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Methodologies

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Sexually transmitted infections (STIs)

Syphilis, chlamydia and gonorrhoea surveillance in New Zealand

ESR undertakes STI surveillance on behalf of the Public Health Agency. The purposes on New Zealand STI surveillance system are:

  • to understand the burden of disease (as an input to planning, policy development, prioritisation and resource allocation),

  • to monitor inequalities in the burden of disease between population groups,

  • to monitor trends in the burden of disease over time,

  • to identify emerging problems, and outbreaks or clusters of disease, and

  • to evaluate the effectiveness of policies and programmes.

Before the Health (Protection) Amendment Act 2016 came into force, STI surveillance comprised a combination of voluntary sentinel clinic surveillance from Sexual Health and Family Planning Clinics, enhanced syphilis surveillance from these clinics, and laboratory surveillance of chlamydia and gonorrhoea.

Significant changes were made to the STI surveillance system after the Health (Protection) Amendment Act 2016 came into force in January 2017, making syphilis, gonorrhoea, HIV and AIDS notifiable to the Medical Officer of Health without identifying information (name, address and place of work), whereas previously only AIDS was notifiable. An interim solution was put in place from November 2018 using REDCap, a secure web application hosted on an ESR server, to collect data for syphilis, gonorrhoea and HIV in a survey format. 

Analytical methods for STI quarterly dashboard

Quarterly dashboard updates are based on data submitted at least two weeks before dashboard publication. Any data submitted after this point will be reflected in subsequent quarterly updates to the dashboard.

Calculations for ethnicity use the Ministry of Health prioritised ethnicity definition.

Methods

Case counts

For laboratory based surveillance rates, the numerator is the total number of laboratory-confirmed cases reported after exclusion of repeat tests for an individual within a defined episode period for the specific disease.

For infectious syphilis surveillance, the case counts are those cases classified as confirmed or probable based on the surveillance case definition. 

Where there is insufficient information provided, ethnicity is reported as Unknown.

Rate calculation

Caveats for interpreting rates:

  • Rates will not be presented where there were fewer than five cases in any category due to instability in these rates.
  • We advise dashboard viewers to consider the absolute number of cases that make up the numerator (see case counts) of any rate being interpreted.
  • With few cases in a numerator, rates could change dramatically based on differences of 1-2 cases. Rates with fewer than 20 cases in the numerator should be interpreted and compared to other rates with caution.
  • Sometimes, the highest rates involve few cases and therefore a relatively small proportion of the overall disease burden for New Zealand.

Laboratory-based surveillance rates use the applicable mid-year population estimates published by Statistics New Zealand as the denominators. Population estimates are downloaded from the Statistics New Zealand website annually and include estimates stratified by age, sex, and ethnicity (prioritised based on Ministry of Health definitions).

Influenza and Respiratory illness

Influenza and other acute respiratory illness surveillance systems

Acute respiratory illness (ARI) includes a range of symptoms like cough, fever, runny nose and sore throat. Acute respiratory illnesses are often caused by viral infections affecting the airways including influenza, SARS-CoV-2 and common cold viruses. 

Surveillance of acute respiratory illness allows for tracking of influenza (flu), as well as other viruses that cause similar symptoms, such as SARS-CoV-2, respiratory syncytial virus (RSV), and those that could be newly emerging. Respiratory virus surveillance systems are in place to monitor virus activity, detect epidemics or pandemics, inform vaccination policy and vaccine strain selection, and guide public health control measures in New Zealand and globally. 

Information on influenza and other respiratory viruses is presented weekly on a dashboard throughout the winter surveillance period (May to October) and as required outside of the winter period. See the acute respiratory illness dashboard and annual reports.

For any questions related to surveillance, please contact surv.queries@esr.cri.nz 

About

Surveillance objectives

The overarching goal of respiratory virus surveillance is to minimise the impact of disease by providing useful information to public health authorities and communities so they may better plan for appropriate health promotion, disease protection and control measures. 

The specific aims of acute respiratory illness surveillance are to: 

  1. To actively monitor and better understand the patterns of activity (e.g. seasonality, severity) of influenza, SARS-CoV- 2 and other respiratory viruses;

  2. Describe the burden of ILI- and SARI-associated influenza, SARS-CoV-2 and other respiratory viruses in New Zealand, including among priority populations;

  3. Describe characteristics of locally circulating influenza, SARS-CoV-2 and other respiratory viruses;

  4. Inform influenza and COVID-19 vaccination and treatment decisions to reduce the burden of disease and support equity of outcomes;

  5. Facilitate decision-making for pandemic influenza risk management nationally and globally.

Overview of respiratory virus surveillance

The burden of respiratory viruses, including influenza, RSV and SARS-CoV-2 can vary widely throughout and between years. While the effects of these viruses vary, it places a substantial burden on the people’s health and the health system every year. 

ARI surveillance systems collect information which together builds a picture of the burden of disease from influenza and other acute respiratory viruses in New Zealand and allows us to assess how well important public health protective measures, such as vaccination, are working. These surveillance systems operate in the community, primary care, hospitals and laboratories to capture disease presentations at different levels of severity. 

Community and hospital surveillance systems

Case definitions:

Influenza-like illness (ILI): ILI is defined by the World Health Organisation (WHO) as an acute respiratory infection with a history of fever (or measured fever of ≥38°C) AND cough.

Severe acute respiratory infection (SARI): SARI is defined by the WHO as the acute onset of cough and fever in the previous 10 days requiring hospitalisation. 

HealthStat sentinel general practice surveillance of influenza-like illness consultations – This system monitors the number of people who have presented to their general practice with influenza-like illness in the past week. Consultation information is extracted from around 300 general practice clinics nationally. Get more information on HealthStat.

HealthLine – This system monitors the number of calls made to Healthline (the free, national, 24-hour telephone health service) for acute respiratory illness advice each week. Calls are triaged using electronic clinical decision support software. Those coded as cold/flu, cough, croup, fever, general aches, headache and/or sore throat are counted as ILI. Non-symptomatic calls (30% of HealthLine calls) are excluded. 

FluTracking – This system relies on voluntary participation by the general public to self-report illness online. It was launched in New Zealand in 2018 and is used to monitor community-level ILI trends. In 2022, there were over 64,700 people who completed at least one FluTracking survey and an average of 37,200 responses were received per week. Participants are given the option to opt out outside of the influenza season (May to October), accordingly the sample size will be smaller at this time. Those who record experiencing a fever and cough are counted as ILI. See more information on FluTracking here. More detailed analysis of FluTracking data, and historical reports are also available

Sentinel GP virological surveillance - ESR works with a network of 50-100 sentinel general practice clinics around the country who take a respiratory swab from a subset of patients presenting to their clinic each week with ILI. These swabs are tested for a range of respiratory viruses at the ESR laboratory (see viral identification and characterisation methods). This system provides information on the different viruses that are circulating and causing illness in the community. 

Sentinel hospital surveillance – This system monitors patients admitted to hospital overnight with SARI in the four hospitals of the Auckland and Counties Manukau districts. Research nurses collect information on SARI patients in general wards and intensive care units (ICUs). Nasopharyngeal swabs are offered to patients if not already taken as part of clinical care and are tested for influenza and other respiratory viruses. Which viruses are tested for varies and is dependent on several factors, including clinical decision making, laboratory capacity and patient characteristics. The system operates from April to October in general wards and year-round in intensive care units (ICUs), though the surveillance period has been extended since the COVID-19 pandemic begun.   

Non-sentinel laboratory surveillance – A voluntary network of hospital laboratories provide data on detections of respiratory viruses in samples taken from individuals tested in hospital, emergency departments and in the community. Results should be interpreted with caution as these are from samples taken for various reasons as part of clinical care and are not systematically collected for surveillance. Samples undergoing testing and the viruses being tested for depend on several factors, including clinical decision making, laboratory capacity and patient demographic, and results will vary by region and over time without necessarily reflecting true epidemiological trends. In addition, negative results are not currently supplied to ESR, and so test positivity is not known.

COVID-19 notifiable disease surveillance - COVID-19 became a notifiable disease in New Zealand on 30 January 2020. The Ministry of Health collects data on reported cases, hospitalisations and deaths. This information is reported on the COVID-19 Trends and Insights Dashboard.  

ESR undertakes testing of wastewater throughout New Zealand on behalf of the Ministry for Health for the presence of SARS-CoV-2. The ESR wastewater dashboard can be found here. 

Viral identification and characterisation methods

Swabs collected through sentinel GP ILI surveillance are tested at ESR for influenza and other respiratory viruses (respiratory syncytial virus (RSV), parainfluenza virus 1–3, human metapneumovirus, rhinovirus and adenovirus). Swabs collected through sentinel hospital surveillance are tested at hospital labs for influenza and other viruses. Results from these tests for SARI patients are forwarded to ESR for integration into surveillance. 

Samples forwarded to ESR that are found to be influenza-positive undergo antigenic, genetic and antiviral characterization either at ESR or the WHO collaborating centres in Melbourne. 

Analytic methods

Rate Calculations 

Population data used to calculate rates of hospitalisations and HealthLine calls are derived from mid-year population estimates published by Statistics New Zealand. HealthStat general practice visit rates are calculated using registered patient populations. Registered patient counts are limited further by participating clinicians, if not all practice clinicians are contributing to surveillance. 

Presented rates are unadjusted. 

MEM Thresholds 

MEM is a standardised method of reporting influenza activity adopted by the European Centre for Disease Prevention and Control that allows intra- and inter- country comparisons. MEM defines the baseline influenza activity in historical data and establishes an epidemic threshold above which the weekly rates are considered to be in the epidemic period. Based on the historical data, influenza activity intensity is then also described according to categories as follows: (i) baseline: weekly rate is below or at the baseline epidemic threshold; (ii) low: weekly rate is above the baseline threshold and below the low average seasonal activity threshold; (iii) medium: weekly rate is between the low and medium activity threshold (iv) high: weekly rate is between the medium and high activity thresholds; (v) very high: weekly rate is above the high activity threshold. 

The historical data used to calculate the MEM thresholds for the GP ILI surveillance graph has been collected by ESR over the years 2000 to 2017, excluding the pandemic year 2009.  The thresholds are set at the 40%, 90%, and 97.5% confidence intervals, and labelled "Low seasonal level", "Moderate Seasonal Level", and "High Seasonal Level".  The level at which the season is defined as having started is labelled "Baseline Seasonal Level". 

Background and methods on EARS

Background and methods on EARS

The early aberration reporting system (EARS) is a widely used surveillance tool that applies aberration detection algorithms to surveillance data and flags anomalies to help with the timely detection of disease outbreaks. ESR has adapted New Zealand's EARS from the original U.S. Centers for Disease Control and Prevention (CDC) version.

Aberration detection algorithms are used by the EARS system to flag events for follow-up. The methods can be applied to different data sets including surveillance data (e.g. notifiable diseases, sentinel influenza, chemical poisoning, vaccine safety) and syndromic data (emergency department data, absenteeism (workplace and school) data and over the counter drug sales).

The EARS program is applied to New Zealand EpiSurv notifiable disease data, and is updated weekly. Access is currently restricted to staff working in the New Zealand health sector as approved by the Ministry of Health. Email survqueries@esr.cri.nz to request access. The analysis uses the notification date (data reported) in allocating week numbers to allow comparison between the data output.

An aberration is defined as a change in the distribution or frequency of health events when compared to historical data.

  • This may or may not be an outbreak

  • This may or may not be of public health interest

Principles and Practice of Public Health Surveillance (2002)

Not all flags will be of public health interest and the system relies on people who understand the data and system well to provide context to the data, e.g. the
aberration may be caused by a change in the laboratory testing method for an organism.

Flags can also be an isolated anomaly and as users become more familiar with their data, they are able to determine which flagging behaviour warrants an investigation.

Good communication between public health professionals is essential in determining whether the aberration requires public health response.

The EARS system has been redeveloped in R and now available in a dashboard. Red triangles are used to indicate anomalies.

EARS methods implemented for notifiable diseases

Spatial cluster & outlier method

The spatial method can be run on a single week of data. The spatial cluster & outlier method applies Local Moran's Index to identify spatial anomalies.

The disease rates in each DHB for a given week are clustered and compared with weights applied based on distance between their centre points.

Anselin, L.,1995, Local Indicators of Spatial Association-LISA. Geographical Analysis, 27, 93-115.

Window method

The window method model used is called 'rki'. The rki model compares the previous 6 weeks of values within a given DHB. An upper limit (threshold) is calculated using the non-outbreak case count from the previous 6 weeks and an alarm is raised if the actual value is bigger than the threshold) .If the mean of the previous 6 weeks is greater than 20 :

  • An aberration is flagged if the current value is greater than two standard deviations from the mean of the previous 6 weeks.

If the mean of the previous 6 weeks is less than 20:

  • An aberration is flagged if the current value is greater than the 95% confidence interval of the Poisson Distribution where mu is the mean of the previous 6 weeks, plus one.