Resurgence of rheumatic fever among Pacific peoples in Aotearoa New Zealand: A 2010–2023 analysis of hospitalisation data with implications for equity policy
Australian and New Zealand Journal of Public Health·
- DOI
- 10.1016/j.anzjph.2025.100301
- PMID
- 41447834
- PMCID
- —
- OpenAlex
- W7117144997
- Study type
- Journal article
- Publisher
- Elsevier BV
- Article type
- journal-article
- Integrity
- current
Why this research matters now
Addressing persistent disparities requires improved monitoring infrastructure and targeted resource allocation to achieve established national health objectives.
Structured evidence summary
Research question
The analysis investigates how ethnicity, residential location, and economic disadvantage shape admission rates for acute rheumatic fever and rheumatic heart disease across New Zealand over a thirteen-year period, while evaluating existing prevention strategies.
Study design
Researchers conducted a retrospective evaluation of nationwide hospital and mortality records, applying statistical modeling to compare incidence shifts across distinct demographic and temporal segments.
Population and setting
The dataset encompasses the entire country, with particular emphasis on Indigenous and Pacific communities residing in highly disadvantaged urban zones such as Counties Manukau.
Main findings
Hospital admissions were heavily concentrated among marginalized ethnic groups in impoverished neighborhoods. Case counts decreased for one demographic during a designated prevention initiative, whereas another demographic showed no corresponding reduction. Admission rates experienced a brief decline during a period of widespread public health restrictions, followed by a rapid increase by the final year of observation.
Public-health relevance
Addressing persistent disparities requires improved monitoring infrastructure and targeted resource allocation to achieve established national health objectives.
Important limitations
The exclusive reliance on hospital admission records limits capture of community-managed cases, while variable reporting standards and fragmented program delivery may influence observed trend accuracy.
GIDS interpretation
This publication establishes a historical baseline regarding disease distribution and policy effectiveness within a defined healthcare jurisdiction, supporting contextual understanding for future observational tracking without suggesting active outbreak detection.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 12 auditable classifier relationships to diseases, places, topics, and study design.