Epidemiological approximation of the enteric manifestation and possible fecal–oral transmission in COVID-19: a preliminary systematic review : European Journal of Gastroenterology & Hepatology

Secondary Logo

Journal Logo
Advanced Search
Reviews

Epidemiological approximation of the enteric manifestation and possible fecal–oral transmission in COVID-19: a preliminary systematic review

Pamplona, Javiera; Solano, Rubénb; Soler, Cristinac; Sabat, Miriama

Author Information

aGastroenterology Service, Santa Caterina Hospital, Girona

bEpidemiology Office, Barcelona

cInternal Medicine Service, Santa Caterina Hospital, Girona, Spain

Received 15 June 2020 Accepted 17 August 2020

Correspondence to Rubén Solano, PhD, Barcelona, Epidemiology Office, Sant Crispi 22, 08870 Barcelona, Spain, Tel: +34 636186240; e-mail: [email protected]

European Journal of Gastroenterology & Hepatology 33(12):p e21-e29, December 2021. | DOI: 10.1097/MEG.0000000000001934
  • Free

Abstract

The recent appearance of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection has led to the publication of the first evidence on gastrointestinal symptoms (GIS), the possible enteric involvement of the virus and the detection of RNA in stool, with its possible implication in the fecal–oral transmission of coronavirus disease 2019 (COVID-19). We aimed to conduct a systematic review to describe the epidemiological scientific evidence on GIS, enteric involvement and fecal excretion of SARS-CoV-2 viral RNA and to discuss the possible fecal–oral transmission pathway of COVID-19.

Introduction

In early December 2019, a set of cases of pneumonia of an unknown cause was identified in Wuhan (China) [1,2]. China notified the WHO office on 31 December 2019. On 7 January 2020, the Chinese Health Authorities confirmed the identification of a novel betacoronavirus [severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)] from the same family that caused SARS or Middle East respiratory syndrome (MERS). On 30 January 2020, the Director-General of the WHO declared a public health emergency of international concern. On 11 March 2020, the WHO made an address that declared the outbreak caused by the novel betacoronavirus 2 (2019-nCoV) a pandemic [3,4].

There is evidence of the similarity of SARS-CoV-2 with the genetic sequences of different coronaviruses (CoVs) present in at least five species of bats, according to surveillance studies conducted [5,6]. At least three of these species were found in Wuhan, Hubei province, in the center of the People’s Republic of China [7], but the bat CoV with which SARS-CoV-2 has the greatest genomic similarity was isolated from Rhinolophus sinicus (genetic sequence MG772933), described in ref. [8], which could indicate that this species could also have been the original source of SARS-CoV-2 and probably reached humans after passing from an intermediate host, the civet Paguma larvata or the pangolin Manis pentadactyla [9,10]. Although said genetic similarity has been studied, the epidemiological link must be proven [11]. The way in which the virus could be transmitted from the animal source to the first human cases is unknown.

As of 22 April 2020, when this article was written, the virus had spread, according to cases reported, to 215 countries, territories or reporting areas around the world, as reflected in the WHO SARS-CoV-2 disease (COVID-19) Situation Report-98 published on 27 April 2020. More than 2 878 196 cases and at least 198 668 deaths have been confirmed [12].

It is important to note that the basic reproduction number (R0), the indicator of transmissibility of SARS-CoV-2, has been estimated at 2.30 from reservoir to person and that person-to-person transmission was 3.58 [13]. Two reviews recorded a total of 32 studies of different methodologies estimating R0 values ranging from 1.5 to 6.5 during the epidemic in Wuhan [14].

In the absence of specific clinical manifestations, the identification of transmission chains and follow-up of subsequent contacts would be much more complicated, especially if many infected individuals remain asymptomatic, presymptomatic or mildly symptomatic carriers [15].

The clinical manifestations such as dry cough, fever and dyspnea are well known and described. In the first series in Wuhan, 2–10% of patients with COVID-19 had GIS such as diarrhea, abdominal pain and vomiting [16,17]. Gastrointestinal infection is possible, and the mechanism for SARS-CoV infection in the gastrointestinal tract is already known to be the cellular receptor of angiotensin-converting enzyme 2 (ACE2) [18].

To date, several studies have been published that refer to the viral excretion of SARS-CoV-2 in stool and investigate whether fecal SARS-CoV-2 RNA levels correlate with disease severity and the presence or absence of GIS, and, on the other hand, analyzing whether SARS-CoV-2 RNA in stool can also be detected in the incubation or convalescent phases of COVID-19 [19], which could imply possible fecal–oral transmission.

The identification of the main routes of transmission of SARS-CoV-2 infection should be a priority in health research, as it may make it possible to define preventive strategies to further reduce its burden of morbidity and mortality. Since different occupations, migratory and mobility activities of communities and populations may represent different pathways for acquiring infection. Our aim was through a systematic review of the literature to know the frequency of GIS and describe the fecal excretion of SARS-CoV-2 in patients with COVID19, which could imply possible fecal–oral transmission.

Methods

Search strategy and inclusion criteria

We conducted a systematic search of electronic medical databases (PubMed, Embase and Google Scholar) from 31 January until 12 April 2020 (date of last search) to retrieve published scientific articles assessing or making references to the GIS, gastrointestinal infection, detection of viral RNA in stool and possible enteric or fecal–oral transmission of the SARS-CoV-2 during the COVID-19 global pandemic. The exact query terms used in the database research were: ‘coronavirus’ OR ‘coronavirus’ AND ‘feces’ OR ‘feces’ OR ‘stool’ AND ‘SARS-CoV-2 transmission’ OR ‘transmission’ AND ‘COVID-19’ OR ‘severe acute respiratory syndrome coronavirus 2’ OR ‘severe acute respiratory syndrome coronavirus 2’ OR ‘2019-nCoV’ OR ‘SARS-CoV-2’ OR ‘2019nCoV’ OR ‘Wuhan’ AND ‘coronavirus’ OR ‘coronavirus’ AND ‘fecal-oral covid-19’ OR ‘gastrointestinal evidence AND covid-19 transmission’ OR ‘intestinal participation in covid-19 transmission’ OR ‘sars-cov-2 AND population transmission’ OR ‘SARS-CoV-2 AND viral RNA concentrations in stool biological samples’ OR ‘stool test AND for determination of SARS-CoV-2’. Each reference retrieved was independently examined, following predefined criteria for determining eligibility for the systematic review (Fig. 1).

F1
Fig. 1.:
Four-level flowchart of studies on epidemiological scientific evidence on the possible fecal–oral transmission pathway of SARS-CoV-2 infection (COVID-19). COVID-19, coronavirus disease 2019; SARS-CoV, severe acute respiratory syndrome coronavirus-2.

Inclusion and exclusion criteria

Eligibility criteria included original and editorial articles, comments, letters to the editor, guidelines and case reports in which original results were presented. Research not involving humans (for example, in-vitro or animal research; experimental studies with an evaluation of SARS-CoV-2 infection in gastrointestinal biological samples recovered from laboratory databases) was included. Eligible study designs included randomized, cohort, case-control, cross-sectional, ecological studies and modeling studies.

Exclusion criteria were: documents written in a language other than English, Portuguese, Spanish, French, Italian; previous systematic reviews were not eligible; studies that do not assess or provide the prevalence of GIS in confirmed cases of COVID-19 or studies than not provide information about the isolation or proteins detection of SARS-CoV-2 from stool samples.

Study selection and data extraction

Decisions were made independently by two reviewers using the search strategy for eligible studies, which were compared, and discrepancies were resolved by consensus or consultation after discussion with another independent investigator. The retrieved study references were stored in an electronic bibliographic data repository to identify additional relevant publications that were missed in the initial search strategy.

For the extraction of data from the selected articles, a predesigned data collection form was prepared to extract relevant information from the full texts, including the study design, year of publication and the period of data collection.

Quality assessment

The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement was used as an instrument for the critical reading and evaluation of cross-sectional epidemiological studies and case series, and those with a focus on prevalence (cohort, case-control and cross-sectional), according to a 22-point checklist related to the different sections of an article: title, summary, introduction, methodology, results and discussion. Of these, 18 points are common to the three study designs: cohort, case-control and cross-sectional; the other four are specific to cohort, case-control or cross-sectional studies [20,21]. The quality of the study was considered HIGH (H) if most summary statements were answered as ‘excellent’ or ‘good’; MEDIUM (M) if internal validity was rated as ‘MEDIUM’, or most summary statements were rated as ‘good’ or ‘fair’; and LOW (L) if internal validity was rated as ‘LOW’, or most summary statements were rated as ‘fair’ or ‘poor’ [22].

Statistical methods

Considering the heterogeneity in the studies identified through the systematic review and the options for presenting the results in each article, quantitative synthesis of the main findings could not be made. We performed a simple pooled analysis to estimate the frequency of GIS as if all COVID-19 patients were from the same study. The data were combined without being weighted.

Results

Study characteristics

In total, we identified 350 references addressing potentially relevant descriptors of the review (Fig. 1). Of these, 33 (9,4%) articles met our eligibility criteria and were therefore included in the analysis (Table 1). All articles selected according to the review objective were published in 2020 due to the recent emergence of the COVID-19 pandemic, and data collection or surveillance periods of these studies took place between December 2019 and 24 March 2020, mainly in the following regions: Asia (88.8%), Europe (12.1%) and the Americas (9.1%). Studies spanned a wide age range, from pediatric subjects 1 day to 92 years of age, in those studies in which information was provided, including experimental studies. Most studies analyzed were observational 24/33 (72.7%), 8/33 (24.2%) cohort and 1/33 (3%) case-control studies. According to the external quality assessment of the studies, 17/33 (51.5%) had medium quality and 14/33 (42.4%) were of high quality, according to STROBE (Table 1).

Table 1. - Demographic characteristics and comparison of quality of the studies included in the review
Primary author/year of publication Country/region Sex n (%) (M: male; F: female) Age (months; years) Monitoring period Design STROBE
Zhang W et al. (2020) [23] Wuhan, China/Asia NK NK 12 December 2019– 3 February 2020 Descriptive Medium
Kim JY et al. (2020) [24] South Korea/Asia Patient 1: Chinese F (primary case) 35–55 years December 2019–February 2020 Descriptive Medium
Patient 2: Korean M
Xu Y et al. (2020) [25] Guangzhou, China/Asia 6/10 (60) M Pediatric 22 January–20 February 2020 Prospective observational, 1 site High
4/10 (40) F
Nicastri E et al. (2020) [26] Rome, Italy/Europe Asymptomatic Italian M1 from Wuhan 20 years 3–22 February 2020 Descriptive, one case Medium
Sun D et al. (2020) [27] Wuhan, Hubei, China/Asia 6 M R: 2 months–15 years 24 January–24 February 2020 Description of a case series Medium
2 F
Lo IL et al. (2020) [28] Macau, China/Asia 3/10 (30) M x̄: 54 years 21 January–16 February 2020 Descriptive Medium
7/10 (70) F R: 27-64 years
Ma X et al. (2020) [29] Shandong, China/Asia Children 6/8 (75) R: 11 months–39 years NK Descriptive Medium
Adults 2/8 (25)
Xiao F et al. (2020) [30] Guangdong, China/Asia NK NK 1–14 February 2020 Descriptive High
Holshue ML et al.(2020) [31] Washington, USA/America 1 M returning from Wuhan on 15 January 35 years 19–20 January 2020 Descriptive 1 case Medium
Kim ES et al. (2020) [32] Seoul, South Korea/Asia 15/28 (53.6) M x̄: 40 years 19 January–17 February 2020 Cohort High
13/28 (46.4) F R: 20–73 years
Wang D et al. (2020) [17] Wuhan, China/Asia 75/138 (54.3) M x̄: 56 years 1 January–3 February 2020 Retrospective cohort High
63/138 (45.7) F R: 22–92 years
Phan LT et al. (2020) [33] Wuhan, China/Asia 2 M (father and child) 65 years (primary case) 17–20 Jan Cohort (3-family member cluster) High
1 F 27 years (secondary case)
Mother NK
Park JY et al. (2020) [34] Seoul, South Korea/Asia 1/5 Girl, contact with mother and uncle z(traveled to Wuhan) confirmed Girl 10 years 29 January–18 February 2020 Description of a case, NK for the cluster Medium
Hsih WH et al. (2020) [35] Taichung, Taiwan/Asia 17 (40) M x̄: 34.0 years 20 January–19 February 2020 Cohort High
26 (60) F R: 3–68 years
Yang X et al. (2020) [36] Wuhan, China/Asia 35 (67) M x̄: 51.9 years 24 December 2019–26 January 2020 Retrospective observational of an outbreak High
17 (33) F
Jin X et al. (2020) [37] Zhejiang, China/Asia 37/74 (50) M x̄: 46.1 ± 14.1 years 17 January 2020–8 February 2020 Retrospective cohort High
37/74 (50) F
Pan L et al. (2020) [38] Hubei, China/Asia 97/204 (47.5) M x̄: 52.9 years (SD ± 16) 18 January–18 March 2020 Multicenter cross-sectional descriptive High
107/204 (52.4) F
Xing YH et al. (2020) [39] Qingdao, Shandong, China/Asia NK Pediatric <10 years 17 January–10 March 2020 Retrospective Descriptive High
R: 1–6 years
Pan Y et al. (2020) [40] Beijing, China/Asia 17 NK NK NK Descriptive Low
Wu Y et al. (2020) [41] Zhuhai, China/Asia NK NK 16 January–15 March 2020 Descriptive Medium
Guan W et al. (2020) [42] China/Asia 58.1 M x̄: 47 years 11 December 2019–31 January 2020 Multicenter cohort High
41.9 F R: 35–58 years
Lu X et al. (2020) [43] Wuhan, China/Asia 104/171 (60.8) M Pediatric <10 years 28 January–26 February 2020 Cross-sectional descriptive Medium
67/171 (39.2) F x̄: 6.7 years
R: 1 day–15 years
Zhang JJ et al. (2020) [44] Wuhan, China/Asia 71/140 (50.7) M x̄: 57 years 16 January–3 February 2020 Retrospective cohort High
69/140 (49.3) F
Liu K et al. (2020) [45] Hubei, Wuhan, China/Asia 61/137 (44.5) M x̄: 57 years 30 December 2019–24 January 2020 Retrospective cross-sectional descriptive Medium
76/137 (55.5) F R: 20–83 years
Nobel YR et al. (2020) [46] New York-Presbyterian-Columbia, USA/America 145/278 (52) M R: 18 years- >70 years 10 March–21 March 2020 Case-controls High
133/272 (48) F
Cholankeril G et al. (2020) [47] California, USA/America 62 (53.4) M x̄: 50 years 4–24 March 2020 Retrospective cross-sectional descriptive Medium
R: 35–67 years
Luo S et al. (2020) [48] Wuhan, China/Asia 102/183 (56) M x̄: 53.8 years 1 January–20 February 2020 Retrospective cross-sectional descriptive Medium
81/183 (44) F
Lescure FX et al. (2020) [49] Paris, France/Europe 3/5 (60) M R: 30–80 years 24 January–19 February 2020 Cohort High
2/5 (40) F
Huang C et al. (2020) [3] Wuhan, China/Asia 30/41 (73) M x̄: 49 years
R: 41–58 years		 31 December 2019–2 January 2020 Cross-sectional descriptive Medium
11/41 (27) F
Chen N et al. (2020) [16] Huanan, China/Asia 67/99 (67.8) M 55.5 years (SD: ± 13.1) 1–25 January 2020 Retrospective cross-sectional descriptive Medium
32/99 (32.3) F
Young BE et al. (2020) [50] Singapore/Asia 9/18 (50) M x̄: 47 years 23 January–3 February 2020 Descriptive of an outbreak Medium
9/18 (50) F
Xu XW et al. (2020) [51] Zhejiang, China/Asia (35, 5) M x̄: 41 10–26 January 2020 Descriptive Low
R: 32–52 years
Wölfel R et al. (2020) [52] Munich, Germany/Europe NK NK 23–27 January 2020 Descriptive of a cluster Medium
Age=may be the mean/median (x̄) and range (R) of ages, NK=data not reflected or is not known; STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist guidelines (observational and descriptive cross-sectional studies), H= high; M= medium; L= low.

General characteristics of the included studies

Due to the novelty in the occurrence of the COVID-19 pandemic, no broad geographical distribution was observed in the studies reviewed, and we included 2/33 (6%) types of articles sent to journals as correspondence articles, letter to the editor or brief review, as they provided data from an original study. Table 1 shows the list of studies according to the inclusion criteria and descriptors used.

The PubMed bibliographic repository was the most widely used for retrieval through open access to available articles. The articles identified were mainly designed as cross-sectional descriptive studies and some observational studies (cohort, cases and controls) with a retrospective or longitudinal design. One case-control study was found, and no ecological or modeling studies or RCT studies were found (Table 1).

As regards sex and age, as another of the sociodemographic variables collected in the different studies included, we found the distribution by sex to be relatively homogeneous in the different studies, with global average distribution of 53.1% male and 46.9% female and varied in a range from pediatric patients of 1 day to adult patients of 92 years of age.

Prevalence of gastrointestinal symptoms in COVID-19

Table 2 shows the presence of GIS, which generally showed great variability between 2 and 100% of all articles reviewed. It also depended on the sample size, which ranged from 1 to 1141 patients included in the different studies. In these studies, the GIS were related to the presence of diarrhea between 1 and 80%, nausea and vomiting between 3.6 and 50% and abdominal pain between 1.9 and 33.3%. According to our pooled analysis, 16.1% presented GIS, 8.3% diarrhea, 12% nausea-vomiting and 4% abdominal pain.

Table 2. - Gastrointestinal symptoms and enteric involvement according to studies included in the review
Primary author/year of publication Sample (N) GIS frequency (%) Diarrhea n (%) Nausea/vomiting n (%) Abdominal pain n (%) Several GIS or other n (%) Positive gastrointestinal Samples
Kim JY et al. (2020) [24] 2 2/2 (100) NK NK NK NK SSa
Xu Y et al. (2020) [25] 10 3/10 (30) 3/10 (30) NK NK NK SSa
Nicastri E et al. (2020) [26] 56 1/56 (1.7) NK NK NK NK SSa
Sun D et al. (2020) [27] 8 8/8 (100) 3/8 (37.5) NK NK 5/8 (62.5) NKa
Lo IL et al. (2020) [28] 10 10/10 (100) 8/10 (80) 5/10 (50) NK NK SSa
Ma X et al. (2020) [29] 27 8/27 (29.6) NK NK NK NK SSa
Holshue ML et al. (2020) [31] 1 1/1 (100) 1/1 1/1 1/1 NK SSa
Kim ES et al. (2020) [32] 28 5/28 (18) 3/28 (39) 1/28 (3.6) 1/28 (3.6) NK SSa
Wang D et al. 2020 [17] 138 36/138 (26.1) 14/138 (10.1) 14/138 (10.1) 3/138 (2.2) NK NKa
5/138 (3.6)
Phan LT et al. (2020) [33] 28 3/28 (10.7) 1/3 (33.3) 1/3 (33.3) NK NK NKa
Hsih WH et al. (2020) [35] 43 2/43 (4.6) 5/43 (11.6) 3/43 (7) 3/43 (7) NK NKa
Jin X et al. (2020) [37] 651 74/651 (11.4) 53/651 (8.1) 10/651 (1.5) NK 3/74 (4) NKa
11/651(1.6)
Pan L et al. (2020) [38] 204 103/204 (50.5) 35/103 (34) 4/103 (3.9) 2/103 (1.9) 81 (78.6) SSa
Xing YH et al. (2020) [39] 60 3/60 (5) 1/3 (33.3) NK 1/3 (33.3) NK SSa
Wu Y et al. (2020) [41] 74 23/74 (31) NK NK NK NK SSa
Guan W et al. (2020) [42] 1099 96/1099 (8.7) 41/1099 (3.8) 55/1099 (5) NK NK NKa
Lu X et al. (2020) [43] 1391 171/1391 (12.3) 15/171 (8.8) 11/171 (6.4) NK NK NKa
Zhang JJ et al. (2020) [44] 140 55/139 (39.6) 18/139 (12.9) 24/139 (17.3) 8/139 (5.8) NK NKa
Liu K et al. (2020) [45] 137 11/137 (8) 11/137 (8) NK NK NK NKa
Nobel YR et al. (2020) [46] 278 97/278 (34.8) 56/278 (20.1) 63/278 (22.6) NK NK NKa
Cholankeril G et al. (2020) [47] 116 37/116 (31.9) 12/116 (10.3) 12/116 (10.3) NK 5/116 (4.3) NKa
Luo S et al. (2020) [48] 1141 183/1141 (16) 68/1141 (5.9) 134/1141 (11.7) 45/1141 (3.9) 16/1141 (9) NKa
119/1141 (10.4)
Huang C et al. (2020) [3] 41 1/40 (3) 1/40 (3) NK NK NK NKa
Chen N et al. (2020) [16] 99 2/99 (2) 1/99 (1) NK NK NK NKa
Young BE et al. (2020) [50] 18 4/18 (22.2) 3/18 (16.6) 3/18 (16.6) NK NK SSa
Xu XW et al. (2020) [51] 62 3/62 3/62 (4.8) NK NK NK NKa
Wölfel R et al. (2020) [52] 9 2/9 (22.2) 2/9 (22.2) NK NK NK SSa
Frequency of gastrointestinal infection by SARS-CoV-2; gastrointestinal symptomatology or enteric involvement (GIS); gastrointestinal sampling that usually included: stool swab (SS) or histological samples (H).
SARS-CoV, severe acute respiratory syndrome coronavirus-2.
aRespiratory samples could include nasal and pharyngeal swabs, bronchoalveolar lavage fluid, sputum or bronchial aspirates (URT and LRT), other serological samples, but in this review, we focused on studies of intestinal samples. NK, data not reflected or datum not known

SARS-CoV-2 detection in stool samples

The samples used for diagnosis of SARS-CoV-2 infection, in some studies [16,23–25,27–31,37–40,48,51], were stool tests and anal swabs regularly collected from subjects with or without GIS (Tables 2 and 3). A histological study of intestinal biopsies was performed in one study [30]. The test for the detection of SARS-CoV-2 viral RNA in gastrointestinal samples mostly corresponded to reverse transcription polymerase reaction for amplification of the main genes such as frame1ab ORF1ab, RdRp and nucleocapsid proteins (S, E, N) (Table 3).

Table 3. - Fecal excretion of viral RNA of severe acute respiratory syndrome coronavirus-2-2 and the possible fecal–oral transmission pathway based on viral load and intestinal cytology according to the experimental studies included in the review
Primary author/year of publication Laboratory technique (genes tested) VLAS (log10 copies/μL, log10 cop/swab, qPCR Ct values) Positive fecal samples n (%) Positive fecal samples after negativization respiratory samples n (%) Fecal RNA detection range (days) Histology Infer fecal–oral transmission
Zhang W et al. (2020) [23] qRT-PCR by HiScript II One Step qRT-PCR n 1 = 4/15 (27%) n:1 = 4/15 (27) NK NK NK NK
Ct: 30.9–31.2 n:2 Day 0: 5/16 (31)
n 2 = Day 1: 5/16 (31%) Day 5: 6/16 (38)
Day 5: 6/16 (38%)
Ct: 17.8–33.8
Kim JY et al. (2020) [24] rRT-PCR (RdRp/E) 500–700 0/2 (0) NK R: 4–19 NK NK
R: 1/27–1/37 × 105
Ma X et al. (2020) [29] qRT-PCR; (ORF1ab/N) nucleic acid detection kit (Bio-germ, Shangai, China) histological NK NK 8/23 (34,7) R: 1–35 NK Family cluster person-person
Xiao F et al. (2020) [30] qRT-PCR; China Disease Control and prevention-standardized quantitative PCR assay. NK 39/73 (53,4) 17/73 (23,3) R: 3–10 ACE2 stained positive in the cytoplasm of glandular cells of gastric, duodenal, and rectal epithelia Propagation of infected cells to uninfected cells
Duodenal-rectal histology by endoscopy histological staining (H&E) and viral staining of the ACE2 receptor, by confocal laser scanning microscopy (Viral nucleocapsid protein staining)
Staining of viral nucleocapsid in the same cells
R: image 20–100 mm
Park JY et al. (2020) [34] RT-PCR (RdRp/E) NK 1/1 (100) 1/1 (100) R: 5–17 NK Family cluster person-person
Xing YH et al. (2020) [39] RT-PCR (ORFab/N) 3/3 (100) Ct value <40 3/3 (100) 3/3 (100) R: 4–30 NK Fecal–oral
Possible contaminated fomites
Pan Y et al. (2020) [40] rRT-PCR (N) 9/17 (53%) 9/17 (53) NK R: 3–15 NK Family cluster person-person
R: 500–1.21 × 105
Wu Y et al. (2020) [41] rRT-PCR kit from LifeRiver Ltd. (Nucleocapsid gen (N), membrane gen (E) and RNA dependent RNA polymerase gene (RdRp). 41/74 (55%) 41/74 (55) 32/41 (78) after first symptom x̄: 27.9 (SD: ± 10.7) NK Possible fecal–oral
Ct: 28,26 ± 11
R: 8–47
R:0-42
After respiratory negativization
x̄: 11.2 (SD: ± 9.2) R: 0–33
Lescure FX et al. (2020) [49] rRT-PCR (RdRp-IP1/E) 6.8–7.4 × 105 g stool 2/5 (40) NK R: 2–18 NK Family cluster person-person
Wölfel R et al. (2020) [52] rRT-PCR (ORFab/N) virus cellular isolation <106; R: 6.76 × 105–7.11 × 108 8/9 (89) 5/8 (62,5) R: 5–12 NK Family cluster
VLAS, viral load in stool or anal swab: value of viral load detected in stool samples or rectal swabs; R, range of days; M, mean number of days; CS, cytological staining of tissue samples; day of detection: day of infection on which SARS-CoV-2 virus is detected in GI samples; Ct, for viral RNA measurements, some authors used cycle threshold (Ct) values to approximately indicate viral load (inversely related to the Ct value). Significant value for SARS-CoV-2 <40.
ACE2, angiotensin-converting enzyme 2; COVID-19, coronavirus disease 2019; NK, data not reflected or is not known; rRT-PCR, reverse transcription polymerase reaction; SARS-CoV, severe acute respiratory syndrome coronavirus-2.

Six of eight studies detected by RT-PCR antigens of SARS-CoV-2 in the stool or anal swaps with a significative viral load (>1 × 106 cop/µL or threshold cycle t value <40). The frequency ranged from 27 to 100% of samples [3,24,35,40–42]. One study not detected significative viral load in two patients [52] and the other only offers qualitative results [30].

The presence of gastrointestinal symptoms (GIS) was not associated with fecal sample viral RNA positivity (P = 0·45) [41].

Six studies detected positive fecal specimen after negativization in respiratory samples [24,29,30,34,39,41]. The frequency ranged from 23.3 (29) to 78% [41]. Notably, one patient had positive fecal samples for 33 days after the respiratory samples became negative, and another was positive for 47 days after the first symptom onset [41].

Histological samples from the stomach, small intestine and colon were screened for the detection and localization of ACE2 receptor cells, and the nucleocapsid of the coronavirus in 1/71 (1.4%) patients, using staining techniques in 2/33 (6%) articles showing abundant ACE2 in the cytoplasm of glandular cells of gastric, duodenal and rectal epithelia (Table 3). The viral nucleocapsid protein of SARS-CoV-2 was visualized in the cytoplasm of gastric, duodenal and rectum glandular epithelial cells of one patient [30].

Discussion

COVID-19 gastrointestinal symptoms

During the 2002 SARS epidemic, diarrhea was reported in 16.7% of cases [53]. In the MERS epidemic, 26% of cases were reported with diarrhea, 21% with nausea-vomiting and 17% with abdominal pain [54].

In the first studies published on COVID-19, conducted in hospital centers in Wuhan (epicenter of the pandemic), nausea or vomiting was observed in 5% and diarrhea in 3.7% of the cases studied [3,17].

Subsequently, many studies have analyzed the occurrence of GIS, showing great variability coinciding with the pooled analysis. Our analysis showed GIS in 16%, diarrhea in 8.1%, nausea-vomiting in 12% and abdominal pain in 4%.

It is well known that the dominant clinical signs of COVID-19 are respiratory symptoms (cough, dyspnea and fever), but, as has been seen in this review, there is a significant percentage of cases with GIS from the time of patient admission (before starting treatment) and that, sometimes, may precede the respiratory symptoms [17,31]. One study showed that up to 3% of cases may have exclusively presented with GIS [38]. The presence of these GIS has not been related to the positivity of viral RNA in stool [41].

On the other hand, studies are showing that the presence of GIS may indicate a higher probability of a severe course [37,42]. A higher percentage of diarrhea was observed in patients with severe disease (5.8%) than in nonsevere disease (3.5%). Guan et al. [42] and a significant serious course was found in patients with GIS (22.97%) than in those without GIS (8.12%) P < 0.001 [36]. In another study, differences in GIS prevalence between nonsevere disease (37.8%) and severe disease (42%) were not found P = 0.610 [44].

Enteric involvement

The finding of an ACE receptor as the entry for SARS-CoV-2 to the cell suggests that human organs with a high level of ACE2 expressions, such as pulmonary alveolar epithelial cells and small intestinal enterocytes, are potentially vulnerable and a target for SARS-CoV-2 infection [29,30,55,56].

The binding of SARS-CoV-2 to ACE2 has been shown to have approximately 10–20 times greater affinity than SARS-CoV via S protein, which may provide an explanation of why SARS-CoV-2 has more person-to-person spread compared with SARS-CoV [57,58]. COVID-19 disease can affect, in addition to the respiratory and gastrointestinal tract, various organs such as the kidneys, liver, musculoskeletal, cardiovascular and neurological systems [59,60].

In this review, we found [28,29] articles supporting the above statement that human ACE2 is a receptor for SARS-CoV-2 expressed in gastric, intestinal and colonic cells [61,62].

The possible infection of the gastrointestinal cells was studied in tissue samples from the esophagus, stomach, duodenum and rectum, and although no significant histological alteration was observed, through staining, the presence in the cytoplasm of the cells of the ACE2 receptors and the nucleocapsid of the SARS-CoV-2 was determined. This indicates the possibility of enteric infection [30]. This enteric infection could release virions and cause possible fecal–oral transmission.

Other reports have suggested that if SARS-CoV-2 can actually infect the human intestinal epithelia, it would have significant implications for fecal–oral transmission and the containment of viral propagation [17,42].

Infection of intestinal cells can be expressed with GIS, such as abdominal pain, vomiting and diarrhea, as demonstrated in some studies [32,63].

One study showed that the extension in days of viral RNA elimination in stools had not been related to disease severity [41].

This reinforces the need for future studies on enteric participation and viral excretion of SARS-CoV-2 in stool and for research on whether fecal SARS-CoV-2 RNA levels correlate with disease severity and the presence or absence of GIS [19].

Fecal levels of SARS-CoV-2 viral RNA and possible fecal–oral transmission of infection

The primary transmission pathway is by inhalation of respiratory microdroplets, but there may be other mechanisms such as: conjunctival, one study showed the presence of RNA in conjunctiva [64]; fecal, another study in Singapore showed the presence of virus RNA in samples from an infected patient’s toilet [65] and on fomites, the same study detected the virus on many surfaces of the room [65].

In this regard, it has been postulated that the dynamics of SARS-CoV-2 must be determined to study possible fecal transmission, and it is, therefore, important to take simultaneous respiratory and fecal samples to study the kinetics and viral load of SARS-CoV-2. The cycle threshold (Ct) values for viral RNA measurements reflect, in an inversely related manner, the viral load and are suggested by some authors for expression [25,66].

Viral kinetics in infected patients have not yet been fully determined. Viral RNA in COVID-19 has been found in stool in the early and late phases of the disease at a rate, in the most numerous series, of between one-third and one-half of the cases [23,40,41]. Viral RNA may remain positive in stool samples, up to an average of 11.2 days and up to a maximum of 33 days after being negative in respiratory samples, suggesting that the virus could actively replicate in the gastrointestinal tract of the infected patient and that fecal–oral transmission could occur after viral clearance in the respiratory tract [40,41].

One German study found high viral loads in stool and the presence of subgenomic RNA in some patients, indicating the possible viability of the virus, though it could not be cultured in stool [52].

In contrast, another study found no significant value of viral RNA in stool [37]. A study of the pediatric population showed persistent excretion of SARS-CoV-2 in the stool of children between 8 and 20 days after negativization in respiratory samples. This would increase the possibility of the virus being transmitted through contaminated fomites, so there is a need for massive efforts at all levels to prevent the spread of infection between children after reopening daycare centers and schools, as noted in one of the articles discussed in this review [39].

It has been suggested that the prolonged RNA presence of SARS-CoV-2 after negativization in respiratory specimens may be an infectious source of COVID-19 in the community and may represent a threat to public health if eligibility for discharge is based on the current version of the COVID-19 diagnosis and treatment plan [39,67]. Therefore, SARS-CoV-2 RT-PCR measurement in stool would be recommended following the clearance of viral RNA in respiratory specimens from hospitalized or quarantined patients [39,41].

High viral load in elderly patients has been associated not only with the low immunity of the elderly but also with high expression of the ACE2 receptor (the cellular entry receptor for SARS-CoV-2) in older adults, and further studies with a larger sample size are needed to clarify and understand the relationship between viral load and disease severity [68,69].

In histological studies, some authors have suggested that if SARS-CoV-2 can actually infect the human intestinal epithelium, it would have significant implications for fecal–oral transmission and the containment of viral propagation [17,42].

It has also been suggested that further studies are needed to elucidate the exact role of fecal–oral transmission in the spread of SARS-CoV-2 through environmental studies, and studies on viability and infectivity [19,70].

Strengths and limitations

To our knowledge, this is the first systematic review on the prevalence of GIS and enteric involvement of COVID-19 infection, and also includes studies on the excretion and concentration of SARS-CoV-2 virus in biological gastrointestinal samples and on the possibility of fecal–oral transmission of COVID-19. This is possibly the first study conducted in Spain, where the pandemic is having a severe impact. Several electronic databases were searched for our systematic review, the vast majority of references were retrieved, and a large number of studies related to the subject matter at hand were included. Furthermore, since the data analysis was essentially descriptive, no significant bias is expected from our methodological option.

However, we found substantial methodological limitations. The heterogeneity between studies and the novelty of the pandemic health event constituted an established limitation of systematic reviews, and, in this case, the majority of studies being conducted at this time are ongoing and have not yet been published. To minimize potential bias, we attempted to select all studies published to date globally, regardless of sample size.

Despite the limitations of the data in the reviewed articles, the estimates reported here show the frequency of the GIS and that the presence of SARS-CoV-2 viral RNA in the stool could represent a significant burden for the probable fecal–oral transmission of the infection. Further work is needed to update the case definition, studying enteric involvement through the design of prospective observational studies using a sample size representative of the population that allows results to be outsourced.

Conclusion

GIS are common in SARS CoV-2 infection at the time of patient admission, sometimes preceding respiratory symptoms, and sometimes represent the only clinical manifestation. The case definition evolves rapidly as knowledge accumulates, and the definition could be revised, including these considerations. The presence of GIS could predict a poorer course of the disease. In the context of the current pandemic, adequate clinical suspicion may lead to an early diagnosis and treatment of the disease and may hypothetically reduce the frequency of progression to more severe disease.

Infection of the gastrointestinal tract is possible due to the presence of ACE2 receptors, and there may be viral replication with fecal elimination. Studies are required to assess viability and transmissibility. Viral RNA is detected in the stool for a longer time than in the respiratory system. As has been suggested, its detection in fecal samples should be considered as one of the routine diagnostic tests to guide decision making on hospital discharge and the lifting of isolation measures.

It is advisable to design and conduct prospective epidemiological studies at the community level or using a sample size representative of different populations and to substantiate the preliminary findings made in some case studies reported in this systematic literature review. Such studies will make it possible to determine the actual prevalence of GIS and its potential correlation with severity.

Acknowledgements

Conflicts of interest

There are no conflicts of interest.

References

1. WHO. Novel coronavirus (2019-nCoV). Situation Report 11. 31 January 2020. 2020. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200131-sitrep-11-ncov.pdf?sfvrsn=de7c0f7_4. [Accessed 29 March 2020].
2. World Health Organization. Clinical management of severe acute respiratory infection when novel coronavirus (2019-nCoV) infection is suspected: interim guidance. 2020. https://www.who.int/docs/default-source/coronaviruse/clinical-management-of-novel-cov.pdf. [Accessed 25 April 2020].
3. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020; 395:497–506.
4. Word Health Organization. WHO Director-General’s opening remarks at the media briefing on COVID-19. 2020. https://www.who.int/es/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020. [Accessed 25 April 2020].
5. Riccucci M. Bats as materia medica: an ethnomedical review and implications for conservation. Vespertilio 2012; 16:249–270.
6. Tang XC, Zhang JX, Zhang SY, Wang P, Fan XH, Li LF, et al. Prevalence and genetic diversity of coronaviruses in bats from China. J Virol 2006; 80:7481–7490.
7. The International Union for Conservation of Nature’s Red List of Threatened Species. Bat species in Wuhan, Hubei province of the People’s Republic of China. 2020. https://www.iucnredlist.org/. [Accessed 6 July, 2020].
8. Hu D, Zhu C, Ai L, He T, Wang Y, Ye F, et al. Genomic characterization and infectivity of a novel SARS-like coronavirus in Chinese bats. Emerg Microbes Infect 2018; 7:154.
9. Wang LF, Eaton BT. Bats, civets and the emergence of SARS. Curr Top Microbiol Immunol 2007; 315:325–344.
10. Liu P, Chen W, Chen JP. Viral metagenomics revealed sendai virus and coronavirus infection of Malayan pangolins (Manis javanica). Viruses 2019; 11:979
11. Wassenaar TM, Zou Y. 2019_nCoV/SARS-CoV-2: rapid classification of betacoronaviruses and identification of Traditional Chinese Medicine as potential origin of zoonotic coronaviruses. Lett Appl Microbiol 2020; 70:342–348.
12. Word Health Organization. Coronavirus disease (COVID-19) weekly epidemiological update and weekly operational update. 2020. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/. [Accessed 25 April 2020].
13. Chen TM, Rui J, Wang QP, Zhao ZY, Cui JA, Yin L. A mathematical model for simulating the phase-based transmissibility of a novel coronavirus. Infect Dis Poverty 2020; 9:24.
14. Bi Q, Wu Y, Mei S, Ye C, Zou X, Zhang Z, et al. Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study. Lancet Infect Dis 2020; 20:911–919.
15. Munster VJ, Koopmans M, van Doremalen N, van Riel D, de Wit E. A novel coronavirus emerging in china – key questions for impact assessment. N Engl J Med 2020; 382:692–694.
16. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020; 395:507–513.
17. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. J Am Med Assoc 2020; 323:1061–1069.
18. Wan Y, Shang J, Graham R, Baric RS, Li F. Receptor recognition by novel coronavirus from Wuhan: an analysis based on decade-long structural studies of SARS. J Virol 2020; 94:e00127–20.
19. Yeo C, Kaushal S, Yeo D. Enteric involvement of coronaviruses: is faecal-oral transmission of SARS-CoV-2 possible? Lancet Gastroenterol Hepatol 2020; 5:335–337.
20. Fletcher R, Fletcher S. Clinical epidemiology. The Essentials. 2005. 4th ed. Philadelphia, PA: Lippincott Williams and Wilkins; 15 ICJME. Uniform Requirements for Manuscripts Submitted to Biomedical Journals. International Committee of Medical Journal Editors. 2010. http://www.icmje.org. [Accessed 25 April 2020].
21. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Prev Med 2007; 45:247–251.
22. Ciapponi A. Critical reading guide to observational studies in epidemiology. Evidence 2010; 13:135–140.
23. Zhang W, Du RH, Li B, Zheng XS, Yang XL, Hu B, et al. Molecular and serological investigation of 2019-nCoV infected patients: implication of multiple shedding routes. Emerg Microbes Infect 2020; 9:386–389.
24. Kim JY, Ko JH, Kim Y, Kim YJ, Kim JM, Chung YS, et al. Viral load kinetics of SARS-CoV-2 infection in first two patients in Korea. J Korean Med Sci 2020; 35:e86.
25. Xu Y, Li X, Zhu B, Liang H, Fang C, Gong Y, et al. Characteristics of pediatric SARS-CoV-2 infection and potential evidence for persistent fecal viral shedding. Nat Med 2020; 26:502–505.
26. Nicastri E, D’Abramo A, Faggioni G, De Santis R, Mariano A, Lepore L, et al. Coronavirus disease (COVID-19) in a paucisymptomatic patient: epidemiological and clinical challenge in settings with limited community transmission, Italy, February 2020. Euro Surveill 2020; 25:2000230.
27. Sun D, Li H, Lu XX, Xiao H, Ren J, Zhang F-R, Liu Z-S. Clinical features of severe pediatric patients with coronavirus disease 2019 in Wuhan: a single center’s observational study. World J Pediatr 2020;16:251–259.
28. Lo IL, Lio CF, Cheong HH, Lei CI, Cheong TH, Zhong X, et al. Evaluation of SARS-CoV-2 RNA shedding in clinical specimens and clinical characteristics of 10 patients with COVID-19 in Macau. Int J Biol Sci 2020; 16:1698–1707.
29. Ma X, Su L, Zhang Y, et al. Do children need a longer time to shed SARS-CoV-2 in stool than adults? J Microbiol Immunol Infect 2020; 53:373–376.
30. Xiao F, Tang M, Zheng X, et al. Evidence for gastrointestinal infection of SARS-CoV-2. Gastroenterology 2020; 158:1831–1833.e3.
31. Holshue ML, DeBolt C, Lindquist S, Lofy KH, Wiesman J, Bruce H, et al.; Washington State 2019-nCoV Case Investigation Team. First case of 2019 novel coronavirus in the United States. N Engl J Med 2020; 382:929–936.
32. Kim ES, Chin BS, Kang CK, Kim NJ, Kang YM, Choi JP, et al.; Korea National Committee for Clinical Management of COVID-19. Clinical course and outcomes of patients with severe acute respiratory syndrome coronavirus 2 infection: a preliminary report of the first 28 patients from the Korean Cohort Study on COVID-19. J Korean Med Sci 2020; 35:e142.
33. Phan LT, Nguyen TV, Luong QC, Nguyen TV, Nguyen HT, Le HQ, et al. Importation and human-to-human transmission of a novel coronavirus in Vietnam. N Engl J Med 2020; 383:872–874.
34. Park JY, Han MS, Park KU, Kim JY, Choi EH. First pediatric case of coronavirus disease 2019 in Korea. J Korean Med Sci 2020; 35:e124.
35. Hsih WH, Cheng MY, Ho MW, Chou C-H, Lin P-C, Chi C-Y, et al. Featuring COVID-19 cases via screening symptomatic patients with epidemiologic link during flu season in a medical center of central Taiwan. J Microbiol Immunol Infect 2020; 53:459–466.
36. Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med 2020; 8:e26.
37. Jin X, Lian JS, Hu JH, Gao J, Zheng L, Zhang Y-M, et al. Epidemiological, clinical and virological characteristics of 74 cases of coronavirus-infected disease 2019 (COVID-19) with gastrointestinal symptoms. Gut 2020; 69:1002–1009.
38. Pan L, Mu M, Ren HG, Sun Y, Wang R, Yan J, et al. Clinical characteristics of COVID-19 patients with digestive symptoms in Hubei, China: a descriptive, cross-sectional, multicenter study. Am J Gastroenterol 2020; 115:766–773.
39. Xing YH, Ni W, Wu Q, Li W-J, Li G-J, Wang W-D, et al. Prolonged viral shedding in feces of pediatric patients with coronavirus disease 2019. J Microbiol Immunol Infect 2020; 53:473–480.
40. Pan Y, Zhang D, Yang P, et al. Viral load of SARS-CoV-2 in clinical samples. Lancet Infect Dis 2020; 20:411–412.
41. Wu Y, Guo C, Tang L, Hong Z, Zhou J, Dong X, et al. Prolonged presence of SARS-CoV-2 viral RNA in faecal samples. Lancet Gastroenterol Hepatol 2020; 5:434–435.
42. Guan W, Ni Z, Hu Y, et al. Clinical characteristics of 2019 novel coronavirus infection in China. medRxiv 2020; 382:1708–1720.
43. Lu X, Zhang L, Du H, Zhang J, Li YY, Qu J, et al. SARS-CoV-2 infection in children. N Engl J Med 2020; 382:1663–1665.
44. Zhang JJ, Dong X, Cao YY, Yuan Y-D, Yang Y-B, Yan Y-Q, et al. Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China. Allergy 2020; 75:1730–1741.
45. Liu K, Fang YY, Deng Y, Liu W, Wang MF, Ma JP, et al. Clinical characteristics of novel coronavirus cases in tertiary hospitals in Hubei Province. Chin Med J (Engl) 2020; 133:1025–1031.
46. Nobel YR, Phipps M, Zucker J, Lebwohl B, Wang TC, Sobieszczyk ME, Freedberg DE. Gastrointestinal symptoms and COVID-19: case-control study from the United States. Gastroenterology 2020; 159:373–375.e2.
47. Cholankeril G, Podboy A, Aivaliotis VI, Tarlow B, Pham EA, Spencer SP, et al. High prevalence of concurrent gastrointestinal manifestations in patients with SARS-CoV-2: early experience from California. Gastroenterology 2020; 159:775–777.
48. Luo S, Zhang X, Xu H. Don’t overlook digestive symptoms in patients with 2019 novel coronavirus disease (COVID-19). Clin Gastroenterol Hepatol 2020; 18:1636–1637.
49. Lescure FX, Bouadma L, Nguyen D, Parisey M, Wicky P-H, Behillil S, et al. Clinical and virological data of the first cases of COVID-19 in Europe: a case series. Lancet Infect Dis 2020; 20:697–706.
50. Young BE, Ong SWX, Kalimuddin S, Low JG, Tan SY, Loh J, et al. Epidemiologic features and clinical course of patients infected with SARS-CoV-2 in Singapore. JAMA 2020; 323:1488–1494.
51. Xu XW, Wu XX, Jiang XG, Xu KJ, Ying LJ, Ma CL, et al. Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series. BMJ 2020; 368:m792.
52. Wölfel R, Corman VM, Guggemos W, Seilmaier M, Zange S, Müller MA, et al. Virological assessment of hospitalized patients with COVID-2019. Nature 2020; 581:465–469.
53. WHO issues consensus document on the epidemiology of SARS. Wkly Epidemiol Rec 2003; 78:373–380.
54. Assiri A, Al-Tawfiq JA, Al-Rabeeah AA, Al-Rabiah FA, Al-Hajjar S, Al-Barrak A, et al. Epidemiological, demographic, and clinical characteristics of 47 cases of Middle East respiratory syndrome coronavirus disease from Saudi Arabia: a descriptive study. Lancet Infect Dis 2013; 13:373–380
55. Hamming I, Timens W, Bulthuis ML, Lely AT, Navis G, van Goor H. Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus. A first step in understanding SARS pathogenesis. J Pathol 2004; 203:631–637.
56. Donoghue M, Hsieh F, Baronas E, Godbout K, Gosselin M, Stagliano N, et al. A novel angiotensin-converting enzyme-related carboxypeptidase (ACE2) converts angiotensin I to angiotensin 1-9. Circ Res 2000; 87:E1–E9.
57. Wrapp D, Wang N, Corbett KS, Goldsmith JA, Hsieh CL, Abiona O, et al. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. Science 2020; 367:1260–1263.
58. Yang Y, Peng F, Wang R, Yange M, Guan K, Jiang T, et al. The deadly coronaviruses: the 2003 SARS pandemic and the 2020 novel coronavirus epidemic in China. J Autoimmun 2020; 1097:102434
59. Bordi L, Nicastri E, Scorzolini L, Di Caro A, Capobianchi MR, Castilletti C, et al. Differential diagnosis of illness in patients under investigation for the novel coronavirus (SARS-CoV-2), Italy, February 2020. Euro Surveill 2020; 25:2000170.
60. Yi Y, Lagniton PNP, Ye S, Li E, Xu RH. COVID-19: what has been learned and to be learned about the novel coronavirus disease. Int J Biol Sci 2020; 16:1753–1766.
61. Letko M, Marzi A, Munster V. Functional assessment of cell entry and receptor usage for SARS-CoV-2 and other lineage B betacoronaviruses. Nat Microbiol 2020; 5:562–569.
62. Zhou P, Yang XL, Wang XG, et al. Discovery of a novel coronavirus associated with the recent pneumonia outbreak in humans and its potential bat origin. Nature 2020; 579:270–273.
63. Liang W, Feng Z, Rao S, Xiao C, Xue X, Lin Z, et al. Diarrhea may be underestimated: a missing link in 2019 novel coronavirus. Gut 2020; 69:1141–1143.
64. Xu L, Zhang X, Song W, et al. Conjunctival polymerase chain reaction-tests of 2019 novel coronavirus in patients in Shenyang, China. medRxiv 2020. doi: 10.1101/2020.02.23.20024935.
65. Yu P, Zhu J, Zhang Z, Han Y, Huang L. A familial cluster of infection associated with the 2019 novel coronavirus indicating potential person-to-person transmission during the incubation period. J Infect Dis 2020; 395:1757–1761.
66. Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020; 382:727e33.
67. National Health Commission of the People’s Republic of China. Diagnosis and treatment plan of Corona virus disease 2019. 2020. tentative 5th ed. http://www.nhc.gov.cn/yzygj/s7653p/202002/3b09b894ac9b4204a79db5b8912d4440.shtml. [Accessed 25 April 2020].
68. Chen Y, Shan K, Qian W. Asians do not exhibit elevated expression or unique genetic polymorphisms for ACE2, the cell-entry receptor of SARS-CoV-2. 2020. https://www.preprints.org/manuscript/202002.0258/v2. [Accessed 25 March 2020].
69. Chen Y, Li L. SARS-CoV-2: virus dynamics and host response. Lancet Infect Dis 2020; 20:515516.
70. Fung SY, Yuen KS, Ye ZW, Chan CP, Jin DY. A tug-of-war between severe acute respiratory syndrome coronavirus 2 and host antiviral defence: lessons from other pathogenic viruses. Emerg Microbes Infect 2020; 9:558–570.
Keywords:

coronavirus; coronavirus disease 2019; enteric virus; epidemiology; fecal–oral; gastrointestinal; severe acute respiratory syndrome coronavirus-2; systematic review

Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.