Pre-symptomatic transmission of SARS-CoV-2 infection: a secondary analysis using published data

Casey, Miriam; Griffin, John M.; McAloon, Conor G.; Byrne, Andrew; Madden, Jamie M.; Evoy, David Mc; Collins, Áine B.; Hunt, Kevin; Barber, Ann; Butler, Francis; Lane, Elizabeth A.; O’Brien, Kirsty; Wall, Patrick; Walsh, Kieran; More, Simon John

doi:10.1101/2020.05.08.20094870

Cited by 53 publications

(64 citation statements)

References 50 publications

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“…This is consistent with the findings of the only mathematical modelling study in our review that explored this question [19]. Uncertainties in estimates of the true proportion and PLOS MEDICINE the relative infectiousness of asymptomatic SARS-Cov-2 infection and other infection parameters contributed to heterogeneous predictions about the proportion of presymptomatic transmission [20,33,51,63,78,91].…”

Section: Discussionsupporting

confidence: 82%

“…We included eight mathematical modelling studies (Fig 4) [19,20,33,51,63,69,78,91]. The models in five studies were informed by analysis of data from contact investigations in China, South Korea, Singapore, and the Diamond Princess cruise ship, using data to estimate the serial interval or generation time [19,20,33,69,78], and in three studies the authors used previously published estimates [51,63,91].…”

Section: Plos Medicinementioning

confidence: 99%

“…generation time, and serial interval [19,20,33,51,63,78,91]. In models that accounted for uncertainty appropriately, most estimates of the proportion of transmission resulting from people with SARS-CoV-2 who are presymptomatic ranged from 20% to 70%.…”

Section: Plos Medicinementioning

confidence: 99%

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Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis

et al. 2020

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Background There is disagreement about the level of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We conducted a living systematic review and metaanalysis to address three questions: (1) Amongst people who become infected with SARS-CoV-2, what proportion does not experience symptoms at all during their infection? (2) Amongst people with SARS-CoV-2 infection who are asymptomatic when diagnosed, what proportion will develop symptoms later? (3) What proportion of SARS-CoV-2 transmission is accounted for by people who are either asymptomatic throughout infection or presymptomatic? Methods and findings We searched PubMed, Embase, bioRxiv, and medRxiv using a database of SARS-CoV-2 literature that is updated daily, on 25 March 2020, 20 April 2020, and 10 June 2020. Studies of people with SARS-CoV-2 diagnosed by reverse transcriptase PCR (RT-PCR) that documented follow-up and symptom status at the beginning and end of follow-up or modelling studies were included. One reviewer extracted data and a second verified the extraction, with disagreement resolved by discussion or a third reviewer. Risk of bias in empirical studies was assessed with an adapted checklist for case series, and the relevance and credibility of modelling studies were assessed using a published checklist. We included a total of 94 studies. The overall estimate of the proportion of people who become infected with SARS-CoV-2 and remain asymptomatic throughout infection was 20% (95% confidence interval [CI] 17-25) with a prediction interval of 3%-67% in 79 studies that addressed this review question. There was some evidence that biases in the selection of participants influence the estimate. In seven studies of defined populations screened for SARS-CoV-2 and then

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Section: Discussionsupporting

confidence: 82%

Section: Plos Medicinementioning

confidence: 99%

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Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis

et al. 2020

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“…There is typically 5 (4-6) days of incubation period [7][8][9]36,37] and an additional 5 (3-7) days of delay from symptom onset to detection [38,39]. We further assume that an additional 45% (30%-55%) of asymptomatic and 15% (10%-25%) mildlysymptomatic cases were among the confirmed exported carriers of COVID-19 [40,41]. Thus, the probability of having an infected individual on board the aircraft is given by / p Dt M = , where D is the daily passenger flux, M is the catchment population size, and t is the exposure time which is the sum of incubation period and delay to symptom onset to detection.…”

Section: Estimating the Number Of Active Cases Using Air Travel Datamentioning

confidence: 99%

Ongoing outbreak of COVID-19 in Iran: challenges and signs of concern with under-reporting of prevalence and deaths

Ghafari

Hejazi

Karshenas

et al. 2020

Preprint

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Many countries with an early outbreak of SARS-CoV-2 struggled to gauge the size and start date of the epidemic mainly due to limited testing capacities and a large proportion of undetected asymptomatic and mild infections. Iran was among the first countries with a major outbreak outside China. Using all genomic sequences collected from patients with a travel link to Iran, we estimate that the epidemic started on 21/01/2020 (95% HPD: 05/12/2019 – 14/02/2020) with a doubling time of 3 days (95% HPD: 1.68 – 16.27). We also show, using air travel data from confirmed exported cases, that from late February to early March the number of active cases across the country were more than a hundred times higher than the reported cases at the time. A detailed province-level analysis of all-cause mortality shows 20,718 (CI 95%: 18,859 – 22,576) excess deaths during winter and spring 2020 compared to previous years, almost twice the number of reported COVID-19-related deaths at the time. Correcting for under-reporting of prevalence and deaths, we use an SEIR model to reconstruct the outbreak dynamics in Iran. Our model forecasted the second epidemic peak and suggests that by 14/07/2020 a total of 9M (CI 95%: 118K – 44M) have recovered from the disease across the country. These findings have profound implications for assessing the stage of the epidemic in Iran and shed light on the dynamics of SARS-CoV-2 transmissions in Iran and central Asia despite significant levels of under-reporting.

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“…Each infection control strategy is limited in some aspect (22,(49)(50)(51)(52)(53). Symptom-based screening has very low sensitivity to detect infections early in the clinical course (when people are most infectious), and poor specificity (12)(13)(14)54).…”

Section: Discussionmentioning

confidence: 99%

Comparison of infection control strategies to reduce COVID-19 outbreaks in homeless shelters in the United States: a simulation study

Chapman

Kushel

Cox

et al. 2020

Preprint

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Background: Multiple COVID-19 outbreaks have occurred in homeless shelters across the US, highlighting an urgent need to identify the most effective infection control strategy to prevent future outbreaks. Objective: To estimate the probability of averting outbreaks in homeless shelters under different infection control strategies. Design: Microsimulation model of COVID-19 transmission in a representative homeless shelter over 30 days under different infection control strategies, including daily symptom-based screening, twice-weekly polymerase-chain-reaction (PCR) testing and universal mask wearing. Setting: A shelter of 250 residents and 50 staff. Patients: Residents and staff of homeless shelters in the US. Model calibrated to data from cross-sectional PCR surveys during COVID-19 outbreaks in five shelters in three US cities. Measurements: Probability of averting a COVID-19 outbreak (≥3 infections in 14 days). Results: Basic reproduction number (R0) estimates for the observed outbreaks ranged from 2.9 to 6.2. The probability of averting an outbreak diminished with higher transmissibility (R0) within the simulated shelter and increasing transmission intensity in the local community. With moderate transmission intensity in the local community, the estimated probabilities of averting an outbreak in a low-risk (R0=1.5), moderate-risk (R0=2.9), and high-risk (R0=6.2) shelter were: 0.33, 0.11 and 0.03 for daily symptom-based screening; 0.52, 0.27, and 0.04 for twice-weekly PCR testing; 0.47, 0.20 and 0.06 for universal masking; and 0.68, 0.40 and 0.08 for these strategies combined. Limitations: R0 values calibrated to reported outbreaks may be higher than for average shelter due to smaller outbreaks going unreported. Conclusion: In high-risk homeless shelter environments and locations with high community incidence of COVID-19 most infection control strategies are unlikely to prevent outbreaks. In lower-risk environments, combined interventions should be adopted to reduce outbreak risk. Primary Funding Source: University of California, San Francisco; UCSF Benioff Homelessness and Housing Initiative.

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Pre-symptomatic transmission of SARS-CoV-2 infection: a secondary analysis using published data

Cited by 53 publications

References 50 publications

Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis

Occurrence and transmission potential of asymptomatic and presymptomatic SARS-CoV-2 infections: A living systematic review and meta-analysis

Ongoing outbreak of COVID-19 in Iran: challenges and signs of concern with under-reporting of prevalence and deaths

Comparison of infection control strategies to reduce COVID-19 outbreaks in homeless shelters in the United States: a simulation study

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