Hospital-based severe acute respiratory infection (SARI) surveillance
The population-based hospital SARI surveillance among residents (catchment population of one million people across the central, east, and south of the Auckland region) was established in 2012 as the first iteration of the Southern Hemisphere Influenza and Vaccine Effectiveness Research and Surveillance (SHIVERS-I) study.49,50 Active surveillance period for ICU was all-year-around and for general medical wards usually during May to September of each year but started early from 7-February-2022 due to COVID-19 community transmission. Research nurses working in secondary and tertiary care hospital settings usually reviewed daily records of all overnight general medical wards and ICU admitted acute inpatients to identify any inpatient with a suspected acute respiratory illness. The research nurses enrolled those patients with cough and history of fever (subjective fever or measured temperature ≥38°C) and onset within the past 10 days, defined by the WHO as SARI. A respiratory specimen (nasopharyngeal or nasal or throat swab) was collected and tested simultaneously by nucleic acid amplification tests (NAAT) specifically for:50 influenza virus, RSV, rhinovirus, parainfluenza virus types 1-3, enterovirus, adenovirus, human metapneumovirus.
SHIVERS-II, III, IV community cohort acute respiratory infection (ARI) surveillance
SHIVERS-II (the second iteration of SHIVERS) is a prospective adult cohort study in the Wellington region, NZ.5 The aim is to understand how adult’s prior influenza exposure influences their subsequent influenza infections or vaccinations. The cohort study has been in operation since 2018 enrolling individuals aged 20-69 years, randomly selected from those healthy individuals listed in the management systems of selected primary care general practices. The study staff followed up SHIVERS-II adult participants (approximately 1400 in 2020, 1100 in 2021, and 900 in 2022) and monitored them for their ILI and ARI episodes.
SHIVERS-III is a prospective infant cohort study for seven years (2019-2026) situated in Wellington, NZ.5 The study aims to understand how a child’s first influenza exposure shapes their immune responses to subsequent influenza exposures. The study staff followed up infant participants (approximately 80 in 2020, 300 in 2021, and 600 in 2022) and monitored them for their ILI and ARI episodes.
SHIVERS-IV is a prospective household cohort study which follows approximately 500 Wellington families (approximately 1800 participants) for up to seven years (2021-2028), aiming to understand transmission of and susceptibility to influenza virus. The study staff followed up household participants (approximately 1000 in 2021 and 1700 in 2022) and monitored them for their ILI and ARI episodes.
The active surveillance period for each of these community studies occurs usually May to September of each year. In 2022, surveillance started early from 7-February due to COVID-19 community transmission. During active surveillance, the study staff sent weekly surveys to participants regarding their ARI. Research nurses reviewed participant’s symptom reports and identified those met ARI case definition: “an acute respiratory illness with fever or feverishness and/or one of following symptoms (cough, running nose, wheezing, sore throat, shortness of breath, loss of sense of smell/taste) with onset in the past 10 days”. Research nurses guided the participant with ARI to take a nasopharyngeal or nasal swab to test by NAAT for influenza, RSV, rhinovirus, parainfluenza virus types 1-3, enterovirus, adenovirus, human metapneumovirus, and SARS-CoV-2.51
HealthStat’s sentinel general practice (GP)-based influenza like-illness (ILI) surveillance and SHIVERS-V sentinel GP-based ARI surveillance
HealthStat general practice (GP) based ILI surveillance is based on a nationally representative random sample of approximately 300 general practices that use ILI Read codes.5,52 The case definition used for ILI by HealthStat is “an acute upper respiratory tract infection, with abrupt onset of two or more symptoms from chills, fever, headache and myalgia”. This surveillance system monitors the number of people who consult GPs with an ILI. HealthStat is based on automated extracts from practice management computer systems. ESR received the data during 2019-2022 from CBG Health Research Ltd and published the weekly data on ESR’s website.53 HealthStat ILI surveillance did not include virological surveillance.
SHIVERS-V sentinel GP-based ARI surveillance (from eight sentinel general practices in Auckland, Wellington, and Dunedin) was established in the middle of June 2021. The participating general practitioners and practice nurses assessed all consultation seeking patients. If a patient met the ARI case definition (the same as SHIVERS-II, III, IV ARI). A respiratory specimen (nasopharyngeal or nasal swab) was collected to test by NAAT for SARS-CoV-2, influenza, RSV, rhinovirus, and other respiratory viruses.
SHIVERS-V traveller ARI surveillance
SHIVERS-V traveller ARI surveillance was established on 10-May-2021 and was operational until 27-Feb-2022. All travellers staying in 32 mandatory government-managed isolation and quarantine (MIQ) facilities were required to test for COVID-19. SHIVERS-V traveller ARI surveillance included five hospital-based laboratories covering 29 MIQ facilities. A daily electronic extract from the COVID-19 éclair (https://www.sysmex-ap.com/product/eclair/) database was generated for each participating hospital laboratory to identify any traveller with a suspected acute respiratory infection who may meet the ARI case definition (the same as SHIVERS-V GP ARI). If there was any left-over specimen after the SARS-CoV-2 testing, the specimen was tested by NAAT for influenza, RSV, rhinovirus, and other respiratory viruses.
Laboratory-based surveillance
The laboratory-based surveillance for influenza, RSV and other common respiratory viruses is carried out all-year-around by the NZ virus laboratory network consisting of the WHO National Influenza Centre (NIC) at ESR and six hospital-based laboratories in Auckland (2), Waikato, Wellington, Christchurch, and Dunedin. This laboratory network tests specimens ordered by clinicians for hospital inpatients and outpatients during normal clinical practice (serving approximately 70% of the NZ population). Sample collection is based on clinician’s judgement, rather than a systematic sampling approach. This may introduce selection bias. In addition, this laboratory network conducts testing for public health surveillance including SARI, ILI/ARI, and SHIVERS-II, III, IV cohort surveillance.
Genome sequencing and assembly
RSV genomes were sequenced using the Illumina (USA) Respiratory Virus Oligo Panel V2 from total RNA purified using the MagMax™ Viral/Pathogen Nucleic Acid Isolation Kit from ThermoFisher Scientific (cat #A48310). Consensus based assembly was performed using Seattle Flu Assembly Pipeline modified to use with the ESR compute infrastructure (https://github.com/seattleflu/assembly). Two additional references were used for consensus calling. These are GISAID assemblies EPI_ISL_2543807 and EPI_ISL_2543850. Both were recent genomes from samples isolated in Australia. For each sample the consensus genome with fewest number of ambiguities were used for downstream analysis.
Phylogenetic analysis of RSV
RSV sequences from NZ were analyzed together with all global RSV full genomes sampled between January 2012 and September 2022, which were obtained from GISAID54 (September 2022; see Supplementary Data for accession numbers). This resulted in 1,359 RSV-A global genomes and 1,259 RSV-B global genomes, including 428 and 242 Australian sampled genomes, respectively. Genomes for each subtype were aligned using MAFFT(v 7),55 using the FFT-NS-2 algorithm. A maximum likelihood phylogenetic tree was estimated using IQ-TREE (v 2.0.3),56 utilising the Hasegawa-Kishino-Yano (HKY+Γ)57 nucleotide substitution model with a gamma distributed rate variation among sites. The best fit model was determined by ModelFinder,58 and branch support assessment using the ultrafast bootstrap method.59 To depict virus evolution in time, we used Least Squares Dating implemented within IQ-TREE to estimate a time-scaled phylogenetic tree using the day of sampling.
Data analyses
Study data were captured using REDCap 10.0.19 electronic data capture tools.60 Analyses were performed in Stata 16.1 (StataCorp LLC).
The observed incidence rates of influenza-PCR-confirmed SARI or ARI or ILI were corrected each week to account for missed swabs from ARI cases by applying the influenza positivity rate of those tested to those not tested (corrected number of influenza-PCR-confirmed SARI or ILI or ARI events = Number of SARI or ILI or ARI x Actual number of influenza-PCR-confirmed SARI or ILI or ARI /Actual number of SARI or ILI or ARI swabs).
Based on SARI and ARI surveillance data from 2015-2019, the start of the annual influenza season and intensity level of the influenza epidemics was defined by using the Moving Epidemic Method (MEM).52,61,62 Briefly, MEM has three main steps: Step 1: for each season separately, the length of the epidemic period is estimated as the minimum number of consecutive weeks with the maximum accumulated percentage rates, splitting the season into three periods: a pre-epidemic, an epidemic, and a post-epidemic period; Step 2: MEM calculates the epidemic threshold as the upper limit of the 95% one-sided confidence interval of 30 highest pre-epidemic weekly rates, the n highest for each season taking the whole training period, where n = 30/number of seasons; Step 3: medium, high, and extra-ordinary intensity thresholds were estimated as the upper limits of the 40%, 90%, and 97.5% one-sided confidence intervals of the geometric mean of 30 highest epidemic weekly rates, the n highest for each season taking the whole training period, where n = 30/number of seasons. Five categories are used to set thresholds and define intensity level as no activity or below epidemic threshold, low (0-40%), moderate (40-90%), high (90-97.5%) and extra-ordinary (>97.5%) one sided confidence interval of the geometric mean.
Laboratory-based surveillance data used the median of the annual total of the specified week period over the years 2015-2019 to represent the reference period for that week period. Median and interquartile ranges were calculated for the number of viruses reported during 2015-2019; Percentage of reduction = {1 - [No. virus/median no. virus (2015-2019)]} x100.