Land-Use and Bakin Birji Pond Dynamics in Relation to Climate Variability and Malaria Seasonality in Zinder Region, Niger
Current Journal of Applied Science and Technology·
- DOI
- 10.9734/cjast/2026/v45i94751
- PMID
- —
- PMCID
- —
- OpenAlex
- —
- Study type
- Journal article
- Publisher
- Sciencedomain International
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The article provides local context on hydro-landscape change, climate measures, and seasonal malaria counts in one Nigerien setting. It identifies a need for finer environmental monitoring and longer, population-standardised malaria time series to evaluate temporal and causal relationships.
Structured evidence summary
Research question
The study assessed long-term changes in land use and the Bakin Birji pond alongside seasonal malaria patterns, and explored associations between monthly climate measures and confirmed malaria counts in Zinder Region, Niger.
Study design
This was an observational analysis combining Landsat-derived land-use maps from 1993, 2008, and 2023, NASA POWER climate data from 1993-2022, and monthly rapid-diagnostic-test-confirmed malaria counts from 2019-2022. Pearson and Spearman correlations were used as exploratory association measures.
Population and setting
The setting was semi-arid Zinder Region, Niger, with malaria records from the Bakin Birji Integrated Health Centre. The abstract does not provide population characteristics or a population denominator.
Main findings
From 1993 to 2023, pond and built-up areas increased while vegetated area declined. Malaria counts were highest in September and October after the main August rainfall peak; climate associations varied by variable and correlation method. The study states that mismatched temporal resolution prevents direct causal attribution of malaria patterns to pond expansion.
Public-health relevance
The article provides local context on hydro-landscape change, climate measures, and seasonal malaria counts in one Nigerien setting. It identifies a need for finer environmental monitoring and longer, population-standardised malaria time series to evaluate temporal and causal relationships.
Important limitations
The study explicitly reports that the pond and malaria datasets have different temporal resolutions, preventing direct causal attribution, and calls for finer-resolution monitoring and longer population-standardised malaria time series. This summary is also limited to the supplied single-article abstract and metadata; the original paper is required for decision-grade interpretation.
GIDS interpretation
The article is discoverable under malaria, Niger, and climate-and-environment topics and may provide contextual background for editorial review. It does not establish or confirm any live surveillance signal.
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 7 auditable classifier relationships to diseases, places, topics, and study design.