COVID-19 Mortality by Demographics in a Brooklyn Hospital

Previous publications have shown worse COVID-19 outcomes in African American and LatinX patients. We are sharing the experience of a 750-bed tertiary safety net hospital in Brooklyn, NY. Copyright © Wolters Kluwer Health, Inc. All rights reserved.

Could Earlier Availability of Boosters and Pediatric Vaccines Have Reduced Impact of COVID-19?

The objective is to evaluate the impact of the earlier availability of COVID-19 vaccinations to children and boosters to adults in the face of the Delta and Omicron variants. We employed an agent-based stochastic network simulation model with a modified SEIR compartment model populated with demographic and census data for North Carolina. We found that earlier availability of childhood vaccines and earlier availability of adult boosters could have reduced the peak hospitalizations of the Delta wave by 10% and the Omicron wave by 42%, and could have reduced cumulative deaths by 9% by July 2022. When studied separately, we found that earlier childhood vaccinations reduce cumulative deaths by 2,611 more than earlier adult boosters. Therefore, the results of our simulation model suggest that the timing of childhood vaccination and booster efforts could have resulted in a reduced disease burden and that prioritizing childhood vaccinations would most effectively reduce disease spread. © 2022 IEEE.

An agent-based model of COVID-19 pandemic and its variants using fuzzy subsets and real data applied in an island environment

In this paper, we present a model of the spread of the COVID-19 pandemic simulated by a multi-agent system (MAS) based on demographic data and medical knowledge. Demographic data are linked to the distribution of the population according to age and to an index of socioeconomic fragility with regard to the elderly. Medical knowledge are related to two risk factors: age and obesity. The contributions of this approach are as follows. Firstly, the two aggravating risk factors are introduced into the MAS using fuzzy sets. Secondly, the worsening of disease caused by these risk factors is modeled by fuzzy aggregation operators. The appearance of virus variants is also introduced into the simulation through a simplified modeling of their contagiousness. Using real data from inhabitants of an island in the Antilles (Guadeloupe, FWI), we model the rate of the population at risk which could be critical cases, if neither social distancing nor barrier gestures are respected by the entire population. The results show that hospital capacities are exceeded. The results show that hospital capacities are exceeded. The socioeconomic fragility index is used to assess mortality and also shows that the number of deaths can be significant. © The Author(s), 2023. Published by Cambridge University Press.

Stochastic simulation of successive waves of COVID-19 in the province of Barcelona.

Analytic compartmental models are currently used in mathematical epidemiology to forecast the COVID-19 pandemic evolution and explore the impact of mitigation strategies. In general, such models treat the population as a single entity, losing the social, cultural and economical specificities. We present a network model that uses socio-demographic datasets with the highest available granularity to predict the spread of COVID-19 in the province of Barcelona. The model is flexible enough to incorporate the effect of containment policies, such as lockdowns or the use of protective masks, and can be easily adapted to future epidemics. We follow a stochastic approach that combines a compartmental model with detailed individual microdata from the population census, including social determinants and age-dependent strata, and time-dependent mobility information. We show that our model reproduces the dynamical features of the disease across two waves and demonstrates its capability to become a powerful tool for simulating epidemic events.

Characterizing Internet Access and Quality Inequities in California M-Lab Measurements

It is well documented that, in the United States (U.S.), the availability of Internet access is related to several demographic attributes. Data collected through end user network diagnostic tools, such as the one provided by the Measurement Lab (M-Lab) Speed Test, allows the extension of prior work by exploring the relationship between the quality, as opposed to only the availability, of Internet access and demographic attributes of users of the platform. In this study, we use network measurements collected from the users of Speed Test by M-Lab and demographic data to characterize the relationship between the quality-of-service (QoS) metric download speed, and various critical demographic attributes, such as income, education level, and poverty. For brevity, we limit our focus to the state of California. For users of the M-Lab Speed Test, our study has the following key takeaways: (1) geographic type (urban/rural) and income level in an area have the most significant relationship to download speed;(2) average download speed in rural areas is 2.5 times lower than urban areas;(3) the COVID-19 pandemic had a varied impact on download speeds for different demographic attributes;and (4) the U.S. Federal Communication Commission's (FCC's) broadband speed data significantly over-represents the download speed for rural and low-income communities compared to what is recorded through Speed Test. © 2022 Owner/Author.

Phone Sharing and Cash Transfers in Togo: Quantitative Evidence from Mobile Phone Data

Phone sharing is pervasive in many low- and middle-income countries, affecting how millions of people interact with technology and each other. Yet there is very little quantitative evidence available on the extent or nature of phone sharing in resource-constrained contexts. This paper provides a comprehensive quantitative analysis of demographic variation in phone sharing patterns in Togo, and documents how a large cash transfer program during the COVID-19 pandemic impacted sharing. We analyze mobile phone records from the entire Togolese mobile network to measure the movement of SIM cards between SIM card slots (often on different mobile devices). By matching phone sharing measures derived from SIM reshuffling to demographic data from a government-run cash transfer program covering hundreds of thousands of individuals, we find that phone sharing is most common among women, young people, and people in rural areas. We also leverage randomization in the cash transfer program to find that the delivery of cash aid via mobile money significantly increases phone sharing among beneficiaries. We discuss the limitations of measuring phone sharing with mobile network data and the implications of our results for future aid programs delivered via mobile money. © 2022 Owner/Author.

State Assessment of Demographic Data and Youth Development to Advance 4-H Programs

4-H youth development programs throughout the United States can be planned and delivered more effectively in their states by assessing demographic data and following research-based theories and models of positive youth development. A review of the research literature determined current youth development theories and models to effectively guide statewide 4-H program implementation. A state assessment was conducted for demographic areas of youth population age, race, socioeconomic status, health factors, child poverty (includes parent-guardian job status at the onset of COVID), and household structure. The Ohio 4-H Youth Development program utilized the demographic data to establish goals of becoming more diverse and inclusive. In addition, demographic data points help for targeted recruitment of youth to include families from diverse socioeconomic backgrounds, household structures, and those with health risks. Finally, implications and conclusions are presented to serve as an illustration for other states to advance their state 4-H programs and practices.

Level of Health Effects among Post COVID Patients

Starting in December of 2019, COVID-19 spread worldwide. A rapid infection rate and human-To-human transmission characterize COVID-19. Although the pandemic has been under effective control, numbers of confirmed and suspected cases continue to rise. Physicians, nurses, and ambulance workers are more likely to be infected than any other group. To assess the level of health effect among post COVID patients and to find out association between the level of health effect among post COVID patients with their selected demographic variables. This study was conducted with 60 post-COVID patients in a quantitative approach, non-experimental descriptive design by purposive sampling technique. A self-structured questionnaire method was used to collect both the demographic data and the level of physiological and psychological health effects. 26.7% of them were under grade 1 health effects, 38.3% of them were of grade 2 health effects, and 35% of them had grade 3 health effects due to COVID-19. The study concluded that it is vital to formulate appropriate medical interventions to enhance physical and mental state among post-COVID patients. Mental health should be prioritized during the pandemic. Mental support should be made available and created accessible during and after the COVID-19 outbreak to lessen the ill effect on physiological health status. © (2022) Society for Biomaterials & Artificial Organs #20059122.

Smart Data Analytics on COVID-19 Data

Advances in computers, information and networks has brought a digital cyber world to our daily lives. They have generated numerous digital things (or cyber entities), which have resided in the cyber world. Meanwhile, countless real things in the conventional physical, social and mental worlds have possessed cyber mappings (or cyber components) to have a cyber existence in cyber world. Consequently, cyberization has been an emerging trend forming the new cyber world and reforming conventional worlds towards cyber-enabled hyper-worlds. As such, cybermatics helps build systematic knowledge about new phenomena, behaviors, properties and practices in the cyberspace, cyberization and cyber-enabled hyper-worlds. Cybermatics is characterized by catching up with the human intelligence (e.g. intelligent sensing, making decision and control, etc.), as well as learning from the nature-inspired attributes (e.g., dynamics, self-adaptability, energy saving). As a cybermatics technique, smart data analytics helps filter out the noise data and produce valuable data. In this paper, we focus on smart data analytics on health data related to coronavirus disease 2019 (COVID-19). It builds temporal and demographic hierarchies, which capture characteristics of COVID-19 patients, to discover valuable knowledge and information about temporal-demographic characteristics of these patients. Evaluation on real-life COVID-19 epidemiological data demonstrates the practicality of our solution in conducting smart data analytics on COVID-19 data. © 2021 IEEE.

Covid-19 Vaccination Concerns and its way out in Rustic Zones

The world is experiencing Covid-19. As the pace of rate of Covid infection 2019 (COVID-19) is quickly expanding in various pieces of world, a dependable conjecture for the aggregate affirmed cases and the quantity of passing can be useful for policymakers in settling on the choices for using accessible assets in the country. The widespread of Covid 19 spoilage the world, with the highest loss of lives in US. To reduce the number of Covid-19 affected population, Vaccine are available in public domain. Some Covid 19 Vaccines are currently in human trials. For the effective result of Covid 19 Vaccine, it must be accepted by maximum number of population. A survey was conducted to analyze the health effect of the vaccine in different category of people. Information was collected such as demographic data (age, sex, gender, marital status), mental condition of people before vaccination, tobacco/smoking, alcohol consumption, people suffering from any prior disease, labour group, people taking precaution medicine after vaccination, prepare for second dose of vaccination. Using these given information we have applied machine learning algorithms to predict if the individual will take the second dose of Covid-19 vaccine or not. © 2022 IEEE.

Vida Decision Support System: An International, Collaborative Project for COVID-19 Management with Integrated Modeling

The Vida Decision Support System (Vida) is an application of the Environment-Vulnerability-Decision-Technology (EVDT) integrated modeling framework specifically aimed at COVID-19 impact and response analysis. The development of Vida has been an international collaboration involving multidisciplinary teams of academics, government officials (including public health, economics, environmental, and demographic data collection officials), and others from six states: Angola, Brazil, Chile, Indonesia, Mexico, and the United States. These collaborators have been involved with the identification of decision support needs, the surfacing and creation of relevant data products, and the evaluation of prototypes, with the vision of creating an openly available online platform that integrates earth observation instruments (Landsat, VIIRs, Planet Lab's PlanetScope, NASA's Socioeconomic Data and Applications Center, etc.) with in-situ data sources (COVID-19 case data, local demographic data, policy histories, mobile device-based mobility indices, etc.). Vida both visualizes historical data of relevance to decision-makers and simulates possible future scenarios. The modeling techniques used include system dynamics for public health, EO-based change detection and machine learning for environmental analysis, and discrete-event simulation of policy changes and impacts. In addition to the direct object of this collaboration (the development of Vida), collaborators have also benefited from sharing individual COVID-19-related insights with the network and from considering COVID-19 response in a more integrated fashion. This work outlines the Vida Decision Support System concept and the EVDT framework on which it is based. The international team is using Vida to evaluate the outcomes in several large cities regarding COVID cases, environmental changes, economic changes and policy decisions. It provides an overview of the overlapping and diverging needs and data sources of each of the collaborating teams, as well as how each of those teams have contributed to the development of Vida. The current state of the Vida prototypes and plans for future development will be presented. Additionally, this work will discuss the lessons learned from this development process and their relevance to other integrated applications. Copyright © 2021 by the International Astronautical Federation (IAF). All rights reserved.

Modeling Residential Electricity Consumption from Public Demographic Data for Sustainable Cities

Demographic factors, statistical information, and technological innovation are prominent factors shaping energy transitions in the residential sector. Explaining these energy transitions requires combining insights from the disciplines investigating these factors. The existing literature is not consistent in identifying these factors, nor in proposing how they can be combined. In this paper, three contributions are made by combining the key demographic factors of households to estimate household energy consumption. Firstly, a mathematical formula is developed by considering the demographic determinants that influence energy consumption, such as the number of persons per household, median age, occupancy rate, households with children, and number of bedrooms per household. Secondly, a geographical position algorithm is proposed to identify the geographical locations of households. Thirdly, the derived formula is validated by collecting demographic factors of five statistical regions from local government databases, and then compared with the electricity consumption benchmarks provided by the energy regulators. The practical feasibility of the method is demonstrated by comparing the estimated energy consumption values with the electricity consumption benchmarks provided by energy regulators. The comparison results indicate that the error between the benchmark and estimated values for the five different regions is less than 8% (7.37%), proving the efficacy of this method in energy consumption estimation processes.

An Efficient Exploratory Demographic Data Analytics Using Preprocessed Autoregressive Integrated Moving Average

The demographic dividend is an essential measure of the growth and development of a country. It refers to the economy’s growth due to a shift in the age structure in the country’s population. In India, around 90% of the population is under the age of 60, which is a stark contrast compared to the world, where more than 20% of the population lies above 60. Such a young population ensures that the working-age group will be vibrant in the coming years, adding to the country’s overall productivity. Today, COVID has caused much damage to an already vibrant economy, because of which millions of people have lost their jobs and have had to migrate back to their hometowns. To recover from this severe damage and take stock of the existing and incoming workforce, it is necessary to identify and analyze the current population that lies in suitable age ranges and understand how to use them optimally. Therefore, analyzing the demographic dividend to identify the workforce of the country becomes an essential task. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Assessing the possible impact of patient's demographic data on coronavirus symptoms

Background and objective: A novel COVID-19 condition emerged in December 2019 and has held a dangerous prognosis. It started as an epidemic in China, particularly in Wuhan city. The ages of individuals prone to infection range from one-month-old to above 90 years. However, fewer cases were reported in kids and newborns. Peoples susceptible to infection are the aged, those taking immunosuppressive agents. Usually, Coronavirus holds flu symptoms, including fever (80-90%), dry cough (50%), and lethargy (20-40%);other symptoms include diarrhea. This survey intended to assess the impact of patients' gender, age, and living circumstances on Coronavirus infection symptoms and evaluate a relationship amongst symptoms of patients with Coronavirus infection. Method: In the present survey, the authors have adopted a quantitative survey method, relying upon face-to-face personal interviews, to receive information from the internal hospital consultant in Iraq. The span of data collection was three weeks. One hundred patients were randomly engaged in this research. The study was carried on special closed topics regarding the patients' demographic data (age and gender) and some common signs of COVID-19 "sore throat, fever, shortness of breath, headache, dry cough, wet cough, arthralgia, as well as diarrhea". Results: A sum of 100 cases participated in this research. The reliability value was (0.733). The Chi-Square test revealed no statistically substantial connection between symptoms of Coronavirus among cases and the patients' demographics data (gender and age). Furthermore, the Chi-Square test explained that there was no statistically vital connection amongst symptoms of cases of Coronavirus (shortness of breath & Dry cough, Sore throat & Dry cough, fever & headache, shortness of breath & sore throat) (p > 0.05). Nonetheless, there was a statistically significant correlation amongst symptoms of cases of Coronavirus (sore throat & wet cough, fever & diarrhea, shortness of breath & wet cough) (p < 0.05). Conclusion: There was a negligible influence of the age of the patient on the sharpness of symptoms. Besides, the symptoms of Coronavirus in males were not remarkably different from those in females. Nevertheless, there was a notable association between fever and diarrhea, wet cough and shortness of breath, and wet cough and sore throat. (English) [ FROM AUTHOR] Antecedentes y objetivo: una nueva condición de COVID-19 surgió en diciembre de 2019 y ha tenido un pronóstico peligroso. Comenzó como una epidemia en China, particularmente en la ciudad de Wuhan. Las edades de las personas propensas a la infección varían desde un mes hasta más de 90 años. Sin embargo, se informaron menos casos en niños y recién nacidos. Las personas susceptibles a la infección son los ancianos, los que toman agentes inmunosupresores. Por lo general, el coronavirus presenta síntomas de la gripe, que incluyen fiebre (80-90%), tos seca (50%) y letargo (20-40%);otros síntomas incluyen diarrea. Esta encuesta tenía como objetivo evaluar el impacto del sexo, la edad y las circunstancias de vida de los pacientes en los síntomas de la infección por coronavirus y evaluar la relación entre los síntomas de los pacientes con infección por coronavirus. Método: En la presente encuesta, los autores han adoptado un método de encuesta cuantitativo, basándose en entrevistas personales cara a cara, para recibir información del consultor interno del hospital en Irak. El lapso de recopilación de datos fue de tres semanas. Cien pacientes participaron aleatoriamente en esta investigación. El estudio se llevó a cabo sobre temas especiales cerrados con respecto a los datos demográficos de los pacientes (edad y sexo) y algunos signos comunes de COVID-19 "dolor de garganta, fiebre, dificultad para respirar, dolor de cabeza, tos seca, tos húmeda, artralgia, así como Diarrea". Resultados: En esta investigación participaron un total de 100 casos. El valor de fiabilidad fue (0,733). La prueba de Chi-Cuadrado no reveló una conexión estadísticamente sustancial entre los síntomas del coronavirus entre los casos y los datos demográficos de los pacientes (sexo y edad). Además, la prueba de Chi-Cuadrado explicó que no había una conexión estadísticamente vital entre los síntomas de los casos de coronavirus (dificultad para respirar y tos seca, dolor de garganta y tos seca, fiebre y dolor de cabeza, dificultad para respirar y dolor de garganta) (p> 0,05)). No obstante, hubo una correlación estadísticamente significativa entre los síntomas de los casos de coronavirus (dolor de garganta y tos húmeda, fiebre y diarrea, dificultad para respirar y tos húmeda) (p <0.05). Conclusión: Hubo una influencia insignificante de la edad del paciente en la agudeza de los síntomas. Además, los síntomas del coronavirus en los hombres no fueron muy diferentes de los de las mujeres. Sin embargo, hubo una asociación notable entre fiebre y diarrea, tos húmeda y dificultad para respirar, tos húmeda y dolor de garganta. (Spanish) [ FROM AUTHOR] Copyright of Archivos Venezolanos de Farmacologia y Terapeutica is the property of Archivos Venezolanos de Farmacologia y Terapeutica 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.)

Lessons Learnt from Managing Orthopaedic Trauma During the First Wave of the COVID-19 Pandemic at a UK District General Hospital.

Background: The Coronavirus disease (COVID-19) pandemic has contributed to over 1,000,000 deaths worldwide. Hospitals responded by expanding services to accommodate the forecasted rise in COVID-19-related admissions. We describe the effects these changes had on management of orthopaedic trauma and patient outcomes at a district general hospital in Southern England. Methods: Data were extrapolated retrospectively from two separate 6-week periods in 2019 and 2020 (1st April-13th May) using electronic records of patients referred to the orthopaedic team. Soft tissue injuries were included where a confirmed diagnosis was made with radiological evidence. Patients were excluded if no orthopaedic intervention was required. Data were compared between the two time periods. Results: There were fewer attendances to hospital in 2020 compared with 2019 (178 vs. 328), but time from presentation to surgery significantly increased in 2020 (2.94 days vs. 4.91 days, p = 0.009). There were fewer operative complications in 2020 (36/145 vs. 11/88, p < 0.001). However, ordinal logistic regression analysis found a significantly greater complication severity in 2020 including death (p = 0.039). Complication severity was unrelated to COVID-19 status. Conclusions: Restructuring of orthopaedic services in response to the COVID-19 pandemic has been associated with significant delays to surgery and higher post-operative complication severity. Our results demonstrate the need for fast-track emergency operative orthopaedic services in UK district general hospitals whilst the COVID-19 pandemic continues.

Clinical and demographic characteristics of patients with COVID-19 infection: Statistics from a single hospital in Iran.

Coronavirus disease 2019 (COVID-19) has caused a global pandemic in early 2020. This infectious disorder has a heterogeneous course ranging from asymptomatic disorder to a critical situation needing intensive cares. In the current study, we present a report of affected patients admitted in a single hospital in Iran. Eighty-two hospitalized patients with COVID-19 were assessed. Demographic, clinical, and paraclinical parameters were gathered and statistically analyzed. The median age (IQR) of the patients was 57.32 (45.75, 70) years. At primary evaluation, fever was present in 45.12% of the affected individuals. The most common clinical symptoms were dyspnea (81.71%) and cough (65.85%). Totally, 12 (14.63%) and 14 (17.07%) of patients had low and high WBC counts, respectively. Lymphopenia was detected in 36 (43.9%) of patients, while 6 (7.32%) of patients had lymphocytosis. High levels of Il-6 were detected in 4 (4.88%) of patients. CRP levels were elevated in 69 (84.1%) of patients. The median (IQR) of hospitalization was 7 (5, 9) days. Totally, 26 patients (31%) were hospitalized in ICU. All patients were discharged with good health conditions except for one patient who died. The current study shows the heterogeneous clinical manifestations and paraclinical parameters of COVID-19 patients.