Examining the impact of COVID-19 on Māori:non-Māori health inequities in Aotearoa, New Zealand: an observational study protocol

Abstract

Introduction

The COVID-19 pandemic has had both direct and indirect impacts on the health of populations worldwide. While racial/ethnic health inequities in COVID-19 infection are now well known (and ongoing), knowledge about the impact of COVID-19 pandemic management on non-COVID-19-related outcomes for Indigenous peoples is less well understood. This article presents the study protocol for the Health Research Council of New Zealand funded project ‘Mā te Mōhio ka Mārama: Impact of COVID-19 on Māori:non-Māori inequities’. The study aims to explore changes in access to healthcare, quality of healthcare and health outcomes for Māori, the Indigenous peoples of Aotearoa New Zealand (NZ) and non-Māori during the COVID-19 outbreak period across NZ.

Methods and analysis

This observational study is framed within a Kaupapa Māori research positioning that includes Kaupapa Māori epidemiology. National datasets will be used to report on access to healthcare, quality of healthcare and health outcomes between Māori and non-Māori during the COVID-19 pandemic in NZ. Study periods are defined as (a) prepandemic period (2015–2019), (b) first pandemic year without COVID-19 vaccines (2020) and (c) pandemic period with COVID-19 vaccines (2021 onwards). Regional and national differences between Māori and non-Māori will be explored in two phases focused on identified health priority areas for NZ including (1) mortality, cancer, long-term conditions, first 1000 days, mental health and (2) rheumatic fever.

Ethics and dissemination

This study has ethical approval from the Auckland Health Research Ethics Committee (AHREC AH26253). An advisory group will work with the project team to disseminate the findings of this project via project-specific meetings, peer-reviewed publications and a project-specific website. The overall intention of the project is to highlight areas requiring health policy and practice interventions to address Indigenous inequities in health resulting from COVID-19 pandemic management (both historical and in the future).

STRENGTHS AND LIMITATIONS OF THIS STUDY.

• This study aims to observe and understand broader health impacts of COVID-19 from an explicit Kaupapa Māori research positioning that includes Kaupapa Māori epidemiology.

• This study will measure health outcomes across several priority health areas to provide a broad view of the impact of COVID-19 on Māori health equity.

• The time periods proposed are arbitrary in nature and may not apply equally to Māori and non-Māori within New Zealand.

Introduction

The COVID-19 pandemic has had both direct and indirect impacts on the health of populations worldwide. Online supplemental table 1 impact of the pandemic extends beyond the direct consequences of infection with the SARS-CoV-2 virus itself and includes broader consequences associated with how countries and health systems managed the pandemic overall. The pandemic highlighted and amplified already existing inequities in health and society more broadly.¹ The impact of border and regional closures on people movement (which were pivotal for successful pandemic control), changed the way that people accessed healthcare services.^2–4 These impacts were particularly evident for screening services and planned interventions.⁵ How health systems ‘restarted’ postlockdown periods are also likely to have contributed to non-COVID-19-related illnesses and health outcomes (in addition to COVID-19 itself).⁶

Significant concerns have been raised by public health experts and clinicians that these issues may have exacerbated existing ethnic health inequities, particularly for many Indigenous peoples worldwide.⁷ In Aotearoa New Zealand (NZ), Māori (Tangata Whenua or the Indigenous peoples of the land—a glossary of Māori terms used in this paper is available in online supplemental table 1 who make up 17% of the total population of 5.1 million,⁸ experience significant inequities in accessing healthcare, have higher hospitalisation rates for avoidable and/or amenable conditions and receive lower quality of care.⁶ As predicted, Māori have been more severely impacted than non-Māori by COVID-19 infection.⁶ The age-standardised hospitalisation rate for COVID-19 is 2.3 times higher than people of ‘NZ European or Other’ ethnicity⁹ and Māori aged under 60 years of age are 3.7 times more likely to die from COVID-19 than people of ‘NZ European or other’ ethnicity.¹⁰

While the inequities in COVID-19 infection are now well documented (and ongoing), knowledge about the impact of COVID-19 pandemic management on non-COVID-19-related health outcomes for Māori compared with non-Māori is less well understood. This article presents the protocol paper for the Health Research Council of New Zealand funded project ‘Mā Te Mōhio Ka Mārama: Impact of COVID-19 on Māori:non-Māori inequities (M2M)’ that aims to comprehensively and independently document the impact of COVID-19 pandemic management on Māori inequities in health at both a nationwide and regional level across NZ. ‘Mā te Mōhio Ka Mārama’ (the headliner for the M2M project) comes from a Māori whakatauki (proverb) that relates to:

Mā te rongo, ka mōhio mā te mōhio, ka mārama mā te mārama, ka matau mā te matau, ka ora.

Through listening, comes awareness, through awareness, comes understanding, through understanding, comes knowledge, through knowledge, come’s life and well-being.

Background

NZ’s approach to COVID-19 was characterised by an early investment in a national elimination strategy, including the near complete closure of country borders, national and regional lockdowns, managed isolation quarantine facilities, and a comprehensive (although traditional) case and contact tracing public health system.^{11 12} Overall, these approaches during the early stages of the pandemic resulted in positive outcomes for the total population of NZ, including comparatively low COVID-19 mortality rates compared with other countries.¹³ Within these broad strategies were significant regional differences, with the Auckland region experiencing the most cases and longest duration of restrictions. A basic timeline of COVID-19 management in NZ is attached that shows the beginning of the COVID-19 pandemic in NZ in March 2020, the Delta wave in late 2021 and the Omicron wave in early 2022 (online supplemental table 2).

COVID-19 and Māori

Māori experiences of COVID-19 have not always aligned with the perceived overall success of the NZ Government’s efforts during the first 2 years of the pandemic. The likelihood of existing health inequities and racism in the health system being exacerbated by the COVID-19 pandemic, also seen historically during previous epidemics in NZ (eg, the 1918 Influenza pandemic), was repeatedly highlighted by Māori health experts even before COVID-19 was widespread in the NZ population.^{7 14} This was supported by statistical modelling early in the pandemic, which estimated that the infection fatality rate of COVID-19 would be 50% higher for Māori compared with non-Māori when age was the dominant risk factor and 2.5 times higher if underlying conditions were prioritised¹⁵ and was subsequently observed during outbreaks.¹⁶

This early identification of increased exposure to risk and severe outcomes for Māori from COVID-19 led to pre-emptive organisation and action from both Māori health and other social sector workers, and communities.^{17 18} A key focus of this work was the early establishment of Te Rōpū Whakakaupapa Urutā (the National Māori Pandemic Group)—a voluntary (and largely unpaid) coalition of health professionals to provide expert public health and clinical advice for whānau (extended family groupings), Māori health providers, community groups and iwi (Māori tribal groupings).¹⁹ Māori healthcare providers also delivered culturally safe and context-appropriate care to local Māori and wider communities and iwi organisations including Te Kahu o Taonui in Te Tai Tokerau (Northland) who used provisions under the Public Health Act (1956) to set up local roadblocks to protect their rohe (region).²⁰

When vaccines became available in NZ,²¹ Māori health experts and advocates advised the government that Māori needed to be prioritised using both Indigenous rights-based and clinical evidence-based grounds.²² However, this advice was not followed, and a prioritisation system based on older age only was implemented. This meant that despite being at higher risk given sociodemographic and clinical risk factors (independent of age), a smaller proportion of Māori were eligible for earlier vaccination than non-Māori (primarily due to the younger population age structure of Māori compared with non-Māori). This approach effectively deprioritised the Māori population for COVID-19 vaccination. This issue was further complicated by poor ethnicity data quality and the use of inappropriate data analysis methods (eg, denominator choice) that undercounted the Māori population resulting in an underestimation of the unvaccinated subgroup for Māori.²³ This failure to appropriately quantify and prioritise Māori health needs early is likely to have contributed to Māori having the lowest COVID-19 vaccination rate of all the major ethnic groupings in NZ.²⁴

In addition, inadequate contact tracing and culturally unsafe public health interventions targeting Māori whānau may have delayed vaccination for Māori. It is hypothesised that the initial failure to target Māori communities appropriately may have contributed to lower levels of Māori ‘trust’ (in what was a low trust environment prepandemic), and therefore, contributing to an environment where misinformation and disinformation about COVID-19 and vaccines were given time to flourish (and embed) across various Māori communities—further exacerbating vaccine inequities.²⁵ Without the significant input of Māori health providers and iwi/hapū-led interventions, the inequities seen in vaccine access are likely to have been much worse.²⁶ Significant funding for Māori-led models of contact tracing (eg, the Māori Regional Coordination Hub in Auckland) and Māori and iwi specific service delivery (eg, Ngāti Whātua) were implemented late into pandemic management, primarily as a result of generic service failure to manage the pandemic in so-called ‘hard to reach’ Māori communities, particularly during the Delta and Omicron waves.²⁷

Alongside lost opportunities to respond to Māori leadership and advice, the Ministry of Health declined requests to share data necessary for delivering services to undervaccinated communities.^{28 29} The government also went against the advice of Māori health experts and communities in shifting to the less rigorous COVID-19 Protection Framework while Māori vaccination rates were still lower than non-Māori, and just before the summer holiday period when large groups of holidaymakers were expected to visit areas where isolated Māori communities with limited access to health services were based.^{30 31}

The government’s actions and decisions in the design of the vaccine roll-out and the rapid shift to the COVID-19 Protection Framework were both deemed to be breaches of the principles of equity and active protection required by Te Tiriti o Waitangi (NZ’s founding constitutional agreement between the Queen of England and Māori chiefs, signed in 1840) as assessed by the Waitangi Tribunal—a permanent commission of inquiry that makes recommendations on claims brought by Māori relating to Crown actions which breach the promises made in the Te Tiriti o Waitangi.³²

Understanding: access to healthcare, quality of healthcare and health outcomes

As the causal implications of colonisation and racism are present at multiple levels of the health system, observations across the domains of access to healthcare, quality of care and health outcomes must all be considered to understand the impact of health system changes on Māori health.³³ This is particularly pertinent when implementing new population-based health interventions targeting the ‘total population’ (eg, prioritising age for vaccine access) as these interventions may lead to worsening health inequities for Māori depending on how they are designed and implemented. This study specifically explores variables associated with: whether Māori received care (ie, healthcare access); if they did receive care, what was the standard of that care and was it appropriate (ie, health quality) and what impact these factors have on health (ie, outcomes) between Māori and non-Māori?

Study design/methods

We will undertake a quantitative analysis of available national datasets that can be used to document changes in access to healthcare, quality of healthcare and health outcomes for Māori and non-Māori ‘pre and through’ the COVID-19 pandemic across NZ. This information is needed to examine the impact of the processes associated with managing COVID-19 in NZ to assist in developing healthcare policy and practice to address inequities. This information will inform government planning for appropriate health equity approaches and policies for future pandemic management, and other large-scale events that may impact on the health system such as natural disasters. Through the dissemination of research findings, this project will support communities, iwi/hapū organisations and/or health providers by providing them with evidence to inform local action and support future research potential. In addition, the project is centred on Māori health gain and the elimination of inequities, aligning with Kaupapa Māori theory and practice and Te Tiriti o Waitangi principles of equity and active protection.³⁴ The M2M study will be conducted between February 2024 and September 2025.

Hypotheses

1. Inequities in health between Māori and non-Māori will be identified in the ‘pre’ COVID-19 period (2015–2019). This reflects the significant evidence to date of Māori health inequities in NZ.^17–19

2. Inequities in non-COVID-19-related health and healthcare will increase between the ‘pre’ and ‘through’ COVID-19 periods across NZ (without the vaccine (2020) and with the vaccine 2021 onwards).

3. Variations in pandemic impacts and management regionally and/or between district health boards (DHBs, regional funder and provider of health services) may result in variations in the changes observed between the ‘pre’ and ‘through’ periods for Māori:non-Māori health inequities.

Objectives

1. To report on access to healthcare, quality of healthcare and health outcomes between Māori and non-Māori ‘pre’ and ‘through’ COVID-19 across NZ.

2. To examine regional differences in access to healthcare, quality of healthcare and health outcomes between Māori and non-Māori across DHBs during the COVID-19 outbreak in NZ.

3. To highlight areas requiring health policy and practice interventions to address Māori inequities in health resulting from COVID-19 (historically and in the future).

Kaupapa Māori research positioning

This study is framed within a Kaupapa Māori research positioning that includes Kaupapa Māori epidemiology. As noted by Simmonds et al, a Kaupapa Māori epidemiological research positioning ‘centralises the needs and aspirations of Māori in research and provides a theoretical basis that is Māori initiated, defined and controlled’ p.3.³⁵ This approach acknowledges that traditional epidemiological methods have often served the interests of numerically dominant populations rather than those of Indigenous peoples. Therefore, it is important to incorporate quantitative methods that can be responsive to the demographic circumstances of the Māori population and maximise the breadth and depth of statistical analyses for Māori to at least the same level as non-Māori.^{35 36} Within a critical Kaupapa Māori positioning, comparing Māori to non-Māori is intended to highlight societal inequities and issues associated with the impact of colonisation (both historical and contemporary) such as power, privilege and racism that underlie Māori health inequities and aligns with Māori rights to monitor the Crown.

As it is consistent with common principles of Kaupapa Māori-based research, this study is Māori-led by senior Māori researchers and is made up of predominantly Māori research and public health expertise.^{37 38} The study has an explicit commitment to develop emerging Māori health researchers to undertake research framed from a Kaupapa Māori positioning, as well as supporting an emerging non-Māori researcher to undertake research that is consistent with Kaupapa Māori principles. The specific principles of this study align with the need for the research to be transformative, beneficial to Māori, under Māori control, informed by mātauranga Māori and aligned with a ‘structural determinants’ approach to critique issues of power, privilege and racism.^{39 40} This research is intended to be emancipatory for Māori, supportive of decolonisation, accepting of diverse Māori realities and consistent with social justice framing that rejects cultural essentialism, victim-blaming and cultural-deficit theorisation.³⁹

Ethics and dissemination

This study has ethical approval from the Auckland Health Research Ethics Committee (AHREC AH26253). We will share our project findings via multiple platforms designed to reach academic, policy and Māori community audiences. An advisory group will work with the project team to disseminate the findings of this project. Key activities will include project branding with regional hui (meetings) to present our findings, a project-specific website inclusive of a community data interface application (to increase potential future use of the data gathered) and a commitment to open access publication of research outputs in peer-reviewed journals.

Patient and public involvement

Patients or the public were not involved in the design of the study.

Conceptual framework

The conceptual framework for the M2M study is presented in figure 1.

Figure 1.

Conceptual plan for the M2M project that has guided study development. BAU, business as usual; M:nM, Māori versus non-Māori; M2M, Mā te Mōhio ka Mārama: Impact of COVID-19 on Māori:non-Māori inequities.

We acknowledge that it may be possible to identify health conditions where inequities are reduced if the actions taken during the shutdown and/or restart-up periods of health services prioritised Māori access, quality and outcomes. If this is found, valuable insights into the health policy and practice interventions that allow for proequity, Tiriti compliant pandemic management may be identified. Regardless, we expect that comprehensively measuring the patterns of inequity between ‘pre’ and ‘through’ COVID-19 periods is a vital activity required to better understand the inequities that should be prioritised and how to potentially avoid inequities worsening during future pandemic outbreaks.

Study periods

Generally, the COVID-19 pandemic in NZ’s context can be understood as having three major time periods:

• Prepandemic period (2015–2019).

• First pandemic year without COVID-19 vaccines (2020).

• Pandemic period with COVID-19 vaccines (2021 onwards).

Data will initially be categorised into 3-month periods (quarters) to allow for detailed time period analyses. We are aware that the application of a single timeline (and the assumption that all ethnic groups within NZ experienced the timeline in the same way) may not be appropriate given variations in how COVID-19 management decisions impacted Māori and non-Māori communities across NZ. The concept of a Māori specific timeline of COVID-19 that potentially differs from non-Māori (eg, in terms of vaccine access/uptake, lockdown exposure, community responsiveness) will be explored within the project specifically. This may influence the time periods outlined above and how they are used for comparisons between Māori and non-Māori.

Research focus areas

We have chosen to focus the ‘first wave’ of our analysis on domains of health that align with the health system priorities outlined by NZ’s Māori Health Authority (Te Aka Whai Ora)⁴¹ as areas that are currently of high importance to improve Māori health. Therefore, the first wave of themes included in the M2M project are mortality, access to the healthcare system, cancer, long-term conditions with a focus on diabetes, first 1000 days and mental health. Within these focus areas, we have identified outcome indicators, which will be confirmed depending on data availability and quality. Rheumatic fever testing is included in a potential ‘second wave’ of focus as it sits outside of the Te Aka Whai Ora priorities but there have been specific issues raised about the impact of COVID-19 testing processes on throat swabs for rheumatic fever in particular.⁴² This is particularly relevant for Māori communities who experience 11.8 times higher rates of initial acute rhemuatic fever hospitalisations and 3.2 times higher rates of initial rheumatic heart disease hospitalisations when compared with those in the European/other ethnicity grouping.⁴³

Data sources

Table 1 summarises the relationship between the focus areas included in the M2M project and the data sources that are planned for inclusion in our analyses. The project encompasses multiple national datasets to provide a multifaceted overview of the change to Māori health equity during the pandemic. The source and purpose of these datasets as well as the methods through which ethnicity data are collected are summarised in table 2. The data quality characteristics of each dataset is an important consideration as missing or inaccurate ethnicity has been found to undercount the Māori population which may lead to an underestimation of differences between Māori and non-Māori.^{23 44} This is discussed further in the ‘Ethnicity data and categorisation’ section of this paper.

Table 1.

Relationship between the themes included in the M2M project and the data sources that are planned for inclusion in our analyses

Prioritisation	Theme	Indicative outcome variables*	Main source dataset
First wave	Mortality	All-cause mortality	National Health Index
	Access to the healthcare system: ED, avoidable hospitalisation	Avoidable hospitalisation length of stay ED presentations GP access no of times accessed experience of barriers	National Minimum Dataset National Non-Admitted Patient Collection New Zealand Health Survey
	Cancer	Screening Specialist appointment Cancer diagnosis Operations public (June 2022) private (Dec 2020)	Bowel Screening Register National Non-Admitted Patient Collection New Zealand Cancer Registry
	Long term conditions with a focus on diabetes	HbA1c testing Gestational diabetes screening Retinal screening Hospital admission Outpatient data	Virtual Diabetes Register Lab Claims Collection National Minimum Dataset
	First 1000 days	Antenatal blood testing Newborn screening Birth weight Child immunisations	Lab Claims Collection National Maternity Collection
	Mental health	Hospital admission K10 questionnaire Use of a mental health helpline Counselling Prescribed medication Alternative/complementary therapies	National Minimum Dataset New Zealand Health Survey
Second wave	Rheumatic fever	Throat swab testing New cases ED presentation Hospital admission	Lab Claims Collection National Minimum Dataset National Non-Admitted Patient Collection

*Dependant on data quality and availability.

ED, emergency department; GP, general practice; HbA1c, glycated haemoglobin; M2M, Mā te Mōhio ka Mārama: Impact of COVID-19 on Māori:non-Māori inequities.

Table 2.

Characteristics of the datasets used in M2M analyses

Dataset	Source organisation	Purpose of dataset	Method of ethnicity data collection
National Health Index (NHI)	Te Whatu Ora Health New Zealand	Unique encrypted identifier for every person who uses the healthcare system in NZ	From healthcare providers
National Minimum Dataset	Te Whatu Ora Health New Zealand	National collection of public and private hospital discharge information including clinical data	Uses NHI
National Non-Admitted Patient Collection	Te Whatu Ora Health New Zealand	Information on outpatient and emergency department patient activity	Uses NHI
New Zealand Health Survey	Ministry of Health	Continuous survey on the health and well-being of the NZ population and is reported annually	Self-identified
Bowel Screening Register	Ministry of Health	Database of those registered in NZ’s national bowel screening programme
New Zealand Cancer Registry	Te Whatu Ora Health New Zealand	Register of all primary malignant diseases in NZ	Uses NHI
Lab Claims Collection	Te Whatu Ora Health New Zealand	Claims and funding information for community-based laboratory testing	Uses NHI
Virtual Diabetes register	Te Whatu Ora Health New Zealand	Data about people suspected as having diabetes, identified through their use of diabetes-related health services that is used to release annual diabetes incidence estimates
National Maternity Collection	Te Whatu Ora Health New Zealand	Information about selected publicly funded maternity services up to 9 months before and 3 months after a birth	Uses NHI
National Immunisation Register	Te Whatu Ora Health New Zealand	Immunisation details for NZ children	Uses NHI

M2M, Mā te Mōhio ka Mārama: Impact of COVID-19 on Māori:non-Māori inequities; NZ, New Zealand.

Data management and governance

As it is consistent with our Kaupapa Māori positioning, we are committed to ensuring that any M2M data are managed in a safe and appropriate manner. The investigators agree to keep any collected data in strict confidence and to use data only for the purposes specified by the M2M project. The project members will not distribute, disclose or reveal individually or group identifiable data for any reason whatsoever, to any outside party. All data and documentation will be stored in a secure environment protected from access by any unauthorised person(s) and ethical guidelines will be followed in the use of any data. M2M-specific project guidelines will be developed and ethical approval has been obtained for the project. The principal investigator will have ultimate responsibility for the management of any data associated with the project. Project governance, which will include approval for data management plans, will occur via a project advisory group that will be convened to meet once per year at a minimum. Overall, our critical Kaupapa Māori positioning is aligned to Māori data sovereignty principles that focus on Māori control of Māori data, production of evidence to support rangatiratanga and an interrogation of inequities from a place of manaakitanga towards Māori and other oppressed communities.⁴⁵

Data analysis

The Kaupapa Māori research positioning of our study necessitates analytic approaches that will uphold our commitment to produce useful outcomes for Māori. The first stage of the analysis for each theme will be to summarise the demographic profile of the NZ population by age group (5-year or 10-year groupings depending on data), gender, NZ Deprivation Index (NZDEP decile/quintile), Geographic Classification for Health,⁴⁶ DHB, and outcomes of interest at each COVID-19 time period for Māori and non-Māori.

Continuous variables will be presented as numbers of observed and missing values, mean, SD, median and IQR, as appropriate. Categorical variables will be presented as frequencies and percentages. Crude and, if appropriate, age-standardised/sex-standardised or adjusted incidence rates will be calculated on binary outcomes (eg, mortality) and compared between Māori and non-Māori using the estimated incidence rate ratios. In line with our Kaupapa Māori positioning, the Māori 2001 Standard⁴⁷ will be used for age standardisation. Using this standard will emphasise events which are more common in the age groups represented by the Māori population, rather than the non-Māori population.⁴⁵ Generalised linear regression models will be used to test the differences in key study outcomes between ethnic groups and any significant change over the study period. The construction of the regression models, and selection of important confounders, will be based on our conceptual framework and prior knowledge of the drivers of ethnic inequities in health ‘pre’ and ‘through’ the COVID-19 pandemic. Ethnic-specific estimates on each outcome will be presented as the mean difference for continuous variables, and absolute risk difference, relative risk or OR for categorical variables, with associated 95% CIs and p values. Results will be compared between study periods to explore for any changes in inequities over time considering any regional outbreaks and potential wider community spread as appropriate. A full statistical analysis plan will be developed at the start of the proposed study and reviewed by the research team on receipt of data from the different data sources, to guide the final data analysis. All study data will be stored securely in accordance with data access agreements and maintained in confidence using encrypted National Health Index (NHI). Data analysis will be conducted by using SAS V.9.4 (SAS Institute). All statistical tests will be two sided at the significance level of p=0.05.

Ethnicity data and categorisation

The ‘quality, consistency and completeness’ of ethnicity data has been identified as a key requirement for identifying and monitoring progress on eliminating health inequities for Māori.⁴⁸ As this project is based on secondary analyses of datasets managed by governmental agencies such as Te Whatu Ora (Health New Zealand), there are some inherent limits to the quality of the data. These limitations will be considered and their potential impact on the accuracy and reliability of the project’s findings will be presented alongside each specific analysis.

Denominator selection is a significant consideration when observing and reporting population-level Māori health data. Understanding changes over time is key to monitoring the health system’s performance for Māori and will be considered in the choice of denominator. For example, time series over the period of interest is not possible with more recently created denominators such as the Health Service Utilisation (HSU), a population of health service users.⁴⁹

Systematic undercounting of Māori in routinely used health datasets is a known factor, which limits the accuracy of estimates of frequencies, prevalence, rates and quantifying and monitoring inequities over time.²³ Specifically, health datasets including the NHI and HSU datasets under-represent Māori when compared with the Estimated Resident Population (ERP).²³ These data limitations will be considered in the interpretation of findings.

The M2M project will use ERP derived from data collected in the NZ Census as the main denominator but may use the HSU population in selected analyses to compare the quality of data generated by these different denominators. The intention of this comparison is to contribute to information available about the methods which produce the highest quality Māori health data analyses.

As the aim of the M2M project is to examine Māori health measures within an Indigenous rights-based positioning that aligns with Te Tiriti o Waitangi requirements, the primary ethnicity categorisation will be Māori versus non-Māori.⁴⁵

Discussion

The M2M project explores the impact of COVID-19 pandemic management on Māori:non-Māori inequities in health at both a nationwide and regional level across NZ. We already know that the COVID-19 pandemic increased Māori heath inequities with higher mortality and morbidity from COVID-19 infection and complications compared with non-Māori. What is less well known is the indirect impacts of pandemic management on non-COVID-19-related health inequities for Māori compared with non-Māori within a NZ context. This study will use nationally available datasets to explore whether inequities in access to healthcare, quality of healthcare and health outcomes have been observed between Māori and non-Māori throughout different stages of the COVID-19 pandemic, and explicitly considering health inequities that existed prior to the pandemic.

We expect this study to positively contribute to the growing evidence base utilising Indigenous research positioning for epidemiological analysis. Holding governments to account for policy-making decisions that can alleviate or exacerbate Indigenous health inequities, particularly during contexts of crisis as seen with the COVID-19 pandemic, remains an important public health activity required to respond to the rights of Indigenous peoples worldwide.

Ethics statements

Patient consent for publication

Not applicable.