Modelling the impact of interventions on imported, introduced and indigenous malaria infections in Zanzibar, Tanzania
Nature Communications·
- DOI
- 10.1038/s41467-023-38379-8
- PMID
- 37173317
- PMCID
- PMC10182017
- OpenAlex
- W4376273493
- Study type
- Journal article
- Publisher
- Springer Science and Business Media LLC
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The findings inform malaria elimination strategy in low-transmission settings with case importation, demonstrating that local transmission remains the primary driver of cases and that coordinated regional intervention is necessary for elimination.
Structured evidence summary
Research question
The study examines how different intervention strategies affect imported, introduced, and indigenous malaria cases in Zanzibar, Tanzania, a low-transmission setting with ongoing case importation.
Study design
A stochastic metapopulation model was developed to distinguish between imported, introduced, and indigenous malaria cases. The model was parameterized using human movement data and malaria prevalence data from Zanzibar and tested scenarios including increased coverage of reactive case detection, reactive drug administration, treatment of infected travelers, and transmission reduction in both Zanzibar and mainland Tanzania.
Population and setting
The study focuses on Zanzibar, Tanzania, a low malaria transmission setting with high case importation rates from mainland Tanzania.
Main findings
Most new cases on both major islands of Zanzibar are indigenous rather than imported, despite high importation rates. Intervention combinations that increase infections treated through reactive case detection or reactive drug administration can substantially reduce malaria incidence. However, elimination within 40 years requires transmission reduction in both Zanzibar and mainland Tanzania.
Public-health relevance
The findings inform malaria elimination strategy in low-transmission settings with case importation, demonstrating that local transmission remains the primary driver of cases and that coordinated regional intervention is necessary for elimination.
Important limitations
This summary relies on the supplied single-article abstract and metadata. The full paper is required for decision-grade interpretation of model assumptions, parameter uncertainty, sensitivity analyses, and generalizability to other settings.
GIDS interpretation
The article was classified for malaria in Tanzania with topics including transmission dynamics, treatment, and climate/environment. It addresses intervention modeling relevant to elimination programs in settings with cross-border transmission, providing context for understanding case classification and intervention impact in low-transmission areas.
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.