CTCmodeler: An Agent-Based Framework to Simulate Pathogen Transmission Along an Inter-individual Contact Network in a Hospital

Duval, Audrey; Dp, Smith; Guillemot, Didier; Opatowski, Lulla; Temime, Laura

doi:10.1007/978-3-030-22741-8_34

Cited by 5 publications

(4 citation statements)

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“…We simulated nosocomial outbreaks of COVID-19 using a dynamic, stochastic, individual-based Susceptible Exposed Infectious Recovered (SEIR) model of SARS-CoV-2 transmission coded in C++ [39]. The model is described fully in Additional File 1 using the Overview, Design concepts, and Details (ODD) protocol for individual-based modelling [12,18,[38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57]. The goals of our model are to simulate (i) dynamic inter-individual contacts among patients and staff in an LTCF setting, (ii) transmission of SARS-CoV-2 along simulated contact networks, and (iii) clinical progression of COVID-19 among individuals infected with SARS-CoV-2.…”

Section: Methodsmentioning

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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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: Methodsmentioning

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 simulation model used in this study is CTCModeler, an individual-based model (IBM) developed to simulate pathogen transmission among and between patients and staff in healthcare settings. (21) The IBM was programmed in C++ with the repast HPC library 2.2.0. In the following, we describe the IBM as it was used for the present study, following the ODD protocol of Grimm et al(22)…”

Section: Appendix A: Supplementary Methods For the Article Optimizingmentioning

confidence: 99%

“…By this time, 7 (0-25) additional patients and/or staff had acquired COVID-19 but did not (yet) show symptoms. The lag until first onset of severe COVID-19 symptoms was greater (12 days from index case, [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] and coincided with a greater number of undetected infections (23,.…”

Section: Covid-19 Spreads Quickly But Symptoms Lagmentioning

confidence: 99%

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

2020

Preprint

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Background: Long-term care facilities (LTCFs) are particularly vulnerable to nosocomial outbreaks of coronavirus disease 2019 , with high rates of transmission and mortality. Timely epidemiological surveillance is essential to detect and respond to outbreaks, but testing resources are highly limited in the current pandemic context. Methods:We used an individual-based transmission model to simulate COVID-19 spread along interindividual contact networks in the LTCF setting. A range of surveillance strategies were evaluated for their ability to detect simulated outbreaks, assuming limited availability of standard RT-PCR tests. Various epidemiological scenarios were considered, including COVID-19 importation from patient transfers or staff members infected in the community. Findings:We estimated a median delay of 7 (95% uncertainty interval: 2-15) days from importation of an asymptomatic COVID-19-infected patient to first presentation of COVID-19 symptoms among any patients or staff, at which point an additional 7 (0-25) individuals were infected but did not (yet) show symptoms. Across a range of scenarios, the reference surveillance strategy (testing individuals with COVID-like symptoms with signs of severity) took a median 11-21 days to detect an outbreak. Group testing (pooling specimens from multiple individuals for a single RT-PCR test) patients and staff with any COVID-like symptoms was both the most timely and efficient strategy, detecting outbreaks up to twice as quickly as the reference, and more quickly than other considered strategies while using fewer tests. Maximizing use of available tests via testing cascades was more effective . CC-BY-NC 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) and containing the terms ("COVID" OR "coronavirus" OR "nCoV" OR "SARS-CoV-2) AND ("long-term care" OR "LTCF"). We identified 16 articles published in academic journals, mostly outbreak reports and editorials describing a need for improved testing and control measures. Very few of the 179 identified preprints were studies of COVID-19 in long-term care. A separate search for the same COVID terms AND ("transmission model" OR "mathematical model" OR "dynamic model") returned 29 published articles, including an evaluation of surveillance strategies in airports, and a range of transmission models at the country or community levels, but none specifically tailored to healthcare settings, whether hospitals, LTCFs or otherwise. Among 776 preprints, we identified a large number of studies assessing and projecting COVID-19 burden in hospital systems, but only two transmission models specific to healthcare settings, neither of which addressed long-term care settings nor options for epidemiological surveillance. Together, this suggests a lack of research on the unique transmission dynamics and surveillance considerations for COVID-19 in healthcare settings. This gap is further highlighted by ex...

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“…We simulated SARS-CoV-2 outbreaks using CTCmodeler, a previously developed stochastic, individual-based transmission model in the LTCF setting. [13,14] Using high-resolution close-proximity interaction data from a 170-bed rehabilitation hospital in northern France, this model simulates (i) detailed inter-individual contacts among patients and staff, (ii) transmission of SARS-CoV-2 along simulated contact networks, and (iii) clinical progression of COVID-19 among infected individuals. A range of COVID-19 containment measures were built into the model.…”

Section: Simulating Sars-cov-2 Outbreaks In the Long-term Care Hospital Settingmentioning

confidence: 99%

Rapid antigen testing as a reactive response to surges in nosocomial SARS-CoV-2 outbreak risk

Duval

Zahar

et al. 2021

Preprint

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Background: Surges in community SARS-CoV-2 incidence increase risk of importation and subsequent transmission in healthcare facilities. Antigen rapid diagnostic testing (Ag-RDT) is widely used for population screening, but its health and economic benefits as a reactive intervention in healthcare settings are unclear. Methods: We used stochastic, individual-based modelling to simulate SARS-CoV-2 transmission in a long-term care facility with varying COVID-19 containment measures in place (social distancing, face masks, vaccination). In contrast to routine symptomatic testing using reverse-transcriptase polymerase chain reaction (RT-PCR), we evaluated the efficacy and health-economic efficiency of single or repeated population-wide Ag-RDT screening interventions implemented in response to surges in nosocomial outbreak risk. Results: Depending on the baseline containment measures in place, nosocomial SARS-CoV-2 incidence was reduced by up to 40-47% (range of means) with routine RT-PCR testing, 59-63% with the addition of a timely round of Ag-RDT screening, and 69-75% with well-timed two-round screening. For the latter, a delay of 4 to 5 days between the first and second rounds was optimal for transmission prevention. Efficacy varied depending on test sensitivity, subpopulations targeted, and SARS-CoV-2 incidence in the community. Efficiency, however, varied primarily depending on the other containment measures in place: surveillance costs for a combined strategy of routine RT-PCR testing and reactive Ag-RDT screening ranged from a mean €420-€10,260/infection averted across scenarios (default unit costs: €5/Ag-RDT test, €50/RT-PCR test). Interpretation: Reactive Ag-RDT screening complements routine RT-PCR testing, and systematic two-round screening helps overcome limited, time-varying diagnostic sensitivity. Health-economic gains scale significantly with underlying nosocomial outbreak risk.

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CTCmodeler: An Agent-Based Framework to Simulate Pathogen Transmission Along an Inter-individual Contact Network in a Hospital

Cited by 5 publications

References 18 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

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

Rapid antigen testing as a reactive response to surges in nosocomial SARS-CoV-2 outbreak risk

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