Wrong person, place and time: viral load and contact network structure predict SARS-CoV-2 transmission and super-spreading events

Evaluation of the effectiveness of UV-C dose for photoinactivation of SARS-CoV-2 in contaminated N95 respirator, surgical and cotton fabric masks

As part of efforts to combat the Covid-19 pandemic and decrease the high transmissibility of the new coronavirus, SARS-CoV-2, effective inactivation strategies, such as UV-C decontamination technologies, can be reliably disseminated and well-studied. The present study investigated the susceptibility of a high viral load of SARS-CoV-2 in filtering facepiece respirators (FFR) N95, surgical mask, cotton fabric mask and N95 straps under three different doses of UV-C, applying both real-time PCR (qPCR) and plaque formation assays to quantify viral load reduction and virus infectivity, respectively. The results show that more than 95% of the amount of SARS-CoV-2 RNA could be reduced after 10 min of UV-C exposure (0.93 J cm^-2 per side) in FFR N95 and surgical masks and, after 5 min of UV-C treatment (0.46 J cm^-2 per side) in fabric masks. Furthermore, the analysis of viable coronaviruses after these different UV-C treatments demonstrated that the lowest applied dose is sufficient to decontaminate all masks ([Formula: see text] 3-log₁₀ reduction of the infective viral load, > 99.9% reduction). However, for the elastic strap of N95 respirators, a UV-C dose three times greater than that used in masks (1.4 J cm^-2 per side) is required. The findings suggest that the complete decontamination of masks can be performed effectively and safely in well-planned protocols for pandemic crises or as strategies to reduce the high consumption and safe disposal of these materials in the environment.

The SARS-CoV-2 viral load in COVID-19 patients is lower on face mask filters than on nasopharyngeal swabs

Face masks and personal respirators are used to curb the transmission of SARS-CoV-2 in respiratory droplets; filters embedded in some personal protective equipment could be used as a non-invasive sample source for applications, including at-home testing, but information is needed about whether filters are suited to capture viral particles for SARS-CoV-2 detection. In this study, we generated inactivated virus-laden aerosols of 0.3–2 microns in diameter (0.9 µm mean diameter by mass) and dispersed the aerosolized viral particles onto electrostatic face mask filters. The limit of detection for inactivated coronaviruses SARS-CoV-2 and HCoV-NL63 extracted from filters was between 10 to 100 copies/filter for both viruses. Testing for SARS-CoV-2, using face mask filters and nasopharyngeal swabs collected from hospitalized COVID-19-patients, showed that filter samples offered reduced sensitivity (8.5% compared to nasopharyngeal swabs). The low concordance of SARS-CoV-2 detection between filters and nasopharyngeal swabs indicated that number of viral particles collected on the face mask filter was below the limit of detection for all patients but those with the highest viral loads. This indicated face masks are unsuitable to replace diagnostic nasopharyngeal swabs in COVID-19 diagnosis. The ability to detect nucleic acids on face mask filters may, however, find other uses worth future investigation.

Pandemic risk management using engineering safety principles

The containment of infectious diseases is challenging due to complex transmutation in the biological system, intricate global interactions, intense mobility, and multiple transmission modes. An emergent disease has the potential to turn into a pandemic impacting millions of people with loss of life, mental health, and severe economic impairment. Multifarious approaches to risk management have been explored for combating an epidemic spread. This work presents the implementation of engineering safety principles to pandemic risk management. We have assessed the pandemic risk using Paté-Cornell's six levels of uncertainty. The susceptible, exposed, infected, quarantined, recovered, deceased (SEIQRD), an advanced mechanistic model, along with the Monte Carlo simulation, has been used to estimate the fatality risk. The risk minimization strategies have been categorized into hierarchical safety measures. We have developed an event tree model of pandemic risk management for distinct risk-reducing strategies realized due to natural evolution, government interventions, societal responses, and individual practices. The roles of distinct interventions have also been investigated for an infected individual's survivability with the existing healthcare facilities. We have studied the Corona Virus Disease of 2019 (COVID-19) for pandemic risk management using the proposed framework. The results highlight effectiveness of the proposed strategies in containing a pandemic.

Reducing travel-related SARS-CoV-2 transmission with layered mitigation measures: symptom monitoring, quarantine, and testing

BACKGROUND

Balancing the control of SARS-CoV-2 transmission with the resumption of travel is a global priority. Current recommendations include mitigation measures before, during, and after travel. Pre- and post-travel strategies including symptom monitoring, antigen or nucleic acid amplification testing, and quarantine can be combined in multiple ways considering different trade-offs in feasibility, adherence, effectiveness, cost, and adverse consequences.

METHODS

We used a mathematical model to analyze the expected effectiveness of symptom monitoring, testing, and quarantine under different estimates of the infectious period, test-positivity relative to time of infection, and test sensitivity to reduce the risk of transmission from infected travelers during and after travel.

RESULTS

If infection occurs 0-7 days prior to travel, immediate isolation following symptom onset prior to or during travel reduces risk of transmission while traveling by 30-35%. Pre-departure testing can further reduce risk, with testing closer to the time of travel being optimal even if test sensitivity is lower than an earlier test. For example, testing on the day of departure can reduce risk while traveling by 44-72%. For transmission risk after travel with infection time up to 7 days prior to arrival at the destination, isolation based on symptom monitoring reduced introduction risk at the destination by 42-56%. A 14-day quarantine after arrival, without symptom monitoring or testing, can reduce post-travel risk by 96-100% on its own. However, a shorter quarantine of 7 days combined with symptom monitoring and a test on day 5-6 after arrival is also effective (97--100%) at reducing introduction risk and is less burdensome, which may improve adherence.

CONCLUSIONS

Quarantine is an effective measure to reduce SARS-CoV-2 transmission risk from travelers and can be enhanced by the addition of symptom monitoring and testing. Optimal test timing depends on the effectiveness of quarantine: with low adherence or no quarantine, optimal test timing is close to the time of arrival; with effective quarantine, testing a few days later optimizes sensitivity to detect those infected immediately before or while traveling. These measures can complement recommendations such as social distancing, using masks, and hand hygiene, to further reduce risk during and after travel.

Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity

The contributions of asymptomatic infections to herd immunity and community transmission are key to the resurgence and control of COVID-19, but are difficult to estimate using current models that ignore changes in testing capacity. Using a model that incorporates daily testing information fit to the case and serology data from New York City, we show that the proportion of symptomatic cases is low, ranging from 13 to 18%, and that the reproductive number may be larger than often assumed. Asymptomatic infections contribute substantially to herd immunity, and to community transmission together with presymptomatic ones. If asymptomatic infections transmit at similar rates as symptomatic ones, the overall reproductive number across all classes is larger than often assumed, with estimates ranging from 3.2 to 4.4. If they transmit poorly, then symptomatic cases have a larger reproductive number ranging from 3.9 to 8.1. Even in this regime, presymptomatic and asymptomatic cases together comprise at least 50% of the force of infection at the outbreak peak. We find no regimes in which all infection subpopulations have reproductive numbers lower than three. These findings elucidate the uncertainty that current case and serology data cannot resolve, despite consideration of different model structures. They also emphasize how temporal data on testing can reduce and better define this uncertainty, as we move forward through longer surveillance and second epidemic waves. Complementary information is required to determine the transmissibility of asymptomatic cases, which we discuss. Regardless, current assumptions about the basic reproductive number of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) should be reconsidered.

Analytical Sensitivity of the Abbott BinaxNOW COVID-19 Ag Card

Multiple rapid antigen (Ag) tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have recently received emergency-use authorization (EUA) from the U.S. Food and Drug Administration (FDA).

Multiple rapid antigen (Ag) tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have recently received emergency-use authorization (EUA) from the U.S. Food and Drug Administration (FDA). Although less sensitive than molecular detection methods, rapid antigen testing offers the potential for inexpensive, quick, decentralized testing. Robust analytical sensitivity data in comparison to reverse transcription-quantitative PCR (qRT-PCR) are currently lacking for many rapid antigen tests. Here, we evaluated the analytical sensitivity of the Abbott BinaxNOW COVID-19 Ag card using SARS-CoV-2-positive clinical specimens quantified by reverse transcription-droplet digital PCR (RT-ddPCR) and multiple FDA EUA qRT-PCR platforms using RNA standards. Initial and confirmatory limits of detection for the BinaxNOW COVID-19 Ag card were determined to be equivalent to 4.04 × 10⁴ to 8.06 × 10⁴ copies/swab. We further confirmed this limit of detection with 72 additional clinical samples positive for SARS-CoV-2 in either phosphate-buffered saline or viral transport medium. One hundred percent of samples with viral loads of >40,000 copies/swab were detected by rapid antigen testing. These data indicate that the BinaxNOW COVID-19 Ag card has an analytical sensitivity approximately equivalent to a generic qRT-PCR cycle threshold (C_T) value of 29 to 30.

Observations on the Occurrence, Transmission and Management of the COVID-19 Pandemic Derived from Physics

Three important observations derived from the ongoing COVID-19 pandemic could result in the development of novel approaches to deal with it and avoid or at least minimize the occurrence and impact of future outbreaks. First, the dramatic increase in pandemics in the past decade alone suggests that the current relationship of humans with the environment is quickly becoming unstable, with potentially catastrophic consequences. In order to reduce the toll in life and property, we would need to shift our emphasis from control of nature to a symbiosis with nature. This, then, can become the new framework for dealing effectively with environmental issues such as climate change, whereby properly applied medical science would provide the necessary impetus for action. Second, the existence of superspreaders of infection among populations in this pandemic requires that we develop objective tests, most likely of a genetic nature, to identify them rather than apply indiscriminate and draconian controls across the board. Not identifying superspreaders in a timely fashion could allow this pandemic to turn into a black swan event, with a catastrophic impact on society. Third, we need to refocus our efforts in dealing with this pandemic from the virus itself to the human hosts. An objective morbidity risk index can be developed such that most of us can go about our daily business without the fear of becoming seriously ill, while measures can be implemented to protect those who are most vulnerable to this virus. These observations point clearly to a need for a paradigm shift.

Characterizing superspreading of SARS-CoV-2 : from mechanism to measurement

Superspreading is a ubiquitous feature of SARS-CoV-2 transmission dynamics, with a few primary infectors leading to a large proportion of secondary infections. Despite the superspreading events observed in previous coronavirus outbreaks, the mechanisms behind the phenomenon are still poorly understood. Here, we show that superspreading is largely driven by heterogeneity in contact behavior rather than heterogeneity in susceptibility or infectivity caused by biological factors. We find that highly heterogeneous contact behavior is required to produce the extreme superspreading estimated from recent COVID-19 outbreaks. However, we show that superspreading estimates are noisy and subject to biases in data collection and public health capacity, potentially leading to an overestimation of superspreading. These results suggest that superspreading for COVID-19 is substantial, but less than previously estimated. Our findings highlight the complexity inherent to quantitative measurement of epidemic dynamics and the necessity of robust theory to guide public health intervention.