Seasonality, molecular epidemiology, and virulence of Respiratory Syncytial Virus (RSV): A perspective into the Brazilian Influenza Surveillance Program

Lucas A Vianna; Marilda M Siqueira; Lays P B Volpini; Iuri D Louro; Paola C Resende

doi:10.1371/journal.pone.0251361

. 2021 May 18;16(5):e0251361. doi: 10.1371/journal.pone.0251361

Seasonality, molecular epidemiology, and virulence of Respiratory Syncytial Virus (RSV): A perspective into the Brazilian Influenza Surveillance Program

Lucas A Vianna ^1,^2,^*, Marilda M Siqueira ³, Lays P B Volpini ⁴, Iuri D Louro ², Paola C Resende ³

Editor: Baochuan Lin⁵

PMCID: PMC8130917 PMID: 34003843

Abstract

Background

Respiratory Syncytial Virus (RSV) is the main cause of pediatric morbidity and mortality. The complex evolution of RSV creates a need for worldwide surveillance, which may assist in the understanding of multiple viral aspects.

Objectives

This study aimed to investigate RSV features under the Brazilian Influenza Surveillance Program, evaluating the role of viral load and genetic diversity in disease severity and the influence of climatic factors in viral seasonality.

Methodology

We have investigated the prevalence of RSV in children up to 3 years of age with severe acute respiratory infection (SARI) in the state of Espirito Santo (ES), Brazil, from 2016 to 2018. RT-qPCR allowed for viral detection and viral load quantification, to evaluate association with clinical features and mapping of local viral seasonality. Gene G sequencing and phylogenetic reconstruction demonstrated local genetic diversity.

Results

Of 632 evaluated cases, 56% were caused by RSV, with both subtypes A and B co-circulating throughout the years. A discrete inverse association between average temperature and viral circulation was observed. No correlation between viral load and disease severity was observed, but children infected with RSV-A presented a higher clinical severity score (CSS), stayed longer in the hospital, and required intensive care, and ventilatory support more frequently than those infected by RSV-B. Regarding RSV diversity, some local genetic groups were observed within the main genotypes circulation RSV-A ON1 and RSV-B BA, with strains showing modifications in the G gene amino acid chain.

Conclusion

Local RSV studies using the Brazilian Influenza Surveillance Program are relevant as they can bring useful information to the global RSV surveillance. Understanding seasonality, virulence, and genetic diversity can aid in the development and suitability of antiviral drugs, vaccines, and assist in the administration of prophylactic strategies.

Introduction

Respiratory Syncytial Virus (RSV) is the most common pathogen associated with acute respiratory tract infections (ARTI), as well as the main cause of bronchiolitis and pneumonia in infants and small children [1]. RSV infection can cause a range of symptoms, varying from mild upper respiratory tract illness to severe lower respiratory tract infection [2]. The reason for different outcomes is still unclear, however, it can be related to the underlying conditions, genetic or acquired host factors, and/or viral characteristics [3, 4]. Some studies have evaluated the association between viral load and disease severity with significant associations [4, 5]. However, most of these studies did not use standardized methods of viral load measurement, therefore, this relationship must be more carefully evaluated. Understanding the role of the viral load in RSV infection may be a tool to establish its relationship with disease progression, severity, clinical outcome, and drug intervention timeframe [6].

RSV treatment is based only on supportive care and infection prevention is limited to passive immunoprophylaxis (Palivizumab) and case isolation [2]. No approved RSV vaccine is available, but promising candidates are currently in development and in advanced clinical trial phases [7].

RSV strains can be classified into two serogroups: RSV-A and RSV-B [8]. The potential virulence attributed to a specific group remains controversial: some authors have pointed RSV-A [9, 10] or RSV-B [11] as the most virulent subtype, while another study has not found significant differences between them [12]. Multiple genotypes were described for RSV-A and RSV-B, based on the gene G second hypervariable region (HVR-2) [13, 14]. In the past two decades, important genetic changes occurred with the emergence of new RSV-A and RSV-B genotypes: RSV-A ON1 containing a duplication of 72 nucleotides, and RSV-B BA with a duplication of 60 nucleotides in the HVR-2 gene G [14, 15]. These genotypes replaced previous ones and have spread globally. Understanding their genetic diversity may reveal the virus’s ability to cause re-infections throughout life, and help in the development of antiviral drugs, diagnostic assays, and vaccines [13].

In 2017, the World Health Organization (WHO) launched the Global Respiratory Syncytial Virus Surveillance Pilot to test the feasibility of using the Global Influenza Surveillance and Response System (GISRS) for RSV surveillance without adversely affecting influenza surveillance [16]. This pilot study results from the global concern about RSV’s impact on public health. Brazil, one of four countries in the Americas included in the pilot, has a remarkable respiratory virus surveillance program, however, more data are required for a better understanding of factors such as RSV circulation, evolution, and pathogenicity. In this study, we used the Brazilian Influenza Surveillance Program to analyze the local prevalence of RSV in children with SARI and to evaluate which factors are potentially associated with disease severity. We also explored the viral seasonality and investigated the influence of climatic factors on circulation. Finally, we conducted a phylogenetic study to understand how the local genetic diversity of RSV behaves when compared to what is observed in the rest of the world.

Materials and methods

Population sampling, study period, and location

This study is a retrospective investigation of respiratory samples (nasopharyngeal secretions, tracheal and bronchoalveolar aspirates, and bronchoalveolar lavages) collected from the Brazilian Influenza Surveillance Program over 34 months. (March 7th, 2016, to December 14th, 2018). A total of 632 samples collected from pediatric patients (from 0 to 36 months old) classified as SARI, residents of 60 municipalities in the state of Espirito Santo (ES), were enrolled in this study. ES is located in southeastern Brazil (S1 Fig) and has a territory of 46,074.447 km², with a population of approximately 4,1 million inhabitants [17]. These samples were screened by real-time RT-qPCR for RSV and Influenza A/B at the ES Central Public Health Laboratory (LACEN/ES), one of 26 Brazilian laboratories that integrate the Brazilian Ministry of Health Influenza Surveillance Program.

RSV and influenza detection and subtyping

Nucleic acids were extracted from respiratory samples using the PureLink^™ Viral RNA/DNA Mini Kit (Invitrogen^®, Thermo Fisher Scientific©), according to the manufacturer’s protocol. All samples were initially tested for Influenza A and B in a TaqMan^® one-step real-time RT-PCR (RT-qPCR) assay using specific primers and probes for influenza (CDC, USA), according to the manufacturer’s recommendations. Additionally, an RT-qPCR assay was performed to identify positive RSV cases using a GoTaq^® Probe 1-Step RT-qPCR Kit (Promega, Madison, WI, EUA). RSV positive samples (i.e. those with cycle threshold [CT] ≤ 40) were subtyped using specific primers and probes for RSV-A and RSV-B N genes. In parallel, Ribonuclease P RNA (RNase P) was used as an internal control for each sample and, in all batches, RNA extraction negative control (MOCK) and a PCR negative control (NTC) were used. All primers and probes are described in the S1 Table.

Clinical and epidemiological data collection

Clinical and epidemiological data were retrieved mainly from the Brazilian Notifiable Diseases Information System (SINAN) database and, in some cases,—when the SINAN form was incomplete—patients’ Medical Records were assessed to fill in missing information. The main information retrieved from SINAN were: 1) clinical outcome (recovery or death); 2) hospitalization length of stay; 3) need for oxygen administration and type (invasive or not invasive); 4) intensive care unit (ICU) need and length of stay; 5) clinical characteristics (fever, cough, dyspnea, O₂ saturation, respiratory distress, comorbidities), and 6) epidemiological and demographical features (age, town or area of residence).

We have used the Brazilian Ministry of Health’s definition of SARI, which is: hospitalized patients with fever and cough or sore throat, and presenting dyspnea or O₂ saturation <95%, or respiratory distress [18]. A Clinical Severity Score (CSS) was adapted from Martinello et al. [19]. A 6-point scale (0 to 5 spectrum) was used, where 0 indicated the mildest condition and 5 indicated the most severe. ICU admission, hospitalization length of stay ≥5 days, oxygen saturation ≤95%, and oxygen therapy noninvasive methods accounted for 1 point each. Two points were assigned for mechanical ventilation.

Viral load quantification

RSV viral load was determined by RT-qPCR using a protocol adapted from Álvarez-Argüelles et al. [20], including a synthetic β-globin dsDNA as a template. To quantify the RSV copy number, expressed in copies per cell (c/c), we designed a dsDNA containing the annealing regions of RSV primers and probe, as well as the upstream and downstream regions (150 bp). This synthetic DNA was incorporated into a pMA-T plasmid, which was used in the RT-qPCR. Standard curves for absolute quantification of RSV and β-globin gene were generated by 10-fold serial dilutions (10⁶−10¹ gene copies), in triplicate. The RSV primers, probe, and thermal cycling protocol adopted were the same used in the diagnostic phase. β-globin primers and probe are listed in the S1 Table. All amplification assays were carried out in an ABI 7500 equipment (Applied Biosystems, Foster City, CA, USA). The viral load status was compared with different clinical features and epidemiological data.

Climate data collection

Climate data (precipitation, temperature, and humidity) of five cities—representing the different geographic regions of the state—were collected daily and kindly provided by the Capixaba Institute of Research, Technical Assistance, and Rural Extension (INCAPER), Vitoria, Espirito Santo, Brazil. The weekly average was accessed by assembling daily data from all collection sites for each epidemiological week (EW). The definition of the RSV epidemic period was based on a previously described protocol [21], which considers RSV outbreak onset, peak, and end. Seasonality onset was defined as the first of 2 consecutive weeks when ≥10% of tested samples for respiratory pathogens were positive for RSV. Similarly, RSV season end was defined when the proportion of positive RSV tests fell below 10% for two consecutive weeks. Peak was determined as the week when the maximum number of RSV positive cases occurred [21].

Partial amplification and sequencing of glycoprotein gene

RSV-A and RSV-B positive samples were selected for sequencing based on the following criteria: a) cycle threshold (ct) value less than 30, due to the difficulty in sequencing samples with ct higher than this; b) representativeness by collection date; c) distinct clinical outcomes; and d) different viral load values.

The partial gene G amplification (about 730 bp) was performed at LVRS/IOC/FIOCRUZ, the National Influenza Center, by conventional RT-PCR, using the QIAGEN OneStep RT-PCR Kit (Qiagen) and a pair of primers (S1 Table) for each subtype. The reverse transcription was performed at 55°C for 30 minutes and the cDNA was amplified by PCR (40 cycles of 94°C/30 seconds, 60°C /1 minute, 72°C/1 minute and a final extension at 72°C/10 minutes). Amplification was confirmed in a 1% agarose gel. DNA was purified using an ExoSap-IT Kit (Affymetrix, Inc., USA) and submitted for sequencing reaction using a BigDye^™ Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems, Foster City, CA, USA) and primers at 3.2 μmolar. The reads were obtained in the ABI 3130XL Genetic Analyzer (Applied Biosystems). Consensus sequences were built from electropherograms comparison with a reference sequence in the software Sequencher 5.1 (Gene Codes Corporation, Ann Arbor, MI, USA). The adopted nomenclature pattern hereon was “hRSV subtype/country/ES-sample number/year.”

RSV genotyping and gene G phylogenetic reconstruction

RSV-A and RSV-B gene G DNA sequences (711 bp and 726 bp, respectively) were used to reconstruct phylogenetic relationships. Genotyping was based on gene G HVR-2, using RSV-A and RSV-B sequences (336 bp and 318 bp, respectively). Reference sequences of previously described genotypes are shown in the S2 Table. Additionally, to place our sequences in a global context we performed a BLAST search (Basic Local Alignment Search Tool), available at https://blast.ncbi.nlm.nih.gov/Blast.cgi. These sequences (S3 Table) were labeled with country of origin and collection year, and those with more than 99.5% genetic similarity using the CD-HIT tool (http://weizhongli-lab.org/cd-hit/servers.php) were removed from the final dataset. Alignments were conducted using Muscle algorithm, via MEGA 6.0 software [22], and, when necessary, they were adjusted manually. The phylogenetic trees were constructed using the Maximum Likelihood (ML) method, complete deletion for gap or missing data treatment, and 1000 replicates of bootstrap probabilities tools, and analyzed using the Mega 6.0 software. General Time Reversible + Gamma (GTR+G) was the nucleotide substitution model elected for all analyses on JModelTest software, except for RSV-A, where the Tamura-Nei + Gamma (TrN+G) substitution model nucleotide recommended for the analysis was used [23]. Mega 6.0 software was employed to calculate the average pairwise distance (p-distance) and to compare the amino acid changes between Brazilian samples and the reference sequences of ON1 (JN257693) and BA (AY333364).

Statistical treatment

Statistical analyses were performed using SPSS 20.0 (SPSS, Inc., Chicago, IL) and R v.3.4.4 software. Chi-square, Fisher exact, Mann–Whitney, Kaplan-Meier, and Kruskal Wallis were used whenever appropriate. The Cox regression model was used to assess whether the viral load had a statistically significant effect on length of stay in ICU, and Schoenfeld Residuals were used to check the proportional hazards assumption. To test the association between climate data and RSV circulation, we performed the Spearman correlation test. A p-value of less than 0.05 was considered statistically significant.

Ethics statement

This project was approved by the Human Research Ethics Committee of the Health Sciences Center of the Federal University of Espirito Santo (UFES), under the number: 018577/2018; CAAE: 84633518.1.0000.5060. The need for consent from parents or guardians was waived by the ethics committee.

Results

RSV clinical and epidemiological data

A total of 632 respiratory samples collected from children under 3 years of age were tested by RT-qPCR for Influenza A, Influenza B, and RSV. RSV is the most prevalent pathogen found in these samples (56%; 352/632) (Table 1). From the RSV positive cases, 51% (180/352) were RSV-A, 42% (147/352) were RSV-B, and co-detections with both subtypes were found in 1.4% (5/352). Twenty samples could not be subtyped (5.7%). Influenza frequency was 7.4% (47/632), of which 74% (35/47) were Influenza A H1N1 pdm09, 15% (7/47) were H3N2, and 11% (5/47) were Influenza B. The median age was 4 months old (1–11.0 interquartile range; IQR). Of the positive cases, 99.7% (351/352) were classified as SARI and 14 deaths (4%) were reported.

Table 1. Number of tested samples, RSV positivity, subtype prevalence, and demographic data from each year and the whole study period.

	2016 n (%)	2017 n (%)	2018 n (%)	2016–18 n (%)
General data
Sample n°	251/632 (40%)	135/632 (21%)	246/632 (39%)	632/632 (100%)
RSV +	155/251 (62%)	80/135 (59%)	117/246 (48%)	352/632 (56%)
RSV -	96/251 (38%)	55/135 (41%)	129/246 (52%)	280/632 (44%)
Flu +	27/251 (11%)	6/135 (4%)	14/246 (6%)	47/632 (7%)
RSV+ deaths	6/155 (4%)	5/80 (6%)	3/117 (3%)	14/352 (4%)
Subtyped samples	141/155 (91%)	78/80 (98%)	113/117 (97%)	332/352 (94%)
Subtypes
RSV-A	58/141 (41%)	14/78 (18%)	108/113 (96%)	180/352 (51%)
RSV-B	80/141 (57%)	63/78 (81%)	4/113 (4%)	147/352 (42%)
RSV-A and RSV-B	3/141 (2%)	1/78 (1%)	1/113 (1%)	5/352 (1.4%)
Demographic data (RSV+)
Median age (months)	4 (1–12.0)	4 (1–10.5)	3 (1–8.0)	4 (1–11.0)
Gender
Male	72/155 (46%)	49/80 (61%)	61/117 (52%)	182/352 (52%)

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Table 2 shows patients’ clinical features of RSV+ and subtypes. The most frequent symptom reported was cough (93%, 318/341), followed by respiratory distress (88%, 269/307), and fever (86%, 288/336). Seventy-four percent (252/342) of the children needed oxygen therapy and 38% (95/252) of these required mechanical ventilation. The median hospitalization length of stay was 8 (6–14 IQR) days. Intensive care was needed for 61% (202/333) of patients and the median number of days in ICU was 6 (3–10 IQR). The Kaplan-Meier test was used as a survival analysis technique and revealed that patients’ recovery took, on average, 8 days from the date of admission to the ICU (S4 Fig and S5 Table).

Table 2. Summary of clinical and epidemiological data by RSV+ and each subtype.

	RSV+ n (%)	RSV-A n (%)	RSV-B n (%)	p-value
Demographic profile
Sample number	352	180	147
Age
Median age: months (IQR¹)	4 (1–11)	4 (1–10.0)	4 (1–12.5)	0.78
Gender
Male (%)	182/352 (52%)	92/180 (51%)	78/147 (53%)	0.725
Clinical profile
Fever	288/336 (86%)	147/174 (84%)	124/139 (89%)	0.223
Cough	318/341 (93%)	162/176 (92%)	134/142 (94%)	0.418
Dyspnea	251/331 (76%)	135/172 (78%)	97/136 (71%)	0.148
O₂ saturation ≤95%	169/277 (61%)	101/150 (67%)	56/109 (51%)	0.009
Respiratory distress	269/307 (88%)	154/167 (92%)	96/120 (80%)	0.002
O₂ Therapy	252/342 (74%)	138/177 (78%)	98/143 (68%)	0.092
Invasive	95/252 (38%)	56/138 (41%)	33/98 (34%)
Noninvasive	157/252 (62%)	82/138 (59%)	65/98 (66%)
Intensive Care	202/333 (61%)	113/168 (67%)	78/142 (55%)	0.03
Median hospitalization days	8 (6–14)	9 (6–15)	8 (5–14.0)	0.15
Median days in Intensive Care	6 (3–10)	7 (4–11.0)	6 (3–9)	0.13
Deaths RSV+	14/352 (4%)	3/180 (2%)	8/147 (5%)	0.07

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¹IQR: interquartile range.

Statistically significant values are highlighted in bold. Although the study included 352 patients with RSV, it is possible to observe that the denominators in the clinical profile differ from this number. This occurred because not all clinical data were recorded for all children.

When compared to RSV-B, patients affected by RSV-A showed a higher frequency of respiratory distress (92% vs 80%, p = 0.002), and more often manifested O₂ saturation ≤95% (67% vs 51%, p = 0.009) and higher requirement for intensive care (67% vs 55%, p = 0.03). Our data also indicate that patients affected by RSV-A stayed one day longer in the hospital and intensive care units than those affected by RSV-B, however, these data were not statistically significant. Lastly, the RSV-A viral load showed more than twice the number of virus copies per cell (median = 57.41 copies/cell) than RSV-B (median = 27.35 copies/cell). RSV-A CSS median was 4 and RSV-B’s was 3, and children infected by RSV-A were most frequently classified in higher severity scores than those infected by RSV-B (Table 3).

Table 3. Clinical Severity Score (CSS): Scores varied from 0 to 5.

Clinical Severity Score (CSS)
CSS	RSV-A n (%)	RSV-B n (%)	p-value	Viral load median (IQR)	n	p-value
0	1 (1%)	10 (15%)	0.003	54.06 (6.12–603.61)	8	0.089
1	8 (8%)	8 (12%)		217.41 (96.38–370.56)	9
2	19 (20%)	11 (17%)		41.18 (6.53–112.59)	16
3	14 (15%)	15 (23%)		17.31 (6.33–125.40)	14
4	26 (27%)	9 (14%)		12.05 (4.32–36.63)	9
5	28 (29%)	13 (20%)		11.81 (1.14–54.24)	18

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Higher values indicated more severe illness. Need for ICU, O₂≤95%, hospitalization length of stay >5 days, and requirement of O₂ therapy accounted for 1 point each. The need for mechanical ventilation accounted for 2 points. Patients infected with RSV-A were most commonly classified into the most severe scores.

Viral load

A total of 156 (44%) samples were submitted to the viral load analysis (Table 4). According to age, the median viral load was higher in children with 4 to 6 months of age (63.0 cop/cell, p = 0.007). Regarding patients’ clinical conditions, we found a lower viral load in patients with fever (26.15 cop/cell) than in those without (111.29 cop/cell; p<0.001), and a higher viral load (70.24 cop/cell) in patients without the need for oxygen therapy (22.69 cop/cell; p = 0.02). Deceased patients had a lower viral load (2.80 cop/cell; p = 0.02) in comparison to the others (37.96 cop/cell). Although lacking statistical support (p = 0.089), a noteworthy observation is the tendency towards a lower viral load in patients with elevated CSS. The viral load analysis was performed regardless of the time between symptoms onset and date of collection, which, in theory, could cause an analytical bias due to the natural decrease in viral load over the course of the disease. However, a segmented analysis (0–3; 4–7 and >7 days between symptom onset and sample collection) revealed very similar results. Furthermore, of the 156 samples used to measure viral titers, only 26 (16%) were collected 7 days after symptoms onset. Therefore, we opted to maintain full sampling for viral load analysis.

Table 4. Comparison of viral load values between gender, age, outcome, and clinical condition.

Demographic data
Parameter		N	Median (IQR¹)	p-value
Gender	Male	78	51.40 (8.13–265.31)	0.08
Gender	Female	78	24.63 (4.46–88.29)	0.08
Age (months)	0–3	86	51.40 (6.12–152.90)	0.007
	4–6	22	63.09 (32.12–211.67)
	7–12	21	39.29 (2.32–236.91)
	>12	26	7.77 (1.72–36.92)
Outcome	Recovery	130	37.96 (6.72–122.71)	0.02
Outcome	Death	7	2.80 (0.04–21.49)	0.02
Clinical data
Fever	Yes	121	26.15 (4.33–104.46)	<0.001
Fever	No	27	111.29 (51.80–408.21)	<0.001
Cough	Yes	144	41.53 (4.86–148.15)	0.59
Cough	No	7	11.52 (7.98–106.29)	0.59
Dyspnea	Yes	106	37.96 (3.91–154.88)	0.69
Dyspnea	No	40	42.05 (8.58–120.16)	0.69
O₂ saturation ≤ 95%	Yes	71	26.41 (3.95–150.65)	0.40
O₂ saturation ≤ 95%	No	51	50.16 (8.36–196.81)	0.40
Respiratory distress	Yes	115	39.29 (4.78–150.13)	0.27
Respiratory distress	No	18	75.69 (12.66–214.26)	0.27
Days of hospitalization	1–4	20	79.36 (11.10–245.08)	0.20
	5–8	49	39.45 (11.89–176.21)
	>8	54	24.42 (4.08–78.04)
Ventilatory support	No	48	70.24 (11.41–342.96)	0.02
	Yes (total)		22.69	0.02
	Yes—noninvasive	65	26.41 (6.26–105.11)	0.35
	Yes—invasive	40	17.31 (3.95–68.70)	0.35
Intensive Care	Yes	82	30.01 (4.41–113.44)	0.73
Intensive Care	No	67	39.29 (6.90–154.61)	0.73
Days of Intensive Care	1–4	20	34.74 (3.60–226.28)	0.547
	5–8	16	16.27 (2.09–106.22)
	>8	24	36.24 (9.10–106.65)
Days of symptom until collect	0–3	51	36.63 (5.99–220.48)	0.19
	4–6	67	39.98 (7.65–135.24)
	7–9	24	19.98 (0.53–77.39)
	>9	12	10.45 (3.92–50.98)
Subtype	RSV-A	64	57.41	0.03
Subtype	RSV-B	76	27.35	0.03

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¹ IQR: interquartile range.

Statistically significant p-values are highlighted in bold.

The Cox regression model showed that the viral load did not have a statistically significant effect on ICU length of stay (p = 0.29; 95% CI: 0.99–1.00). Schoenfeld Residuals (S5 Fig and S6 Table) showed that the proportional hazards assumption was met (p = 0.95).

Viral seasonality and climatic analysis

In 2016 and 2017, the RSV season started in the 12^th EW (March, early fall season), peaked between the 16^th–20^th EW, and ended in the winter season, between the 31^st–32^nd EW (Fig 1; S7 Table). In 2018, the beginning of RSV seasonality was observed earlier, with the first cases occurring in the 3^rd EW, (January, in the middle of summer). The peak took place in the 14^th EW and the end occurred in the 27^th EW. Thus, the RSV seasonal period in 2016, 2017, and 2018 lasted 20, 19, and 24 weeks, respectively.

Fig 1 — The X-axis shows the epidemiological weeks (EW) for each year. The primary Y-axis displays the number of positive cases for each of the subtypes and the secondary Y-axis shows the values of the climatic variables. The gray zone indicates the total number of samples tested in each EW.

Precipitation rate and relative humidity percentage have not been shown to influence the distribution of RSV cases by Spearman’s correlation test (p = 0.55 and 0.11, respectively). The mean temperature, however, showed a minor and inverse correlation with RSV infections (-0.16; p = 0.05).

Although RSV-A and RSV-B co-circulated each year, it is noteworthy that the subtype distribution changed over the years. In 2016, RSV-B predominated (n = 80; 58%) over RSV-A (n = 58; 42%). In 2017 this difference increased, and RSV-B was responsible for 82% of the cases (n = 63). Finally, in 2018, there was a shift in this pattern and almost all RSV cases were caused by RSV-A (n = 108; 96%).

Phylogeny of RSV and genetic analysis

The phylogenetic reconstructions revealed that 36 RSV-A were classified as GA2.ON1 genotype and 21 RSV-B were classified as BA genotypes, based on the 2^nd HVR (S2 and S3 Figs). Some local genetic groups of both genotypes and a slightly higher diversity among the RSV-A strains (p-distance = 1.8%) were observed in comparison to RSV-B (p-distance = 1.6%) (Figs 2 and 3).

Fig 2 — The tree was built using the maximum likelihood method on MEGA 6.0 software from a MUSCLE alignment of G gene sequences of 711 bp. Previously published sequences from known genotypes were retrieved from the NCBI database. Numbers from 1 to 5 within the squares indicate the patients’ CSS. The cross indicates patients who died due to RSV infection. The stars indicate the viral load, categorized by color (in copies per cell).

RSV-A ES Brazilian strains, from 2016 to 2018, are clustered with strains that circulated in North America, South America, Asia, Africa, and Oceania, from 2011 to 2018. A Brazilian main local cluster BR.1 (L142S, L274P, Y304H, and T320A) circulated in ES state, from 2016 to 2018. Additionally, two new subclusters, BR.1.1 (E106G,) and BR.1.2 (N103T, S144I, E224V, S270P, and/or P298L) were detected co-circulating in the ES state in 2018. Amino acid substitutions, compared with the RSV-A GA2.ON1 reference strain (JN257693), can be observed in the S8 Table. The average CSS inside the BR.1 cluster was 2.84, while the average in the rest of the BR strains was 3.78, showing that the BR.1 cluster may be more associated with lower severity disease than the other strains. The viral load seemed to be higher on BR.1 strains when compared to other Brazilian strains.

RSV-B gene G phylogenetic reconstruction (Fig 3) revealed that Brazilian strains from 2016 to 2018 belonged to a cluster containing global strains circulating since 1999. ES Brazilian strains were distributed through this main cluster and presented punctual amino acid substitutions, some of them with a potential loss of O-glycosylation, such as T229N and/or S287F (strains from 2017). Inside the main cluster, some local subclusters were observed, such as the BR.1 (S101G loss glycosylation site, P217L, and T248A loss glycosylation site) and BR.2 (G136S and S269P), in samples from 2016, revealing a large diversity among RSV-B viruses circulating in the ES State during that year. Additionally, two strains from 2017 presented an insertion of tree nucleotides at codon 228. All these amino acid substitutions, compared with the RSV-B BA reference strain (AY333364), are described in the S9 Table. CSS and viral load data were unavailable for most of the RSV-B sequences, therefore, we could not compare those data with the genetic strains observed.

Discussion

In this paper, we investigated RSV features using the Brazilian Influenza Surveillance Program and addressed some RSV issues listed in the WHO global RSV surveillance pilot objectives [16], such as the RSV burden in hospitalized children and mapping of local seasonality. Additionally, we described the molecular characteristics of gene G which revealed RSV-A and RSV-B local clusters co-circulating in Brazil.

RSV is prevalent in Brazilian children with SARI

RSV prevalence in different Brazilian regions is highly diverse, ranging from 7.7% to 77.6% [24–26]. In the ES state, from 2016 to 2018, the prevalence in hospitalized children up to 3 years of age was 56%. These differences are probably related to the use of diverse methods of RSV detection (e.g. RT-PCR or immunofluorescence) or patient inclusion criteria (e.g. age, symptoms, period of the year). During the 1997–98 season, Checon et al. found a prevalence of 28% in the capital of ES State [26]. This lower prevalence in comparison to our study can be attributed to the less sensitive method used by the authors (immunofluorescence) and a broader target population age (children ≤ 5 years old).

In our study, the median age of four months in hospitalized children with RSV confirms the higher prevalence in children younger than one year of age [2], which justifies why RSV vaccine candidates are aiming to protect, primarily, infants and young children [7]. Although the median hospitalization length of stay found here is similar to some other studies [27, 28], notably, most of them report a shorter duration [1, 4, 25]. One hypothesis that could explain this finding is the fact that all children included in our study were diagnosed with SARI, which makes our study group a cohort with severe RSV infection. Another hypothesis is linked to the possibility that most of the children in the study had an infection in the lower respiratory tract. Aerosol transmission increases the chances of inhaling viral particles in the lower airways, while larger droplets are retained in the upper airways [29]. Naturally, aerosol infections tend to trigger a more severe course of infection [30].

The subtype but not the viral load appears to be associated with disease severity

RSV infection can cause a range of clinical outcomes [2], but factors attributed to a worse outcome remain unclear [3, 4]. Several studies have shown that the male gender is a risk factor for RSV infection [2], while others have not observed such a connection [31]. Although not statistically significant, we observed that male children were slightly more affected than female, which could support the hypothesis that male children are at higher risk. Nevertheless, the CSS median was three for both genders.

Although some authors have found no correlation between subtypes and disease severity [32, 33], many others indicate RSV-A as the most virulent subtype [9, 10, 12, 34, 35]. We have found that children infected with RSV-A revealed a higher clinical score index (CSS median = 4)–therefore, a more severe disease—when compared to those infected with RSV-B (CSS median = 3). Children infected by RSV-A required O₂ therapy more often than those infected by RSV-B and, of all children who needed O₂ therapy, those affected by subgroup A needed mechanical ventilation more frequently. Although these data did not have statistical support, other studies found the same connection [9, 10]. Our data also show that children infected by subgroup A required ICU more often (p = 0.03) and remained hospitalized and in ICU a day longer, on average, when compared to those infected by RSV-B, which is in agreement with previous studies [35, 36]. Notwithstanding, we highlight that only one genotype was found for each subtype (ON1 and BA), thus, those differences in severity could be a consequence of differences in the genotype’s virulence, rather than in the subtype’s.

The correlation between disease severity and viral load remains controversial. While several authors have shown that the severity of the infection follows the viral load [4, 5, 37, 38], others have not [7, 12, 33]. Some studies found an association between viral load and symptom frequency, but not severity itself [39, 40]. Viral load measurement methods are widely variable between studies: some authors use plaque assay [4] or semi-quantitative analyses, such as ct [5, 7, 32], others use quantitative methods [38–41]. Moreover, most studies that use quantitative methods do not normalize the measurements. Respiratory samples are naturally heterogeneous and the collection technique can influence viral genome concentration [38].

In this study, we used a standardized method for measuring the viral load. Interestingly, we found a lower viral load in patients with fever (p = 0.00), with the need for ventilatory support (p = 0.02), and in those who died (p = 0.02). Our data conflict with previous studies that demonstrated a positive association between viral load and the presence of cough, fever [39], and the need for intubation [37]. However, two recent studies reported a higher viral load in less severe RSV disease [42, 43]. Piedra et al. observed a positive correlation between viral load and mucosal concentration of proinflammatory cytokines that may suggest that high RSV loads can protect from disease progression due to the promotion of an early robust innate immune response [42, 43]. Conflicting results between studies could be attributed to the different methods used to calculate viral load, various study designs, and indicators of disease severity.

The seasonal period of RSV may fluctuate and its circulation is slightly associated with temperature

In temperate countries, RSV peak activity occurs in the winter and several studies have shown the connection between cold temperatures and viral circulation [44]. In contrast, in tropical countries, there is a wide range of variability in the timing and duration of epidemics and the correlation between climatic factors and viral activity is controversial [21, 45]. Although in the Southern Hemisphere the RSV wave usually starts between March and June and decreases between August and October [21], in Brazil, a continental country with five geographic regions, a wide variation in the seasonality is seen, such as those observed in the northeastern [46] and southern [47] regions.

Here, we showed that RSV’s activity was very similar between the 2016 and 2017 seasons, with the circulation onset occurring in March (EW 12) and ending in July/August (EW 31–32), during the winter season. These data are in accord with the Brazilian Society of Pediatrics, which recommends the administration of Palivizumab from February to July [48]. Nonetheless, in 2018, we observed an early occurrence of the seasonality onset by nine weeks, with the beginning of circulation occurring in January (summer season) and the end taking place in the Fall instead of Winter.

In the southeastern region, it was observed that the RSV peak usually happens in early April [49]. Our data shows that, in 2016, the RSV peak occurred in May, suggesting subtle differences even inside the same geographical region. In 2018, there was an extension of RSV’s seasonality duration by 4.5 weeks when compared to the average in 2016–2017. Those observations are especially worrisome since major variations could make a preventive measure harder to implement. Understanding local epidemics is important in managing the time of prophylaxis, supporting vaccine development, and following morbidity and mortality caused by RSV infection [44]. Thus, establishing RSV surveillance in real-time may allow for the identification of patterns and possible variations in prophylaxis time. RSV seasonality usually lasts five to six months [21]. In our study, the longest seasonal period occurred in 2018 (6 months), followed by 2016 (5 months) and 2017 (4.75 months). Interestingly, the prevalence of RSV-A was high in 2018 (96%), medium in 2016 (41%), and low in 2017 (18%). These data reinforce the theory that RSV-A may lengthen the seasonality [50].

Climatic factors, such as humidity, rainfall, and temperature have been assumed to impact RSV seasonality [44, 51]. However, this association remains controversial. An inverted correlation between RSV circulation, temperature, and humidity was observed in a Brazilian study, carried out in the state of São Paulo [52]. In this study, a minor correlation was found between temperature decrease and case number increase. However, no correlation was found concerning humidity or precipitation.

ON1 and BA were the only genotypes detected

All RSV-A isolates were ON1 genotype and all RSV-B were BA, which confirms the fast-global dissemination of RSV with nucleotide duplication. These findings are consistent with recently published reports performed in other countries, such as the Philippines [53], Kenya [54], Italy [55], USA, and Puerto Rico [56].

Overall p-distance during the study period in RSV-A was 1.8%. A recent study observed an overall p-distance of 1.4% within ON1 [13]. A noteworthy observation is the fact that in 2017 we found the lowest prevalence of RSV-A in ES (18%), and yet, still, the highest genetic diversity. Phylogeny showed that 2017 strains were distributed in almost all genetic clusters, which showed high diversity that year. RSV-A phylogenetic analysis revealed ongoing genetic changes, with BR.1 grouping the most recent strains, suggesting that BR.1 strains may be under positive selective pressure. Changes in the circulation of RSV strains have been considered a mechanism for evading immune response generated by previous strains, which possibly allows for re-infections to occur [57].

As demonstrated, in 2018 RSV-B was responsible for only 4% of cases. Therefore, the phylogenetic analysis did not include any RSV-B samples from that year. Older strains, from 2009 to 2014, are positioned at the base of the BA cluster, however, sample strains collected between 2015 and 2018 did not form genetic groups related to the year of collection. This observation may suggest an absence of positive pressure.

Although we found clusters composed exclusively of ES samples, it is necessary to expand the sequencing of RSV samples globally to verify if there is, in fact, the formation of local genetic groups or if the observation is caused by a sample bias.

Previous studies showed that a large part of the genetic variability between RSV strains comes from changes in the O-glycosylation profile and that this may be associated with an evolutionary mechanism of immune response evasion [58]. Here, we investigated and listed strain amino acid substitutions and also those shared within and between clusters. However, we did not carry out an in-depth analysis to understand the role of these mutations, as our objective was purely observational. Among the mutations found, one of the most interesting was the insertion of three nucleotides at codon 228 in RSV-B. Further studies are essential to understand virus evolution and pathogenicity mutation consequences.

Limitations of this study include the fact that the majority of patients had an acute infection, thus, the prevalence found refers only to SARI, and the absence of a mild infection group prevents further analysis of severity influencing factors. Furthermore, clinical data were taken from notification forms, which often contain inconsistencies and missing data. Despite those caveats, we believe the data provide valuable epidemiological, genetic, and clinical information on RSV.

Conclusion

In this study, we observed a high prevalence of RSV in children under three years of age even when using the Brazilian Influenza Surveillance Program. This result is important because it shows that the establishment of global RSV surveillance within the Influenza surveillance system allows for the detection of a large number of cases. Our data suggest that RSV-A is, in fact, more virulent than RSV-B. Notably, no correlation between viral load and disease severity was observed. The observation of a marked early onset of the seasonal period is worrisome since this can make it difficult to administer prophylactic measures at the right time, however, it is necessary to expand the historical series of seasonality in the state of Espirito Santo. The average temperature was the only climatic factor to show interference with the viral circulation. Our data show the annual co-circulation of RSV-A and RSV-B, however, with considerable fluctuations in the prevalence of subtypes. ON1 and BA were the only genotypes found in the studied period, which corroborates a series of recent studies. The establishment of a global and standardized real-time RSV surveillance may allow for the collection of data that will help to understand the complex mechanisms of viral evolution and will facilitate the development of future vaccines and antiviral drugs.

Supporting information

S1 Fig. Map of the Espirito Santo State (Brazil) and its federal highways.

The state is divided into 78 municipalities, of which 60 were represented by children with SARI and 46 with children with confirmed RSV infection. The colors of the municipalities represent the number of positive RSV cases.

(TIF)

Click here for additional data file.^{(9.9MB, tif)}

S2 Fig. RSV-A phylogenetic tree based on 336 bp of the HVR-2 of G gene.

The tree was built using the maximum likelihood method on MEGA 6.0 software from a MUSCLE alignment, with some manual editions. Reference sequences from each described genotype were downloaded from the NCBI GenBank and used in the phylogenetic reconstruction. The genotypes were classified by colors and all ES strains were grouped within the ON1 genotype.

(TIF)

Click here for additional data file.^{(10.4MB, tif)}

S3 Fig. RSV-A phylogenetic tree based on 318 bp of the HVR-2 of G gene.

(TIF)

Click here for additional data file.^{(10.3MB, tif)}

S4 Fig. Survival curve in relation to ICU length of stay estimated by the Kaplan-Meier test.

Given the small number of deaths, it was necessary to modify the analysis to assess the likelihood of cure.

(TIF)

Click here for additional data file.^{(6.7MB, tif)}

S5 Fig. Graph of Schoenfeld residues: There was no marked trend, indicating that the premises for the application of the Cox model were met.

(TIF)

Click here for additional data file.^{(5.7MB, tif)}

S1 Table. Primers, probes, and DNA fragments used in the study.

“F”, “R”, and “P”, represent the sequence of the forward and reverse primers, and the probe, respectively. A synthetic DNA fragment from RSV was included in a pMA-t vector.

(DOCX)

Click here for additional data file.^{(22.4KB, docx)}

S2 Table. List of the sequences used to build the phylogeny based on HVR-2 of gene G for both subtypes RSA-A and RSV-B.

(DOCX)

Click here for additional data file.^{(21.8KB, docx)}

S3 Table. List of the sequences used to build the phylogeny based on gene G for both subtypes RSV-A and RSV-B.

The collection date of some sequences was unavailable.

(DOCX)

Click here for additional data file.^{(43.3KB, docx)}

S4 Table. General table that provides all epidemiological, clinical, and climatic data of the study.

(XLSX)

Click here for additional data file.^{(182KB, xlsx)}

S5 Table. Cox (proportional hazards) regression: Given that the p-value is >0.05, it can be inferred that the viral load has no significant effect on ICU length of stay.

(DOCX)

Click here for additional data file.^{(12.7KB, docx)}

S6 Table. Proportional hazards assumption test: The premises for the application of the Cox model were met.

(DOCX)

Click here for additional data file.^{(12.4KB, docx)}

S7 Table. Duration and climatic characteristics of RSV seasonality in the years studied.

(DOCX)

Click here for additional data file.^{(18.5KB, docx)}

S8 Table. List of amino acid changes in RSV-A.

Residues in blue and red show potential losses and gains of O-glycosylation sites, respectively.

(XLSX)

Click here for additional data file.^{(19.4KB, xlsx)}

S9 Table. List of amino acid changes in RSV-B.

Residues in blue and red show potential losses and gains of O-glycosylation sites, respectively.

(XLSX)

Click here for additional data file.^{(15.3KB, xlsx)}

Acknowledgments

We would like to thank Liliana Cruz Spano for her significant theoretical and experimental support to this work, Beatriz Alves Vianna, Fabíola Karla Correa Ribeiro, and Mirella Martins Tostes for their assistance in editing and improving the language, all researchers who upload genetic sequences in the public genetic database—GenBank, patients, parents and guardians, the Espirito Santo State Health Department, and the Brazilian Ministry of Health, represented by the Influenza Technical Group.

Data Availability

The sequences produced here were deposited on the GenBank platform, under the accession number MW026969–MW027004 and MW030961-MW030981, and in the GISAID platform, under the accession number EPI_ISL_549271–EPI_ISL_549327.

Funding Statement

This work was funded by Espirito Santo Research and Innovation Support Foundation (FAPES; https://fapes.es.gov.br/), under project Fapes/CNPq n° 05/2017 and by INOVA Fiocruz Program (https://portal.fiocruz.br/programa-inova-fiocruz), under project VPPCB-008-FIO-18. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0251361.r001

Decision Letter 0

Baochuan Lin

16 Dec 2020

PONE-D-20-30854

Landscape of Respiratory Syncytial Virus (RSV): a perspective into the Brazilian Influenza Surveillance Program

PLOS ONE

Dear Dr. Vianna,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

I have received the reviews of your manuscript. While your paper addresses an interesting question, the reviewers stated several concerns about your study and did not recommend publication in its present form. Both reviewers voice a number of concerns regarding the presentation as well as data analysis, and these comments need to be addressed carefully. Please see reviewers’ insightful comments below.

The quality of the language needs to be improved, there are quite a few awkward sentences, typo and grammatical errors throughout the manuscript. Please have a fluent, preferably native, English-language speaker thoroughly copyedit your manuscript for language usage, spelling, and grammar.

Please submit your revised manuscript by Jan 30 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Baochuan Lin, Ph.D.

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: No

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This manuscript has scientifically valid information that is worth publishing. The authors have done a lot of work and produced data. However, the manuscript cannot be accepted at its present form.

Title - Revise the title to reflect the key findings of the research.

Introduction - Revise the introduction and make it shorter and its current form it distracts the reader.

Methodology - Organize the Methodology - Study population, experimental methods - RT-qPCR, sequencing etc. in a brief form that gives a good understanding of the sequence of events with relevant methodology.

Results - They need to be organized in the order of appearance as in the Methodology. You do not have to replicate all the information given in the Tables in the texts. Redundancy also distracts the reader and I found it difficult to organize the results to understand the authors' way of cohesion.

Discussion - Again follow the order of your results in Discussion.

Overall - You must revise this manuscript shortening certain sections and organizing the manuscript from I to D. Otherwise the results produced cannot be understood by the authors.

Language must be clear, correct, and unambiguous. At its current form it is difficult to follow the authors. Please also look into typographical or grammatical errors when your revise the manuscript. You may ask a native speaker to read the manuscript after fixing all the issues indicated.

Please follow the PLOS ONE formatting guidelines well before you submit after revision.

Reviewer #2: Reviewer #1

Summary

The manuscript by Vianna et al. describes an evaluation of the role of viral load and genetic diversity of RSV on disease severity in hospitalized children under 3 years old identified using the Brazilian Influenza Surveillance Program and the influence of climate factors on RSV seasonality in Espirito Santo State of Brazil. The authors present data showing no correlation between viral load and disease severity and that some clinical features of disease severity were significantly higher among patients with RSV-A compared to RSV-B. The manuscript is very extensive and the authors often reference Supplemental information to support interpretations and main messages (e.g. clinical severity scores). Genetic diversity analyses revealed local co-circulating clusters of RSV-A (all ON1) and RSV-B (all BA) during the period of study (2016-2018), with severity of disease impact investigated for RSV-A strains only due to lack of CSS data for RSV-B strains. Finally, climate factors including precipitation rate, percent humidity, and mean temperature showed no significant correlation on RSV seasonality between 2016-2018. The authors recognize the importance of global RSV surveillance and highlight the potential of the Global Influenza Surveillance and Response System (GISRS) as a platform to collect data that could follow temporal evolution of RSV and potentially support the development RSV vaccine and antivirals. Given the limited availability of RSV surveillance data in Brazil, this study provides recent information to better understanding of seasonality and the impact of RSV molecular epidemiology on disease severity relative to other areas of the world

Major Comments for the Author

1. The authors present generalized conclusions that are not specific to the Brazilian aspect or timeframe on which this study is based. Key results to support the identified objectives are not highlighted in the abstract or the conclusion (e.g. the influence of climate factors on RSV seasonality and the role of genetic diversity of RSV on disease severity). Clinical severity scores referenced in the abstract and results to support interpretations of the role of viral load and genetic diversity of RSV on disease severity, should be presented in the main tables/figures of the manuscript as opposed to supplemental. The authors should revise these areas and sharpen the focus of their Discussion through reduction to improve readability and presentation of key messages of RSV surveillance in Brazil between 2016-2018 relative to previous observations in Brazil or other parts of the world during the similar timeframe.

2. The current title (and abstract) fail to address the presented timeframe of RSV surveillance or what aspects of “landscape” or “perspectives” the authors are referring to relative to their objectives and results. The authors should consider revision.

3. Figure 2 and Figure 3 are out of focus and uninterruptable for review. The authors should revise.

4. Line 90-92, 130-133, and 270-276. The authors statement of “seasonal oscillation” (Line 90-92) is not supported by their main observations (Line 270-276) from Fig. 1, and in turn, their statement regarding “creating difficulties for determination of the most appropriate period to start prophylaxis” is not substantiated and is in contrast to their later statement of “recommends the administration of palivizumab from February to July” (Line 359). The authors state (Line 130-133) that “seasonality onset and end were defined as the first and last of 2 consecutive weeks, respectively, when the number of RSV cases exceeded 10% of the number detected during the RSV peak week” and reference Obando-Pacheco et al 2018 [21]. However, Obando-Pacheco et al 2018 states that “the onset of RSV season was defined as the first 2 consecutive weeks when >10% of the total tested samples for respiratory pathogens were positive for RSV. The end of the RSV season was defined similarly as when the proportion of positive RSV tests fell below 10% for 2 consecutive weeks.”. Given the impact of molecular testing on determining RSV seasonality, the authors should revise their analysis and adopt a more accepted threshold for seasonality assessment based on %RSV positive cases as opposed to the number of RSV cases to support a potential interpretation of “seasonal oscillation” (see also Midgley et al. 2017 JID 216(3):345-355).

5. Table 1: The authors should revise this Table to provide both numerators and denominators to allow for readability and logical follow with the main text. This will also allow the reader to appropriately follow the statistical assessment employed of relative proportions. In addition, Influenza prevalence is noted in the main text, but not in the corresponding Table 1. The authors should to revise the Table to include all relevant data for the reader.

6. Line 225-232 and Table 2: The authors should rephrase their statement regarding “clinical features of patients affect by RSV” to better reflect clinical characteristics of patients with SARI, since clinical data are presented for the total 632 patients and the 327 patients with RSV (180 RSV-A and 147 RSV-B). The numbers and percentages in the main text reflect the total population (N=632) and not the population of patients with RSV disease (N=327). The authors should further revise this Table to provide both numerators and denominators to allow for readability and logical follow with the main text. This will also allow the reader to appropriately follow the statistical assessment employed of relative proportions and to distinguish between RSV and everything else. Finally, viral load data in Table 2 is out of place without a (%) and should be included in Table 3 where viral load values are presented.

Minor Comments for Author (Required)

7. Line 17 and 40. The authors are repetitive in their statements in the Background and Conclusion sections of their Abstract regarding “understanding seasonality, genetic features…may support antiviral and vaccine development. The authors should revise the abstract and clarify how the results of this study specifically support antiviral and vaccine development

8. Lines 21, 38, 81, 83, 88, 339-440. Is the Brazilian Influenza Surveillance Program part of WHO’s Global Respiratory Syncytial Virus Surveillance Pilot and/or the Global Influenza Surveillance and Response System (GISRS)? The authors should consider revising for clarity; in particular Lines 338-340 at the start of the Discussion section where both programs are discussed in the context of the objectives of the current study. Recommend that the authors be consistent throughout the manuscript in their reference to the Influenza Surveillance Program as to which this study is based on (ie. National, Brazilian, or just Influenza Surveillance Program are used throughout the manuscript; pick one version and capitalize all words).

9. Line 30 and Line 105: What were the remaining 44% of case caused by, all influenza?

10. Line 48: The authors should clarify in the text the source of the “Influenza and other respiratory virus epidemiological reports” as to whether these are from the Brazilian and/or National Influenza Surveillance Program.

11. Line 57: The authors should explain the rationale as to why the previously observed significant association between viral load and disease severity should be more carefully studied in the Introduction. The authors later state in the Discussion that the correlation between viral load and disease severity remains controversial (Line 423). The authors are advised to further emphasize that one of the strengths of their study in finding of a lack of correlation between viral load and disease severity is the use of standardized methods for measuring viral load (see Lines 432-442)

12. Line 60: The authors should revise this sentence to clarify that the context by which “the treatment is based” in referring to RSV since this is new paragraph

13. Line 72: The authors should supplement reference 15 with a reference that defines the multiple genotypes of RSV-B

14. Line 78: Reference 15 does not support the statement that understanding RSV genetic diversity will help designing antiviral drugs, diagnostic assays, and vaccines. The authors should revise.

15. Fig 1: The y-axis and X-axis should be labeled within the figure.

16. Line 126-127: Location of INCAPER should be provided.

17. Line 143: The authors should define in Supplemental Table 1 or elsewhere in the main text what RSV gene the primers and probes used to subtype RSV-A and RSV-B were directed against

18. Line 161: The authors should clarify what they mean by “partial amplification” and by RSV positive samples with Ct values between 30-40 were not subjected or attempted for sequencing.

19. Line 179-180: The authors should provide a reference to the source of their reference sequences

20. Line 37, 74, 194, 294, 334, 421, 444, 466: The authors should correct their documentation of the RSV B genotype from BA to BA1 per the accession number provided and documented

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2021 May 18;16(5):e0251361. doi: 10.1371/journal.pone.0251361.r002

Author response to Decision Letter 0

25 Jan 2021

Editor comments:

Comment 1: Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at:

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Answer: After a careful review, we have modified the formatting of the headings and legends of the supplementary figures and tables to meet PLOS ONE's style requirements. We also corrected some tables that presented values highlighted in red, contrary to the rules of PLOS ONE. Finally, we increased the font size of the Materials and methods, Results and Discussion subheadings to 16 pt, according to rules.

Comment 2: We note that you included minors (age<18) in your study. Please provide additional details regarding minor’s consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this information.”

Answer: We agree with this observation. The sentence “The need for parents or guardians’ consent was waived by the ethics committee.” was included in “Ethics Statement” section. Please, check the lines 207-208.

Reviewer #1 comments:

1. Title - Revise the title to reflect the key findings of the research.

Answer: To address this comment, we have changed the title to: “Seasonality, molecular epidemiology and virulence of Respiratory Syncytial Virus (RSV): a perspective into the Brazilian Influenza Surveillance Program”. However, considering that this study addressed several aspects of RSV, the inclusion of key findings would make the title too large and we have opted to make it shorter and easier to read.

2. Introduction - Revise the introduction and make it shorter and its current form it distracts the reader.

Answer: We have changed the introduction and eliminated sentences that, although interesting, would not affect the understanding of the objectives. However, Introduction size reduction was small. It turns out that this study has addressed multiple aspects of RSV (e.g.: prevalence, association between severity and subtypes, viral load, seasonality and association with climatic factors and phylogenetic aspects), as we understand that these are important aspects to discuss.

3. Methodology - Organize the Methodology - Study population, experimental methods - RT-qPCR, sequencing etc. in a brief form that gives a good understanding of the sequence of events with relevant methodology.

Answer: We have changed the way methods are presented, in order to maintain the same pattern presented at the results.

Thus, methods are now as follows:

1. Population sampling, study period and location

2. RSV and Influenza detection and subtyping

3. Clinical and epidemiological data collection

4. Viral load quantification

5. Climate data collection

6. Partial amplification and sequencing of glycoprotein gene

7. RSV genotyping and gene G phylogenetic reconstruction

8. Statistical treatment.

9. Data availability

10. Ethics Statement

4. Results - They need to be organized in the order of appearance as in the Methodology. You do not have to replicate all the information given in the Tables in the texts. Redundancy also distracts the reader and I found it difficult to organize the results to understand the authors' way of cohesion.

Answer: We think this comment will make the manuscript easier to read. As recommended, we have reorganized the objectives in the same pattern presented in the results, and eliminated redundant information.

5. Discussion - Again follow the order of your results in Discussion.

Answer: We have organized the discussion in the same order presented in Methods and Results and created subsections in the discussion, in order to improve reading.

6. Overall - You must revise this manuscript shortening certain sections and organizing the manuscript from I to D. Otherwise the results produced cannot be understood by the authors.

Answer: To address this recommendation, we have reduced the text as much as possible, without interfering with data presentation quality and consistency. We have reduced redundancies in the results (data being presented in the text and table) and removed some excerpts throughout the manuscript that we consider less relevant.

7. Language must be clear, correct, and unambiguous. At its current form it is difficult to follow the authors. Please also look into typographical or grammatical errors when your revise the manuscript. You may ask a native speaker to read the manuscript after fixing all the issues indicated.

Answer: we have asked a native speaker to thoroughly review the manuscript.

8. Please follow the PLOS ONE formatting guidelines well before you submit after revision.

Answer: We have done so.

Reviewer #2 comments:

Answer: We appreciate the observations. However, some results of this study are not related to a specific location or timeframe. The correlation analyzes between viral load, genetic differences and severity are examples. These results possibly transcends the time and place of the study and, therefore, are not specific to the Brazilian aspect or timeframe.

As recommended, we have included the key results in both abstract and conclusion. We also transformed supplementary table 4 into Table 3. Previous table 3, which presented data on viral load, is now part of Table 4.

Given the different approaches taken in the study, we chose to divide the discussion into topics, in the hope of improving the quality of reading and regarding the discussion length, we removed some less important passages in order to improve the readability and presentation of key messages of the study.

Answer: as changing the Title was also a recommendation of Reviewer 1, and to clarify which aspects of the “landscape” the study focused on, we have changed the title to: “Seasonality, molecular epidemiology and virulence of Respiratory Syncytial Virus (RSV): a perspective into the Brazilian Influenza Surveillance Program”. We hope this new title is suitable for both Reviewers.

3. Figure 2 and Figure 3 are out of focus and uninterruptable for review. The authors should revise.

Answer: Figures 2 and 3 were redone to improve quality and readability. We decided to change the size and save the file as .EPS.

Answer: We agree with the Reviewer, and, in fact, there was a misinterpretation of season beginning and end definition by Obando-Pacheco et al. (2018). Therefore, we reviewed the data and corrected the analysis. However, there were no changes in season onset in any year, but there were small changes in season end, as described below:

1. End in 2016: from EW 33 to EW 32.

2. End in 2017: from EW 30 to EW 31.

3. End in 2018: from EW 26 to EW 27.

Although the reviewer understood that the data do not support the claim that there was a fluctuation in season period during the study, we would like to point out that in 2016 and 2017 the RSV seasonal period started at epidemiological week (EW) 12 and ended at EW 32 and 31, respectively. In contrast, in 2018 the season was anticipated to EW 3, which is 9 weeks before the start in previous years. Season end was also anticipated to EW 27. There are the reasons why we understand there was an oscillation in the seasonal period during our study. As Palivizumab is administered in five consecutive monthly doses and considering that the first dose should be administered one month before season start, this oscillation may have an impact in the administration of prophylactic drugs.

In order to make this point clearer, we have restructured the discussion paragraphs.

Answer: we have revised Table 1, making the requested changes.

Answer: Table 2 and the associated text present clinical data only of RSV infected patients. This table had an error in the "Sample number" field, which contained the total number of samples studied (632), however, the analyzes were performed only with the 352 RSV positive children. The error has been corrected. We took the opportunity to correct some fields containing three decimal places, standardizing the values to two decimal places. We have also relocated table 2 viral load data to table 3, as suggested. Finally, we included denominators to facilitate data interpretation.

Minor Comments for Author (Required)

Answer: We have eliminated the redundant part from the "Background" and briefly discussed how seasonal period, virulence and genetic diversity can assist in the development and application of vaccines and antiviral drugs.

Answer: The Brazilian Influenza Surveillance Program is part of WHO’s Global Respiratory Syncytial Virus Surveillance. We chose to use the term “Brazilian Influenza Surveillance Program” with capital words, as suggested.

9. Line 30 and Line 105: What were the remaining 44% of case caused by, all influenza?

Answer: In this study, only RSV and Influenza were tested. In 56% of the cases RSV was detected, the influenza virus was found in 7% of the samples and the remaining 37% cases were undetermined.

Answer: We have followed previous Reviewers’ recommendations to shorten the introduction, and because of that we have removed this text, as explained to the other reviewer.

Answer: To address that, we have rewritten the Introduction as follows:

“Some studies have evaluated the association between viral load and disease severity, with significant associations [6,7]. However, most of these studies did not use standardized methods of viral load measurement, therefore, this relationship must be more carefully evaluated.”

12. Line 60: The authors should revise this sentence to clarify that the context by which “the treatment is based” in referring to RSV since this is new paragraph.

Answer: We have rephrased the sentence to: “RSV treatment is based only […]”.

13. Line 72: The authors should supplement reference 15 with a reference that defines the multiple genotypes of RSV-B.

Answer: We have added the study by Trento et al. (2006) which was already mentioned in reference #17 (now reference #14, since due to the removal of some sections to reduce the text, the corresponding references were also removed).

14. Line 78: Reference 15 does not support the statement that understanding RSV genetic diversity will help designing antiviral drugs, diagnostic assays, and vaccines. The authors should revise.

Answer: It is possible to find in reference 15 (now reordered to reference 13) two excerpts that support this statement: “RSV diversity is an important factor that allows for reinfections to occur throughout life and also has implications for design of diagnostic assays, antiviral therapies, and preventive strategies (passive immunization and vaccines)”. (in the introduction).

“Genotype classification and assignment is of importance in order to understand the evolution, epidemiology, and clinical presentation of this virus, and has implications regarding the development of vaccines and other preventive interventions.” (in the discussion).

15. Fig 1: The y-axis and X-axis should be labeled within the figure.

Answer: Figure 1 has been edited, including caption for the two Y axes and the X axis. Caption is displayed in a text box.

16. Line 126-127: Location of INCAPER should be provided.

Answer: We have included the city, state and country of INCAPER. Please, check the line 145.

17. Line 143: The authors should define in Supplemental Table 1 or elsewhere in the main text what RSV gene the primers and probes used to subtype RSV-A and RSV-B were directed against.

Answer: In the methodology, we include the requested information as follows: “RSV positive samples (i.e. those with cycle threshold [CT] ≤ 40) were subtyped using specific primers and probes to N gene of RSV-A and RSV-B.” Please, check the line 105.

18. Line 161: The authors should clarify what they mean by “partial amplification” and by RSV positive samples with Ct values between 30-40 were not subjected or attempted for sequencing.

Answer: Partial amplification in this case refers to the fact only part of the gene was amplified. We have included the approximate sequenced G gene fragment size, as follows:

“The partial gene G amplification (about 730 bp) was performed at LVRS/IOC/FIOCRUZ”

We have also included the following sentence in bold: “a) cycle threshold (ct) value less than 30, due to the difficulty in sequencing samples with higher ct than this;”

19. Line 179-180: The authors should provide a reference to the source of their reference sequences.

Answer: The requested data is already available in supplementary tables 2 and 3. All reference sequences were taken from NCBI Genbank. These supplementary tables contain access numbers, genotypes and collection locations of each sequence.

20. Line 37, 74, 194, 294, 334, 421, 444, 466: The authors should correct their documentation of the RSV B genotype from BA to BA1 per the accession number provided and documented.

Answer: The classification into the BA cluster is controversial. We prefer classify as BA. More studies are needed to standardize the RSV nomenclature of genotypes into BA and ON1.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file.^{(35.7KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0251361.r003

Decision Letter 1

Baochuan Lin

15 Mar 2021

PONE-D-20-30854R1

Seasonality, molecular epidemiology and virulence of Respiratory Syncytial Virus (RSV): a perspective into the Brazilian Influenza Surveillance Program

PLOS ONE

Dear Dr. Vianna,

The reviewers agreed that the revised manuscript showed significant improvement, however, one reviewer still have concern regarding clinical data which needs to be address carefully. In addition, I have found quite a few typos and error within the manuscript that need to be corrected (see attached PDF file from editor)

Please submit your revised manuscript by Apr 29 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Baochuan Lin, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

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1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #3: All comments have been addressed

Reviewer #4: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #3: Yes

Reviewer #4: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: No

Reviewer #4: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #3: No

Reviewer #4: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #3: Yes

Reviewer #4: Yes

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6. Review Comments to the Author

Reviewer #3: The clinical dataset does not appear to have been uploaded in the way the genetic data has. Some of the statistical choices are suboptimal but overall this is decent if unglamorous science that fits the PLoS model

Reviewer #4: No further comments to strengthen the paper. Thank you for allowing me to review your paper and thanks for making the changes.

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Reviewer #3: Yes: Paul Walsh

Reviewer #4: No

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PLoS One. 2021 May 18;16(5):e0251361. doi: 10.1371/journal.pone.0251361.r004

Author response to Decision Letter 1

24 Mar 2021

RESPONSE TO REVIEWERS

Editor’s comments:

The reviewers agreed that the revised manuscript showed significant improvement, however, one reviewer still have concern regarding clinical data, which needs to be address carefully. In addition, I have found quite a few typos and error within the manuscript that need to be corrected (see attached PDF file from editor).

Answer: Dear Editor, thank you for considering our manuscript. We thoroughly checked comments in the PDF file and made all suggested corrections

Comment 1: About the sentence: "RSV viral load was determined by RT-qPCR using a protocol adapted from Álvarez-Argüelles et al. [20], including a synthetic β-globin dsDNA as a template.”, it was asked if the β-globin dsDNA was used as an internal PCR control.

Answer: β-globin dsDNA was used for sample cell quantification; using the same standard curve construction method applied for measuring RSV copies, we were able to calculate the number of cells in the sample. Applied Biosystems 7500 Real-Time PCR Software is able to use various known concentrations of β-globin (comparing these curves with the sample amplification curve) to estimate number of β-globin copies in the sample. This number can later be used to calculate the number of cells in a sample. In time, the marker used as an internal control was the human RNAse P gene.

Comment 2: About the sentence: " Male gender was 220 slightly more affected by RSV (n=182; 52%) […]” it was asked whether the finding was statistically significant.

Answer: Negative. The difference found in the proportion between male and female patients affected by RSV presented no statistical support. However, as other authors commonly present these data, we decided to show it as well. In addition, we compared viral load between genders.

Comment 3: About the sentence: “S4 Table shows the difference in severity by ethnicity.”, it was asked for more description.

Answer: To address the request of reviewer #3 (Comment n°9), we decided to eliminate discussions about race from the manuscript, and, therefore, the S4 table was removed.

Comment 4: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Answer: We use the Zotero software as an indexer of bibliographic references. In this way, all the works cited are listed automatically. Even so, we revised the manuscript to ensure that all and only the papers cited are referenced.

Once the discussion in the context of race was removed from the manuscript, the references used were also eliminated, namely:

• Reference 31 (Cardena et al., 2005);

• Reference 32 (Brasil. Síntese de Indicadores Sociais: uma análise das condições de vida da população brasileira);

• Reference 33 (Nair et al., 2010)

We also added a reference (de-Paris et al., 2014) in order to include data on length of hospital stay in the discussion. This measure aimed to meet the recommendation of reviewer #3 to emphasize the data on duration of hospitalization found in our study.

Two other references (Thomas, 2013 [ref. 30] and Wonderlich et al, 2017 [ref. 31]) were added in order to support the discussion suggested by the reviewer in his comment No. 17.

We did not use papers that have been retracted.

Reviewer #3 comments:

Topic n°1: Sample selection

Comment n°1: How were the municipalities selected? Was sampling representative? And if so was a weighting scheme used that would allow improved generalization of the results? Given the international audience of PLoS, I would favor including a map with distance marker, topography and major roads be provided perhaps this could be done as a link to a google map page would be helpful and avoid the impression of being a gimmick to Brazilian readers while helping international ones.

Answer: Most of our study was carried out in the Molecular Biology II sector of the Central Laboratory of Espirito Santo (LACEN/ES). This government agency is part of the national laboratory surveillance network for Influenza and other respiratory viruses and, for this reason, has the duty to investigate all cases that fit the SARI concept adopted in Brazil. Thus, any sample collected in this context, even if it comes from private institutions, must be sent to LACEN for diagnosis of Influenza, Respiratory Syncytial Virus and, most recently, of SARS CoV 2. Therefore, no sampling or weighting scheme was used, for the simple fact that virtually all samples of children up to 3 years old with SARI in Espirito Santo were present in our study. Consequently, the sampled municipalities were all those with suspected cases (61 municipalities). Of these, 46 presented at least one child with a confirmed case of RSV infection.

We have built a map of the state of Espirito Santo (S1 Fig.), with the main highways (federal highways), distance marker and topography, as requested. We plotted the number of confirmed RSV cases in each municipality throughout the study period. We are grateful for the idea, which will help the international community better understand the geographic space of the study.

Comment n°2: Median length of stay was high at 8 days suggesting this was a sicker than usual group of infants with RSV. The potential for this later result should be signaled in the sampling scheme.

Answer: To address this comment, we have included the following text:

"Although the median length of hospitalization found here is similar to some other studies [28,29], notably most studies report a shorter duration [1,4,26]. One hypothesis that could explain this finding is the fact that all children included in our study were diagnosed with SARI, which makes our study group a cohort with severe RSV infection. Another hypothesis is linked to the possibility that most of the children in the study had an infection in the lower respiratory tract. Aerosol transmission increases the chances of inhaling viral particles in the lower airways, while larger droplets are retained in the upper airways [30]. Naturally, aerosol infections tend to trigger a more severe course of infection [31].”

We would like to point that there was no sampling scheme, as all the samples in the Espirito Santo State are sent to us for analysis.

Topic n°2: Clinical Outcomes and study definitions

Comment n°3: Dichotomizing 02 saturation, especially at 95% which is not a clinically used threshold seemed odd. 90%, 92% or even 94% would be consistent with variously described clinical thresholds.

Answer: This is a retrospective study in which all clinical data were taken directly from the SARI epidemiological records, used by the Brazilian health system. In these forms, there is a field with the following question: “Oxygen saturation ≤ 95%?”. There is no field in the records for filling with the measured saturation per se, but only if it was above, equal or below 95%. It is, therefore, qualitative data. The reviewer very well pointed out that the dichotomization of O2 saturation is not commonly clinically used; however, unfortunately, this was the only possible way of analysis, given the data available. However, it is necessary to say that saturation ≤95% is used as an element in the definition of SARI in Brazil and, although it is not the most common form found in studies, it is used as an indicator of severity in respiratory diseases.

Comment n°4: CSS score seems very crude. Was it derived and validated before this study? If not, it is simply reframing the data already gathered and would be better analyzed as discrete variables rather than as a score. It would be better to analyze the CSS itself as an ordinal variable. This would also increase the statistical power of the analysis.

Answer: The CSS used in our study was adapted from Martinello and colleagues, 2002 (see the comparison in the table below). The adaptations were made due to subtle differences in the way data was obtained. For example, the way of measuring oxygen saturation in our study, as explained in response to comment No. 3, was obtained in a binary way (yes or no) in relation to a saturation lower than 95%. In contrast, Martinello et al., 2002 used the threshold of 87%. CSS was a way that we found to combine the data most associated with disease severity in a single parameter. It is the use of the basic principle of "reduction of dimensionality" of the problem. In our view, CSS was treated as an ordinal categorical variable, and not as a discrete variable. In fact, CSS cannot be used as a discrete value since "score # 2" is not twice as severe as score # 1, for example.

Martinello et al., 2002 This study

Assessed factors Number of points

Mechanically ventilator support 2 2

Use of supplemental oxygen 1 1

Hospital admission 1 - *

Hospitalization ≥ 5 days 1 1

Oxygen saturation ≤ 87% 1 1

ICU admission - 1

Range 0-6 points 0-5 points**

* Since virtually all patients in our study were diagnosed with SARI, they were all hospitalized. In this way, everyone would receive 1 point on the scale used by Martinello et al., 2002. As only the most serious cases required admission to ICU, we modified the score for this situation.

** In our study, a patient who was initially treated with oxygen supplementation, however, due to the worsening of the case, required mechanical ventilation received 2 points and not 3 for the fact that he was, technically, in both categories.

Comment n°5: Dyspnea (p=0.148) and respiratory distress (p=0.002) seem difficult to distinguish to me. Do the authors mean tachypnea? If so, what rate/age thresholds were used? Invasive versus non-invasive 02 therapies.

Answer: The SARI notification form used by the Brazilian health system includes both parameters: dyspnea and respiratory distress, that should be informed by the doctor or nurse during the patient's care, and yes, these are synonyms. Dyspnea is a more technical term that, according to the American Thoracic Society (ATS), is defined as a subjective experience of respiratory distress. But as people can generally only describe what they can understand, a more lay term is also present in the notification. Our group discussed the possibility of eliminating one term, but opted to keep both terms in the analysis, since this is how data was originally collected and analyzed.

Topic n°3: Viral load and clinical outcomes

Comment n°6: “According to age, median viral load was higher in children with 4 to 6 months old (63.0 261 cop/cell, p=0.007). Regarding patient clinical conditions, we found lower viral load I 262 patients with fever (26.15 cop/cell) than those without it (111.29 cop/cell; p=0.00)”. A key point is this: were those children who had no fever treated with antipyretics? If so then maybe this is an effect of the antipyretic which has been shown to increase viral shedding in animal models of RSV and duration of shedding in rhinovirus. If they were not the implication may be that fever was reflecting an antibody response to higher viral loads. (Also, write this as p<0.01.)

Answer: All clinical information was obtained from SARI notification forms. In these forms, in most cases, the drugs used in the treatment are not listed. That is why it is impossible to retrieve information about which patients used antipyretics or not. Thus, although it was a very interesting recommendation by the reviewer, unfortunately it is not possible to carry out this type of analysis.

Comment n°7: (Table 4 and line 265) “Although lacking statistical support (p=0.089), a noteworthy observation is the tendency of lower viral load in patients with elevated CSS.” The viral load analysis was performed regardless of time between symptom onset and date of collection, which, in theory, could alter the interpretation. However later it appears that they did a sensitivity analysis implying Day 7 measures had essentially the same results as other time points? It was unclear to me exactly what they mean here.

Answer: The CSS was calculated based on parameters generally associated with the severity of the infection, such as the need for intensive therapies, the use of mechanical ventilation, hospitalization, etc. When comparing the median viral load between the different clinical severity scores, we noticed a tendency for the lowest scores (less severe disease) to have a higher viral load. This observation could indicate an inversely proportional relationship between viral titers and the severity of the disease. Although it seems to be an unexpected relationship, other authors found very similar results (Haynes et al., 2013; Piedra et al., 2017). Knowing that the tendency of viral load is to decrease as the disease progresses, a possible common doubt to the reader would be whether these findings could not be associated with a bias caused by different sample collection dates. Therefore, we performed a serial analysis in which the results were very similar to the result using the sampling indistinctly from the date of collection. However, in our study there was no statistical significance for the relationship found, which limits us to go further in the discussion.

Comment n°8: The authors also found fever and viral load to be inversely related. This is important because it is counterintuitive at first blush but makes complete sense when interpreted in the context of RSV being capable of infecting via aerosols reaching the alveoli as well as droplets seeding the upper airways. If lung ultrasound data were available that would be an interesting way to address this apparent paradox. (Probably requires another paper though.)

Answer: Once again, we would like to thank the reviewer's brilliant insights. However, unfortunately, we do not have lung ultrasound data on patients. This analysis, nevertheless, can be the focus of a new prospective study for more robust investigations in this and other aspects.

Topic n°4: Race

Comment n°9: The authors’ use of race is baffling to me. Rather than using race which is suspect at the best of times, and per their discussion, especially in Brazil, could the authors use SES? If race is important, and their own discussion suggests otherwise, some classification other than color is needed. If it can’t be explained it should be dropped.

Answer: In fact, the inclusion of this discussion in the study raised doubts even among the authors. The idea would be to bring more data about a topic that has already been addressed in other studies (doi:10.1542/peds.2004-0059) and not to cause discomfort to readers. This comment was important to reinforce that the comparison between races, although in the best intention of evaluating possible differences between ancestry and response to infections, is inappropriate. In addition, as the reviewer rightly stated, our data do not suggest that there is a direct relationship between the severity of the infection and ethnicities. So, we appreciate the feedback and decided to remove this topic from the study.

Topic n°5: Climate data

Comment n°10: Line 368 on Precipitation rate and relative humidity percentage have not been shown to influence the distribution of RSV cases by Spearman's correlation test (p = 0.55 and 0.11, respectively). The mean temperature, however, showed a minor and inverse correlation with RSV infections (-0.16; p = 0.05). Please use 'did not' rather 'have not been shown' if these are your findings rather than someone else’s. If they are from someone else, please include the reference.

Answer: Those are our findings and, therefore, we made the correction as advised.

Topic n°6: Table 1

Comment n°11: Unclear why there are P-values in Table 1 unless the authors are testing a hypothesis that there were important differences between seasons. If they are, then they should say this and incorporate season as a variable in the final model

Answer: The reviewer's comment is pertinent. Yes, the p-value in table 1 resulted from a comparison of the scenarios between the seasons, which shows that some of the difference observed is not accidental. However, due to the length of the manuscript and following the suggestion of the other reviewers to decrease the size of the discussion and sharpen the focus in some areas, we chose not to discuss these results. Taking into account that data without discussion adds little to scientific knowledge, we chose to remove this statistical data from the table, which will make it cleaner and easier to interpret. We are grateful for the observation.

Comment n°12: (Comment about Table 1) The authors report (%) implying that percentages are in parentheses however it appears that it is the proportions they are reporting in parentheses.

Answer: We would like to thank the reviewer for the observation. Certainly, the header of the tables indicated that the relationship would be presented in percentage, but the data were presented in proportion. We changed the presentation to the percentage format (%) as shown in the table.

Topic n°7: Table 2

Comment n°13: This is important. I would have placed death with the outcomes/clinical profile. In demographics it is sufficient to provide the number for one gender only. Indicating the use of a specific test as a Table foot note is needed only if not already in the methods or is less commonly used.

Answer: As advised, we moved the RSV death data to the "Clinical profile" category, kept the gender data for a single gender and removed the table foot note containing the statistical tests performed, since they were frequently used methods.

Topic n°7: Table 3

Comment n°14: Table 3 appears to analyze CSS as categorical rather than ordinal data. Please be consistent with format for decimals; either, or. but do not use them interchangeably. I expect PLoS favors the US/UK format of ‘.’. It would be better to present the components of the CSS individually and the CSS itself as an ordinal variable. This would also increase the statistical power of the analysis.

Answer: As reported in comment n°4, CSS was analyzed as an ordinal variable. In addition, the components used in the construction of the CSS were treated individually in the comparison between the subtypes RSV-A and RSV-B (Table 2). Finally, we inform that we have corrected the field in which there was a "," instead of a “.” in table 3. All other numbers followed the US / UK format.

Topic n°8: Table 4

Comment n°15: Same comments as for prior tables apply. Days in intensive care should be compared using a survival analysis technique. If a p value appears as ‘= 0.000’ in computer software, please report it as p <0.001.

Answer: As requested, we performed the survival curve of patients who required admission to the ICU and, for this, we used the non-parametric Kaplan-Meier test. However, considering that of the patients with data on ICU entry and exit, only 5 died and 134 had “recovery” as an outcome, we used the cure outcome and not death as usual as "failure". That is, the test revealed that the average time until the recovery of children admitted to ICU was 8 days, from the first day of intensive care. From this, we used the Cox regression (or proportional hazards regression) in order to assess whether the viral load would have a statistically significant effect on the duration of ICU stay. Since the p-value was greater than 0.05, we can infer that there is no such effect. We emphasize that we use Schoenfeld residuals and that the proportional hazards assumption were met. We also modified presentation of the p-values as suggested by the reviewer.

Topic n°8: Figure 1

Comment n°16: Please add a second X -axis below the current one to indicate season or month. I have not been able to download the supplemental materials – I just get a pdf of the submission.

Answer: Below the X-axis we inserted three dividing lines that represent each of the years (seasons) of the study.

Topic n°9: Discussion

Comment n°17: An explanation not raised by the authors is that maybe these children had predominantly lower respiratory tract disease. This could arise where the bulk of the viral transmission occurred via the airborne rather than the large droplet route and that some of the infection started in the alveoli rather than the larger airways. This would lead to a more rapid onset and more severe disease. See above comments for the other areas of concern. This is slightly more nuanced than the previous reviewers who argue the data shows no correlation between viral load and disease. I think the nuance is warranted.

Answer: Initially, we had doubts about which point in the discussion of the results the reviewer wanted to address that question. However, we believe that it fits properly in the discussion regarding the prolonged hospital stay observed in our study. Thus, we included the following text (see answer to comment n°2):

“Although the median length of hospitalization found here is similar to some other studies [28,29], notably most studies report a shorter duration [1,4,26]. One hypothesis that could explain this finding is the fact that all children included in our study were diagnosed with SARI, which makes our study group a cohort with severe RSV infection. Another hypothesis is linked to the possibility that most of the children in the study had an infection in the lower respiratory tract. Aerosol transmission increases the chances of inhaling viral particles in the lower airways, while larger droplets are retained in the upper airways [30]. Naturally, aerosol infections tend to trigger a more severe course of infection [31].”

Topic n°9: Clinical dataset

Comment n°18: The clinical dataset does not appear to have been uploaded in the way the genetic data has. Some of the statistical choices are suboptimal but overall this is decent if unglamorous science that fits the PLoS model.

Answer: In order to meet the reviewer's requirements, we decided to upload the table with general data (including clinical data) as a supplementary table (S4 Table) in the materials and methods section. In this way, clinical data are also accessible as suggested by the reviewer. Regarding the statistical analysis, we performed the survival analysis recommended in comment n°15.

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PLoS One. doi: 10.1371/journal.pone.0251361.r005

Decision Letter 2

Baochuan Lin

13 Apr 2021

PONE-D-20-30854R2

Seasonality, molecular epidemiology and virulence of Respiratory Syncytial Virus (RSV): a perspective into the Brazilian Influenza Surveillance Program

PLOS ONE

Dear Dr. Vianna,

While the revised manuscript is scientifically sound, I have a few comments that need to be addressed. 1. Line 61-62, only one study is cited, so please change "..., other studies..." to "..., other study..." 2. S1 Table, please include PCR conditions. 3. Line 171, there is no need to cite reference 22 , suggest delete. Please change "...Sequencher 5.1 [22]." to "...Sequencher 5.1 (Gene Codes Corporation, Ann Arbor, MI, USA). 4. Line 224, please delete the statement "Male gender was slightly more affected by RSV", since it is not statistically significant and not supported by the data from 2016 (Table 1). 5. Line 232 - 235, are the number of 341, 307, 336, 342 and 252 out of the total 632 patients? I am trying to clarify whether the authors mean that out of 632 patients, 341 experienced cough and 318 (93%) are RSV+ etc.? 6. Line 272 - 274, not sure what the authors wish to convey, this sentence needs rephrasing for clarity. 7. Figure legends for figures 2&3 need correction since no highlighted in bold in the figures. 8. Line 516 - 518, delete this sentence or move to the very beginning of the conclusion.

Additionally the quality of language still needs improvement. We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.

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We look forward to receiving your revised manuscript.

Kind regards,

Baochuan Lin, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #3: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #3: I can't edit the manuscript for typos but the authors have addressed my concerns to the extent possible in their available data, and what cannot be answered should not delay the paper further.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #3: Yes: Paul Walsh

PLoS One. 2021 May 18;16(5):e0251361. doi: 10.1371/journal.pone.0251361.r006

Author response to Decision Letter 2

21 Apr 2021

We thank the editor for the critical assessment of our manuscript. In the following we address the concerns point by point.

Editor’s comments:

While the revised manuscript is scientifically sound, I have a few comments that need to be addressed.

Comment n°1: Line 61-62, only one study is cited, so please change "..., other studies..." to "..., other study..."

Reply: We have done so.

Comment n°2: S1 Table, please include PCR conditions.

Reply: As suggested, we include thermocycling conditions for each set of primers and probes used.

Comment n°3: Line 171, there is no need to cite reference 22, suggest delete. Please change "...Sequencher 5.1 [22]." to "...Sequencher 5.1 (Gene Codes Corporation, Ann Arbor, MI, USA).

Reply: We removed the reference and included the recommended excerpt.

Comment n°4: Line 224, please delete the statement "Male gender was slightly more affected by RSV", since it is not statistically significant and not supported by the data from 2016 (Table 1).

Reply: We have done so.

Comment n°5: Line 232 - 235, are the number of 341, 307, 336, 342 and 252 out of the total 632 patients? I am trying to clarify whether the authors mean that out of 632 patients, 341 experienced cough and 318 (93%) are RSV+ etc.?

Reply: We are grateful for the editor's observation, as this would possibly be a common question for readers. Therefore, we decided to include the following excerpt in the caption of Table 2:

“Although the study included 352 patients with RSV, it is possible to observe that the denominators in the clinical profile differ from this number. This occurred because not all clinical data were recorded for all patients.”

Comment n°6: Line 272 - 274, not sure what the authors wish to convey, this sentence needs rephrasing for clarity.

Reply: We rephrased the sentence as follows:

“However, a segmented analysis (0-3; 4-7 and >7 days between symptom onset and sample collection) revealed very similar results. Furthermore, of the 156 samples used to measure viral titers, only 26 (16%) were collected 7 days after symptoms onset. Therefore, we prefer to maintain full sampling for viral load analysis.”

Comment n°7: Figure legends for figures 2&3 need correction since no highlighted in bold in the figures.

Reply: Fixed.

Comment n°8: Line 516 - 518, delete this sentence or move to the very beginning of the conclusion.

Reply: The section was deleted.

Comment n°9: Additionally the quality of language still needs improvement. We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.

Reply: Manuscript editing was performed by other two researchers with proficiency in the English language and also by a professional reviewer with experience in scientific journals. We hope that this time the spelling, grammar, and language are in perfect harmony with the formal language.

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PLoS One. doi: 10.1371/journal.pone.0251361.r007

Decision Letter 3

Baochuan Lin

26 Apr 2021

Seasonality, molecular epidemiology, and virulence of Respiratory Syncytial Virus (RSV): a perspective into the Brazilian Influenza Surveillance Program

PONE-D-20-30854R3

Dear Dr. Vianna,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Baochuan Lin, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0251361.r008

Acceptance letter

Baochuan Lin

4 May 2021

PONE-D-20-30854R3

Seasonality, molecular epidemiology, and virulence of Respiratory Syncytial Virus (RSV): a perspective into the Brazilian Influenza Surveillance Program

Dear Dr. Vianna:

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Supplementary Materials

S1 Fig. Map of the Espirito Santo State (Brazil) and its federal highways.

(TIF)

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S2 Fig. RSV-A phylogenetic tree based on 336 bp of the HVR-2 of G gene.

(TIF)

Click here for additional data file.^{(10.4MB, tif)}

S3 Fig. RSV-A phylogenetic tree based on 318 bp of the HVR-2 of G gene.

(TIF)

Click here for additional data file.^{(10.3MB, tif)}

S4 Fig. Survival curve in relation to ICU length of stay estimated by the Kaplan-Meier test.

Given the small number of deaths, it was necessary to modify the analysis to assess the likelihood of cure.

(TIF)

Click here for additional data file.^{(6.7MB, tif)}

S5 Fig. Graph of Schoenfeld residues: There was no marked trend, indicating that the premises for the application of the Cox model were met.

(TIF)

Click here for additional data file.^{(5.7MB, tif)}

S1 Table. Primers, probes, and DNA fragments used in the study.

“F”, “R”, and “P”, represent the sequence of the forward and reverse primers, and the probe, respectively. A synthetic DNA fragment from RSV was included in a pMA-t vector.

(DOCX)

Click here for additional data file.^{(22.4KB, docx)}

S2 Table. List of the sequences used to build the phylogeny based on HVR-2 of gene G for both subtypes RSA-A and RSV-B.

(DOCX)

Click here for additional data file.^{(21.8KB, docx)}

S3 Table. List of the sequences used to build the phylogeny based on gene G for both subtypes RSV-A and RSV-B.

The collection date of some sequences was unavailable.

(DOCX)

Click here for additional data file.^{(43.3KB, docx)}

S4 Table. General table that provides all epidemiological, clinical, and climatic data of the study.

(XLSX)

Click here for additional data file.^{(182KB, xlsx)}

S5 Table. Cox (proportional hazards) regression: Given that the p-value is >0.05, it can be inferred that the viral load has no significant effect on ICU length of stay.

(DOCX)

Click here for additional data file.^{(12.7KB, docx)}

S6 Table. Proportional hazards assumption test: The premises for the application of the Cox model were met.

(DOCX)

Click here for additional data file.^{(12.4KB, docx)}

S7 Table. Duration and climatic characteristics of RSV seasonality in the years studied.

(DOCX)

Click here for additional data file.^{(18.5KB, docx)}

S8 Table. List of amino acid changes in RSV-A.

Residues in blue and red show potential losses and gains of O-glycosylation sites, respectively.

(XLSX)

Click here for additional data file.^{(19.4KB, xlsx)}

S9 Table. List of amino acid changes in RSV-B.

Residues in blue and red show potential losses and gains of O-glycosylation sites, respectively.

(XLSX)

Click here for additional data file.^{(15.3KB, xlsx)}

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Data Availability Statement

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PERMALINK

Seasonality, molecular epidemiology, and virulence of Respiratory Syncytial Virus (RSV): A perspective into the Brazilian Influenza Surveillance Program

Lucas A Vianna

Marilda M Siqueira

Lays P B Volpini

Iuri D Louro

Paola C Resende

Roles

Abstract

Background

Objectives

Methodology

Results

Conclusion

Introduction

Materials and methods

Population sampling, study period, and location

RSV and influenza detection and subtyping

Clinical and epidemiological data collection

Viral load quantification

Climate data collection

Partial amplification and sequencing of glycoprotein gene

RSV genotyping and gene G phylogenetic reconstruction

Statistical treatment

Ethics statement

Results

RSV clinical and epidemiological data

Table 1. Number of tested samples, RSV positivity, subtype prevalence, and demographic data from each year and the whole study period.

Table 2. Summary of clinical and epidemiological data by RSV+ and each subtype.

Table 3. Clinical Severity Score (CSS): Scores varied from 0 to 5.

Viral load

Table 4. Comparison of viral load values between gender, age, outcome, and clinical condition.

Viral seasonality and climatic analysis

Fig 1. Circulation of RSV-A and RSV-B between 2016 and 2018 in Espirito Santo State.

Phylogeny of RSV and genetic analysis

Fig 2. RSV-A phylogenetic tree.

Fig 3. RSV-B phylogenetic tree.

Discussion

RSV is prevalent in Brazilian children with SARI

The subtype but not the viral load appears to be associated with disease severity

The seasonal period of RSV may fluctuate and its circulation is slightly associated with temperature

ON1 and BA were the only genotypes detected

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Baochuan Lin

Roles

Author response to Decision Letter 0

Decision Letter 1

Baochuan Lin

Roles

Author response to Decision Letter 1

Decision Letter 2

Baochuan Lin

Roles

Author response to Decision Letter 2

Decision Letter 3

Baochuan Lin

Roles

Acceptance letter

Baochuan Lin

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

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