ABSTRACT
ObjectivesThe aim of this study was to conduct a scoping review of estimates of the relative infectiousness of asymptomatic persons infected with SARS-CoV-2 compared with symptomatic individuals. DesignRapid scoping review of literature available until 8th April 2020. SettingInternational studies on the infectiousness of individuals infected with SARS-CoV-2 ParticipantsStudies were selected for inclusion if they defined asymptomatics as a separate cohort distinct from pre-symptomatics and if they provided a quantitative measure of the infectiousness of asymptomatics relative to symptomatics. Primary outcome measuresThe relative number of secondary cases produced by an average primary case, the relative probability of transmitting infection upon contact, and the degree of viral shedding. ResultsVery few studies reported estimates of relative infectiousness of asymptomatic compared with symptomatic individuals. Significant differences exist in the definition of infectiousness. Viral shedding studies in general show no difference in shedding levels between symptomatic and asymptomatic individuals but are likely to be impacted by insufficient statistical power. Two contact tracing studies provided estimates of 0.7 and 1.0, but differences in approach and definition preclude comparison across the two studies. Finally, two modelling studies suggest a relative infectiousness of around 0.5 but one of these was more reflective of the infectiousness of undocumented rather than asymptomatic cases. Importantly, one contact tracing study showing a very low level of infectiousness of asymptomatic was not included in the analysis at this point due difficulties interpreting the reported findings. ConclusionsThe present study highlights the need for additional studies in this area as a matter of urgency. For the purpose of epidemiological modelling, we cautiously suggest that at present, asymptomatics could be considered to have a degree of infectiousness which is about 0.40-0.70 that of symptomatics. However, it must be stressed that this suggestion comes from a very low evidence base and that estimates exist that are close to zero and close to 1. ARTICLE SUMMARYO_ST_ABSStrengths and limitations of this studyC_ST_ABS- Differences in the definition of infectiousness and a low number of studies estimating this parameter negate the potential to provide a pooled quantitative estimate or relative infectiousness. - The present study highlights the need for additional studies in this area as a matter of urgency. - Several of the studies reviewed are in pre-print stage and are not peer-reviewed.
ABSTRACT
BackgroundThe transmissibility of SARS-CoV-2 determines both the ability of the virus to invade a population and the strength of intervention that would be required to contain or eliminate the spread of infection. The basic reproduction number, R0, provides a quantitative measure of the transmission potential of a pathogen. ObjectiveConduct a scoping review of the available literature providing estimates of R0 for SARS-CoV-2, provide an overview of the drivers of variation in R0 estimates and the considerations taken in the calculation of the parameter. DesignScoping review of available literature between the 01 December 2019 and 07 May 2020. Data sourcesBoth peer-reviewed and pre-print articles were searched for on PubMed, Google Scholar, MedRxiv and BioRxiv. Selection criteriaStudies were selected for review if (i) the estimation of R0 for SARS-CoV-2 represented either the initial stages of the outbreak or the initial stages of the outbreak prior to the onset of widespread population restriction ("lockdown"), (ii) the exact dates of the study period were provided and (iii) the study provided primary estimates of R0. ResultsA total of 20 R0 for SARS-CoV-2 estimates were extracted from 15 studies. There was substantial variation in the estimates reported. Estimates derived from mathematical models fell within a wider range of 1.94-6.94 than statistical models which fell between the range of 2.2 to 4.4. Several studies made assumptions about the length of the infectious period which ranged from 5.8-20 days and the serial interval which ranged from 4.41-14 days. For a given set of parameters a longer duration of infectiousness or a longer serial interval equates to a higher R0. Several studies took measures to minimise bias in early case reporting, to account for the potential occurrence of super-spreading events, and to account for early sub-exponential epidemic growth. ConclusionsThe variation in reported estimates of R0 reflects the complex nature of the parameter itself, including the context (i.e. social/spatial structure), the methodology used to estimate the parameter, and model assumptions. R0 is a fundamental parameter in the study of infectious disease dynamics, however it provides limited practical applicability outside of the context in which it was estimated, and should be calculated and interpreted with this in mind. STRENGTHS AND LIMITATIONS OF THE SCOPING REVIEWO_LIThis study provides an overview of basic reproduction number estimates for SARS-CoV-2 across a range of settings, a fundamental parameter in gauging the transmissibility of an emerging infectious disease. C_LIO_LIThe key drivers of variation in R0 estimates and considerations in the calculation of the parameter highlighted across the reviewed studies are discussed. C_LIO_LIThis evidence may be used to help inform modelling studies and intervention strategies. C_LIO_LIGiven the need for rapid dissemination of information on a newly emerging infectious disease, several of the reviewed papers were in the pre-print phase yet to be peer-reviewed. C_LI
ABSTRACT
ObjectivesCoronavirus disease (COVID-19) caused by the SARS-CoV-2 virus is spreading rapidly worldwide and threatening the collapse of national health care systems. The development of effective resource models are critical for long term health planning. The aim was to evaluate the available literature, to consider parameters affecting hospital resources, to effectively guide health policy and planning for future waves of infection. DesignA detailed search of the literature, using Google Scholar, PubMED, MedRxiv and BioRxiv, was conducted for the time period 1st Dec 2019 to 31st May 2020; using appropriate keywords: resultant articles were scrutinised in detail, and appraised for reported data pertaining to hospitalization and hospital length of stay (LOS). ResultsDisease presentation was described in China; 81 % mild, 14 % moderate and 5 % severe. The experience, thus far, in Europe and the USA are suggestive of a higher degree of severity. Initial reports suggest high hospitalisation and ICU admittance rates. More recent reports from the European Centre for Disease Prevention and Control (ECDC) lower this estimation. Perhaps the relative age, the level of pre-existing conditions, and other health factors may be contributors to differences. Data from Irish cases suggest hospitalisation rate may be lower in parts of Europe and time dependent. Hospital LOS is described in 55 articles, with median lengths of stay between 3 and 52 days. The evidence regarding the LOS in ICU is reported in 31 studies, 26 deemed relevant. The majority of studies report ICU LOS between 7 to 11 days. Many of these studies are likely skewed towards shorter stay due to study cut-off dates. Indications based on ICU LOS reported for patients continuing care suggest median ICU stay will progressively increase. ConclusionsThese parameter estimates are key to the development of an effective health care resource model. Based on our appraisal of the literature, is it essential that Europe manages mitigation measures to ensure that hospital and ICU capacity does not become overwhelmed to manage COVID-19 in subsequent infection waves. Strengths and limitations of this studyO_LIThe study provides timely information on the differences in hospitalisation, length of stay and ICU length of stay due to COVID-19 in a number of countries worldwide at the end of wave one in Europe; C_LIO_LIThis rapid review builds on a previously available review paper that reported length of stay in the early phase of the pandemic; many more studies outlining length of stay, and in particular, ICU length of stay, are now available; C_LIO_LIThis rapid review reports on study mortality rate giving an interesting insight into differences across countries and continents; C_LIO_LILimitations associated with any rapid review are pertinent to this study; a narrow aim was set, and the sources of the literature may be limited by the time-limited constraint of gathering relevant literature; and a number of articles available were in pre-print form and only undergoing peer review; and C_LIO_LIThis rapid review provides evidence-based estimates of Hospital and ICU length of stay due to COVID-19 infection across a number of countries to steer policy and provide parameter estimates for utilisation within a hospital resource model as preparations are made for subsequent waves of infection. C_LI
ABSTRACT
ObjectiveTo estimate the proportion of pre-symptomatic transmission of SARS-CoV-2 infection that can occur and timing of transmission relative to symptom onset. Setting/designSecondary analysis of international published data. Data sourcesMeta-analysis of COVID-19 incubation period and a rapid systematic review of serial interval and generation time, which are published separately. ParticipantsStudies were selected for analysis if they had transparent methods and data sources and they provided enough information to simulate full distributions of serial interval or generation time. Twenty-three estimates of serial interval and five of generation time from 17 publications were included. MethodsSimulations were generated of incubation period and of serial interval or generation time. From these, transmission times relative to symptom onset were calculated and the proportion of pre-symptomatic transmission was estimated. Outcome measuresTransmission time of SARS-CoV-2 relative to symptom onset and proportion of pre-symptomatic transmission. ResultsTransmission time ranged from a mean of 2.91 (95% CI: 3.18-2.64) days before symptom onset to 1.20 (0.86-1.55) days after symptom onset. Unweighted pooling of estimates of transmission time based on serial interval resulted in a mean of 0.60 days before symptom onset (3.01 days before to 1.81 days after). Proportion of pre-symptomatic transmission ranged from 42.8% (39.8%-45.9%) to 80.6% (78.1%-83.0%). The proportion of pre-symptomatic transmission from pooled estimates was 56.4% (34.9%-78.0%). ConclusionsWhilst contact rates between symptomatic infectious and susceptible people are likely to influence the proportion of pre-symptomatic transmission, there is substantial potential for pre-symptomatic transmission of SARS-CoV-2 in a range of different contexts. Our work suggests that transmission is most likely in the day before symptom onset whereas estimates suggesting most pre-symptomatic transmission highlighted mean transmission times almost three days before symptom onset. This highlights the need for rapid case detection, contact tracing and quarantine. Strengths and weaknesses of this studyO_LIWe estimate the extent and variation of pre-symptomatic transmission of SARS-CoV-2 infection across a range of contexts. This provides important information for development and targeting of control policies and for the parameterisation of transmission models. C_LIO_LIThis is a secondary analysis using simulations based on published data, some of which is in pre-print form and not yet peer-reviewed. There is overlap in the contact tracing data that informed some of our source publications. We partially address this by summarising data at source location level as well as at study level. C_LIO_LIPopulations where symptomatic people are rapidly isolated are likely have relatively more pre-symptomatic transmission. This should be borne in mind whilst interpreting our results, but does not affect our finding that there is substantial potential for pre-symptomatic transmission of SARS-CoV-2 infection. C_LIO_LIA strength of our approach is that it builds an understanding of pre-symptomatic transmission from a range of estimates in the literature, facilitates discussion for the drivers of variation between them, and highlights the consistent message that consideration of pre-symptomatic transmission is critical for COVID-19 control policy. C_LI
