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Article

SARS-CoV-2 Antibody Response against Mild-to-Moderate Breakthrough COVID-19 in Home Isolation Setting in Thailand

1
Siriraj Population Health and Nutrition Research Group, Department of Research Group and Research Network, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
2
Center of Research Excellence on Therapeutic Proteins and Antibody Engineering, Department of Parasitology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
3
Division of Ambulatory Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
4
Division of Infectious Diseases and Tropical Medicine, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
5
Department of Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
6
Division of Ambulatory Paediatrics, Department of Paediatrics, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
7
Department of Anesthesiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Member names are provided in the Acknowledgements.
Vaccines 2022, 10(7), 1131; https://doi.org/10.3390/vaccines10071131
Received: 15 June 2022 / Revised: 11 July 2022 / Accepted: 13 July 2022 / Published: 15 July 2022
(This article belongs to the Special Issue Global Trends of COVID-19 Vaccination and Immunology)

Abstract

:
Background: In December 2021, Omicron replaced Delta as the dominant coronavirus disease 2019 (COVID-19) variant in Thailand. Both variants embody diverse epidemiological trends and immunogenicity. We investigated whether Delta and Omicron patients’ biological and clinical characteristics and immunogenicity differed post-COVID-19 infection. Methods: This retrospective cohort study investigated the clinical outcomes and laboratory data of 5181 patients with mild-to-moderate COVID-19 (Delta, 2704; Omicron, 2477) under home isolation. We evaluated anti-receptor-binding domain immunoglobulin G (anti-RBD IgG) and surrogate viral neutralizing (sVNT) activity in 495 individuals post-COVID-19 infection during the Delta pandemic. Results: Approximately 84% of all patients received favipiravir. The median cycle threshold (Ct) values were lower for Omicron patients than Delta patients (19 vs. 21; p < 0.001), regardless of vaccination status. Upper respiratory tract symptoms were more frequent with Omicron patients than Delta patients. There were no significant associations between Ct and Omicron symptoms (95% confidence interval 0.98–1.02). A two-dose vaccine regimen reduced hospital readmission by 10% to 30% and death by under 1%. Anti-RBD IgG and sVNT against Delta were higher among older individuals post-COVID-19 infection. Older individuals expressed anti-RBD IgG and sVNT for a more extended period after two-dose vaccination than other age groups. Conclusions: After a full vaccination course, breakthrough mild-to-moderate Delta and Omicron infections have limited immunogenicity. Prior infections exert reduced protection against later reinfection or infection from novel variants. However, this protection may be sufficient to prevent hospitalization and death, particularly in countries where vaccine supplies are limited.

Graphical Abstract

1. Introduction

In 2021, Thailand faced multiple rapid waves of coronavirus disease 2019 (COVID-19). Social distancing and vaccines were encouraged as survival tools for people to circumvent the threats [1,2]. CoronaVac (a whole-cell inactivated vaccine, Sinovac, Life Science) and ChAdOx1 (a modified chimpanzee DNA adenovirus-vectored vaccine, AstraZeneca/Oxford) were more widely used than other vaccines by Thais [3]. The CoronaVac vaccine is based on a form of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that has been weakened and safely generates an immune response [4]. The AstraZeneca vaccine is based on the virus’s genetic instructions containing the SARS-CoV-2 structural surface glycoprotein antigen (spike protein; nCoV-19) gene to build the spike protein. The spike protein fragments can then be recognized by the immune system [4,5]. Both vaccines were efficacious against symptomatic COVID-19 caused by the Wuhan strain, but they proved to be less effective against other COVID-19 variants of concern, including Delta and Omicron [6,7]. The vaccine effectiveness is low and wanes faster against infection and mild-to-moderate symptomatic disease but is high against severe disease caused by the Omicron variant. Evidence indicated that the vaccine effectiveness against severe disease outcome after receipt of a primary series with either CoronaVac or AstraZeneca or a booster dose increased to >70% for all vaccines within the first 3 months after a final dose [8]. Omicron displaced Delta as the predominant variant during the study period [1]. Randomly selected SARS-CoV-2 variants captured by surveillance conducted by the Department of Medical Science [6] and worldwide during weeks 4 to 10 of 2022 demonstrated that almost all new infections in Thailand were due to Omicron (99.6%) (Supplementary Figure S1).
Since 2020, the Thai National Treatment Guidelines for COVID-19 from the Ministry of Public Health [9] recommended that favipiravir, a broad-spectrum nucleotide analog targeting the viral RNA-dependent RNA polymerase [10], be the treatment option for patients at increased risk of severe disease and mild severity of pneumonia. It has widely been repurposed to treat mild-to-moderate cases of COVID-19, including Delta and Omicron. In our experiences and in earlier studies, it showed promising results in patients with mild-to-moderate COVID-19 with well-tolerated side effects [11,12]. Remdesivir [13], a monophosphoramidate prodrug of the nucleoside GS-441524, is only recommended for use in severe disease due to limited access. In addition, monipiravir [13], the oral prodrug of beta-D-N4-hydroxycytidine (NHC), and anti-SARS-CoV-2 monoclonal antibodies were not available during the study period.
A combination of waning vaccine-derived immunity and the arrival of the SARS-CoV-2 variants, Delta (B.1.617.2) and Omicron (B.1.1.529), led to breakthrough infections after COVID-19 vaccination or prior infection [7,14]. This greatly overloaded the nation’s public health system and exacerbated socioeconomic disparities [2,15]. In response, home isolation (HI) was implemented for patients with mild-to-moderate symptoms nationwide to combat the overwhelming demand for hospital beds (Supplementary File Method S1).
The Omicron variant caused less severe disease than other variants [16]. Nevertheless, there were serious concerns about its increased transmissibility [17], potential for reduced sensitivity to neutralizing antibodies, and newly emerged lineages (BA.4 and BA.5) [18,19,20]. Very few studies have verified the guidance for vaccination after a mild-to-moderate COVID-19 infection, particularly in countries where the provision of full vaccination courses is challenging [21]. Here, we present the results of our analyses of retrospective information from mildly to moderately symptomatic individuals who were seropositive for SARS-CoV-2. All patients were in the HI system during the Delta and Omicron pandemics. They were treated between July 2021 and March 2022.

2. Materials and Methods

This retrospective cohort study evaluated the treatment outcomes and immunogenicity of mild-to-moderate COVID-19 patients admitted to the HI system of Siriraj Hospital, Bangkok, Thailand. The Institutional Review Board (IRB), Faculty of Medicine Siriraj Hospital, Mahidol University reviewed and approved the follow-up study (COA: Si 732/2021 and Si 833/2021), and it was registered in ClinicalTrials.gov (NCT05328479).

2.1. Study Population

The data collection reported here was performed between 8 July 2021 and 15 March 2022. The study population comprised 2704 and 2477 patients during the Delta (before November 2021) and Omicron (after 12 January 2022) pandemics. All had been positive with SARS-CoV-2, determined via reverse transcriptase–polymerase chain reaction (RT-PCR) testing. Someone who met the inclusion criteria was considered to have mild symptoms, or perhaps be asymptomatic, and was referred to the Siriraj-Home system (SI-Home) in which medicine is delivered by health personnel within 24 h rather than being relegated to a field hospital or another potentially unpleasant arrangement. Data relating to clinical information and laboratory test findings were retrieved (after IRB approval) from patients’ electronic medical records without any personal identifiable information. The study protocol and guidelines for COVID-19 standard care were based on national and World Health Organization recommendations [15,22].

2.2. Patient Selection and Procedures

A subset of 495 patients (age ≥ 12 years) were recruited for a reactogenicity and immunogenicity follow-up study after COVID-19 recovery at 21 to 150 days post-COVID-19 onset. All participants provided informed consent for this study. They were tested for SARS-CoV-2 antibodies and a surrogate virus neutralization (sVNT) against SARS-CoV-2 Wuhan and Delta variants (Figure 1). The patients were classified into different exposure groups based on vaccination status prior to COVID-19 infection, study antibody, and PCR test (Supplementary Methods S1).

2.3. Outcome Measures

The rationale for mild-to-moderate COVID-19 treatment is described in Method S1. In brief, the primary treatment strategy in Thailand included early favipiravir treatment and recommended outpatient antiviral therapies. The primary outcome was a comparison of patients’ baseline clinical and biological characteristics with Delta and Omicron variants of SARS-CoV-2 infections in the HI system. Treatment groups were categorized into 3 groups: (1) symptomatic treatment (S), (2) symptomatic treatment plus favipiravir treatment (Favi), and (3) symptomatic treatment plus favipiravir and dexamethasone treatment (Favi/Dexa). The “date of disease onset” was defined as the day when new-onset, self-reported respiratory symptoms were observed. The durations from illness onset to first hospital admission, first favipiravir treatment, and discharge up to 14 days were measured. Viral loads were considered in cycle threshold (Ct) value analyses. Analyses considered viral loads for comparisons of Ct values by the vaccine exposure groups and self-reported symptoms. A Ct value ≥30 corresponded to a copy number threshold <106/mL or less, indicating low viral RNA [23].

2.4. Diagnosis of COVID-19

The diagnosis of COVID-19 is made based on the detection of ≥2 SARS-CoV-2 genes via RT-PCR from a nasopharyngeal (NP) swab, throat swab, and/or any respiratory samples, as previously described [24]. Our COVID-19 diagnostic assay was a probe-based qualitative RT-PCR probe. The Allplex™ 2019-nCoV Assay (Seegene, Seoul, South Korea) was used for SARS-CoV2 detection. The targeted COVID-19 genes detected here included the nucleocapsid (N), envelope (E) of Sarbecovirus, and RNA-dependent RNA polymerase (RdRp) of COVID-19 according to the manufacturer’s instructions and as described previously [25].

2.5. Serological Assays

Patients were randomly invited to test for anti-SARS-CoV-2 receptor-binding domain immunoglobulin G (anti-RBD IgG, (S1 subunit, No. 06S60)) and SARS-CoV-2 nucleocapsid protein (SARS-CoV-2 IgG II Quant for use with ARCHITECT; Abbott Laboratories, Chicago, IL, USA) [15]. The anti-SARS-CoV-2 RBD IgG assay linearly measures the level of antibody between 21.0 and 40,000.0 arbitrary units (AUs)/mL, which was converted later to the WHO International Standard concentration as binding antibody unit per mL (BAU/mL) following the equation provided by the manufacturer (BAU/mL = 0.142 × AU/mL) [26]. A level greater or equal to the cutoff value of 50 AU/mL or 7.1 BAU/mL was defined as seropositive. A Surrogate Virus Neutralization Test (sVNT) was undertaken against the original (Wuhan) strain and the Delta (B1.1617.2) strain due to its availability during the study period. Briefly, plasma was pre-incubated with horseradish-peroxidase-conjugated receptor-binding domain protein (HRP-conjugated RBD protein). Subsequently, the mixture was transferred to each well containing Streptavidin bound with Biotin-conjugated angiotensin-converting enzyme 2 (ACE2). The plate was washed, and the substrate and stop solution were added. Finally, the optical density absorbance was measured using a spectrophotometer at 450 nm. The inhibition rate was calculated through this formula:
Inhibition   rate   % = 1 OD 450   of   Sample   OD 450   of   Negative   control   × 100 .
Sample diluent was used as the negative control. White blood cell count, C-reactive protein, and D-dimer results were retrieved from electronic medical records from patients who were readmitted to the hospital.

2.6. Statistical Analysis

Multivariable analysis was performed via binary logistic regression for vaccination variables. We used negative binomial mixed models to analyze factors associated with numeric variables, including symptoms and the Chalder fatigue scale [27] (Supplementary Table S1). Cox regression analysis was used to analyze the factors of the negative conversion time (NCT) of SARS-CoV-2 RNA. The NCT is closely related to clinical manifestation and disease progression in COVID-19 patients. First, univariate analysis was performed, and the indicators with statistical significance were analyzed with Kaplan–Meier survival analysis. A Cox proportional hazard model was used for multivariate analysis. Normally distributed continuous variables were summarized as the mean ± SD; otherwise, the median (interquartile range, IQR) was used. Categorical variables were expressed using numbers and percentages. The statistical significance of Ct values, IgG, sVNT, and others was determined using Kruskal–Wallis and Dunn’s multiple comparisons tests using GraphPad Prism 9 (GraphPad Software, San Diego, CA, USA) and STATA version 17 (Stata Corp., College Station, TX, USA).

3. Results

3.1. Demographic and Clinical Data

During the Delta and Omicron pandemics, 2704 and 2477 patients were enrolled, respectively (Table 1). The mean age of the Omicron patients was younger than that of the Delta patients (31.3 ± 12.3 vs. 33.8 ± 11.6 years; p < 0.001). The proportion of COVID-19 infections was highest in the group aged 25 years or more during the Delta wave (1470 (54.4%)) and during the Omicron wave (1220, (49.3%)), whereas an increased proportion of COVID-19 infections was observed in the young during the Omicron pandemic (1015, (41%)). The frequent initial symptoms in the Delta wave were low-grade fever (95.2%) and cough (60.7%). With the Omicron wave, however, cough (47.7%) and being asymptomatic (39.1%) were frequently found.
The median duration from disease onset to HI admission was 5.1 days (interquartile range (IQR) = 2.4) for the Delta wave and 2.8 days (IQR = 1.6) for the Omicron wave (p = 0.021). The median peak viral RNA based on Ct values during the Omicron wave (19.0 (IQR = 5.7)) was lower than for the Delta wave (21.0 (IQR = 7.8); p < 0.001). Our results showed no significant correlation between Ct values and vaccination status during the Delta and Omicron pandemics. Retrospective analysis revealed that patients receiving dexamethasone treatment had Ct levels significantly below 20 during the Delta wave (p < 0.001). This finding indicates that the Ct levels were associated with disease severity in the Delta but not in the Omicron wave. According to age groups, there was no differences between common symptoms in all age groups in either the Delta or Omicron pandemics, whereas the Ct values in all age groups in the Delta pandemic (Ct 20.1 to 21.8) were higher than those in the Omicron pandemic (Ct 18.8 to 20.6) (Supplementary Tables S2 and S3).

3.2. Rehospitalized COVID-19 Patients

Eighty-nine (3.3%) and forty-three (1.7%) patients in the HI system were eventually rehospitalized during the Delta and Omicron waves, respectively (Table 2). The mean age of patients with Delta was older than that of patients with Omicron (55 years, IQR = 24 vs. 33 years, IQR = 14; p < 0.001). Compared with the Omicron patients, those with Delta had marked lymphocytopenia (0.4-fold) and neutrocytosis (1.8-fold). They also had higher levels of serum C-reactive protein (CRP) (21.2-fold), aspartate aminotransferase (1.6-fold), alanine aminotransferase (2.3-fold), and D-dimer (2-fold) (p < 0.05). Vaccination with at least two doses was associated with reduced readmission rates of the Delta patients (odds ratio (OR) = 0.305; 95% confidence interval (CI) 0.189–0.504) and Omicron patients (OR = 0.131; 95% CI 0.052–0.334) than of unvaccinated and partially vaccinated Delta and Omicron patients.

3.3. Number of Symptoms and Fatigue Scores during Home Isolation

The risk factors of sex, the severity of illness, and vaccination status were significantly related to increased fatigue, determined by the Chalder fatigue scale (Table 3). Neutralizing antibody titers were independently associated with the number of symptoms (relative risk = 1.22; 95% CI 1.05–1.42; p = 0.009). However, the association of neutralizing antibody titers was not statistically significant for fatigue. The severity of the initial illness was associated with persistent fatigue (adjusted relative risk (aRR) = 1.43; p = 0.039) and was weakly associated with the number of symptoms (aRR = 1.22; p = 0.03). In the stratified analysis of the patients, increased antibody titers remained associated with the number of symptoms (aRR = 1.04; p = 0.025) and the fatigue score (aRR = 1.09; p = 0.015). Patients who were vaccinated prior to COVID-19 infection reported a significantly lower number of symptoms (p < 0.001) and lower fatigue scores (p = 0.01) than unvaccinated patients. The Cox proportional hazard model revealed that fever (Exp(B), 0.75; p < 0.001), cough (Exp(B), 0.84; p < 0.001) and loss of smell (Exp(B), 0.81; p < 0.001) were independent risk factors of prolonged NCT of SARS-CoV-2 RNA in patients with COVID-19 (Supplementary Table S4 and Figure S2).

3.4. Clinical Manifestations and Viral Burden

The Ct values decreased markedly in unvaccinated Omicron-dominant individuals (19 (IQR = 17–22)) compared with Delta-dominant individuals (21 (IQR = 18–26); age/sex-adjusted; p < 0.001; Figure 2). No difference was observed in individuals vaccinated with either ChAdOx1 or CoronaVac (age/sex-adjusted, p = 0.175), indicating that vaccination was still valuable in reducing viral load. During the Omicron wave, new PCR-positive cases were likely to be in the low Ct subpopulation regardless of the number of vaccine doses, the vaccine type, or the time since the last vaccination. However, Ct levels tended to vary during the Delta wave (Figure 3). During the Delta but not the Omicron pandemics, patients who had at least two-dose vaccination prior to COVID-19 infection reported a significantly lower number and probability of any symptoms (OR = 0.25; 95% CI 0.12–0.52; p < 0.001) and common COVID-19 symptoms (cough, fever, and anosmia/ageusia (OR = 0.28; 95% CI 0.13–0.58; p < 0.001)) than unvaccinated individuals (Figure 4A and Supplementary Table S5). No correlation between Ct values and the probability of reporting any symptoms was noted in the Omicron pandemic (Figure 4B–E and Supplementary Table S6).

3.5. Immune Responses against SARS-CoV-2 Variants

Higher antibody titers were observed in both unvaccinated COVID-19 and vaccinated breakthrough COVID-19 patients. The titers reached their peak around 2 to 3 months post-COVID-19 (PC) and decreased gradually over the following 3 months. The RBD-IgG geometric mean titers (GMT) at baseline (1–2 months PC) were higher in the ChAdOx1 groups (one, two, and three doses) than in the CoronaVac groups. However, no differences in titers were observed between the two groups 3 months PC (ChAdOx1: one dose (822 binding antibody units (BAU)/mL), two doses (945 BAU/mL), and three doses (886 BAU/mL) vs. (CoronaVac: one dose (1174 BAU/mL) and two doses (974 BAU/mL)). In contrast, infected individuals with prior vaccination had higher antibody titers at all time points compared with previously unvaccinated participants with COVID-19 infection (p < 0.05; Figure 5A and Supplementary Tables S7 and S8, Figure S3).
The anti-RBD IgG levels and sVNT against the Delta variant were markedly correlated (r = 0.486 to r = 0.599), particularly in the unvaccinated group and vaccinated group (Figure 6 and Supplementary Table S9). In both males and females, the GMT of anti-RBD IgG was significantly higher in unvaccinated cases after 2 months (Figure 7A). Older individuals had significantly higher GMT of anti-RBD IgG than the younger individuals in both the unvaccinated and ChAdOx1 groups. Although there was no significant difference in anti-RBD IgG between age groups in the CoronaVac groups, anti-RBD IgG tended to be higher in the older than in the younger individuals (Figure 8A).
Most patients had highly positive sVNT against Wuhan and Delta. Higher sVNT was observed chiefly in breakthrough COVID-19 patients vaccinated with either CoronaVac-prime or ChAdOx1-prime, regardless of the numbers of dose. The titers peaked around 2 to 3 months PC and decreased by approximately 10% to 20% after 3 months, compared with 2 to 3 months PC (Figure 5B and Supplementary Figure S3). The titers were significantly higher against the Wuhan strain than the Delta variant (p < 0.001). Using sVNT, the proportion of individuals with a value for a neutralizing test against Delta above the sVNT cutoff of 30 was approximately 66% to 88% of unvaccinated participants (pink dots). This range contrasted with 83% to 89% for one or two doses of ChAdOx1 (pale blue dots), 100% for three doses of ChAdOx1, and 67% to 95% for one or two doses of CoronaVac.
In fully vaccinated individuals at 2 to 3 months PC, the mean sVNT to the Delta relative to the Wuhan variant was reduced 0.7-fold (from 96.4 to 72.3, ChAdOx1 group). As compared with unvaccinated COVID-19 patients, the mean sVNT for the Delta variant of ChAdOx1-boosted individuals at 2 to 3 months PC were increased 2.8-fold (from 34.7 to 98) and 2.1-fold (from 34.7 to 72.3, compared with two-dose ChAdOx1 group, Figure 5B). In both males and females, the sVNT was significantly higher in unvaccinated cases after 2 months (Figure 7B). The proportion of plasma samples exhibiting such a neutralizing activity against Delta tended to be nearly 1- to 2-fold higher among older than younger individuals (Figure 8B–D and Supplementary Table S10).

4. Discussion

We confirmed the following central findings. First, illness is mild in most patients, and medical intervention is not needed, particularly in fully vaccinated individuals. These findings confirm that early access to treatment and prompt responses via telehealth visits and antiviral medications provide statistically favorable efficacy in sustaining COVID-19 and improving outcomes in an appropriate outpatient setting [28]. Recent studies demonstrated that patients receiving favipiravir had higher viral clearance rates than patients given standard symptomatic treatment; this higher rate prevented hospitalization [28]. A systematic review and meta-analysis of clinical trials summarized that favipiravir exerted low efficacy in mortality reduction for patients with mild-to-moderate COVID-19. However, the authors also pointed out that that finding might have resulted from delayed treatment in many trials [29].
Second, understanding the relationship between symptoms, viral load, and predictive immunity is crucial to planning for booster vaccination programs. Our results contrast with a recent study [30] reporting lower Ct values for patients infected during the relatively mild Omicron wave than patients infected during the Delta wave. Data showed that primary immunization with two doses of ChAdOx1 or CoronaVac vaccine provided limited protection against symptomatic disease caused by the Delta and the Omicron variants, and vaccine effectiveness waned quickly. Higher neutralizing activity was observed after a booster dose [31]. However, we are the first to show that breakthrough COVID-19 infection with prior vaccination was associated with a significantly lower number of symptoms and fatigue even in the mild-to-moderate COVID-19 disease. On the other hand, the lower the number of symptoms was, the lower the antibody titers were. The difference in risk between the Delta and Omicron waves varied considerably with age but not gender. The risk of hospitalization differed the most for those aged 60 years (50% lower for Omicron compared with Delta) [32]. In contrast, for children under the age of 12 years, there was no significant difference in the risk of hospitalization between Omicron and Delta. The risk of death remained minimal in children. Our unpublished data showed that infected children during the Delta and Omicron pandemics were hospitalized due to insufficient oral intake, anorexia, gastrointestinal tract symptoms, and hypovolemia rather than increased COVID-19 severity.
In addition, in the Omicron pandemic, children made up a larger proportion of patients than in the previous infection waves. One potential explanation for this was that the Omicron variant’s extremely high transmissibility, when coupled with a lack of built-up immunity due to vaccination for 5–11-year-olds in Thailand not being authorized in early 2022 or past infection in young children, left children more vulnerable to Omicron, compared with adults who had access to vaccines for months. Another reason might be that other restrictions and isolation policies were eased at the same time, and parents had the ability to return to the workplace, where transmission also occurred, and immunity waned.
In the mild-to-moderate COVID-19 cases during the Delta and Omicron pandemics, IgG and sVNT were higher in patients with more severe common COVID-19 symptoms. The titers were also associated with high viral loads and older individuals (who were generally vaccinated and had more severe symptoms than asymptomatic individuals) [7]. Higher igG and sVNT was shown in breakthrough COVID-19 patients vaccinated with either CoronaVac-prime or ChAdOx1-primary doses. The titers peaked around 2 to 3 months PC and remained stable for at least 3 months. However, receiving booster vaccines ensured better predictive immunity against COVID-19. In the Omicron pandemic, viral load was not correlated with symptoms. This finding was likely due to Omicron’s milder conditions, an improved vaccination campaign, and quick access to medication treatment. Our results are consistent with the findings of Servellita et al. [7], who examined neutralizing responses in Delta and Omicron breakthrough infections. Substantial increases in antibody titers to Wuhan and Delta were demonstrated, especially after vaccination boosting. In symptomatic or mild Delta and Omicron breakthrough infections, the extent of conferred cross-neutralizing immunity against Omicron and Delta was limited. However, Wratil et al. [33] found that sera from patients with Omicron breakthrough infections significantly enhanced Omicron viral neutralization (17.4-fold).
It is well documented that COVID-19 primarily manifests as a respiratory tract infection, and emerging data indicate it involves multiple systems. Several hematological laboratory investigations have shown that lymphocytes, neutrophils, CRP, elevated D-dimer, and hemostasis are altered significantly in COVID-19 patients [12]. This finding is a potential indicator for both disease progression and the effectiveness of therapy [12]. Evidence indicates that mild COVID-19 may be associated with a potent initial innate antiviral response induction and viral neutralization. These might evade host innate immune activation and, in turn, increase proinflammatory response and immune cell infiltration [34,35]. Even though we did not have a complete set of these parameters for every subject due to the nature of retrospective data from mild-to-moderate COVID-19, we had some patients with worsening conditions who were eventually hospitalized and whose blood was examined. Our results indicated that, during the Delta but not the Omicron wave, these patients had increased neutrophils and lymphocytopenia and activation of the coagulation cascade. However, there were reports that Omicron patients had abnormal levels of neutrophils, lymphocytes, and monocytes and demonstrated signs of coagulopathies [35,36,37]. The adaptive immune response was a key element of the clinical outcome after SARS-CoV-2 infection and supported vaccine efficacy. T-cell responses activated early and correlated with protection but were relatively weakened in severe COVID-19 and were associated with intense activation and lymphopenia [38]. Inflammatory cytokines such as IL-6, IL-8, IL-1β, TNF-α, IFNγ-induced protein10 (IP-10), granulocyte-macrophage colony-stimulating factor (GM-CSF), and chemokines (CC motif) ligand 2 (CCL2), CCL-5, and CCL3 were generally produced by macrophages, mast cells, endothelial and epithelial cells during the innate immune response. Many studies have shown that elevated IL-6 significantly affected the onset of cytokine storm [39,40]. IL-6 played a pleiotropic role in the immune system and was crucial for the formation of TH17 and follicular helper T cells. However, IL-6 could block cytotoxic CD8 + T cells by inhibiting IFN-γ secretion. In addition, IL-6 could impair the cell-induced antiviral response in the cytokine storm. Our unpublished data showed some increased IL-6 levels in some COVID-19 patients. However, we need to clarify the factors predisposing cytokine storms and other inflammatory cytokines. Some studies investigated the T-cell immunity induced after SARS-CoV-2 infection in mild symptomatic cases, showing S-SARS-CoV-2-specific IFN-γ T-cell response was developed [41]. CD4+ T-cell responses against SARS-CoV-2 were more prevalent than CD8+ T-cell responses in adults with mild-to-moderate COVID-19 infection [42]. Still, more in-depth research on the underlying etiology is necessary. Gao Y et al. [43] demonstrated that SARS-CoV-2 spike-specific CD4+ and CD8+ T cells elicited by BNT162B2 vaccination or previous infection remain largely intact against the Omicron variant. Together with intrinsic viral factors, these immune reactivities, in part, explain why severe disease appears to be minimal after breakthrough infection with this particular variant.
A recent genome-wide association analysis (GWAS) [44] showed associations of loci on chromosomes 5q32 and 9q21.13 with COVID-19 susceptibility and two suggestive loci on the severity of chromosomes 12q22 and 3p24.3. Interestingly, the association signal on chromosome 5q32 coincided with IL17B encoding a T-cell-derived cytokine known as interleukin-17B (IL-17B). IL-17B was reported to play a role as a proinflammatory inducer in inflammatory disease, stimulating the release of tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) from a monocytic cell line, resulting in neutrophil infiltration [45,46]. This supports our finding of hyperneutrophilia seen in our COVID-19 cohort.
These data combined with ours suggest that the higher infectivity of Omicron may be related to (1) a decreased viral load, (2) probably lower past protective immunity against Omicron (either from vaccines or natural infection with Delta), (3) an asymptomatic stage of infected individuals with respiratory symptoms, and (4) age [20]. The substantial variations in patients’ symptoms and immunogenicity underscore the heterogenicity of protective immunity against future infections. However, an individual previously infected with SARS-CoV-2 is advised to receive a full vaccination course or at least one additional dose of a vaccine after the infection to protect against reinfection from circulating variants [47]. High vaccination rates also help to reduce the transmission of COVID-19. Unfortunately, vaccination rates are still low in some rural areas, important risk groups, and low-income countries [48].
There are several limitations to our study. We only had blood test results from a small subset of hospitalized patients and assumed these findings might be similar to all milder infection cases without hospitalization. No patients with Omicron were treated with Dexamethasone (Favi/Dexa) in the HI system due to the reduced severity of the Omicron infection and increased hospitalization availability for worse cases. However, to compare both waves, we excluded patients in the Favi/dexa group in the Delta wave from the analyses, and the p-value was not affected in all parameters. Furthermore, no serology data from patients during the Omicron wave or long-term follow-up data were available for our analysis. Consequently, we could not determine the antibody levels against the Omicron variants, the vaccine efficacy after COVID-19 infection, or the vaccine impact on long COVID-19.
Our future COVID-19 research aims are (1) to gain further insight into the long-term monitoring of neutralizing antibodies and (2) to establish whether breakthrough Omicron infections provide protective immunity against reinfection by SARS-CoV-2 Omicron sub-lineages BA.4 and BA.5.

5. Conclusions

Omicron’s mild severity means that a full vaccination course is effective against severe outcomes. Consequently, in countries where vaccine supplies are limited, a full vaccination course with prime or mixed vaccines, and a booster shot for individuals at risk, might be enough to induce high levels of short-term immunity and prevent hospitalization and death. These outcomes should be achievable regardless of a higher viral burden or the symptoms, especially during the Omicron wave in the absence of novel variants.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/vaccines10071131/s1, Figure S1: Trend of SARS-CoV-2 variants circulating in Thailand, deaths and vaccination status during analysis period; Methods S1: Study design, eligibility, and inclusion and exclusion criteria; Figure S2: Kaplan–Meier estimate of time to symptom alleviation as reported by COVID-19-adapted FLU-PRO questionnaire (July–October 2021 (Delta)); Figure S3: Plasma anti-immunoglobulin G (IgG) and antibody (sVNT) levels against SARS-CoV-2; Table S1: General comorbidity questionnaire; Table S2: Characteristics of participants at enrollment (July–October 2021 (Delta)) by age; Table S3: Characteristics of participants at enrollment (January–March 2022 (Omicron)) by age; Table S4: Independent factors of NCT of SARS-CoV-2 RNA by the multivariate Cox’s proportional hazard model by age >18 years (July–October 2021 (Delta)); Table S5: Characteristics of the first positive symptoms between the Delta and Omicron pandemics for people aged >18 years; Table S6: Independent associations with symptoms reporting between the Delta and Omicron pandemics for people aged >18 years; Table S7: Characteristics of the participants and geometric mean humoral immunogenicity assay responses according to anti-SARS-CoV-2 nucleocapsid protein and vaccine group; Table S8: Anti-RBD IgG and sVNT geometric mean concentration (GMC) among unvaccinated, ChAdOx1, and CoronaVac; Table S9: SARS-CoV-2 sVNT geometric mean concentration (GMC) among unvaccinated, ChAdOx1, and CoronaVac by Wuhan and Delta variants; Table S10: Anti-RBD IgG and sVNT geometric mean concentration (GMC) among unvaccinated, ChAdOx1, and CoronaVac by age. References [6,9,24,25,49] are cited in the supplementary materials.

Author Contributions

P.M., A.S., S.P. and K.M. conceived and designed the manuscript, analyzed the data, and drafted the manuscript. P.P. (Pochamana Phisalprapa), N.S. (Naruemit Sayabovorn), W.S., C.W., C.A., T.S., T.C., R.T., M.C., G.S., P.P. (Pakpoom Phoompoung), S.S., S.M. and SPHERE performed patient care and revised and reviewed the manuscript. P.M., A.S., S.P. and K.M. performed critical revisions of the manuscript. W.T. performed IgG testing and provided data establishing testing. N.S. (Nitat Sookrung) and A.T. performed sVNT testing. A.S. performed biostatistical analysis and review. All authors read the manuscript and agreed with its content. The corresponding author (K.M.) attests that all listed authors meet authorship criteria and that no others have been omitted. All staff who carried out COVID-19 care are listed in the Supplementary Materials. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by Siriraj Hospital, Mahidol University (grant number R016534002).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Faculty of Medicine Siriraj Hospital, Mahidol University (COA: Si 732/2021 and Si 833/2021).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Raw data used in this study, including de-identified patient metadata and test results, are available upon request.

Acknowledgments

We are grateful for the support of the COVID-19 teams: the Siriraj Population Health and Nutrition Research (SPHERE) Group that is composed of the following members—Sureeporn Pumeiam, Bonggochpass Pinsawas, Pichanun Mongkolsucharitkul, Apinya Surawit, Tanyaporn Pongkunakorn, Sophida Suta, Thamonwan Manosan, Suphawan Ophakas, and Korapat Mayurasakorn. We would also like to thank Tassanee Narkdontri, Nipaporn Teerawattanapong, and Worapanit Lerdsaeng from the Siriraj Center of Research Excellence for Diabetes and Obesity Research (SiCORE-DO), the Research Department and Department of Immunology and Utane Runpanich from the Department of Immunology for performing IgG assays, and the Center of Research Excellence on Therapeutic Proteins and Antibody Engineering, the Department of Parasitology for performing the surrogate virus neutralization test.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Figure 1. Study source recruitment and enrollment.
Figure 1. Study source recruitment and enrollment.
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Figure 2. Ct value trajectories of confirmed COVID-19 infection and symptoms during the Delta and Omicron pandemics in vaccinated and unvaccinated individuals. (A) Ct values by vaccination/reinfection status and (B) Ct values by waves and vaccination type. * p < 0.05.
Figure 2. Ct value trajectories of confirmed COVID-19 infection and symptoms during the Delta and Omicron pandemics in vaccinated and unvaccinated individuals. (A) Ct values by vaccination/reinfection status and (B) Ct values by waves and vaccination type. * p < 0.05.
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Figure 3. Ct value trajectories of confirmed COVID-19 infection and symptoms during the Delta (A,B) and Omicron (CF) pandemics in vaccinated and unvaccinated individuals. Ct values in PCR-positives after receiving ChAdOx1 or CoronaVac or BioNTech or Moderna vaccines or unvaccinated, regardless of vaccine doses by time since July 2021. Red dots are represented in all figures as reference values.
Figure 3. Ct value trajectories of confirmed COVID-19 infection and symptoms during the Delta (A,B) and Omicron (CF) pandemics in vaccinated and unvaccinated individuals. Ct values in PCR-positives after receiving ChAdOx1 or CoronaVac or BioNTech or Moderna vaccines or unvaccinated, regardless of vaccine doses by time since July 2021. Red dots are represented in all figures as reference values.
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Figure 4. Ct value trajectories of confirmed COVID-19 infection and symptoms during the Delta and Omicron pandemics in vaccinated and unvaccinated individuals. (A) Self-report symptoms in PCR-positives by numbers of vaccination/reinfection status. Probability of reporting common (B,D) fever, cough, anosmia, or ageusia or (C,E) any symptoms by Ct values and vaccination status in PCR-positives.
Figure 4. Ct value trajectories of confirmed COVID-19 infection and symptoms during the Delta and Omicron pandemics in vaccinated and unvaccinated individuals. (A) Self-report symptoms in PCR-positives by numbers of vaccination/reinfection status. Probability of reporting common (B,D) fever, cough, anosmia, or ageusia or (C,E) any symptoms by Ct values and vaccination status in PCR-positives.
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Figure 5. Immune responses after breakthrough COVID-19 infection with prior CoronaVac or ChAdOx1 vaccination during the Delta pandemic. (A) The scatter plot of geometric mean titers (GMTs) of SARS-CoV-2 anti-spike protein receptor-binding domain antibodies’ (Anti-RBD IgG) concentrations in serum samples obtained from subjects after COVID-19 infection and with prior various vaccination status (CoronaVac vs. ChAdOx1). Sera at different time points from patients recovered from COVID-19 are shown as reference level (red). (B) Scatter plots demonstrate an inhibition rate of Wuhan and Delta RBD-blocking antibodies measured using a surrogate viral neutralization test (sVNT) by vaccination/reinfection status; the lower dot line represents the cut-off level for seropositivity. All sera were from the patients during the Delta pandemic. * p < 0.05; ** p < 0.01; **** p < 0.0001.
Figure 5. Immune responses after breakthrough COVID-19 infection with prior CoronaVac or ChAdOx1 vaccination during the Delta pandemic. (A) The scatter plot of geometric mean titers (GMTs) of SARS-CoV-2 anti-spike protein receptor-binding domain antibodies’ (Anti-RBD IgG) concentrations in serum samples obtained from subjects after COVID-19 infection and with prior various vaccination status (CoronaVac vs. ChAdOx1). Sera at different time points from patients recovered from COVID-19 are shown as reference level (red). (B) Scatter plots demonstrate an inhibition rate of Wuhan and Delta RBD-blocking antibodies measured using a surrogate viral neutralization test (sVNT) by vaccination/reinfection status; the lower dot line represents the cut-off level for seropositivity. All sera were from the patients during the Delta pandemic. * p < 0.05; ** p < 0.01; **** p < 0.0001.
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Figure 6. Immune responses after breakthrough COVID-19 infection with prior CoronaVac or ChAdOx1 vaccination during the Delta pandemic. Dot plots show the correlation between the level of anti-SARS-CoV-2 RBD IgG and surrogate viral neutralization test (sVNT) for the SARS-CoV-2 delta variant in plasma of study participants (total, (A) who were unvaccinated (C), or completed two doses of ChAdOxX1 (B), CoronaVac (D) and had breakthrough infection.
Figure 6. Immune responses after breakthrough COVID-19 infection with prior CoronaVac or ChAdOx1 vaccination during the Delta pandemic. Dot plots show the correlation between the level of anti-SARS-CoV-2 RBD IgG and surrogate viral neutralization test (sVNT) for the SARS-CoV-2 delta variant in plasma of study participants (total, (A) who were unvaccinated (C), or completed two doses of ChAdOxX1 (B), CoronaVac (D) and had breakthrough infection.
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Figure 7. Immune responses after breakthrough COVID-19 infection with prior CoronaVac or ChAdOx1 vaccination during the Delta pandemic. Anti-RBD IgG concentrations (A), sVNT (B) by sex/vaccination/reinfection status. * p < 0.05; ** p < 0.01.
Figure 7. Immune responses after breakthrough COVID-19 infection with prior CoronaVac or ChAdOx1 vaccination during the Delta pandemic. Anti-RBD IgG concentrations (A), sVNT (B) by sex/vaccination/reinfection status. * p < 0.05; ** p < 0.01.
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Figure 8. Immune responses after breakthrough COVID-19 infection with prior CoronaVac or ChAdOx1 vaccination during the Delta pandemic. Antibodies (Anti-RBD IgG) (A) by age/vaccination, and sVNT (BD) by age groups/vaccination/infection status. * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001.
Figure 8. Immune responses after breakthrough COVID-19 infection with prior CoronaVac or ChAdOx1 vaccination during the Delta pandemic. Antibodies (Anti-RBD IgG) (A) by age/vaccination, and sVNT (BD) by age groups/vaccination/infection status. * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001.
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Table 1. Characteristics and laboratory findings of all confirmed COVID-19 patients, compared between those with symptomatic treatment (S), symptomatic treatment plus 5–14 days’ standard favipiravir treatment (Favi) and symptomatic treatment plus 5–14 days’ standard favipiravir treatment plus dexamethasone treatment (Favi/Dexa) *.
Table 1. Characteristics and laboratory findings of all confirmed COVID-19 patients, compared between those with symptomatic treatment (S), symptomatic treatment plus 5–14 days’ standard favipiravir treatment (Favi) and symptomatic treatment plus 5–14 days’ standard favipiravir treatment plus dexamethasone treatment (Favi/Dexa) *.
CharacteristicsJuly–October 2021 (Delta)January–March 2022 (Omicron)p *
All Patients (n = 2704)S
(n = 352)
Favi
(n = 2277)
Favi/Dexa (n = 75)p *,†All Patients
(n = 2477)
S
(n = 520)
Favi
(n = 1957)
p *,‡
n%n%n%n% n%n%n%
Female sex145153.717650.0123554.24053.30.332144658.434065.4110656.50.0200.001
Age, year, mean (SD)33.8(11.6)15.7(9.4)36.0(8.7)52.5(6.4)<0.00131.3(12.3)36.0(15.4)30.1(11.2)<0.001<0.001
<2595535.327578.167729.734.0<0.001101541.011522.190046.0<0.001<0.001
25–60147054.47521.3135059.34560.0 122049.336069.286043.9
>6027910.320.625011.02736.0 2429.8458.719710.1
Body weight, kg, mean (SD)57.5(22.0)38.3(21.4)59.7(20.9)69.7(13.2)0.04355.8(22.4)61.6(16.7)54.2(23.4)0.0340.007
Presence of comorbidities
Diabetes mellitus1626.010.31516.61013.3<0.0011506.1346.51165.90.6040.922
Hypertension31311.672.028312.42330.7<0.00151320.711622.339720.30.312<0.001
Dyslipidemia1234.520.61135.0810.70.0171084.4163.1924.70.1070.742
Obesity230.900.0231.000.00.114411.771.3341.70.5340.009
Malignancy220.800.0210.911.30.176251.020.4231.20.1090.458
Neurologic disease70.300.070.300.00.28827110.97815.01939.90.001<0.001
Heart disease331.210.3311.411.30.230381.520.4361.80.0160.332
Lung disease511.910.3301.32026.7<0.001na na na
Kidney disease140.510.3130.600.00.641100.410.290.50.3920.546
Others33612.4339.429212.81114.70.15875330.416231.259130.20.674<0.001
Presenting symptoms
Asymptomatic infection39014.410329.328612.611.3<0.00196939.122443.174538.10.038<0.001
Fever/history of fever125046.213337.8107447.24357.30.00126710.8234.424412.5<0.001<0.001
BT (°C), median (IQR) 36.6(0.7)36.3(0.6)36.6(0.7)37.0(0.6)0.01536.8(0.5)36.7(0.4)36.9(0.5)0.149<0.001
<37.5247495.231897.0209495.36283.80.002210788.848995.5161886.90.015<0.001
37.5–38.01204.6103.0994.51114.9 24410.3214.122312.0
>38.060.200.050.211.4 231.020.4211.1
Cough164260.715243.2142562.66586.7<0.001118147.724246.593948.00.558<0.001
Sore throat103838.48123.091840.33952.00.010118147.724246.593948.00.558<0.001
Rhinorrhea41915.54713.435815.71418.70.38362625.314327.548324.70.189<0.001
Productive sputum53719.94613.146520.42634.70.029na na na
Loss of taste31211.5236.527412.01520.00.010431.7122.3311.60.261<0.001
Loss of smell82130.46618.872531.83040.00.017431.7122.3311.60.261<0.001
Dyspnea30511.351.427111.92938.70.012241.020.4221.10.126<0.001
Myalgia28210.4113.124910.92229.30.0052068.35210.01547.90.1180.009
Diarrhea1264.7113.11084.779.3<0.001632.5101.9532.70.312<0.001
Nausea/vomiting592.220.6492.2810.70.038371.551.0321.60.2600.067
Others154957.316847.7132858.35370.7<0.0011917.7366.91557.90.449<0.001
Clinical features at the time of admission
Time from symptom onset to PCR diagnosis, median (IQR), days1.9(1.6)2.1(1.9)1.9(1.6)1.9(1.5)0.3942.0(1.1)2.1(1.0)2.0(1.1)0.1670.049
Time from symptom onset to admission, median (IQR), days5.1(2.4)5.6(2.6)5.0(2.3)5.2(2.0)0.3372.8(1.6)3.2(2.0)2.6(1.4)0.0320.021
Cycle threshold **
Cycle threshold, median (IQR)21.0(7.8)24.1(9.4)20.7(7.4)18.5(4.3)0.00119.0(5.7)21.4(6.9)19.7(5.3)0.001<0.001
<20111843.18825.997945.05168.9<0.001116249.420138.796152.4<0.001<0.001
20–30121847.018955.6100846.32128.4 97441.424046.273440.0
>302559.86318.51908.722.7 2169.27815.01387.5
Envelope (E), median (IQR)17.5(8.4)20.9(9.9)17.3(8.0)14.3(4.7)0.01218.0(5.4)17.8(5.1)19.0(6.7)0.121<0.001
RNA-dependent RNA polymerase (RdRp), median (IQR)22.3(8.2)25.9(9.6)22.0(7.7)19.7(4.7)<0.00119.3(5.4)20.3(6.9)19.1(5.0)0.220<0.001
Referred back to the hospital, yes893.330.9612.72533.3<0.001431.751.0381.90.128<0.001
Dead, yes50.200.000.056.7<0.00120.100.020.10.4660.308
* Continuous data of characteristics and laboratory findings of all confirmed COVID-19 patients presented as mean (SD), median (IQR), and range at p < 0.05 indicates statistical significance. The statistical significance was assessed using the Fisher’s exact test and Kruskal–Wallis test; statistical difference within the Delta group was at p < 0.05. The statistical significance was assessed using the Fisher’s exact test and Mann–Whitney test statistical difference within the Omicron group at p < 0.05. § The statistical significance was assessed using the Fisher’s exact test and Mann–Whitney test; statistical difference between Delta and Omicron groups was at p < 0.05. Body temperature (BT) is a measure of the balance between heat generation and heat loss of the body. Interquartile range (IQR) is a measure of statistical dispersion. ** Cycle threshold (Ct) value from RT-PCR tests represents the cycle number at which the signal breaches the threshold for positivity; a lower Ct value is indicative of a high viral load.
Table 2. Demographic, clinical, and laboratory findings of all of patients referred back for in-patient care and compared between those during the Delta and the Omicron pandemic *.
Table 2. Demographic, clinical, and laboratory findings of all of patients referred back for in-patient care and compared between those during the Delta and the Omicron pandemic *.
CharacteristicsJuly–October 2021 (Delta)January–March 2022 (Omicron)p *
All Patients (n = 89)Alive
(n = 84)
Dead
(n = 5)
p *,†All Patients (n = 43)Alive
(n = 41)
Dead
(n = 2)
p *,‡
n%n%n% n%n%n%
Male sex4449.44351.2120.00.1752046.51843.92100.00.1210.753
Age, year, median (IQR)55.0(24.0)55.5(24.5)54.0(5.0)0.61733.0(14.0)30.5(12.0)81.0(8.5)0.073<0.001
<1855.656.000.00.0172558.12561.000.00.0220.697
18–442629.22631.000.0 49.349.800.0
45–643741.63238.15100.0 37.037.300.0
≥652123.62125.000.0 1125.6922.02100.0
Presence of comorbidities
Diabetes mellitus2325.82125.0240.00.457716.3717.100.0na<0.001
Hypertension2831.52631.0240.00.6721023.31024.400.0na<0.001
Dyslipidemia1213.51214.300.00.364614.0614.600.0na<0.001
Heart diseasena na na 37.037.300.0na<0.002
Others3134.82833.3360.00.22424.724.900.0na0.258
Presenting symptoms of entering HI
Asymptomatic infection910.1910.700.00.4403274.43073.22100.00.3960.020
Fever/history of fever4955.14654.8360.00.4642762.82561.02100.00.5300.003
BT (°C), median (IQR) **36.8(0.5)36.8(0.5)36.8(0.2)0.15636.7(0.9)36.7(0.9)--na
>38.0910.189.5120.00.42924.724.900.0na0.660
Cough6168.55869.0360.00.6722046.51843.92100.00.2580.533
URI ††4550.64351.2240.00.4892148.82151.200.00.1110.174
Loss of taste/smell2224.72125.0120.00.20112.312.400.00.7930.008
Dyspnea5359.64857.15100.00.01324.724.900.00.706<0.001
Muscle aches2325.82125.0240.00.101818.6819.500.00.3990.925
Diarrhea1314.61113.1240.00.09824.724.900.00.7060.219
Nausea/vomiting1011.21011.9120.00.413614.0614.600.00.4830.372
Chest radiograph on referral date
Pneumonia detected in chest radiograph5157.34857.1360.00.6381227.91229.300.0na0.158
Hematological, median (IQR)
WBC ‡‡ (×103/µL)7.7(7.4)7.7(7.4)7.4(7.2)0.7856.3(4.0)6.3(3.7)8.8(9.8)0.0610.012
Lymphocytes (×103/µL)0.8(0.8)0.9(0.4)0.8(0.8)0.0381.8(2.1)1.8(2.0)2.1(2.6)0.914<0.001
<1 × 103/uL3539.33238.1360.00.5921227.91126.8150.00.4920.001
Neutrophil (×103/µL)6.1(7.0)6.4(7.4)6.1(7.0)0.5843.4(2.5)3.4(2.6)6.1(7.3)0.047<0.001
Creatinine (mg/dL)0.8(0.4)0.8(0.4)1.0(1.6)0.0680.8(0.8)0.8(0.9)0.8(0.3)0.047<0.001
eGFR §§ (mL/min/1.73 m2)84.5(37.5)84.5(38.2)56.4(87.1)0.08067.0(64.5)67.0(64.5)--na0.139
AST ¶¶ (U/L)47.5(27.5)47.0(26.0)59.0(146.0)0.04330.0(17.0)30.0(17.0)36.0-na<0.001
>403539.33238.1360.00.0561023.31024.400.00.552<0.001
ALT ¶¶ (U/L)41.5(32.5)42.0(32.0)19.0(39.0)0.33718.0(8.0)17.5(8.0)22.0-na<0.001
>402932.62833.3120.00.51137.037.300.00.771<0.001
C-reactive protein (mg/L)72.1(65.2)72.5(64.0)64.1(54.7)0.1543.4(9.2)3.4(8.7)67.6(29.3)0.0350.008
<1069.546.7266.70.0053173.83075.0150.00.114<0.001
10–1004063.54066.700.0 819.0820.000.0
>1001727.01626.7133.3 37.125.0150.0
Procalcitonin (ng/mL)0.1(0.3)0.1(0.2)0.5(1.5)0.0850.1(0.3)0.1(0.3)0.1(0.2)0.439<0.001
>0.054083.33681.84100.00.097969.2763.62100.00.3050.257
D-dimer, median (ng/mL)2671.9(1008.9)2552.1(1067.1)4308.0(2872.6)0.0591347.0(4588.5)1297.0(2723.0)7633.0-na0.029
<5001329.51331.700.00.21500.000.000.00.1170.099
501–30002556.82356.1266.7 562.5571.400.0
>3000613.6512.2133.3 337.5228.61100.0
Cycle Threshold ‖‖ (viral load at the time of entering HI)
Nucleocapsid (N), median (IQR)19.1(5.4)19.2(5.2)16.1(3.7)0.84618.9(3.9)18.9(3.2)18.2(5.6)0.7290.023
<205764.05363.1480.00.7143172.13073.2150.00.5670.414
20–302831.52732.1120.0 920.9819.5150.0
>3044.544.800.0 37.037.300.0
Vaccine status
Unvaccinated5865.25464.3480.00.4082967.42765.92100.00.6030.134
1 dose1011.2910.7120.0 920.9922.000.0
≥2 doses2123.62125.000.0 511.6512.200.0
ORcrude (95% CI) ***0.309 (0.189–0.504)0.131 (0.052–0.334)
ORage and sex adjusted0.142 (0.016–0.265)0.109 (0.011–0.318)
ORfully adjusted0.299 (0.012–7.643)0.105 (0.005–0.294)
* Continuous data of demographic, clinical, and laboratory findings of all patients referred back presented as mean (SD), median (IQR), and range at p < 0.05 which indicates statistical significance; OR, odds ratio. The statistical significance was assessed using the Fisher’s exact test and Kruskal–Wallis test; statistical difference within the Delta group was at p < 0.05. The statistical significance was assessed using the Fisher’s exact test and Mann–Whitney test; statistical difference within the Omicron group was at p < 0.05. § The statistical significance was assessed using the Fisher’s exact test and Mann–Whitney test; statistical difference between Delta and Omicron groups was at p < 0.05. Home isolation (HI): Once a COVID-19 infection has been diagnosed, medical staff will assess home isolation. The patients should generally be in good health and should not be suffering from any of the following conditions: chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), cardiovascular disease, cerebrovascular disease, uncontrollable diabetes, or other conditions that may be considered by doctors to be a risk. Patients must agree to strictly isolate themselves from others. Body temperature (BT) is a measure of the balance between heat generation and heat loss of the body. ** Interquartile range (IQR) is a measure of statistical dispersion. †† Upper respiratory infection (URI) affects the upper part of your respiratory system. ‡‡ White blood count (WBC) is part of the immune system, helping to defend the body against infections and disease. §§ Estimated Glomerular Filtration Rate (eGFR) is used to determine if one has kidney disease. ¶¶ Aspartate aminotransferase (AST) is an enzyme that is present in various tissues of the body, while alanine aminotransferase (ALT) is found mainly in your liver, used to check for liver conditions, while AST is found in more parts of the body than ALT. For this reason, abnormal levels of ALT tend to be better indicators of liver problems than AST. ‖‖ Cycle threshold (Ct) value from RT-PCR tests represents the cycle number at which the signal breaches the threshold for positivity; a lower Ct value is indicative of a high viral load. *** Effect estimates are reported as ORs (95% CIs); unvaccinated and 1-dose (reference) groups vs. >2 doses were compared by using multivariable logistic regression to calculate adjusted ORs (aORs) with 95% CIs.
Table 3. COVID-19 patient factors associated with increasing number of symptoms and higher fatigue score at 14-day follow-up—negative binomial mixed models (July 2021 to March 2022) *.
Table 3. COVID-19 patient factors associated with increasing number of symptoms and higher fatigue score at 14-day follow-up—negative binomial mixed models (July 2021 to March 2022) *.
Characteristicsn %Number of Symptoms (0–12)Fatigue Score (0–27)
RR §95% CI p *,‖aRR **95% CIp *,‖RR95% CIp *,††aRR95% CIp *,††
Female sex219458.41.02(0.94, 1.10)0.6501.03(0.96, 1.11)0.3611.13(0.99, 1.30)0.0711.15(1.00, 1.31)0.049 *
Age, year, median (range)31 (17–47)1.00(1.00, 1.00)0.9661.00(1.00, 1.00)0.1461.00(0.99, 1.00)0.4581.00(0.99, 1.00)0.292
Comorbidity
Hypertension76920.51.05(0.95, 1.16)0.3221.04(0.93, 1.16)0.4880.97(0.81, 1.15)0.708---
Dyslipidemia2316.21.01(0.89, 1.15)0.8901.07(0.93, 1.22)0.3530.97(0.77, 1.22)0.7811.11(0.86, 1.42)0.427
Diabetes mellitus3118.30.99(0.87, 1.13)0.9140.95(0.83, 1.09)0.4910.83(0.65, 1.05)0.1150.81(0.63, 1.04)0.104
Asthma/COPD ‡‡974.80.99(0.85, 1.15)0.8820.99(0.86, 1.14)0.8820.84(0.64, 1.10)0.2110.85(0.65, 1.11)0.232
Chronic heart disease651.71.07(0.83, 1.39)0.5921.07(0.84, 1.37)0.5681.22(0.77, 1.93)0.391.30(0.83, 2.04)0.252
Severity of initial illness1022.71.34(1.11, 1.61)0.002 *1.22(1.02, 1.45)0.030 *1.46(0.95, 1.75)0.0511.43(1.37, 1.72)0.039 *
Immunosuppression §§, median (range)8.89 (7.94–9.53)1.05(1.03, 1.08)<0.001 *1.04(1.01, 1.08)0.025 *1.04(1.00, 1.10)0.0741.09(1.02, 1.16)0.015 *
Neutralizing antibody titers ¶¶, median (range)4.58 (4.55–4.59)1.22(1.08, 1.37)0.001 *1.22(1.05, 1.42)0.009 *1.18(0.80, 1.20)0.8761.14(0.66, 1.19)0.324
Vaccinated, yes257768.60.81(0.76, 0.87)<0.001 *0.78(0.72, 0.84)<0.001 *0.85(0.75, 0.97)0.014 *0.84(0.73, 0.96)0.011 *
* Analysis of associated factors was conducted using negative binomial mixed models. RR, relative risk; aRR, adjusted relative risk. Statistical significance at the level of p < 0.05 is shown in bold text. Patients were assessed for 12 symptoms mentioned in Supplementary Table S1. Chalder fatigue score is only validated for patients aged >18 years (n = 3756); possible fatigue scores range from 0 (no fatigue) to 27 (worst possible fatigue). § The relative risk (RR) is the risk of an event in an experimental group relative to that in a control group. The 95% confidence interval (CI) is used to estimate the precision of the OR. Factors with significance level p < 0.05 in univariable analysis were included in the multivariable analysis of symptoms at 14-day follow-up. ** Adjusted relative risk (aRR) is the difference in increased risk of symptoms and fatigue score. †† Factors with significance level p < 0.05 in univariable analysis were included in the multivariable analysis of fatigue score at 14-day follow-up. ‡‡ COPD is chronic obstructive pulmonary disease. §§ SARS-CoV-2 spike protein antibody titers, log10 transformed. ¶¶ Neutralizing antibody titers, log10 transformed.
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Mongkolsucharitkul, P.; Surawit, A.; Pumeiam, S.; Sookrung, N.; Tungtrongchitr, A.; Phisalprapa, P.; Sayabovorn, N.; Srivanichakorn, W.; Washirasaksiri, C.; Auesomwang, C.; Sitasuwan, T.; Chaisathaphol, T.; Tinmanee, R.; Chayakulkeeree, M.; Phoompoung, P.; Tangjittipokin, W.; Senawong, S.; Sanpawitayakul, G.; Muangman, S.; Mayurasakorn, K.; on behalf of the Siriraj Population Health and Nutrition Research Group. SARS-CoV-2 Antibody Response against Mild-to-Moderate Breakthrough COVID-19 in Home Isolation Setting in Thailand. Vaccines 2022, 10, 1131. https://doi.org/10.3390/vaccines10071131

AMA Style

Mongkolsucharitkul P, Surawit A, Pumeiam S, Sookrung N, Tungtrongchitr A, Phisalprapa P, Sayabovorn N, Srivanichakorn W, Washirasaksiri C, Auesomwang C, Sitasuwan T, Chaisathaphol T, Tinmanee R, Chayakulkeeree M, Phoompoung P, Tangjittipokin W, Senawong S, Sanpawitayakul G, Muangman S, Mayurasakorn K, on behalf of the Siriraj Population Health and Nutrition Research Group. SARS-CoV-2 Antibody Response against Mild-to-Moderate Breakthrough COVID-19 in Home Isolation Setting in Thailand. Vaccines. 2022; 10(7):1131. https://doi.org/10.3390/vaccines10071131

Chicago/Turabian Style

Mongkolsucharitkul, Pichanun, Apinya Surawit, Sureeporn Pumeiam, Nitat Sookrung, Anchalee Tungtrongchitr, Pochamana Phisalprapa, Naruemit Sayabovorn, Weerachai Srivanichakorn, Chaiwat Washirasaksiri, Chonticha Auesomwang, Tullaya Sitasuwan, Thanet Chaisathaphol, Rungsima Tinmanee, Methee Chayakulkeeree, Pakpoom Phoompoung, Watip Tangjittipokin, Sansnee Senawong, Gornmigar Sanpawitayakul, Saipin Muangman, Korapat Mayurasakorn, and on behalf of the Siriraj Population Health and Nutrition Research (SPHERE) Group. 2022. "SARS-CoV-2 Antibody Response against Mild-to-Moderate Breakthrough COVID-19 in Home Isolation Setting in Thailand" Vaccines 10, no. 7: 1131. https://doi.org/10.3390/vaccines10071131

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