Suitable Measures Research Articles

Participatory design based on opinion pooling.

We focus here on methods for locating future urban development, ranging from entire towns to site designs. These methods articulate the urban design problem in terms of a series of factors pertaining to different measures of land suitability that are represented as spatial surfaces or maps. In realistic problems, these factors inevitably conflict with one another, and we thus define various design methods that enable us to select optimal locations for development based on weighting these factors in different ways. We begin with methods for resolving conflicts between the suitability maps using simple averaging with equal weights and then introduce methods for representing the interactions between the factors as a hierarchy for how these factors can be related to each other following an order for their differential weighting. We then generalize this method to ways in which a variety of individual experts can pool their knowledge of the problem to achieve a consensus solution using a process of group dynamics. The implication is that these kinds of dynamics might be used to enable effective public participation where conflicts between opinions can be resolved collectively. We are currently exploring this through methods of geodesign where networks of stakeholders, planners and designers can be brought together to solve these problems both empirically as well as formally.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

Evolutionary Stress Detection Framework through Machine Learning and IoT (MLIoT-ESD)

Background: Life nowadays is full of stress due to lifestyle changes and the modernera race. Almost everyone around us is suffering from stress and anxiety. Mostly, stress identification is done by medical practitioners in a very late stage in which suitable help measures cannot be provided and hence result in suicides or early age deaths due to cardiac arrest, etc. One major reason behind the delay is the time required in stress identification by traditional approaches, and above that, the amount of time and financial support expected is always not feasible to be available. Hence, in this paper, we proposed an evolutionary research framework for stress identification by the usage of both machine learning and IoT. Here, we also conducted a pilot study on 83 records available over the decade since 2014 using PRISMA guidelines, and a bibliographic network visualization was also performed using VOS viewer. Objectives: This study aimed to develop a stress detection framework using Machine Learning and the Internet of Things (IoT) as technology advanced over a decade. Methods: More than 80 research papers from honorable repositories like Scopus and Web of Science were gathered according to the guidelines of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020, and the VOSviewer tool was further applied to construct the bibliographic depictions. Various datasets and methods used over ten years with their performance were also discussed. Results: This research was conducted to gather various types of stressors, the impact of various Machine Learning and IoT algorithms and concepts on various datasets and their respective results. Conclusion: Various available datasets and results with multiple algorithms were discussed in a crisp tabular form for better understanding. A methodology based on an amalgamation of Machine Learning and IoT was also proposed due to various research gaps available so that stress detection could be done in a cost-effective way.

How survey scoring decisions can influence your study's results: A trip through the IRT looking glass.

Though much effort is often put into designing psychological studies, the measurement model and scoring approach employed are often an afterthought, especially when short survey scales are used (Flake & Fried, 2020). One possible reason that measurement gets downplayed is that there is generally little understanding of how calibration/scoring approaches could impact common estimands of interest, including treatment effect estimates, beyond random noise due to measurement error. Another possible reason is that the process of scoring is complicated, involving selecting a suitable measurement model, calibrating its parameters, then deciding how to generate a score, all steps that occur before the score is even used to examine the desired psychological phenomenon. In this study, we provide three motivating examples where surveys are used to understand individuals' underlying social emotional and/or personality constructs to demonstrate the potential consequences of measurement/scoring decisions. These examples also mean we can walk through the different measurement decision stages and, hopefully, begin to demystify them. As we show in our analyses, the decisions researchers make about how to calibrate and score the survey used has consequences that are often overlooked, with likely implications both for conclusions drawn from individual psychological studies and replications of studies. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Geometric features and traffic dynamic analysis on 4-leg intersections

AbstractWith the escalating density of vehicles converging at road intersections, the surge in road accidents, traffic conflicts, and traffic congestion has emerged as a pressing concern. This research paper addresses these challenges by employing MC (manual control) techniques to mitigate encroachment issues at three selected intersections. These intersections were identified through a comprehensive analysis of the Ranking-based Instance Selection (RIS), enabling the design of suitable measures to facilitate smooth traffic flow and minimize the occurrence of crashes. In order to gather pertinent data, the study incorporates various parameters such as traffic volume, peak flow rate (PFR), traffic conflicts, accidents, and intersection inventory. Through the implementation of our proposed approaches, which involve both MC techniques and signalized operation, a supreme level of service (LOS) is attainable. Notably, our findings demonstrate a remarkable reduction in the volume-to-capacity ratio (v/c ratio) of up to 0.62. This paper thus serves as a significant contribution to the field of traffic management, offering practical insights for optimizing intersection design and effectively addressing the challenges posed by increased traffic density.

Suitable and Style-Consistent Multi-Texture Recommendation for Cartoon Illustrations

Texture plays an important role in cartoon illustrations to display object materials and enrich visual experiences. Unfortunately, manually designing and drawing an appropriate texture is not easy even for proficient artists, let alone novice or amateur people. While there exist tons of textures on the Internet, it is not easy to pick an appropriate one using traditional text-based search engines. Although several texture pickers have been proposed, they still require the users to browse the textures by themselves, which is still labor-intensive and time-consuming. In this article, an automatic texture recommendation system is proposed for recommending multiple textures to replace a set of user-specified regions in a cartoon illustration with visually pleasant look. Two measurements, the suitability measurement and the style-consistency measurement, are proposed to make sure that the recommended textures are suitable for cartoon illustration and at the same time mutually consistent in style. The suitability is measured based on the synthesizability, cartoonity, and region fitness of textures. The style-consistency is predicted using a learning-based solution since it is subjective to judge whether two textures are consistent in style. An optimization problem is formulated and solved via the genetic algorithm. Our method is validated on various cartoon illustrations, and convincing results are obtained.

Comparison of EKFC, Pakistani CKD-EPI and 2021 Race-Free CKD-EPI creatinine equations in South Asian CKD population: A study from Pakistani CKD community cohort.

South Asian individuals possess a high risk of chronic kidney disease. There is a need to study, evaluate, and compare the newly suggested glomerular filtration rate (eGFR) equations for accurate CKD diagnosis, staging, and drug dosing. This study aimed to (1) evaluate the European Kidney Function Consortium (EKFC), Pakistani CKD-EPI, and 2021 Race-Free CKD-EPI creatinine equation in the South Asian population with CKD and (2) to examine the expected implications on both CKD classification as well as End Stage Renal Disease (ESRD) prevalence across these equations in South Asian population. We carried out a cross-sectional investigation on 385 participants, a CKD cohort ≥ 18 years, at Allama Iqbal Medical College, Jinnah Hospital, Lahore. Serum creatinine was measured by Jaffe's method and rGFR was measured by inulin clearance. Pakistani CKD-EPI has a lower median difference at -1.33 ml/min/1.73m2 elevated precision (IQR) at 2.33 (-2.36, -0.03) and higher P30 value at 89.35% than 2021 CKD-EPI and EKFC equations. The mean difference (ml/min/1.73m2), 95% agreement limits (ml/min/1.73m2) of CKD-EPI PK: -1.18, -6.14, 2021 CKD-EPI: -5.98, -13.24 and EKFC: -5.62, -13.01 (P <0.001). These equations highly correlated to rGFR (P <0.001). An upward re-classification in GFR categories was shown by 2021 CKD-EPI and EKFC compared to the Pakistani CKD-EPI equation. However, there was an exception regarding the G5 category, where an elevated count of 217 (56.36%) was shown for CKD-EPI PK. The prevalence of ESRD was seen in entire age groups and prevailed among females more than in males overall equations. Pakistani CKD-EPI exhibited outstanding performance, while 2021 CKD-EPI and EKFC demonstrated poor performances and could not show an adequate advantage for both CKD classification and prevalence of ESRD compared to Pakistani CKD-EPI. Therefore, Pakistani CKD-EPI appears optimal for this region and warrants future validation in other South Asian countries. In contrast, suitable measures must be implemented in Pakistani laboratories.

Agricultural Solid Waste and its Management: An Overview

Waste is one of the most pressing issues of the present time. Its effects seemed so drastic that concerns about its proper management raised questions around the globe. The major areas of developing and underdeveloped countries are used for agriculture and allied activities. Most of the waste generated in a country comprisesd agricultural wastes, most of which are solid. There is an urgent need to manage this agricultural waste to avoid environmental degradation and mitigate its ill effects on human and animal health. It was found that vermicomposting seemed to be by far the most affordable and quickest method of agricultural solid waste management. It also describes the problem of crop residue burning, which is quite prevalent in developing countries like India. It was also seen that the respective central and state governments must frame specific policies and laws for agricultural waste management. As agricultural solid wastes have good re-use and conversion potential, and it was suggested that suitable measures that can be taken to implement sustainable management of agricultural solid wastes.

Seasonal flood risk for paddy rice production in northwest Peninsular Malaysia

ABSTRACT Managing flood risk to crop productions can be made cost-effective by considering the seasonality of flood hazard. This study attempts to quantify expected seasonal flood risk to paddy production in northwest Peninsular Malaysia. The seasonal flood risk was quantified following the region’s standard planting seasons and accounts the seasonal annual maxima flood and potential losses to the crop production. The highest expected annual damage (EAD) is from the wet planting season between September and November during the vegetative and reproductive growth phases, amounting to more than MYR 700,000 EAD. These months coincide with the northeast monsoon season, typically occurring from November to March each year. Seasonal flood risk remains a threat to the nation, and the quantified expected losses provide strong justification of the need for a proactive and strategic action plan.

Improved Care and Treatment Options for Patients with Hyperphagia-Associated Obesity in Bardet-Biedl Syndrome

Bardet-Biedl syndrome (BBS) is a rare, autosomal recessive multisystem disease. The pathophysiological origin is a dysfunction of the primary cilium. Clinical symptoms are heterogeneous and variable: retinal dystrophy, obesity, polydactyly, kidney abnormalities, hypogenitalism and developmental delays are the most common features. By the approval of the melanocortin 4 receptor agonist setmelanotide, a drug therapy for BBS-associated hyperphagia and obesity can be offered for the first time. Hyperphagia and severe obesity represent a considerable burden and are associated with comorbidity and increased mortality risk. Due to the limited experience with setmelanotide in BBS, a viable comprehensive therapy concept is to be presented. Therapy decision and management should be conducted in expert centers. For best therapeutic effects with setmelanotide adequate information of the patient about the modalities of the therapy (daily subcutaneous injection) and possible adverse drug events are necessary. Furthermore, the involvement of psychologists, nutritionists and nursing services (support for the application) should be considered together with the patient. The assessment of therapy response should be carried out with suitable outcome measurements and centrally reported to an adequate register.

The Overview of Challenges in Detecting Patients' Hazards During Robot-Aided Remote Home Motor Rehabilitation

Home, minimally‐supervised rehabilitation has become an arising technological trend due to the shortages in medical staff. Implementing such requires providing advanced tools for automatic real‐time safety monitoring. The paper presents an approach to designing the mentioned safety system based on measurements and modelling the interface between a patient’s musculoskeletal system and a rehabilitation device. The content covers the segmentation of patients regarding their health conditions and assigns them suitable measurement techniques. The defined groups are described with the hazards, which they are most endangered, and their causes. Each case is correlated with the appropriate data type that may be used to detect potential risk. Moreover, a concept of using presented knowledge for tracking the safety of bones and soft tissues according to the biomechanical standards is included. The paper forms a set of guidelines for designing safety systems based on measurements for robot‐aided home kinesiotherapy. It can be used to select an appropriate approach regarding a specific case; so to decrease costs and increase the accuracy of the designed tools.

The influence of increasing mineral fertilizer application on nitrogen leaching of arable land and grassland—results of a long-term lysimeter study

IntroductionDespite various efforts to reduce nitrogen leaching from agricultural land, the permissible nitrate concentrations in groundwater have often been exceeded in the past. Intensive farming is often seen as the cause of the deterioration in water quality. Therefore, the present lysimeter study aimed to quantify nitrogen (N) leaching at different N fertilization levels for the agricultural land use systems of arable land and grassland to derive suitable management measures for improving groundwater quality.MethodsThe effects of three different of mineral fertilization treatments (50%, 100%, and 150%) in arable land and grassland use on four distinct soil types (loamy sand, sand, loam, loess) concerning seepage formation, nitrogen concentrations, nitrogen loads, dry matter yields and nitrogen balances were tested. The study was conducted at the lysimeter facility of the Helmholtz Centre of Environmental Research – UFZ at Falkenberg (northeast Germany). Twenty-four non-weighable lysimeters with a surface area of 1 m² and a depth of 1.25 m were managed as grassland and arable land with three different fertilization treatments since 1985.Results and DiscussionFor arable land use, N leaching differed between the studied soil types, with the highest N loads from the sand (36.6 kg ha–1 yr–1 ) and loamy sand (30.7 kg ha–1 yr–1 ) and the lowest N loads from loess (12.1 kg ha–1 yr–1) and loam soil (13.1 kg ha–1 yr–1). In contrast to grassland use, a reduction of N fertilization level by 50 % did not result in reduced N leaching for arable land, whereas a maximal 29% reduced dry matter yields was observed. An increase of N fertilization by 50 % did not cause significant enhanced N leaching at arable land use. Soil-and management-related factors (soil type, texture, soil tillage, crop rotation, and others) mask the effect of increased N fertilization rates in arable land using lysimeters. For arable land use, a reduction of N fertilizer levels as the only measure was insufficient to reduce NO3– leaching, and other strategies besides N fertilization levels are required to improve groundwater quality. Measures should be targeted to reduce N losses by mineralization processes.

Soil quality evaluation of different land use modes in small watersheds in the hilly region of southern Jiangsu

The Yixing Yuantianjian small watershed is a provincial soil erosion key management area in the hilly region of southern Jiangsu. It has been implemented key national soil erosion control project for small watershed management, which is typical and representative in the region. It is important to quantitatively evaluate the soil quality of the area under different land use modes and then select suitable ecological restoration measures to promote the ecological and economic construction of small watersheds in the hilly region of southern Jiangsu. Used four types of land use (forest land, garden land, arable land and abandoned land) in the Yixing Yuantianjian small watershed as the research object, 13 soil physical and chemical property indicators were screened based on principal component analysis, correlation analysis and Norm value calculation to construct a minimum data set (MDS) for soil quality evaluation. The results showed that the variability of soil chemical indicators of land use modes was higher than that of soil physical indicators in the study area. The MDS indicators affected by soil quality in the small watershed are sand content (Sand), total nitrogen (TN), available nitrogen (AN), available potassium (AK), total soil porosity (TSP) and bulk density (BD), which provide valid information on soil quality in the area with high accuracy. The soil quality index for different land use modes in the small watershed in the hilly areas of southern Jiangsu was SQI forest land (0.83) > SQI cultivated land (0.74) > SQI garden land (0.66) > SQI abandoned land (0.46), with soil quality at a medium to high level. AN was the key factor limiting the soil quality of this watershed. This study can provide a scientific basis for soil quality enhancement and ecological restoration in the small watersheds of the southern Jiangsu hilly region.

First report of Paracapillaria philippinensis infection in flowerhorn cichlid in India.

The flowerhorn cichlid is a popular ornamental fish in many Asian countries. The present study reports the occurrence of Paracapillaria philippinensis (Chitwood et al., 1968), a parasitic nematode in flowerhorn cichlid (Cichlasoma sp.) from south India. The infected fish demonstrated clinical symptoms viz. dark coloration, poor appetite, lethargy, erratic swimming, and white stringy faeces. Microscopic observation of the intestinal content and faeces revealed the presence of adult worms, larvae, and unembryonated eggs. PCR amplification of eukaryotic 18S rRNA, P. philippinensis-specific SSU rRNA gene, and the subsequent sequence analysis confirmed the species identity as P. philippinensis. The generated sequences were submitted in the GenBank, NCBI, under the accession numbers, MK895507.1, MK895446.1, MW144993.1, and OR685675.1. This is the first scientific report of P. philippinensis in fish from India, and it confirms that the flowerhorn cichlid can act as a definitive host for P. philippinensis. This report alerts fish handlers and enthusiasts to undertake suitable precautionary measures while handling live flowerhorn cichlids to prevent possible transmission of P. Philippinensis, which has the potential to infect humans causing intestinal capillariasis.

Cybersecurity Vulnerabilities in Healthcare: A Threat to Patient Security

Healthcare information systems hold significant importance; hence, their cybersecurity is crucial. Exposed networks make it easy for cybercriminals to launch cyberattacks and access healthcare data. Thus, concerns regarding cybersecurity and its link to healthcare privacy, confidential data, and medical devices are growing. Therefore, cybersecurity vulnerabilities in healthcare and patient security are significant issues. Healthcare information systems comprise correlated networks and play a vital role in treating and saving patients. However, advanced circulated ransomware attacks on hospitals prevent access to electronic health records for providing appropriate patient care, thus forcing doctors to turn to other facilities. These cyberattacks can leak patient data, and regaining control of information systems and patient data is highly expensive, thus resulting in extensive monetary losses. Cyberattacks aimed toward electronic medical records, information technology systems, and medical devices have corrupted the best systems across clinics and small offices with physicians, as well as merged health systems. There is an urgency to address cybersecurity vulnerabilities in healthcare; however, opinions differ regarding suitable measures for safeguarding patient data and ensuring infrastructural security. We aimed to reconcile these diverging hypotheses and provide an understanding of the current landscape and directions for further improvements by reviewing several studies on healthcare cybersecurity. We also interviewed healthcare professionals, cybersecurity experts, and administrators and distributed a survey questionnaire to healthcare organizations to gather quantitative data on existing cybersecurity measures and vulnerabilities. Our analyses show that healthcare organizations are vulnerable to a variety of threats, cyberattacks disrupt the health sector, cybersecurity vulnerabilities impact patient security, and implementations of cybersecurity measures are inconsistent across organizations. Owing to the sophisticated nature of cyberattacks, the healthcare industry must prioritize cybersecurity and provide the funding required to develop critical systems for safeguarding patients and their data. The study's findings underscore the need for standardized cybersecurity practices in healthcare to address inconsistencies in measures across organizations. Adequate and ongoing investment in cybersecurity infrastructure is imperative to counter increasingly sophisticated cyberattacks. Additionally, protecting patient data and maintaining trust within the healthcare sector are ethical imperatives that should guide industry actions. By embracing these implications, the healthcare industry can enhance patient security, financial stability, and ethical integrity.

Spontaneous fractures in healthy postmenopausal women aged 55+ years in two health centers: Laquintinie Hospital and General Hospital, Douala, Cameroon

Background: Women in their old age are facing some health issues due to physiological changes. It was observed many cases of osteoporosis during menopause. At that stage of their life, women undergo ovaries atrophy caused by hormonal imbalance. Estrogen deficiency is a leading cause of osteoporosis in postmenopausal women. That is why at menopause when its level drops women have fragile bones and are prone to fractures of many kinds. Fractures are associated with a high risk of morbidity which is why we aimed to identify and characterize the state of fractures in older women during menopause in our country. Method: A survey was performed at the orthopedic-traumatology and rheumatology unit of 2 different health centers: Laquintinie Hospital of Douala and Douala General Hospital (DGH). Files of postmenopausal women admitted for fracture were screened. The data were analyzed by SPSS and statistical significance was considered when P-value &lt; 0.05. Results: 643 files of postmenopausal women admitted for fractures were analyzed. Results showed that 29% (186/643) of women at menopause aged above 55 years old had spontaneous fractures. The mean age was 71.89 years, ranging from 55 to 119 years. Falls and domestic accidents were the top two most represented causes (38.2 and 31.7 % respectively). Among those fractures, 70% happened after minimal trauma. The wrist was the favorite anatomical site for patients aged ranged between 55-64 years. As for UEF (Upper end of the femur) fracture, it increased in an age-related manner. Absence of trauma was observed the less in population aged between 55 and 64 years (11.5% ; P&lt;0.001); and it was highest in women aged 85+ years (64%). Conclusion: Postmenopausal women in our population have disabilities due to spontaneous fractures which impact negatively their quality of life. We should spread awareness among women before they reach menopause to take suitable measures to reduce the incidence of fractures and related morbidity at a certain age.

Low voltage grid resilience: Evaluating electric vehicle charging strategies in the context of the grid development plan Germany

The ongoing transition to decentralized renewable energy sources and sector-coupled consumers is reshaping the energy system. Changes at lower grid levels can stress lines and transformers. Crucial for a successful local energy transition are grid relief measures. Battery electric vehicles contribute to higher loads on grid equipment but also offer flexibility. This paper assesses the influence of four different charging strategies for battery electric vehicles across five representative low-voltage grids based on the grid development plan in Germany for the years 2021, 2037, and 2045. Results indicate that grid stress, specifically capacity stress, will emerge by 2037 and 2045. Decentralized photovoltaic systems are the primary contributors to this stress due to high simultaneous generation. Up to nearly 20% of photovoltaic power may need to be curtailed in 2045, especially in rural grids during the summer, to prevent overloads.Charging strategies linked to wholesale power market prices can inadvertently lead to higher consumption-induced grid overloads, necessitating the consideration of local grid restrictions. Implementing grid-friendly charging strategies, such as reduced charging power or alignment with local photovoltaic production, can mitigate those grid overloads from almost 8% down to 0.11%. However, these charging strategies have limited impact on photovoltaic-induced overloads due to the low number of connected battery electric vehicles during the day.In summary, appropriate charging strategies can ease low-voltage grid stress and are suitable measures to manage the challenges of decentralized energy transition and battery-electric vehicle adoption.

Probing Temperature-Induced Plasmonic Nonlinearity: Unveiling Opto-Thermal Effects on Light Absorption and Near-Field Enhancement.

Precise measurement and control of local heating in plasmonic nanostructures are vital for diverse nanophotonic devices. Despite significant efforts, challenges in understanding temperature-induced plasmonic nonlinearity persist, particularly in light absorption and near-field enhancement due to the absence of suitable measurement techniques. This study presents an approach allowing simultaneous measurements of light absorption and near-field enhancement through angle-resolved near-field scanning optical microscopy with iterative opto-thermal analysis. We revealed gold thin films exhibit sublinear nonlinearity in near-field enhancement due to nonlinear opto-thermal effects, while light absorption shows both sublinear and superlinear behaviors at varying thicknesses. These observations align with predictions from a simple harmonic oscillation model, in which changes in damping parameters affect light absorption and field enhancement differently. The sensitivity of our method was experimentally examined by measuring the opto-thermal responses of three-dimensional nanostructure arrays. Our findings have direct implications for advancing plasmonic applications, including photocatalysis, photovoltaics, photothermal effects, and surface-enhanced Raman spectroscopy.

Quantitative evaluation of crowd intelligence innovation system health: An ecosystem perspective

Crowd intelligence innovation (CII) is an open problem-solving model, typically performs on a crowdsourcing-based online innovation platform, which is highly dependent on the engagement and high-quality work of participants. On an online platform, many demanders publish tasks, and innovators submit schemes, which forms a complex CII system. To ensure such a CII system operates sustainably, it is critical for the platform operators to know the current system’s health statuses before taking proper management actions. However, the large influx of participators with varied behaviors makes it extremely difficult to evaluate the health statuses of the system and capture its characteristics. Practicable method for quantitatively evaluating the health status of a CII system is still missing. Therefore, this study proposed a new quantitative health status evaluation method from an ecosystem perspective. First, the crowd intelligence innovation ecosystem (CIIE) was established by mapping the CII system onto the natural ecosystem based on ecological theory. Second, the health status of CIIE was described by its internal health status and external health status using a mixed method. The internal health status of the CIIE was defined and evaluated based on its health characteristics in terms of stability, ascendency, development capacity, and redundancy measurements using ecological network analysis. The external health status was evaluated using the ecological entropy index system. As the primary verification of the feasibility of our proposed approach, a case study of Zhubajie was conducted. These results confirmed the feasibility of our evaluation method. With this method, the health status of CIIEs could be accurately measured, which supported the management and organization the CII systems. Future work will focus on adapting suitable measures to improve the operation of CII.

Discrimination of Plant Structures in 3D Point Cloud Through Back-Projection of Labels Derived from 2D Semantic Segmentation

In the decommissioning of the Fukushima Daiichi Nuclear Power Station, radiation dose calculations necessitate a 3D model of the workspace are performed to determine suitable measures for reducing exposure. However, the construction of a 3D model from a 3D point cloud is a costly endeavor. To separate the geometrical shape regions on 3D point cloud, we are developing a structure discrimination method using 3D and 2D deep learning to contribute to the advancement of 3D modeling automation technology. In this paper, we present a method for transferring and fusing labels to handle 2D prediction labels in 3D space. We propose an exhaustive label fusion method designed for plant facilities with intricate structures. Through evaluation on a mock-up plant dataset, we confirmed the method’s effective performance.

Exploring and measuring the health resilience of urban buildings against the pandemic: A case study of Hong Kong public housing during COVID-19

The worldwide spread of COVID-19 raises considerable concern about occupant health and pandemic prevention. The building plays a significant role in preventing and controlling the pandemic as most of the time people stay within the built environment. Even urban resilience is widely used to cope with urban changes, the concept of resilience has seldom been adopted at the building level for occupants' health during the pandemic. There is a lack of suitable measurement methods specially designed for health resilience. Consequently, this study designs the framework of “building health resilience (BHR)” to reveal buildings’ ability to resist the pandemic spread within occupants, and develops the BHR model to measure the building performance in health resilience. The case study of Hong Kong public housing under COVID-19 reveals that implementing BHR framework and measurement approach are effective for single buildings and building groups within certain areas or during different periods. This study contributes to proposing BHR and developing BHR measurement approach by considering the building scale and external pandemic situation in nearby local area of the building. The BHR model is quite flexible to adapt to diverse disturbance scenarios to quantify the BHR performance, provides valuable results to find out weak buildings during the pandemic spread, and takes targeted actions toward healthy and resilient buildings.