Modelling testing and response strategies for COVID-19 outbreaks in remote Australian Aboriginal communities
BMC Infectious Diseases·
- DOI
- 10.1186/s12879-021-06607-5
- PMID
- —
- PMCID
- —
- OpenAlex
- W3197435733
- Study type
- Journal article
- Publisher
- Springer Science and Business Media LLC
- Article type
- journal-article
- Integrity
- current
Publication version
This article has a linked preprint
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Open linked preprint →Why this research matters now
The paper is relevant to planning outbreak response in remote communities with shared-household contact patterns. It describes how response timing, quarantine breadth, testing, and adherence may affect containment in the modeled setting.
Structured evidence summary
Research question
The article asks which testing, contact quarantine, and lockdown approaches would be most effective for controlling a COVID-19 outbreak in remote Australian Aboriginal communities.
Study design
This is an individual-based simulation study modeling SARS-CoV-2 spread under different response strategies. It compares multiple outbreak-control scenarios after a case is introduced.
Population and setting
The modeled setting is remote Australian Aboriginal and Torres Strait Islander communities, including communities of roughly 100 to 3,500 people. The model represents large, interconnected households.
Main findings
The abstract reports that secondary spread is often already underway by the time the first case is detected. Quarantining extended-household contacts, adding exit testing, and placing non-quarantined households under a 14-day lockdown were reported to reduce outbreak size in the modeled scenarios; the model also indicates that high compliance is necessary for control.
Public-health relevance
The paper is relevant to planning outbreak response in remote communities with shared-household contact patterns. It describes how response timing, quarantine breadth, testing, and adherence may affect containment in the modeled setting.
Important limitations
The abstract does not provide formal limitations, so interpretation is limited to the supplied single-article abstract and metadata. Because the evidence comes from a simulation model, the reported effects depend on the model structure and scenario assumptions, and the original paper is needed for decision-grade interpretation.
GIDS interpretation
For GIDS indexing, this article is discoverable as a modeling study about COVID-19 outbreak response in remote Aboriginal communities. It provides contextual evidence on response strategies rather than live surveillance confirmation.
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 8 auditable classifier relationships to diseases, places, topics, and study design.