Physiological impacts on construction workers under extremely hot and humid weather

High Bacterial Contamination Load of Self-Service Facilities in Sakaka City, Aljouf, Saudi Arabia, with Reduced Sensitivity to Some Antimicrobials

Although self-service facilities (SSFs) have been used on a large scale worldwide, they can be easily contaminated by microorganisms from the hands of their sequential users. This research aimed to study the prevalence and antimicrobial susceptibility/resistance of bacteria contaminating SSFs in Sakaka, Aljouf, Saudi Arabia. We randomly swabbed the surfaces of 200 SSFs, then used the suitable culture media, standard microbiological methods, and the MicroScan WalkAway Microbiology System, including the identification/antimicrobial susceptibility testing-combo panels. A high SSFs' bacterial contamination load was detected (78.00%). Ninety percent of the samples collected in the afternoon, during the maximum workload of the SSFs, yielded bacterial growth (p < 0.001 *). Most of the contaminated SSFs were supermarket payment machines, self-pumping equipment at gas stations (p = 0.004 *), online banking service machines (p = 0.026 *), and barcode scanners in supermarkets. In the antiseptic-deficient areas, 55.1% of the contaminated SSFs were detected (p = 0.008 *). Fifty percent of the contaminated SSFs were not decontaminated. The most common bacterial contaminants were Escherichia coli (70 isolates), Klebsiella pneumoniae (66 isolates), Staphylococcus epidermidis (34 isolates), methicillin-resistant Staphylococcus aureus (18 isolates), and methicillin-sensitive Staphylococcus aureus (14 isolates), representing 31.53%, 29.73%, 15.32%, 8.11%, and 6.31% of the isolates, respectively. Variable degrees of reduced sensitivity to some antimicrobials were detected among the bacterial isolates. The SSFs represent potential risks for the exchange of antimicrobial-resistant bacteria between the out-hospital environment and the hospitals through the hands of the public. As technology and science advance, there is an urgent need to deploy creative and automated techniques for decontaminating SSFs and make use of recent advancements in materials science for producing antibacterial surfaces.

Beyond heat exposure - new methods to quantify and link personal heat exposure, stress, and strain in diverse populations and climates: The journal Temperature toolbox

Fine-scale personal heat exposure (PHE) information can help prevent or minimize weather-related deaths, illnesses, and reduced work productivity. Common methods to estimate heat risk do not simultaneously account for the intensity, frequency, and duration of thermal exposures, nor do they include inter-individual factors that modify physiological response. This study demonstrates new whole-body net thermal load estimations to link PHE to heat stress and strain over time. We apply a human-environment heat exchange model to examine how time-varying net thermal loads differ across climate contexts, personal attributes, and spatiotemporal scales. First, we investigate summertime climatic PHE impacts for three US cities: Phoenix, Miami, and New York. Second, we model body morphology and acclimatization for three profiles (middle-aged male/female; female >65 years). Finally, we quantify model sensitivity using representative data at synoptic and micro-scales. For all cases, we compare required and potential evaporative heat losses that can lead to dangerous thermal exposures based on (un)compensable heat stress. Results reveal misclassifications in heat stress or strain due to incomplete environmental data and assumed equivalent physiology and activities between people. Heat strain is most poorly represented by PHE alone for the elderly, non-acclimatized, those engaged in strenuous activities, and when negating solar radiation. Moreover, humid versus dry heat across climates elicits distinct thermal responses from the body. We outline criteria for inclusive PHE evaluations connecting heat exposure, stress, and strain while using physiological-based methods to avoid misclassifications. This work underlines the value of moving from "one-size-fits-all" thermal indices to "fit-for-purpose" approaches using personalized information.