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This paper presents an agent-based simulation-optimization modeling and algorithmic framework to determine the optimal vaccine center location and vaccine allocation strategies under budget constraints during an epidemic outbreak. Both simulation and optimization models incorporate population health dynamics, such as susceptible (S), vaccinated (V), infected (I) and recovered (R), while their integrated utilization focuses on the COVID-19 vaccine allocation challenges. We first formulate a dynamic location-allocation mixed-integer programming (MIP) model, which determines the optimal vaccination center locations and vaccines allocated to vaccination centers, pharmacies, and health centers in a multi-period setting in each region over a geographical location. We then extend the agent-based epidemiological simulation model of COVID-19 (Covasim) by adding new vaccination compartments representing people who take the first vaccine shot and the first two shots. The Covasim involves complex disease transmission contact networks, including households, schools, and workplaces, and demographics, such as age-based disease transmission parameters. We combine the extended Covasim with the vaccination center location-allocation MIP model into one single simulation-optimization framework, which works iteratively forward and backward in time to determine the optimal vaccine allocation under varying disease dynamics. The agent-based simulation captures the inherent uncertainty in disease progression and forecasts the refined number of susceptible individuals and infections for the current time period to be used as an input into the optimization. We calibrate, validate, and test our simulation-optimization vaccine allocation model using the COVID-19 data and vaccine distribution case study in New Jersey. The resulting insights support ongoing mass vaccination efforts to mitigate the impact of the pandemic on public health, while the simulation-optimization algorithmic framework could be generalized for other epidemics. [ FROM AUTHOR] Copyright of IISE Transactions is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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In recent years, the use of bicycle as a healthy and economical means of transportation has been promoted worldwide. In addition, with the increase in bicycle commuting due to the COVID-19, the use of bicycles are attracting attention as a last-mile means of transportation in Mobility as a Service(MaaS). To help ensure a safe and comfortable ride using a smartphone mounted on a bicycle, this study focuses on analyzing facial expressions while riding to determine potential comfort along the route with the surrounding environment and to provide a map that users can explicitly feedback(FB) after riding. Combining the emotions of facial expressions while riding and FB, we annotate comfort to different locations. Afterwards, we verify the relationship between locations with high level of comfort based on the acquired data and the surrounding environment of those locations using Google Street View(GSV). © 2023 Owner/Author.
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Due to the inappropriate or untimely distribution of post-disaster goods, many regions did not receive timely and efficient relief for infected people in the coronavirus disease outbreak that began in 2019. This study develops a model for the emergency relief routing problem (ERRP) to distribute post-disaster relief more reasonably. Unlike general route optimizations, patients' suffering is taken into account in the model, allowing patients in more urgent situations to receive relief operations first. A new metaheuristic algorithm, the hybrid brain storm optimization (HBSO) algorithm, is proposed to deal with the model. The hybrid algorithm adds the ideas of the simulated annealing (SA) algorithm and large neighborhood search (LNS) algorithm into the BSO algorithm, improving its ability to escape from the local optimum trap and speeding up the convergence. In simulation experiments, the BSO algorithm, BSO+LNS algorithm (combining the BSO with the LNS), and HBSO algorithm (combining the BSO with the LNS and SA) are compared. The results of simulation experiments show the following: (1) The HBSO algorithm outperforms its rivals, obtaining a smaller total cost and providing a more stable ability to discover the best solution for the ERRP;(2) the ERRP model can greatly reduce the level of patient suffering and can prioritize patients in more urgent situations.
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This study discusses the development of the intellectual property (IP) marketplace model based on mobile location-aware computing. Referring to statistics released by the Directorate General of Intellectual Property, there has been a growth in the number of intellectual property rights (IPR) applications in recent years, even during the Covid-19 pandemic. On the other hand, after IPR protection, the commercialization of IPR is one of the pillars of the IP system. Nevertheless, research institutions such as LIPI/BRIN indicate that the potential for commercializing IPR is still low. Furthermore, the opportunity is that cellular networks have covered almost all parts of Indonesia, and there has been significant growth in smartphone users. The method utilized in this research is prototyping. This research results from an IP marketplace model based on mobile location-aware computing in Indonesia. Using the smartphone user's location, contextual IPR information from the user's location related to IPR will enter their smartphone. The experimental results indicate that the application can display a list of IPR information according to the smartphone user's location. Furthermore, the search feature can forage IPR listing information based on user queries. © 2022 IEEE.
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The state government of Sarawak with the help of the Sarawak Disaster Management Committee (SDMC) has continuously made the updated information on the state COVID-19 situation and its ensuing control measures available to general public in the form of daily press statements. However, these statements are merely providing textual information on daily basis though the data are in fact rich in temporal and spatial properties. Since the onset of COVID-19 pandemic, spatiotemporal analysis becomes the key element to better understand the spread of COVID-19 in various spatial levels worldwide. Hence, there is an urgent need to convert this textual information into more valuable insights by applying geo-visualization techniques and geospatial statistics. The paper demonstrates the prospect of retrieving geospatial data from publicly available document to locate, map and analyze the spread of COVID-19 up to division level of Sarawak. Specifically, map visualization and geospatial statistical analysis are performed for the list of exposed locations, which are indeed locations visited by COVID-19 patients prior to being tested positive in Kuching division, using open-source geospatial software QGIS. It is found that these exposed locations concentrate on the build-up areas in the division and are in south-west to north-east direction of the center of Kuching in September and October 2021. Despite the number of exposed locations published is relatively small compared to the number of confirmed cases reported, both are nearly strongly correlated. The insights gained from such geospatial analysis may assist the local public health authorities to impose applicable disease control interventions at division level. © 2023 Horizon Research Publishing. All rights reserved.
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Tackling with Covid-19 dilemma of vaccine distribution needed a stack of analysis and examination. This paper develops a generalizable framework for designing a hub vaccination dispensing network to achieve expand the Covid-19 vaccination coverage for public. Designing a hub location routing network for vaccine distribution is the main concern for this research. The proposed model hinges on maximum coverage and patients' safety by considering high-priority population alongside the cost reduction in an uncertain environment. The hub location model enhances the accessibility of the vaccines to various communities and helps to overcome the challenges. The results of this model were examined through both numerical and case studies in the north of Tehran to demonstrate its application. Furthermore, in order to reduce the costs of vaccine imports, vaccine entry routing can be developed from border and air points to the country in order to be able to perform vaccination in the fastest time and lowest cost in the future. The results concede that increasing the number of outreach dispensing locations per hub dispensing location will not necessarily result in increased coverage.
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Power transmission lines are integral and very important components of power systems. Because of the length of these lines and the complexity of the power grids, the lines may encounter various incidents such as lightning strike, shortage, and breakage. When an incident or a fault occurs, a fast process of identification, localization, and isolation of the fault is desired. An accurate fault localization would have a great impact in reducing the restoration time of the system. One of the most popular solutions for fault detection and localization is the distance relays using the impedance-based algorithms. However, these relays are still not perfect with nonzero errors of the fault locations. This paper will present a new approach using the neural networks in addition to a distance relays to correct the fault location estimation of the relay. The solution will be based only on the voltage and current signals measured at the beginning of the lines. The training samples' signals of the transient states on the lines are generated using ATP/EMTP, and then regenerated into the relay tester Omicron CMC-356 to test with the real Siemens 7SA522 relay to improve its fault location results. The numerical results will show that the solution had helped to reduce the average fault location error from 0.92% to 0.42% for 4 types of shortage faults on the lines. [ FROM AUTHOR] Copyright of Turkish Journal of Electrical Engineering & Computer Sciences is the property of Scientific and Technical Research Council of Turkey and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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The COVID-19 has placed pandemic modeling at the forefront of the whole world's public policymaking. Nonetheless, forecasting and modeling the COVID-19 medical waste with a detoxification center of the COVID-19 medical wastes remains a challenge. This work presents a Fuzzy Inference System to forecast the COVID-19 medical wastes. Then, people are divided into five categories are divided according to the symptoms of the disease into healthy people, suspicious, suspected of mild COVID-19, and suspicious of intense COVID-19. In this regard, a new fuzzy sustainable model for COVID-19 medical waste supply chain network for location and allocation decisions considering waste management is developed for the first time. The main purpose of this paper is to minimize supply chain costs, the environmental impact of medical waste, and to establish detoxification centers and control the social responsibility centers in the COVID-19 outbreak. To show the performance of the suggested model, sensitivity analysis is performed on important parameters. A real case study in Iran/Tehran is suggested to validate the proposed model. Classifying people into different groups, considering sustainability in COVID 19 medical waste supply chain network and examining new artificial intelligence methods based on TS and GOA algorithms are among the contributions of this paper. Results show that the decision-makers should use an FIS to forecast COVID-19 medical waste and employ a detoxification center of the COVID-19 medical wastes to reduce outbreaks of this pandemic. © 2023, Crown.
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With the expanding popularity of Location-Based Games and the rise of advertising therein, there exists a need to comprehend the impact of Location-Based Game Advertising (LGA). This paper seeks to identify what makes positively affective LGA, leveraging Pokémon GO as a probe. Researchers conducted twenty-seven (n=27) semi-structured interviews with Pokémon GO players to reveal lived experiences regarding LGA. Our findings highlight the following direct implications for LGA: (1) LGA act as a digital billboard, conveying qualitative alongside locative information, and (2) well-received LGA enhances the player's agency. We additionally identify findings that have auxiliary implications to LGA: (3) positive memorability occurs when points of interest match physical reality, and (4) ludic engagement is a mediating factor in the memorability of locations. This research demonstrates that LGA in Location-Based Games is surprisingly well-received. However, developers must provide extra consideration to the player's agency for such techniques to be effective. © 2023 ACM.
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This set of tables introduces new data for national and state-level public elementary and secondary revenues and expenditures for fiscal year (FY) 2021. Specifically, these tables include the following school finance data: (1) revenue and expenditure totals;(2) revenues by source;(3) expenditures by function and object;(4) current expenditures;(5) revenues and current expenditures per pupil;(6) expenditures from Title I funds;and (7) revenues and expenditures from COVID-19 Federal Assistance Funds. The tables chosen for this report demonstrate the range of information available when using the National Public Education Financial Survey (NPEFS). [For "Revenues and Expenditures for Public Elementary and Secondary Education: FY 20. Finance Tables. NCES 2022-301," see ED619372.]
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The issue of unsold homes in Malaysia has recently caused the housing developers great anxiety. The nationwide issue of unsold homes was caused by the fact that more homes were built than were purchased by customers. As a result, it is important to figure out what factors can influence potential homebuyers to make a purchase. In order to better understand this issue, the study's objective was to determine the factors that influence homebuyers' decisions in Kota Bharu, Kelantan. The study specifically sought to ascertain whether variables including quality, price, location, promotion, and corporate image had an effect on consumers' decisions to purchase homes. Since the nation was dealing with the Covid-19 outbreak, which made face-to-face questionnaire distribution on the ground nearly impossible to carry out, 382 respondents from Kota Bharu, Kelantan, participated in this study through questionnaires disseminated using the Google Form technique. This study used the Principal Axis Factor and Promax Rotation to evaluate the instruments. Before doing a bootstrapped regression analysis, all seven multiple regression assumptions were examined and verified. The findings showed that only location and promotion variables were positive and significantly influencing the house buying decision. These findings led to a number of strategy recommendations that helped the industry develop the best plans for boosting upcoming sales. It is hoped that by identifying the variables influencing homebuyers' purchasing decisions, housing developers can get an understanding of this phenomenon and be better able to plan and build homes that will live up to buyers' expectations. © 2023 by MIP.
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With the advent of agricultural revolution, sedentary lifestyle called for people to exchange their surplus goods in return for the others they need. In settlements, emerged by this tradition, bazaars became the first commercial places where the sell-ers and buyers meet. Being one of the most important public places in the culture and daily-life of a particular locality from past to present, it is essential for bazaars to be located, planned, and designed in line with the requirements of the time so that they sustain their existence properly. COVID-19, initial cases of which-ironically-were seen among the staff of a live-animal and seafood wholesale wet market in Wuhan, China in December 2019, shortly transformed into a global pandemic, changed our daily routines by directly affecting the use of especially open pub-lic spaces and commercial places. Thus, these spaces and land -uses need to be reconsidered in terms of the "new normals" and "physical distance rules" during and after the coronavirus pandemic. This study, which also includes evaluations for the post-COVID-19 period, aimed at a set of holistic criteria for the location-planning-design of bazaar places that are important for social life in Turkiye regarding their public-commercial use. Accordingly, after examining the before and ongoing COVID-19 literature, world bazaars, and legislation;locational, planning, and design scale properties of bazaars that would effectively serve a local population are put forward by introducing the Bazaar Places Planning Table (BPPT). Subsequently, a simple version of BPPT is tested for bazaar places of a medium-scale city.
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Introduction: Several studies have evaluated the occurrence of oral lesions and changes in sensory functions in patients positive for COVID-19. Objective(s): To evaluate the manifestations of COVID-19, emphasizing olfactory and gustatory changes, xerostomia, and oral lesions. Material(s) and Method(s): A cross-sectional and observational study was conducted. Approved by the Institutional Ethics Committee (#46151121.6.0000.5141). All patients were diagnosed by reverse transcription-polymerase chain reaction assay (RT-PCR) and considered to have mild symptoms, according to the latest WHO joint report. The patients were evaluated at a reference Service for COVID-19 in Minas Gerais, Brazil. The oral cavity was evaluated for each patient on the second and seventh days. Result(s): A total of 414 patients older than 18 years were evaluated. One hundred thirty-nine presented at least one of the studied conditions, oral lesions (19.08%) were the most frequently observed, followed by gustatory disorders (18.11%), xerostomia (14.25%), and olfactory dysfunction (14%). Among the oral lesions, there were various anatomical locations and clinical presentations. The occurrence involving lips and tongue represented 49 oral lesions, the most prevalent being, respectively, ulcerations (n=51), candidiasis (n=8), and erythema or red plaques (n=7). Fifty patients died. Conclusion(s): This study represents, to date, the largest case series of oral lesions in Brazilian patients with COVID-19, and oral alterations were observed in an expressive percentage of patients with COVID-19. However, it cannot be concluded that SARS-CoV-2 directly causes them.
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This article highlights the relatively limited but growing discussion surrounding ethical guidelines for the use of location tracking technology. After a review of recent literature related to location data and geoprivacy, this article is divided into two sections: The first highlights views of public officials and location tracking experts over the potential misuse of location data, especially in the context of the COVID-19 pandemic. The data come from available transcripts of the Location Tech Task Force organized in 2020 by the American Geographical Society as part of its EthicalGEO initiative. The second section documents various institutional approaches to elevate the dialogue and inform governance of location-based data and technology, including the development of the Locus Charter, an emerging international framework on the ethical use of location data. In conclusion, we urge the professional and academic geographic communities to engage with the elaboration and dissemination of ethical frameworks to guide the use and management of data from location tracking technology. (English) [ FROM AUTHOR] La reciente erudición geográfica feminista ha urgido a los geógrafos a distanciarse de los enfoques androcéntricos y eurocéntricos, y a abrir la disciplina a perspectivas diversas. En tanto que numerosos estudios se han enfocado a diversificar y descolonizar la geografía por medio de prácticas de reclutamiento, tutoría y producción de conocimiento, solo muy pocos han analizado cómo se traduce la diversidad en las prácticas de enseñanza, en particular en contextos donde la diversidad está relativamente bien establecida entre el personal. Basado en una encuesta por cuestionario entre el personal docente, en un análisis del contenido de los programas de los cursos y un análisis cuantitativo de los datos de los empleados del departamento, este artículo explora hasta qué punto la diversidad dentro del departamento conduce a la diversidad en las prácticas de la enseñanza. Desarrollando un marco de los espacios de la diversidad, analizamos tres espacios que potencialmente permiten practicar la diversidad en la enseñanza: El espacio académico del departamento promueve la libre elección de los tópicos de investigación y enseñanza, y las condiciones flexibles del trabajo;el espacio del departamento permite a los individuos asumir compromisos en la configuración de la enseñanza geográfica;y el espacio del conocimiento promueve la diversidad como un ideal. Sin embargo, encontramos que practicar la diversidad en geografía implica enfrentar los retos de las estructuras universitarias tradicionales y neoliberales y de las jerarquías formales y percibidas. Aún más, existe una necesidad de prácticas concretas sobre diversidad a niveles individuales e institucionales para llevar activamente las diversas perspectivas al salón de clase. (Spanish) [ FROM AUTHOR] 女权地理学的最新研究, 敦促地理学者远离以男性和欧洲为核心的方法, 接受不同的观点。许多研究都侧重通过招聘、指导和知识生产, 去实现地理学的多样化和去殖民化。只有少数研究分析了多样性如何转化为教学实践（尤其是在教职员工多样性相对稳定的情况下）。基于教师问卷调查、课程大纲内容分析以及对地理系员工数据的定量分析, 本文探讨了地理系的多样性在多大程度上导致教学实践的多样性。我们建立了一个多样性的空间框架, 分析了可能实现教学多样性的三个空间："学术空间"促进对研究课题、课程题目和灵活工作条件的自由选择, "地理系空间"使个人能够参与地理教学的建设, "知识空间"促进理想的多样性。然而, 传统的和新自由主义的大学体系以及严格的等级制度, 是实现地理多样性的挑战。此外, 还需要在个人和体制层面采取切实的多样性实践, 积极地将不同观点带入课堂。 (Chinese) [ FROM AUTHOR] Copyright of Professional Geographer is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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The pandemic has changed consumer habits, leading to an increase in parcel delivery and changing consumer requirements. Last-mile delivery has become more important than ever. Parcel delivery providers face a major challenge, as research shows that many consumers will maintain the same shopping habits as during the pandemic. It is, therefore, necessary to find sustainable and not just short-term solutions for the last-mile delivery. Identifying suitable locations for micro-depots in urban areas and delivery with e-cargo bicycles can be one of them. This article has two objectives: (1) to determine whether the changes brought by Covid-19 affect the selection of the appropriate micro-depot site and to what extent;and (2) whether the extension of the Analytical Hierarchy Process (AHP) by evaluating the technical efficiency of micro-depo sites locations changes the ranking of most favourable locations and to what extent. We first gathered existing criteria for selecting a suitable micro-depot location through a literature review. Then, a qualitative and quantitative analysis were performed to check suitability of criteria and complement the current set of criteria with potential new criteria resulting from Covid-19. A real numerical example of one of the past researches was selected to perform Delphi and super-efficiency Data Envelopment Analysis (DEA) analysis. Results of Delphi analysis, where the AHP was applied, revealed that Covid-19 had not affected the type of stakeholders' demands (city administration, citizens and logistics companies) taken into account, but their importance. However, upgrading the AHP with a super-efficient DEA model has completely changed the order of the most relevant micro-depot locations. © 2023 The Authors. Published by ELSEVIER B.V.
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We use data on human mobility obtained from mobile applications to explore the activity patterns in the neighbourhoods of Greater London as they emerged from the first wave of COVID-19 lockdown restrictions during summer 2020 and analyse how the lockdown guidelines have exposed the socio-spatial fragmentation between urban communities. The location data are spatially aggregated to 1 km2 grids and cross-checked against publicly available mobility metrics (e.g. Google COVID-19 Community Report, Apple Mobility Trends Report). They are then linked to geodemographic classifications to compare the average decline of activities in the areas with different sociodemographic characteristics. We found that the activities in the deprived areas dominated by minority groups declined less compared to the Greater London average, leaving those communities more exposed to the virus. Meanwhile, the activity levels declined more in affluent areas dominated by white-collar jobs. Furthermore, due to the closure of non-essential stores, activities declined more in premium shopping destinations and less in suburban high streets.
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BACKGROUND: People living with HIV (PLWH) report high levels of anxiety. This study assessed the prevalence of COVID-19-related anxiety in PLWH. METHODS: Participants were recruited from two UK HIV clinics (01/03/2020 - 30/05/2022) and asked to complete the Coronavirus Anxiety Scale. The proportion with scores ≥9 (cut-off for dysfunctional pandemic-related anxiety) and ≥1 (reporting of any pandemic-related anxiety) were analysed. RESULTS: 115 PLWH were included, predominantly identifying as male (83.5%, n = 96), white (58.3%, n = 67) and reporting post-secondary education (82.6%, n = 95), with a median age of 51 years (range 22-93). Median CAS score was 0, with 4.4% scoring ≥9 (n = 5). More women scored ≥9 than men (16.7% (n = 3) and 2.1% (n = 2) respectively). Black African (13.6%, n = 3) and Other Ethnic Minority PLWH (25%, n = 2) had a greater proportion of scores ≥9 than White/Asian PLWH (both 0%). SARS-CoV-2 exposure was associated with scores greater than 1 but not greater than 9. CAS score was not associated with lower CD4 (<350 cells/mm3), detectable HIV viral load (≥50 copies/ml), or a history of pre-pandemic anxiety. CONCLUSIONS: Pandemic-related anxiety was low, but we identified a sub-population reporting dysfunctional pandemic related anxiety. Future work should further investigate the psychological impact of the pandemic on this group.
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Rapid urbanization has gradually strengthened the spatial links between cities, which greatly aggravates the possibility of the spread of an epidemic. Traditional methods lack the early and accurate detection of epidemics. This study took the Hubei province as the study area and used Tencent's location big data to study the spread of COVID-19. Using ArcGIS as a platform, the urban relation intensity, urban centrality, overlay analysis, and correlation analysis were used to measure and analyze the population mobility data of 17 cities in Hubei province. The results showed that there was high similarity in the spatial distribution of urban relation intensity, urban centrality, and the number of infected people, all indicating the spatial distribution characteristics of "one large and two small" distributions with Wuhan as the core and Huanggang and Xiaogan as the two wings. The urban centrality of Wuhan was four times higher than that of Huanggang and Xiaogan, and the urban relation intensity of Wuhan with Huanggang and Xiaogan was also the second highest in the Hubei province. Meanwhile, in the analysis of the number of infected persons, it was found that the number of infected persons in Wuhan was approximately two times that of these two cities. Through correlation analysis of the urban relation intensity, urban centrality, and the number of infected people, it was found that there was an extremely significant positive correlation among the urban relation intensity, urban centrality, and the number of infected people, with an R2 of 0.976 and 0.938, respectively. Based on Tencent's location big data, this study conducted the epidemic spread research for "epidemic spatial risk classification and prevention and control level selection" to make up for the shortcomings in epidemic risk analysis and judgment. This could provide a reference for city managers to effectively coordinate existing resources, formulate policy, and control the epidemic.
Subject(s)
COVID-19 , Epidemics , Animals , Humans , Big Data , COVID-19/epidemiology , Disease Outbreaks , CitiesABSTRACT
INTRODUCTION: The COVID-19 pandemic has disrupted the residency match process by eliminating away rotations and changing from in-person to virtual interviews. In this study, we explore the impact of the COVID-19 pandemic on the geographic match distance of United States (US) senior medical students across all specialties. METHODS: We collected publicly available student match data between 2018 and 2021 from US allopathic medical schools and calculated match distance between medical school and residency training using a novel metric - the "match space." Match space was codified by whether the student matched at their home institution, home state, adjacent state, same or adjacent US census division (non-adjacent state) or skipped at least one US census division. Adjusting for covariates, ordinal logistic regression correlated school and specialty characteristics with match distance pre- and post-pandemic for all specialties. We defined and ranked specialty competitiveness using predictive values from factor analysis. RESULTS: A total of 34,672 students representing 66 medical schools from 28 states matched into 26 specialties in 50 states and Canada. Fifty-nine percent of students were from public institutions, and 27% of schools ranked in the top 40 for research. The mean percentage of in-state students by school was 60.3% (range 3-100%). Match space was lower after the pandemic (adjusted odds ratio (OR) 0.94, 95% CI 0.90-0.98; p=0.006), from schools with higher in-state percentages (OR 0.74, 95% CI 0.72-0.76), from top National Institutes of Health-funded institutions (OR 0.88, 95% CI 0.85-0.92), from the Northeast (OR 0.71, 95% CI 0.67-0.75; Midwest reference), and the West (OR 0.67, 95% 0.60-0.74). Match space was higher for students graduating from private schools (OR 1.11, 95% CI 1.05-1.19), from the South (OR 1.62, 95% CI 1.2-1.33), and matching into more competitive specialties (OR 1.08, 95% CI 1.02-1.14). The top five most competitive specialties were Plastic Surgery, Neurosurgery, Dermatology, Orthopedic Surgery, and Otolaryngology. Internal Medicine ranked eighth. CONCLUSIONS: After the COVID-19 pandemic, students graduating from US allopathic schools matched closer to their home institution. Students attending public schools, schools with more in-state matriculants, and schools with higher research rankings also matched closer to their home institutions. Specialty competitiveness and US census region also impacted match distance. Our study adds insight into how geographic match patterns were influenced by school, specialty choice, and the pandemic.
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Fieldwork is an important part of geography education in many countries. However, little fieldwork-related activities are being observed in Indonesia, specifically at the senior secondary level. In an effort to address this issue, investigators have developed a fieldwork-based blended learning model to be used in the country. This study involved 187 students from three high schools who followed the developed learning model. To measure the effectiveness of the developed model, a correlational analysis that examined the effect of location and session allocation on the test scores of students was used. Questionnaires were distributed to gain insight into the responses of students toward the learning system and qualitative methods were used to capture the learning experiences of these students while using the model. The obtained results show that the grades of the students were significantly affected by location rather than study sessions. Furthermore, students responded positively to the fieldwork-based blended learning model, although traditional classroom learning remained the most preferred option. Interestingly, it was found that students in Indonesia preferred to study with large groups of classmates over smaller groups. These findings confirmed the hypothesis that cultural and religious factors, specifically the concepts of "gotong royong" and "jama'ah" in Islam, respectively, influenced the perceptions of students and group preferences when studying.