship. Outbreaks in congregate living and other high-density contact environments have been observed, including in prisons, nursing homes, and university dormitories ( 24 , 25 ). Outbreak control has been challenging in these settings because of the need to maintain ongoing social distancing in environments where that is often infeasible.…”

Section: Discussionmentioning

confidence: 99%

Modeling Dynamic Network Strategies for SARS-CoV-2 Control on a Cruise Ship

Jenness

Willebrand

Malik

et al. 2020

Preprint

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SARS-CoV-2 outbreaks have occurred on several nautical vessels, driven by the high-density contact networks on these ships. Optimal strategies for prevention and control that account for realistic contact networks are needed. We developed a network-based transmission model for SARS-CoV-2 on the Diamond Princess outbreak to characterize transmission dynamics and to estimate the epidemiological impact of outbreak control and prevention measures. This model represented the dynamic multi-layer network structure of passenger-passenger, passenger-crew, and crew-crew contacts, both before and after the large-scale network lockdown imposed on the ship in response to the disease outbreak. Model scenarios evaluated variations in the timing of the network lockdown, reduction in contact intensity within the sub-networks, and diagnosis-based case isolation on outbreak prevention. We found that only extreme restrictions in contact patterns during network lockdown and idealistic clinical response scenarios could avert a major COVID-19 outbreak. Contact network changes associated with adequate outbreak prevention were the restriction of passengers to their cabins, with limited passenger-crew contacts. Clinical response strategies required for outbreak prevention included early mass screening with an ideal PCR test (100% sensitivity) and immediate case isolation upon diagnosis. Public health restrictions on optional leisure activities like these should be considered until longer-term effective solutions such as a COVID-19 vaccine become widely available.

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“…9,10,14,18,19 Asymptomatic SARS-CoV-2 infections were also identified, with rates from 16% to 69.7%. 9,10,[12][13][14]16,17,19 In studies by Arons et al and Escobar et al, 88-92% of residents with asymptomatic infections developed symptoms during subsequent follow up. 9,12 By contrast, Patel et al and Graham et al reported only 3% to 10% of asymptomatic infections developing subsequent symptoms among nursing home residents.…”

Section: Clinical Presentationmentioning

confidence: 99%

“…9,10,[12][13][14]16,17,19 In studies by Arons et al and Escobar et al, 88-92% of residents with asymptomatic infections developed symptoms during subsequent follow up. 9,12 By contrast, Patel et al and Graham et al reported only 3% to 10% of asymptomatic infections developing subsequent symptoms among nursing home residents. 14,16 Prognosis Following COVID-19 diagnosis, many LTCF residents required subsequent hospitalization or expired ( Table 1).…”

Section: Clinical Presentationmentioning

confidence: 99%

Coronavirus disease 2019 (COVID-19) in long-term care facilities: A review of epidemiology, clinical presentations, and containment interventions

Gmehlin

Munoz-Price

2020

Infect. Control Hosp. Epidemiol.

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Long-term care facilities (LTCFs) and their populations have been greatly affected by the coronavirus disease 2019 (COVID-19) pandemic. In this review, we summarize the literature to describe the current epidemiology of COVID-19 in LTCFs, clinical presentations and outcomes in the LTCF population with COVID-19, containment interventions, and the role of healthcare workers in SARS-CoV-2 transmission in these facilities.

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Mitigation of a Coronavirus Disease 2019 Outbreak in a Nursing Home Through Serial Testing of Residents and Staff

Cited by 38 publications

References 9 publications

Optimizing COVID-19 surveillance in long-term care facilities: a modelling study

Optimizing COVID-19 surveillance in long-term care facilities: a modelling study

Modeling Dynamic Network Strategies for SARS-CoV-2 Control on a Cruise Ship

Coronavirus disease 2019 (COVID-19) in long-term care facilities: A review of epidemiology, clinical presentations, and containment interventions

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