-
Journal of Environmental Management Jun 2024Selecting the optimal monitoring points in a water distribution network is challenging due to the complex spatiotemporal variability of water quality degradation. The...
Selecting the optimal monitoring points in a water distribution network is challenging due to the complex spatiotemporal variability of water quality degradation. The lack of a standardized methodology for monitoring point selection forces operators to rely on general recommendations, historical data and professional experience, which can mask water quality problems and increase the risk to consumers. This study proposes a new methodology to optimize the selection of monitoring points in distribution networks. The method considers the spatiotemporal degradation of water quality, the definition of representative zones and two selection criteria: global representativeness and potential health risk. Representative zones were determined for each node of the network based on hydraulic paths and their water quality spatial variability. Part of the distribution network in Quebec City, Canada was used as the case study, in which four water quality parameters were investigated: free chlorine residual (FRC), heterotrophic plate counts (HPC), trihalomethanes (THMs) and haloacetic acids (HAAs). Seasonal variabilities (summer and winter) were also analyzed. The results obtained for the two criteria and for both seasons were compared, and methodological and practical recommendations were established for dynamic monitoring programs that respond to the needs of operators.
PubMed: 38908156
DOI: 10.1016/j.jenvman.2024.121505 -
PLOS Global Public Health 2024Community Health Workers (CHWs) are a key human resource for health particularly in low- and middle-income countries. In many parts of the world, CHWs are known to have...
Community Health Workers (CHWs) are a key human resource for health particularly in low- and middle-income countries. In many parts of the world, CHWs are known to have played an instrumental role in controlling the COVID-19 pandemic. This study explored the involvement of CHWs in the COVID-19 response in Uganda. A qualitative study that involved 10 focus group discussions (FGDs) among CHWs was conducted. The study was carried out in 5 districts of Amuria, Karenga, Kamwenge, Bugiri and Pader. The FGD guide used explored the role of CHWs in the COVID-19 response in their communities including lived experiences, challenges, and coping mechanisms. The data were analyzed thematically with the support of NVivo version 12 pro (QSR International). CHWs were at the frontline of COVID-19 prevention interventions at households and in the community. CHWs raised awareness on prevention measures including wearing face masks, hand hygiene, and social distancing. They identified suspected cases such as new members entering the community, as well as individuals returning from abroad with signs and symptoms of COVID-19. CHWs mobilized the community and increased awareness on COVID-19 vaccination which played an important role in reducing misinformation. They also supported home-based management of mild COVID-19 cases through isolation of patients; provided health and nutritional guidance among patients in their homes; and referred suspected cases to health facilities for testing and management. Both monetary and non-monetary incentives were provided to support CHWs in the COVID-19 response. However, the adequacy and timing of the incentives were inadequate. Routine services of CHWs such as health promotion and treatment of childhood illnesses were disrupted during the pandemic. CHWs played an instrumental role in response to the pandemic especially on surveillance, risk communication, and observance of preventing measures. Strategies to ensure that routine services of CHWs are not disrupted during pandemics are needed.
PubMed: 38905244
DOI: 10.1371/journal.pgph.0003312 -
PloS One 2024Faces are a crucial environmental trigger. They communicate information about several key features, including identity. However, the 2019 coronavirus pandemic (COVID-19)...
Faces are a crucial environmental trigger. They communicate information about several key features, including identity. However, the 2019 coronavirus pandemic (COVID-19) significantly affected how we process faces. To prevent viral spread, many governments ordered citizens to wear masks in public. In this research, we focus on identifying individuals from images or videos by comparing facial features, identifying a person's biometrics, and reducing the weaknesses of person recognition technology, for example when a person does not look directly at the camera, the lighting is poor, or the person has effectively covered their face. Consequently, we propose a hybrid approach of detecting either a person with or without a mask, a person who covers large parts of their face, and a person based on their gait via deep and machine learning algorithms. The experimental results are excellent compared to the current face and gait detectors. We achieved success of between 97% and 100% in the detection of face and gait based on F1 score, precision, and recall. Compared to the baseline CNN system, our approach achieves extremely high recognition accuracy.
Topics: Humans; COVID-19; Neural Networks, Computer; Machine Learning; Deep Learning; Algorithms; SARS-CoV-2; Face; Gait; Biometric Identification
PubMed: 38905186
DOI: 10.1371/journal.pone.0300614 -
Translational Vision Science &... Jun 2024This study enhances Meibomian gland (MG) infrared image analysis in dry eye (DE) research through artificial intelligence (AI). It is comprised of two main stages:...
PURPOSE
This study enhances Meibomian gland (MG) infrared image analysis in dry eye (DE) research through artificial intelligence (AI). It is comprised of two main stages: automated eyelid detection and tarsal plate segmentation to standardize meibography image analysis. The goal is to address limitations of existing assessment methods, bridge the curated and real-world dataset gap, and standardize MG image analysis.
METHODS
The approach involves a two-stage process: automated eyelid detection and tarsal plate segmentation. In the first stage, an AI model trained on curated data identifies relevant eyelid areas in non-curated datasets. The second stage refines the eyelid area in meibography images, enabling precise comparisons between normal and DE subjects. This approach also includes specular reflection removal and tarsal plate mask refinement.
RESULTS
The methodology achieved a promising instance-wise accuracy of 80.8% for distinguishing meibography images from 399 DE and 235 non-DE subjects. By integrating diverse datasets and refining the area of interest, this approach enhances meibography feature extraction accuracy. Dimension reduction through Uniform Manifold Approximation and Projection (UMAP) allows feature visualization, revealing distinct clusters for DE and non-DE phenotypes.
CONCLUSIONS
The AI-driven methodology presented here quantifies and classifies meibography image features and standardizes the analysis process. By bootstrapping the model from curated datasets, this methodology addresses real-world dataset challenges to enhance the accuracy of meibography image feature extraction.
TRANSLATIONAL RELEVANCE
The study presents a standardized method for meibography image analysis. This method could serve as a valuable tool in facilitating more targeted investigations into MG characteristics.
Topics: Humans; Artificial Intelligence; Dry Eye Syndromes; Meibomian Glands; Female; Male; Middle Aged; Image Processing, Computer-Assisted; Adult; Diagnostic Techniques, Ophthalmological; Aged; Infrared Rays
PubMed: 38904611
DOI: 10.1167/tvst.13.6.16 -
BMC Infectious Diseases Jun 2024Planned behaviors and self-care against the coronavirus are two important factor in controlling its spread and self-care behaviors depend on the level of health...
BACKGROUND
Planned behaviors and self-care against the coronavirus are two important factor in controlling its spread and self-care behaviors depend on the level of health literacy. This research was conducted to determine the mediating role of health literacy in the relationship between elements of planned behavior and self-care in dealing with the Covid-19.
METHODS
In this descriptive-analytical quantitative study, the sample size was calculated using Cochrane's formula and considering a p-value of 0.51, α = 0.05, and d = 0.05, and 313 students were selected based on stratified and random method. To gather data and assess various aspects of variables, a questionnaires were utilized, focusing on health literacy, self-car and planned behavior. The relationship between the variables was examined by SPSS version 26 and via descriptive statistics, including the mean and standard deviation, and inferential statistics such as Pearson's correlation coefficient (P = 0.05), path analysis, and determining the standard coefficients between self-care and planned behavior, mediated by the indicators of the health literacy.
RESULTS
A significant difference was found between the level of health literacy of women and men. The comparison of the mean health literacy and self-care behavior in terms of other variables did not show any significant difference. Meanwhile, the comparison of health status control behaviors, hand washing, and mask use did not show any significant difference between the two groups. A positive and significant correlation was found between self-care behaviors, attitude, subjective norms, perceived behavioral control, and behavioral intention. The relationship of health literacy and psychological variables of attitude, subjective norms, and perceived behavioral control with self-care against COVID-19 was significant.
CONCLUSION
The direct and significant impact of health literacy on individuals' self-care behaviors against the coronavirus was not observed. However, health literacy did have a significant effect on subjective norms. This finding is important because subjective norms significantly influenced individuals' behavioral intention, which in turn had a significant effect on self-care behaviors against the coronavirus. Thus, health literacy played a mediating role in this relationship. Furthermore, attitude emerged as the strongest predictor of behavioral intention, exerting a direct effect. Conversely, perceived behavioral control did not directly and significantly affect students' self-care behaviors.
Topics: Humans; COVID-19; Health Literacy; Male; Female; Self Care; Surveys and Questionnaires; SARS-CoV-2; Young Adult; Adult; Health Behavior; Health Knowledge, Attitudes, Practice; Students; Adolescent
PubMed: 38902618
DOI: 10.1186/s12879-024-09513-8 -
Scientific Reports Jun 2024Regular screening for cervical cancer is one of the best tools to reduce cancer incidence. Automated cell segmentation in screening is an essential task because it can...
Regular screening for cervical cancer is one of the best tools to reduce cancer incidence. Automated cell segmentation in screening is an essential task because it can present better understanding of the characteristics of cervical cells. The main challenge of cell cytoplasm segmentation is that many boundaries in cell clumps are extremely difficult to be identified. This paper proposes a new convolutional neural network based on Mask RCNN and PointRend module, to segment overlapping cervical cells. The PointRend head concatenates fine grained features and coarse features extracted from different feature maps to fine-tune the candidate boundary pixels of cell cytoplasm, which are crucial for precise cell segmentation. The proposed model achieves a 0.97 DSC (Dice Similarity Coefficient), 0.96 TPRp (Pixelwise True Positive Rate), 0.007 FPRp (Pixelwise False Positive Rate) and 0.006 FNRo (Object False Negative Rate) on dataset from ISBI2014. Specially, the proposed method outperforms state-of-the-art result by about on DSC, on TPRp and on FNRo respectively. The performance metrics of our model on dataset from ISBI2015 are slight better than the average value of other approaches. Those results indicate that the proposed method could be effective in cytological analysis and then help experts correctly discover cervical cell lesions.
Topics: Humans; Female; Uterine Cervical Neoplasms; Neural Networks, Computer; Cervix Uteri; Image Processing, Computer-Assisted; Algorithms; Early Detection of Cancer
PubMed: 38902285
DOI: 10.1038/s41598-024-64583-7 -
Scientific Reports Jun 2024In the face of infectious disease outbreaks, the collective behavior of a society can has a profound impact on the course of the epidemic. This study investigates the...
In the face of infectious disease outbreaks, the collective behavior of a society can has a profound impact on the course of the epidemic. This study investigates the instantaneous social dilemma presented by individuals' attitudes toward vaccine behavior and its influence on social distancing as a critical component in disease control strategies. The research employs a multifaceted approach, combining modeling techniques and simulation to comprehensively assess the dynamics between social distancing attitudes and vaccine uptake during disease outbreaks. With respect to modeling, we introduce a new vaccination game (VG) where, unlike conventional VG models, a 2-player and 2-strategy payoff structure is aptly embedded in the individual behavior dynamics. Individuals' willingness to adhere to social distancing measures, such as mask-wearing and physical distancing, is strongly associated with their inclination to receive vaccines. The study reveals that a positive attitude towards social distancing tends to align with a higher likelihood of vaccine acceptance, ultimately contributing to more effective disease control. As the COVID-19 pandemic has demonstrated, swift and coordinated public health measures are essential to curbing the spread of infectious diseases. This study underscores the urgency of addressing the instantaneous social dilemma posed by individuals' attitudes. By understanding the intricate relationship between these factors, policymakers, and healthcare professionals can develop tailored strategies to promote both social distancing compliance and vaccine acceptance, thereby enhancing our ability to control and mitigate the impact of disease outbreaks in the future.
Topics: Humans; COVID-19; Physical Distancing; Vaccination; SARS-CoV-2; COVID-19 Vaccines; Attitude; Pandemics; Communicable Disease Control
PubMed: 38902279
DOI: 10.1038/s41598-024-64143-z -
NPJ Biofilms and Microbiomes Jun 2024During the COVID-19 pandemic, facemasks played a pivotal role in preventing person-person droplet transmission of viral particles. However, prolonged facemask wearing...
During the COVID-19 pandemic, facemasks played a pivotal role in preventing person-person droplet transmission of viral particles. However, prolonged facemask wearing causes skin irritations colloquially referred to as 'maskne' (mask + acne), which manifests as acne and contact dermatitis and is mostly caused by pathogenic skin microbes. Previous studies revealed that the putative causal microbes were anaerobic bacteria, but the pathogenesis of facemask-associated skin conditions remains poorly defined. We therefore characterized the role of the facemask-associated skin microbiota in the development of maskne using culture-dependent and -independent methodologies. Metagenomic analysis revealed that the majority of the facemask microbiota were anaerobic bacteria that originated from the skin rather than saliva. Previous work demonstrated direct interaction between pathogenic bacteria and antagonistic strains in the microbiome. We expanded this analysis to include indirect interaction between pathogenic bacteria and other indigenous bacteria classified as either 'pathogen helper (PH)' or 'pathogen inhibitor (PIn)' strains. In vitro screening of bacteria isolated from facemasks identified both strains that antagonized and promoted pathogen growth. These data were validated using a mouse skin infection model, where we observed attenuation of symptoms following pathogen infection. Moreover, the inhibitor of pathogen helper (IPH) strain, which did not directly attenuate pathogen growth in vitro and in vivo, functioned to suppress symptom development and pathogen growth indirectly through PH inhibitory antibacterial products such as phenyl lactic acid. Taken together, our study is the first to define a mechanism by which indirect microbiota interactions under facemasks can control symptoms of maskne by suppressing a skin pathogen.
Topics: Animals; Mice; Masks; Microbiota; Humans; COVID-19; Skin; Acne Vulgaris; SARS-CoV-2; Female; Metagenomics; Disease Models, Animal; Bacteria; Microbial Interactions; Dermatitis, Contact
PubMed: 38902263
DOI: 10.1038/s41522-024-00512-w -
Nature Communications Jun 2024During the early stages of the SARS-CoV-2 pandemic, before vaccines were available, nonpharmaceutical interventions (NPIs) such as reducing contacts or antigenic testing...
During the early stages of the SARS-CoV-2 pandemic, before vaccines were available, nonpharmaceutical interventions (NPIs) such as reducing contacts or antigenic testing were used to control viral spread. Quantifying their success is therefore key for future pandemic preparedness. Using 1.8 million SARS-CoV-2 genomes from systematic surveillance, we study viral lineage importations into Germany for the third pandemic wave from late 2020 to early 2021, using large-scale Bayesian phylogenetic and phylogeographic analysis with a longitudinal assessment of lineage importation dynamics over multiple sampling strategies. All major nationwide NPIs were followed by fewer importations, with the strongest decreases seen for free rapid tests, the strengthening of regulations on mask-wearing in public transport and stores, as well as on internal movements and gatherings. Most SARS-CoV-2 lineages first appeared in the three most populous states with most cases, and spread from there within the country. Importations rose before and peaked shortly after the Christmas holidays. The substantial effects of free rapid tests and obligatory medical/surgical mask-wearing suggests these as key for pandemic preparedness, given their relatively few negative socioeconomic effects. The approach relates environmental factors at the host population level to viral lineage dissemination, facilitating similar analyses of rapidly evolving pathogens in the future.
Topics: Humans; COVID-19; SARS-CoV-2; Phylogeography; Phylogeny; Germany; Bayes Theorem; Genome, Viral; Pandemics
PubMed: 38902246
DOI: 10.1038/s41467-024-48641-2