Literature DB >> 33143712

At what times during infection is SARS-CoV-2 detectable and no longer detectable using RT-PCR-based tests? A systematic review of individual participant data.

Sue Mallett1, A Joy Allen2, Sara Graziadio3, Stuart A Taylor4, Naomi S Sakai4, Kile Green2, Jana Suklan2, Chris Hyde5, Bethany Shinkins6, Zhivko Zhelev5, Jaime Peters5, Philip J Turner7, Nia W Roberts8, Lavinia Ferrante di Ruffano9, Robert Wolff10, Penny Whiting11, Amanda Winter3, Gauraang Bhatnagar12, Brian D Nicholson7, Steve Halligan4.   

Abstract

BACKGROUND: Tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral ribonucleic acid (RNA) using reverse transcription polymerase chain reaction (RT-PCR) are pivotal to detecting current coronavirus disease (COVID-19) and duration of detectable virus indicating potential for infectivity.
METHODS: We conducted an individual participant data (IPD) systematic review of longitudinal studies of RT-PCR test results in symptomatic SARS-CoV-2. We searched PubMed, LitCOVID, medRxiv, and COVID-19 Living Evidence databases. We assessed risk of bias using a QUADAS-2 adaptation. Outcomes were the percentage of positive test results by time and the duration of detectable virus, by anatomical sampling sites.
RESULTS: Of 5078 studies screened, we included 32 studies with 1023 SARS-CoV-2 infected participants and 1619 test results, from - 6 to 66 days post-symptom onset and hospitalisation. The highest percentage virus detection was from nasopharyngeal sampling between 0 and 4 days post-symptom onset at 89% (95% confidence interval (CI) 83 to 93) dropping to 54% (95% CI 47 to 61) after 10 to 14 days. On average, duration of detectable virus was longer with lower respiratory tract (LRT) sampling than upper respiratory tract (URT). Duration of faecal and respiratory tract virus detection varied greatly within individual participants. In some participants, virus was still detectable at 46 days post-symptom onset.
CONCLUSIONS: RT-PCR misses detection of people with SARS-CoV-2 infection; early sampling minimises false negative diagnoses. Beyond 10 days post-symptom onset, lower RT or faecal testing may be preferred sampling sites. The included studies are open to substantial risk of bias, so the positivity rates are probably overestimated.

Entities:  

Keywords:  Anatomical sampling; COVID-19; Diagnostic test; Duration virus detection; IPD; QUADAS-2; RT-PCR; SARS-CoV-2; Systematic review

Mesh:

Year:  2020        PMID: 33143712      PMCID: PMC7609379          DOI: 10.1186/s12916-020-01810-8

Source DB:  PubMed          Journal:  BMC Med        ISSN: 1741-7015            Impact factor:   8.775


Background

Accurate testing is pivotal to controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), otherwise known as the coronavirus disease 2019 (COVID-19). Considerable political and medical emphasis has been placed on rapid access to testing both to identify infected individuals so as to direct appropriate therapy, appropriate return to work, and to implement containment measures to limit the spread of disease. However, success depends heavily on test accuracy. Understanding when in the disease course the virus is detectable is important for two purposes, firstly to understand when and how to detect SARS-CoV-2, and secondly to understand how long individuals are likely to remain infective posing a risk to others. The success of COVID-19 testing depends heavily on the use of accurate tests at the appropriate time. Testing for active virus infection relies predominantly on reverse transcription polymerase chain reaction (RT-PCR), which detects viral ribonucleic acid (RNA) that is shed in varying amounts from different anatomical sites and at different times during the disease course. It is increasingly understood that differences in virus load impact directly on diagnostic accuracy, notably giving rise to negative tests in disease-positive individuals [1, 2]. Positivity is contingent upon sufficient virus being present to trigger a positive test which may depend on test site, sampling methods, and timing [3]. For example, it is believed that positive nasopharyngeal RT-PCR declines within a week of symptoms so that a positive test later in the disease course is more likely from sputum, bronchoalveolar lavage fluid, or stool [4]. Nomenclature for anatomical site is also unclear, with a wide variety of overlapping terms used such as “oral”, “throat”, “nasal”, “pharyngeal”, and “nasopharyngeal”. Because testing is pivotal to management and containment of COVID-19, we performed an individual participant data (IPD) systematic review of emerging evidence about test accuracy by anatomical sampling site to inform optimal sampling strategies for SARS-CoV-2. We aimed to examine at what time points during SARS-CoV-2 infection it is detectable at different anatomical sites using RT-PCR-based tests.

Methods

This IPD systematic review followed the recommendations of the PRISMA-IPD checklist [5].

Eligibility

Eligible articles were any case series or longitudinal studies reporting participants with confirmed COVID-19 tested at multiple times during their infection and provided IPD for RT-PCR test results at these times. We stipulated that test timings were linked to index dates of time since symptom onset or time since hospital admission as well as COVID-19 diagnosis by positive RT-PCR and/or suggestive clinical criteria, for example World Health Organization (WHO) guidelines [6].

Search strategy and article selection

Search strings were designed and conducted subsequently in PubMed, LitCOVID, and medRxiv by an experienced information specialist (NR). The search end date was 24 April 2020. We additionally included references identified by COVID-19: National Institute for Health Research (NIHR) living map of living evidence (http://eppi.ioe.ac.uk/COVID19_MAP/covid_map_v4.html), COVID-19 Living Evidence (https://ispmbern.github.io/covid-19/living-review/) with a volunteer citizen science team, “The Virus Bashers” (Additional file 1: Table S1).

Data extraction

Data were extracted into pre-specified forms. We did not contact authors for additional information. Study, participant characteristics, and ROB were extracted in Microsoft Excel (KG, JS, SG, JA, AW, SM). Data included country, setting, date, number of participants and IPD participants, inclusion criteria, IPD selection, participant age, sample types, RT-PCR test type and equipment, and primers. RT-PCR test results were extracted using Microsoft Access (SM, BS, JP, ZZ, CH).

Risk of bias

We could not identify an ideal risk of bias (ROB) tool for longitudinal studies of diagnostic tests, so we adapted the risk of bias tool for diagnostic accuracy studies QUADAS-2 [7] to include additional signalling questions to cover anticipated issues. ROB signalling questions, evaluation criteria, and domain assessment of potential bias are reported (Additional file 1: Table S2).

Sampling method and grouping

Details of sampling sites and methods, including location of the sampling site(s) and any sample grouping (for example, if combined throat and nasal swabs), were extracted from full texts by a clinician (NS) with queries referred to a second clinician (ST). If stated, details of sampling methodology were recorded, including who collected samples, information regarding anatomical location (e.g. how the nasopharynx was identified), and sample storage (Additional file 1: Table S3).

RT-PCR test result conversion to binary results

IPD RT-PCR results were extracted from each article and converted to binary results (“positive” or “negative”). Data from Kaplan-Meier (KM) curves were extracted using Web digitizer [8] (Additional file 1: Table S3).

Data analysis

Days since symptom onset and days since hospital admission were calculated from reported IPD. Data were presented collated across 5-day time intervals for each sample method, with longer times grouped within the longest time interval, and 95% CI was calculated for proportions. For comparison of duration of positive RT-PCR from respiratory tract (RT) and faecal samples, analysis and graphical presentation were restricted to participants sampled by both methods. Data analysis used STATA (14.2 StataCorp LP, Texas, USA) (Additional file 1: Table S3).

Results

Included studies

A total of 5078 articles were identified, 116 full text articles were screened, and 32 articles were included [9-40] (Fig. 1). Most articles were from China, in hospitalised adult participants (Table 1). Articles reported on a total of 1023 participants and 1619 test results.
Fig. 1

PRISMA flowchart

Table 1

Study characteristics of study design

RefAuthor yearCountryLocationSettingDate recruitedNo. of participants in studyNo. of IPD participantsStudy designInclusion criteria: reference test
[9]Cai 2020aChinaWenzhouCommunity18 December 2019–12 February 20203534Contact tracing, all patients visited a shopping mall (confirmed COVID-19 cases that had contact with each other)Positive RT-PCR test
[16]Chang 2020ChinaPLA General Hospital, BeijingHospital28 January 2020 to 9 February 20201616Confirmed COVID-19 patients released from the Treatment Center of PLA General HospitalPositive RT-PCR test from throat swabs
[10]Chen 2020aChinaBeijing Ditan Hospital, Capital Medical UniversityHospital20 January to 27 February13322Retrospectively identified a convenience sample of patients admitted to hospitalAt least 2 positive RT-PCR test pharyngeal swabs
[12]Chen 2020bChinaShanghai, Shanghai Public Health Clinical Center.Public Health Clinical Center20 January 2020 to 6 February 2020249248Retrospective cohort of laboratory confirmed casesPositive RT-PCR test according to WHO interim guidelines
[29]He 2020ChinaGuangzhou Eighth People’s Hospital, Guangzhou, ChinaHospital21 January 2020 to 14 February 20209419All admitted COVID confirmed cases admitted to hospitalAt least one positive RT-PCR test throat sample
[24]Hu 2020aChinaQingdao, ShandongHospital29 January 2020 to 12 March 20205959Retrospective cohort of confirmed hospital casesPositive RT-PCR test
[30]Hu 2020bChinaSecond Hospital of Nanjing, ChinaHospital28 January 2020 to 9 February 20202423Initial asymptomatic patientsPositive RT-PCR test and/or positive CT
[28]Cai 2020bChinaShanghai, ChinaHospital19 January 2020 to 3 February 2020101010 children admitted to hospitalPositive RT-PCR test nasopharyngeal or throat swab
[31]Kujawski 2020USAMultiple sites, USACommunity20 January 2020 to 5 February 20201212First 12 patients confirmed SARS-CoV-2 positive in the USAPositive RT-PCR test in ≥ 1 specimen from a patient. Confirmed by CDC
[39]Lavezzo 2020ItalyPadua, Veneto region, ItalyCommunity21 February 2020 to 7 March 2020281280Epidemiological study of entire population of Vo’, Italy, during complete closure of population movementPositive RT-PCR test on nasopharyngeal swab
[27]Lescure 2020FranceParis, BordeauxHospital24 January 2020 to 29 January 202055First 5 patients in France, exposed to COVID-19 in Hubei Province, China, prior to travel to FrancePositive RT-PCR test
[34]Li 2020ChinaXuzhouCommunity13 January 2020 to 17 February 202077Asymptomatic contact tracingPositive RT-PCR test
[14]Liu 2020aChinaHospital of Nanchang UniversityHospital21 January 2020 to 4 February 20207625Patients admitted to the hospitalPositive RT-PCR test from nasal swabs
[32]Liu 2020bChinaXixi Hospital of HangzhouHospital22 January 2020 to 11 February 20201010Hospital admissionTwo consecutive positive RT-PCR tests
[18]Lo 2020ChinaCentro Hospitalar Conde de Sao Januario, Macau SAR, ChinaHospital21 January 2020 to 16 February 20201010Retrospective study of first 10 COVID-confirmed patients in MacauPositive RT-PCR test
[20]Lu 2020ChinaNantong, Nantong Third HospitalHospital23 January 2020 to 6 March 20203635Retrospective analysis of clinical patients with fever, coughing, or lung inflammationPositive RT-PCR test
[19]Song 2020ChinaWuhan No. 1 Hospital, Nanjing Medical UniversityHospital31 January to 14 March 20201313Confirmed by CT imagesPositive RT-PCR test
[13]To 2020China (Hong Kong)Public Health Lab services branch in Hong KongPublic Health LabNot reported121212 patients who presented with fever and acute respiratory distress, or pneumonia, and travel to Wuhan 14 days before onset of symptomsPositive RT-PCR test from nasopharyngeal or sputum sample
[17]Wolfel 2020GermanyMunich, GermanyHospitalNot reported99Patients that acquired infections upon known close contact to an index case (part of a larger cluster of epidemiologically linked cases that occurred after 23 January 2020 in Munich, Germany)Positive RT-PCR test from oro- or nasopharyngeal swab
[37]Wu 2020ChinaZhuhai, GuangdongHospital16 January 2020 to 15 March 20207441Retrospective study of hospitalised patientsPositive RT-PCR test in two sequential respiratory tract samples
[40]Wyllie 2020USANew Haven, CTCommunity (healthcare workers)Not reported to 5 April 202098 (44 inpatients)19Study of inpatients (44) and healthcare workers (98)Positive RT-PCR test by nasopharyngeal swab or saliva
[21]Xia 2020ChinaZhejiangHospital26 January 2020 to 9 February 20203030A prospective interventional case series study of confirmed novel coronavirus pneumonia (NCP) patients at hospitalPositive RT-PCR test
[23]Xiao 2020ChinaTongji Hospital, Huazhong, WuhanHospital21 January 2020 to 12 February 2020565630 confirmed novel coronavirus pneumonia (NCP) patients were selectedPositive RT-PCR test
[33]Xu 2020aChinaChangzhouHospital23 January 2020 to 27 February 20205148Hospital admission including 12 family clustersConfirmed COVID-19 by Chinese diagnosis and treatment guideline
[36]Xu 2020bChinaGuangzhou, Guangzhou Women and Children’s Medical CenterHospital but from community surveillance22 January 2020 to 20 February 20201010“Highly suspected” children with contact with confirmed COVID-19 person, or member of infected family group who was placed in quarantinePositive RT-PCR test from nasopharyngeal or rectal swabs
[11]Yang 2020ChinaShenzhen Third People’sHospital11 January and 3 February 202021313COVID-19 positive hospitalised patientsPositive RT-PCR test
[26]Young 2020Singapore4 hospitals in SingaporeHospital23 January 2020 to 3 February 20201818Contact tracing. First hospitalised patients in SingaporePositive RT-PCR test
[22]Yuan 2020ChinaFifth Affiliated Hospital, Zhuhai, Guangdong Province, ChinaHospitalLate January66Case seriesPositive RT-PCR test
[25]Zhang 2020aChinaWuhan Pulmonary Hospital, CAS Key Laboratory of Special PathogensHospitalNot reportedUnclear16Prospective cohort patientsPositive RT-PCR test from oral swab
[35]Zhang 2020bChinaGuangdongHospital30 January 2020 to 5 February 202077Prior hospitalisation for COVID-19, discharged under quarantine and subsequently positive by RT-PCR againPositive RT-PCR test
[38]Zheng 2020ChinaZheijang, ChinaHospital19 January 2020 to 15 February 20209696Retrospective cohort of 96 consecutively confirmed hospital casesPositive RT-PCR test
[15]Zou 2020ChinaZhuhai, GuangdongCommunity and hospital7 January to 26 January 202018172 family clusters of patients infected by SARS-CoVPositive RT-PCR test. Assay from Chinese CDC
PRISMA flowchart Study characteristics of study design Twenty-six (81%) articles reported data on test results since the start of symptoms, and 23 (72%) since hospital admission. Sixteen studies including 22% (229/1023) of the participants reported both these time points: The median time between symptom onset and hospitalisation was 5 days (interquartile range (IQR) 2 to 7 days). The median number of participants per study was 22 (IQR 9 to 56, range 5 to 232), and the median number of RT-PCR test results per participant was 4 (IQR 2 to 9) (Table 2).
Table 2

Study characteristics of IPD participant, sample site, and test type

RefAuthor yearHow were IPD participants selected?Percentage of maleAge median (years)Age mean (years)Age range (years)Sample sitePCR test type; name of equipment if reportedGenomic targets; primers reported/referenced/ included
[9]Cai 2020IPD of almost all patients in studyNRNRNRNRNot reportedqRT-PCR; not reportedORF1ab, N-gene; not reported
[16]Chang 2020IPD of all patients in study6936Not reportedIQR 24–43ThroatqRT-PCR; not reportedNot reported; not reported
[10]Chen 2020aInitial or follow-up positive sputum or faecal samples paired with a follow-up negative pharyngeal sample643737IQR 30–49Faeces, sputum, URT (pharyngeal)qRT-PCR; not reportedORF1ab, N-gene; not reported
[12]Chen 2020bIPD of all patients in study5151IQR 36–64URTqRT-PCR; not reportedORF1ab, N-gene; not reported
[29]He 2020IPD for all 94 patients presented, but could only extract 19 IPD from overlapping graphs5047ThroatqRT-PCR; not reportedN-gene; not reported
[24]Hu 2020aIPD of all patients in study4846NRNRNasopharyngealqRT-PCR; not reportedORF1ab, N-gene; not reported
[30]Hu 2020bIPD of almost all patients in study3333385–95ThroatqRT-PCR; BGI GenomicsORF1ab; primers included
[28]Jiehao 2020IPD of all patients in study40763 months–11 yearsURTqRT-PCR; not reportedORF1ab, N-gene; not reported
[31]Kujawski 2020IPD of all patients in study675321–68Throat, nasopharyngeal, sputum, urine, faecesqRT-PCR; not reportedN-gene; not reported
[39]Lavezzo 2020All residents identified with infection50NRNRNRNasopharyngealqRT-PCR; One Step Real Time kit (Thermo Fisher Scientific, USA)E-gene, RdRp; primers referenced
[27]Lescure 2020IPD of all patients in study60464730–80Nasopharyngeal, faeces, conjunctiva, urine, blood, LRT (pleural)qRT-PCR; not reportedE-gene, RdRp; primers included
[34]Li 2020IPD of all patients in study57424321–62ThroatqRT-PCR; not reportedNot reported; not reported
[14]Liu 2020a25 participants with serial samples tested for PCRNRNANANANasopharyngealqRT-PCR; not reportedNot reported; not reported
[32]Liu 2020bIPD of all patients in study404234–50Mixed URT (nasal, throat)qRT-PCR; not reportedE-gene, RdRp, N-gene; not reported
[18]Lo 2020IPD of all patients in study3054NRNRFaeces, nasopharyngeal, urineqRT-PCR; BioGermORF1ab, N-gene; not reported
[20]Lu 2020IPD of all patients in studyNRNRNRNRSputum, URT (pharyngeal), faeces, bloodqRT-PCR; not reportedORF1ab, N-gene; primers included
[19]Song 2020IPD of all patients in study100NRNR22–67URT (pharyngeal)qRT-PCR; Huirui biotechnologyNot reported; not reported
[13]To 2020IPD of all patients in study586337 to 75SalivaqRT-PCR; QuantiNova SYBR Green RT-PCR kit (Qiagen)S-gene; not reported
[17]Wolfel 2020IPD of all patients in studyNRNot reportedNot reportedNot reportedSputum, faeces, URT (pharyngeal)qRT-PCR; Tib-Molbiol, GermanyE-gene, RdRp; not reported
[37]Wu 2020Retrospective 41 patients with positive faecal samples only53NRNRNRThroat, faecesqRT-PCR; 2019-nCOV Real Time RT-PCR kit (LifeRiver Ltd)E-gene, RdRp, N-gene
[40]Wyllie 2020Patients with multiple nasopharyngeal swabs or multiple saliva swabsInpatients (52), healthcare workers (16)NR6123–92Nasopharyngeal, salivaqRT-PCR; US CDC RT-PCR primer/probe setsN-gene; primers referenced
[21]Xia 2020IPD of all patients in study70515513–83Sputum, conjunctivaqRT-PCR; BioGermNot reported; not reported
[23]Xiao 2020IPD of all patients in study61555525–83URT (pharyngeal)qRT-PCR; Shanghai Huirui Biotechnology Co.ORF1ab, N-gene; not reported
[33]Xu 2020aIPD of almost all patients in study493 groups: imported 35 [29–51], secondary 37 [24–47.5], tertiary 53 [35–65]24–65ThroatqRT-PCR; BioGermORF1ab, N-gene; not reported
[36]Xu 2020bIPD of all patients in study60782 months–16 yearsNasopharyngeal, faecesqRT-PCR; BioGermORF1ab, N-gene; primers included
[11]Yang 2020Not reported how 13 patients for serial sampling IPD data chosen51522–86Mixed URT (nasal swabs, throat swabs) and mixed LRT (sputum and bronchoalveolar lavage fluid (BALF))qRT-PCR; GeneoDX Co.Not reported; not reported
[26]Young 2020IPD of all patients in study504731–73Nasopharyngeal, faeces, urine, bloodqRT-PCR; not reportedORF1ab, N-gene, S-gene; primers included
[22]Yuan 2020IPD of all patients in study33645936–71Nasopharyngeal, faecesqRT-PCR; not reportedE-gene, RdRp, N-gene; not reported
[25]Zhang 2020aNot reportedNRNRNRNRURT (oral), faecesqRT-PCR; HiScript®II One Step qRT-PCR SYBR®Green Kit (Vazyme Biotech Co.)S-gene; primer included
[35]Zhang 2020bIPD of all patients in study86262210 months–35 yearsThroat, faeces, bloodqRT-PCR; not reportedNot reported; not reported
[38]Zheng 2020IPD of all patients in study6055NRNRSputum, faeces, bloodqRT-PCR; SARS-CoV-2 detection kit (BoJie Shanghai)ORF1ab; not reported
[15]Zou 2020IPD of almost all patients in study505926–76Throat, URT (nasal)qRT-PCR; not reportedORF1ab, N-gene; not reported
Study characteristics of IPD participant, sample site, and test type

Sampling site reporting

Articles variably specified sampling sites according to anatomical location, or grouped more than one site for analysis, for example as upper RT (Additional file 1: Table S4). The most frequent sample sites were faeces (n = 13), nasopharyngeal (n = 10), and throat (n = 9), although there was a range of other sites including blood, urine, semen, and conjunctival swabs (Table 2). Details of sampling method were generally absent. Two studies specified the person taking the samples. One study described how the nasopharynx was identified and the swab technique (length of contact time with the nasopharynx and twisting). Five studies specified sample storage and transport details.

Sampling site positivity over time

We present RT-PCR test results for 11 different sampling sites at different times during SARS-CoV-2 infection. Figures 2 and 3 show the number of positive and negative RT-PCR results for 5-day time intervals since symptom onset and time from hospital admission, respectively.
Fig. 2

Number of positive and negative RT-PCR test results since symptom onset. Each panel shows a separate site used in participant sampling. Nasopharyngeal, saliva, and sputum were used where clearly reported. Throat included throat and oropharyngeal. Other URT includes samples reported in articles as nasal, mixed nasal and throat, oral, pharyngeal, or upper respiratory tract. For pharyngeal sampling, it was not clear if this was nasopharyngeal or oropharyngeal. Other LRT includes sampling reported as lower respiratory tract or one article including pleural fluid sampling. Blood included serum, plasma, or blood. Faeces included stool or anal swab. Each panel shows 5-day time periods since the onset of symptoms: 0–4 days, 5–9 days, 10–14 days, 15–19 days, 20–25 days, 26–30 days, 31–34 days, and 35 to max days. The numbers of positive RT-PCR tests are shown as dark blue bars and dark grey bars from 0 to 14 days and 15 to 40 days, respectively, and the number of negative RT-PCR results is shown similarly as light blue bars and light grey bars. Different colours are used before and after 15 days to indicate caution, as after 15 days testing is enriched in more severely ill participants. The total number of tests within a particular time period can be read from the x-axis

Fig. 3

Number of positive and negative RT-PCR test results since hospital admission. Each panel shows a separate site used in participant sampling. Nasopharyngeal, saliva, and sputum were used where clearly reported. Throat included throat and oropharyngeal. Other URT includes samples reported in articles as nasal, mixed nasal and throat, oral, pharyngeal, or upper respiratory tract. For pharyngeal sampling, it was not clear if this was nasopharyngeal or oropharyngeal. Other LRT includes sampling reported as lower respiratory tract or one article including pleural fluid sampling. Blood included serum, plasma, or blood. Faeces included stool or anal swab. Each panel shows 5-day time periods since the hospital admission: 0–4 days, 5–9 days, 10–14 days, 15–19 days, 20–25 days, 26–30 days, 31–34 days, and 35 to max days. The numbers of positive RT-PCR tests are shown as dark blue bars and dark grey bars from 0 to 14 days and 15 to 40 days, respectively, and the number of negative RT-PCR results is shown similarly as light blue bars and light grey bars. Different colours are used before and after 15 days to indicate caution, as after 15 days testing is enriched in more severely ill participants. The total number of tests within a particular time period can be read from the x-axis

Number of positive and negative RT-PCR test results since symptom onset. Each panel shows a separate site used in participant sampling. Nasopharyngeal, saliva, and sputum were used where clearly reported. Throat included throat and oropharyngeal. Other URT includes samples reported in articles as nasal, mixed nasal and throat, oral, pharyngeal, or upper respiratory tract. For pharyngeal sampling, it was not clear if this was nasopharyngeal or oropharyngeal. Other LRT includes sampling reported as lower respiratory tract or one article including pleural fluid sampling. Blood included serum, plasma, or blood. Faeces included stool or anal swab. Each panel shows 5-day time periods since the onset of symptoms: 0–4 days, 5–9 days, 10–14 days, 15–19 days, 20–25 days, 26–30 days, 31–34 days, and 35 to max days. The numbers of positive RT-PCR tests are shown as dark blue bars and dark grey bars from 0 to 14 days and 15 to 40 days, respectively, and the number of negative RT-PCR results is shown similarly as light blue bars and light grey bars. Different colours are used before and after 15 days to indicate caution, as after 15 days testing is enriched in more severely ill participants. The total number of tests within a particular time period can be read from the x-axis Number of positive and negative RT-PCR test results since hospital admission. Each panel shows a separate site used in participant sampling. Nasopharyngeal, saliva, and sputum were used where clearly reported. Throat included throat and oropharyngeal. Other URT includes samples reported in articles as nasal, mixed nasal and throat, oral, pharyngeal, or upper respiratory tract. For pharyngeal sampling, it was not clear if this was nasopharyngeal or oropharyngeal. Other LRT includes sampling reported as lower respiratory tract or one article including pleural fluid sampling. Blood included serum, plasma, or blood. Faeces included stool or anal swab. Each panel shows 5-day time periods since the hospital admission: 0–4 days, 5–9 days, 10–14 days, 15–19 days, 20–25 days, 26–30 days, 31–34 days, and 35 to max days. The numbers of positive RT-PCR tests are shown as dark blue bars and dark grey bars from 0 to 14 days and 15 to 40 days, respectively, and the number of negative RT-PCR results is shown similarly as light blue bars and light grey bars. Different colours are used before and after 15 days to indicate caution, as after 15 days testing is enriched in more severely ill participants. The total number of tests within a particular time period can be read from the x-axis The sampling sites yielding the greatest proportion of positive tests were nasopharyngeal, throat, sputum, or faeces. Insufficient data were available to evaluate saliva and semen. Only 33% of participants who were tested with blood samples had detectable virus (44/133; 6 articles [20, 26, 27, 31, 35, 38]), and almost no samples tested from urine or conjunctival sampling detected virus presence. Using nasopharyngeal sampling, 89% (147/166, 95% CI 83 to 93) RT-PCR test results were positive from 0 to 4 days post-symptom onset and 81% (100/124, 95% CI 73 to 87) 0 to 4 days post-hospital admission (Figs. 2 and 3). At 10 to 14 days, the percentage of test results positive reduced to 54% (120/222, 95% CI 47 to 61) post-symptoms and 45% (37/82, 95% CI 34 to 57) post-admission (Additional file 1: Figures S6 and S7). Using throat sampling at 0 to 4 days post-symptoms, 90% (91/101, 95% CI 83 to 95) of test results from participants with SARS-CoV-2 were detected by RT-PCR sampling, falling to 42% (58/139, 95% CI 33 to 50) at 10 to 14 days post-symptom onset (Fig. 2, Additional File 1: Figures S6 and S7). Similar results were observed for time since hospital admission, where at 0 to 4 days 80% (173/215, 95% CI 75 to 86) of result were positive, falling to 35% (55/155, 95% CI 28 to 44) between 10 and 14 days (Fig. 3, Additional file 1: Figures S6 and S7). Using faecal sampling, 55% test results are positive (22/40, 95% CI 38 to 71) at 0 to 4 days post-symptom onset.

Upper and lower respiratory tract sampling

We further grouped sites into upper (URT) and lower (LRT) respiratory tract. The rate of sample positivity reduced faster from URT sites compared to LRT sites (Fig. 4a). Given that analysis across all participants is likely to be influenced by preferential URT sampling of participants with less severe disease, we also analysed participants who underwent both URT and LRT sampling. Again, URT sites on average cleared faster (median 12 days, 95% CI 8 to 15 days) than LRT sites (median 28 days, 95% CI 20 to not estimable; Fig. 4b); the majority of participants clear virus from URT site before LRT (Fig. 4c). Data based on time since hospital admission are consistent with data for time since symptom onset.
Fig. 4

Comparison of duration of detectable virus from upper and lower respiratory tract sampling. a Time to undetectable virus in upper and lower respiratory tract samples. Kaplan-Meier with 95% confidence intervals and number at risk. All samples in review. b Time to undetectable virus in upper and lower respiratory tract samples in participants who were tested with both upper and lower respiratory tract sampling. Kaplan-Meier with 95% confidence intervals and number at risk. Restricted to participants with both sampling methods. c Time to undetectable virus in upper and lower respiratory tract samples in participants who were tested with both upper and lower respiratory tract sampling. Scatterplot where each dot represents a single participant, with the time to undetectable virus with both upper and lower respiratory tract sampling shown for each participant

Comparison of duration of detectable virus from upper and lower respiratory tract sampling. a Time to undetectable virus in upper and lower respiratory tract samples. Kaplan-Meier with 95% confidence intervals and number at risk. All samples in review. b Time to undetectable virus in upper and lower respiratory tract samples in participants who were tested with both upper and lower respiratory tract sampling. Kaplan-Meier with 95% confidence intervals and number at risk. Restricted to participants with both sampling methods. c Time to undetectable virus in upper and lower respiratory tract samples in participants who were tested with both upper and lower respiratory tract sampling. Scatterplot where each dot represents a single participant, with the time to undetectable virus with both upper and lower respiratory tract sampling shown for each participant

Faecal vs. respiratory tract sampling

Across participants sampled by both RT and faecal sampling since hospital admission, 29% of participants were detected using RT sampling but not by faecal sampling (52/177 participants, 95% CI 23 to 37%, 10 studies). The time to RT-PCR tests becoming undetectable varied greatly by participant, although time to undetectable virus was similar for both sampling sites (Fig. 5), in participants with RT-PCR test results from both RT and faecal samples. Thirty-nine out of 89 participants (44%, 95% CI 33 to 55%) had a shorter duration of detection in faecal samples than in RT samples.
Fig. 5

Comparison of days to undetectable virus from respiratory tract and faecal sampling. Time to undetectable virus in faecal compared to any respiratory tract sample in participants who were tested with both sampling. Scatterplot where each dot represents a single participant, with the time to undetectable virus with both faecal and respiratory tract sampling shown for each participant. Thirty percent of participants tested at both sampling sites do not have detectable virus in faecal samples

Comparison of days to undetectable virus from respiratory tract and faecal sampling. Time to undetectable virus in faecal compared to any respiratory tract sample in participants who were tested with both sampling. Scatterplot where each dot represents a single participant, with the time to undetectable virus with both faecal and respiratory tract sampling shown for each participant. Thirty percent of participants tested at both sampling sites do not have detectable virus in faecal samples Median time to clearance from RT was shorter in participants based on time since hospitalisation (125 participants, p = 0.014), whilst similar in participants since onset of symptoms (87 participants, p = 0.15) (Additional file 1: Figures S8).

Intermittent false negative results

Many articles reported intermittent false negative RT-PCR test results for participants within the monitoring time span. Where participant viral loads were reported, several different profiles were distinguished; two examples are shown in Fig. 6 [14, 15]. Intermittent false negative results were reported either where the level of virus is close to the limit of detection, or in participants with high viral load but for unclear reasons.
Fig. 6

Example participants with intermittent false negative results. a An example of a participant with high viral load, but where alternate RT-PCR test results report high viral load or undetectable virus. b A participant where virus levels have reduced over time to a level around the limit of viral detection, and at these low levels of virus, intermittent negative results will occur due to differences in the location or amount of sample

Example participants with intermittent false negative results. a An example of a participant with high viral load, but where alternate RT-PCR test results report high viral load or undetectable virus. b A participant where virus levels have reduced over time to a level around the limit of viral detection, and at these low levels of virus, intermittent negative results will occur due to differences in the location or amount of sample The proportion of studies with high, low, or unclear ROB for each domain is shown in Fig. 7, and ROB for individual studies is shown in Additional file 1: Table S5. All studies were judged at high ROB. All but one were judged at high ROB for the participant selection domain [17], mainly as they only included participants with confirmed SARS-CoV-2 infection based on at least one positive PCR test. Studies also frequently selected a subset of the participant cohort for longitudinal RT-PCR testing, and only results for these participants were included in the study. Ten studies were judged at unclear ROB for the index test domain as the schedule of testing was based on clinician choice rather than being pre-specified by the study or clinical guidelines, or because the samples used for PCR testing were not pre-specified. Eleven studies were judged at high ROB for the flow and timing domain mainly because continued testing was influenced by easy access to participants, such as by continued hospitalisation.
Fig. 7

Risk of bias by adapted QUADAS-2 domain. An adapted version of QUADAS-2 for longitudinal studies was used (Additional file 1: Table S2). For each domain, the percentage of studies by concern for potential risk of bias is shown: low (green), unclear (yellow), and high (red)

Risk of bias by adapted QUADAS-2 domain. An adapted version of QUADAS-2 for longitudinal studies was used (Additional file 1: Table S2). For each domain, the percentage of studies by concern for potential risk of bias is shown: low (green), unclear (yellow), and high (red)

Discussion

Key findings

Negative RT-PCR test results were common in people with SARS-CoV-2 infection confirming that RT-PCR testing misses identification of people with disease. Our IPD systematic review has established that sampling site and time of testing are key determinants of whether SARS-CoV-2 infected individuals are identified by RT-PCR. We found that nasopharyngeal sampling was positive in approximately 89% (95% CI 83 to 93) of tests within 4 days of either symptom onset. Sampling 10 days after symptom onset greatly reduced the chance of a positive test result. There were limited data on new methods of sample collection like saliva in these longitudinal studies. Sputum samples have similar or higher levels of detection to nasopharyngeal sampling, although this may be influenced by preferential sputum sampling in severely ill participants. Although based on few participants tested at both sampling sites, URT sites have faster viral clearance than LRT in most of these participants; 50% of participants were undetectable at URT sites 12 days after symptom onset compared to 28 days for LRT. We found that faecal sampling is not suitable for initial detection of disease, as up to 30% of participants detected using respiratory sampling are not detected using faecal sampling. Viral detection in faecal samples may be useful to establish virus clearance, although as noted, whether RT or faecal samples have longer duration of viral detection varies between participants. All included studies were judged at high ROB, so results of this review should be interpreted with caution. Table 3 provides an overview of the major methodological limitations and their potential impact on study results. A major source of bias is that all but one study [19] restricted inclusion to participants with confirmed SARS-CoV-2 infection based on at least one positive RT-PCR test, meaning that the percentage of positive RT-PCR testing is likely to be overestimated.
Table 3

Biases and issues in interpretation

DomainDetails of bias and applicability issuesImpact on interpretation of study data
Participants (source of bias)

In these studies, the reference test usually incorporates RT-PCR (index test).

• RT-PCR testing is usually a key component of identifying people with SARS-CoV-2 infection.

• Participants will not be detected or included in these studies when SARS-CoV-2 is not present at easily sampled sites and at the time that participants were available for testing.

Unclear how many and what severity of participants with SARS-CoV-2 are not included in studies.

People who do not have a positive RT-PCR test at some point are excluded. This could lead to overestimation of positivity.

Rates of positivity will be inflated as only people with virus accessible for sampling for RT-PCR tests will be included in studies.
Participants (source of bias)Most participants are identified or present based on respiratory tract symptoms such as cough or respiratory distress.Unclear how many and what severity of participants with SARS-CoV-2 are not included in studies.
• Participants will not be detected or included in these studies when less common symptoms or asymptomatic.
• Participants included will be biased to over-represent people with detectable virus in respiratory tract sampling sites and at times frequently used for testing (post symptom onset or at admission to hospital).

Studies will inflate positivity for sampling sites that overlap with sampling sites used in RT-PCR reference testing.

• For example, we identified 30% of participants with RT positivity but with negative results from faecal sampling. However, if participants had only faecal virus, would they have been included in the studies?

Index test: RT-PCR (applicability)• Studies included are likely to use more invasive sampling methods than acceptable in widespread population testing. For example, nasopharyngeal testing is likely in many current studies to be based on long swabs and self test kits.Percentage of people with detectable virus may be overestimated when testing is applied in real-world clinical use and in population testing.
• Studies will use experienced staff to obtain samples, handle, process, and conduct tests.
• Studies are mostly sampling participants in hospital settings or in specialised research community testing research where sample handling, transport, and storage have been standardised.
• Variation in RT-PCR kits is minimised as studies are based in few hospitals or limited to a research setting
Index test: RT-PCR (applicability)

Sample RNA extraction methods are designed predominantly for respiratory samples.

• RT-PCR sample preparation kits used are mostly designed for extraction of virus from respiratory samples, not from faecal samples. It is unclear how efficiently these kits extract virus RNA from stool samples.

Percentage of people with virus present in faecal samples and duration of shedding in faecal samples may be underestimated.
Index test: RT-PCR (applicability)RT-PCR tests detect both infectious and inactive (inactive due to immune system or dead) virus.Percentage of people with clinically important detectable virus may be overestimated.
• Few studies link RT-PCR testing to cell assays to test for infectious virus.
Index test: RT-PCR (applicability)

Rate of virus aggregation or clearance by immune system may affect the sampling efficiency at some sampling sites.

• Both the innate and adaptive immune system will aggregate and clear virus particles from bodily fluids. It is not clear what the time scale of clearance or how this influences detection of virus at different sites and at which time points.

Percentage of people with detectable virus may be underestimated.
Index test: RT-PCR (applicability)

Reporting of sampling sites and methods is poor.

• Poor reporting may have led to less ideal grouping of sampling in analysis.

• Some studies are likely to use a variety of nasopharyngeal sampling methods depending on the individual participants, but the type of sampling is typically reported at a study level for a particular sampling site.

Percentage of people with detectable virus may be over- or underestimated.
Flow and timingUncertainty and inconsistencies in time of samplingPercentage of people with detectable virus may be over- or underestimated at particular times.

• Time of symptom onset can be subjective unless based on fever, but some participants do not have fever.

• Time of symptom onset may be different if asked of participants in ICU setting.

• Time of hospitalisation and discharge may be affected by function hospitalisation serves in containment of disease spread. In some studies, the hospitals were also quarantine centres, so participants were hospitalised immediately at onset of mild symptoms rather than restricted to patients needing oxygen.

Flow and timingClinical cohort within studies changes across time points.Percentage of people with detectable virus may be overestimated at particular later time points as these correspond to participants who were severely ill.

• Participants who have recovered from COVID-19 in most studies are typically not tested after 2 negative tests 24 h apart.

• Many studies only test inpatients at the hospital, so the participants sampled between 0 and 14 days typically have less severe disease than those tested longer

Flow and timing (selective outcome reporting)Some studies only publish IPD data for a selection of people.Available IPD data may not represent a typical spectrum of participants in the different settings (community setting, hospital, ICU, nursing home, prison).
Publication biasPublished data is likely to be biased towards publication of research active groups which may not represent typical real world.Percentage of people with detectable virus may be overestimated.

BAL bronchoalveolar lavage, COVID-19 coronavirus disease 2019, ICU intensive care unit, IPD individual participant data, RNA ribonucleic acid, RT-PCR reverse transcription polymerase chain reaction, SARS-CoV-2 severe acute respiratory syndrome coronavirus 2

Biases and issues in interpretation In these studies, the reference test usually incorporates RT-PCR (index test). • RT-PCR testing is usually a key component of identifying people with SARS-CoV-2 infection. Participants will not be detected or included in these studies when SARS-CoV-2 is not present at easily sampled sites and at the time that participants were available for testing. Unclear how many and what severity of participants with SARS-CoV-2 are not included in studies. People who do not have a positive RT-PCR test at some point are excluded. This could lead to overestimation of positivity. Studies will inflate positivity for sampling sites that overlap with sampling sites used in RT-PCR reference testing. • For example, we identified 30% of participants with RT positivity but with negative results from faecal sampling. However, if participants had only faecal virus, would they have been included in the studies? Sample RNA extraction methods are designed predominantly for respiratory samples. • RT-PCR sample preparation kits used are mostly designed for extraction of virus from respiratory samples, not from faecal samples. It is unclear how efficiently these kits extract virus RNA from stool samples. Rate of virus aggregation or clearance by immune system may affect the sampling efficiency at some sampling sites. • Both the innate and adaptive immune system will aggregate and clear virus particles from bodily fluids. It is not clear what the time scale of clearance or how this influences detection of virus at different sites and at which time points. Reporting of sampling sites and methods is poor. • Poor reporting may have led to less ideal grouping of sampling in analysis. • Some studies are likely to use a variety of nasopharyngeal sampling methods depending on the individual participants, but the type of sampling is typically reported at a study level for a particular sampling site. • Time of symptom onset can be subjective unless based on fever, but some participants do not have fever. • Time of symptom onset may be different if asked of participants in ICU setting. • Time of hospitalisation and discharge may be affected by function hospitalisation serves in containment of disease spread. In some studies, the hospitals were also quarantine centres, so participants were hospitalised immediately at onset of mild symptoms rather than restricted to patients needing oxygen. Participants who have recovered from COVID-19 in most studies are typically not tested after 2 negative tests 24 h apart. • Many studies only test inpatients at the hospital, so the participants sampled between 0 and 14 days typically have less severe disease than those tested longer BAL bronchoalveolar lavage, COVID-19 coronavirus disease 2019, ICU intensive care unit, IPD individual participant data, RNA ribonucleic acid, RT-PCR reverse transcription polymerase chain reaction, SARS-CoV-2 severe acute respiratory syndrome coronavirus 2 Lack of technical details, for example of how samples are taken and RT-PCR tests performed, limits the applicability of findings to current testing. Compared to real life, studies were likely to use more invasive sampling methods, use experienced staff to obtain samples, and sample participants in hospital settings where sample handling could be standardised. Consequently, estimates of test performance are likely to be overestimated compared to real-world clinical use and in community population testing including self-test kits. These limitations have important implications for how testing strategies should be implemented and in particular how a negative RT-PCR test result should be interpreted.

Putting the findings into context of literature

The accuracy of RT-PCR testing is limited by sampling sites used, methods, and the need to test as soon as possible from symptom onset in order to detect the virus. Previous studies have established that in COVID-19 infection, viral loads typically peak just before symptoms and at symptom onset [4] and estimated false negative test results over time since exposure from upper respiratory tract samples [2]. To our knowledge, there has been no prior systematic review of RT-PCR using IPD to quantify the percentage of persons tested who are positive and how this varies by time and sampling site. Understanding the distribution of anatomical sites with detectable virus is clinically relevant, especially given independent viral replication sites in nose and throat using distinct and separate genetic colonies [17]. Understanding of different patterns of detection and duration of virus detection at different body sites is essential when designing strategies of testing to contain virus spread. Notably, it is unclear if detection of virus in faeces is important in disease transmission, although faecal infection was shown in SARS and MERS [41].

Strengths of study

This review uses robust systematic review methods to synthesise published literature and identifies overall patterns not possible from individual articles. Using IPD, we examined data across studies and avoided study-level ecological biases present when using overall study estimates. IPD regarding sample site at different time points during infection is vital because it provides an overview of test performance impossible from individual studies alone. Synthesised IPD can also substantiate or reject patterns appearing within individual studies. Within-participant paired comparisons of sampling sites also become possible with sufficient data.

Limitations of study

The main limitation is the risk of bias in the included studies. Although constraints were understandable given the circumstances in which the studies were done, the consequences for validity need to be highlighted. The percentage of positive RT-PCR testing is likely to be overestimated, because inclusion was restricted to participants with confirmed SARS-CoV-2 infection based on at least one positive RT-PCR test in all but one study [19]. This means that people who had a COVID-19 infection but never tested positive on at least one RT-PCR test would not have been included. This could arise if SARS-CoV-2 is not present at easily sampled sites or at the time participants were tested. This makes it impossible to determine the true false negative rate of the test—the proportion of people who actually have SARS-CoV-2 but would receive a negative RT-PCR test result. It is possible that only half of persons infected by SARS-CoV-2 may test positive, as a community surveillance study in Italy found only 53% (80/152) persons tested RT-PCR positive in households quarantined for 18 days with persons who tested PCR positive [39]. The same study also identified households where no one tested RT-PCR positive, but where there were clusters of persons with symptoms typical of COVID. Poor reporting of sampling methods and sites impaired our ability to distinguish between and report on variability between them. For some sampling methods such as saliva and throat swabs, more studies are needed. There were also sparse data on sampling methods that are becoming more widespread, such as participant self-sampling [42] and short nasal swab sampling (anterior nares/mid turbinate) [43]. Our index times may be subject to bias as symptom onset is somewhat subjective and hospital admission practices vary by country, pandemic stage, and hospital role (i.e. healthcare vs. isolation). The results presented do not correspond to following the same participants across time, but the testing at clinically relevant time snapshots reported from individual studies, so that participants tested at later time points are likely to have more severe disease; this does not limit the interpretation of results in understanding testing of participants in most clinical contexts. Comparisons of sampling sites should be restricted to participants tested at the relevant sites. We have used analysis methods that do not include clustering within studies, to keep analyses simple to understand and present, and to avoid complications of fitting models where the number of participants in each cluster varies. Ultimately, many potentially eligible studies did not report IPD which led to their exclusion, or only reported IPD for a subset of participants in the study. We would welcome contact and data sharing with clinicians and authors to rectify this.

Implications for policy/practice/future research

To avoid the consequences of missed infection, samples for RT-PCR testing need to be taken as soon as symptoms start for detection of SARS-CoV-2 infection in preventing ongoing transmission. Even within 4 days of symptom onset, some participants infected with SARS-CoV-2 will receive negative test results. Testing at later times will result in a higher percentage of false negative tests in people with SARS-CoV-2, particularly at upper RT sampling sites. After 10 days post-symptoms, it may be important to use lower RT or faecal sampling. Valid estimates are essential for clinicians interpreting RT-PCR results. However, ROB considerations suggest that the positive percentage rates we have estimated may be optimistic, possibly considerably so. Participants can have detectable virus in different body compartments, so virus may not be detected if samples are only taken from a single site. Some hospitals in the UK now routinely take RT-PCR samples from multiple sites, such as the nose and throat. More studies are urgently needed on evolving sampling strategies such as self-collected samples which include saliva and short nasal swabs. Future studies should avoid the risks of bias we have identified by precisely reporting the anatomical sampling sites with a detailed methodology on sample collection. Table 4 details example studies helpful for future study design.
Table 4

Examples from included studies

Study characteristicDetailReference
Study design: representative recruitment

Representative participants

• Community infection

• Contact tracing including asymptomatic

• Hospitalised patients

Population surveillance of Italian town, with PCR testing across [39]

Contact tracing [9, 30, 34]

Retrospective cohort of 96 hospitalised patients [38]

Study design: planned testing and follow-up

Informative sampling

• Multiple sampling sites per participant

• Planned schedule of sampling

• Sampling continues after negative test results

• Sampling continues after hospital discharge

Three samples per patient, multiple testing including prolonged testing even after multiple negative results [10]

Population surveillance of Italian town over 18 days [39]

Long follow-up post-hospital [16, 35, 36]

Planned schedule of testing ([30], asymptomatic contact tracing follow-up [3638])

Study design: samplingReporting of sampling methods (sample site, staff conducting test, sample volumes, and methods)

Most studies had very sparse reporting of sample collection methods.

Example of fuller reporting [40]

Individual participant data reporting for sharingExamples of plots and tables that facilitated sharing of individual participant data

Retrospective cohort of 96 patients all tested with sputum, faeces, and blood. Plot shows time span of positive test results, hospitalisation timing, and disease severity for individual patients [38]

Data showing time course of illness with PCR test results [9, 31]

Data showing RT-PCR test results by patient and time point [10]

Viral load over time [15]

Examples from included studies Representative participants • Community infection • Contact tracing including asymptomatic • Hospitalised patients Population surveillance of Italian town, with PCR testing across [39] Contact tracing [9, 30, 34] Retrospective cohort of 96 hospitalised patients [38] Informative sampling • Multiple sampling sites per participant • Planned schedule of sampling • Sampling continues after negative test results • Sampling continues after hospital discharge Three samples per patient, multiple testing including prolonged testing even after multiple negative results [10] Population surveillance of Italian town over 18 days [39] Long follow-up post-hospital [16, 35, 36] Planned schedule of testing ([30], asymptomatic contact tracing follow-up [36-38]) Most studies had very sparse reporting of sample collection methods. Example of fuller reporting [40] Retrospective cohort of 96 patients all tested with sputum, faeces, and blood. Plot shows time span of positive test results, hospitalisation timing, and disease severity for individual patients [38] Data showing time course of illness with PCR test results [9, 31] Data showing RT-PCR test results by patient and time point [10] Viral load over time [15] Further sharing of IPD will be important, and we would welcome contact from groups with IPD data we can include in ongoing research.

Conclusions

RT-PCR misses detection of people with SARS-CoV-2 infection; early sampling minimises false negative diagnoses. Beyond 10 days post-symptom onset, lower RT or faecal testing may be preferred sampling sites. The included studies are open to substantial risk of bias, so the positivity rates are probably overestimated. Additional file 1. Including additional tables and figures: search details, QUADAS-2 adaption, anatomical sample size details, risk of bias by article, percentage positive and negative RT-PCR results by sample for days since symptom onset and days since hospitalisation, time to undetectable virus in faecal and respiratory tract.
  32 in total

1.  Caution should be exercised for the detection of SARS-CoV-2, especially in the elderly.

Authors:  Yajun Yuan; Nan Wang; Xueqing Ou
Journal:  J Med Virol       Date:  2020-04-25       Impact factor: 2.327

2.  Quantitative Detection and Viral Load Analysis of SARS-CoV-2 in Infected Patients.

Authors:  Fengting Yu; Liting Yan; Nan Wang; Siyuan Yang; Linghang Wang; Yunxia Tang; Guiju Gao; Sa Wang; Chengjie Ma; Ruming Xie; Fang Wang; Chianru Tan; Lingxiang Zhu; Yong Guo; Fujie Zhang
Journal:  Clin Infect Dis       Date:  2020-07-28       Impact factor: 9.079

3.  Virological assessment of hospitalized patients with COVID-2019.

Authors:  Roman Wölfel; Victor M Corman; Wolfgang Guggemos; Michael Seilmaier; Sabine Zange; Marcel A Müller; Daniela Niemeyer; Terry C Jones; Patrick Vollmar; Camilla Rothe; Michael Hoelscher; Tobias Bleicker; Sebastian Brünink; Julia Schneider; Rosina Ehmann; Katrin Zwirglmaier; Christian Drosten; Clemens Wendtner
Journal:  Nature       Date:  2020-04-01       Impact factor: 49.962

4.  QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies.

Authors:  Penny F Whiting; Anne W S Rutjes; Marie E Westwood; Susan Mallett; Jonathan J Deeks; Johannes B Reitsma; Mariska M G Leeflang; Jonathan A C Sterne; Patrick M M Bossuyt
Journal:  Ann Intern Med       Date:  2011-10-18       Impact factor: 25.391

5.  Indirect Virus Transmission in Cluster of COVID-19 Cases, Wenzhou, China, 2020.

Authors:  Jing Cai; Wenjie Sun; Jianping Huang; Michelle Gamber; Jing Wu; Guiqing He
Journal:  Emerg Infect Dis       Date:  2020-06-17       Impact factor: 6.883

6.  SARS-CoV-2 Viral Load in Upper Respiratory Specimens of Infected Patients.

Authors:  Lirong Zou; Feng Ruan; Mingxing Huang; Lijun Liang; Huitao Huang; Zhongsi Hong; Jianxiang Yu; Min Kang; Yingchao Song; Jinyu Xia; Qianfang Guo; Tie Song; Jianfeng He; Hui-Ling Yen; Malik Peiris; Jie Wu
Journal:  N Engl J Med       Date:  2020-02-19       Impact factor: 91.245

7.  Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing, China.

Authors:  Zhiliang Hu; Ci Song; Chuanjun Xu; Guangfu Jin; Yaling Chen; Xin Xu; Hongxia Ma; Wei Chen; Yuan Lin; Yishan Zheng; Jianming Wang; Zhibin Hu; Yongxiang Yi; Hongbing Shen
Journal:  Sci China Life Sci       Date:  2020-03-04       Impact factor: 10.372

8.  Clinical and virological data of the first cases of COVID-19 in Europe: a case series.

Authors:  Francois-Xavier Lescure; Lila Bouadma; Duc Nguyen; Marion Parisey; Paul-Henri Wicky; Sylvie Behillil; Alexandre Gaymard; Maude Bouscambert-Duchamp; Flora Donati; Quentin Le Hingrat; Vincent Enouf; Nadhira Houhou-Fidouh; Martine Valette; Alexandra Mailles; Jean-Christophe Lucet; France Mentre; Xavier Duval; Diane Descamps; Denis Malvy; Jean-François Timsit; Bruno Lina; Sylvie van-der-Werf; Yazdan Yazdanpanah
Journal:  Lancet Infect Dis       Date:  2020-03-27       Impact factor: 25.071

9.  Clinical features and dynamics of viral load in imported and non-imported patients with COVID-19.

Authors:  Tianmin Xu; Cong Chen; Zhen Zhu; Manman Cui; Chunhua Chen; Hong Dai; Yuan Xue
Journal:  Int J Infect Dis       Date:  2020-03-14       Impact factor: 3.623

10.  Prolonged presence of SARS-CoV-2 viral RNA in faecal samples.

Authors:  Yongjian Wu; Cheng Guo; Lantian Tang; Zhongsi Hong; Jianhui Zhou; Xin Dong; Huan Yin; Qiang Xiao; Yanping Tang; Xiujuan Qu; Liangjian Kuang; Xiaomin Fang; Nischay Mishra; Jiahai Lu; Hong Shan; Guanmin Jiang; Xi Huang
Journal:  Lancet Gastroenterol Hepatol       Date:  2020-03-20
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  49 in total

Review 1.  Return to Activity After SARS-CoV-2 Infection: Cardiac Clearance for Children and Adolescents.

Authors:  Devyani Chowdhury; Michael A Fremed; Peter Dean; Julie S Glickstein; Jeff Robinson; Neil Rellosa; Deepika Thacker; David Soma; Susannah M Briskin; Chad Asplund; Jonathan Johnson; Christopher Snyder
Journal:  Sports Health       Date:  2021-08-24       Impact factor: 4.355

2.  Comparison of Home Antigen Testing With RT-PCR and Viral Culture During the Course of SARS-CoV-2 Infection.

Authors:  Victoria T Chu; Noah G Schwartz; Marisa A P Donnelly; Meagan R Chuey; Raymond Soto; Anna R Yousaf; Emily N Schmitt-Matzen; Sadia Sleweon; Jasmine Ruffin; Natalie Thornburg; Jennifer L Harcourt; Azaibi Tamin; Gimin Kim; Jennifer M Folster; Laura J Hughes; Suxiang Tong; Ginger Stringer; Bernadette A Albanese; Sarah E Totten; Meghan M Hudziec; Shannon R Matzinger; Elizabeth A Dietrich; Sarah W Sheldon; Sarah Stous; Eric C McDonald; Brett Austin; Mark E Beatty; J Erin Staples; Marie E Killerby; Christopher H Hsu; Jacqueline E Tate; Hannah L Kirking; Almea Matanock
Journal:  JAMA Intern Med       Date:  2022-07-01       Impact factor: 44.409

3.  SARS-CoV-2 RNA and antibody dynamics in a Dutch household study with dense sampling frame.

Authors:  Wanda G H Han; Arno Swart; Axel Bonačić Marinović; Dirk Eggink; Johan Reimerink; Lisa A Wijsman; Bas van der Veer; Sharon van den Brink; Anne-Marie van den Brandt; Sophie van Tol; Gert-Jan Godeke; Fion Brouwer; Marieke Hoogerwerf; Daphne F M Reukers; Nynke Rots; Chantal Reusken; Adam Meijer
Journal:  Sci Rep       Date:  2022-05-13       Impact factor: 4.996

Review 4.  Tools and Techniques for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)/COVID-19 Detection.

Authors:  Seyed Hamid Safiabadi Tali; Jason J LeBlanc; Zubi Sadiq; Oyejide Damilola Oyewunmi; Carolina Camargo; Bahareh Nikpour; Narges Armanfard; Selena M Sagan; Sana Jahanshahi-Anbuhi
Journal:  Clin Microbiol Rev       Date:  2021-05-12       Impact factor: 26.132

5.  A simplified alternative diagnostic algorithm for SARS-CoV-2 suspected symptomatic patients and confirmed close contacts (asymptomatic): A consensus of Latin American experts.

Authors:  Fabian F Fay; Carlos Arturo Alvarez-Moreno; Pablo E Bonvehi; Carolina Cucho Espinoza; Marco Luis Herrera Hidalgo; Marcel Marcano-Lozada; Carlos M Perez; Alvaro Pulchinelli; Klever Vinicio Sáenz-Flor; Antonio Condino-Neto
Journal:  Int J Infect Dis       Date:  2021-05-20       Impact factor: 12.074

6.  Incidence of SARS-CoV-2 infection according to baseline antibody status in staff and residents of 100 long-term care facilities (VIVALDI): a prospective cohort study.

Authors:  Maria Krutikov; Tom Palmer; Gokhan Tut; Chris Fuller; Madhumita Shrotri; Haydn Williams; Daniel Davies; Aidan Irwin-Singer; James Robson; Andrew Hayward; Paul Moss; Andrew Copas; Laura Shallcross
Journal:  Lancet Healthy Longev       Date:  2021-06-03

7.  Concordance of Upper and Lower Respiratory Tract Samples for SARS-CoV-2 in Pediatric Patients: Research Letter.

Authors:  Elaina E Lin; Elikplim H Akaho; Anna Sobilo; Allison M Blatz; William R Otto; Audrey R Odom John
Journal:  Anesthesiology       Date:  2021-06-01       Impact factor: 8.986

8.  Household transmission of SARS-CoV-2 from unvaccinated asymptomatic and symptomatic household members with confirmed SARS-CoV-2 infection: an antibody-surveillance study.

Authors:  Maala Bhatt; Amy C Plint; Ken Tang; Richard Malley; Anne Pham Huy; Candice McGahern; Jennifer Dawson; Martin Pelchat; Lauren Dawson; Terry Varshney; Corey Arnold; Yannick Galipeau; Michael Austin; Nisha Thampi; Fuad Alnaji; Marc-André Langlois; Roger L Zemek
Journal:  CMAJ Open       Date:  2022-04-12

9.  Distinct clinical and immunological profiles of patients with evidence of SARS-CoV-2 infection in sub-Saharan Africa.

Authors:  Ben Morton; Kayla G Barnes; Jennifer Cornick; Kondwani C Jambo; Catherine Anscombe; Khuzwayo Jere; Prisca Matambo; Jonathan Mandolo; Raphael Kamng'ona; Comfort Brown; James Nyirenda; Tamara Phiri; Ndaziona P Banda; Charlotte Van Der Veer; Kwazizira S Mndolo; Kelvin Mponda; Jamie Rylance; Chimota Phiri; Jane Mallewa; Mulinda Nyirenda; Grace Katha; Paul Kambiya; James Jafali; Henry C Mwandumba; Stephen B Gordon
Journal:  Nat Commun       Date:  2021-06-11       Impact factor: 14.919

10.  SARS-CoV-2 Subgenomic RNA Kinetics in Longitudinal Clinical Samples.

Authors:  Renu Verma; Eugene Kim; Giovanny Joel Martínez-Colón; Prasanna Jagannathan; Arjun Rustagi; Julie Parsonnet; Hector Bonilla; Chaitan Khosla; Marisa Holubar; Aruna Subramanian; Upinder Singh; Yvonne Maldonado; Catherine A Blish; Jason R Andrews
Journal:  Open Forum Infect Dis       Date:  2021-06-11       Impact factor: 4.423

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