Objective: This study aimed to assess the prevalence of respiratory symptoms among informal waste pickers in Colombia and identify the contributing demographic, environmental, and occupational risk factors. Methods: A cross-sectional study was conducted with 179 informal waste pickers from four Colombian cities. Respiratory symptoms and demographic data were collected through questionnaires. Statistical methods including logistic regression, principal component analysis (PCA), Random Forest modelling, and K-means clustering were applied to identify predictors and patterns related to respiratory health. Results: The most frequently reported symptoms were cough (46.8%), phlegm (18.4%), and shortness of breath (19.6%). Logistic regression identified age as a significant predictor of respiratory symptoms, while Random Forest analysis highlighted cough as the strongest predictor, followed by age, race, and education level. K-means clustering revealed three groups, with older workers showing the highest prevalence of symptoms. PCA indicated that respiratory symptoms and demographic factors explained significant variance in health outcomes. Conclusions: Informal waste pickers in Colombia are at elevated risk for respiratory health issues, particularly older workers exposed to prolonged occupational hazards. Targeted interventions, including improved use of protective measures and policies addressing informal work conditions, are needed to mitigate these risks and improve workers’ health and safety.

A source-traceable computational implementation of the ERBio method for occupational biological risk assessment. It provides deterministic risk calculation, versioned questionnaires, a scientifically audited regulatory biological-agent registry, workplace-level assessment, preventive planning outputs, bilingual Spanish-English functionality and reproducible reports. The software preserves a single language-neutral calculation core and keeps method-faithful components distinct from explicit computational extensions. The underlying ERBio method was developed by Aguilar-Elena and is described in Aguilar-Elena (2015) .

Provides a unified toolkit for occupational chemical exposure risk assessment, implementing three internationally recognised methods end to end: the qualitative control-banding methods COSHH Essentials (UK Health and Safety Executive) and the method of the French National Research and Safety Institute (INRS), together with the quantitative statistical procedure of the UNE-EN 689 standard for comparing measured exposure levels against occupational exposure limits. Every step of each method, from hazard banding and exposure scoring to lognormal or normal distribution fitting, one-sided tolerance limits, and monitoring-interval recommendations, is implemented as a small, independently callable, and unit-tested function, so assessments are reproducible and auditable without depending on any graphical interface. Optional 'shiny' applications provide a guided, interactive workflow for occupational hygienists and health and safety practitioners who prefer not to write code. References: UK Health and Safety Executive (2003) ; Mallet, Pilorget and Berne (2013, ISBN:978-2-7389-2166-2) "Evaluation du risque chimique" INRS ED 6084; European Committee for Standardisation (2018) .