Abstract
Introduction
Real-time reverse transcriptase-polymerase chain reaction (rRT-PCR) of nasopharyngeal/ oropharyngeal swab has been the gold standard test for detection of SARS-CoV-2 infection The relationship between cycle threshold (Ct) values of rRT-PCR and severity of disease remain disputable and not clearly defined in COVID-19.
Methodology
This is a single-centered retrospective observational study conducted at Government Corona Hospital (GCH), Guindy, Chennai. In the present study, we compared the Ct value of rRT-PCR from nasopharyngeal swab specimens with a diverse range of symptoms and disease severity among 240 individuals who were hospitalized with COVID-19, viz., mild cases (MC; n = 160), moderately severe cases (MSC; n = 46) and severe cases (SC; n = 34) in the first and second waves of COVID-19 pandemic.
Results
The study included 240 hospitalized COVID-19 patients with a median age of 52 years (range 21 to 90 years). MC, MSC, and SC all had median Ct values of 25.0 (interquartile range – IQR 20.0 to 30.5), 29.5 (IQR 23.0 to 34.0), and 29.0 (IQR 24 to 37.5) for the ORF1ab gene. The Ct value differed significantly between mild vs moderate, and mild vs severe cases. The Ct value of SC group with co-morbidity of type 2 diabetes have a significant difference compared to non-diabetes group (p value <0.05). There was a significant difference in the median Ct value of ORF1ab gene among the MSC group and MC but not in the SC group in the first and second waves of the pandemic (p<0.05).
Conclusion
We conclude that SARS-CoV-2 Ct values of rRT-PCR alone does not have a role in aiding severity stratification among patients with COVID-19 since the viral dynamics and Ct value may vary due to the emerging variants that occur in different waves of the pandemic.
Keywords: Ct value, COVID-19, Sars-CoV-2, RT-PCR, COVID-diabetes, Co-morbidity
1. Background
Coronavirus disease 19 (COVID-19) is caused by a novel coronavirus referred as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [1]. SARS-CoV-2 contains a single-stranded, roughly 30 kb positive-sense RNA genome. The SARS-CoV-2 genome serves as an mRNA to translate two polyproteins from the ORF1a and ORF1b (open reading frame) region, which are then cleaved by two viral proteases into sixteen non-structural proteins (nsp). The ORF1a codes for nsp 1–11 and ORF1b codes for nsp 12–16, which occupy around 3/4th of the viral genome commencing from the 5′ end. The SARS-CoV-2 genome also codes four structural proteins (S - spike, E - envelope, M - membrane, N – nucleocapsid) and six accessory proteins (3a, 6, 7a, 7b, 8 and 9b), which occupy around 1/4th of the genome from the 3′end [2].
Real-time reverse transcriptase-polymerase chain reaction (rRT-PCR) of nasopharyngeal/ oropharyngeal swab has been the gold standard test for detection of SARS-CoV-2 infection [3]. The cycle threshold (Ct) value in Real-time PCR refers to the number of cycles required for the fluorescent signal to reach the threshold (i.e. exceed background signal). The rRT-PCR Ct value estimates the SARS-CoV-2 RNA copy numbers, with lower cycle threshold values suggesting higher viral copy numbers and vice versa. [4]. Among the SARS-related viral genomes, three regions have conserved sequences. They are RdRp gene (RNA-dependent RNA polymerase gene) in the ORF1ab region, the E gene, and the N gene. Among these genes, both the RdRp and E genes have high analytical sensitivity for detection. Thus, the COVID-19 testing assay is designed as a two-target system, where E gene detects universal SARS coronaviruses and a confirmatory testing with a second set of primers (using ORF1ab gene or RdRp gene), which detects only SARS-CoV-2 [3].
Severity of SARS-CoV-2 infection was assessed by various factors including clinical symptoms, oxygen saturation (SpO2), requirement for oxygen support, chest computed tomographic findings, biochemical parameters of elevated C-reactive protein (CRP) and LDH levels [4,5]. Chest computed tomography (CT) is widely used to diagnose pneumonia. Virus shedding in COVID-19 positive cases is believed to be very high during the first week of infection, with 7.11 × 108 RNA copies per ml on day 4, and that viral RNA remains detectable in throat swabs well into the second week of infection [6]. A significant correlation between Ct value and successful isolation of SARS-CoV-2 virus in cell culture has been reported, where samples with Ct values of 13–17 led to positive virus culture whereas those with Ct values equivalent or above 34 lacked infectious viral particles [7]. Our study aimed to determine if there exists an association between Ct value of SARS-CoV-2 rRT-PCR with clinical features and severity of COVID-19 disease among the hospitalized patients in the first and second waves of COVID-19 pandemic.
2. Methods
This is a retrospective observational study conducted at Government Corona Hospital (GCH), a tertiary COVID care hospital in Chennai, India. The samples were collected by trained healthcare workers during February 2021 (end of first wave) to March 2021 (beginning of second wave) as well as in the month of August 2021 (second wave). Nasopharyngeal swab (NP) swab samples were collected from 240 COVID-19 affected individuals on day 1 of admission at the Government Corona Hospital (GCH), Guindy, Chennai, India. NP swab samples were collected from COVID-19 patients in viral transport medium (VTM) and the samples were transported to the lab within 3 h of collection. All patients with COVID-19 diagnosis had COVID-19 confirmed based on rRT-PCR test done at an Indian Council of Medical Research (ICMR) approved laboratory or State Government Laboratory under the Greater Chennai Corporation (GCC) or based on Chest computed tomography (CT). The study protocol was approved by the Institutional Ethics Committee of ICMR-National Institute for Research in Tuberculosis (NIRT-IEC 2020 036) and ethics committee of Madras Medical College. The swab samples were collected with the informed consent of the study participants. Participants in the study who met the following criteria were classified as mild, moderately severe, or severe cases respectively if they were presented with: i) mild clinical symptoms without shortness of breath, dyspnea or abnormal chest imaging, ii) fever and evidence of lower respiratory disease during clinical assessment or imaging, and having an oxygen saturation (SpO2) <94% (range 90–94%) at room air, and iii) respiratory distress with oxygen saturation <90% at room air, requirement for mechanical ventilation, and/or admission to intensive care unit (ICU) [8]. Clinical, demographic and disease severity data collected for the main study were utilized for the purpose of this analysis.
Real-time RT-PCR (rRT-PCR) was performed at our laboratory again on all nasopharyngeal swab samples collected on day 1 of admission at the GCH, Guindy, Chennai for the enrolled participants. This was done to avoid discrepancy in collection of nasopharyngeal samples, extraction of viral RNA and rRT-PCR testing performed in different laboratories using different type of kits with different cut-off values for the COVID test done earlier. Viral RNA was extracted from nasopharyngeal swab samples using the GENETIX Purifier HT96 automated nucleic acid extraction system with the GeneMag viral RNA purification kit (Genetix Biotech, India). Two hundred microliters of nasopharyngeal swab specimen were used for extraction of viral RNA. Reverse transcription reaction followed by amplification of Sarbecovirus ‘E’ gene, SARS-CoV-2 specific ‘ORF1ab’ gene, and ‘RPP30’ gene (internal control) were performed by single step RT-PCR using COVIDsure Multiplex Real-time RT-PCR kit, Labsystems Diagnostics, Trivitron Healthcare, India (CE IVD marked; Validated and approved by ICMR, Government of India) according to manufacturer's instructions. Each 20 µl of reaction mixture contained 10 µl of 2X RT-PCR mix, 2 µl of primer-probe mix (ORF1ab-FAM; E-HEX; RPP30-ROX), 3 µl of RNAse-free water, and 5 µl of viral RNA template. RT-PCR was set for 40 cycles. The cycling conditions were 15 min at 46 °C for reverse transcription, 2 min at 95 °C for PCR initial activation followed by 40 cycles of 10s at 95 °C and 30s at 58 °C. The RT-PCR reactions were performed on a Bio-rad CFX-96 Real-time PCR Detection System. The Ct value ≤36 at all genes (‘E’ gene, ‘ORF1ab’ gene and ‘RPP gene’) was required for a sample to be characterized as positive. Correspondingly, Ct value of ‘ORF1ab’ and ‘E’ genes either greater than 36 or nil (no amplification), but Ct value of ‘RPP’ gene ≤36 would be considered as negative. When there was no amplification in rRT-PCR, the detection limit of Ct = 40, which was used to indicate negative samples in subsequent analysis.
A radar chart was prepared by plotting the Ct values of the mild, moderate and severe cases using Microsoft-Excel 2010. Continuous variables were described using medians and interquartile ranges (IQR) and compared using Mann-Whitney U test (non-parametric data). Categorical data were expressed as total numbers and percentages, and comparison between two groups was done using Chi-square test with Yates correction or Fisher's exact test. Multiple comparisons between groups were done using Kruskal-Wallis test with Dunn's multiple comparison test. All tests were two-tailed; p value of less than 0.05 was considered to be statistically significant. Statistical analyses were performed by using Prism 8.0 (Graph pad).
3. Results
Two hundred and forty patients with COVID-19 were included for this analysis. Of these, 160 belonged to the mild (MC), 46 to the moderately severe (MSC), and 34 to the severe (SC) COVID-19 categories, respectively. Age of the COVID-19 patients ranged from 21 years to 90 years, with a median age of 52 years. Of the 160 COVID-19 patients with mild symptoms, 109 males and 51 females were present. There were 23 males and 23 females among the MSC. There were 21 males and 13 females among the Severe COVID-19 cases with acute respiratory distress syndrome (ARDS) [Table 1 ].
Table 1.
Clinical profile, demographic characteristics and disease severity of the study participants
Table 1. Clinical profile, demographic characteristics and disease severity of COVID-19 patients.
| Clinical features | Mild COVID-19 (n = 160) | Moderate COVID-19 (n = 46) | Severe COVID-19 (n = 34) | Chi square test (χ) value | Statistical significance |
|---|---|---|---|---|---|
| Age (years) | N.A† | p = 0.28, ns | |||
| <30 | 16 (10) | 1 (2.1) | 1 (2.9) | ||
| 31–40 | 27 (16.8) | 6 (13) | 3 (8.8) | ||
| 41–50 | 38 (23.7) | 11 (23.9) | 9 (26.4) | ||
| 51–60 | 35 (21.8) | 15 (32.6) | 9 (26.4) | ||
| 61–70 | 31 (19.3) | 6 (13) | 8 (23.5) | ||
| >71 | 13 (8.1) | 7 (15.2) | 4 (11.7) | ||
| Gender | p = 0.076 | ||||
| Male | 109 (68.1) | 23 (50) | 21 (61.8) | 5.14 | |
| Female | 51 (31.8) | 23 (50) | 13 (38.2) | ||
| Ct value | p = 0.29, ns | ||||
| <24 | 72 (45.0) | 15 (32.6) | 10 (29.4) | ||
| >24 | 76 (47.5) | 26 (56.5) | 17 (50) | ||
| Ct value not detected | 12 (7.5) | 05 (10.8%) | 07 (20.5) | 5.35 | p = 0.067, ns |
| Median Ct (25–75th percentile) and range | 25.0 (IQR 20.0 to 30.5) | 29.5 (IQR 23.0 to 34.0) | 29.0 (IQR 24 to 37.5) | ||
| Co-morbidities | |||||
| Type 2 Diabetes | 71 (44.3) | 21 (45.6) | 18 (52.9) | 0.829 | p = 0.66, ns |
| Hypertension | 40 (25) | 14 (30.4) | 15 (44) | 5.08 | p = 0.078, ns |
| Onset of symptoms (days) | 2.72 (range 0 to 10) | 5.06 (range 2 to 7) | 5.3 (range 3 to 7) | N.A †† | p <0.0001 |
| Range | 1 to 10 days | 1 to 10 days | 2 to 10 days | ||
| Symptoms | |||||
| Fever | 68 (42.5) | 33 (71.7) | 22 (64.7) | 15.09 | p <0.001 |
| Cough | 70 (43.7) | 26 (56.5) | 21 (61.7) | 5.01 | p = 0.081, ns |
| Sore throat | 43 (26.8) | 13 (28.2) | 14 (41.1) | 2.79 | p = 0.246, ns |
| myalgia | 40 (25) | 18 (39.1) | 15 (44.1) | 6.88 | p = 0.032 |
| dyspnea | 8 (5) | 11 (23.9) | 9 (26.4) | 20.8 | p <0.001 |
| diarrhea | 6 (3.75) | 3 (6.5) | 3 (8.8) | 1.79 | p = 0.40, ns |
| Anosmia or taste abnormality | 42 (26.2) | 14 (30.4) | 11 (32.3) | 0.69 | p = 0.70, ns |
| Loss of smell | 39 (24.3) | 11 (23.9) | 9 (26.4) | 0.08 | p = 0.96, ns |
Fisher's exact test was used for analysis.
Mann Whitney U test was used for analysis.
In 148 of 160 (92.5%) mild, 41 of 46 (89.1%) moderate, and 27 of 34 (79.4%) severe COVID-19 cases, SARS-CoV-2 viral RNA was found. MC, MSC, and SC all had median Ct values of 25.0 (interquartile range (IQR) 20.0 to 30.5), 29.5 (IQR 23.0 to 34.0), and 29.0 for the ORF1ab gene (IQR 24 to 37.5). There was a significant difference in Ct value between the MC and MSC groups, as well as between the MC and SC groups, but not between the MSC and SC groups, when we analysed the Ct value of the ORF1ab gene among mild, moderate, and severe COVID-19. The Ct value of ORF1ab gene among the mild, moderate, and severe COVID-19 cases is displayed in Fig 1 a. We also compared the Ct values of the three groups by plotting a radar chart. We observed that the Ct values of the moderate and severe COVID-19 cases clustered in a particular region of the plot. While, the Ct value of the mild COVID-19 was found to be scattered uniformly throughout the axes (Fig 1b).
Fig 1.
a. Ct value of ORF1ab gene and severity of COVID-19 disease. Ct value of ORF1ab gene in the scatter plot was compared between the mild (n = 160), moderate (n = 46) and severe (n = 34) groups. The Ct cut off value of rRT-PCR of ORF1ab gene was 36. In 12 (7.5%) of the MC, 05 (10.8%) of the moderate, and 07 (20.5%) of the severe cases, Ct value was not detected. There was a significant difference in Ct value between MC and MSC (Mann Whitney U test, p value = 0.02), and the differences between mild and severe cases were highly significant (Mann Whitney U test, p value = 0.005). Fig 1b. Ct value of mild (n = 160), moderate (n = 46) and severe COVID-19 (n = 34) cases presented in a radar chart. The serial numbers of the mild COVID-19 cases were denoted in outer circles. The serial numbers were not mentioned for moderate and severe COVID-19 cases but are included within the chart. The Ct values from 0 to 40 are marked in inner circles. Each Ct value of a sample is denoted as a dot which is connected by lines. Lines connecting the dots are in green color for mild COVID-19 cases, blue in color for moderate COVID-19 cases, and yellow in color for severe COVID-19 cases.
Majority of the COVID-19 patients presented with fever, dry cough, sore throat and myalgia. The other symptoms reported were fatigue, breathlessness, anosmia and loss of sense of taste. The clinical characteristics and demography of the mild, moderate, and severe COVID-19 cases are presented in Table 1. The onset of symptoms was significantly late in both moderate and severe COVID-19 compared to mild (p <0.001). Symptoms such as cough, sore throat, diarrhea, anosmia, and loss of smell were commonly present among different groups COVID-19, irrespective of the severity of disease. Fever (p<0.001), myalgia (p = 0.032), and dyspnea (p<0.001) were significantly associated with moderate and severe COVID-19 cases.
Males with mild COVID-19 cases had a median Ct value of 25 (IQR 20.0 to 31.0), while females had a Ct value of 26 (IQR 21.0 to 30.0). However, the median Ct value for males in the moderately severe group was 31.0 (IQR 24.0 to 35.0), while the median Ct value for females in this group was 28.0 (IQR 21.0 to 31.0). In contrast, the median Ct values for the severe COVID-19 group were 27.0 (IQR 22.0 to 34.5) for males and 33.0 (IQR 26.0 to 38.0) for females, respectively. The analysis revealed that there was a not a significant difference in Ct value between males and females in the mild, moderate, and severe COVID-19 groups. Fig 2 a represents the findings.
Fig 2.
a. Ct value of ORF1ab gene was compared between males and females in the mild, moderate and severe COVID-19 cases. In the scatter plot with bar, there was a not a significant difference in Ct value between males and females in MC, MSC, and SC. Fig2b. Ct value of ORF1ab gene was compared with severity of COVID-19 in diabetic vs non-diabetic groups. The comparison of Ct value between the diabetic and non-diabetic groups in the violin plot indicated that there was a significant difference in Ct value between the diabetic and non-diabetic groups in severe COVID-19; Mann Whitney U test, p value = 0.015 (* p value < 0.05).
The comorbid conditions commonly present in the COVID-19 patients were type 2 diabetes and hypertension. Among mild COVID-19 patients, 71 of 160 (44.3%) individuals had type 2 diabetes, and 40 of 160 (25%) had hypertension. Among moderate COVID-19 patients, 21 of 46 individuals (45.6%) had type 2 diabetes, and 14 of 46 (30.4%) had hypertension. Among severe COVID-19 patients, 18 of 34 (52.9%) had type 2 diabetes and 15 of 34 (44%) had hypertension. The proportion of patients with type 2 diabetes comorbidity was not different among mild, moderate and severe COVID-19 cases.
The Ct value of ORF1ab gene was compared between individuals with diabetes and non-diabetes among mild, moderate, and severe COVID-19. The results indicated that there was a significant difference in Ct value among severe COVID-19 category with diabetes with a median Ct value of 25 (IQR 20.75 to 33.25) and non-diabetes with a median Ct value of 33 (IQR 27.0 to 40.0) (p value = 0.015) [Fig 2b].
Finally, Ct value of ORF1ab gene among mild, moderate, and severe COVID-19 between the first and second waves of COVID-19 were also compared. The median Ct value in the first and second waves among mild COVID-19 were 27.0 and 24.0, moderate COVID-19 were 31 and 24.0 and severe COVID-19 were 33.5 and 27.5 respectively. The findings revealed that during the first and second waves of the pandemic, there was a highly significant difference in Ct values among moderate COVID-19 patients (p value = 0.003) and a substantial difference in Ct values among mild COVID-19 patients (p value = 0.023) [Fig 3 ]. However, there was no appreciable difference in the Ct levels of severe COVID-19 patients between the first and second waves of the pandemic.
Fig 3.
Comparing the Ct value of ORF1ab gene with severity of COVID-19 disease in the 1st and 2nd wave of the pandemic. In the scatter plot with bar, there was a significant difference in mild COVID-19 (Mann-Whitney U test, p value = 0.023), and a highly significant difference in moderate COVID-19 (p value = 0.003) between the 1st and 2nd waves of the pandemic.
4. Discussion
In this study, we investigated whether the Ct values of rRT-PCR test done on nasopharyngeal swab specimens (NP) of SARS-CoV-2 infected individuals would serve as a useful marker for grading COVID-19 disease severity among those getting hospitalized for treatment of COVID-19. Though there was a significant difference in Ct value between mild and moderate COVID-19 groups as well as mild and severe COVID-19 groups, the Ct value was not related to viral load or severity of COVID-19 disease among mild, moderate, and severe groups. In fact, the Ct value of mild COVID-19 was low (median Ct = 25.0) compared to moderate (median Ct 29.5) and severe (median Ct 29.0) categories of COVID-19. This was mainly attributed to the number of days of onset of symptoms and COVID testing done by the individuals among the different groups. Age of the COVID-19 patients among MC, MSC, and SC in the study were not significantly different. The median Ct value of mild COVID-19 cases was similar in both males and females in MC, whereas there was a minor difference in MSC, and a considerable difference in SC. The Ct value of MSC in females was slightly low compared to males. Conversely, the Ct value of SC in females was considerably high compared to males. This implies gender differences may play a role in moderately severe COVID-19 and severe COVID-19. Other studies have also implicated gender differences in immune response to various pathogens [9,10].
In this context, the time of sampling since onset of symptoms has a strong correlation with Ct value. In the present study, the mean time of onset of symptoms for the three groups significantly varied between MC, MSC and SC groups (p <0.0001). The duration of illness prior to testing was significantly lower in the MC group as compared to the MSC and SC groups. Though these patients were able to seek medical attention promptly, it is likely that some of these individuals could have got tested after trying out some self-medication or home remedies. We therefore are of the opinion that the timing of sample collection is an important factor that should be controlled while correlating Ct values with the disease severity. The results of the RT-PCR test and its interpretation are also influenced by laboratory parameters such as sample collection, sample volume, and laboratory methods for viral RNA extraction and rRT-PCR [11,12]. For example, the quality and volume of nasal samples vary considerably between two samplings by the same collecting person, thus reflecting a difference in Ct value. Similarly differences in the viral RNA extraction, RT-PCR methods and kits from various vendors are likely to influence the test results [12]. However, the variations are avoided in our study since we employed a uniform protocol for both viral RNA extraction and rRT-PCR.
The Ct value of severe COVID-19 was associated with early Ct value in type 2 diabetes comorbidity compared to late Ct value in non-diabetes. To the best of our knowledge this is one of the early reports that shows the difference in Ct values between diabetes and non-diabetes in severe COVID-19 group. However, the following factors must be considered for correlating the viral load (low Ct values) with disease severity, viz, host factors, viral dynamics and shedding, and sampling issues. Numerous host factors, including the underlying illness state and genetic factors, are known to affect the severity and course of the disease [13,14]. We therefore are of the opinion that Ct values of different individuals do not reflect disease severity at the same level.
Viral factors such as viral dynamics, viral viability, infectivity and virus shedding also play a vital role in influencing the Ct values [15].
There was a significant difference in the median Ct value of ORF1ab gene among the MSC group and MC but not in the SC group in the first and second waves of the pandemic. Moderately severe and severe COVID-19 patients in the present study were higher in the second wave compared to the first wave of the pandemic. Moderately severe COVID-19 patients were significantly associated with late Ct value in the first wave and early Ct value in the second wave. The difference in the Ct value was mainly attributed to the high frequency of delta variants (B.1617.2) in the second wave of the pandemic [16]. The utility of COVID-19 PCR Ct values in patient management and disease severity prediction has continued to remain disputable. One study reported that viral recovery in cell culture was not possible in samples with Ct value greater than 24, or symptom onset to test greater than 8 days [13]. While, Gniazdowski et al. reported that virus growth in cell culture was highly effective with 76.7% positive isolation rate from samples with Ct values between 10 and 20, and reduced to 24% for values between 20 and 30 and almost nil for values between 30 and 40 [17]. There are retrospective studies which found a significant association between low Ct values and severe COVID-19 related outcomes [18,19]. Whereas, other studies observed no correlation between rRT-PCR Ct values and disease severity [20,21].
An interesting observation in our analysis was that the Ct values of nasopharyngeal SARS-CoV-2 RNA was significantly higher between those with type 2 diabetes and non-diabetes in the SC group. In addition, MC and MSC groups were significantly associated with early Ct value in the 2nd wave of COVID-19 pandemic. However, this finding is not seen in severe COVID-19 group. We conclude that SARS-CoV-2 Ct value alone does not have a role in aiding severity stratification among patients with COVID-19 since the viral dynamics and Ct value may vary due to the emerging variants in different waves of the pandemic.
Declarations
Ethical approval: The study protocol was approved by the Institutional Ethics Committee of National Institute for Research in Tuberculosis (NIRT-IEC 2020 036) and Ethics committee of Madras Medical College, Chennai. Informed written consent was obtained from study participants.
Funding
The study was funded by ICMR – NIRT Intramural funding
CRediT authorship contribution statement
Sudhakar Natarajan: Conceptualization, Methodology, Resources, Formal analysis, Data curation, Investigation, Writing – original draft, Writing – review & editing, Funding acquisition. Mohan Ranganathan: Data curation, Investigation, Resources, Writing – review & editing. P L Natarajan: Data curation, Resources, Writing – review & editing. Manohar Nesakumar: Data curation, Investigation, Writing – original draft, Writing – review & editing. S Anbalagan: Investigation, Writing – review & editing. K Lucia Precilla: Data curation, Writing – review & editing. H Hemalatha: Data curation, Writing – review & editing. M Kannan: Data curation, Resources. G Narendran: Resources, Writing – review & editing. S Mahalakshmi: Data curation, Investigation, Resources, Writing – review & editing. Gomathi Karmegam: Data curation, Investigation, Resources, Writing – review & editing. Lakshmi Prakash: Data curation, Investigation, Resources, Writing – review & editing. K Narayanasamy: Resources, Investigation, Writing – review & editing. Luke Elizabeth Hanna: Resources, Funding acquisition, Supervision, Writing – review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
We acknowledge the support provided by Indian Council of Medical research (ICMR) - National Institute for Research in Tuberculosis (NIRT), Chetpet, Chennai and we thank ICMR-NIRT for intramural funding of the study. We thank the Department of Science and Technology (DST), Govt. of India for providing JRF fellowship to MR in a DST-SYST funded project. We acknowledge all the healthcare workers involved in diagnosis and treatment of COVID-19 patients at Government Corona Hospital (GCH), Guindy, Chennai.
Availability of data and materials
All the data presented in the manuscript are available within the manuscript.
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