Environmental change increases the transmission risk of visceral leishmaniasis in central China around the Taihang mountains

Environmental Health, Journal Year: 2025, Volume and Issue: 24(1)

Published: May 4, 2025

Visceral leishmaniasis is a neglected life-threatening sandfly-borne disease, which brings growing public health threat in Central China around the Taihang Mountains. However, spatiotemporal dynamics of visceral local community and potential driving factors remain poorly understood. We analyzed patterns new reported cases region from 2006 to 2023, combined random forest modeling approach with environmental covariates identify main influencing related transmission risk disease. Our results show that there was total number 800 human cases, affecting 29 cities, 113 counties across region, exhibiting geographic expansion disease during this period, especially Shanxi province. Two high-risk clusters were identified study. Environmental change-related factors, including standardized precipitation deviation, cumulative change ratio, normalized difference vegetation index (NDVI) change, played important roles increasing leishmaniasis, their relative contributions summing up 66.17%. findings provide better understanding recurrence Mountains, underscore prevention control measures should be taken immediately reduce risk.

Language: Английский

Evaluating the Spatial Relationships Between Tree Cover and Regional Temperature and Precipitation of the Yucatán Peninsula Applying Spatial Autoregressive Models

Land, Journal Year: 2025, Volume and Issue: 14(5), P. 943 - 943

Published: April 26, 2025

Deforestation and forest degradation are important drivers of global warming, yet their implications on regional temperature precipitation patterns more elusive. In the Yucatán Peninsula, cover loss deterioration has been rapidly advancing over past decades. We applied local indicators spatial association (LISA) cluster analysis autoregressive models (SAR) to evaluate relationships between tree precipitation. integrated NASA’s Global Forest Cover Change (GFCC) WorldClim’s historical monthly weather datasets (2000–2015) assess effects deforested, degraded, dense land distributions Peninsula. LISA analyses show warmer drier conditions geographically coincide with deforested degraded cover, but outliers allude potential influence impacts climate. Controlling dependencies including covariates, SAR indicate that deforestation is associated higher annual mean temperatures minimum during dry wet seasons, decreased in season. Degraded was related maximum did not relate variability. highlight complex interactions climate emphasize importance conservation for mitigating change.

Language: Английский