Creating symptom-based criteria for diagnostic testing: a case study based on a multivariate analysis of data collected during the first wave of the COVID-19 pandemic in New Zealand.

BACKGROUND: Diagnostic testing using PCR is a fundamental component of COVID-19 pandemic control. Criteria for determining who should be tested by PCR vary between countries, and ultimately depend on resource constraints and public health objectives. Decisions are often based on sets of symptoms in individuals presenting to health services, as well as demographic variables, such as age, and travel history. The objective of this study was to determine the sensitivity and specificity of sets of symptoms used for triaging individuals for confirmatory testing, with the aim of optimising public health decision making under different scenarios. METHODS: Data from the first wave of COVID-19 in New Zealand were analysed; comprising 1153 PCR-confirmed and 4750 symptomatic PCR negative individuals. Data were analysed using Multiple Correspondence Analysis (MCA), automated search algorithms, Bayesian Latent Class Analysis, Decision Tree Analysis and Random Forest (RF) machine learning. RESULTS: Clinical criteria used to guide who should be tested by PCR were based on a set of mostly respiratory symptoms: a new or worsening cough, sore throat, shortness of breath, coryza, anosmia, with or without fever. This set has relatively high sensitivity (> 90%) but low specificity (< 10%), using PCR as a quasi-gold standard. In contrast, a group of mostly non-respiratory symptoms, including weakness, muscle pain, joint pain, headache, anosmia and ageusia, explained more variance in the MCA and were associated with higher specificity, at the cost of reduced sensitivity. Using RF models, the incorporation of 15 common symptoms, age, sex and prioritised ethnicity provided algorithms that were both sensitive and specific (> 85% for both) for predicting PCR outcomes. CONCLUSIONS:  If predominantly respiratory symptoms are used for test-triaging,  a large proportion of the individuals being tested may not have COVID-19. This could overwhelm testing capacity and hinder attempts to trace and eliminate infection. Specificity can be increased using alternative rules based on sets of symptoms informed by multivariate analysis and automated search algorithms, albeit at the cost of sensitivity. Both sensitivity and specificity can be improved through machine learning algorithms, incorporating symptom and demographic data, and hence may provide an alternative approach to test-triaging that can be optimised according to prevailing conditions.

An outbreak of Salmonella Typhimurium phage type 42 associated with the consumption of raw flour.

A cluster of salmonellosis cases caused by Salmonella Typhimurium phage type 42 (STM42) emerged in New Zealand in October 2008. STM42 isolates from a wheat-based poultry feed raw material (broll; i.e., product containing wheat flour and particles of grain) had been identified in the 2 months prior to this cluster. Initial investigations indicated that eating uncooked baking mixture was associated with illness. A case-control study was conducted to test the hypothesis that there was an association between STM42 cases and consumption of raw flour or other baking ingredients. Salmonella isolates from human and non-human sources were compared using pulsed-field gel electrophoresis (PFGE) and multiple-locus variable number tandem repeat analysis (MLVA). Environmental investigations included testing flour and other baking ingredients from case homes, unopened bags of flour purchased from retail stores, and inspection of an implicated flour mill. A case-control study of 39 cases and 66 controls found cases had 4.5 times the odds of consuming uncooked baking mixture as controls (95% confidence interval [CI] 1.6-12.5, p-value 0.001). Examination of individual baking ingredients found that, after adjusting for eggs, flour had an odds ratio (OR) of 5.7 (95% CI 1.1-29.1, p-value 0.035). After adjusting for flour, eggs had an OR of 0.8 (95% CI 0.2-3.4, p-value 0.762). PFGE patterns were identical for all STM42 isolates tested; however, MLVA distinguished isolates that were epidemiologically linked to the cluster. STM42 was recovered from flour taken from four cases' homes, two unopened packs purchased from retail stores and packs from three batches of retrieved (recalled) product. This outbreak was associated with the consumption of uncooked baking mixture containing flour contaminated with STM42. The implicated flour mill initiated a voluntary withdrawal from sale of all batches of flour thought to be contaminated. Media releases informed the public about implicated flour brands and the risks of consuming uncooked baking mixture.

Pandemic (H1N1) 2009 and seasonal influenza A (H1N1) co-infection, New Zealand, 2009.

Co-infection with seasonal influenza A (H1N1) and pandemic (H1N1) 2009 could result in reassortant viruses that may acquire new characteristics of transmission, virulence, and oseltamivir susceptibility. Results from oseltamivir-sensitivity testing on viral culture suggested the possibility of co-infections with oseltamivir-resistant (seasonal A [H1N1]) and -susceptible (pandemic [H1N1] 2009) viruses.

COVID-19 in New Zealand and the impact of the national response: a descriptive epidemiological study.

BACKGROUND: In early 2020, during the COVID-19 pandemic, New Zealand implemented graduated, risk-informed national COVID-19 suppression measures aimed at disease elimination. We investigated their impacts on the epidemiology of the first wave of COVID-19 in the country and response performance measures. METHODS: We did a descriptive epidemiological study of all laboratory-confirmed and probable cases of COVID-19 and all patients tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in New Zealand from Feb 2 to May 13, 2020, after which time community transmission ceased. We extracted data from the national notifiable diseases database and the national SARS-CoV-2 test results repository. Demographic features and disease outcomes, transmission patterns (source of infection, outbreaks, household transmission), time-to-event intervals, and testing coverage were described over five phases of the response, capturing different levels of non-pharmaceutical interventions. Risk factors for severe outcomes (hospitalisation or death) were examined with multivariable logistic regression and time-to-event intervals were analysed by fitting parametric distributions using maximum likelihood estimation. FINDINGS: 1503 cases were detected over the study period, including 95 (6·3%) hospital admissions and 22 (1·5%) COVID-19 deaths. The estimated case infection rate per million people per day peaked at 8·5 (95% CI 7·6-9·4) during the 10-day period of rapid response escalation, declining to 3·2 (2·8-3·7) in the start of lockdown and progressively thereafter. 1034 (69%) cases were imported or import related, tending to be younger adults, of European ethnicity, and of higher socioeconomic status. 702 (47%) cases were linked to 34 outbreaks. Severe outcomes were associated with locally acquired infection (crude odds ratio [OR] 2·32 [95% CI 1·40-3·82] compared with imported), older age (adjusted OR ranging from 2·72 [1·40-5·30] for 50-64 year olds to 8·25 [2·59-26·31] for people aged ≥80 years compared with 20-34 year olds), aged residential care residency (adjusted OR 3·86 [1·59-9·35]), and Pacific peoples (adjusted OR 2·76 [1·14-6·68]) and Asian (2·15 [1·10-4·20]) ethnicities relative to European or other. Times from illness onset to notification and isolation progressively decreased and testing increased over the study period, with few disparities and increasing coverage of females, Maori, Pacific peoples, and lower socioeconomic groups. INTERPRETATION: New Zealand's response resulted in low relative burden of disease, low levels of population disease disparities, and the initial achievement of COVID-19 elimination. FUNDING: Ministry of Business Innovation and Employment Strategic Scientific Investment Fund, and Ministry of Health, New Zealand.

The burden of Legionnaires' disease in New Zealand (LegiNZ): a national surveillance study.

BACKGROUND: Legionnaires' disease is under-diagnosed because of inconsistent use of diagnostic tests and uncertainty about whom to test. We assessed the increase in case detection following large-scale introduction of routine PCR testing of respiratory specimens in New Zealand. METHODS: LegiNZ was a national surveillance study done over 1-year in which active case-finding was used to maximise the identification of cases of Legionnaires' disease in hospitals. Respiratory specimens from patients of any age with pneumonia, who could provide an eligible lower respiratory specimen, admitted to one of 20 participating hospitals, covering a catchment area of 96% of New Zealand's population, were routinely tested for legionella by PCR. Additional cases of Legionnaires' disease in hospital were identified through mandatory notification. FINDINGS: Between May 21, 2015, and May 20, 2016, 5622 eligible specimens from 4862 patients were tested by PCR. From these, 197 cases of Legionnaires' disease were detected. An additional 41 cases were identified from notification data, giving 238 cases requiring hospitalisation. The overall incidence of Legionnaires' disease cases in hospital in the study area was 5·4 per 100 000 people per year, and Legionella longbeachae was the predominant cause, found in 150 (63%) of 238 cases. INTERPRETATION: The rate of notified disease during the study period was three-times the average over the preceding 3 years. Active case-finding through systematic PCR testing better clarified the regional epidemiology of Legionnaires' disease and uncovered an otherwise hidden burden of disease. These data inform local Legionnaires' disease testing strategies, allow targeted antibiotic therapy, and help identify outbreaks and effective prevention strategies. The same approach might have similar benefits if applied elsewhere in the world. FUNDING: Health Research Council of New Zealand.

Increasing incidence of invasive group A streptococcus disease in New Zealand, 2002-2012: a national population-based study.

OBJECTIVES: To analyse the incidence, demographics and molecular epidemiology of invasive group A streptococcal (GAS) disease in New Zealand between 2002 and 2012. METHODS: Using laboratory-based surveillance data, invasive GAS isolates were identified from the Institute of Environmental Science and Research, New Zealand. Hospitalization and mortality data were obtained from the New Zealand Ministry of Health. Molecular typing was performed by sequence analysis of the emm gene. RESULTS: The incidence of invasive GAS infections increased from 3.9 per 100,000 population in 2002 to 7.9 per 100,000 population (P < 0.001) in 2012. The incidence was highest in the over 75-year age group, and in Pacific peoples. There was temporal variation in emm types associated with invasive GAS disease, with emm1 being the overall predominant emm type. The diversity of emm types varied significantly according to ethnicity. Overall, 59% of GAS isolates were theoretically covered by an experimental M-protein vaccine. CONCLUSIONS: Our study provides valuable data on the epidemiology of invasive GAS disease in New Zealand, and represents one of the few studies to assess such longitudinal data across an entire nation. The increase in invasive GAS disease is concerning, and reasons for this should be explored further.

Risk of giardiasis in Aucklanders: a case-control study.

BACKGROUND: Giardia is one of the leading protozoal causes of human gastrointestinal illnesses. It is prevalent in both developed and developing countries. Currently, giardiasis is the most commonly notified waterborne disease in New Zealand. The aim of the study was to identify potentially modifiable risk factors for Giardia infection in the adult population in Auckland. METHODS: This case-control study involved 183 Giardia-positive cases and 336 randomly selected controls, aged between 15 and 64 years. Exposure information was collected retrospectively over the telephone for the 21 days preceding the date of onset of symptoms. Both univariate and multiple logistic regression analyses were carried out. RESULTS: The majority of cases were in the 25-44-year age group and in the New Zealand European ethnic group. Housewives and nursing mothers were at significant risk of the disease (odds ratio (OR)=2.06; 95% CI=1.4-3.74), as were the occupational groups exposed to human wastes (OR=4.04, 95% CI=1.85-8.85). Consumption of drinking water from New Zealand supplies other than metropolitan mains supplies (OR=2.11, 95% CI=1.36-3.27) or from sources outside New Zealand (OR=7.97, 95% CI=4.20-15.12) represented a significantly higher risk, as did traveling (OR=7.57, 95% CI=4.03-14.23) and swimming in pools or fresh water at least once a week (OR=2.04, 95% CI= 1.33-3.12). CONCLUSIONS: The study identified potentially modifiable risk factors for Giardia infection. These findings should be investigated further in different groups and settings to ensure better protection of the public health.

Meningococcal disease and meteorological conditions in Auckland, New Zealand.

OBJECTIVE: The purpose of the study was to explore and model the relationship between meteorological variables and meningococcal disease notifications in Auckland during an ongoing group B meningococcal disease epidemic. METHODS: An ecological study design was used to investigate the relationship between 1,097 notified cases of meningococcal disease from January 1992 to December 1998 among residents of Auckland's three health districts and various meteorological variables. Descriptive epidemiology and Poisson regression modelling were used to describe this relationship. FINDINGS: The study found that the occurrence of meningococcal disease varied with season, increased with high humidity and cooler temperatures and appeared to decline with prolonged periods of heavy rain. Poisson regression analysis showed a significant relationship between the expected number of cases developing meningococcal disease on a given day and season and temperature. DISCUSSION: The results of the modelling analysis provide the initial work for the future development of a predictive tool to forecast the magnitude and duration of the annual peak in meningococcal disease incidence using routine notification data and meteorological recordings, thus allowing for better management of the public health workload and interventions, and the appropriate timing of media campaigns.

Giardia infection in Auckland and New Zealand: trends and international comparison.

AIMS: To describe the epidemiological pattern of Giardia infection in the Auckland region and compare it with national and international patterns of Giardia infection. METHODS: Anonymised giardiasis notification data from the Auckland District Health Board for the period July 1996 to June 2000 were analysed by person, place and time. Infection rates and relative risks were calculated and compared with national and international information. RESULTS: Auckland had a significantly higher rate of Giardia infection than New Zealand as a whole. Infection rates, which peaked during February-May, were significantly higher in Pakeha/Europeans and Asian/others, compared with Maori/Pacificans. Adjusted notification rates were higher for residents of North Shore and Auckland cities than for other areas of Auckland. The crude regional and national notification rates were almost six times the rate of laboratory identification of positive isolates in the UK and four times US reported rates. CONCLUSIONS: The higher rates of giardiasis observed in Auckland and New Zealand, in comparison with other developed countries, may be related to environmental or social factors. Missing ethnicity information precludes clear interpretation of variations in notification rate by ethnic group and suggests a need for improvement in data collection. There are opportunities to investigate the influence of risk factors on seasonal changes in notification rates both locally and nationally.

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.

Ayurvedic medicine: patients in peril from plumbism.

Heavy metals are commonly incorporated into Ayurvedic preparations as ashes or 'bhasmas'. A widely disseminated belief within Ayurvedic medicine is that these heavy metals can be valuable therapeutic components. Western toxicology refutes this contention. We report eight cases of lead poisoning occurring in or near the Auckland region of New Zealand. In all cases, poisoning was attributable to consumption of Ayurvedic 'herbal medicines'. Whole blood lead levels ranged from 1.5 to 6.9 micromol/L. Six patients had symptomatic lead poisoning, requiring treatment with chelation therapy. A high index of suspicion is required to detect lead poisoning, which should be suspected in people taking Ayurvedic remedies, especially if they have associated anaemia or abdominal symptoms.

A descriptive epidemiology of giardiasis in New Zealand and gaps in surveillance data.

INTRODUCTION: Giardia is the most commonly notified waterborne disease in New Zealand, which has high incidence rates compared with other developed countries. Four years of giardiasis notification data were analysed to describe the epidemiological patterns of infection in New Zealand and compared with local and international data. METHODS: Anonymised information was collected nationally for 7818 notified cases of giardiasis between July 1996 and June 2000. International data were collected from the data sources of respective countries. Infection rates adjusted for confounding factors were calculated and presented by age, gender, ethnicity, and area using statistical and spatial methods. RESULTS: Most cases occurred in the 1-4 year age group followed by the 25-44 year age group, and were of Pakeha/European ethnicity. Ethnicity was unknown for 18% of cases, thus affecting demographic calculations. Rates were elevated for several Health Districts in New Zealand (West Coast, Wellington, Waikato, Auckland, Hawke's Bay, Hutt, Rotorua, and Tauranga). CONCLUSIONS: The higher rates of giardiasis observed in New Zealand, in comparison with other developed countries, may be related to environmental or social factors. Time-trend analysis suggests a seasonal pattern. This study identified vulnerable groups and major data-gaps. Recommendations for improvements in disease surveillance and data quality are discussed. Geographical information system (GIS) applications are useful for disease monitoring.