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Characterization of circulating RSV strains among subjects in the OUTSMART-RSV surveillance program during the 2016-17 winter viral season in the United States

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Background Respiratory syncytial virus (RSV) is an established cause of serious lower respiratory disease in infants, elderly and high-risk populations. The OUTSMART surveillance program aims to characterize patient populations and currently circulating RSV strains, and monitor temporal and geographic evolution of RSV F and G proteins in the U.S. Methods The OUTSMART 2016–17 study collected RSV-positive samples from 25 RSVAlert® laboratories from 4 U.S. regions and Puerto Rico during November 2016 through March 2017. Frequencies of A and B subtypes and genotypes were determined for several demographic and geographic variables. To gauge the representativeness of the OUTSMART patients, results were compared to discharge data from the NEDS and NIS databases. Results A total of 1,041 RSV-positive samples with associated demographic data were obtained and the RSV F gene and second variable region of the G gene were sequenced. The majority of samples (76.0%) came from children under 2 years old: <1 year (48.4%), 1–2 years (27.6%). The OUTSMART patient sample was similar to NEDS and NIS for age, gender, and geographic location. Both OUTSMART and national RSV cases peaked in January. Of OUTSMART samples, 45.3% were subtype A, 53.7% were subtype B and 1.0% were mixed A and B. The percentage of RSV B cases increased with increasing age. Hospitalization (length of hospital stay, LOS, >24 hrs) occurred in 29.0% of patients of which 52.0% had RSV B. Outpatients (LOS <24 hrs) were 64.4% of total of which 73.3% were diagnosed in the ER and discharged, while only 6% were diagnosed in other outpatient settings. Conclusions The OUTSMART 2016–17 study was representative of the U.S. RSV experience. Geographic and temporal information from the RSV surveillance program will be used to establish a molecular baseline of RSV F and G sequence variability and to help inform development of novel agents for RSV prophylaxis and treatment.
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RESEARCH ARTICLE
Characterization of circulating RSV strains
among subjects in the OUTSMART-RSV
surveillance program during the 2016-17
winter viral season in the United States
Alexey Ruzin
1
*, Susan T. Pastula
2
, Elizabeth Levin-Sparenberg
2
, Xiaohui Jiang
2
,
Jon Fryzek
2
, Andrey Tovchigrechko
1
, Bin Lu
3
, Yanping Qi
3
, Hui Liu
3
, Hong Jin
3
, Li Yu
1
,
Judith Hackett
1
, Tonya Villafana
1
, Mark T. Esser
1
1AstraZeneca/MedImmune, Gaithersburg, Maryland, United States of America, 2Epidstat Institute, Ann
Arbor, Michigan, United States of America, 3AstraZeneca/MedImmune, Mountain View, California, United
States of America
*ruzina@medimmune.com
Abstract
Background
Respiratory syncytial virus (RSV) is an established cause of serious lower respiratory dis-
ease in infants, elderly and high-risk populations. The OUTSMART surveillance program
aims to characterize patient populations and currently circulating RSV strains, and monitor
temporal and geographic evolution of RSV F and G proteins in the U.S.
Methods
The OUTSMART 2016–17 study collected RSV-positive samples from 25 RSVAlert
®
labo-
ratories from 4 U.S. regions and Puerto Rico during November 2016 through March 2017.
Frequencies of A and B subtypes and genotypes were determined for several demographic
and geographic variables. To gauge the representativeness of the OUTSMART patients,
results were compared to discharge data from the NEDS and NIS databases.
Results
A total of 1,041 RSV-positive samples with associated demographic data were obtained
and the RSV F gene and second variable region of the G gene were sequenced. The major-
ity of samples (76.0%) came from children under 2 years old: <1 year (48.4%), 1–2 years
(27.6%). The OUTSMART patient sample was similar to NEDS and NIS for age, gender,
and geographic location. Both OUTSMART and national RSV cases peaked in January. Of
OUTSMART samples, 45.3% were subtype A, 53.7% were subtype B and 1.0% were mixed
A and B. The percentage of RSV B cases increased with increasing age. Hospitalization
(length of hospital stay, LOS, >24 hrs) occurred in 29.0% of patients of which 52.0% had
RSV B. Outpatients (LOS <24 hrs) were 64.4% of total of which 73.3% were diagnosed in
the ER and discharged, while only 6% were diagnosed in other outpatient settings.
PLOS ONE | https://doi.org/10.1371/journal.pone.0200319 July 24, 2018 1 / 16
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OPEN ACCESS
Citation: Ruzin A, Pastula ST, Levin-Sparenberg E,
Jiang X, Fryzek J, Tovchigrechko A, et al. (2018)
Characterization of circulating RSV strains among
subjects in the OUTSMART-RSV surveillance
program during the 2016-17 winter viral season in
the United States. PLoS ONE 13(7): e0200319.
https://doi.org/10.1371/journal.pone.0200319
Editor: Stephania A Cormier, Louisiana State
University System, UNITED STATES
Received: April 7, 2018
Accepted: June 22, 2018
Published: July 24, 2018
Copyright: ©2018 Ruzin et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant
surveillance data are within the paper and its
Supporting Information files. The analysis code
and reference data specific to the bioinformatics
portion of the project are available at (https://
github.com/andreyto/rsv_epi_2017_suppl).
Funding: This work was supported by
AstraZeneca/MedImmune. The funder had no role
in study design, data collection and analysis,
Conclusions
The OUTSMART 2016–17 study was representative of the U.S. RSV experience. Geo-
graphic and temporal information from the RSV surveillance program will be used to estab-
lish a molecular baseline of RSV F and G sequence variability and to help inform
development of novel agents for RSV prophylaxis and treatment.
Introduction
Respiratory syncytial virus (RSV) is an established cause of serious lower respiratory disease,
particularly among children [1]. RSV typically exhibits distinct seasonality in temperate
regions, with onset beginning in late fall or early winter, and ending in late spring [1].
In 2015 there were an estimated 33 million RSV infections globally in children under 5
years old, resulting in about 3 million hospitalizations and 60,000 deaths [2]. In the U.S.,
approximately 2.1 million children under age 5 require medical care for RSV each year, with
3% hospitalized, 25% treated in emergency departments (ED), and 73% seen in pediatric prac-
tices [3]. Reinfection is common throughout life, although symptoms in adults and older chil-
dren are often milder or absent [4].
Recent studies reported that among viral respiratory admissions of young children, RSV
hospitalizations are 6–14 times higher than for influenza [5,6]. In the U.S., annual costs for
RSV in children under 5 are estimated to be $400 million for RSV hospitalizations, $258 mil-
lion for ambulatory medical care and more than $300 million for direct hospital charges [7,8].
RSV is a non-segmented, single strand negative virus comprised of 11 proteins including 3
surface proteins (F, G, SH), of which F and G are the most important as they elicit both neu-
tralizing and non-neutralizing antibodies. RSV has two major subtypes, A and B, based on
antigenic and genetic variation in the G attachment protein [9]. The F fusion protein is highly
conserved with 90% sequence identity between the subgroups [10], elicits broadly neutralizing
antibodies, and is the target of the licensed mAb, palivizumab [11]. The F protein is also the
target of a more potent neutralizing mAb, MEDI8897, with half-life extension technology that
is currently being evaluated in pre-term infants [12,13]. In contrast, the heavily glycosylated G
attachment protein is highly variable, differing by 53% at the amino acid level between A and
B subtypes [10].
A number of studies show RSV A and B can cocirculate during a single epidemic and tem-
poral and geographic clustering of RSV genotypes can occur [14]. The evolution of RSV geno-
types through accumulated changes in amino acids of the G protein are likely due to immune
pressure from neutralizing antibodies elicited following infection [15,16]. RSV is sub-classi-
fied into 13 RSV A genotypes and 20 RSV B genotypes based on the second hyper-variable
region of the G gene [17,18]. Currently, predominate RSV B genotypes are derived from the
Buenos Aires strain, first identified in 1999, which has a 60 base pair duplication in the second
hyper-variable region of the G gene [19]. The predominant RSV A genotypes are derived from
Ontario 1 (ON1), first described in 2006, which has a 72 base pair duplication in the G protein
[20]. Numerous studies compared the severity of RSV A and B infections in hospitalized chil-
dren with inconsistent results as to which subtype is more likely to cause severe infections
[14]. These conflicting reports suggest temporal and geographic differences may be important
in understanding the association of RSV genotype and disease and that monitoring the molec-
ular evolution of RSV would be useful in assisting the development of anti-RSV drugs and pro-
phylactic approaches.
U.S. RSV surveillance winter 2016-17
PLOS ONE | https://doi.org/10.1371/journal.pone.0200319 July 24, 2018 2 / 16
decision to publish, or preparation of the
manuscript.
Competing interests: This work was sponsored by
AstraZeneca/MedImmune. AR, AT, BL, YQ, HL, HJ,
LY, JH, TV, and ME are employees and
stockholders of AstraZeneca/MedImmune. SP, EL-
S, XJ, and JF are employees of EpidStat Institute,
which is a research institute that provides expert
assistance on the evaluation of complex health
issues and on the conduct and interpretation of
epidemiological studies to pharmaceutical and
medical device companies, and are paid
consultants to AstraZeneca. ME, AR, HL, and LY
(AstraZeneca/MedImmune) conceptualized the
study design and set up data collection. XJ, SP, EL-
S, JF, ME, AR, BL, YQ, HL, AT, HJ, JH, and TV
made contributions to the analysis and
interpretation of the data (AstraZeneca/
MedImmune and EpidStat). SP, EL-S, ME, AR, and
TV (AstraZeneca/MedImmune and EpidStat)
drafted the manuscript and, along with BL, HJ, YQ,
JH, (AstraZeneca/MedImmune) critically revised
the manuscript. ME, AR, LY, TV, AT, SP, EL-S, and
JF (AstraZeneca/MedImmune and EpidStat) were
active participants in discussions regarding the
development of the manuscript and decision to
publish. This does not alter our adherence to PLOS
ONE policies on sharing data and materials.
AstraZeneca/Medimmune and Epidstat had no
direct roles in study design, data collection,
analysis, manuscript development or revision.
Abbreviations: ED, Emergency Department; ER,
Emergency Room; HCUP, Healthcare Cost and
Utilization Project; ICD9-CM, International
Classification of Diseases, Ninth Revision, Clinical
Modification; LOS, length of stay; mAb,
monoclonal antibody; NA, Not Available; NEDS,
National Emergency Department Sample; NIS,
National Inpatient Sample; OUTSMART,
Observational United States Targeted Surveillance
of Monoclonal Antibody Resistance and Testing;
PCR, Polymerase Chain Reaction; QNS, Quality/
Quantity Not Sufficient; RNA, Ribonucleic Acid;
RSV, Respiratory Syncytial Virus; UTM, Universal
Transport Medium; VTM, Viral Transport Medium.
The first experimental RSV vaccine was tested in the 1960s and not only failed to protect
against RSV in clinical trials, but led to enhanced disease following subsequent RSV infection
such that 80% of infants who received the vaccine were hospitalized and two died [21,22]. A
successful passive immunization approach with immunoglobulin was developed over 25 years
later with the approval of Respigamin 1996 [23] followed by the approval of a monoclonal
antibody (mAb), palivizumab (Synagis) in 1998 [24]. Currently, Palivizumab is the only pro-
phylactic agent approved by the FDA for prevention of RSV in high-risk infants and children
[25]. Although rare, Palivizumab resistant viruses have been identified in the clinical setting
[26]. Several novel vaccines and mAbs are in development to prevent RSV disease in infants
and the elderly [2729]. To assist with medical decision making regarding current RSV pro-
phylaxis and to help inform the development of new agents, the RSVAlert system was devel-
oped [30]. RSVAlert currently tracks RSV testing and results from approximately 480 hospital
laboratories across the U.S. (https://rsvalert.com). The Observational United States Targeted
Surveillance of Monoclonal Antibody Resistance and Testing of RSV (OUTSMART-RSV) pro-
gram was developed to collect samples and associated case information and to provide F and
G sequence data from a subset of laboratories participating in RSVAlert. OUTSMART was
piloted in 2015–2016 and allows more complete characterization of currently circulating
strains, including their temporal and geographic evolution in the U.S., and further characteri-
zation of the RSV patient population.
Materials and methods
Study design
The OUTSMART 2016–17 study collected and analyzed a series of RSV-positive samples and
associated anonymized, demographic data from a subset of hospital-based laboratories partici-
pating in RSVAlert and included 25 laboratories from 4 U.S. regions and Puerto Rico during
November 2016 to March 2017 (Fig 1). Participating laboratories were selected and recruited
based on their geographic location to represent all US regions including: West (including
Alaska and Hawaii), Midwest, South, Northeast and Puerto Rico. The number of sites per each
region were selected to provide approximately equal representation by region. Historical
reporting of >50 RSV-positive samples per season to RSVAlert system was also taken into
consideration during the site selection. Additionally, RSVAlert provided numbers of RSV-
positive tests and total RSV tests conducted per month for each of the participating laborato-
ries (S1 Data).
Sample collection and analysis
Participating laboratories were instructed to provide a single RSV-positive respiratory sample
(in UTM or VTM) per patient for a maximum of ten samples each month during the five
months of the study period, resulting in a maximum total of 50 samples from each laboratory
throughout the study period. The sites were instructed to provide the first 10 RSV-positive
samples collected from the beginning of each month. The variability in the number of samples
received from each site is primarily attributed to RSV-positive sample availability at that site
for each month (some sites received less than 10 samples in a given month) and also by the
compliance of each site to the study protocol. One laboratory, provided forty purified RSV
RNA samples. In addition to samples, information collected included lab location (U.S. region
and division, state, county, city, zip), date of sample collection, sample number, de-identified
patient information such as age, gender, and length of hospital stay (LOS)(S2 Data). In this
study, inpatients and outpatients were defined as those with LOS of either >24 hours or <24
hours in the hospital, respectively.
U.S. RSV surveillance winter 2016-17
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Sequencing and bioinformatic analyses
Next generation sequencing (NGS) using the MiSeq (Illumina) was conducted on the PCR-
amplified second hypervariable region of the G gene and the full-length F gene. Samples that
did not generate at least 1,000 mapped reads with at least 4-fold depth of coverage of both F
and G genes were marked as QNS and were excluded from the analysis. Contigs were con-
structed from the de-multiplexed MiSeq reads using Geneious software (Version 10.0.9, Bio-
matters Inc. Newark, NJ). A multiple sequence alignment (MSA) was built from the translated
G protein sequences using MAFFT [31], and pairwise dissimilarity matrix was computed
using Bishop–Friday substitution model [32]. To reduce the effects of PCR and sequencing
artifacts, sequences were clustered at 97% similarity cutoff. A single representative sequence
was picked within each cluster to build a neighbor-joining phylogenetic tree [33]. Detailed
sequencing and bioinformatic methods are available in S1 Text.
Comparison to national databases
To assess the representativeness of the OUTSMART patient sample with that of the U.S.,
results were compared to discharge data from the November 2013-March 2014 Nationwide
Fig 1. Map of participating OUTSMART laboratories during the 2016–2017 season. Pie-charts represent proportions of RSV A (blue), RSV B (orange),RSV A+B
(red) and QNS (yellow) samples per lab. Numbers within the pie charts represent the total number of samples per lab.
https://doi.org/10.1371/journal.pone.0200319.g001
U.S. RSV surveillance winter 2016-17
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Emergency Department Sample (NEDS) [34] and the National Inpatient Sample (NIS) [35].
The NIS is a nationally representative sample of hospital inpatient stays and the NEDS is a
nationally representative sample of hospital-based ED visits. Both were developed by the
Healthcare Cost and Utilization Project (HCUP) and sponsored by the Agency for Healthcare
Research and Quality (AHRQ). The NEDS contains data from approximately 30 million all-
payer ED visits annually, and when weighted, represents approximately 135 million ED visits.
The NIS contains records from more than 7 million all-payer hospital stays annually and rep-
resents more than 35 million hospitalizations when weighted. Both databases contain multiple
diagnostic codes for each hospitalization or ED visit, based on the International Classification
of Diseases,Ninth Revision,Clinical Modification (ICD-9-CM; hereafter, described as ICD-9).
During the study period, there were 3 RSV-specific ICD-9 codes: 480.1: Pneumonia due to
RSV; 466.11: Bronchiolitis due to RSV; and 079.6: RSV. Our analysis included all hospitaliza-
tions and ED visits with at least one of the three RSV-specific ICD-9 codes listed in any diag-
nostic position in the patient record. Frequencies of ED visits and hospitalizations were
calculated by age group, gender, U.S. region, and month based on the weighted estimate of
total number of hospitalizations or ED visits due to RSV during the study period.
Statistical methods
Frequencies of A and B subtypes were calculated by age group, gender, LOS, and U.S. region.
The frequency of samples per month for each lab was also determined as was the percent posi-
tive among all tests conducted for each month, and for each month by RSV subtype. The per-
cent of RSV B between age groups was compared using logistic regression with a Bonferroni
correction to adjust for multiple comparisons. Chi-square tests were used to compare the age
distributions in OUTSMART with the national samples. All data management and statistical
analyses for this study were carried out using SAS version 9.4 (SAS Institute Inc., Cary, NC,
USA), with procedures that incorporated NIS- and NEDS-provided weights to account for the
structure of the sample survey data.
Results
The twenty-five laboratories that participated in OUTSMART throughout the U.S. West
(including Alaska and Hawaii), Midwest, South, Northeast regions and Puerto Rico (Fig 1)
reported a total of 9,758 RSV-positive tests (10.7%) out of 90,840 tests conducted during
November 2016—March 2017. Of the 25 participating laboratories, 16 submitted less than 50
samples (range: 23–48), 6 submitted 50 samples, and 1 laboratory submitted more than 50
samples (n = 60), resulting in a subset of 1,041 RSV positive samples with associated demo-
graphic data that were submitted to the OUTSMART surveillance program for F and G
sequencing analyses to characterize variability of the F and G antigens and to determine the
temporal and geographic distributions of RSV A and B genotypes. Of the 1,041 RSV positive
samples, 836 samples (80.3%) yielded specific PCR amplified fragment of sufficient quantity
and quality suitable for sequencing analysis. The remaining samples (205 samples; 19.7%)
were marked as QNS (quantity/quality non-sufficient) and were not used in sequencing analy-
sis as they failed to produce enough material suitable for sequencing. Thus, all samples with
sufficient quantity and quality of DNA were sequenced and analyzed.
The monthly positive samples were reported by RSV subtype and the temporal distribution
of both A and B subtypes was generally similar (Fig 2A). The number of positive samples for
subtype B and subtype A peaked in December 2016 and January 2017, respectively. To deter-
mine if the seasonality pattern identified in the OUTSMART study was generalizable to the
U.S. RSV experience, OUTSMART data was compared with NEDS and NIS databases. The
U.S. RSV surveillance winter 2016-17
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proportion of positive RSV tests out of all RSV tests conducted by OUTSMART participating
laboratories had an approximately normal distribution which peaked in January and was simi-
lar to that of the NEDS and NIS databases (Fig 2B).
OUTSMART subject demographics were also similar to NEDS and NIS. The largest disease
burden was in those <1 year (OUTSMART: 48.4%, NEDS 59.7%, NIS 57.8%), followed by the
1–2 year age group (OUTSMART: 27.6%, NEDS 28.2%, NIS 22.3%) (Table 1). The databases
were also similar by gender (Percent male—OUTSMART: 53.1%, NEDS 53.8%, NIS 54.6%)
(Table 1), and region. The largest proportions of cases occurred in the South (OUTSMART:
27.2%, NEDS: 34.4%, NIS: 37.8%), though the national samples had larger proportions of sam-
ples from the South than OUTSMART (Table 1). Subtype B was more frequent in the Midwest
and South regions. The Northeast and West had almost equal distributions of A and B sub-
types (Fig 1 and S1 Table).
There were 387 subtype A and 457 subtype B viral sequences determined from the five dif-
ferent geographic regions. These sequences were assigned to genotypes based on the sequence
of the second hyper-variable region of G gene. All RSV A samples belonged to the Ontario 1
(ON1) genotype [20] and all RSV B samples belonged to the Buenos Aires 9 (BA9) genotype
[19], except one which belonged to the Buenos Aires 10 (BA10) genotype. In addition, we
combined RSV A and RSV B sequences into distinct sub-genotypes or clusters based upon a
97% identity in the G second hyper-variable region (61 clusters for RSV A and 73 clusters for
RSV B) and mapped them to different geographic regions (Fig 3). This analysis revealed that
the 5 most frequent RSV A clusters comprised 48% of the 387 RSV A samples and the 5 most
frequent RSV B clusters comprised 39% of the 457 RSV B samples. There were no obvious
Fig 2. Temporal distributions of RSV positive tests. (A) OUTSMART 2016–17 RSV positive tests by RSV subtype. (B) All RSV positive tests in OUTSMART—
participating laboratories, and RSV in NEDS and NIS.
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U.S. RSV surveillance winter 2016-17
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differences in geographic distribution of these strains in the West, Midwest, South and North-
east suggesting they were broadly distributed across the different U.S. regions.
The age distributions of OUTSMART samples were compared separately for inpatient and
ER admissions with the two different national databases. OUTSMART inpatients included
fewer infants <1 year old than NIS (46.7% vs. 57.8%) and more older patients over age 60
(13.9% vs. 8.2%) (Table 2). The distribution of ER patients by age was similar in the OUT-
SMART and NEDS databases (Table 2).
Of the OUTSMART samples with determined RSV subtype (n = 836; 80.3%), 45.3% were
subtype A, 53.7% were subtype B, and 1% had both A and B subtypes (Fig 4 and S2 Table).
Most samples (76.0%) came from children 2 years of age: <1 year (48.4%) and 1–2 years
(27.6%) (Table 1). RSV B was more frequent in all ages with the exception of <1 month and
1–2 year old children, in which RSV A was more common (Fig 3). The highest proportion of
RSV B cases (73.4%) was observed in subjects ages 60+ followed by the 6-59-year-old group
(71.9%) (Fig 4 and S2 Table).
Severity of illness associated with RSV subtype, gender, or age was explored by categoriz-
ing RSV hospitalizations into LOS <24 hours and >24 hours. Hospitalizations >24 hours
occurred among 29.0% of patients. Young children, 2 years of age, were the most fre-
quently seen with RSV as both inpatients (214/302, 70.9%) and outpatients (546/670, 81.5%).
(Table 3). LOS was stratified by referring department (Table 4) and 73.3% (n = 491) of RSV
subjects with <24 hour LOS had samples collected from the ED and were discharged whereas
only 6% of the samples came from an outpatient setting such as a doctor’s office. In contrast,
only 19.2% of inpatient RSV cases were diagnosed in the ER with a significant number of
samples coming from the pediatric intensive care unit and ICU. However, no information
was provided for 55.3% of inpatient RSV cases (Table 4). These data suggest that a significant
Table 1. Comparison of OUTSMART November 2016—March 2017 RSV positive tests with RSV in NEDS and NIS November 2013-March 2014 by age, gender and
region.
OUTSMART NEDS
a,c
NIS
b,c
N % N % N %
Age <1 year 504 48.4% 66,982 59.7% 39,130 57.8%
1–2 year 287 27.6% 31,628 28.2% 15,070 22.3%
3–5 year 74 7.1% 6,293 5.6% 3,750 5.5%
6–59 year 90 8.6% 2,958 2.6% 4,195 6.2%
60+ year 86 8.3% 4,352 3.9% 5,545 8.2%
All 1,041 100.0%112,213 100.0%67,690 100.0%
Gender Male 553 53.1% 60,449 53.8% 37,030 54.6%
Female 488 46.9% 51,841 46.2% 30,830 45.4%
All 1,041 100.0%112,290 100.0%67,860 100.0%
Region Mid-West 241 23.2% 34,258 30.5% 15,800 23.3%
North East 219 21.0% 19,509 17.4% 13,005 19.2%
South 283 27.2% 38,611 34.4% 25,640 37.8%
West 263 25.3% 19,912 17.7% 13,415 19.8%
PR 35 3.4% - - - -
Total 1,041 100.0%112,290 100.0%67,860 100.0%
a
NEDS: National Emergency Room Sample—Approx. 20% stratified sample of U.S. emergency room visits
b
NIS: National Inpatient Sample—Approx. 20% stratified sample of U.S. hospital discharges
c
RSV identified by ICD-9 codes 480.1, 466.11, 079.6 in NEDS and NIS
https://doi.org/10.1371/journal.pone.0200319.t001
U.S. RSV surveillance winter 2016-17
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proportion of RSV disease in both the young and the old is managed in the emergency room
without admitting the subject into the hospital.
Discussion
The OUTSMART RSV surveillance program characterizes circulating RSV strains and moni-
tors their temporal and geographic evolution in the U.S. to help inform the development of
Fig 3. RSV A and B genotypes of 2016–17 OUTSMART samples by geographic region. The phylogenetic tree in the
left panel was built using the representative G protein sequences from 97%-identity clusters, with the horizontal scale
under the tree showing branch lengths derived from the dissimilarity metric. The corresponding bars in the right panel
represent the number of samples in each cluster, with horizontal scale under the bar plot showing sample counts.
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U.S. RSV surveillance winter 2016-17
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anti-RSV mAbs and vaccines. RSV surveillance is also important in providing timely informa-
tion to physicians for the administration of Palivizumab to eligible high-risk infants [36,37].
The OUTSMART program was generally representative of the U.S. RSV infection experience
in terms of age, gender distribution and seasonality compared to national data (Fig 2B). The
OUTSMART RSV program is designed to run for several years to monitor temporal and
regional differences in predominant subtype [38,39], specifically in the southeastern U.S.
where the RSV season typically begins earlier and lasts longer [40,41] than in other areas of
the country. RSV surveillance is additionally conducted by the Centers for Disease Control
and Prevention (NREVSS) [42], the international Respiratory Syncytial Virus Network
(ReSVinet) [43] and the European Influenza Surveillance Network (EISN) [44]. While all show
differences in onset and length of RSV seasons depending on regional setting, none provide
molecular typing of strains or characterize them temporally or geographically. This study,
which characterized both G and F genotypes, along with surveillance data from these other
networks can help inform timing of administration of a mAb or vaccine in clinical trials and
provide a baseline for molecular heterogeneity of viruses currently in circulation prior to test-
ing and licensure of an RSV mAb or vaccine [36,37].
Compared to the national databases for inpatient and emergency admissions, OUT-
SMART-participating laboratories differed in their age distributions of annual positive RSV
cases (Chi-square p-value <0.001 and 0.010, respectively) (Table 2). This may have been due
to patient sampling or a shift in age-specific infection rates since the national data were from a
different season compared to OUTSMART. As the OUTSMART program progresses, accu-
mulation of results from additional seasons will allow for a more accurate comparison to
national trends.
Table 2. OUTSMART November 2016—March 2017 RSV positive inpatient and Emergency Room cases com-
pared with NIS and NEDS RSV positive cases during November 2013-March 2014 by age group.
Age OUTSMART Inpatient
a
NIS
b,d
N % N %
<1 year 141 46.7% 39,130 57.8%
1–2 year 73 24.2% 15,070 22.3%
3–5 year 20 6.6% 3,750 5.5%
6–59 year 26 8.6% 4,195 6.2%
60+ year 42 13.9% 5,545 8.2%
Total 302 100.0%67,690 100.0%
Age OUTSMART Emergency Room/
department
NEDS
c,d
N % N %
<1 year 305 55.6% 66,982 59.7%
1–2 year 176 32.1% 31,628 28.2%
3–5 year 32 5.8% 6,293 5.6%
6–59 year 24 4.4% 2,958 2.6%
60+ year 12 2.2% 4,352 3.9%
Total 549 100.0%112,213 100.0%
a.
OUTSMART Inpatient: Length of stay>24 hr
b.
NIS: National Inpatient Sample—Approx. 20% stratified sample of U.S. hospital discharges
c.
NEDS: National Emergency Room Sample—Approx. 20% stratified sample of U.S. ER visits
d.
RSV identified by ICD-9 codes 480.1, 466.11, 079.6 in NIS
https://doi.org/10.1371/journal.pone.0200319.t002
U.S. RSV surveillance winter 2016-17
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Fig 4. OUTSMART 2016–17 percent RSV-positive tests by age and subtype. Error bars represent 95% confidence intervals.
https://doi.org/10.1371/journal.pone.0200319.g004
Table 3. OUTSMART 2016–17 RSV-positive tests by LOS, age and subtype.
LOS Age RSV subtype All
A B A+B QNS
N % N % N % N N %
<24 hr
a
2 year 227 47.3% 248 51.7% 5 1.0% 66 546 52.4%
3–59 year 24 33.8% 46 64.8% 1 1.4% 31 102 9.8%
60 year 3 20.0% 12 80.0% 0 0% 7 22 2.1%
Total 254 44.9%306 54.1%6 1.1%104 670 64.4%
>24 hr
a
2 year 86 52.8% 76 46.6% 1 0.6% 51 214 20.6%
3–59 year 10 40.0% 15 60.0% 0 0% 21 46 4.4%
60 year 9 27.3% 24 72.7% 0 0% 9 42 4.0%
Total 105 47.5%115 52.0%1 0.5%81 302 29.0%
NA 2 year 12 52.2% 11 47.8% 0 0% 8 31 3.0%
3–59 year 3 30.0% 6 60.0% 1 10.0% 6 16 1.5%
60 year 5 31.3% 11 68.8% 0 0% 6 22 2.1%
Total 20 40.8%28 57.1%1 2.0%20 69 6.6%
Total 379 45.3%449 53.7%8 1.0%205 1,041
b
100.0%
a.
<24 hours defined as outpatient, >24 hours defined as inpatient
b.
836 total samples with known subtype, 205 QNS
https://doi.org/10.1371/journal.pone.0200319.t003
U.S. RSV surveillance winter 2016-17
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There were limitations to this study design, which was intended to cover all 4 regions and 9
divisions of the country defined by the U.S. census. Some areas were not as well represented as
others such as the upper Midwest and West. When comparing data to national trends, NIS
and NEDS estimates are based on ICD9 codes and not laboratory-confirmed diagnoses, so
comparability to the OUTSMART data is limited. OUTSMART could not be compared to the
national sample from the same season because the 2016–17 national data was not yet available.
Lastly, the use of hospital-based laboratory data on RSV infections markedly underestimates
the full burden of RSV disease in the U.S. However, because these cases are laboratory-verified,
the data are useful in providing additional information on hospital and ER burden of RSV
disease.
Hospitalizations are often used as the key measure of severity and to estimate the economic
impact of RSV infection. This significantly underestimates the true burden of RSV disease by
not evaluating cases, which may include severe cases, which are medically managed in the ER
without hospital admission or in physician offices as outpatients. In 2003, Leader and Kohlhase
examined several national databases and found that between 1997–2000, there were 718,000
ER visits for lower respiratory infections in infants <1 year, with a cost of $202 million. Only
29% of these patients were admitted [45]. An additional challenge to accurate estimation of
total RSV burden is that routine RSV testing is rarely performed in outpatient settings and is
not recommended by the American Academy of Pediatrics (AAP) [46].
One of the strengths of the OUTSMART study is that it was designed to be an ongoing sur-
veillance program with widespread participation and laboratory-confirmed diagnoses of RSV.
A database of trends in infection rates will be built to inform drug and vaccine development
programs. Information from OUTSMART will also be used to establish a baseline of RSV F
and G sequences as a reference for future epidemiology studies and clinical trials. A separate
report will describe the conservation of the F protein and the susceptibility of different RSV
isolates to neutralization by a novel mAb MEDI8897, currently being developed to prevent
medically attended lower respiratory tract infections due to RT-PCR confirmed RSV in all
infants [13,47]. In addition, an ex-U.S. RSV surveillance program entitled INFORM-RSV has
Table 4. OUTSMART 2016–17 RSV-positive tests by LOS, referring department and subtype.
RSV Subtype (Sequencing Results)
A B AB QNS All
LOS Referring department N % N % N % N N % of LOS category
<24 hr
a
Emergency room/department (ER/ED) 207 47.9% 220 50.9% 5 1.2% 59 491 73.3%
Pediatric Intensive Care Unit (PICU) 0 0% 1 100.0% 0 0% 0 1 0.1%
Outpatient Facility 13 37.1% 21 60.0% 1 2.9% 5 40 6.0%
Other 34 34.7% 64 65.3% 0 0% 40 138 20.6%
Total <24 hr 670 64.4%
>24 hr
a
Emergency room/department (ER/ED 26 54.2% 22 45.8% 0 0% 10 58 19.2%
Pediatric Intensive Care Unit (PICU) 21 67.7% 10 32.3% 0 0% 16 47 15.6%
ICU (Other than PICU) 1 12.5% 7 87.5% 0 0% 6 14 4.6%
Pediatric Ward 4 25.0% 12 75.0% 0 0% 0 16 5.3%
Other 53 44.9% 64 54.2% 1 0.8% 49 167 55.3%
Total >24 hr 302 29.0%
Other 20 40.8% 28 57.1% 1 2.0% 20 69 100.0%
Total Other 69 6.6%
a.
<24 hours defined as outpatient, >24 hours defined as inpatient
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U.S. RSV surveillance winter 2016-17
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been launched in collaboration with ReSViNET (www.resvinet.org) to collect RSV samples
from Europe, South America, South Africa, Australia and Japan.
An interesting observation in this study was that there was a significantly larger proportion
of RSV B detected in the 6–59 (p = 0.001) and 60+ (p<0.001) age groups as compared to the
1–2 year old age group (Fig 4). The difference in RSV A and B prevalence in the elderly versus
the very young may be the result of pre-existing immunity to RSV A gained from previous
infections. It will be interesting to see if the prevalence of A and B in different age groups
changes over time and whether that correlates with changes in the F and G genes.
Nearly one-third of RSV-positive cases identified in the OUTSMART program were hospi-
talized for greater than 24 hours. Hospitalization rates for RSV positive patients published by
Radin et al. [48] were similar to those estimated using data from OUTSMART. Radin et al.
reported that 28% of all RSV cases were hospitalized in their study of three separate U.S. popu-
lations. They also found that 71% of identified RSV cases were under age 4 [48], similar to the
infection rate of 76% found amongst OUTSMART patients of 2 years of age.
Most RSV cases in OUTSMART were diagnosed in the ER and did not result in the subject
being admitted to the hospital for more than 24 hours. Over 70% of RSV cases with <24 hours
LOS were diagnosed in the ED, and only 6% in doctor’s offices or clinics likely due to primarily
hospital-based case collection. Most ER diagnoses were in children less than 2 years old.
Parents may be choosing the costlier treatment setting of the ER for their children over waiting
for a pediatrician appointment due to perceived urgency of symptoms, or lack of private health
insurance or primary care provider. In total, 64.4% of RSV cases that spent less than 24 hours
in the hospital were seen in the ER. This is an important finding from the OUTSMART study
in that much of the burden of RSV disease does not appear to lie in hospitalizations, but in the
ER. OUTSMART has identified a signal for future research to gain more clarity of the full bur-
den of RSV disease in all healthcare settings.
An additional explanation for the large proportion of cases diagnosed in the ED compared
with other outpatient settings such as a physician’s office, is that very little testing for RSV is
conducted in these settings as it does not alter treatment decisions [3,7,49]. A better under-
standing of the burden of disease and related costs in the outpatient setting is necessary to bet-
ter inform the design of clinical studies and the future impact of novel interventions.
Despite the inability to completely capture all circulating RSV cases due to lack of uniform
diagnostic testing in all healthcare settings, OUTSMART provides a reasonable description of
verified RSV diagnoses based on current medical practice. Future RSV surveillance and epide-
miology studies will need to address the burden of disease in all settings, including outpatient
clinics and the ER.
Supporting information
S1 Data. Total number of tests conducted and total number of positive tests at OUT-
SMART participating labs.
(XLSX)
S2 Data. 2016–2017 OUTSMART surveillance data.
(XLSX)
S1 Table. OUTSMART 2016–17 RSV-positive tests by region and age and subtype.
(DOCX)
S2 Table. OUTSMART 2016–17 RSV-positive tests by gender, age and subtype.
(DOCX)
U.S. RSV surveillance winter 2016-17
PLOS ONE | https://doi.org/10.1371/journal.pone.0200319 July 24, 2018 12 / 16
S1 Text. Supplementary methods.
(DOCX)
Acknowledgments
The authors would like to thank all the members of the RSV Alertand OUTSMART laborato-
ries that contributed samples and data to the study.
Author Contributions
Conceptualization: Alexey Ruzin, Hui Liu, Li Yu, Mark T. Esser.
Data curation: Xiaohui Jiang.
Formal analysis: Alexey Ruzin, Susan T. Pastula, Elizabeth Levin-Sparenberg, Xiaohui Jiang,
Jon Fryzek, Andrey Tovchigrechko, Bin Lu, Yanping Qi, Hui Liu, Hong Jin, Judith Hackett,
Tonya Villafana, Mark T. Esser.
Methodology: Alexey Ruzin, Jon Fryzek, Andrey Tovchigrechko, Mark T. Esser.
Project administration: Alexey Ruzin, Bin Lu, Mark T. Esser.
Supervision: Alexey Ruzin, Jon Fryzek, Mark T. Esser.
Writing – original draft: Alexey Ruzin, Susan T. Pastula, Elizabeth Levin-Sparenberg, Tonya
Villafana, Mark T. Esser.
Writing – review & editing: Alexey Ruzin, Susan T. Pastula, Elizabeth Levin-Sparenberg,
Andrey Tovchigrechko, Bin Lu, Yanping Qi, Hui Liu, Hong Jin, Li Yu, Judith Hackett,
Tonya Villafana, Mark T. Esser.
References
1. Borchers AT, Chang C, Gershwin ME, Gershwin LJ. Respiratory syncytial virus—a comprehensive
review. Clin Rev Allergy Immunol. 2013; 45(3):331–79. https://doi.org/10.1007/s12016-013-8368-9
PMID: 23575961.
2. Shi T, McAllister DA, O’Brien KL, Simoes EAF, Madhi SA, Gessner BD, et al. Global, regional, and
national disease burden estimates of acute lower respiratory infections due to respiratory syncytial virus
in young children in 2015: a systematic review and modelling study. Lancet. 2017; 390(10098):946–58.
https://doi.org/10.1016/S0140-6736(17)30938-8 PMID: 28689664.
3. Hall CB, Weinberg GA, Iwane MK, Blumkin AK, Edwards KM, Staat MA, et al. The burden of respiratory
syncytial virus infection in young children. N Engl J Med. 2009; 360(6):588–98. https://doi.org/10.1056/
NEJMoa0804877 PMID: 19196675.
4. Hall CB. Respiratory syncytial virus and parainfluenza virus. N Engl J Med. 2001; 344(25):1917–28.
https://doi.org/10.1056/NEJM200106213442507 PMID: 11419430
5. Iwane MK, Edwards KM, Szilagyi PG, Walker FJ, Griffin MR, Weinberg GA, et al. Population-based sur-
veillance for hospitalizations associated with respiratory syncytial virus, influenza virus, and parainflu-
enza viruses among young children. Pediatrics. 2004; 113(6):1758–64. PMID: 15173503
6. Schanzer DL, Saboui M, Lee L, Nwosu A, Bancej C. Burden of influenza, respiratory syncytial virus,
and other respiratory viruses and the completeness of respiratory viral identification among respiratory
inpatients, Canada, 2003–2014. Influenza Other Respir Viruses. 2017. Epub 2017/12/16. https://doi.
org/10.1111/irv.12497 PMID: 29243369.
7. Hall CB. The burgeoning burden of respiratory syncytial virus among children. Infectious disorders drug
targets. 2012; 12(2):92–7. Epub 2012/02/18. PMID: 22335498.
8. Paramore LC, Ciuryla V, Ciesla G, Liu L. Economic impact of respiratory syncytial virus-related illness
in the US: an analysis of national databases. PharmacoEconomics. 2004; 22(5):275–84. Epub 2004/
04/06. PMID: 15061677.
U.S. RSV surveillance winter 2016-17
PLOS ONE | https://doi.org/10.1371/journal.pone.0200319 July 24, 2018 13 / 16
9. Collins PL, Melero JA. Progress in understanding and controlling respiratory syncytial virus: Still crazy
after all these years. Virus research. 2011. https://doi.org/10.1016/j.virusres.2011.09.020 PMID:
21963675
10. Beeler JA, van Wyke Coelingh K. Neutralization epitopes of the F glycoprotein of respiratory syncytial
virus: effect of mutation upon fusion function. Journal of virology. 1989; 63(7):2941–50. PMID: 2470922
11. Storch GA. Humanized monoclonal antibody for prevention of respiratory syncytial virus infection. Pedi-
atrics. 1998; 102(3 Pt 1):648–51. Epub 1998/09/17. PMID: 9738192.
12. Domachowske JB, Khan AA, Esser MT, Jensen K, Takas T, Villafana T, et al. Safety, Tolerability, and
Pharmacokinetics of MEDI8897, an Extended Half-Life Single-Dose Respiratory Syncytial Virus Prefu-
sion F-Targeting Monoclonal Antibody Administered as a Single Dose to Healthy Preterm Infants.
Pediatr Infect Dis J. 2018. Epub 2018/01/27. https://doi.org/10.1097/INF.0000000000001916 PMID:
29373476.
13. Griffin MP, Khan AA, Esser MT, Jensen K, Takas T, Kankam MK, et al. Safety, Tolerability, and Phar-
macokinetics of MEDI8897, the Respiratory Syncytial Virus Prefusion F-Targeting Monoclonal Antibody
with an Extended Half-Life, in Healthy Adults. Antimicrob Agents Chemother. 2017; 61(3). https://doi.
org/10.1128/AAC.01714-16 PMID: 27956428.
14. Pangesti KNA, Abd El Ghany M, Walsh MG, Kesson AM, Hill-Cawthorne GA. Molecular epidemiology
of respiratory syncytial virus. Rev Med Virol. 2018. Epub 2018/01/30. https://doi.org/10.1002/rmv.1968
PMID: 29377415.
15. Sullender WM. Respiratory syncytial virus genetic and antigenic diversity. Clinical microbiology reviews.
2000; 13(1):1–15, table of contents. PMID: 10627488
16. Cane PA. Molecular epidemiology of respiratory syncytial virus. Reviews in medical virology. 2001;
11(2):103–16. https://doi.org/10.1002/rmv.305 PMID: 11262529
17. Yu X, Kou Y, Xia D, Li J, Yang X, Zhou Y, et al. Human respiratory syncytial virus in children with lower
respiratory tract infections or influenza-like illness and its co-infection characteristics with viruses and
atypical bacteria in Hangzhou, China. J Clin Virol. 2015; 69:1–6. Epub 2015/07/26. https://doi.org/10.
1016/j.jcv.2015.05.015 PMID: 26209367.
18. Gimferrer L, Andres C, Campins M, Codina MG, Rodrigo JA, Melendo S, et al. Circulation of a novel
human respiratory syncytial virus Group B genotype during the 2014–2015 season in Catalonia (Spain).
Clin Microbiol Infect. 2016; 22(1):97.e5–e8. Epub 2015/09/27. https://doi.org/10.1016/j.cmi.2015.09.
013 PMID: 26408279.
19. Trento A, Galiano M, Videla C, Carballal G, Garcia-Barreno B, Melero JA, et al. Major changes in the G
protein of human respiratory syncytial virus isolates introduced by a duplication of 60 nucleotides. J Gen
Virol. 2003; 84(Pt 11):3115–20. https://doi.org/10.1099/vir.0.19357-0 PMID: 14573817.
20. Eshaghi A, Duvvuri VR, Lai R, Nadarajah JT, Li A, Patel SN, et al. Genetic variability of human respira-
tory syncytial virus A strains circulating in Ontario: a novel genotype with a 72 nucleotide G gene dupli-
cation. PLoS One. 2012; 7(3):e32807. https://doi.org/10.1371/journal.pone.0032807 PMID: 22470426.
21. Kapikian AZ, Mitchell RH, Chanock RM, Shvedoff RA, Stewart CE. An epidemiologic study of altered
clinical reactivity to respiratory syncytial (RS) virus infection in children previously vaccinated with an
inactivated RS virus vaccine. Am J Epidemiol. 1969; 89(4):405–21. PMID: 4305197.
22. Kim HW, Canchola JG, Brandt CD, Pyles G, Chanock RM, Jensen K, et al. Respiratory syncytial virus
disease in infants despite prior administration of antigenic inactivated vaccine. American Journal of Epi-
demiology. 1969; 89(4):422–34. PMID: 4305198
23. Simoes EA, Groothuis JR, Tristram DA, Allessi K, Lehr MV, Siber GR, et al. Respiratory syncytial virus-
enriched globulin for the prevention of acute otitis media in high risk children. J Pediatr. 1996; 129
(2):214–9. Epub 1996/08/01. PMID: 8765618.
24. Palivizumab, a Humanized Respiratory Syncytial Virus Monoclonal Antibody, Reduces Hospitalization
From Respiratory Syncytial Virus Infection in High-risk Infants. Pediatrics. 1998; 102(3):531–7. PMID:
9724660
25. American Academy of Pediatrics ID. Updated guidance for palivizumab prophylaxis among infants and
young children at increased risk of hospitalization for respiratory syncytial virus infection. Pediatrics.
United States: by the American Academy of Pediatrics; 2014. p. e620–38. https://doi.org/10.1542/
peds.2014-1666 PMID: 25070304
26. Zhu Q, McAuliffe JM, Patel NK, Palmer-Hill FJ, Yang CF, Liang B, et al. Analysis of respiratory syncytial
virus preclinical and clinical variants resistant to neutralization by monoclonal antibodies palivizumab
and/or motavizumab. The Journal of infectious diseases. 2011; 203(5):674–82. https://doi.org/10.1093/
infdis/jiq100 PMID: 21208913
27. Graham BS. Vaccine development for respiratory syncytial virus. Curr Opin Virol. 2017; 23:107–12.
Epub 2017/05/20. https://doi.org/10.1016/j.coviro.2017.03.012 PMID: 28525878.
U.S. RSV surveillance winter 2016-17
PLOS ONE | https://doi.org/10.1371/journal.pone.0200319 July 24, 2018 14 / 16
28. Higgins D, Trujillo C, Keech C. Advances in RSV vaccine research and development—A global agenda.
Vaccine. 2016; 34(26):2870–5. https://doi.org/10.1016/j.vaccine.2016.03.109 PMID: 27105562
29. Villafana T, Falloon J, Griffin MP, Zhu Q, Esser MT. Passive and active immunization against respira-
tory syncytial virus for the young and old. Expert review of vaccines. 2017; 16(7):1–13. Epub 2017/05/
21. https://doi.org/10.1080/14760584.2017.1333425 PMID: 28525961.
30. Boron ML, Edelman L, Groothuis JR, Malinoski FJ. A novel active respiratory syncytial virus surveil-
lance system in the United States: variability in the local and regional incidence of infection. Pediatr
Infect Dis J. 2008; 27(12):1095–8. https://doi.org/10.1097/INF.0b013e3181812c8e PMID: 18989237.
31. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in per-
formance and usability. Mol Biol Evol. 2013; 30(4):772–80. Epub 2013/01/19. https://doi.org/10.1093/
molbev/mst010 PMID: 23329690.
32. Wright ES. Using DECIPHER v2.0 to Analyze Big Biological Sequence Data in R. The R Journal. 2016;
8(1):352–9.
33. Schliep KP. phangorn: phylogenetic analysis in R. Bioinformatics. 2011; 27(4):592–3. Epub 2010/12/
21. https://doi.org/10.1093/bioinformatics/btq706 PMID: 21169378.
34. HCUP. Introduction to the HCUP Nationwide Emergency Department Sample (NEDS) 2015. Agency
for Healthcare Research and Quality, Healthcase Cost and Utilization Project, 2017 2017 Dec 12.
Report No.
35. Hcup. Introduction to the HCUP National Inpatient Sample (NIS) 2013. Agency for Healthcare Research
and Quality Healthcare Cost and Utilization Project (HCUP), 2015.
36. Committee On Infectious Diseases and Bronchilitis Guidelines Committee. Updated Guidance for Pali-
vizumab Prophylaxis Among Infants and Young Children at Increased Risk of Hospitalization for Respi-
ratory Syncytial Virus Infection. Pediatrics. 2014; 134(2):415–20. https://doi.org/10.1542/peds.2014-
1665 PMID: 25070315
37. Anderson EJ, Carosone-Link P, Yogev R, Yi J, Simoes EAF. Effectiveness of Palivizumab in High-risk
Infants and Children: A Propensity Score Weighted Regression Analysis. Pediatr Infect Dis J. 2017;
36(8):699–704. https://doi.org/10.1097/INF.0000000000001533 PMID: 28709160.
38. Jafri HS, Wu X, Makari D, Henrickson KJ. Distribution of respiratory syncytial virus subtypes A and B
among infants presenting to the emergency department with lower respiratory tract infection or apnea.
Pediatr Infect Dis J. 2013; 32(4):335–40.
39. Landes MB, Neil RB, McCool SS, Mason BP, Woron AM, Garman RL, et al. The frequency and season-
ality of influenza and other respiratory viruses in Tennessee: two influenza seasons of surveillance
data, 2010–2012. Influenza Other Respir Viruses. 2013; 7(6):1122–7. https://doi.org/10.1111/irv.12145
PMID: 23962104.
40. Walsh EE. Respiratory Syncytial Virus Infection: An Illness for All Ages. Clin Chest Med. 2017; 38
(1):29–36. https://doi.org/10.1016/j.ccm.2016.11.010 PMID: 28159159.
41. Mullins JA, Lamonte AC, Bresee JS, Anderson LJ. Substantial variability in community respiratory syn-
cytial virus season timing. Pediatr Infect Dis J. 2003; 22(10):857–62. https://doi.org/10.1097/01.inf.
0000090921.21313.d3 PMID: 14551484.
42. Rose EB, Wheatley A, Langley G, Gerber S, Haynes A. Respiratory Syncytial Virus Seasonality—
United States, 2014–2017. MMWR Morb Mortal Wkly Rep. 2018; 67(2):71–6. Epub 2018/01/19. https://
doi.org/10.15585/mmwr.mm6702a4 PMID: 29346336.
43. Obando-Pacheco P, Justicia-Grande AJ, Rivero-Calle I, Rodriguez-Tenreiro C, Sly P, Ramilo O, et al.
Respiratory Syncytial Virus Seasonality: A Global Overview. J Infect Dis. 2018. Epub 2018/02/02.
https://doi.org/10.1093/infdis/jiy056 PMID: 29390105.
44. Broberg EK, Waris M, Johansen K, Snacken R, Penttinen P, European Influenza Surveillance N. Sea-
sonality and geographical spread of respiratory syncytial virus epidemics in 15 European countries,
2010 to 2016. Euro Surveill. 2018; 23(5). Epub 2018/02/08. https://doi.org/10.2807/1560-7917.ES.
2018.23.5.17-00284 PMID: 29409569.
45. Leader S, Kohlhase K. Recent trends in severe respiratory syncytial virus (RSV) among US infants,
1997 to 2000. J Pediatr. 2003; 143(5 Suppl):S127–32. Epub 2003/11/15. PMID: 14615711.
46. Ralston SL, Lieberthal AS, Meissner HC, Alverson BK, Baley JE, Gadomski AM, et al. Clinical practice
guideline: the diagnosis, management, and prevention of bronchiolitis. Pediatrics. 2014; 134(5):e1474–
502. Epub 2014/10/29. https://doi.org/10.1542/peds.2014-2742 PMID: 25349312.
47. Zhu Q, McLellan JS, Kallewaard NL, Ulbrandt ND, Palaszynski S, Zhang J, et al. A highly potent
extended half-life antibody as a potential RSV vaccine surrogate for all infants. Sci Transl Med. 2017;
9(388). https://doi.org/10.1126/scitranslmed.aaj1928 PMID: 28469033.
U.S. RSV surveillance winter 2016-17
PLOS ONE | https://doi.org/10.1371/journal.pone.0200319 July 24, 2018 15 / 16
48. Radin JM, Hawksworth AW, Kammerer PE, Balansay M, Raman R, Lindsay SP, et al. Epidemiology of
pathogen-specific respiratory infections among three US populations. PLoS One. 2014; 9(12):e114871.
https://doi.org/10.1371/journal.pone.0114871 PMID: 25549089.
49. Binder W, Thorsen J, Borczuk P. RSV in adult ED patients: Do emergency providers consider RSV as
an admission diagnosis? Am J Emerg Med. 2017; 35(8):1162–5. https://doi.org/10.1016/j.ajem.2017.
06.022 PMID: 28633906.
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PLOS ONE | https://doi.org/10.1371/journal.pone.0200319 July 24, 2018 16 / 16
... The RSV genome encodes 11 proteins, two of which, surface proteins F and G, are the major targets of neutralizing and non-neutralizing antibodies. RSV can be further divided into subtypes A and B which co-circulate at approximately the same rate [12]. Subtype differences are based on antigenic and genetic variability of the G protein, whereas F maintains greater than 90% sequence identity between groups [12,13]. ...
... RSV can be further divided into subtypes A and B which co-circulate at approximately the same rate [12]. Subtype differences are based on antigenic and genetic variability of the G protein, whereas F maintains greater than 90% sequence identity between groups [12,13]. RSV F, a class I viral fusion protein responsible for fusing the viral and host-cell membranes [14], is the target of palivizumab and the majority of neutralizing antibodies (nAb) raised by natural infection [15][16][17]. ...
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... Unlike the seasonal circulation of RSV that is generally observed in temperate [16][17][18] 16 . ...
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Respiratory viral infections contribute significantly to morbidity and mortality worldwide, but representative data from sub-Saharan Africa are needed to inform vaccination strategies. We conducted population-based surveillance in rural Gambia using standardized criteria to identify and investigate children with acute lower respiratory infection (ALRI). Naso- and oropharyngeal swabs were collected. Each month from February through December 2015, specimens from 50 children aged 2–23 months were randomly selected to test for respiratory syncytial (RSV), parainfluenza (PIV) and influenza viruses. The expected number of viral-associated ALRI cases in the population was estimated using statistical simulation that accounted for the sampling design. RSV G and F proteins and influenza hemagglutinin genes were sequenced. 2385 children with ALRI were enrolled, 519 were randomly selected for viral testing. One or more viruses were detected in 303/519 children (58.4%). RSV-A was detected in 237 and RSV-B in seven. The expected incidence of ALRI associated with RSV, PIV or influenza was 140 cases (95% CI, 131–149) per 1000 person-years; RSV incidence was 112 cases (95% CI, 102–122) per 1000 person-years. Multiple strains of RSV and influenza circulated during the year. RSV circulated throughout most of the year and was associated with eight times the number of ALRI cases compared to PIV or IV. Gambian RSV viruses were closely related to viruses detected in other continents. An effective RSV vaccination strategy could have a major impact on the burden of ALRI in this setting.
... A number of international studies examining RSV epidemiology and genomics are ongoing [50][51][52][53], and information from these is most likely to be useful if collected and presented in a standard format. Participants at the workshop were unanimous in agreeing on the importance of standardization of a number of aspects of RSV research, and ways in which this would improve our understanding of RSV disease [6]. ...
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Respiratory syncytial virus (RSV) is the most common cause of serious lower respiratory tract illness in infants and children and causes significant disease in the elderly and immunocompromised. Recently there has been an acceleration in the development of candidate RSV vaccines, monoclonal antibodies and therapeutics. However, the effects of RSV genomic variability on the implementation of vaccines and therapeutics remain poorly understood. To address this knowledge gap, the National Institute of Allergy and Infectious Diseases and the Fogarty International Center held a workshop to summarize what is known about the global burden and transmission of RSV disease, the phylogeographic dynamics and genomics of the virus, and the networks that exist to improve the understanding of RSV disease. Discussion at the workshop focused on the implications of viral evolution and genomic variability for vaccine and therapeutics development in the context of various immunization strategies. This paper summarizes the meeting, highlights research gaps and future priorities, and outlines what has been achieved since the meeting took place. It concludes with an examination of what the RSV community can learn from our understanding of SARS-CoV-2 genomics and what insights over sixty years of RSV research can offer the rapidly evolving field of COVID-19 vaccines.
... The boost in polyclonal antibody to all neutralisation-sensitive epitopes offers an advantage over post-F, which presents fewer epitopes, and approaches such as prophylactic monoclonal antibody, for which efficacy might be susceptible to minor antigenic drift in selected RSV F epitopes. 8,[21][22][23] The greatest limitation of our study is that it is a small phase 1 study, where responses to vaccine were tested in 15-20 healthy adults per study group. The major target populations for a pre-F subunit protein vaccine are pregnant women and older adults. ...
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Background Multiple active vaccination approaches have proven ineffective in reducing the substantial morbidity and mortality caused by respiratory syncytial virus (RSV) in infants and older adults (aged ≥65 years). A vaccine conferring a substantial and sustainable boost in neutralising activity is required to protect against severe RSV disease. To that end, we evaluated the safety and immunogenicity of DS-Cav1, a prefusion F subunit vaccine. Methods In this randomised, open-label, phase 1 clinical trial, the stabilised prefusion F vaccine DS-Cav1 was evaluated for dose, safety, tolerability, and immunogenicity in healthy adults aged 18–50 years at a single US site. Participants were assigned to receive escalating doses of either 50 μg, 150 μg, or 500 μg DS-Cav1 at weeks 0 and 12, and were randomly allocated in a 1:1 ratio within each dose group to receive the vaccine with or without aluminium hydroxide (AlOH) adjuvant. After 71 participants had been randomised, the protocol was amended to allow some participants to receive a single vaccination at week 0. The primary objectives evaluated the safety and tolerability at every dose within 28 days following each injection. Neutralising activity and RSV F-binding antibodies were evaluated from week 0 to week 44 as secondary and exploratory objectives. Safety was assessed in all participants who received at least one vaccine dose; secondary and exploratory immunogenicity analysis included all participants with available data at a given visit. The trial is registered with ClinicalTrials.gov, NCT03049488, and is complete and no longer recruiting. Findings Between Feb 21, 2017, and Nov 29, 2018, 244 participants were screened for eligibility and 95 were enrolled to receive DS-Cav1 at the 50 μg (n=30, of which n=15 with AlOH), 150 μg (n=35, of which n=15 with AlOH), or 500 μg (n=30, of which n=15 with AlOH) doses. DS-Cav1 was safe and well tolerated and no serious vaccine-associated adverse events deemed related to the vaccine were identified. DS-Cav1 vaccination elicited robust neutralising activity and binding antibodies by 4 weeks after a single vaccination (p<0·0001 for F-binding and neutralising antibodies). In analyses of exploratory endpoints at week 44, pre-F-binding IgG and neutralising activity were significantly increased compared with baseline in all groups. At week 44, RSV A neutralising activity was 3·1 fold above baseline in the 50 μg group, 3·8 fold in the 150 μg group, and 4·5 fold in the 500 μg group (p<0·0001). RSV B neutralising activity was 2·8 fold above baseline in the 50 μg group, 3·4 fold in the 150 μg group, and 3·7 fold in the 500 μg group (p<0·0001). Pre-F-binding IgG remained significantly 3·2 fold above baseline in the 50 μg group, 3·4 fold in the 150 μg group, and 4·0 fold in the 500 μg group (p<0·0001). Pre-F-binding serum IgA remained 4·1 fold above baseline in the 50 μg group, 4·3 fold in the 150 μg group, and 4·8 fold in the 500 μg group (p<0·0001). Although a higher vaccine dose or second immunisation elicited a transient advantage compared with lower doses or a single immunisation, neither significantly impacted long-term neutralisation. There was no long-term effect of dose, number of vaccinations, or adjuvant on neutralising activity. Interpretation In this phase 1 study, DS-Cav1 vaccination was safe and well tolerated. DS-Cav1 vaccination elicited a robust boost in RSV F-specific antibodies and neutralising activity that was sustained above baseline for at least 44 weeks. A single low-dose of pre-F immunisation of antigen-experienced individuals might confer protection that extends throughout an entire RSV season. Funding The National Institutes of Allergy and Infectious Diseases.
... This is consistent with the findings of other RSVH studies [16,[19][20][21][22]. One study of the OUTSMART-RSV surveillance program during the 2016-2017 winter viral season in the US reported that 46.7% of the inpatient sample consisted of children aged <1 year [23]. The recent modeling tool developed by the Centers for Disease Control and Prevention showed the potential impact of multiple immunization products on medically attended RSV infections in infants [24]. ...
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Background: In 2014, the American Academy of Pediatrics stopped recommending palivizumab to otherwise healthy 29-34 weeks' gestational age (wGA) infants aged <12 months at respiratory syncytial virus (RSV) season start. Here, we compare the burden of RSV hospitalizations (RSVH) and all-cause bronchiolitis hospitalizations (BH) before and after 2014 among otherwise healthy 29-34 wGA infants hospitalized at <6 months of age. Methods: A historical, observational cohort study was conducted to evaluate RSVH and BH in 29-34 wGA infants during the 2010-2017 RSV seasons using encounter data from 51 US children's hospitals that comprise the Pediatric Health Information System. Results: The overall cohort included 67,570 RSVH out of 96,281 patients with BH. wGA was known for 22,937 RSVH and 33,289 BH. For 29-34 wGA infants, there were 8.7% and 14.2% RSVH before and after 2014, respectively (P<0.0001). Intensive care unit admissions increased for RSVH (from 54.5% to 64.2%; P=0.0002) and BH (from 46.7% to 54.5%; P=0.0005) after controlling for sex, race, comorbidity, and cluster. The total cost of care increased for RSVH from $37 million to nearly $60 million. Discussion: RSVH, BH, and their severity increased among 29-34 wGA infants in the 3 RSV seasons following 2014.
... Gaps in our knowledge remain with regard to the cause of mutations in the F protein. We know that the RSV B genome is more diverse compared with the RSV A genome [7]. Suptavumab escape does not seem to be the driving mechanism of escape mutants in this study, as the isolates from the placebo group showed the same mutations. ...
... Therefore, RSV global surveillance is required. The Observational US Targeted Surveillance of Monoclonal Antibody Resistance and Testing of RSV (OUTSMART-RSV) surveillance program characterized circulating RSV strains in the U.S. during the 2017-18 season [11]. RSV strains that are resistant to palivizumab were found to be rare [10]. ...
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Background: Respiratory syncytial virus (RSV) is a global cause of severe respiratory morbidity and mortality in infants. While preventive and therapeutic interventions are being developed, including antivirals, vaccines and monoclonal antibodies, little is known about the global molecular epidemiology of RSV. INFORM is a prospective, multicenter, global clinical study performed by ReSViNET to investigate the worldwide molecular diversity of RSV isolates collected from children less than 5 years of age. Methods: The INFORM study is performed in 17 countries spanning all inhabited continents and will provide insight into the molecular epidemiology of circulating RSV strains worldwide. Sequencing of > 4000 RSV-positive respiratory samples is planned to detect temporal and geographical molecular patterns on a molecular level over five consecutive years. Additionally, RSV will be cultured from a subset of samples to study the functional implications of specific mutations in the viral genome including viral fitness and susceptibility to different monoclonal antibodies. Discussion: The sequencing and functional results will be used to investigate susceptibility and resistance to novel RSV preventive or therapeutic interventions. Finally, a repository of globally collected RSV strains and a database of RSV sequences will be created.
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Respiratory syncytial virus (RSV) causes a spectrum of respiratory illnesses in infants and young children that may lead to hospitalizations and a substantial number of outpatient visits, which result in a huge economic and healthcare burden. Most hospitalizations happen in otherwise healthy infants, highlighting the need to protect all infants against RSV. Moreover, there is evidence on the association between early-life RSV respiratory illness and recurrent wheezing/asthma-like symptoms As such, RSV is considered a global health priority. However, despite this, the only prevention strategy currently available is palivizumab, a monoclonal antibody (mAb) indicated in a subset of preterm infants or those with comorbidities, hence leaving the majority of the infant population unprotected against this virus. Therefore, development of prevention strategies against RSV for all infants entering their first RSV season constitutes a large unmet medical need. The aim of this review is to explore different immunization approaches to protect all infants against RSV. Prevention strategies include maternal immunization, immunization of infants with vaccines, immunization of infants with licensed mAbs (palivizumab), and immunization of infants with long-acting mAbs (e.g., nirsevimab, MK-1654). Of these, palivizumab use is restricted to a small population of infants and does not offer a solution for all-infant protection, whereas vaccine development in infants has encountered various challenges, including the immaturity of the infant immune system, highlighting that future pediatric vaccines will most likely be used in older infants (>6 months of age) and children. Consequently, maternal immunization and immunization of infants with long-acting mAbs represent the two feasible strategies for protection of all infants against RSV. Here, we present considerations regarding these two strategies covering key areas which include mechanism of action, “consistency” of protection, RSV variability, duration of protection, flexibility and optimal timing of immunization, benefit for the mother, programmatic implementation, and acceptance of each strategy by key stakeholders. We conclude that, based on current data, immunization of infants with long-acting mAbs might represent the most effective approach for protecting all infants entering their first RSV season.
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Respiratory syncytial virus (RSV) is a major health problem. A better understanding of the geographical and temporal dynamics of RSV circulation will assist in tracking resistance against therapeutics currently under development. Since 2015, the field of RSV molecular epidemiology has evolved rapidly with around 20–30 published articles per year. The objective of this systematic review is to identify knowledge gaps in recent RSV genetic literature to guide global molecular epidemiology research. We included 78 studies published between 2015 and 2020 describing 12,998 RSV sequences of which 8,233 (63%) have been uploaded to GenBank. Seventeen (22%) studies were performed in low‐ and middle‐income countries (LMICs), and seven (9%) studies sequenced whole‐genomes. Although most reported polymorphisms for monoclonal antibodies in clinical development (nirsevimab, MK‐1654) have not been tested for resistance in neutralisation essays, known resistance was detected at low levels for the nirsevimab and palivizumab binding site. High resistance was found for the suptavumab binding site. We present the first literature review of an enormous amount of RSV genetic data. The need for global monitoring of RSV molecular epidemiology becomes increasingly important in evaluating the effectiveness of monoclonal antibody candidates as they reach their final stages of clinical development. We have identified the following three knowledge gaps: whole‐genome data to study global RSV evolution, data from LMICs and data from global surveillance programs.
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Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract infection among infants and young children, resulting in annual epidemics worldwide. INFORM-RSV is a multi-year clinical study designed to describe the global molecular epidemiology of RSV in children under five years of age by monitoring temporal and geographical evolution of current circulating RSV strains, F protein antigenic sites, and their relationships with clinical features of RSV disease. During the pilot season (2017–2018), 410 RSV G-F gene sequences were obtained from 476 RSV-positive nasal samples collected from 8 countries (United Kingdom, Spain, the Netherlands, Finland, Japan, Brazil, South Africa, and Australia). RSV B (all BA9 genotype) predominated over RSV A (all ON1 genotype) globally (69.0% vs. 31.0%) and in all countries except South Africa. Geographic clustering patterns highlighted wide transmission and continued evolution with viral spread. Most RSV were from infants <1 year of age (81.2%), males (56.3%), and patients hospitalized >24 hours (70.5%) with no differences in subtype distribution. Compared to 2013 reference sequences, variations at F protein antigenic sites were observed for both RSV A and B strains with high frequency polymorphisms at antigenic site Ø (I206M/Q209R) and site V (L172Q/S173L/K191R) in RSV B strains. The INFORM-RSV 2017–2018 pilot season establishes an important molecular baseline of RSV strain distribution and sequence variability with which to track the emergence of new strains and provide an early warning system of neutralization escape variants that may impact transmission or the effectiveness of vaccines and mAbs under development.
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Respiratory syncytial virus (RSV) is considered the most common pathogen causing severe lower respiratory tract infections among infants and young children. We describe the seasonality and geographical spread of RSV infection in 15 countries of the European Union and European Economic Area. We performed a retrospective descriptive study of weekly laboratory-confirmed RSV detections between weeks 40/2010 and 20/2016, in patients investigated for influenza-like illness, acute respiratory infection or following the clinician’s judgment. Six countries reported 4,230 sentinel RSV laboratory diagnoses from primary care and 14 countries reported 156,188 non-sentinel laboratory diagnoses from primary care or hospitals. The median length of the RSV season based on sentinel and non-sentinel surveillance was 16 (range: 9–24) and 18 (range: 8–24) weeks, respectively. The median peak weeks for sentinel and non-sentinel detections were week 4 (range: 48 to 11) and week 4.5 (range: 49 to 17), respectively. RSV detections peaked later (r = 0.56; p = 0.0360) and seasons lasted longer with increasing latitude (r = 0.57; p = 0.0329). Our data demonstrated regular seasonality with moderate correlation between timing of the epidemic and increasing latitude of the country. This study supports the use of RSV diagnostics within influenza or other surveillance systems to monitor RSV seasonality and geographical spread.
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Background: MEDI8897 is a recombinant human monoclonal antibody being developed for prophylaxis of serious respiratory syncytial virus (RSV) disease in all infants. Methods: In this phase 1b/2a dose-escalation study, healthy preterm infants with a gestational age of 32-35 weeks were randomized to receive a single intramuscular injection of MEDI8897 (10, 25 or 50 mg) or placebo. Safety, pharmacokinetics, RSV-neutralizing antibody and antidrug antibody (ADA) assessments were performed during the 360-day follow-up period. Infants who experienced medically attended lower respiratory tract infections (LRTIs) were tested for RSV. Results: MEDI8897 serum half-life ranged from 62.5-72.9 days. On day 151, 87% of infants in the 50 mg group had serum concentrations above the 90% effective concentration target level of 6.8 µg/mL, and 90% showed a ≥4-fold rise from baseline in serum RSV-neutralizing antibody levels. Adverse events (AEs) were reported in 17 of 18 (94.4%) placebo and 66 of 71 (93.0%) MEDI8897 recipients. Three MEDI8897 recipients experienced 5 serious AEs (3 LRTIs, 2 febrile seizures). ADA was detected at any time postbaseline in 28.2% of MEDI8897 recipients and at day 361 only in 26.5% of subjects. ADA response was not associated with AEs. Five (7%) MEDI8897 recipients experienced medically attended LRTIs through day 150; 1 tested positive for RSV (10 mg group). Conclusions: MEDI8897 had a favorable safety profile in healthy preterm infants. The extended half-life of MEDI8897 and demonstrated RSV-neutralizing activity support protection from RSV for the duration of a typical 5-month season after a single 50 mg intramuscular (IM) dose.
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Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infection in young children worldwide (1-3). In the United States, RSV infection results in >57,000 hospitalizations and 2 million outpatient visits each year among children aged <5 years (3). Recent studies have highlighted the importance of RSV in adults as well as children (4). CDC reported RSV seasonality nationally, by U.S. Department of Health and Human Services (HHS) regions* and for the state of Florida, using a new statistical method that analyzes polymerase chain reaction (PCR) laboratory detections reported to the National Respiratory and Enteric Virus Surveillance System (NREVSS) (https://www.cdc.gov/surveillance/nrevss/index.html). Nationally, across three RSV seasons, lasting from the week ending July 5, 2014 through July 1, 2017, the median RSV onset occurred at week 41 (mid-October), and lasted 31 weeks until week 18 (early May). The median national peak occurred at week 5 (early February). Using these new methods, RSV season circulation patterns differed from those reported from previous seasons (5). Health care providers and public health officials use RSV circulation data to guide diagnostic testing and to time the administration of RSV immunoprophylaxis for populations at high risk for severe respiratory illness (6). With several vaccines and other immunoprophlyaxis products in development, estimates of RSV circulation are also important to the design of clinical trials and future vaccine effectiveness studies.
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Background: A regression-based study design has commonly been used to estimate the influenza burden; however, these estimates are not timely and many countries lack sufficient virological data. Alternative approaches that would permit a timelier assessment of the burden, including a sentinel surveillance approach recommended by the World Health Organization (WHO), have been proposed. We aimed to estimate the hospitalization burden attributable to influenza, respiratory syncytial virus (RSV), and other respiratory viruses (ORV) and to assess both the completeness of viral identification among respiratory inpatients in Canada and the implications of adopting other approaches. Methods: Respiratory inpatient records were extracted from the Canadian Discharge Abstract Database from 2003 to 2014. A regression model was used to estimate excess respiratory hospitalizations attributable to influenza, RSV, and ORV by age group and diagnostic category and compare these estimates with the number with a respiratory viral identification. Results: An estimated 33 (95% CI: 29, 38), 27 (95% CI: 22, 33), and 27 (95% CI: 18, 36) hospitalizations per 100 000 population per year were attributed to influenza, RSV, and ORV, respectively. An influenza virus was identified in an estimated 78% (95% CI: 75, 81) and 17% (95% CI: 15, 21) of respiratory hospitalizations attributed to influenza for children and adults, respectively, and 75% of influenza-attributed hospitalizations had an ARI diagnosis. Conclusions: Hospitalization rates with respiratory viral identification still underestimate the burden. Approaches based on acute respiratory case definitions will likely underestimate the burden as well, although each proposed method should be compared with regression-based estimates of influenza-attributed burden as a way of assessing their validity.
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We have previously estimated that respiratory syncytial virus (RSV) was associated with 22% of all episodes of (severe) acute lower respiratory infection (ALRI) resulting in 55 000 to 199 000 deaths in children younger than 5 years in 2005. In the past 5 years, major research activity on RSV has yielded substantial new data from developing countries. With a considerably expanded dataset from a large international collaboration, we aimed to estimate the global incidence, hospital admission rate, and mortality from RSV-ALRI episodes in young children in 2015. We estimated the incidence and hospital admission rate of RSV-associated ALRI (RSV-ALRI) in children younger than 5 years stratified by age and World Bank income regions from a systematic review of studies published between Jan 1, 1995, and Dec 31, 2016, and unpublished data from 76 high quality population-based studies. We estimated the RSV-ALRI incidence for 132 developing countries using a risk factor-based model and 2015 population estimates. We estimated the in-hospital RSV-ALRI mortality by combining in-hospital case fatality ratios with hospital admission estimates from hospital-based (published and unpublished) studies. We also estimated overall RSV-ALRI mortality by identifying studies reporting monthly data for ALRI mortality in the community and RSV activity. We estimated that globally in 2015, 33·1 million (uncertainty range [UR] 21·6-50·3) episodes of RSV-ALRI, resulted in about 3·2 million (2·7-3·8) hospital admissions, and 59 600 (48 000-74 500) in-hospital deaths in children younger than 5 years. In children younger than 6 months, 1·4 million (UR 1·2-1·7) hospital admissions, and 27 300 (UR 20 700-36 200) in-hospital deaths were due to RSV-ALRI. We also estimated that the overall RSV-ALRI mortality could be as high as 118 200 (UR 94 600-149 400). Incidence and mortality varied substantially from year to year in any given population. Globally, RSV is a common cause of childhood ALRI and a major cause of hospital admissions in young children, resulting in a substantial burden on health-care services. About 45% of hospital admissions and in-hospital deaths due to RSV-ALRI occur in children younger than 6 months. An effective maternal RSV vaccine or monoclonal antibody could have a substantial effect on disease burden in this age group. The Bill & Melinda Gates Foundation.
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Respiratory syncytial virus (RSV) is a major cause of viral lower respiratory tract infections among infants and young children in both developing and developed countries. There are two major antigenic groups of RSV, A and B, and additional antigenic variability occurs within the groups. The most extensive antigenic and genetic diversity is found in the attachment glycoprotein, G. During individual epidemic periods, viruses of both antigenic groups may cocirculate or viruses of one group may predominate. When there are consecutive annual epidemics in which the same group predominates, the dominant viruses are genetically different from year to year. The antigenic differences that occur among these viruses may contribute to the ability of RSV to establish reinfections throughout life. The differences between the two groups have led to vaccine development strategies that should provide protection against both antigenic groups. The ability to discern intergroup and intragroup differences has increased the power of epidemiologic investigations of RSV. Future studies should expand our understanding of the molecular evolution of RSV and continue to contribute to the process of vaccine development.
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Respiratory syncytial virus (RSV) is considered the most common pathogen causing severe lower respiratory tract infections among infants and young children. We describe the seasonality and geographical spread of RSV infection in 15 countries of the European Union and European Economic Area. We performed a retrospective descriptive study of weekly laboratory-confirmed RSV detections between weeks 40/2010 and 20/2016, in patients investigated for influenza-like illness, acute respiratory infection or following the clinician's judgment. Six countries reported 4,230 sentinel RSV laboratory diagnoses from primary care and 14 countries reported 156,188 non-sentinel laboratory diagnoses from primary care or hospitals. The median length of the RSV season based on sentinel and non-sentinel surveillance was 16 (range: 9-24) and 18 (range: 8-24) weeks, respectively. The median peak weeks for sentinel and non-sentinel detections were week 4 (range: 48 to 11) and week 4.5 (range: 49 to 17), respectively. RSV detections peaked later (r = 0.56; p = 0.0360) and seasons lasted longer with increasing latitude (r = 0.57; p = 0.0329). Our data demonstrated regular seasonality with moderate correlation between timing of the epidemic and increasing latitude of the country. This study supports the use of RSV diagnostics within influenza or other surveillance systems to monitor RSV seasonality and geographical spread.
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Respiratory syncytial virus (RSV) is the leading cause of acute lower respiratory infections (ALRI) in children. By the age of 1 year, 60-70% of children have been infected by RSV. In addition, early-life RSV infection is associated with the development of recurrent wheezing and asthma in infancy and childhood. The need for precise epidemiologic data regarding RSV as a worldwide pathogen has been growing steadily as novel RSV therapeutics are reaching the final stages of development. To optimize the prevention, diagnosis and treatment of RSV infection in a timely manner, knowledge about the differences in the timing of the RSV epidemics worldwide is needed. Previous analyses, based on literature reviews of individual reports obtained from medical databases, have fail to provide global country seasonality patterns. Until recently, only certain countries have been recording RSV incidence through their own surveillance systems. This analysis was based on national RSV surveillance reports and medical databases from 27 countries worldwide. This is the first study using original source high-quality surveillance data to establish a global, robust and homogeneous report on global country-specific RSV seasonality.