Mahmoud Taghavi, Khadije Bakhshi, Ahmad Zarei
et al.
Elevated levels of metal(loid)s in soil may pose potential threats to the ecosystem and can be harmful for human health. The concentrations of As, Cd, Pb, Cr and Ni were determined in agricultural soil collected from 45 pistachio orchards around Feizabad city, Khorasan Razavi province, Iran using ICP-OES. Also, soil pollution indices including contamination factor (CF), pollution load index (PLI) and geo-accumulation index (Igeo) were evaluated. In addition, non-carcinogenic and carcinogenic risk indices were estimated. The mean concentrations of metal(loid)s were in the order of Ni = 466.256 > Cr = 120.848 > Pb = 12.009 > As = 5.486 > Cd = 0.394 mg/kg. Concentrations of As, Cd and Pb in the soil samples were within their respective permissible limits set by World Health Organization (WHO). But concentrations of Cr and Ni in 84.4 and 100% of the samples, respectively exceeded the WHO allowable limits. The CF, PLI and Igeo showed that soil of some of the pistachio orchards was contaminated with some metals. The possible sources of the metals in the soil are application of pesticides, chemical fertilizers, manures as well as irrigation water. Hazard quotient (HQ) ad Hazard index (HI) values from soil of all the orchards were found to be well below the respective threshold limit (1), suggesting that there is no immediate non-cancer threat arising from the contamination at all the orchards with metal(loid)s for children and adults. The highest cancer risk values (1.13E-02 for children and 1.25E-03 for adults) were estimated for Ni in the soil. Collectively, this study provides valuable information to improve the soil in the pistachio orchards to reduce metal(loid)s contamination and minimize the associated health risks to the population in the area.
Human mobility prediction is vital for urban planning, transportation optimization, and personalized services. However, the inherent randomness, non-uniform time intervals, and complex patterns of human mobility, compounded by the heterogeneity introduced by varying city structures, infrastructure, and population densities, present significant challenges in modeling. Existing solutions often require training separate models for each city due to distinct spatial representations and geographic coverage. In this paper, we propose UniMove, a unified model for multi-city human mobility prediction, addressing two challenges: (1) constructing universal spatial representations for effective token sharing across cities, and (2) modeling heterogeneous mobility patterns from varying city characteristics. We propose a trajectory-location dual-tower architecture, with a location tower for universal spatial encoding and a trajectory tower for sequential mobility modeling. We also design MoE Transformer blocks to adaptively select experts to handle diverse movement patterns. Extensive experiments across multiple datasets from diverse cities demonstrate that UniMove truly embodies the essence of a unified model. By enabling joint training on multi-city data with mutual data enhancement, it significantly improves mobility prediction accuracy by over 10.2\%. UniMove represents a key advancement toward realizing a true foundational model with a unified architecture for human mobility. We release the implementation at https://github.com/tsinghua-fib-lab/UniMove/.
Background: Parental academic support plays a significant role in fostering academic resilience in students. By providing encouragement, guidance, and emotional support, parents can help their children develop the coping skills and self-confidence necessary to overcome obstacles and persist in their academic endeavors. Objectives: This study examines the relationship between parental academic support and students’ academic well-being, with a particular focus on the mediating role of academic resilience. Methods: This study employed a descriptive-correlational design. The population included all high school students in Ahvaz city during the 2022 - 2023 academic year. A sample of 384 students was selected using a multistage cluster sampling method. The research instruments included the School-Related Well-Being Scale (SWBS), Academic Support Scale, and Academic Resilience Scale. Structural equation modeling (SEM) in SPSS 25 and AMOS 25 was used to analyze the model relationships, followed by bootstrapping to test indirect effects. Results: The findings indicated significant positive relationships between academic resilience and academic well-being, and between parental academic support and academic resilience (P < 0.001). However, the direct relationship between parental academic support and academic well-being was not significant. The indirect relationship between parental academic support and academic well-being through academic resilience was found to be significant (P = 0.006). The final model demonstrated a good fit to the data, as evidenced by fit indices, including RMSEA (0.001), TLI (0.99), and CFI (0.99). Conclusions: The findings support the hypothesized mediating role of academic resilience. These results suggest that parental involvement, which fosters students' ability to recover from setbacks and persist in their studies, ultimately contributes to positive academic experiences and well-being.
Abstract In examining visa-waiver agreements, previous studies have primarily focused on economic motivations and effects. In this article, we explore the potential political motivations and consequences. Particularly, we propose that there is a positive relationship between visa-waivers and democracy. We test this using a global dataset that records bilateral travel visa requirements for all countries between 1973 and 2013. We find support for our main hypothesis. We also examine the relationship between democracy, visa waivers and economic development. Contrary to our expectations, we find that democracy continues to exert influence on visa waivers even at high levels of income. Non-democracies fail to attain visa waivers even when they are wealthy. Finally, we explore whether visa waivers could have an impact on individuals’ attitudes towards democracy. Using survey data from 18 Latin American countries, we find suggestive evidence that that visa-waivers can have a positive impact on individuals’ democratic attitudes. Taken together, the findings suggest that democracy and visa-waivers might have a mutually reinforcing relationship.
Abstract Studies on migration aspirations have provided fresh perspectives for two decades by focusing on the changing nature of aspirations, the aspirations-cap/abilities nexus, and by offering a counterpoint through the ‘aspirations to stay’. Building from these, this article proposes a model to explain the intensity and strength of (im)mobility aspirations, given that these can be strong and specific but also weak, mild, conditional, and even conflicting. To do so, I focus on the preferences to migrate or to stay by examining how the two dimensions of (im)mobility – the intrinsic and the instrumental – interact. I study the different emotions and thoughts attached to (im)mobility, how life and migration aspirations are intertwined, and the ways in which migration and stay aspirations can co-exist. In doing so, I differentiate between three ideal-type strengths of aspirations: harmonious, conflicting, and indeterminate aspirations. Harmonious aspirations capture strong convictions about what is more convenient: staying or migrating. Conflicting aspirations stress that both migration and stay aspirations can be concurrently present and equally strong. Indeterminate aspirations represent uncertainty or indifference about where to be. With this focus, the paper provides a simple approach to orient research beyond ideal-type categories by incorporating complex, often contradictory emotions. The paper draws on 37 qualitative interviews in two former mining regions in North-West Spain to advance theorization on migration aspirations and decision-making and to question if the division between migration and stay aspirations is clear-cut.
The advancement of 5G technology has transformed various aspects of life, including tourism, by enabling people worldwide to communicate and travel with ease. Traveling to different places and countries is now seamless, removing language barriers and facilitating easy access to information on culture, accommodation, and tourist attractions. Additionally, access to applications that facilitate quicker language translation further enhances the travel experience. Phetchaburi Province holds significant importance as a global tourist destination. UNESCO has recognized Phetchaburi as a member of the UNESCO Creative Cities Network (UCCN), comprising one of 49 cities worldwide acknowledged for their creative city initiatives. Phetchaburi Province stands as the 5th city in Thailand to receive this designation. This research investigated 5G performance in Phetchaburi Province, both the inner and outer city, focusing on download and upload speeds. The results indicate that there is widespread 5G coverage throughout Phetchaburi Province, including urban and rural areas, especially for the 5G network with a good performance provided by one of the mobile network operators. In addition, the statistical analysis reveals differences in 5G performances between the inner city and the outer city of Phetchaburi Province, particularly for download speeds (p-value < 0.001).
Lindsey T Ellis, Amit Ahluwalia, Kensey Gosch
et al.
Introduction: The US has the highest maternal mortality (MM) rate among developed countries with significant disparities between Black, Hispanic, and Native American birthing people and their White counterparts. Missouri ranks among the 10 states with the highest MM. It has been presumed that the general population’s lack of knowledge surrounding the issue and distrust of the medical system both contribute significantly to MM. Thus, suggestions for improving maternal mortality have been centered primarily around education. To date, there has been a paucity of research surrounding the knowledge and perceptions of MM in the general population. This study sought to understand the perceptions of MM among a representative sample of pregnant people in Missouri. Methods: This is an anonymous, cross-sectional survey conducted from May 2022-August 2022 across the state of Missouri. The Missouri Perinatal Quality Collaborative/ Maternal-Child Learning and Action Network (LAN/PQC) iteratively developed a 46-question survey, distributed in both English and Spanish, to elicit opinions of birthing people in Missouri, assessing their knowledge about state-specific maternal mortality issues. The target population included individuals 18 years and older with a Missouri zip code who identified as someone of birthing potential. Those without a Missouri zip code, who identified as male, and not pregnant were excluded. All survey questions were uploaded into a secure database (REDcap) and accessible to participants through a survey link. The survey was pilot tested by placing a QR code and survey link on social media platforms by the authors. Once feasibility was confirmed, an additional survey link was distributed through an email listserv purchased from a data distribution platform (Dynata). Demographic data, including age, race, pregnancy status, number of lifetime pregnancies, number of living children, and preferred language, were recorded. All survey responses were documented without patient identifiers following signed, informed consent. The survey was aimed to sample 1500 respondents online racially representative of the Missouri birthing population. The study was approved by Saint Luke’s Hospital of Kansas City IRB and was designed to follow STROBE guidelines for the reporting of cross-sectional studies. Participants were asked general knowledge about maternal mortality including whether or not they knew it was a public health issue in Missouri, if they knew someone who died as a result of pregnancy, and if they themselves had ever been concerned about dying as a result of pregnancy. These results were reported as “yes” or “no” responses. Qualifying questions to positive responses included whether the perceived rate of maternal mortality in Missouri was high or low, suspected underlying medical and social causes and timeframe, and personal relationship to the decedent in the case of known death. For those who answered positively about concern for dying in pregnancy, qualifying responses were recorded on a Likert scale (1 for not at all concerned, 2 for a little concerned, 3 for somewhat concerned, 4 for very concerned and 5 for extremely concerned). Respondents were also asked to identify certain groups of people according to race, income status, insurance status, urban versus rural place of residence, educational status, and marital status that may suffer disproportionately from maternal deaths. Statistical analysis was performed in SAS 9.4. Descriptive statistics are reported in percentages and counts for categorical outcomes and means ± SD for continuous outcomes. Knowledge questions were analyzed as yes or no responses and reported in frequencies. Perceived etiologies for maternal mortality are reported as nominal data in percentages. Logistic regression was performed utilizing employment status, insurance status, marital status, education attainment, and difficulty with finances as predictors variables. Questions were stratified by age, race, and self-reported zip code. Results: Eighty-five people met inclusion criteria with an average age of 30.4 ± 7.6 and parity of 3.1 ± 2.0. Of those, 65.9% identified as White, 25.9% as Black, 8.2% as Hispanic, 3.5% as Native American, 4.7% as Asian, and 2.4% as Hawaiian Native or Pacific Islander. Over 85% reported awareness that MM was an issue in Missouri, and 59.2% reported they believed those numbers to be high. Thirty percent of people reported knowing someone who had died from a pregnancy-related cause; of those, 73.9% reported that the person who died was a family member or personal friend. Only 21.2% of pregnant people reported not being concerned about dying during their pregnancy. Seventy-five percent of the pregnant cohort reported trusting their medical providers’ recommendations. Discussion: Our study found that over 85% of pregnant people in Missouri are aware of MM, and a majority are aware that the MM rate is high. This contradicts commonly held beliefs that our patients’ lack of knowledge may be an opportunity for our efforts. Our survey also revealed that 75% of patients trust their medical providers despite much blame being placed on distrust of the health care system. Further surveys of health care providers may be helpful to reveal how exactly MM can be improved.
Direct and indirect exposure to terrorist attacks can have a significant impact on major life decisions, including the choice of whether to have a child. This study aims to investigate how terrorist attacks affect fertility. By pooling data from three years of cross-sectional surveys conducted between 2010 and 2015 by the Pakistan Bureau of Statistics, our findings reveal a positive correlation between terrorist attacks and fertility among women of childbearing age in Pakistan. Specifically, the probability of giving birth two years following a terrorist attack in one’s home district, all else equal, is 64 percent, compared to the probability of a woman not giving birth two years following a terrorist attack, which is 36 percent. Furthermore, our analysis demonstrates that persistent terrorist attacks, that is, domestic and non-suicide incidents, result in higher probabilities of giving birth during a particular year. Conversely, less common and more prominent terrorist attacks – transnational and suicide incidents – result in lower probabilities of giving birth during a particular year. Additionally, we find that women from above-average-income households, those with higher education levels, older mothers, and those residing in rural areas are more likely to adjust their fertility upwards in response to terrorist attacks.
Urban groups. The city. Urban sociology, City population. Including children in cities, immigration
Wensi Alka, Dzulfikri D, Khaula Amelia Khusna
et al.
Teaching and learning activities had shifted to online classes due to Covid-19 pandemic outbreaks. Hence,primary school teachers in Indonesia encountered several challenges with the unexpected changes inEnglish face-to-face classroom interaction to online learning with digital platforms. This study exploredthe challenges faced by four Indonesian EFL primary school teachers in implementing online learningand teachers’ solutions to the challenges. A qualitative study with a phenomenological approach was usedas the research design, and the data collection was obtained through observation and interview. Thisstudy showed that teachers found online English Language Teaching (ELT) activities more difficult thanface-to-face classrooms due to some challenges. The technical issue became the first challenge faced bythe teachers since both teachers and students needed an internet connection and device management.Secondly, most teachers found it difficult to implement various teaching methods in online learning. Theother reasons were that enhancing students’ engagement required more effort, and assessing students’English development took more work than in the face-to-face classroom. The implication of this researchis for teachers and students as it may help them address and generate new insights about the challengesand solutions in online classrooms. Furthermore, it highlights specific areas for future research.
Education, City population. Including children in cities, immigration
The combination between innovative topics and emerging technologies lets researchers define new processes and models. New needs regard the definition of modular and scalable approaches, with society and environment in mind. An important topic to focus on is the smart city one. The use of emerging technologies lets smart cities develop new processes to improve services offered from various actors, either industries or government. Smart cities were born to improve quality of life for citizens. To reach this goal, various approaches have been proposed, but they lack on a common interface to let each stakeholder communicate in a simple and fast way. This paper shows the proposal of an architecture to overcome the actual limitations of smart cities: it uses Blockchain technology as a distributed database to let everyone join the network and feel part of a community. Blockchain can improve processes development for smart cities. Scalability is granted thanks to a context-aware approach: applications do not need to know about the back-end implementation, they just need to adapt to an interface. With Blockchain, it is possible to collect data anonymously to make some statistical analysis, to access public records to ensure security in the city and to guarantee the origin of products and energy.
In today's world, many cities are embracing cutting-edge technology and transforming into "smart cities". These emerging innovations are revolutionizing the standard of living for people, and as a result, smart city infrastructure development has become a major focus for city planners and policymakers worldwide. The goal is to create more livable, sustainable, and efficient urban environments, and software engineering plays a crucial role in achieving this. In this article, we will delve into what makes a city "smart" and what it means for the future. We will explore the software engineering roadmap for smart city infrastructure development, highlighting the goals and challenges that come with this innovative approach to urban planning. Our aim is to provide valuable insights into the importance of software engineering in achieving successful smart city infrastructure development. As cities continue to grow and evolve, it is essential to adopt new technologies that can help us build smarter, more sustainable communities. Smart city initiatives are paving the way for a brighter future, and software engineering is at the forefront of this movement. By understanding the software engineering roadmap for smart city infrastructure development, we can work towards creating more livable, efficient, and sustainable urban environments for generations to come.
Clara H. Mulder, Isabel Palomares-Linares, Sergi Vidal
Migration is often viewed as a way to enhance occupational careers. However, particularly in Mediterranean countries, labour market outcomes may also depend on local family resources. We investigate how men’s and women’s labour market outcomes differ between (1) those who migrated and those who did not; and (2) those who live close to family and those who live farther away. Our main contributions are the investigation of the association between migration and labour market outcomes in a different context than the more commonly studied Northern and Western European countries and the United States, and of the role of living close to family in labour market outcomes. We used a sample of labour market participants from the “Attitudes and Expectations About Mobility” survey, conducted in Spain in 2019. Our results show that the likelihood of being a professional is greater for women who migrated than for those who did not, and that the likelihood of being unemployed or in a temporary job is lower for women who live close to family than for those who do not, but neither association was found for men. The finding for living close to family is in line with the notion that nearby family may protect women in particular from precarious labour market positions. The finding for migration differs from previous findings for Northern and Western Europe and the United States, which indicate that migration is beneficial to men in particular. This difference might be specific to a low-migration context, but data limitations prevent firm conclusions.
Urban groups. The city. Urban sociology, City population. Including children in cities, immigration
Cities are continuously evolving human settlements. Our cities are under strain in an increasingly urbanized world, and planners, decision-makers, and communities must be ready to adapt. Data is an important resource for municipal administration. Some technologies aid in the collection, processing, and visualization of urban data, assisting in the interpretation and comprehension of how urban systems operate. The relationship between data analytics and smart cities has come to light in recent years as interest in both has grown. A sophisticated network of interconnected systems, including planners and inhabitants, is what is known as a smart city. Data analysis has the potential to support data-driven decision-making in the context of smart cities. Both urban managers and residents are becoming more interested in city dashboards. Dashboards may collect, display, analyze, and provide information on regional performance to help smart cities development have sustainability. In order to assist decision-making processes and enhance the performance of cities, we examine how dashboards might be used to acquire accurate and representative information regarding urban challenges. This chapter culminates Data Analytics on key indicators for the city's urban services and dashboards for leadership and decision-making. A single web page with consolidated information, real-time data streams pertinent to planners and decision-makers as well as residents' everyday lives, and site analytics as a method to assess user interactions and preferences are among the proposals for urban dashboards. Keywords: -Dashboard, data analytics, smart city, sustainability, Smart cities, City dashboards, Urban services, Decision-making, Interconnected systems, Real-time data streams, Key indicators, and Urban challenges.
Understanding the determinants underlying variations in urban health status is important for informing urban design and planning, as well as public health policies. Multiple heterogeneous urban features could modulate the prevalence of diseases across different neighborhoods in cities and across different cities. This study examines heterogeneous features related to socio-demographics, population activity, mobility, and the built environment and their non-linear interactions to examine intra- and inter-city disparity in prevalence of four disease types: obesity, diabetes, cancer, and heart disease. Features related to population activity, mobility, and facility density are obtained from large-scale anonymized mobility data. These features are used in training and testing graph attention network (GAT) models to capture non-linear feature interactions as well as spatial interdependence among neighborhoods. We tested the models in five U.S. cities across the four disease types. The results show that the GAT model can predict the health status of people in neighborhoods based on the top five determinant features. The findings unveil that population activity and built-environment features along with socio-demographic features differentiate the health status of neighborhoods to such a great extent that a GAT model could predict the health status using these features with high accuracy. The results also show that the model trained on one city can predict health status in another city with high accuracy, allowing us to quantify the inter-city similarity and discrepancy in health status. The model and findings provide novel approaches and insights for urban designers, planners, and public health officials to better understand and improve health disparities in cities by considering the significant determinant features and their interactions.
Abstract Objectives Children admitted to hospital with severe acute malnutrition (SAM) and acute illness can be challenging to nutritionally rehabilitate. There is limited understanding on predictors of weight gain during hospitalization in this vulnerable population. This work aimed to predict the weight gain in children using anthropometric, biochemical, clinical, and socio-demographic variables. Methods We included 5,044 children aged 0–59 months with SAM hospitalized in the Dhaka Hospital at icddr, b between 2011 and 2019. Surveillance data was collected during hospitalization and analyzed retrospectively. The 15% weight gain from hospital admission to discharge was considered as outcome because it is recommended as the transition criteria from facility to community-based management. We trained a Random Forest classifier to identify the best set of predictors of a 15% weight gain. A total of 78 features were considered. The developed diagnostic model was validated based on the area under the curve (AUC) between the true positive and the false positive rates. Results The classification of data based on the outcome (weight gain > 15%) created unbalanced classes, a larger group with 15% weight gain. To balance this data disparity, we finally included 263 children in this analysis. A model including 197 children (75% of the dataset) was identified in the training dataset, while the rest were used as a test dataset. Validation in the test dataset revealed an AUC of 69.05% when considering all 78 predictors. Among the top predictors were mid-upper arm circumference at admission, family income and breastfeeding duration. Conclusions This analysis revealed the role of socio-economic status as well as the importance of breastfeeding practices in attaining 15% weight gain from hospital admission to discharge in under five children treated for SAM. This finding has important implications for future work regarding childhood feeding practices and community-based detection of children with SAM. Funding Sources Joannah and Brian Lawson Center for Child Nutrition, Ontario Graduate Scholarship, Canadian Institutes of Health Research Healthy Cities Research Initiative, and icddr, b, Dhaka, Bangladesh.
In this research work, we present a mathematical model for novel coronavirus-19 infectious disease which consists of three different compartments: susceptible, infected, and recovered under convex incident rate involving immigration rate. We first derive the formulation of the model. Also, we give some qualitative aspects for the model including existence of equilibriums and its stability results by using various tools of nonlinear analysis. Then, by means of the nonstandard finite difference scheme (NSFD), we simulate the results for the data of Wuhan city against two different sets of values of immigration parameter. By means of simulation, we show how protection, exposure, death, and cure rates affect the susceptible, infected, and recovered population with the passage of time involving immigration. On the basis of simulation, we observe the dynamical behavior due to immigration of susceptible and infected classes or one of these two.
By mid-July 2020, more than 138 000 US citizens died of novel coronavirus disease 2019 (COVID-19).1 While an estimated 0.03% of the deaths were children, aged birth through 14 years, many more children were affected directly by the deaths of their parents, grandparents, and caregivers.1 Given the human loss and public health efforts to mitigate the incidence of COVID-19, access to pediatric physical and mental health care was significantly impacted. The COVID-19 pandemic revealed glaring health disparities in the US. Health disparities are preventable differences in health outcomes due to racial, ethnic, ability, immigration status, or other marginalizing characteristics. Of 42 states and cities reporting mortality data to the Centers for Disease Control and Prevention, 34 (81.0%) reported higher (>20%) mortality rates among Black individuals in the US than would be predicted based on Black population distribution.1 Among people of color in the US, the overall state mortality disparities, measured by distribution of COVID-19 deaths, were up to 360% higher for Black individuals in the US than would be predicted based on their state population percentage.1 Reported COVID-19 mortality rates were up to 1100% higher in 1 state for the American Indian population, up to 167% higher for Asian populations, and up to 219% higher for Hispanic/Latinx populations.1 The statewide mortality rates, however, may not be the whole story. Some cities have even higher COVID-19 mortality disparities. Health disparities in the US may be primarily caused by structural racism and institutional policies that support residential segregation, underfunded schools, unequal pay and benefits, and lack of universal health care.2 All states without COVID-19 mortality percentage disparities among the Black population enacted the Affordable Care Act (ACA), compared with the ACA enactment in only 50% of the 10 states with the highest disparity percentages of COVID-19 mortality among Black individuals.1,3 Tragically, children who live in families with the least resources—those who are poor, disabled, and from marginalized populations— are experiencing the most hardship from the novel coronavirus pandemic due to food scarcity, housing insecurity, and lack of access to health care. What can we do to bridge the physical and mental health care gaps exacerbated during mitigation strategies to reduce COVID-19? Telehealth may provide part of the answer. The ubiquity of cell phones across the US, with approximately 96% of US citizens owning cell phones, supports the expansion of telehealth.4 The Pew Research Center found an equal distribution of cell phone ownership across White, Black, and Hispanic/ Latinx populations and urban, suburban, and rural environments.4 Telehealth, therefore, because of its flexible platforms and broad accessibility, may help to reduce pediatric health disparities. Federal Code 42 CFR §410.78 describes telehealth as a set of services available to patients in specific geographic locations where the health care professional uses interactive audio and video telecommunication systems that permit asynchronous or real-time 2-way communication between the patient and distant-site clinician.5 Telehealth is considered and reimbursed the same as inperson visits.6 The national emergency that resulted from the COVID-19 pandemic led to the passage of Public Law 116-123withaSection1135waiver.6 TheSection1135waiver allowed the secretary of Health and Human Services to temporarily waive certain Medicare requirements, resulting in the expansion of telehealth services. Before the COVID-19 pandemic, restrictions on telehealth access existed. A patient living in a rural area had to travel to a medical facility to receive telehealth services from a health care professional. A patient could receive telehealth in their home only under certain conditions, such as home dialysis or treatment of substance use disorder or a co-occurring mental health disorder. During the COVID-19 pandemic, the Section 1135 waiver allowed all patients to receive telehealth in their homes. Permission to provide health care within the home of the patient is a privilege and a benefit for the clinician. For physicians, nurse practitioners, psychologists, and other professionals providing pediatric health care, telehealth virtual home visits may inform therapeutic recommendations through visual understanding of the home environment and resources. Before the COVID-19 pandemic, regulations for telehealthcredentialingvariedbystateandinsurer.Healthcare professionals usually needed a license in the state where the patient received care. During the COVID-19 pandemic, Centers for Medicare and Medicaid Services regulations allowed out-of-state physicians in all states and territories to obtain emergency medical licenses, with localespecific easing of telehealth credentialing regulations.7 Changes in Medicare and Medicaid guidance allowed by the Section 1135 waiver increased a wide range of previously unavailable telehealth services. Before COVID-19, telehealth professionals were limited to physicians, physician assistants, nurse practitioners, nursemidwives, mental health professionals, and dietitians. The Section 1135 waiver increased the clinical disciplines eligible to provide and bill for telehealth services. Medicare, Medicaid, and private insurance now reimburse for telehealth services delivered by speech therapists, physical therapists, and occupational therapists. The Section 1135 waiver expanded mental health services by authorizing clinical psychologists and clinical social workers to bill for evaluation and manageVIEWPOINT
Objectives To evaluate the clinical and economic consequences of continuous subcutaneous insulin infusion (CSII) vs. multiple daily injections (MDI) in children and adolescents with type 1 diabetes mellitus (T1DM) from a public health care system in developed areas of developing country, considering changes in glycemic Control, daily insulin requirements, lipid profile, body mass index (BMI), frequency of severe hypoglycemia and Diabetic Ketoacidosis (DKA) and diabetic complications. Methods This was a retrospective cohort study of children and adolescents with T1DM. Data were collected at baseline and the end of every year including glycated hemoglobin (HbA1c), insulin dose, lipid profile, blood pressure, and adverse events (severe hypoglycemia and DKA). The Cost-effectiveness analysis was performed using the IQVIA CORE Diabetes Model (CDM) to simulate diabetes progression by utilizing the clinical data obtained from the two groups. The main outcome measures were Life Expectancy, Quality adjusted life years (QALYs), Total Costs and Incremental Costs and Effectiveness Ratio (ICER) of CSII compared with MDI in Chinese pediatric patients with T1DM in Qingdao City (60 years). Results Mean HbA1c values and daily insulin doses were significantly lower in those receiving CSII therapy throughout follow-up. Mean direct lifetime costs were ¥ 67,137 higher with CSII treatment than with MDI for pediatric patients. Treatment with CSII was associated with an improvement in life expectancy of 0.41 years for pediatric patients compared with MDI based on CORE diabetes model simulation. The corresponding gains in QALYs were 0.42. These data produced corresponding ICER is ¥ 161,815 per QALY for pediatric T1DM patients in Qingdao. Sensitivity analyses suggested that our base-case assumptions were mostly robust. Conclusions CSII is associated with improved long‐term clinical outcomes compared with MDI. Based on this model analysis, CSII appears to be more cost-effective for the Qingdao TIDM pediatric population and health care system.