Low risk of SARS-CoV-2 transmission by fomites in real-life conditions

Mondelli, Mario U.; Colaneri, Marta; Seminari, Elena; Baldanti, Fausto; Bruno, Raffaele

doi:10.1016/s1473-3099(20)30678-2

Cited by 150 publications

(134 citation statements)

References 5 publications

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“…Other epidemiological uncertainties that we were unable to account for include temporal variability in SARS-CoV-2 transmissibility over the infectious period, individual-level variation in transmissibility, and a potential role for environmental acquisition [80,81], although recent evidence suggests the former may be of limited relevance [82]. Further, most LTCFs have already implemented control measures, such as interruption of social activities and provisioning of personal protective equipment, that should act to reduce transmission from baseline.…”

Section: Discussionmentioning

confidence: 96%

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: Discussionmentioning

confidence: 96%

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

Duval

Pouwels

et al. 2020

BMC Med

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“…As we progress with COVID, various criteria have been introduced and evaluated in COVID-19 spread risk [ 54 , 55 ]. Transmission ways of coronavirus and prioritizing their importance are still under debate and more studies are underway to understand transmission ways better [ 56 ]. Although the risk calculation could be very complicated based on time, room volume, air circulation, etc.…”

Section: Experimental Designmentioning

confidence: 99%

An Interoperable Architecture for the Internet of COVID-19 Things (IoCT) Using Open Geospatial Standards—Case Study: Workplace Reopening

Liang

Saeedi

Ojagh

et al. 2020

Sensors

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To safely protect workplaces and the workforce during and after the COVID-19 pandemic, a scalable integrated sensing solution is required in order to offer real-time situational awareness and early warnings for decision-makers. However, an information-based solution for industry reopening is ineffective when the necessary operational information is locked up in disparate real-time data silos. There is a lot of ongoing effort to combat the COVID-19 pandemic using different combinations of low-cost, location-based contact tracing, and sensing technologies. These ad hoc Internet of Things (IoT) solutions for COVID-19 were developed using different data models and protocols without an interoperable way to interconnect these heterogeneous systems and exchange data on people and place interactions. This research aims to design and develop an interoperable Internet of COVID-19 Things (IoCT) architecture that is able to exchange, aggregate, and reuse disparate IoT sensor data sources in order for informed decisions to be made after understanding the real-time risks in workplaces based on person-to-place interactions. The IoCT architecture is based on the Sensor Web paradigm that connects various Things, Sensors, and Datastreams with an indoor geospatial data model. This paper presents a study of what, to the best of our knowledge, is the first real-world integrated implementation of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) and IndoorGML standards to calculate the risk of COVID-19 online using a workplace reopening case study. The proposed IoCT offers a new open standard-based information model, architecture, methodologies, and software tools that enable the interoperability of disparate COVID-19 monitoring systems with finer spatial-temporal granularity. A workplace cleaning use case was developed in order to demonstrate the capabilities of this proposed IoCT architecture. The implemented IoCT architecture included proximity-based contact tracing, people density sensors, a COVID-19 risky behavior monitoring system, and the contextual building geospatial data.

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“…Because of the identifiability problem 9,61,62 and a general lack of consensus regarding the mechanisms of transmission in various diseases, we caution against the overextrapolation of these findings to any particular epidemic. As of fall 2020, the evidence for widespread surface transmission of SARS-CoV-2 remains dubious [30][31][32][33][34][35][36][37][38][39][40][41] . Insofar as SARS-CoV-2 is not the last of the emerging infectious diseases, then we should remain vigilant about understanding how different routes of transmission may influence disease dynamics, as there remain other microparasites in human and nonhuman hosts that are transmitted via the environmental route and require our attention.…”

Section: Models That Include Indirect Transmission Recapitulate Aspecmentioning

confidence: 99%

“…However, one feature of SARS-CoV-2 transmission that was validated in laboratory settings, but whose epidemiological role remains highly controversial, is SARS-CoV-2 free-living survival. Specifically, several laboratory and epidemiological findings offer conflicting evidence that indirect or environmental transmission (via free-living virus) may play a role in some settings [30][31][32][33][34][35][36][37][38][39][40][41] , and to our knowledge, none have fully investigated how this route of transmission may influence features of outbreaks. Several unknowns notwithstanding, the availability of SARS-CoV-2 data make it a valuable model for examining the particulars of indirect transmission in emerging outbreaks.…”

mentioning

confidence: 99%

Variation in microparasite free-living survival and indirect transmission can modulate the intensity of emerging outbreaks

Ogbunugafor

Miller-Dickson

Meszaros

et al. 2020

Sci Rep

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Variation in free-living microparasite survival can have a meaningful impact on the ecological dynamics of established and emerging infectious diseases. Nevertheless, resolving the importance of indirect and environmental transmission in the ecology of epidemics remains a persistent challenge. It requires accurately measuring the free-living survival of pathogens across reservoirs of various kinds and quantifying the extent to which interaction between hosts and reservoirs generates new infections. These questions are especially salient for emerging pathogens, where sparse and noisy data can obfuscate the relative contribution of different infection routes. In this study, we develop a mechanistic, mathematical model that permits both direct (host-to-host) and indirect (environmental) transmission and then fit this model to empirical data from 17 countries affected by an emerging virus (SARS-CoV-2). From an ecological perspective, our model highlights the potential for environmental transmission to drive complex, nonlinear dynamics during infectious disease outbreaks. Summarizing, we propose that fitting alternative models with indirect transmission to real outbreak data from SARS-CoV-2 can be useful, as it highlights that indirect mechanisms may play an underappreciated role in the dynamics of infectious diseases, with implications for public health.

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Low risk of SARS-CoV-2 transmission by fomites in real-life conditions

Abstract: (20)30678-2 1 surfaces is less frequent than hitherto recognised. We declare no competing interests.

Cited by 150 publications

References 5 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

An Interoperable Architecture for the Internet of COVID-19 Things (IoCT) Using Open Geospatial Standards—Case Study: Workplace Reopening

Variation in microparasite free-living survival and indirect transmission can modulate the intensity of emerging outbreaks

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