Hasil untuk "data science"

Cornelius A James, Sarah L Krein, Sarah Yon et al.

Abstract BackgroundMobile health (mHealth) apps are widely available, and some have proven safe and effective for management of specific chronic conditions. Despite a high degree of interest, the potential of these technologies has yet to be realized. Patient and clinician attitudes are key factors that influence the adoption of mHealth apps but remain poorly understood, particularly in the United States. ObjectiveThis study aimed to identify both patient and clinician attitudes that can influence recommending and adopting mHealth apps. MethodsUsing well-established technology adoption and implementation science frameworks, this study included a deductive content analysis using a rapid qualitative analytic method. Semistructured interviews were conducted with patients and clinicians to identify technical and material, social and personal, and policy and organizational factors that can influence the recommendation or adoption of mHealth apps. The interviews and data analysis were performed between September 2023 and August 2024. ResultsParticipants included 20 clinicians (n=12, 60% general internists) with a mean time in practice of 17 (SD 11.6) years, and 28 patients with a mean age of 59 (SD 12.1) years. A total of 7 categories related to patients’ and clinicians’ attitudes toward mHealth apps emerged: (1) apps as tools to improve health by extending care, (2) the role of apps in enhancing the patient–clinician relationship, (3) the need for simplicity and efficiency in app design, (4) the influence of prior experience with mHealth apps, (5) comfort with technology, (6) recommendations from trusted sources, and (7) education and hands-on experience. Although similar factors were considered by patients and clinicians, their views about older adults’ interest and ability to use mHealth apps differed. ConclusionsUnderstanding patient and clinician views about mHealth apps provides critical insights for developing approaches to facilitate their use. These findings suggest patients and clinicians share similar views about the benefits of mHealth apps. Nonetheless, clinicians’ perceptions about older patients’ interest and ability to use mHealth apps may negatively impact recommendation of mHealth apps and subsequent adoption by older adults.

Isabel Cristina Cadavid, Érika Frydrych Capelari, Caroline Salvati et al.

Abstract In recent years, significant efforts have been made to understand the phyllosphere microbiome. To clarify current research trends and identify knowledge gaps, we conducted a systematic review of the literature and investigated the methodologies used to analyze microbiome communities associated with plants, along with the objectives of these studies. Applying systematic review principles, we assessed 333 reports from the Web of Science database for eligibility. Articles were included if they presented original research on microbiomes associated with phyllosphere tissues identified by next-generation sequencing. Of these, 268 reports, published from 2009 to March 2025, were retrieved. These reports were used to extract data in a controlled and methodical manner. The analyses identified the most frequently studied plant species and primary tissues, the geographical locations sampled, the variables investigated in the phyllosphere microbiome, and the methodologies and tools employed. A comparison of the number of studies on below-ground (n=1562) versus above-ground tissue (n=375) underscores the relatively unexplored nature of above-ground research. We notice a surprisingly low number of studies from the Southern Hemisphere. Additionally, through data mining, we identify the most dominant bacteria and fungi reported in phyllosphere studies. Based on these findings, we offer recommendations for future research on the phyllosphere.

Nimrod Serok, Shlomo Havlin, Efrat Blumenfeld Lieberthal

Abstract We introduce a novel decentralised traffic light control strategy, termed the Tree Method, designed to mitigate the challenges posed by conflicting traffic flows operating on competing cycle times during specific phases at traffic intersections. This methodology hinges on the precise identification and subsequent prioritisation of congestion bottlenecks, assessed through their expansive influence on the entire road network. The Tree Method calculates the cost associated with each congestion tree and advances a prioritisation scheme that emphasises the global, rather than local, impact of traffic flow. To evaluate the effectiveness of this approach, we utilised the Simulation of Urban Mobility (SUMO) to conduct a series of simulations incorporating both realistic and abstract Origin-Destination (OD) matrices across varying traffic conditions. The Tree Method demonstrated a significant capability in identifying the principal contributors to congestion and their upstream effects, leading to major improvements in throughput and average travel times. Comparative analysis of the Tree Method against other, traffic light control techniques revealed superior performance also in improving conditions for the majority of drivers and across time. This means that traffic moves more smoothly through junctions, with fewer delays and shorter queues, even under heavy demand. Additionally, the simplicity of the Tree Method’s analytical framework supports real-time operational adjustments, aligning well with the dynamic feedback loops inherent in traffic flow systems. As cities face growing congestion challenges, our findings highlight a control strategy that is both effective and simple enough to be deployed in real urban environments.

Qingliang Song, Lianghao Liu, Qinhe Yang et al.

BackgroundMetabolic diseases represent a significant global public health concern, imposing substantial burdens on healthcare systems, economies, and patient quality of life. Current treatments have limitations, underscoring the need for safer alternatives. Quercetin, a natural flavonoid with favorable human tolerability, shows promise for metabolic disorder management.PurposeThis review critically evaluates the existing evidence on quercetin’s role in metabolic disease management, summarizing its pharmacological advancements and clinical data in treating nine metabolic disorders: diabetes mellitus (DM), metabolic dysfunction-associated fatty liver disease (MAFLD), obesity, atherosclerosis, hyperuricemia, gouty arthritis, hyperlipidemia, osteoporosis, and polycystic ovary syndrome (PCOS).MethodsWe systematically reviewed studies (2003-2025) from Web of Science, PubMed, Science Direct, and CNKI reporting quercetin’s effects in metabolic diseases.ResultsQuercetin exhibits multifaceted pharmacological activities, including anti-inflammatory, antioxidant, antiapoptotic, hypolipidemic, and hypoglycemic effects. This underpins its therapeutic potential against nine metabolic disorders. Furthermore, emerging nanodelivery systems have demonstrated enhanced bioavailability, stability, and overall efficacy of quercetin while mitigating its dose-dependent toxicity.ConclusionQuercetin shows considerable promise in the intervention of metabolic diseases. However, current research lacks mechanistic depth, bioavailability enhancement data, and clinical validation Additionally, clinical studies validating its therapeutic efficacy remain scarce. Further mechanistic investigations and randomized controlled trials are imperative to elucidate quercetin’s precise mechanisms and substantiate its clinical potential in metabolic disease management.

Emre Aydilek

This research aims to contribute to a macro-level understanding of the intellectual foundations of the field of political science by examining it in depth through bibliometric analysis and discovering the epistemological insights hidden in it, as well as the basic dimensions of studies in the discipline. Thus, it is objectives to provide basic data and guidance to academics working on the methodology of the discipline of political science. Accordingly, the trends, topics, and general themes of academic studies published in universally respected journals with high-impact factors in the field of political science will be identified. The article's original value is the first thorough bibliometric study of the discipline in Turkish national literature and one of the first few thorough bibliometric studies in international literature. This study conducted a brief literature review to examine key scientific texts on political science methodology that reflect general trends. Subsequently, data retrieved from two selected databases (Scopus and WoS) were analyzed and interpreted using text-mining tools (WOSviewer and R Studio). As a result of this analysis, 17 datasets and meaningful patterns emerged. Word clouds, bibliometric maps, heat maps, and word maps were obtained, which include the analysis of studies according to years, fields, types, impact values, factors, themes, trends, and countries with the most studies. The findings are interpreted in the conclusion, and a general trend in the discipline is presented.

Yingbo Li, Zihan Wang, Mariano Andres Imbert Rodriguez et al.

Abstract This study establishes a theoretical framework linking organized R&D (ORD) and mission-oriented innovation (MOI) through a collective action lens. MOI performance is evaluated using three key indicators: academic publications, Science and Technology Awards (STA), and granted patents. ORD dimensions are operationalized through research teams, human resources, academic milieu, and public funding. Leveraging survey data and archival records from 23 Chinese universities, we employ baseline regressions and structural equation modeling (SEM) to elucidate ORD’s influence pathways on MOI performance. Results indicate that research teams serve as significant mediators linking public funding, academic milieu, and human resources to MOI outcomes as well as the heterogeneous roles of ORD determinants in MOI performance. This study specifically highlights how the scale and allocation mechanisms of public funding more actively facilitate MOI performance outcomes through ORD. By integrating macro-micro connections between MOI and ORD, this research provides policymakers with targeted and actionable recommendations for enhancing MOI in higher education institutions.

Thorsten Meyer-Feil, Nicole Strutz, René Schwesig et al.

Introduction Mobilisation and mobility in clinical settings are essential to the recovery process after surgery and trauma-related hospital admission. In addition to personal support from physiotherapists and nursing staff, aids such as walkers are applied. Walkers equipped with smart features have the potential to benefit geriatric patients by facilitating routine clinical workflows and, where appropriate, by providing health professionals with information on gait patterns and vital parameters.The overarching goal of this project is to develop an innovative smart walker for clinical use, guided by three objectives: (a) Identify the feature requirements of the smart walker from the perspectives of patients and health professionals, (b) Co-design the smart walker using a user-centred approach involving older patients, health professionals and clinical engineers and (c) Pilot-test the smart walker in real time with older patients admitted to German clinics.Methods and analysis We will employ a three-phased exploratory sequential mixed-methods approach in this project. Phase I explores potentially useful characteristics of a smart walker via a scoping literature review (part 1 of phase I) and a qualitative interview and observational study, including questionnaires on sociodemographic data and technology readiness, involving four to six patients and four to eight nurses and physiotherapists (part 2 of phase I). Phase II focuses on developing and validating a smart walker through a user experience design, with at least three iterative test cycles involving a minimum of three asymptomatic participants and three to seven potential users in each cycle. Phase III comprises a pilot study conducted at a University Hospital in Germany involving at least twelve patients. Data integration takes a data-building approach, combining qualitative and quantitative results in the final analysis to generate a comprehensive understanding and to create and refine insights into the feature needs and use of a smart walker by patients.Ethics and dissemination The study was approved by the Ethics Committee of University Medicine Halle, Germany (Approval No. 2025-032; date of approval: 03/04/2025). Study results will be disseminated through peer-reviewed journals and conferences.PROSPERO registration number The study protocol was registered at the Open Science Framework Platform (OSF, register number: 10.17605/OSF.IO/CTPF4).

Dr. Emily Carter

Data science is playing an increasingly vital role in disaster preparedness and recovery by providing real-time insights, predictive analytics, and AI-driven decision support systems. By leveraging big data, remote sensing, and machine learning algorithms, emergency response teams can enhance disaster forecasting, optimize resource allocation, and improve post-disaster recovery efforts. This paper explores the applications of data science in disaster management, covering areas such as AI-powered risk assessment, real-time disaster monitoring, and predictive analytics for early warning systems. Additionally, challenges such as data accuracy, integration with existing emergency frameworks, and ethical considerations in crisis response are discussed, along with emerging trends in AI-driven disaster resilience..

Emily Carter

Data science is playing a transformative role in mental health care by enabling early diagnosis, personalized treatment plans, and real-time monitoring of patients. By leveraging big data analytics, artificial intelligence (AI), and machine learning (ML), mental health professionals can analyze patient behaviors, detect patterns, and predict risks. This paper explores the applications of data science in mental health care, covering key areas such as AI-powered mental health chatbots, predictive analytics for early diagnosis, and digital biomarkers for psychiatric disorders. Additionally, challenges such as data privacy concerns, ethical considerations, and model biases are discussed, along with emerging trends in AI-driven mental health interventions

Nimantha Karunathilaka, Christina Parker, Peter A. Lazzarini et al.

Abstract Background Recent evidence suggests that diabetes-related lower-extremity complications (DRLECs) may be associated with cognitive changes in people with diabetes. However, existing literature has produced inconsistent findings, and no systematic reviews have been conducted to investigate whether DRLECs impact the cognition of people with diabetes. This systematic review evaluated existing studies that investigated cognition in people with diabetes with DRLECs and without DRLECs. Method Seven databases; MEDLINE, PubMed, CINAHL, EMBASE, Cochrane, PsycINFO and Web of Science were searched from inception until 22/8/2022 for studies that compared cognition in people with diabetes with and without DRLECs. Results were independently screened for eligibility and assessed for methodological quality by two authors, with key data extracted. Studies were eligible for meta-analysis if the studies reported similar cases, controls, and outcome measures. Results Thirteen studies were included in the review, with eleven of medium methodological quality, one of high quality, and one of low quality. Four studies found significant differences in cognition between those with and without DRLECs, four found significant associations between diabetes-related lower-extremity complications and cognition, and five found no differences or associations. One small meta-analysis of eligible studies found that there was no statistically significant difference in cognition in people without, compared to with, peripheral neuropathy (Mean difference = -0.49; 95%CI: -1.59–0.61; N = 3; n = 215). Leave-one-out sensitivity analyses further confirmed that there was no significant difference in cognition among people with and without peripheral neuropathy (p > 0.05). Conclusion DRLECs may be related to cognition in people with diabetes, however, existing evidence is unclear due to variability in used methodologies that may challenge concluding the findings. Future high-quality studies investigating cognition among people with and without DRLECs are needed.

Peide Liu, Baoying Zhu, Mingyan Yang et al.

High-quality marine economic development (HMED) is regarded as a new development pattern of the marine economy in China. This paper aims to examine the dynamic changes and improvement strategies of HMED from the perspective of the green total factor productivity (GTFP) growth. First, the GTFP growth of the marine economy in China’s coastal regions for the period 2007–2020 is calculated using the bootstrapped Malmquist index. Second, the dynamic changes and spatial impacts of the GTFP growth are characterized using kernel density estimation (KDE). Moreover, a novel analytical framework to study the improvement strategies of the GTFP is developed. Within this framework, the fuzzy set qualitative comparative analysis (fsQCA) method is used to explore the paths to achieve HMED. The findings show that: (i) the GTFP growth for coastal regions shows significant fluctuations, suggesting that a stable pattern of marine economic development has yet to be established; (ii) the regional distribution of GTFP growth varies significantly, with provinces with fast GTFP growth gathering resources from neighboring provinces, resulting in a siphon effect; (iii) for coastal provinces that lack certain development conditions, the combined effect of other advantageous factors can be used to achieve HMED. Finally, this study presents policy recommendations for achieving HMED, which can provide insights into the design of China’s future marine economic policies. First published online 10 September 2024

Haiyan Yu

Muhammad Salman, Salah Uddin Khan, Mansour Shrahili

Rotator cuff (RC) tendinopathy is the most debilitating musculoskeletal condition in general population and is considered to be the third commonly encountered musculoskeltal (MSK) disorder. After getting approval from ethical review committee (ERC) of Rawal Institute of Health Sciences, this Randomized control trail was initiated at Rawal General & Dental Hospital. The duration of this study was 6 months from March 10, 2023 to August 09, 2023. Forty patients of both genders between the age of 25 and 50 years who were suffering from RC tendinopathy were included in this study. Those who had any kind of cardiac complications, neurological disorders, or diabetes mellitus were excluded from this study. Two equal groups ( n = 20 each) were formed. Group A was given kinesio tape (KT) and group B was treated with dry needling (DN). Totally six sessions of each intervention were given to each patient at the rate of two sessions per week along with 10 min of interferential therapy and 10 min of moist packs to each patient. Statistical package for social science (SPSS) version 21 and Microsoft excel were used for the analysis of data. The mean ± standard deviation (SD) of age in group A was 35.30±8.07 and in group B it was 31.51 ± 2.46. The median and interquartile range (IQR) of SF-36 [quality of life (QoL)] at the baseline was 37.64 (1.75) in group A and 37.38 (1.31) in group B, respectively. Md (IQR) postinterventional improved with 91.31 (8.20) in group A, and in group B it was 90.37 (15.78) with P < 0.05. Within-group analysis showed a significant difference ( P < 0.05) in each group. Between-group analysis depicted a significant difference ( P < 0.05) on the Pain Numeric Scale score and an insignificant difference ( P > 0.05) on the basis of QoL (SF-36). It was revealed that KT is more effective in the reduction of disability in terms of pain as compared to DN whereas both interventions are equally effective in improving the QoL in RC tendinopathy.

Yiqing Yan, Nimesh Pinnamaneni, Sachin Chalapati et al.

Abstract DNA is a promising candidate for long-term data storage due to its high density and endurance. The key challenge in DNA storage today is the cost of synthesis. In this work, we propose composite motifs, a framework that uses a mixture of prefabricated motifs as building blocks to reduce synthesis cost by scaling logical density. To write data, we introduce Bridge Oligonucleotide Assembly, an enzymatic ligation technique for synthesizing oligos based on composite motifs. To sequence data, we introduce Direct Oligonucleotide Sequencing, a nanopore-based technique to sequence short oligos, eliminating common preparatory steps like DNA assembly, amplification and end-prep. To decode data, we introduce Motif-Search, a novel consensus caller that provides accurate reconstruction despite synthesis and sequencing errors. Using the proposed methods, we present an end-to-end experiment where we store the text “HelloWorld” at a logical density of 84 bits/cycle (14–42× improvement over state-of-the-art).

elisha blessing

In the contemporary landscape of international business and financial services, a paradigm shift is underway with the advent of the Data Revolution. This transformation is propelled by the unprecedented growth and accessibility of data, coupled with advancements in analytics and data science. This abstract provides an overview of the multifaceted impact of the Data Revolution on global business and financial services, highlighting its potential to usher in a new era of innovation, efficiency, and strategic decision-making.The convergence of Analytics, Big Data, and Data Science has created an ecosystem where organizations can derive actionable insights from vast and diverse datasets. The sheer volume and variety of data available today empower businesses to make informed decisions, optimize processes, and identify previously unseen opportunities. In the realm of international business, this translates into enhanced cross-border collaborations, improved supply chain management, and a more profound understanding of global market dynamics.Financial services, as a crucial component of the global economy, are experiencing a renaissance driven by the Data Revolution. The integration of advanced analytics and machine learning algorithms allows financial institutions to refine risk management strategies, detect fraudulent activities with greater accuracy, and personalize services for clients based on comprehensive data profiles. This not only enhances the overall efficiency of financial services but also fosters a more resilient and adaptive financial ecosystem.Furthermore, the abstract explores the role of data in shaping the future of decision-making in international business and financial services. The ability to harness data-driven insights empowers executives and policymakers to navigate complex geopolitical landscapes, anticipate market trends, and proactively address emerging challenges. As a result, the Data Revolution serves as a catalyst for informed and strategic decision-making, fostering a climate of adaptability and resilience in the face of global uncertainties.In conclusion, the Data Revolution is reshaping the landscape of international business and financial services, offering unprecedented opportunities for innovation and growth. Organizations that embrace the full potential of analytics, Big Data, and data science are poised to lead in this era of transformative change. This abstract sets the stage for a comprehensive exploration of the manifold implications and applications of the Data Revolution in the realms of global business and financial services.

Sofia Fernandes, Ana F Oliveira, Juliana D Reis et al.

Introduction In recent years, growing attention has been given to the study of the impact of cancer-related cognitive impairment (CRCI) in working non-central nervous system (CNS) cancer survivors. Available literature has shown that working cancer survivors identify cognitive problems at work as very problematic and worrisome. Some reviews have discussed the association between CRCI and work-related outcomes; however, none to date have investigated this association through comprehensive systematic review with meta-analysis. Hence, this work will comprehensively summarise existing evidence from quantitative studies assessing the relationship between CRCI and work-related outcomes of adult non-CNS cancer survivors at working age.Methods and analysis The systematic review procedures and its report will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Electronic searches in the databases Web of Science, Scopus, PubMed, ProQuest, PsycINFO and CINAHL, complemented by a manual search of other relevant articles, will be performed from 2000 onwards to identify relevant publications. Two independent reviewers will assess studies for inclusion and extract data from each article using a standardised form. Studies eligible for inclusion must be quantitative, contain adult non-CNS cancer survivors with CRCI, and a measure of cognitive functioning and work-related outcomes. To assess risk of bias, the Joanna Briggs Institute Critical Appraisal Tool Studies checklists will be independently used by the two researchers. Synthesis of the included articles will be conducted using a narrative method and through meta-analysis. Meta-analysis will be reported via correlation for the association between CRCI and work-related outcomes. The cumulative evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation system.Ethics and dissemination Ethics approval is not required since individual patient data will not be collected. The findings will be published in a peer-review indexed journal, presented at scientific meetings and included in a chapter of a Doctoral thesis.PROSPERO registration number CRD42020165458.

Anibal Alviz-Meza, Manuel H. Vásquez-Coronado, Jorge G. Delgado-Caramutti et al.

Abstract Using past material and spiritual remains, cultural heritage examines communities’ identity formation across time. Cultural heritage requires public and private institutions to care about its restoration, maintenance, conservation, and promotion. Through a bibliometric perspective, this study has analyzed, quantified, and mapped the scientific production of the fourth industrial revolution applied to heritage studies from 2016 to 2021 in the Scopus and Web of Science databases. Biblioshiny software from RStudio was employed to categorize and evaluate the contribution of authors, countries, institutions, and journals. In addition, VOSviewer was used to visualize their collaboration networks. As a main result, we found that augmented reality and remote sensing represent the research hotspot concerning heritage studies. Those techniques have become common in archaeology, as well as museums, leading to an increase in their activity. Perhaps, more recent tools, such as machine learning and deep learning, will provide future pathways in cultural heritage from data collected in social networks. This bibliometric analysis, therefore, provides an updated perspective of the implementations of technologies from industry 4.0 in heritage science as a possible guideline for future worldwide research.

Jean Ichter, Olivier Gargominy, Marie-France Leccia et al.

An All Taxa Biodiversity Inventory (ATBI) is a comprehensive inventory of all species in a given territory. In 2007, the French Parc national du Mercantour and the Italian Parco Naturale Alpi Marittime started the first and most ambitious ATBI in Europe with more than 350 specialists and dozens of technicians and data managers involved.The ATBI datasets from the Parc national du Mercantour in France are now publicly available. Between 2007 and 2020, 247,674 occurrences were recorded, checked and published in the INPN information system. All this information is available in open access in the GBIF web site. With 12,640 species registered, the ATBI is the most important inventory in France. This data paper provides an overview of main results and its contribution to the French National Inventory of Natural Heritage. It includes a list of 52 taxa new to science and 53 species new to France, discovered thanks to the ATBI.

Likun Han, Xunming Wang, Zhixin Hao et al.

Climate changes and its influences on human society are of increasing concern in science communities. Based on the reconstructed climate data and CENTURY model, we simulated net primary productivity of grassland and the grain yield of highland barley during the pre-industrial millennium in Ali Prefecture, Tibet Autonomous Region. It showed that the variation of precipitation and temperature together affected the fluctuation of land productivity. Wavelet analysis results showed that the land productivity in Ali fluctuated within main periodic bands of 180 yr. We found that the rise and falls of the Guge Kingdom in Ali was synchronic with the fluctuation of land productivity, and the collapse of the Guge Kingdom was obviously related to the sudden change of climate in the 17th century, which turned dry and cold. By combining with historical studies, this study further proposes the mechanism of land productivity fluctuation under climate change on Guge Kingdom. Our findings are helpful to understand the relationship between climate change and social vulnerability, especially providing a typical case study of ancient plateau countries.

Saadeh R, Khader Y, Alyahya M et al.

Rami Saadeh,1 Yousef Khader,1 Mohammad Alyahya,2 Majid Al-Samawi,1 Mohammed Z Allouh3,4 1Department of Public Health and Community Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan; 2Department of Health Management and Policy, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan; 3Department of Anatomy, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates; 4Department of Anatomy, Faculty of Medicine, Jordan University of Science and Technology, Irbid, JordanCorrespondence: Mohammed Z Allouh, Department of Anatomy, College of Medicine and Health Sciences, United Arab Emirates University, P. O. Box: 15551, Al Ain, United Arab Emirates, Tel +97 137 137 551, Email m_allouh@uaeu.ac.aePurpose: To identify areas that need improvement in Jordanian health centers regarding infection prevention and control (IPC) programs; water, sanitation, and hygiene (WASH) services; and other protective measures, especially in the context of coronavirus disease (COVID-19).Methods: This is a national assessment study that comprised hospitals of different sectors in Jordan, including, Ministry of Health (MoH), private, and military hospitals. The study included 23 Jordanian hospitals. Assessment tools were developed and adapted mainly from the WASH Facility Improvement Tool (WASH FIT) and other tools. Hospitals were assessed to meet targets based on whether indicators were fully met, partially met, or not met.Results: The mean percentage of the 150 indicators that met the standards was 83.2% (72.6% for MoH, 84.5% for private, and 90.4% for military hospitals). The percentage of indicators, both WASH/IPC and training and education indicators, that met the targets were higher in military hospitals than in MoH and private hospitals. However, in context of COVID-19, only 64.7% of indicators related to precautionary measures were met by all hospitals.Conclusion: The data available on WASH/IPC in Jordan are scarce, and the study findings will help in preventing severe consequences of the COVID-19 pandemic. There is scope for improvement in many WASH/IPC aspects, and urgent actions should be taken, especially to fill the gaps in COVID-19 precautionary measures.Keywords: COVID-19, healthcare, hospitals, infection control, waste management