The relationship between early isolation and the duration of viral shedding of mild and asymptomatic infection with SARS-CoV-2 Omicron BA.2 variant.

Dear editor

We read with great interest the study by Noh et al. which reported that patients with COVID-19 showed prolonged viral shedding and the asymptomatic patients had potential to spread SARS-CoV-2 without recognition. In past months, the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BA.2 variant has been spreading rapidly in Shanghai, China. Asymptomatic patients and those with mild symptoms accounted for the majority of Omicron BA.2 infections and played an important role in the transmission of COVID. According to the “dynamic zero” COVID policy, the confirmed cases without any symptoms or with mild symptoms were required to be admitted to Fangcang shelter hospitals that were the alternative care sites in Shanghai. This study aimed to evaluate the relationship between early isolation and duration of viral shedding (DVS) of patients without any symptoms or with mild symptoms.

This retrospective, multi-center, observational study was conducted in Shanghai, China. All patients with SARS-CoV-2 Omicron BA.2 variant infection who had no symptoms or mild symptoms were recruited from 3 major Fangcang shelter hospitals between March 26, 2022 and May 20, 2022. Patients with time lag from diagnosis to Fangcang hospital admission (TLDA) >1 week were excluded. TLDA was defined as time (day) from illness onset to being admitted to Fangcang shelter hospitals. The early isolation was defined as TLDA≤3 days, late isolation was defined as TLDA >3 days. Mild and asymptomatic infection with SARS-CoV-2 Omicron variant was defined in supplementary file.

The value of cycle threshold of nucleic acid test higher than 35 was considered as negative result of SARS-CoV-2. Two consecutive negative nucleic acid tests were regarded as the negative viral load. The duration of viral shedding (DVS) was defined as the time from illness onset to the negative viral load.

Linear and logistic regression model was applied to estimate odds ratio (ORs) and 95% confidence intervals (CIs) for the association between the TLDA and DVS. The model was adjusted by underlying diseases (yes or no), age (<18, 18∼59, and ≥60 years old), vaccination status (unvaccinated, partial, full and booster vaccination), and types of vaccine (unvaccinated, inactivated vaccine, adenovirus vector vaccine and protein subunit vaccine). Statistical significance was set at p value <0.05 (two-tailed). All statistical analyses were performed using R software 4.1.0.

199,590 cases were finally included in the study, 152,746 patients (76.53%) were in early isolation groups and 46,844 patients (23.47%) were in late isolation groups. The mean DVS and TLDA were 6.51 ± 3.3 and 1.42 ± 0.97 in early isolation group, and were 9.34 ± 2.87 and 5.07 ± 1.06 in late isolation group (Table 1 ). Table 1 shows the detailed information about the characteristics of study participants. Linear regression model showed that longer TLDA and late isolation were related with longer DVS (OR, 2.25; 95%CI, 2.23–2.26; and OR, 16.79; 95%CI, 16.24–17.35; respectively). Logistic regression model showed that patients with longer TLDA or late isolation were found to have a higher probability of DVS ≥14 days (OR, 1.31; 95%CI, 1.30, 1.33; and OR, 2.58; 95%CI, 2.47, 2.69; respectively) (Table 2 ).

Table 1

The characteristics of study participants.

	Total	From illness onset to being admitted to hospitals
		Early isolation (≤3 days)	Late isolation (>3 days)
Sample size	199,590	152,746	46,844
Sex (male,%)	118,211 (59.23%)	91,007 (59.58%)	27,204 (58.07%)
Mean age (years old, m±sd)	41.44 ± 15.38	41.08 ± 15.29	42.61 ± 15.62
Age group (n,%)
<18 y	10,209 (5.11%)	7439 (4.87%)	2770 (5.91%)
18∼59y	165,569 (82.95%)	127,456 (83.44%)	38,113 (81.36%)
≥60 y	23,812 (11.93%)	17,851 (11.69%)	5961 (12.73%)
Underlying diseases (Yes,%)	13,436 (6.73%)	9735 (6.37%)	3701 (7.90%)
Types of vaccine (n,%)
Unvaccinated	43,998 (22.04%)	34,743 (22.75%)	9255 (19.76%)
Inactivated vaccine	149,530 (74.92%)	113,199 (74.11%)	36,331 (77.56%)
Adenovirus vector vaccine	3960 (1.98%)	3108 (2.04%)	853 (1.82%)
Protein subunit vaccine	2102 (1.05%)	1696 (1.11%)	406 (0.87%)
Vaccination status (n,%)
Unvaccinated	43,998 (22.04%)	34,743 (22.75%)	9255 (19.76%)
Partial	5087 (2.55%)	3895 (2.55%)	1192 (2.55%)
Full (without booster)	64,406 (32.27%)	48,653 (31.85%)	15,753 (33.63%)
Booster	86,099 (43.14%)	65,455 (42.85%)	20,644 (44.07%)
DVS (days, m±sd)*	7.17 ± 3.42	6.51 ± 3.3	9.34 ± 2.87
DVS ≥7 days (n,%)	108,547 (54.38%)	66,973 (43.85%)	41,574 (88.75%)
DVS ≥10 days (n,%)	43,746 (21.92%)	26,190 (17.15%)	17,556 (37.48%)
DVS ≥14 days (n,%)	9009 (4.51%)	5159 (3.38%)	3850 (8.22%)
Days from illness onset to being admitted to hospitals (days, m±sd)	2.27 ± 1.84	1.42 ± 0.97	5.07 ± 1.06
Early isolation (n,%)	152,746 (76.53%)	152,746 (100%)	0

Duration of viral shedding: the time from illness onset to the negative viral load; m±sd: mean± standard deviation.

Table 2

The association between TLDA and DVS.

Outcomes	Crude OR (95%CI)	P	Adjusted OR (95%CI)	P
TLDA (Continuous)
DVS (Continuous)	2.25 (2.23, 2.27)	<0.001	2.25 (2.23, 2.26)	<0.001
DVS ≥7 days	1.82 (1.81, 1.83)	<0.001	1.83 (1.81, 1.84)	<0.001
DVS ≥10 days	1.38 (1.37, 1.39)	<0.001	1.38 (1.38, 1.39)	<0.001
DVS ≥14 days	1.31 (1.30, 1.32)	<0.001	1.31 (1.30, 1.33)	<0.001
TLDA (Categorical, Reference= early isolation)
DVS (Continuous)	16.91 (16.36, 17.48)	<0.001	16.79 (16.24, 17.35)	<0.001
DVS ≥7 days	10.10 (9.80, 10.42)	<0.001	10.18 (9.88, 10.50)	<0.001
DVS ≥10 days	2.90 (2.83, 2.96)	<0.001	2.93 (2.87, 3.00)	<0.001
DVS ≥14 days	2.56 (2.45, 2.67)	<0.001	2.58 (2.47, 2.69)	<0.001

Adjusted: Models were adjusted by underlying diseases (yes or no), age (<18, 18∼59, and ≥60 years old), vaccination status (unvaccinated, partial, full and booster vaccination), and types of vaccine (unvaccinated, inactivated vaccine, adenovirus vector vaccine and protein subunit vaccine).

TLDA: The time lag from diagnosis to isolation (days); DVS: the duration of viral shedding; OR: odds ratio; CIs: confidence intervals; early isolation: the time from diagnosis to isolation ≤3 days.

This is the first study examining the effects of TLDA on DVS in mild and asymptomatic infection with SARS-CoV-2 Omicron BA.2 variant. Our results show that short TLDA or early isolation (≤3 days) were associated with short DVS. Previous studies with small sample size reported that delayed hospital admission were associated with prolonged viral shedding in patients with SARS-CoV-2 pneumonia. , Based on large sample size, this study provides further evidence that early admission and isolation are beneficial to reduce DVS for patients without any symptoms or with mild symptoms. Limitations of the study include the lacking of data for patients who were not admitted to the Fangcang hospital.

Further investigations are needed to explore the mechanism of early isolation in Fangcang hospital contributing to the shorter DVS.

Funding

This study did not receive any funding.

Ethical approval

The study was approved by the ethics committee of the Shanghai Children's Medical Center and conducted according to the Declaration of Helsinki guidelines. The requirement of obtaining informed consent was waived because this study was conducted retrospectively, and all patients’ information was handled anonymously.

Data availability statement

The deidentified individual participant dataset used in this article will be made available with publication upon reasonable request.

Supplementary file

Definition of mild and asymptomatic infection with SARS-CoV-2 Omicron variant

CRediT authorship contribution statement

Yong Yin: Conceptualization, Visualization, Formal analysis, Writing – original draft. Jilei Lin: Conceptualization, Visualization, Formal analysis, Writing – original draft. Shuhua Yuan: Conceptualization, Visualization, Formal analysis, Writing – original draft. Shilu Tong: Supervision, Data curation, Formal analysis, Writing – review & editing. Erzhen Chen: Conceptualization, Visualization, Supervision, Data curation, Writing – review & editing. Junhua Zheng: Conceptualization, Visualization, Supervision, Data curation, Writing – review & editing. Wei Wang: Conceptualization, Visualization, Supervision, Data curation, Writing – review & editing.

Declaration of Competing Interest

There are no conflict of interests