COVID-19 Infection Rates Research Articles

COVID-19 and Family Visits: A Systematic Jurisdiction Analysis of Family Visitation and Safety Policies in Juvenile Correctional Facilities in the United States

When COVID-19 first hit the United States, juvenile correctional facilities across the country discontinued all in-person activities including family visits. Correctional facilities across the country were among the last institutions to reopen their doors for in-person activities given the heightened risk of rapid spread. Drawing on data gathered in February and March 2022, this study examined the state of family visitation policies and COVID-19 safety responses adopted by juvenile correctional facilities, as reported on websites, including information on the different types of contact allowed; COVID-19 safety protocols and practices; availability of information on COVID-19 infection and vaccination rates; and the overall timeliness, consistency, and comprehensiveness of the information available to families with incarcerated minor children. Our findings highlight just how untimely, inconsistent, and incomprehensive information and policies were across jurisdictions, sometimes with little to no stated explanation for their decision-making. We argue that juvenile correctional facilities should take a family-focused approach when developing and disseminating policies that impact the lives of incarcerated youth and their families, especially in times of global uncertainty.

Trends in Intention to Take the Second Booster COVID-19 Vaccination and Associated Factors in China: Serial Cross-Sectional Surveys.

The escalating complexity of the COVID-19 epidemic underscores the need for heightened attention to booster vaccinations. This study aims to examine the changing trend in the public's intention to receive the second COVID-19 booster vaccination over time and the associated factors following the COVID-19 policy optimization in China. Eight cross-sectional surveys utilizing SMS questionnaire links were conducted in Guangzhou, China, from December 2022 to April 2023. The Mann-Kendall test was employed to analyze the trend in intentions to receive the second booster vaccination across the survey time. Adjusted and multivariate logistic analyses were used to analyze the factors associated with vaccination intention. Parallel analyses were performed for two subgroups with different COVID-19 infection statuses. A total of 9860 respondents were surveyed in the eight rounds, of which 8048 completed the first booster vaccination and were included in the analysis. The overall COVID-19 infection rate was 60.0% (4832/8048), while the overall vaccination intention was 72.2% (5810/8048) among respondents. The vaccination intention exhibited a significant declining trend over time, decreasing from 81.5% in December 2022 to 52.2% in April 2023. An adjusted logistic regression analysis revealed that anxiety and depression were negatively associated with an intention to receive the second booster vaccination, while COVID-19-related preventive behaviors and a high engagement in COVID-19-related information were positively associated with an intention to receive the second booster vaccination. A subgroup analysis revealed that the association between psychological and behavioral characteristics and vaccination intention remained relatively stable among individuals with different histories of COVID-19 infections. There was a significant decline in the intention to receive the second booster vaccination following the optimization of the COVID policy in China. Our findings emphasize the urgency of the second booster vaccination and provide a foundation for the development of tailored interventions to enhance and sustain vaccination intention among the public.

Frequency of Mortality and Adverse Outcomes of COVID-19 in Hospitalized Type 2 Diabetics with a History of Sitagliptin or Metformin Use

Background: The relationship between various blood glucose-lowering treatments for type 2 diabetes mellitus (T2DM) and the mortality and complication rates of COVID-19 infection holds significant relevance. Objectives: This retrospective study aimed to investigate the clinical progression of COVID-19 in T2DM patients previously treated with sitagliptin, metformin, or a combination of both. Methods: The study reviewed the medical records of T2DM patients with COVID-19 who had received treatment with sitagliptin, metformin, or both. Participants were selected from those admitted to Naft Hospital in Ahvaz, Iran, from March 2020 to March 2022. Data on mortality and adverse outcomes related to COVID-19 were gathered from the medical records. Results: The study included 529 diabetic patients treated with metformin (n = 197), sitagliptin (n = 231), or both (n = 101) for a minimum of three months. The overall mortality rate among diabetic patients was 15.1%, with the metformin group showing the highest mortality rate at 28.9% (P < 0.0001). Significant differences were observed among the three treatment groups in terms of the frequency of acute respiratory failure (P < 0.0001), stroke (P = 0.002), pulmonary embolism (P < 0.0001), and the necessity for ICU admission (P < 0.0001). Nonetheless, the incidence of myocardial infarction did not significantly differ between the groups. Conclusions: The findings suggest that sitagliptin use for blood sugar control in T2DM patients may help reduce adverse outcomes and the risk of death due to COVID-19. Mortality and morbidity rates were found to be higher in patients treated with metformin compared to those in the other groups.

Evaluating IgG Levels, Vaccination Effects, and COVID-19 Infection Severity in Renal Transplant Recipients

Several studies have reported that different factors play an important role in the production of IgG after VOVID-19 vaccination. This study aimed at studying COVID-19 infection rates and severity in renal transplant recipients and vaccine responsiveness. comorbidity hemodialysis requirements, and immune suppression treatment regimens. In this cross-sectional study, IgG levels was measured in renal transplant recipients using automated benchtop immunoanalyzer Vidas at the Duhok Center for Kidney Disease and Transplantation. In this study group, only 30 individuals experienced the SARS-COVID-2 infection, with only three cases being severe. The most frequently reported symptoms of SARS-COVID-2 virus infection were fatigue (18/30) 60%, high temperature (17/30) 56%, headache (12/30) 40%, and poor endurance (11/30) 36.6%. The IgG titers were significantly different between the vaccinated 33.067 ± 2.5 versus unvaccinated individuals 23.916 ± 3.31with p value = 0.025. On the other hand, demographic characteristics of the cohort including: comorbidities, hemodialysis, different age groups, gender, infection/no-infection differences had no statistically significant impact on the IgG titers. Vaccination significantly increased the levels of protective IgG level in kidney transplant recipients. It is crucial to focus on increasing the acceptance of vaccination among kidney transplant recipients to prevent infections from other COVID-19 variants or pathogen outbreaks.

Investigating the Effects of Control Strategies of Urban Bus Systems during the early outbreak of COVID-19 epidemic in China: a Survey of 211 cities

Whether large-scale COVID-19 tightening policies related to public transit contribute to slower rises in COVID-19 infection rates remains debatable. Therefore, this article extracted text data on urban bus control strategies in 211 Chinese cities and recorded active confirmed cases per million persons per day in each city. The Kruskal-Wallis one-way ANOVA test (K samples) and accompanying pairwise comparisons were conducted using SPSS. Analysis shows that there are noticeable regional differences in the northern and southern parts of China during the pandemic in the control of public transit. Furthermore, based on the economic scale of the same population level, a comparison was made between all cities with high control intensity and some with low control intensity. We find no significant differences in the number of people diagnosed with COVID-19 between the two pairs of some of the compared cities, indicating that the public transport control strategies of some cities are overly strict and questionable. The heat maps of pairwise comparisons show that city pairs with no significant differences in the number of confirmed COVID-19 cases account for many city clusters in the same interval. Additionally, in the comparative analysis of cities with the same population base, the proportion of no significant difference in the statistical analysis results of the number of confirmed COVID-19 cases increased with the decrease of the economic level of the cities. This pattern reflects the overly strict bus control strategies of some less economically developed cities during the COVID-19 pandemic. Therefore, in the face of large-scale epidemics in the future, policies should formulate control strategies based on reality.

Subacute Thyroiditis Following COVID-19 and COVID-19 Vaccination

ObjectiveCOVID-19 infection and immunizations have been implicated in developing a range of thyroid diseases, including subacute thyroiditis (SAT). This study aimed to evaluate the association between COVID-19 infection and/or COVID-19 vaccination with SAT. MethodsA population of 3 million adults insured by Clalit Health Services was evaluated from March 2020 to September 2022. Patients with a new diagnosis of SAT were identified and matched in a 1:10 ratio to a control group. Each control was assigned an index date that was identical to that of their matched case, defined as the date of SAT diagnosis. Multivariate conditional logistic regression models were used to evaluate the association between COVID-19 infection, vaccine, and thyroiditis. ResultsA total of 3221 patients with SAT were matched with 32 210 controls. Rates of COVID-19 vaccination (first, second, or third dose) and COVID-19 infection were evaluated prior to the date of SAT diagnosis (disease group) or index date (control group) to detect a possible association. No difference was detected between the groups in relation to vaccinations at the 30 days, 60 days, and 90 days of time points (P = .880/0.335/0.174, respectively). No difference was found between groups in relation to COVID-19 infection at these time points (P = .735/0.362/0.956, respectively). There was higher use of medications for the treatment of thyroiditis, including nonsteroidal anti-inflammatory drugs (28.6% vs 7.9%, P < .01), steroids (10.3% vs 1.8%, P < .01), and beta-blockers (18.3% vs 5.4%, P < .01). ConclusionBased on this large population study, no association was found between COVID-19 infection and/or the COVID-19 vaccine and SAT.

A Novel Computational Instrument Based on a Universal Mixture Density Network with a Gaussian Mixture Model as a Backbone for Predicting COVID-19 Variants’ Distributions

Various published COVID-19 models have been used in epidemiological studies and healthcare planning to model and predict the spread of the disease and appropriately realign health measures and priorities given the resource limitations in the field of healthcare. However, a significant issue arises when these models need help identifying the distribution of the constituent variants of COVID-19 infections. The emergence of such a challenge means that, given limited healthcare resources, health planning would be ineffective and cost lives. This work presents a universal neural network (NN) computational instrument for predicting the mainstream symptomatic infection rate of COVID-19 and models of the distribution of its associated variants. The NN is based on a mixture density network (MDN) with a Gaussian mixture model (GMM) object as a backbone. Twelve use cases were used to demonstrate the validity and reliability of the proposed MDN. The use cases included COVID-19 data for Canada and Saudi Arabia, two date ranges (300 and 500 days), two input data modes, and three activation functions, each with different implementations of the batch size and epoch value. This array of scenarios provided an opportunity to investigate the impacts of epistemic uncertainty (EU) and aleatoric uncertainty (AU) on the prediction model’s fitting. The model accuracy readings were in the high nineties based on a tolerance margin of 0.0125. The primary outcome of this work indicates that this easy-to-use universal MDN helps provide reliable predictions of COVID-19 variant distributions and the corresponding synthesized profile of the mainstream infection rate.

Influence of vaccination on critical COVID-19 patients with acute respiratory failure: a retrospective cohort study

BackgroundDespite vaccines’ effectiveness in reducing COVID-19 infection rates and disease severity, their impact on critical patients presenting with acute respiratory failure is elusive. The aim of this study was to further investigate the influence of vaccination on mortality rates among severely ill COVID-19 patients experiencing acute respiratory failure.MethodsThis retrospective cohort study was carried out at a tertiary medical center in Taiwan. From April to September 2022, patients who tested positive for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through reverse transcription polymerase chain reaction (RT-PCR) and subsequently experienced acute respiratory failure were included in the study. Baseline characteristics, including vaccination history, along with information regarding critical illness and clinical outcomes, were gathered and compared between patients who received the vaccine and those who did not.ResultsA total of 215 patients with COVID-19 exhibiting acute respiratory failure, as confirmed via RT‒PCR, were included in the analysis. Of this cohort, sixty-six (30.7%) patients died within 28 days. Neither administration of the vaccine nor achievement of primary series vaccination status had a significantly different effect on 28 day mortality, number of viral shedding events, acute respiratory distress syndrome (ARDS) incidence or other clinical outcomes. Patients who received the booster vaccine and completed the primary series showed a tendency of increased 28 days of ventilator-free status, though this difference was not statistically significant (p = 0.815).ConclusionsVaccination status did not significantly influence mortality rates, the occurrence of ARDS, or the viral shedding duration in COVID-19 patients with acute respiratory failure.

Associations between lifestyle factors and COVID-19 infection rates: a cross-sectional analysis in the USA

IntroductionThe COVID-19 pandemic has underscored the vital connection between lifestyle factors and health outcomes, highlighting the need to understand how lifestyle choices influence both chronic and infectious diseases. Despite known...

From art to health action: lessons from a community-based, culturally tailored arts-meets-health educational campaign in Hispanic communities.

Robust digital and community-led approaches are needed to combat health misinformation, as highlighted by the COVID-19 pandemic. Such gaps in public health outreach, compounded by systemic health barriers, contributed to higher rates of COVID-19 infection, mortality, and mental health effects among Hispanics during the peak of the pandemic. Thus, we conducted a community-based art-meets-health intervention [Stay Connected Los Angeles (SCLA)] to address the impacts of the COVID-19 pandemic in Hispanic communities. Led by local artists in collaboration with public health specialists and community members, SCLA used multimedia to promote infection mitigation behaviors and psychological well-being among the 120,000 residents of Eastern Los Angeles. Campaign materials were designed with input from community representatives and included digital media, large-scale murals, and comic-book style pieces. Two semi-structured focus groups (one in English and another in Spanish) were conducted to solicit participants' views on attributes of the campaign. Independent coders analyzed transcripts and applied thematic analysis to summarize key learnings regarding central health and mitigation messages, media modalities, how health information would be communicated, and the ideal spokespersons for delivering health-related messages. Focus group participants emphasized the effectiveness of social media, GIFs, and references to popular media. Further, youth involvement in the creative process was deemed to be important. Participants highlighted the need for clarity in public health messaging and adaptation of visual campaigns to the preferences of diverse age groups through different art styles. Finally, community leaders were found to be critical health information sources. As a model of a culturally tailored arts-meets health public education campaign, SCLA yielded valuable information on how to structure future public health messaging and media to create a meaningful improvement in health knowledge, mental well-being, and compliance with mitigation behaviors in communities that are often overlooked. Contributions from local artists can heighten appeal and acceptability of messages.

Spatial distribution of COVID-19 infection in Thailand and its related factors during 2020-2021

Background: The COVID-19 pandemic, with over 759 million confirmed cases and 6.8 million deaths globally as of March 2023, underscores the critical need for effective control measures. Objectives: This study investigates the spatial dynamics of the disease in Thailand from 2020 to 2021, focusing on the association between demographic, environmental, and socioeconomic factors and COVID-19 infection rates, utilizing Geographic Information Systems. Methods: In this cross-sectional study, QGIS and GeoDa were employed to analyze the spatial pattern of COVID-19 infection rates using Local Moran’s I statistics for spatial autocorrelation. Spatial regression, specifically the Spatial Lag Model and Spatial Error Model was utilized to identify factors related to the observed spatial patterns. Results: The study identified high incidence clusters in southern and central Thailand. Population density, age demographics, and urbanization were found to be positively correlated with incidence rates. Environmental factors such as temperature showed a negative correlation, while forest area coverage exhibited a complex influence. Socioeconomic variables, including income and alcohol density, displayed varying effects, while tobacco density was positively associated with incidence. Conclusion: This comprehensive study underlines the importance of considering spatial dynamics in pandemic analysis. It reveals the multifaceted interplay between demographic, environmental, and socioeconomic factors in COVID-19 transmission. These findings provide valuable insights for targeted interventions and effective pandemic control strategies in Thailand and similar regions.

Examining COVID-19 pandemic-related economic and household stress and its association with mental health, alcohol, and substance use in a national sample of Latinx sexual minority and heterosexual adults.

Sexual minority adults of Latinx descent faced compounded intersectional stressors during the COVID-19 pandemic across socioeconomic and health domains. Latinx people have experienced some of the highest COVID-19 infection, hospitalization, and mortality rates in the United States in addition to significant economic challenges. Yet, current data have not observed the unique pandemic-related experiences of sexual minority Latinx (SML) adults. We examined sexual identity differences in economic and household stress, social support, mental health symptomatology (depression, anxiety), alcohol, and substance use among sexual minority and nonsexual minority Latinx adults in the United States. Primary data were collected via the AmeriSpeak panel, a national probability sample of U.S.-based 2,286 Latinx adults [sexual minority = .34% (n = 465)]. Data were collected from November 2020 to January 2021, during the third wave of the COVID-19 pandemic. SML adults endorsed higher levels of economic and household stress, mental health symptomatology, and alcohol and substance use than nonsexual minority Latinx adults. Economic stress was associated with increased mental health symptomatology, alcohol, and substance use among SML adults. Social support moderated the association between economic stress and mental health symptomatology and substance use, but not alcohol use. Findings highlighted unique intersectional considerations among SML adults during the COVID-19 pandemic, including the importance of social support and the negative toll of economic stress on mental health and substance use. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The economics of deep and machine learning-based algorithms for COVID-19 prediction, detection, and diagnosis shaping the organizational management of hospitals

Research background: Deep and machine learning-based algorithms can assist in COVID-19 image-based medical diagnosis and symptom tracing, optimize intensive care unit admission, and use clinical data to determine patient prioritization and mortality risk, being pivotal in qualitative care provision, reducing medical errors, and increasing patient survival rates, thus diminishing the massive healthcare system burden in relation to severe COVID-19 inpatient stay duration, while increasing operational costs throughout the organizational management of hospitals. Data-driven financial and scenario-based contingency planning, predictive modelling tools, and risk pooling mechanisms should be deployed for additional medical equipment and unforeseen healthcare demand expenses. Purpose of the article: We show that deep and machine learning-based and clinical decision making systems can optimize patient survival likelihood and treatment outcomes with regard to susceptible, infected, and recovered individuals, performing accurate analyses by data modeling based on vital and clinical signs, surveillance data, and infection-related biomarkers, and furthering hospital facility optimization in terms of intensive care unit bed allocation. Methods: The review software systems employed for article screening and quality evaluation were: AMSTAR, AXIS, DistillerSR, Eppi-Reviewer, MMAT, PICO Portal, Rayyan, ROBIS, and SRDR. Findings &amp; value added: Deep and machine learning-based clinical decision support tools can forecast COVID-19 spread, confirmed cases, and infection and mortality rates for data-driven appropriate treatment and resource allocations in effective therapeutic and diagnosis protocol development, by determining suitable measures and regulations and by using symptoms and comorbidities, vital signs, clinical and laboratory data and medical records across intensive care units, impacting the healthcare financing infrastructure. As a result of heightened use of personal protective equipment, hospital pharmacy and medication, outpatient treatment, and medical supplies, revenue loss and financial vulnerability occur, also due to expenses related to hiring additional staff and to critical resource expenditures. Hospital costs for COVID-19 medical care, screening, treatment capacity expansion, and personal protective equipment can lead to further financial losses while affecting COVID-19 frontline hospital workers and patients.

Through the eyes of community health workers: what was needed to increase COVID-19 vaccine uptake in the Missouri Southeast region.

Public health emergencies, such as the COVID-19 pandemic, elucidate the strengths, weaknesses, and significant gaps in infrastructure, compatibility and consistency in communication systems, as well as the quality of collaborative relationships, and provider and workforce capacity. They also expose longstanding patterns of mistrust in the government and healthcare systems, and inadequacy in socio-economic infrastructures. These issues resulted in higher COVID-19 infection and mortality rates, and lower vaccination rates in many rural counties across the nation, including Missouri. In response to these challenges, the COVID-19 Response Network was formed in the Southeast corner of the state. The Network was a community-academic partnership that brought together community and faith-based leaders, academicians, healthcare providers and administrators, public health practitioners, and pharmacists to facilitate collaboration on education and outreach efforts aimed at reducing vaccine inequity in the 16-county project area. Importantly, the Network also included Community Health Workers (CHWs) who worked with these different agencies and organizations and were at the heart of implementing Network activities. The intent of this study was to assess their perspectives on the factors that influenced community engagement and communication strategies, and increased vaccine uptake in rural Missouri. Qualitative methods, including in-depth interviews, were used to explore the professional and personal experiences of CHWs working at the grassroots level during an ongoing pandemic. Narrative analysis revealed effective communication and engagement strategies for increasing vaccine uptake in rural communities. For instance, fear-based messaging was perceived as coercive and met with resistance. In contrast, messages that shared personal experiences and catered to the human need to protect their loved ones were more effective. Trust in the source of information was critical. This study highlights the significance of exploring and leveraging the capacities of trusted community members like CHWs to increase the effectiveness of public health interventions in rural communities.

Home alone: Evaluating the implications of government mandates and disease prevalence on time usage during the pandemic

During the COVID-19 pandemic governments and individuals alike faced incentives to limit the spread of the disease. Our objective is to assess the extent to which government mandates and private actions influenced time allocated to specific activities and the social interactions of individuals. Information on how individuals spent their time before and during the early stages of the pandemic come from the American Time Use Survey (ATUS), which identifies time use for a 24-hour period and includes each individual's activities, locations and companions. We combine the time diary data with data on state-level restrictions from the Kaiser Family Foundation and state-level COVID-19 infection and death rates from Johns Hopkins University. Our findings suggest that private actions in response to reported death rates are comparable to the effects of state-level public mandates on the outcome variables of time alone and time at home. In evaluating effects based on sex and age, we find that young males experienced the largest disruption in time use, significantly changing both their location and their companions. We also find important age profile differences between males and females.

Motives for Vaccination Against COVID-19 Among the Ultra-orthodox Jewish Community in Israel

According to official data, the ultra-Orthodox group in Israel had the highest COVID-19 infection rate yet the lowest vaccination rate compared to the general population. The present study aimed to explore the rate of vaccine uptake as well as reported reasons for vaccine avoidance. In addition, we examined whether several protection motivation theory (PMT) components are good predictors of vaccine uptake. The components we addressed were: perceived susceptibility to the threat of COVID-19, perceived severity of the virus, and perceived efficiency and safety of the vaccine (i.e., response efficacy). The sample included 623 individuals (337 men) aged 18 + who were drawn from a database of a survey company specializing in the ultra-Orthodox community. We conducted a cross-sectional online survey between June 22, 2021, and July 7, 2021, approximately six months after the beginning of vaccination distribution. Results revealed that 65.8% of the participants (versus 89% of the general population) were vaccinated. Women were vaccinated at lower rates than men, whereas those in the Misnagdim ultra-Orthodox subgroup were vaccinated at higher rates than other subgroups in that community. The most prominent reasons for vaccine avoidance were perceived immunity based on prior infection by the virus and lack of trust in the vaccine’s safety. In support of the PMT model, the perceived severity of the virus and the vaccine high efficacy were significant predictors of vaccine uptake. The study results call for better outreach to this community and specific psycho-education interventions tailored for its women.

Influence of Environmental Factors and Genome Diversity on Cumulative COVID-19 Cases in the Highland Region of China: Comparative Correlational Study.

The novel coronavirus SARS-CoV-2 caused the global COVID-19 pandemic. Emerging reports support lower mortality and reduced case numbers in highland areas; however, comparative studies on the cumulative impact of environmental factors and viral genetic diversity on COVID-19 infection rates have not been performed to date. The aims of this study were to determine the difference in COVID-19 infection rates between high and low altitudes, and to explore whether the difference in the pandemic trend in the high-altitude region of China compared to that of the lowlands is influenced by environmental factors, population density, and biological mechanisms. We examined the correlation between population density and COVID-19 cases through linear regression. A zero-shot model was applied to identify possible factors correlated to COVID-19 infection. We further analyzed the correlation of meteorological and air quality factors with infection cases using the Spearman correlation coefficient. Mixed-effects multiple linear regression was applied to evaluate the associations between selected factors and COVID-19 cases adjusting for covariates. Lastly, the relationship between environmental factors and mutation frequency was evaluated using the same correlation techniques mentioned above. Among the 24,826 confirmed COVID-19 cases reported from 40 cities in China from January 23, 2020, to July 7, 2022, 98.4% (n=24,430) were found in the lowlands. Population density was positively correlated with COVID-19 cases in all regions (ρ=0.641, P=.003). In high-altitude areas, the number of COVID-19 cases was negatively associated with temperature, sunlight hours, and UV index (P=.003, P=.001, and P=.009, respectively) and was positively associated with wind speed (ρ=0.388, P<.001), whereas no correlation was found between meteorological factors and COVID-19 cases in the lowlands. After controlling for covariates, the mixed-effects model also showed positive associations of fine particulate matter (PM2.5) and carbon monoxide (CO) with COVID-19 cases (P=.002 and P<.001, respectively). Sequence variant analysis showed lower genetic diversity among nucleotides for each SARS-CoV-2 genome (P<.001) and three open reading frames (P<.001) in high altitudes compared to 300 sequences analyzed from low altitudes. Moreover, the frequencies of 44 nonsynonymous mutations and 32 synonymous mutations were significantly different between the high- and low-altitude groups (P<.001, mutation frequency>0.1). Key nonsynonymous mutations showed positive correlations with altitude, wind speed, and air pressure and showed negative correlations with temperature, UV index, and sunlight hours. By comparison with the lowlands, the number of confirmed COVID-19 cases was substantially lower in high-altitude regions of China, and the population density, temperature, sunlight hours, UV index, wind speed, PM2.5, and CO influenced the cumulative pandemic trend in the highlands. The identified influence of environmental factors on SARS-CoV-2 sequence variants adds knowledge of the impact of altitude on COVID-19 infection, offering novel suggestions for preventive intervention.

Spatiotemporal analysis of urban development patterns and COVID-19 in Mashhad, Iran

This study evaluates the impact of city spatial development patterns on the spread of airborne pandemics, focusing on Mashhad, Iran. Using ArcGIS spatial statistics, 91 spatial indices were examined between March 5, 2020, and October 2, 2021, during five distinct waves of the virus, revealing that private vehicle ownership and limited use of public transportation did not significantly reduce COVID-19 infection rates in Mashhad. Instead, factors such as proximity to transportation hubs, healthcare facility polarization, and retail shop distribution had a significant impact. Surprisingly, demographic vulnerability and conventional population-related factors had relatively minor effects. The study also highlights the influence of building concentration with high floor area ratios (FAR) and the impact of local authorities' optimism in reducing social distancing measures, especially in travel and traffic control, on the increased spread of the virus during recent waves.

Does Western or Chinese Zodiac Sign Predict COVID Infections and Death?

Humans have been fascinated by and studying the sky since the beginning of time. Beliefs in Chinese and Western astrology persist in modern society and have gained increasing interest in light of the COVID-19 pandemic. Zodiac signs are typified by certain qualities, for example, obsessive-compulsive traits in Libras and Virgos or the highly social traits in Leos and Geminis. We investigate whether the various characteristics or personalities purported of assigned birth signs may alter the predisposition to COVID-19 infections or mortality. This is a retrospective, single-center cohort study of 2545 adult patients with confirmed COVID-19 infection presenting to the emergency room over a 14-month period (September 2020 to November 2021). COVID-19 infectivity was determined based on polymerase chain reaction (PCR) testing. Western and Chinese Zodiac signs were designated using date of birth. Both Zodiac signs were evaluated for risk of infection and death. Mortality rates across the zodiac and astrology signs showed no statistical difference using the 12-sample test for equality of proportions. Coincidentally, the mean age for the deceased was 74.5 years, and it was 53.9 years for those alive, resulting in a difference of 20.6 years. A two-sample t-test confirms that the observed difference of 20.6 years of age between the two groups is statistically significant with a p-value <0.05. The coefficient of the predictor age is statistically significant. The odds ratio estimate of age is 1.06, with the corresponding 95% confidence interval (CI) being (1.048, 1.073). This means that the odds of dying increase by 6% for every additional year. Astrology once held a significant impact on beliefs in medicine and continues in Chinese and Ayurvedic medicine. Our study utilized local data to determine if COVID-19 infection rates and mortality might have a relationship to astrological designations of Chinese and Western zodiac signs. Data analysis demonstrated that there was no statistical significance found between Western and Chinese Zodiac signs and mortality or infections. Similar to many previous studies, age can be a risk factor for mortality.

COVID-19 vaccines breakthrough infection and adverse reactions in medical students: a nationwide survey in Iran.

There are different types of COVID-19 vaccines approved worldwide. Since no national studies focus on vaccine-related adverse reactions and breakthrough cases, this study aimed to investigate the rate of adverse events and COVID-19 infection in medical students in Iran. This retrospective cohort study included Iranian medical students who received two doses of COVID-19 vaccines. The medical team gathered the demographic characteristics, comorbidities, type of vaccine, adverse events following vaccination, and history of COVID-19 infection data through a phone interview. The frequency of adverse events and breakthrough infection was stratified by vaccine type (ChAdOx1-S, Gam-COVID-Vac, and BIBP-CorV). A total of 3,591 medical students enrolled in this study, of which 57.02% were females, with a mean age of 23.31 + 4.87. A PCR-confirmed and suspicious-for-COVID-19 breakthrough infection rate of 4.51 and 7.02% was detected, respectively. There was no significant relation between breakthrough infection and gender, BMI, blood groups, and comorbidities. However, there was a significant difference in breakthrough infection rate among different types of vaccines (p = 0.001) and history of COVID-19 infection (p = 0.001). A total of 16 participants were hospitalized due to COVID-19 infection after vaccination for reasons such as dyspnea, abnormal imaging, or decreased oxygen saturation. No severe infection or death was observed in the studied population. Vaccination prevented severe COVID-19 infection, although a high breakthrough infection rate was evident among Iranian medical students during the Delta variant's peak. Vaccine effectiveness may be fragile during emerging new variants and in high-exposure settings. Moreover, adverse events are rare, and the benefits of vaccination outweigh the side effects. However, many limitations challenged this study, and the results should be cautious.