Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1075
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3195
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Spotted fever rickettsioses are tick-borne diseases of major epidemiological importance worldwide. Ticks can interact pathogenically with humans through endemic foci or sporadic epidemic outbreaks. Novel analytical tools and decision-making frameworks for tick-borne disease surveillance may improve resource allocation and enhance the response capacity of public health services. In this study, we characterize and model the bioclimatic suitability of three tick species-Amblyomma aureolatum, A. ovale, and A. sculptum-across Brazil. The climatic niche of each species was quantified using four modelling algorithms (BIOCLIM, GLM, Maxent, and SVM) implemented within an automated modelling workflow (modleR). A total of 585 occurrence records were retained for modelling: 55 for A. aureolatum, 120 for A. ovale, and 410 for A. sculptum, covering the entire Brazilian territory. Amblyomma sculptum exhibited a broader tolerance to temperature and precipitation variability, suggesting a wider potential distribution range compared to the other two species. This species was primarily associated with grassland habitats, such as those in the Cerrado biome. In contrast, A. aureolatum and A. ovale were more strongly associated with forested areas, particularly along the Atlantic Forest coastal region. The modelling outputs presented here provide valuable insights to support targeted health surveillance and intervention strategies for tick-borne diseases in Brazil.
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http://dx.doi.org/10.12834/VetIt.3701.34484.2 | DOI Listing |