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This study aims to examine the relationship between public knowledge, awareness and attitudes towards post-COVID-19 infection prevention in Sarawak. At present, Sarawak is in the post-pandemic stage, marked by a gradual return to normalcy, albeit with some persistent changes caused by the pandemic.

Data were collected from various geographic areas in Sarawak through a Google Form link and QR code during a cross-sectional study, resulting in the acquisition of 1,128 responses. Data analysis was performed using SPSS 28.0 and WarpPLS 8.0.

The result revealed that out of five hypotheses, four were found to be supported, indicating a positive relationship between public knowledge, awareness and attitudes towards COVID-19 infection prevention. However, an unsupported relationship was found between public awareness and infection prevention practices.

This study is limited to the Malaysian population and has a cross-sectional design, affecting generalizability. It is recommended that future research complete an in-depth study of the knowledge, awareness and practices of COVID-19 using other data collection techniques.

Public health and policymakers can use the study to implement effective communication strategies and prioritize digitalization for economic recovery. It highlights the importance of preventive measures and the public’s role in managing future pandemics.

The originality of this research can be drawn from key findings that indicate that people overall gained knowledge on the prevention measures during the post-COVID-19 pandemic, and the accuracy of the information significantly impacts public knowledge, awareness and practices of COVID-19 infection prevention.

This study aims to explore the management learning during a long-term crisis like a pandemic. The paper addresses both what health-care managers have learnt during the COVID-19 pandemic and how the management learning is characterized.

The paper is based on a qualitative case study carried out during the COVID-19 pandemic at two different public hospitals in Sweden. The study, conducted with semi-structured interviews, applies a combination of within-case analysis and cross-case comparison. The data were analyzed using thematic deductive analysis with the themes, i.e. sensemaking, decision-making and meaning-making.

The COVID-19 pandemic was characterized by uncertainty and a need for continuous learning among the managers at the case hospitals. The learning process that arose was circular in nature, wherein trust played a crucial role in facilitating the flow of information and enabling the managers to get a good sense of the situation. This, in turn, allowed the managers to make decisions meaningful for the organization, which improved the trust for the managers. This circular process was iterated with higher frequency than usual and was a prerequisite for the managers’ learning. The practical implications are that a combined management with hierarchical and distributed management that uses the normal decision routes seems to be the most successful management method in a prolonged crisis as a pandemic.

The gained knowledge can benefit hospital organizations, be used in crisis education and to develop regional contingency plans for pandemics.

This study has explored learning during the COVID-19 pandemic and found a circular process, “the management learning wheel,” which supports management learning in prolonged crises.

Menstruation is a part of the female reproductive cycle that begins with adolescence. Menstruation is a natural change; it relates to several malpractices and misconceptions that may contribute to adverse health outcomes.

The authors have searched relevant papers using Google Scholar and PubMed to write this mini review.

During menstruation, poor hygiene maintenance can cause serious illness, which includes the urinary tract and reproductive tract infection. Menstruation management is a hygienic system, and it is essential for females because poor hygiene maintenance during menstruation can cause some infections and numerous sexually transmitted diseases. There are a few nanotechnology-based products that have come into the market to offer some relief to females during their periods.

This mini review will help researchers to design innovative female hygiene products that can relieve the discomfort caused to women during their reproductive age.

At the beginning of the Corona Virus Disease 2019 (COVID-19) pandemic, a digitalized construction environments surfaced in the heating, ventilation and air conditioning (HVAC) systems in the form of a modern delivery system called demand controlled ventilation (DCV). Demand controlled ventilation has the potential to solve the building ventilation's biggest problem of managing indoor air quality (IAQ) for controlling COVID-19 transmission in indoor environments. However, the improper evaluation and information management of infection prevention on dense crowd activities such as measurement errors and volatile organic compound (VOC) generation failure rates, is fragmented so the aim of this research is to integrate this and explore potentials with machine learning algorithms (MLAs).

The method used is a thorough systematic literature review (SLR) approach. The results of this research consist of a detailed description of the DCV system and digitalized construction process of its IAQ elements.

The discussion revealed that DCV has a potential for being further integrated by perceiving it as a MLAs and hereby enabling the management of IAQ level from the perspective of health risk function mechanism (i.e. VOC and CO₂) for maintaining a comfortable thermal environment and save energy of public and private buildings (PPBs). The appropriate MLA can also be selected in different occupancy patterns for seasonal variations, ventilation behavior, building type and locations, as well as current indoor air pollution control strategies. Furthermore, the conceptual framework showed that MLA application such as algorithm design/Model Predictive Control (MPC) integration can alleviate the high spread limitation of COVID-19 in the indoor environment.

Finally, the research concludes that a large unexploited potential within integration and innovation is recognized in the DCV system and MLAs which can be improved to optimize level of IAQ from the perspective of health throughout the building sector DCV process systems. The requirements of CO₂ based DCV along with VOC concentrations monitoring practice should be taken into consideration through further research and experience with adaption and implementation from the ventilation control initial stage of the DCV process.

In the digital age, the spread of online behavior and real-world information leads to social contagion. This study aims to investigate the contagion phenomenon of online physician choice and then discuss its potential influence on the sub-specialization process in the healthcare service industry. In specific, this study aims to propose the basic mechanism of infection and immunity as follows – exposure to antigen may lead to an immune response, and the success of the immune response may depend on the provision of appropriate immune signaling.

Data collected from haodf.com including 4 disease types and 247 physicians from 2008 to 2015 were used to test the proposed hypotheses. Panel vector autoregression method was utilized to analyze the panel data.

The obtained result shows that social contagion of physician choice over disease type is salient on e-consultation platforms, indicating that physicians associated with/on haodf.com are concentrating on an even narrower type of disease. Disclosing more simple signals (physician history orders) results in more disease concentration for that physician in the future. In contrast, disclosing more detailed signals (physician-contributed knowledge or physician reviews) leads to less disease concentration.

This finding implies that physician-contributed knowledge and physician reviews may act as immune signal which will tend to trigger a success immune response. This study not only suggests managers should be careful about the double-edged sword effect of online physician choice contagion but also provides the useful approaches to promote or restrain such a contagion in a flexible way.

As of July 30, 2020, more than 17 million novel coronavirus disease 2019 (COVID-19) cases were registered including 671,500 deaths. Yet, there is no immediate medicine or vaccination for control this dangerous pandemic and researchers are trying to implement mathematical or time series epidemic models to predict the disease severity with national wide data.

In this study, the authors considered COVID-19 daily infection data four most COVID-19 affected nations (such as the USA, Brazil, India and Russia) to conduct 60-day forecasting of total infections. To do that, the authors adopted a machine learning (ML) model called Fb-Prophet and the results confirmed that the total number of confirmed cases in four countries till the end of July were collected and projections were made by employing Prophet logistic growth model.

Results highlighted that by late September, the estimated outbreak can reach 7.56, 4.65, 3.01 and 1.22 million cases in the USA, Brazil, India and Russia, respectively. The authors found some underestimation and overestimation of daily cases, and the linear model of actual vs predicted cases found a p-value (<2.2e-16) lower than the R2 value of 0.995.

In this paper, the authors adopted the Fb-Prophet ML model because it can predict the epidemic trend and derive an epidemic curve.

Intense interest has been shown in creating new and effective biocide agents as a result of changes in bacterial isolates, bacterial susceptibility to antibiotics, an increase in patients with burns and wounds and the difficulty of treating infections and antimicrobial resistance. Woven, nonwoven and knitted materials are used to make dressings; however, nonwoven dressings are becoming more popular because of their softness and high absorption capacity. Additionally, textiles have excellent geometrical, physical and mechanical features including three-dimensional structure availability, air, vapor and liquid permeability, strength, extensibility, flexibility and diversity of fiber length, fineness and cross-sectional shapes. It is necessary to treat every burn according to international protocol and along with it has to focus on particular problems of patients and the best possible results.

The objective of this paper is to conduct a thorough examination of research pertaining to the utilization of textiles, as well as alternative materials and innovative techniques, in the context of burn wound dressings. Through a critical analysis of the findings, this study intends to provide valuable insights that can inform and guide future research endeavors in this field.

In the past years, there have been several dressings such as xeroform petrolatum gauze, silver-impregnated dressings, biological dressings, hydrocolloid dressings, polyurethane film dressings, silicon-coated nylon dressings, dressings for biosynthetic skin substitutes, hydrogel dressings, newly developed dressings, scaffold bandages, Sorbalgon wound dressing, negative pressure therapy, enzymatic debridement and high-pressure water irrigation developed for the fast healing of burn wounds.

This research conducts a thorough analysis of the role of textiles in modern burn wound dressings.

This study addresses the COVID-19 infection and its relationship with the city’s constructive intensity, commuting time to work and labor market dynamics during the lockdown period.

Microdata from formal workers in Recife was used to adjust a probability model for disease contraction.

The authors' results indicate that greater distance to employment increases the probability of infection. The same applies to constructive intensity, suggesting that residences in denser areas, such as apartments in buildings, condominiums and informal settlements, elevate the chances of contracting the disease. It is also observed that formal workers with completed higher education have lower infection risks, while healthcare professionals on the frontlines of combating the disease face higher risks than others. The lockdown effectively reduced contagion by limiting people’s mobility during the specified period.

The research shows important causal relationships, making it possible to think about public policies for the health of individuals both when commuting to work and in living conditions, aiming to control contagion by COVID-19.

The lockdown effectively reduced contagion by limiting people’s mobility during the specified period.

It is also observed that formal workers with completed higher education have lower infection risks, while healthcare professionals on the frontlines of combating the disease face higher risks than others.

The authors identified positive and significant relationships between these urban characteristics and increased contagion, controlling for neighborhood, individual characteristics, comorbidities, occupations and economic activities.

This research aims to ascertain the various operational maturity challenges faced by the online food ordering and delivery enterprises (OFODE), their nature and their interactive relationships. In particular, this paper aims to (a) identify the most relevant operational maturity challenges faced by the OFODE during the COVID-19 lockdown in Oman, (b) explore and establish any likely structural relationship among these challenges and (c) put them into logical clusters.

Experts helped to reduce the 18 initially identified maturity challenges to 13 most pressing ones. Mutual relationships, dominance of interactions and their classifications were explored using fuzzy interpretive structural modeling (FISM) and fuzzy MICMAC analysis.

The study of situation-specific operational maturity challenges convinced the authors to propose a distinct FISM model that depicts the relationship among these challenges. Keeping commissions and fees reasonable emerges as the challenge which all other challenges seemingly culminate into. One of the most important situation-specific challenges (i.e. customer confidence about infection free delivery) emerges as a linkage challenge which aggravates as well as is aggravated by certain challenges.

Besides enriching literature, the proposed model has implications for practitioners particularly when the similar lethal waves are experienced anywhere. The number of respondents, subjective approach, specific context as well as the geographical area coverage are the key limitations.

To the best of the authors’ knowledge, this study is the first known scientific effort which attempts to model the operational maturity challenges faced by the OFODE during COVID-19 lockdown period. The authors used the FISM modeling approach to forge these interrelated challenges into a structural model.

This study aims to measure whether admittance in the quarantine ward due to COVID-19 can affect one’s mental health. Nowadays, many countries worldwide are battling with the threat of the COVID-19 contagion, and it is difficult to understand how the pandemic leaves psychological impacts on one’s well-being.

This research used qualitative and quantitative approaches to assess the psychological impacts of quarantine due to COVID-19. Population of the present study were 250 patients who were admitted in quarantine centres of Pakistan. The data analysis was conducted through univariate analysis using (ANVOVA) software.

This study found that patients who were quarantined due to the COVID-19 infection displayed multiple psychological symptoms such as a lack of self-control, anxiety, low general health and vitality, depression and negative well-being.

There is an urgency to provide psychological treatments to each afflicted person and their family members to establish a healthy community.

This research investigates whether admittance in the quarantine ward due to COVID-19 can affect mental health in Pakistan.