Determining the spatial distribution of environmental and socio-economic suitability for human leptospirosis in the face of limited epidemiological data
Infectious Diseases of Poverty·
- DOI
- 10.1186/s40249-022-01010-x
- PMID
- 35927739
- PMCID
- PMC9351081
- OpenAlex
- W4289755205
- Study type
- Journal article
- Publisher
- Springer Science and Business Media LLC
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The approach offers a baseline for planning intervention measures in settings where leptospirosis is underreported and misdiagnosed. The methodology is designed to be evolutive and can incorporate new evidence as studies and data on disease determinants become available.
Structured evidence summary
Research question
The study aimed to identify spatial patterns of environmental and socioeconomic suitability for human leptospirosis in the urban agglomeration of Santa Fe, Argentina, where accurate epidemiological data are limited.
Study design
The authors used a knowledge-based index constructed with the Zonation algorithm and cluster analysis to map suitability for leptospirosis. They geocoded surveillance cases from 2010 to 2019 and integrated environmental data from satellite imagery with socioeconomic data from public platforms.
Population and setting
The study focused on the urban agglomeration of Santa Fe, Argentina, examining human leptospirosis cases reported to the national surveillance system between 2010 and 2019.
Main findings
Suitability for human leptospirosis increased from downtown areas toward peri-urban and suburban zones. Downtown areas had higher socioeconomic conditions, while peri-urban and suburban areas formed two clusters distinguished by environmental determinants. The highest disease incidence overlapped with the highest suitability scores, though the association was weak (CSc r = 0.21, P < 0.001).
Public-health relevance
The approach offers a baseline for planning intervention measures in settings where leptospirosis is underreported and misdiagnosed. The methodology is designed to be evolutive and can incorporate new evidence as studies and data on disease determinants become available.
Important limitations
Only 56.36% of reported human leptospirosis cases could be geocoded. The correlation between suitability scores and observed incidence was low. This summary relies on the supplied single-article abstract and metadata; the original paper is required for decision-grade interpretation.
GIDS interpretation
The classifier links associate this paper with leptospirosis, climate and environment, One Health, and surveillance topics. These links aid discoverability for researchers and decision-makers interested in spatial epidemiology and knowledge-based approaches to disease mapping in data-limited contexts.
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 6 auditable classifier relationships to diseases, places, topics, and study design.