Basic Statistics Research Articles

Risk-Informed Performance-Based methods for cyber-attack on nuclear power facilities

A new approach is described that offers a Risk-Informed Performance-Based (RIPB) framework for quantifying the risk associated with a cyber-attack on a nuclear power-generating facility. The first part of the method involves 1) the creation of a simplified 10 CFR 73.54 compliant cyber infrastructure, 2) modeling of design basis threats against the network and passive defense of the network and 3) applying the model metrics as inputs into a Bayesian analysis to calculate the exploit probability of a plant controller. The RAVEN code package was used to perform a stochastic calculation to quantify the aleatory uncertainty associated with exploiting a plant controller and produce basic statistics associated with those outputs, such as the standard deviation and standard error. Other tools, such as ADAPT, were also explored, which could be leveraged for direct DPRA analysis of network topology, such that new failure modes or initiating events could be discovered. The second aspect of the RIPB method considers the impact of the controller on the physical plant. This evaluation was conducted by postulating an accident scenario possibly caused by the dynamics of an exploited process controller, initiating that event in a RELAP5 model controlled by the RAVEN risk analysis package, and demonstrating the types of algorithms that can be used to quantify the consequences of the accident scenario. The new two-part method explored in this work provides the uncertainty associated with a cyber-initiating event and the associated consequences of a postulated accident resulting from that exploit, as well as example tools and algorithms for performing the analysis.

Direct numerical simulations of compressible turbulent channel flows with asymmetric thermal walls

This paper extends the work of Tamano & Morinishi (J. Fluid Mech., vol. 548, 2006, pp. 361–373) by simulating supersonic turbulent channel flow with asymmetric thermal walls using a larger computational domain and a finer mesh. Direct numerical simulation is carried out for four cases with different thermal wall boundaries at the top wall at fixed $Ma=1.5$ , $Re=6000$ and $Pr=0.72$ , while the bottom wall is maintained at a constant temperature of $T_L$ equal to the reference temperature. These cases are referred to as the adiabatic case TAd, where the top wall is adiabatic; the pseudo-adiabatic case T32, where the top wall is isothermal with temperature $T_{w,t}=T_A$ ; the sub-adiabatic case T25, with $T_{w,t}=0.77T_A$ ; and the super-adiabatic case T40, with $T_{w,t}=1.24T_A$ . Here, $T_A=3.234$ is the mean temperature at the adiabatic wall in the TAd case. The objective of this study is to compare and contrast the TAd case with its corresponding T32 case, and to investigate the effect of the wall temperature difference between the two isothermal walls. Comparisons of the basic turbulent statistics, the heat transfer between the Favre-averaged mean-flow kinetic energy, the Favre-averaged turbulent kinetic energy and the Favre-averaged mean internal energy, as well as the wall heat transfer properties, indicate that the TAd case and its corresponding T32 case are generally equivalent. The only discernible difference is in the region very close to the top wall for the temperature-fluctuation-related quantities. The analysis reveals that the asymmetry of the thermal walls causes asymmetry in the flow and thermal fields. In addition, the transfer of the heat generated by the pressure dilatation and the viscous stress is facilitated by the turbulent heat flux term and the mean molecular heat flux term.

LITERATURE REVIEW: BASIC STATISTICS IN EDUCATIONAL RESEARCH

This paper provides a comprehensive exploration of the role and significance of basic statistics in educational research. Drawing upon historical foundations and theoretical frameworks, the study elucidates the evolution of statistical methodologies and their application in understanding complex educational phenomena. Key pioneers such as Francis Galton and Karl Pearson are highlighted for their foundational contributions, laying the groundwork for statistical analysis in education. The paper examines various statistical techniques, including descriptive and inferential statistics, correlation analysis, regression analysis, and analysis of variance (ANOVA), showcasing their relevance in analyzing diverse aspects of teaching, learning, and educational outcomes. Moreover, the integration of statistical methodologies into educational research is examined across domains such as educational management, policy-making, and teaching practice, emphasizing their role in informed decision-making, resource allocation, and policy formulation. Despite the benefits, challenges such as sample bias and misapplication of statistical tests are acknowledged, underscoring the importance of methodological rigor and statistical literacy among researchers and practitioners. Looking ahead, the paper discusses future directions in educational research, including the integration of advanced statistical techniques and efforts to promote statistical literacy. Overall, this paper offers a comprehensive framework for understanding the complexities of basic statistics in educational research, highlighting its transformative potential in driving positive change and innovation within the education sector.

Cooperative Society: A Veritable Tool for Wealth Creation and Poverty Alleviation in Bayelsa State

Concerns have also been raised about cooperative organisations' efforts to reduce poverty and generate wealth in the communities in which they operate. Most cooperatives fail to achieve their goal of enhancing members' financial security and well-being, which ultimately results in their dissolution. Thus, this study looked at how cooperative societies in Bayelsa state contribute to wealth development and poverty reduction. In order to accomplish its goals, the study employed a survey research methodology with a structured questionnaire, which was analysed using chi-square and basic descriptive statistics. The study's findings showed that cooperatives help members acquire assets both directly and indirectly (in the form of cash or in kind). The support of cooperative society has enabled the acquisition of a variety of assets, including buildings, cars, gadgets, and land. This helped each member achieve their needs for safety and physiology while also improving the people's economic situation. Members who gained assets after they satisfied their fundamental needs were able to transcend extreme poverty. Asset acquisition is a physical economic progress. Here, cooperatives function as both major contributors to and agents of poverty alleviation. Therefore, in order for cooperative society activities to continue having a good influence on the livelihood of its members in Bayelsa state, it is advised that they be appropriately governed by the government and the relevant agencies.

Eurasian aspen (Populus tremula L.): Central Europe's keystone species 'hiding in plain sight'.

Knowledge of Eurasian aspen's (Populus tremula L.) ecological and growth characteristics is of high importance to plant and wildlife community ecology, and noncommercial forest ecosystem services. This research assessed these characteristics, identified aspen's habitat optimum, and examined causality of its current scarce distribution in central Europe. We analyzed a robust database of field measurements (4,656,130 stands) for forest management planning over 78,000 km2 of the Czech territory. Our analysis we used GIS techniques, with basic and multivariate statistics such as general linear models, ordination, and classification. Results describe a species of broad ecological amplitude that has heretofore attracted little research attention. Spatial analysis showed significant differences between aspen and other forest non-forest cover types. Additionally, we found significant association between the proportion of aspen in a stand, the size of forest property, and the forest category. The results demonstrate historic reasons for aspen's widespread presence, though contemporary occurrence is limited. This study advances the concept of a quantitatively based aspen ecological optimum (niche), which we believe may be beneficial for numerous aspen associates in the context of anticipated warming. Irrespective of local ecology (i.e., the realized aspen niche), the study confirms that profit-driven policy in forestry is chiefly responsible for historic aspen denudation in central Europe. Even so, we demonstrate that ample habitat is present. Further solutions for improving aspen resilience are provided to support these keystone systems so vital to myriad dependent flora and fauna.

Sustainable goods transport – inland navigation

Inland navigation plays a crucial role in goods transport, facilitating the movement of goods via rivers and canals. Sustainability in Goods transport involves reducing environmental impact, promoting social responsibility, and enhancing efficiency. Sustainability in goods transport includes optimising transportation routes, investing in fuel-efficient vehicles, and promoting alternative fuels. Green technologies such as GPS tracking and route optimisation software can improve efficiency. Encouraging sustainable packaging materials and carbon offsetting can further reduce environmental impact. Inland navigation can be greener by adopting alternative fuels, improving vessel efficiency, and optimising routes. Maintenance and modernisation of infrastructure, environmental protection measures, and modal shifts from road transport also contribute to sustainability. Various factors influence the performance of inland navigation, including infrastructure, water levels, vessel characteristics, regulations, economic conditions, technological advancements, environmental factors, and social considerations. Integrating sustainable practices and addressing these factors can lead to a more environmentally friendly and efficient goods water transport system. This paper investigates the connections between inland goods transport and sustainability, identifying the main factors. Some basic statistics were collected and analysed to show the performance of inland navigation. The analysis showed that inland navigation is very diverse in Europe, Western Europe is more developed than Eastern European countries. In conclusion, it can be stated that many factors influence the development of Eastern European inland navigation.

Profiling English sentences based on CEFR levels

Abstract The study aims to demonstrate the procedure for constructing the CEFR-based Sentence Profile (CEFR-SP), a dataset with the CEFR levels assigned for sentences, and to identify the characteristics at each level. Basic statistics such as word length and sentence length are presented for each CEFR level for 7,511 carefully selected sentences, and statistical tests are conducted between adjacent levels to identify criterial features. The findings reveal significant differences in word length between adjacent levels, while word difficulty is not significant in discriminating levels at either end (A1–A2, C1–C2). Sentence length and depth are also not significant discriminators for higher levels (B2–C1, C1–C2). Notably, sentence-level data generally exhibit discriminative values compared to text-level statistics, indicating their direct capture of characteristics at each CEFR level.

“R” U ready?: a case study using R to analyze changes in gene expression during evolution

As high-throughput methods become more common, training undergraduates to analyze data must include having them generate informative summaries of large datasets. This flexible case study provides an opportunity for undergraduate students to become familiar with the capabilities of R programming in the context of high-throughput evolutionary data collected using macroarrays. The story line introduces a recent graduate hired at a biotech firm and tasked with analysis and visualization of changes in gene expression from 20,000 generations of the Lenski Lab’s Long-Term Evolution Experiment (LTEE). Our main character is not familiar with R and is guided by a coworker to learn about this platform. Initially this involves a step-by-step analysis of the small Iris dataset built into R which includes sepal and petal length of three species of irises. Practice calculating summary statistics and correlations, and making histograms and scatter plots, prepares the protagonist to perform similar analyses with the LTEE dataset. In the LTEE module, students analyze gene expression data from the long-term evolutionary experiments, developing their skills in manipulating and interpreting large scientific datasets through visualizations and statistical analysis. Prerequisite knowledge is basic statistics, the Central Dogma, and basic evolutionary principles. The Iris module provides hands-on experience using R programming to explore and visualize a simple dataset; it can be used independently as an introduction to R for biological data or skipped if students already have some experience with R. Both modules emphasize understanding the utility of R, rather than creation of original code. Pilot testing showed the case study was well-received by students and faculty, who described it as a clear introduction to R and appreciated the value of R for visualizing and analyzing large datasets.

Predicting mechanical neck pain intensity in computer professionals using machine learning: identification and correlation of key features.

Mechanical neck pain has become prevalent among computer professionals possibly because of prolonged computer use. This study aimed to investigate the relationship between neck pain intensity, anthropometric metrics, cervical range of motion, and related disabilities using advanced machine learning techniques. This study involved 75 computer professionals, comprising 27 men and 48 women, aged between 25 and 44 years, all of whom reported neck pain following extended computer sessions. The study utilized various tools, including the visual analog scale (VAS) for pain measurement, anthropometric tools for body metrics, a Universal Goniometer for cervical ROM, and the Neck Disability Index (NDI). For data analysis, the study employed SPSS (v16.0) for basic statistics and a suite of machine-learning algorithms to discern feature importance. The capability of the kNN algorithm is evaluated using its confusion matrix. The "NDI Score (%)" consistently emerged as the most significant feature across various algorithms, while metrics like age and computer usage hours varied in their rankings. Anthropometric results, such as BMI and body circumference, did not maintain consistent ranks across algorithms. The confusion matrix notably demonstrated its classification process for different VAS scores (mild, moderate, and severe). The findings indicated that 56% of the pain intensity, as measured by the VAS, could be accurately predicted by the dataset. Machine learning clarifies the system dynamics of neck pain among computer professionals and highlights the need for different algorithms to gain a comprehensive understanding. Such insights pave the way for creating tailored ergonomic solutions and health campaigns for this population.

Sometimes less is more: experience with endoscopic myringoplasty.

A retrospective review of the outcomes of patients who underwent endoscopic myringoplasties in our institution was conducted. The aim was to highlight our results with this procedure. The database of patient records was manually checked, and the patients who had undergone Endoscopic Myringoplasties were identified, and their demographics, admitting notes, operating notes, and discharge summaries were reviewed. Graft failure was considered if the patient had a perforation in the graft during the outpatient follow-up. The information was compiled, and basic statistics were derived. A total of 31 patients were identified who had undergone Endoscopic Myringoplasty. Patients' age ranged from 14-52 years. None of the patients developed any immediate postoperative complications. Follow-up otoscopic examination showed 28 patients with an intact graft and only one patient with graft failure. Two patients were lost to follow up. Our success rate with Endoscopic Myringoplasty is 96.6%, which is comparable to the international standard success rate of 80-95%. The results of this study encourage adopting an endoscopic approach where the expertise is available.

Climate change, biodiversity loss, and Indigenous Peoples' health and wellbeing: A systematic umbrella review.

Indigenous Peoples worldwide are experiencing a cascade of impacts on their health and wellbeing as a result of climate change and biodiversity loss. Existing literature at the interface of climate change, biodiversity loss, and Indigenous health tells us that Indigenous Peoples are among those most disproportionately and acutely affected by these impacts. Yet, a gap exists with respect to comprehensively and critically synthesizing the impacts reported across this literature and identifying Indigenous-led responses. Guided by an Indigenous advisory group, we employed a systematic umbrella review methodology, following PRISMA guidelines, to characterize the global secondary literature (PROSPERO registration #: CRD42023417060). In so doing, we identified the proximal, intermediate, distal, and gendered impacts of climate change and biodiversity loss on Indigenous health and wellbeing as well as Indigenous-led responses. Five databases were searched for published reviews, along with a grey literature search that focused on underrepresented geographic regions in the academic literature. Two independent reviewers conducted two-stage screening, data extraction, and quality assessment of retrieved records. Basic descriptive statistics were calculated. Qualitative data were analyzed thematically, using a constant comparative approach. A total of 38 review articles met the eligibility criteria and 37 grey literature records were retrieved and included in the review. Reviews were published between 2010-2023 and geographically clustered in the Circumpolar North. Intersecting proximal, intermediate, and distal impacts were characterized as place-based and specific, and linked to colonialism as an antecedent to and driver of these impacts. Gendered impacts were underexplored within reviews. Reviewed literature underscored the value of engaging diverse knowledge systems; platforming localized, community-led adaptation to climate change and biodiversity loss, while addressing sociopolitical constraints to these efforts; and applying a broader conceptualization of health that aligns with Indigenous frameworks. Going forward, we must foreground equity- and rights-based considerations within integrated responses to climate and biodiversity crises.

ПРОГРАМНЕ ЗАБЕЗПЕЧЕННЯ РОЗУМНОГО ГОДИННИКА ДЛЯ САМОСТІЙНИХ ЗАНЯТЬ СПОРТОМ ТА ФІТНЕСОМ

According to available statistics, the most popular smart watch among users is the Apple Watch. Today, there are more than 100 million unique users of this device, 75% of whom use it for sports. With a wide array of different sensors to track a user's physical parameters, neither Apple nor third-party developers have yet developed software to systematize all the collected data to improve an athlete's physical pa-rameters and achieve personal athletic goals. The purpose of the research is to find the possibility of improving the physical parameters of a novice athlete by means of a comprehensive analysis of his activity data collected by a smart watch and creating more personalized recommendations during training based on this data. There are many fitness apps available for the Apple Watch, each with its own unique features and features. Unfortunately, none of the analyzed applications pro-vide sufficient information regarding the correct execution of training and the collec-tion of indicators, which is a disadvantage for users who want to do sports without risks to their health. One of the main challenges of software development for smartwatches is the lack of extensive monetization opportunities. This led to the lack of interest of large companies and teams in this type of software. Small screen size and limited process-ing power compared to desktop or mobile devices are also issues. This means that developers must optimize both the user interface and the algorithms of their software product to increase the speed of the application. Another challenge is the diversity of the smartwatch market, where different devices run on different operating systems and have different hardware specifications. You have to consider the specifics and limitations of each device and platform and make sure that your apps are optimized for each of them, or focus on building your software products for only a limited num-ber of devices. Due to the lack of tools for developing applications for several platforms at once, the path of developing an application for only one platform - for WatchOS - was chosen. Also, one of the goals is to create an application that is completely autono-mous from a smartphone. For this, a simple and minimalistic interface and a simple algorithm for analyzing training data have been developed. The proposed application is focused on running. Statistics will be collected dur-ing the first few training sessions. After starting the activity, the application will start displaying all the standard information, such as pace, heart rate, activity time, dis-tance traveled. This data comes from the sensors and modules of the smart watch. When basic training statistics are collected, the app will begin to display tips on how to continue training.

Comparison of injury risk indicators in amateur female rugby players from different countries

Background: Most specific rugby movements require an efficient stretch-shortening cycle (SSC). Reactive strength index (RSI) and leg stiffness have been considered a reliable measure of SSC capability and an indicator of ACL injury risk. The aim of this study was to assess and compare absolute leg stiffness (ALS) and RSI in amateur female rugby players from different countries.Methods: Players of three female rugby teams participated in the study: the female Czech team, the junior female Czech team, and the female university English team. Twenty repetitions of the submaximal bilateral hopping test were used for the calculation of ALS. RSI was obtained from 5 repetitions of the maximum hop test. Results: The values of the basic statistics were as follows: the female Czech team (median, mean SD): ALS, 25.3 kNm–1, 25.4 3.6 kNm–1; RSI, 0.53, 0.60 0.24; the junior female Czech team (median, mean SD): ALS, 22.7 kNm–1, 23.1 4.6 kNm–1; RSI, 0.37, 0.42 0.19, and the female university English team (median, mean SD): ALS, 22.7 kNm–1, 24.0 3.5 kNm–1; RSI, 0.61, 0.59 0.20. Only a between-group comparison of RSI of the female Czech team and the junior female Czech team (p = 0.04, r = 0.37, medium effect) showed significant differences. Conclusion: No significant differences between groups were found, except for Czech teams of different ages in RSI. The lower values of ALS and RSI compared to other studies can potentially be associated with a higher risk of ACL injury.

Measuring the digital behavior for health purposes of the Garifuna community in Atlántida, Honduras

Historically, the Garifuna community has been relegated to northern Honduras. The access indicators for the behavior in telecommunications services of this ethnic group are not known in depth. A sample has been chosen to study variables such as hours of use of computers and mobiles, the monthly budget for telecommunications services, and characterization of complementary final services, especially the behavior and digital knowledge from the intersection of technology together with an aspect of common knowledge among the Garifuna, which in this case is proposed to carry out the analysis to be able to encourage and promote health in terms of the prevention of sexually transmitted diseases (STD). Data were collected electronically using an instrument between January and May 2022. In the behavior and knowledge of digital technologies, basic statistics have been used to analyze quantitative data, but an unstructured text analysis algorithm has been used, together with graph theory, to find the relationships between the terms used by the participants. The result has been widespread access to telecommunications services, but there is also low knowledge of the basic concepts associated with these technologies. Keywords: Digital behavior; Garifuna; algorithm; ICT; mobile services

Reliability Model of Medical Equipment in University of Port Teaching Hospital

In this research, on medical equipment maintainability and reliability we conducted basic statistics analysis using University of Port Harcourt Teaching Hospital as the case study; the data collected covered 18 departments, namely; Anatomical Pathology, Micro Biology, Chemical Pathology Laboratory, Radiography Department, Pediatrics, Hemodialialysis, Hematology and Blood Transfusion, Physiotherapy, Dental Department, MDR-TB unit, Pharmacy, ICU, Assisted Conception Unit, Orthopedic Ward, Care for Elderly Laboratory, Family Planning Unit, Community Medicine and Labour Ward. The results of the parametric Weibull distribution percentile suggested that the reliability of the devices tends to fail every 21 days. The reliability plot of the model indicated that the devices tend to decrease its life span with age, the Weibull model was adequately fitted following the results of Anderson adjust test of goodness of fit and the probability plot. In comparison, the Probability value of goodness of fit P(0.0000) of Weibull distribution model was compared with that of exponential distribution model P(0.034), the outcome showed that Weibull distribution is better to model the data of medical equipment in University of Port Harcourt Teaching Hospital.

Assessment of Genetic Variability, Heritability and Genetic Advance for Seed Yield and Its Contributing Traits in Greengram [Vigna radiata (L.) Wilczek

Vigna radiata L. Wilczek, sometimes known as greengram or mungbean, is a popular pulse crop in India. Most of its cultivation takes place in India's subsistence farming systems. It is cultivated in three distinct seasons in India, despite the extremely low average productivity. Due to the crop's extensive growth in a variety of environmental circumstances, the local germplasm exhibits a high degree of genetic variation. In order to determine the genetic variability, heritability, and genetic advancement of 40 green gram genotypes, a study utilizing twelve quantitative variables was conducted. For every traits, significant variance was discovered using basic descriptive statistics. High Phenotypic Coefficients of Variation (PCV) and high Genotypic Coefficients of Variation (GCV) were identified for seed yield per plant, number of branches per plant, number of clusters per plant, biological yield per plant, number of pods per plant and 100 seed weight. Moderate PCV and GCV values observed for number of seeds per pod, plant height, harvest index, pod length and days to 50% flowering, whereas low PCV and GCV values were observed for days to maturity. Most of the characters studied in the current study had high estimates of heritability coupled with high to moderate genetic advance as a percentage of mean. This may be attributed to the preponderance of additive gene action and their high selective value, meaning that selection pressure can be applied profitably to these characters to improve them rationally.

Peningkatan Kompetensi dan Skill Petugas Statistik Diskominfo Provinsi Jambi melalui Pelatihan Penggunaan Software Mortpak dan PAST 4.03 serta Platform Canva

The Jambi Province Communication and Information Office (Dinas Kominfo) is an agency who carry out work based on Law Number 23 of 2014 concerning Government Regions, with one of the affairs being the main task and function, namely statistical affairs sectoral. Regional Sectoral Statistics Performance refers to Presidential Regulation Number 39 of 2019 concerning One Indonesian Data (SDI), BPS Perka Number 4 of 2019 concerning the Implementation of Regional Sectoral Statistics. According to Law No. 16 of 1997 concerning Statistics, the types of statistics based on the purpose of their use consist of basic statistics which fully organized by BPS, sectoral statistics carried out by government agencies independently or together with BPS, as well as special statistics organized by institutions, organizations, individuals, and or other elements of society independently or together with BPS. Results Statistics organized by BPS are published in the Official Statistics Gazette (BRS) regularly and transparent so that the public can easily find out and or obtain the required data. Law No. 16/1997 also stipulates the establishment of the Statistical Society Forum as a forum to accommodate the aspirations of the statistical community, which is tasked with providing advice and consideration to BPS. These important points realize the implementation of the National Statistical System reliable and, effective. The role of Sectoral Statistics that must be carried out by the Ministry of Communication and Informatics is related to the provision of data development sector, assisting statistical activities in Other institutions, as well as any performance related to the methodology, education, and training in sectoral statistics. Data collection, presentation, and publication of quality data by the Ministry of Communication and Informatics, cannot be separated from the role of officers statisticians and data collectors. With regard to this Community Service (PPM) Program, the PPM Team In general, it is observed that in carrying out their work, Field Data Collecting Officers and Data Entry Officers often experience difficulties in terms of classification of data for each sector that is a priority for development, especially sectors Environment and Ecology. Entry clerks sometimes only present data individually descriptive in Ms. Excel, without being processed and without further analysis on certain software, in particular related to demographic, ecological, and environmental data. As a solution to the performance problems of Statistics/Data Collection Officers At the Jambi Province Communications and Information Office, upgrading was given in the form of training in the use of Mortpak software and training in data collection for the environmental sector and ecology.

Scientific Impact of Novel Instrumentation: The Case of MUSE

In the process of transforming science cases into a viable and affordable design for a novel instrument, there is the problem of how to gauge their scientific impact, especially when they end up in competing top level requirements that can be incompatible with each other. This research note presents a case study for scientific impact of the integral field spectrograph MUSE in terms of number of refereed publications from 2014 to 2024 as a figure of merit, broken down by different research areas. The analysis is based on the Basic ESO Publication Statistics service and NASA's Astrophysics Data System.

The CT Scan Lung Severity Score and Vaccination Status in COVID-19 patients in India: Perspective of an Independent Radiology Practice

Background Patients with COVID-19 often undergo a high-resolution CT scan to determine the extent of lung involvement. The aim of this study was to determine lung involvement in confirmed/suspected COVID-19 patients (encountered at an independent radiology practice) and its correlation to vaccination status amidst the second COVID-19 wave in India. Methods We retrospectively queried our data from April 2021 to identify adult patients (>17 years) who had confirmed (positive RT-PCR or antigen test) or suspected COVID-19 (classic symptoms but negative RT-PCR) and received a high-resolution CT scan to determine the extent of lung involvement using the CT severity (CT-SS) score. The patients were classified into three groups based on their vaccination status to determine their correlation with the CT-SS score: fully vaccinated, partially vaccinated, and unvaccinated. Basic descriptive statistics, univariate tests, and multivariate linear regression analyses were performed. Results We identified 229 patients (median age, 45 years; 60% male), of whom 205 (89%) had confirmed COVID-19 (positive RT-PCR) and 24 had suspected disease (negative RT-PCT but classic symptoms). Of 229 patients, 29 (13%) had complete vaccination, 38 (17%) had partial vaccination, and 162 (70%) had no vaccination. The CT score of the completely vaccinated patients was significantly lower than that of the partially or unvaccinated patients (median 0 v. 3.5 v. 10, respectively p<.01). Conclusion Here, we present real-world findings from an independent radiology practice (a unique and common practice model) in India amid the second COVID-19 wave, showing significantly lower CT severity scores in fully or partially vaccinated patients compared to unvaccinated patients. Complete vaccination of patients may be critical in preventing severe lung disease.

Estimating sectoral COVID-19 economic losses in the Philippines using nighttime light and electricity consumption data.

Economic loss estimation is critical for policymakers to craft policies that balance economic and health concerns during pandemic emergencies. However, this task is time-consuming and resource-intensive, posing challenges during emergencies. To address this, we proposed using electricity consumption (EC) and nighttime lights (NTL) datasets to estimate the total, commercial, and industrial economic losses from COVID-19 lockdowns in the Philippines. Regression models were employed to establish the relationship of GDP with EC and NTL. Then, models using basic statistics and weather data were developed to estimate the counterfactual EC and NTL, from which counterfactual GDP was derived. The difference between the actual and the counterfactual GDP from 2020 to 2021 yielded economic loss. This paper highlights three findings. First, the regression model results established that models based on EC (adj-R2 ≥ 0.978) were better at explaining GDP than models using NTL (adj-R2 ≥ 0.663); however, combining both EC and NTL improved the prediction (adj-R2 ≥ 0.979). Second, counterfactual EC and NTL could be estimated using models based on statistics and weather data explaining more than 81% of the pre-pandemic values. Last, the estimated total loss amounted to 2.9 trillion PhP in 2020 and 3.2 trillion PhP in 2021. More than two-thirds of the losses were in the commercial sector as it responded to both policies and the COVID-19 case surge. In contrast, the industrial sector was affected primarily by the lockdown implementation. This method allowed monitoring of economic losses resulting from long-term and large-scale hazards such as the COVID-19 pandemic. These findings can serve as empirical evidence for advocating targeted strategies that balance public health and the economy during pandemic scenarios.