Human occupation, not forest structure, determines sand fly abundance in the Amazon.

BACKGROUND

Across Amazonian deforestation frontiers, phlebotomine sand flies transmit Leishmania spp., the causative agents of American cutaneous leishmaniasis (ACL). Landscape modification can alter vector ecology and transmission risk, yet the relative roles of forest cover, landscape configuration, and deforestation timeline remain poorly understood. We evaluated how landscape composition and configuration, assessed across multiple spatial scales, and deforestation timeline influence sand fly abundance and Leishmania infection in Cruzeiro do Sul, Acre, Brazil.

METHODS

Sand flies were collected at 20 study sites during two cross-sectional surveys conducted in 2022 and 2024. Landscape metrics, including forest cover and edge density, were quantified within circular buffers of 3, 5, and 7 km2 around each site. Deforestation timeline, defined as time since initial forest loss, was used as a proxy for the duration of human occupation. Associations with sand fly abundance and Leishmania infection were assessed using Bayesian regression models, applying negative binomial models for abundance and binomial models for infection probability. Infection was detected using quantitative polymerase chain reaction (PCR) and confirmed by Sanger sequencing.

RESULTS

Forest cover and edge density, across all spatial scales, were not associated with sand fly abundance or Leishmania infection. In contrast, longer deforestation timelines were consistently associated with higher sand fly abundance, driven largely by increased captures of the sand fly species Nyssomyia antunesi. No landscape variable showed a clear association with infection occurrence.

CONCLUSIONS

Sand fly abundance in this Amazonian frontier was associated with the duration of human occupation rather than with current forest structure. These findings suggest that vector populations can persist in human-modified landscapes and highlight the importance of incorporating deforestation timeline into ACL surveillance and risk assessment.