BACKGROUND: The working population is exposed daily to unavoidable climatic conditions due to their occupational settings. Effects of the weather such as rain, heat, and air pollution may increase the risk of diseases, injuries, accidents, and even death during labor. OBJECTIVE: This paper aims to summarize the impacts of climate change on workers’ health, safety and performance, identifying the risks, affected workplaces and the range of methodological approaches used to assess this problem. METHODS: A thorough systematic mapping was conducted in seven scientific international databases: Emerald, IEEE Xplore, Science Direct, Scielo, Scopus, SpringerLink, and Web of Science. Three research questions guided the extraction process resulting in 170 articles regarding the impacts of climate change on occupational health and safety. RESULTS: We found an accentuated trend in observational studies applying primary and secondary data collection. Many studies focused on the association between rising temperatures and occupational hazards, mainly in outdoor work settings such as agriculture. The variation of temperature was the most investigated impact of climate change. CONCLUSIONS: We established a knowledge base on how to explore the impacts of climate change on workers’ well-being and health. Researchers and policymakers benefit from this review, which explores the suitable methods found in the literature and highlights the most recurring risks and their consequences to occupational health and safety.

Representing financial costs and productivity penalties, work accidents and occupational diseases generate concerns in organizations in a global sphere. Although strategies to reduce or eliminate occupational risks and measures of prevention are being increasingly developed worldwide, accidents remain very frequent (Alli, 2008). According to the Yearbook of Social Security Statistical, in 2018 approximately 235 thousand accidental benefits were granted, including pension for death, sickness, and accident assistance, representing a cost of R$ 366,723.00 (Brasil, 2018). Also, between 2012 and 2018, a total of 351,796,758 working days were lost due to work leave, this number takes into account every work leave that happened across the country even if it happened simultaneously, according to the Digital Observatory on Occupational Health and Safety (2018). International standards, such as ISO 45000, offer guidelines for the standardization of the organization's Occupational Health and Safety Management System (OHSMS), defining criteria, policies and objectives to be followed, however, for these safety measures to be effective, companies need to maintain control over them (Almeida & Nunes, 2014; International Organization for Standardization, 2018).

Workers may be exposed to conditions that put their physical and mental integrity at risk, from workplace settings to climate characteristics. Heat stress is a harmful health condition caused by exceeding the human body’s tolerance limits, leading to illness and increasing the chance of work accidents. Heat stress indexes, such as the Humidex and the Heat Index (HI), are used to measure these impacts. These indexes are significant as they provide a quantitative measure of the heat stress experienced by workers, taking into account both environmental and individual factors. Objective: This study aims to compare multiple heat stress indexes, relating them to historical Brazilian occupational accident data. Methods: We selected eight indexes and applied multiple correspondence analysis to each one, a statistical method that generates graphs to visualize the association between variables in a database. Results: The analysis and comparison of the graphs indicated that seven of the eight indexes presented similar behavior. It was also possible to relate ranges of index values with specific characteristics of the accidents. Conclusions: The technique allowed us to analyze the relationship between climate and work accidents and showed that the choice of the heat stress index does not significantly alter the results for most indexes studied.

Occupational accidents can be potentialized by factors related to the workplace or the environment, such as climatic conditions. Air temperature, wind speed, and humidity can be used to monitor occupational heat stress, leading to cramps, exhaustion, stroke, and even death. Under the climate change scenario, measuring these variables is fundamental to developing adaptation strategies for maintaining the workers’ well-being. However, when dealing with this high data volume from distinctive factors, traditional techniques are insufficient to extract all information effectively. Therefore, computational intelligence and data analytics tools can enhance data processing and analysis. Machine learning techniques have been successfully applied to occupational health and climate contexts. This paper explores the literature regarding applying these techniques to investigate the effects of climate change on occupational health. We conducted a systematic review through five scientific databases guided by three research questions, resulting in 24 selected papers. 75% of the papers screened used primary data collected from wearable sensors to monitor the well-being of workers, where we identified a trend of using supervised machine learning techniques, especially classification and regression algorithms, such as SVM, RF, and KNN. The remaining focus is on using secondary data from national databases to investigate the risk, with a trend of using feature selection techniques and classification tasks. Considering this topic is relatively new, we developed an agenda to guide future research, with suggestions to follow the trends found in this review and highlight the potential of expanding to multiple future research paths.

The School Bus Routing Problem (SBRP) is widely discussed in the operations research literature and can be solved by several exact methods and heuristics. This problem seeks to designate the most efficient routes for a fleet of school buses, minimizing the total distance covered and considering variables such as bus stop locations, number of passengers, and the assigned destination for each of them. This study aims at solving a real case SBRP of a small-sized county located in the state of Paraná. The proposed method is based on the Capacitated Vehicle Routing Problem (CVRP) and Travelling Salesman Problem (TSP) combined with a heuristic correction that guarantees sequence constraints, in which the student has to be collected before visiting their destination school. It was possible to obtain two routes of 30.76 km and 17.42 km respectively and both with the total vehicles’ capacity of 24 students, which corresponds to the reduction of about 10% in the daily distance covered by two buses.