Impacts of the COVID-19 lockdown on self-reported mood and self-rated health of community-dwelling adults with chronic illness.

AIM: To determine whether self-reported mood or self-rated health were affected in community-dwelling adults with chronic illness following COVID-19 lockdown. METHODS: This was a repeated cross-sectional study using secondary data. We included New Zealanders aged 40+ who underwent International Residential Instrument (interRAI) assessments in the year prior to COVID-19 lockdown (25 March 2019-24 March 2020) or in the year following COVID-19 lockdown (25 March 2020-24 March 2021). Pairwise comparisons were made between each pre-lockdown quarter and its respective post-lockdown quarter to account for seasonality patterns. Data from 45,553 (pre-lockdown) and 45,349 (post-lockdown) assessments were analysed. Outcomes (self-reported mood, self-rated health) were stratified by socio-demographic variables. RESULTS: Self-reported mood improved in the first quarter post-lockdown among those aged 80+, as well as among women, people of European ethnicity, those living alone and those living in more deprived areas. Self-rated health improved in these same groups, as well as among those aged 65-79, and among men. No differences in self-reported mood or self-rated health were found in the second, third, or fourth quarters post-lockdown. CONCLUSIONS: Self-reported mood and self-rated health of community-dwelling adults with chronic illness were not negatively affected following COVID-19 lockdown, and temporarily improved among some sub-groups. However, the longer-term impacts of the COVID-19 pandemic need to be closely monitored.

Impact of COVID-19 on the health and psychosocial status of vulnerable older adults: study protocol for an observational study.

BACKGROUND: Many countries around the world have adopted social distancing as one of the public health measures to reduce COVID-19 transmissions in the community. Such measures could have negative effects on the mental health of the population. The aims of this study are to (1) track the impact of COVID-19 on self-reported mood, self-rated health, other health and psychosocial indicators, and health services utilization of people who have an interRAI assessment during the first year of COVID-19; (2) compare these indicators with the same indicators in people who had an interRAI assessment in the year before COVID-19; and (3) report these indicators publicly as soon as data analysis is completed every 3 months. METHODS: interRAI COVID-19 Study (iCoS) is an observational study on routinely collected national data using the interRAI Home Care and Contact Assessment, which are standardized geriatric assessment tools mandated for all people assessed for publicly funded home support services and aged residential care in New Zealand. Based on the 2018/19 figures, we estimated there are 36,000 interRAI assessments per annum. We will compare the four post-lockdown quarters (from 25th March 2020) with the respective pre-lockdown quarters. The primary outcomes are self-reported mood (feeling sad, depressed or hopeless: 0 = no, 1 = yes) and self-rated health (0 = excellent, 1 = good, 2 = fair, 3 = poor). We will also analyze sociodemographics, other secondary health and psychosocial indicators, and health services utilization. Descriptive statistics will be conducted for primary outcomes and other indicators for each of the eight quarters. We will compare the quarters using regression models adjusted for demographic characteristics using weights or additional variables. Key health and psychosocial indicators will be reported publicly as soon as data analysis is completed for each quarter in the 12-month post-lockdown period by using a data visualization tool. DISCUSSION: This rapid translation of routinely collected national interRAI data will provide a means to monitor the health and psychosocial well-being of vulnerable older New Zealanders. Insights from this study can be shared with other countries that use interRAI and prepare health and social services for similar epidemics/pandemics in the future.

Risk Factors and Attack Rates of Seasonal Influenza Infection: Results of the Southern Hemisphere Influenza and Vaccine Effectiveness Research and Surveillance (SHIVERS) Seroepidemiologic Cohort Study.

Background: Understanding the attack rate of influenza infection and the proportion who become ill by risk group is key to implementing prevention measures. While population-based studies of antihemagglutinin antibody responses have been described previously, studies examining both antihemagglutinin and antineuraminidase antibodies are lacking. Methods: In 2015, we conducted a seroepidemiologic cohort study of individuals randomly selected from a population in New Zealand. We tested paired sera for hemagglutination inhibition (HAI) or neuraminidase inhibition (NAI) titers for seroconversion. We followed participants weekly and performed influenza polymerase chain reaction (PCR) for those reporting influenza-like illness (ILI). Results: Influenza infection (either HAI or NAI seroconversion) was found in 321 (35% [95% confidence interval, 32%-38%]) of 911 unvaccinated participants, of whom 100 (31%) seroconverted to NAI alone. Young children and Pacific peoples experienced the highest influenza infection attack rates, but overall only a quarter of all infected reported influenza PCR-confirmed ILI, and one-quarter of these sought medical attention. Seroconversion to NAI alone was higher among children aged <5 years vs those aged ≥5 years (14% vs 4%; P < .001) and among those with influenza B vs A(H3N2) virus infections (7% vs 0.3%; P < .001). Conclusions: Measurement of antineuraminidase antibodies in addition to antihemagglutinin antibodies may be important in capturing the true influenza infection rates.

Effectiveness of seasonal influenza vaccination in community-dwelling elderly people: an individual participant data meta-analysis of test-negative design case-control studies.

BACKGROUND: Several aggregate data meta-analyses have provided estimates of the effectiveness of influenza vaccination in community-dwelling elderly people. However, these studies ignored the effects of patient-level confounders such as sex, age, and chronic diseases that could bias effectiveness estimates. We aimed to assess the confounder-adjusted effectiveness of influenza vaccines on laboratory-confirmed influenza among elderly people by conducting a global individual participant data meta-analysis. METHODS: In this individual participant data meta-analysis, we considered studies included in a previously conducted aggregate data meta-analysis that included test-negative design case-control studies published up to July 13, 2014. We contacted all authors of the included studies on Dec 1, 2014, to request individual participant data. Patients were excluded if their unique identifier was missing, their vaccination status was unknown, their outcome status was unknown, or they had had suspected influenza infection more than once in the same influenza season. Cases were patients with influenza-like illness symptoms who tested positive for at least one of A H1N1, A H1N1 pdm09, A H3N2, or B viruses; controls were patients with influenza-like illness symptoms who tested negative for these virus types or subtypes. Influenza vaccine effectiveness against overall and subtype-specific laboratory-confirmed influenza were the primary and secondary outcomes. We used a generalised linear mixed model to calculate adjusted vaccine effectiveness according to vaccine match to the circulating strains of influenza virus and intensity of the virus activity (epidemic or non-epidemic). Vaccine effectiveness was defined as the relative reduction in risk of laboratory-confirmed influenza in vaccinated patients compared with unvaccinated patients. We did subgroup analyses to estimate vaccine effectiveness according to hemisphere, age category, and health status. FINDINGS: We received 23 of the 53 datasets included in the aggregate data meta-analysis. Furthermore, six additional datasets were provided by data collaborators, which resulted in individual participant data for a total of 5210 participants. A total of 4975 patients had the required data for analysis. Of these, 3146 (63%) were controls and 1829 (37%) were cases. Influenza vaccination was significantly effective during epidemic seasons irrespective of vaccine match status (matched adjusted vaccine effectiveness 44·38%, 95% CI 22·63-60·01; mismatched adjusted vaccine effectiveness 20·00%, 95% CI 3·46-33·68; analyses in the imputed dataset). Seasonal influenza vaccination did not show significant effectiveness during non-epidemic seasons. We found substantial variation in vaccine effectiveness across virus types and subtypes, with the highest estimate for A H1N1 pdm09 (53·19%, 10·25-75·58) and the lowest estimate for B virus types (-1·52%, -39·58 to 26·16). Although we observed no significant differences between subgroups in each category (hemisphere, age, and health status), influenza vaccination showed a protective effect among elderly people with cardiovascular disease, lung disease, or aged 75 years and younger. INTERPRETATION: Influenza vaccination is moderately effective against laboratory-confirmed influenza in elderly people during epidemic seasons. More research is needed to investigate factors affecting vaccine protection (eg, brand-specific or type-specific vaccine effectiveness and repeated annual vaccination) in elderly people. FUNDING: University Medical Center Groningen.

Influenza vaccine effectiveness for hospital and community patients using control groups with and without non-influenza respiratory viruses detected, Auckland, New Zealand 2014.

BACKGROUND: We aimed to estimate the protection afforded by inactivated influenza vaccine, in both community and hospital settings, in a well characterised urban population in Auckland during 2014. METHODS: We used two different comparison groups, all patients who tested negative for influenza and only those patients who tested negative for influenza and had a non-influenza respiratory virus detected, to calculate the vaccine effectiveness in a test negative study design. Estimates were made separately for general practice outpatient consultations and hospitalised patients, stratified by age group and by influenza type and subtype. Vaccine status was confirmed by electronic record for general practice patients and all respiratory viruses were detected by real time polymerase chain reaction. RESULTS: 1039 hospitalised and 1154 general practice outpatient consultations met all the study inclusion criteria and had a respiratory sample tested for influenza and other respiratory viruses. Compared to general practice patients, hospitalised patients were more likely to be very young or very old, to be Maori or Pacific Islander, to have a low income and to suffer from chronic disease. Vaccine effectiveness (VE) adjusted for age and other participant characteristics using all influenza negative controls was 42% (95% CI: 16 to 60%) for hospitalised and 56% (95% CI: 35 to 70%) for general practice patients. The vaccine appeared to be most effective against the influenza A(H1N1)pdm09 strain with an adjusted VE of 62% (95% CI:38 to 77%) for hospitalised and 59% (95% CI:36 to 74%) for general practice patients, using influenza virus negative controls. Similar results found when patients testing positive for a non-influenza respiratory virus were used as the control group. CONCLUSION: This study contributes to validation of the test negative design and confirms that inactivated influenza vaccines continue to provide modest but significant protection against laboratory-confirmed influenza.

A chest radiograph scoring system in patients with severe acute respiratory infection: a validation study.

BACKGROUND: The term severe acute respiratory infection (SARI) encompasses a heterogeneous group of respiratory illnesses. Grading the severity of SARI is currently reliant on indirect disease severity measures such as respiratory and heart rate, and the need for oxygen or intensive care. With the lungs being the primary organ system involved in SARI, chest radiographs (CXRs) are potentially useful for describing disease severity. Our objective was to develop and validate a SARI CXR severity scoring system. METHODS: We completed validation within an active SARI surveillance project, with SARI defined using the World Health Organization case definition of an acute respiratory infection with a history of fever, or measured fever of ≥ 38 °C; and cough; and with onset within the last 10 days; and requiring hospital admission. We randomly selected 250 SARI cases. Admission CXR findings were categorized as: 1 = normal; 2 = patchy atelectasis and/or hyperinflation and/or bronchial wall thickening; 3 = focal consolidation; 4 = multifocal consolidation; and 5 = diffuse alveolar changes. Initially, four radiologists scored CXRs independently. Subsequently, a pediatrician, physician, two residents, two medical students, and a research nurse independently scored CXR reports. Inter-observer reliability was determined using a weighted Kappa (κ) for comparisons between radiologists; radiologists and clinicians; and clinicians. Agreement was defined as moderate (κ > 0.4-0.6), good (κ > 0.6-0.8) and very good (κ > 0.8-1.0). RESULTS: Agreement between the two pediatric radiologists was very good (κ = 0.83, 95% CI 0.65-1.00) and between the two adult radiologists was good (κ = 0.75, 95% CI 0.57-0. 93). Agreement of the clinicians with the radiologists was moderate-to-good (pediatrician:κ = 0.65; pediatric resident:κ = 0.69; physician:κ = 0.68; resident:κ = 0.67; research nurse:κ = 0.49, medical students: κ = 0.53 and κ = 0.56). Agreement between clinicians was good-to-very good (pediatrician vs. physician:κ = 0.85; vs. pediatric resident:κ = 0.81; vs. medicine resident:κ = 0.76; vs. research nurse:κ = 0.75; vs. medical students:κ = 0.63 and 0.66). Following review of discrepant CXR report scores by clinician pairs, κ values for radiologist-clinician agreement ranged from 0.59 to 0.70 and for clinician-clinician agreement from 0.97 to 0.99. CONCLUSIONS: This five-point CXR scoring tool, suitable for use in poorly- and well-resourced settings and by clinicians of varying experience levels, reliably describes SARI severity. The resulting numerical data enables epidemiological comparisons of SARI severity between different countries and settings.

Whooping cough­where are we now? A review.

AIMS: This paper describes the recent trends of pertussis and vaccine uptake in New Zealand based on notifications and immunisation registration information since 2011. It highlights the current risk for the infant in the first months after birth and the crucial role a pertussis booster in pregnancy could play. It also aims to show that protection of infants by the acellular pertussis vaccine can be improved by timely immunisation even in a situation of improving overall uptake rates that are nearing the national target of 95%. METHODS: We analysed New Zealand notification data for pertussis, extracted from EpiSurv between August 2011 and December 2013, which included the period of the last epidemic. Pertussis immunisation coverage data were extracted from the National Immunisation Register (NIR). Population estimates were based on 2006 census data. Deprivation was analysed using the New Zealand Deprivation Index 2006. RESULTS: Despite immunisation coverage at 12 months having exceeded 90% New Zealand experienced a large epidemic from 2011 to 2014, with several hundred infant hospitalisations and three deaths. Notification data indicated an average annual rate of pertussis in the New Zealand population of 102 per 100,000 with the highest rates in the youngest age groups. While an overall increase in immunisation coverage in New Zealand was evident and the timeliness showed improvement across ethnic groups and deprivation deciles, there was a marked geographical variation within DHBs and between ethnic groups. CONCLUSIONS: Given the recent published evidence, pertussis vaccination should be offered to all mothers between weeks 28 and 38 of pregnancy. Further improvements are still possible in coverage at 6 months, particularly in Maori and but also in Pacific populations, as well as in more deprived populations. DHBs work towards achieving the 95% target can contribute to the improvement in the timeliness of immunisation.

Implementing hospital-based surveillance for severe acute respiratory infections caused by influenza and other respiratory pathogens in New Zealand.

BACKGROUND: Recent experience with pandemic influenza A(H1N1)pdm09 highlighted the importance of global surveillance for severe respiratory disease to support pandemic preparedness and seasonal influenza control. Improved surveillance in the southern hemisphere is needed to provide critical data on influenza epidemiology, disease burden, circulating strains and effectiveness of influenza prevention and control measures. Hospital-based surveillance for severe acute respiratory infection (SARI) cases was established in New Zealand on 30 April 2012. The aims were to measure incidence, prevalence, risk factors, clinical spectrum and outcomes for SARI and associated influenza and other respiratory pathogen cases as well as to understand influenza contribution to patients not meeting SARI case definition. METHODS/DESIGN: All inpatients with suspected respiratory infections who were admitted overnight to the study hospitals were screened daily. If a patient met the World Health Organization's SARI case definition, a respiratory specimen was tested for influenza and other respiratory pathogens. A case report form captured demographics, history of presenting illness, co-morbidities, disease course and outcome and risk factors. These data were supplemented from electronic clinical records and other linked data sources. DISCUSSION: Hospital-based SARI surveillance has been implemented and is fully functioning in New Zealand. Active, prospective, continuous, hospital-based SARI surveillance is useful in supporting pandemic preparedness for emerging influenza A(H7N9) virus infections and seasonal influenza prevention and control.

The effectiveness of seasonal trivalent inactivated influenza vaccine in preventing laboratory confirmed influenza hospitalisations in Auckland, New Zealand in 2012.

BACKGROUND: Few studies report the effectiveness of trivalent inactivated influenza vaccine (TIV) in preventing hospitalisation for influenza-confirmed respiratory infections. Using a prospective surveillance platform, this study reports the first such estimate from a well-defined ethnically diverse population in New Zealand (NZ). METHODS: A case test-negative design was used to estimate propensity adjusted vaccine effectiveness. Patients with a severe acute respiratory infection (SARI), defined as a patient of any age requiring hospitalisation with a history of a fever or a measured temperature ≥38°C and cough and onset within the past 7 days, admitted to public hospitals in South and Central Auckland were eligible for inclusion in the study. Cases were SARI patients who tested positive for influenza, while non-cases (controls) were SARI patients who tested negative. Results were adjusted for the propensity to be vaccinated and the timing of the influenza season. RESULTS: The propensity and season adjusted vaccine effectiveness (VE) was estimated as 39% (95% CI 16;56). The VE point estimate against influenza A (H1N1) was lower than for influenza B or influenza A (H3N2) but confidence intervals were wide and overlapping. Estimated VE was 59% (95% CI 26;77) in patients aged 45-64 years but only 8% (-78;53) in those aged 65 years and above. CONCLUSION: Prospective surveillance for SARI has been successfully established in NZ. This study for the first year, the 2012 influenza season, has shown low to moderate protection by TIV against influenza positive hospitalisation.

Evaluation of rapid and simple techniques for the enrichment of viruses prior to metagenomic virus discovery.

The discovery of new or divergent viruses using metagenomics and high-throughput sequencing has become more commonplace. The preparation of a sample is known to have an effect on the representation of virus sequences within the metagenomic dataset yet comparatively little attention has been given to this. Physical enrichment techniques are often applied to samples to increase the number of viral sequences and therefore enhance the probability of detection. With the exception of virus ecology studies, there is a paucity of information available to researchers on the type of sample preparation required for a viral metagenomic study that seeks to identify an aetiological virus in an animal or human diagnostic sample. A review of published virus discovery studies revealed the most commonly used enrichment methods, that were usually quick and simple to implement, namely low-speed centrifugation, filtration, nuclease-treatment (or combinations of these) which have been routinely used but often without justification. These were applied to a simple and well-characterised artificial sample composed of bacterial and human cells, as well as DNA (adenovirus) and RNA viruses (influenza A and human enterovirus), being either non-enveloped capsid or enveloped viruses. The effect of the enrichment method was assessed by both quantitative real-time PCR and metagenomic analysis that incorporated an amplification step. Reductions in the absolute quantities of bacteria and human cells were observed for each method as determined by qPCR, but the relative abundance of viral sequences in the metagenomic dataset remained largely unchanged. A 3-step method of centrifugation, filtration and nuclease-treatment showed the greatest increase in the proportion of viral sequences. This study provides a starting point for the selection of a purification method in future virus discovery studies, and highlights the need for more data to validate the effect of enrichment methods on different sample types, amplification, bioinformatics approaches and sequencing platforms. This study also highlights the potential risks that may attend selection of a virus enrichment method without any consideration for the sample type being investigated.

Risk factors and immunity in a nationally representative population following the 2009 influenza A(H1N1) pandemic.

BACKGROUND: Understanding immunity, incidence and risk factors of the 2009 influenza A(H1N1) pandemic (2009 H1N1) through a national seroprevalence study is necessary for informing public health interventions and disease modelling. METHODS AND FINDINGS: We collected 1687 serum samples and individual risk factor data between November-2009 to March-2010, three months after the end of the 2009 H1N1 wave in New Zealand. Participants were randomly sampled from selected general practices countrywide and hospitals in the Auckland region. Baseline immunity was measured from 521 sera collected during 2004 to April-2009. Haemagglutination inhibition (HI) antibody titres of ≥1:40 against 2009 H1N1 were considered seroprotective as well as seropositive. The overall community seroprevalence was 26.7% (CI:22.6-29.4). The seroprevalence varied across age and ethnicity. Children aged 5-19 years had the highest seroprevalence (46.7%;CI:38.3-55.0), a significant increase from the baseline (14%;CI:7.2-20.8). Older adults aged ≥60 had no significant difference in seroprevalence between the serosurvey (24.8%;CI:18.7-30.9) and baseline (22.6%;CI:15.3-30.0). Pacific peoples had the highest seroprevalence (49.5%;CI:35.1-64.0). There was no significant difference in seroprevalence between both primary (29.6%;CI:22.6-36.5) and secondary healthcare workers (25.3%;CI:20.8-29.8) and community participants. No significant regional variation was observed. Multivariate analysis indicated age as the most important risk factor followed by ethnicity. Previous seasonal influenza vaccination was associated with higher HI titres. Approximately 45.2% of seropositive individuals reported no symptoms. CONCLUSIONS: Based on age and ethnicity standardisation to the New Zealand Population, about 29.5% of New Zealanders had antibody titers at a level consistent with immunity to 2009 H1N1. Around 18.3% of New Zealanders were infected with the virus during the first wave including about one child in every three. Older people were protected due to pre-existing immunity. Age was the most important factor associated with infection followed by ethnicity. Healthcare workers did not appear to have an increased risk of infection compared with the general population.