COVID-19 Infection Rates Research Articles

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.

Incidence Rate of Covid-19 Infection in People with Fourth Dose of Vaccines Bivalent Mrna from October 2022 to October 2023 in A General Medicine Office in Toledo (Spain)

Background Incidence rate of covid-19 infection in people vaccinated with 4th dose of RNA covid-19 vaccine remain subject of debate and is not clearly known Objective Estimate the incidence rate of covid-19 in vaccinated 4th dose people in general practitioner care level. Methodology An incidence rates epidemiological analysis of covid-19 infection in people with 4th dose of bivalent mRNA vaccines based in a longitudinal study from October, 2022 to October, 2023, in a general practice setting in Toledo, Spain. Results 21 cases of covid-19 infection in vaccinated people with 4th dose were included. Incidence rate of covid-19 infection in total vaccinated people with 4th dose from October 2022 to October 2023 was 2%; it was greater in &gt; = 65 years vs. &lt; 65 years (3% vs. 1%), and in women vs. men (2% vs. 1%). Regarding incidence rate of covid-19 infection in vaccinated people with 4th dose in general population of the office was 1%; It was again older at &gt; = 65 years vs. &lt; 65 years (1% vs. 0.5%), but without differences between women and men (1% vs. 1%). Conclusion In general practice setting in Toledo, Spain, crude incidence rate of covid-19 infection in vaccinated people with 4th dose and in general population of the office was low. However, the population segments of &gt;= 65 years and women, even with fourth vaccine dose, have a higher risk of covid-19 infection, and consequently should continue receiving booster vaccine. But these results should be interpreted with caution since the number of tests carried out in the community was low

Vaccination coverage against COVID-19 among rural population in Haryana, India: A cross-sectional study.

Conducting a study in rural pre-dominant areas will help to understand the penetration of the vaccination campaign during the COVID-19 health crisis. This study aimed to investigate vaccination coverage against COVID-19 among the rural adult population in India and to identify factors associated with vaccination coverage. A population-based cross-sectional study was conducted among the rural population in one district of north India from January to February 2023. A semi-structured questionnaire was designed on the SurveyMonkey digital platform for interviewing the participants, which consisted of questions related to socio-demographic profile, health problems, vaccination status, types of vaccine, re-infection after vaccination, and functional difficulties. The data regarding infection with COVID-19 was collected based on self-reported positive testing for SARS-CoV 2 on RT-PCR. A total of 3700 eligible individuals were enumerated for the survey, out of which 2954 (79.8%) were interviewed. The infection rate of past COVID-19 infection, based on self-report of testing positive, was 6.2% (95%CI: 5.3-7.1). Covishield vaccine was received by most participants (81.3%, 2380) followed by Covaxin (12.3%, 361) and Pfizer manufactured vaccine (0.03,1). The coverage for first, second, and booster doses of the vaccine was 98.2% (2902), 94.8% (2802), and 10.7% (315) respectively. The risk of reinfection at 12 months or more among participants with two doses of vaccine was 1.6% (46/2802, 95%CI: 1.2-2.1). The coverage among those with severe functional difficulties was lesser as compared to those with some or no difficulties. Vaccination coverage against COVID-19 in rural Haryana, India is not dependent on factors like gender or occupation but is dependent on age and education. Although the full and partial vaccination coverage is high, the booster dose coverage is poor. In addition, the presence of severe disability was significantly associated with reduced vaccination coverage.

A mathematical model for the transmission of co-infection with COVID-19 and kidney disease

The world suffers from the acute respiratory syndrome COVID-19 pandemic, which will be scary if other co-existing illnesses exacerbate it. The co-occurrence of the COVID-19 virus with kidney disease has not been available in the literature. So, further research needs to be conducted to reveal the transmission dynamics of COVID-19 and kidney disease. This study aims to create mathematical models to understand how COVID-19 interacts with kidney diseases in specific populations. Therefore, the initial step was to formulate a deterministic Susceptible-Infected-Recovered (SIR) mathematical model to depict the co-infection dynamics of COVID-19 and kidney disease. A mathematical model with seven compartments has been developed using nonlinear ordinary differential equations. This model incorporates the invariant region, disease-free and endemic equilibrium, along with the positivity solution. The basic reproduction number, calculated via the next-generation matrix, allows us to assess the stability of the equilibrium. Sensitivity analysis is also utilised to understand the influence of each parameter on disease spread or containment. The results show that a surge in COVID-19 infection rates and the existence of kidney disease significantly enhances the co-infection risks. Numerical simulations further clarify the potential outcomes of treating COVID-19 alone, kidney disease alone, and co-infected cases. The study of the potential model can be utilised to maximise the benefits of simulation to minimise the global health complexity of COVID-19 and kidney disease.

Critical lessons from a pragmatic randomized trial of home-based COVID-19 testing in rural Native American and Latino communities.

Native Americans and Latinos have higher COVID-19 infection and mortality rates and may have limited access to diagnostic testing. Home-based testing may improve access to care in rural and underserved populations. This study tests the effect of community health worker (CHW) support on accessibility, feasibility, and completion of COVID-19 home testing among Native American and Latino adults living on the Flathead Reservation in Montana and in Yakima Valley, Washington. A two-arm, multisite, pragmatic randomized controlled trial was conducted using block randomization stratified by site and participant age. Active arm participants received CHW assistance with online COVID-19 test kit registration and virtual swabbing support. The passive arm participants received standard-of-care support from the kit vendor. Logistic regression modeled the association between study arm and test completion (primary outcome) and between study arm and test completion with return of valid test results (secondary outcome). Responses to posttest surveys and interviews were summarized using deductive thematic analysis. Overall, 63% of participants (n=268) completed COVID-19 tests, and 50% completed tests yielding a valid result. Active arm participants had higher odds of test completion (odds ratio: 1.66, 95% confidence interval [1.01, 2.75]). Differences were most pronounced among adults ≥60years. Participants cited ease of use and not having to leave home as positive aspects, and transportation and mailing issues as negative aspects of home-based testing. CHW support led to higher COVID-19 test completion rates, particularly among older adults. Significant testing barriers included language, educational level, rurality, and test kit issues.

Mental and Physical Symptoms and Perceived Health Risks of Pregnant and Postpartum Women following the Significant Shift in COVID-19 Management in China: A Cross-Sectional Survey

Background. There was a remarkable downgrade in China’s COVID-19 response strategies in January 2023. The COVID-19 infection rate grew rapidly in the early stages following the management policy shift. This study attempted to explore the associations between SARS-CoV-2 infection and mental or physical health status in pregnant and postpartum women and the role of perceived health risks and family members’ SARS-CoV-2 infection status on these associations by capturing the impact of policy shifts in a short period of time. Methods. This cross-sectional study with a random sample from a convenience sample of hospitals was conducted in pregnant and postpartum women in January 2023. Standardized assessment tools were employed to assess anxiety, depressive and physical symptoms, and feelings of hopelessness. Hierarchical multiple logistic regressions were conducted to examine the mechanisms of associations of interests by including a range of sociodemographic factors, self-perceived health, SARS-CoV-2 infection status, and perceived health risks as covariates. Results. Of the 1,013 pregnant and postpartum women aged 32.0 ± 0.3 years, 58.2% (n = 590) were diagnosed with COVID-19, and 49.4% (n = 500) had family members who were infected with SARS-CoV-2. Nearly 98% of the included participants took measures to prevent SARS-CoV-2 infection. A COVID-19 diagnosis was positively associated with feelings of hopelessness (OR = 1.68, 95% CI: 1.20–2.35), probable anxiety (OR = 6.42, 95% CI: 2.18–24.61), possible depression (OR = 2.56, 95% CI: 1.07–6.70), and physical symptoms (OR = 6.28, 95% CI: 1.63–42.03) after adjusting for sociodemographic and health characteristics, while the associations presented no statistical significance when family members’ SARS-CoV-2 infection status and perceived health risks were introduced into the models. Conclusions. Our results suggested that pregnant and postpartum women may experience physical and mental health challenges when they or their family members contracted COVID-19 in the context of a considerable shift in COVID-19 management. Early detection of poor health status and its risk factors for vulnerable groups during shifts in health policy and administrative practice is very necessary, and health services, including easy access to psychosocial support and obstetric counselling, should be prioritized.

Estimating hidden relationships in dynamical systems: Discovering drivers of infection rates of COVID-19.

Discovering causal influences among internal variables is a fundamental goal of complex systems research. This paper presents a framework for uncovering hidden relationships from limited time-series data by combining methods from nonlinear estimation and information theory. The approach is based on two sequential steps: first, we reconstruct a more complete state of the underlying dynamical system, and second, we calculate mutual information between pairs of internal state variables to detail causal dependencies. Equipped with time-series data related to the spread of COVID-19 from the past three years, we apply this approach to identify the drivers of falling and rising infections during the three main waves of infection in the Chicago metropolitan region. The unscented Kalman filter nonlinear estimation algorithm is implemented on an established epidemiological model of COVID-19, which we refine to include isolation, masking, loss of immunity, and stochastic transition rates. Through the systematic study of mutual information between infection rate and various stochastic parameters, we find that increased mobility, decreased mask use, and loss of immunity post sickness played a key role in rising infections, while falling infections were controlled by masking and isolation.

Prevalence and Predictors of COVID-19 Breakthrough Infections Among Vaccinated Health Care Providers and Medical Students at All India Institute of Medical Sciences Nagpur, Central India

ABSTRACT Context: As per the national policy, two doses of COVID-19 vaccine at least four weeks apart were available for administration to all HCW’s since January 2021. A small proportion of individuals will contract COVID-19 despite complete vaccination. Healthcare workers (Health Care Providers) represent a very high-risk group for contracting COVID-19 infection. Aim: To determine the breakthrough infection rate of COVID-19 among vaccinated healthcare providers and students. Methodology: The present cross-sectional study was conducted at All India Institute of Medical Sciences, Nagpur from August to December 2022. The sample size of 308 was achieved through proportionate stratified sampling among different cadres of employees working at the institute. Statistical Analysis: Chi-square test was used for significance. Fischer’s Exact test was used wherever necessary. A P value &lt; 0.05 was considered statistically significant. Strength of the association was estimated using odds ratio. Results: The mean (SD) age of participants in our study was 29.26 (±8.64) years. Prevalence of COVID breakthrough infection was found to be 28.25% [95% CI: 23–33]. It was found that those participants having one or more co-morbidities and are directly involved in COVID patient care were likely to suffer more from COVID-19 breakthrough infection. Conclusion: Predictors of COVID-19 breakthrough infection found to be a presence of one or more co-morbidities, direct involvement with COVID-19 patients and not observing respiratory hygiene. There is increased risk among participants with comorbidities and involving directly in patient care. Therefore, it is recommended that vaccine policy needs to focus on high-risk group.

Myasthenia Gravis and COVID-19: A Systematic Review and Meta-analysis.

Patients with myasthenia gravis (MG), an autoimmune disease affecting the neuromuscular junction, exhibits varying rates of COVID-19 infection across different studies. This systematic review and meta-analysis aim to estimate the pooled prevalence of COVID-19 infection in individuals with MG. We systematically searched PubMed, Scopus, EMBASE, Web of Science, Google Scholar, and gray literature, including references to the research published before October 2021. The total number of participants, the first author, the publication year, the country of origin, the number of MG patients, their symptoms, hospitalization rates, and deaths were all extracted as study data. Our literature search yielded 253 articles, of which 75 remained after removing duplicates. Finally, 18 articles were included in the meta-analysis. The pooled prevalence of COVID-19 infection in MG cases was found to be 2% (95% CI, 1%, 3%; I2=85%, P<0.001). Additionally, the pooled prevalence of hospitalization among those with COVID-19 infection was 43% (95% CI, 26%, 60%; I2=97.6%; P<0.001), and the pooled prevalence of MG exacerbation was 33% (95% CI, 20%, 46%; I2=92.6%; P<0.001). In summary, this systematic review and meta-analysis reveal that the pooled prevalence of COVID-19 infection in individuals with MG is 2%.

Social and Environmental Factors Influencing COVID-19 Transmission and Mortalities in Developing and Developed Nations

Background: The study sought to establish environmental and social factors that influenced the transmission and mortalities of COVID-19 in developing and developed nations. The factors that were assessed included temperature, average age of the population, urbanization, population density, and percentage of old-aged people in the population. The dependent variables were COVID-19 transmission and COVID-19-related deaths. Methods: The study employed a pragmatism research philosophy. It also relied on a deductive research approach and a descriptive research design. It adopted a mixed-method approach as it used both qualitative and quantitative data. It was a cross-sectional study, given its data measurement at a particular point in time. Data was analyzed and presented using descriptive techniques. Results: Statistical analyses were conducted to quantify the relationships between various factors and COVID-19 outcomes. A Kendall’s Tau test revealed a robust negative correlation between COVID-19 cases and temperature (Tb = -0.560, p&lt;0.005). This result was further confirmed by Spearman’s rank correlation, showing a strong negative correlation with r(13) = -0.684, p&lt;0.007. Similarly, a strong negative correlation was observed between COVID-19 deaths and average annual temperature using both Kendall’s Tau (Tb = -0.495, p&lt;0.014) and Spearman’s rank correlation (r(13) = -0.648, p&lt;0.012). Age emerged as a significant factor, with a strong positive correlation found between age and both COVID-19 infections (Tb = 0.516, p&lt;0.010; r(13) = 0.670, p&lt;0.009) and COVID-19-related mortalities (r(13) = 0.516, p&lt;0.029). Urbanization was also positively correlated with COVID-19 infections (Tb = 0.530, p&lt;0.008; r(13) = 0.640, p&lt;0.014) and COVID-19 deaths (Tb = 0.398, p&lt;0.048; r(13) = 0.561, p&lt;0.037). Interestingly, no significant correlation was found between population density and COVID-19 infections or deaths in both developed and developing countries, as evidenced by Kendall’s Tau (TB = 0.331, p&lt;0.1; Tb = 0.133, p&lt;0.511) and Spearman’s rank correlation (r(13) = 0.425, p&lt;0.130; r(13) = 0.161, p&lt;0.583), respectively. Moreover, the percentage of elderly individuals in a country exhibited a strong positive correlation with both COVID-19 infections (Tb = 0.464, p&lt;0.021; r(13) = 0.642, p&lt;0.013) and COVID-19-related deaths (r(13) = 0.541, p&lt;0.046).Conclusion: The study focused on social, demographic, and environmental factors influencing COVID-19 incidence and mortality in developing and developed nations. The study highlights significant COVID-19 transmission and mortality disparities between developed and developing countries. Developed countries exhibited higher infection and mortality rates, coupled with elevated death rates per million and infection rates per million, as compared to their developing counterparts. The research identified a correlation between lower average annual temperatures and increased mortality in developed countries. Contrary to this, high average annual temperatures were associated with a decline in COVID-19 infections.Moreover, developed countries, characterized by higher urbanization levels, population densities, and percentages of aged individuals, experienced elevated COVID-19 infection rates. The study also unveiled a positive correlation between age and COVID-19 infections, with developed countries hosting significantly older populations than their developing counterparts. However, population density did not clearly correlate with COVID-19 infections or deaths.

A population level study on the determinants of COVID-19 vaccination rates at the U.S. county level

Multiple COVID-19 vaccines were proven to be safe and effective in curbing severe illness, but despite vaccine availability, vaccination rates were relatively low in the United States (U.S.). To better understand factors associated with low COVID-19 vaccine uptake in the U.S., our study provides a comprehensive, data-driven population-level statistical analysis at the county level. We find that political affiliation, as determined by the proportion of votes received by the Republican candidate in the 2020 presidential election, has the strongest association with our response variable, the percent of the population that received no COVID-19 vaccine. The next strongest association was median household income, which has a negative association. The percentage of Black people and the average number of vehicles per household are positively associated with the percent unvaccinated. In contrast, COVID-19 infection rate, percentage of Latinx people, postsecondary education percentage, median age, and prior non-COVID-19 childhood vaccination coverage are negatively associated with percent unvaccinated. Unlike previous studies, we do not find significant relationships between cable TV news viewership or Twitter misinformation variables with COVID-19 vaccine uptake. These results shed light on some factors that may impact vaccination choice in the U.S. and can be used to target specific populations for educational outreach and vaccine campaign strategies in efforts to increase vaccination uptake.

Correlation or Causation: Unraveling the Relationship between PM2.5 Air Pollution and COVID-19 Spread Across the United States

Numerous studies have examined the potential connection between air pollution, particularly PM2.5, and the incidence of COVID-19 cases during the pandemic. While several studies have demonstrated a strong correlation, caution is advised as correlation does not imply causation. To address this concern, our two-year observational study employs a comprehensive approach that utilizes a large sample size and draws on temporal and spatial data across the United States, surpassing the limitations of previous studies restricted to specific locations. Through rigorous correlation and regression analyses, we control for potential confounding factors. Air pollution data, a crucial component of our study, has been sourced from the United States Environmental Protection Agency (EPA). Additionally, COVID-19 case data is extracted from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, providing a robust and widely recognized dataset for our analyses. Notably, a significant spatial correlation exists between COVID-19 cases and population size (r=0.98, p-value &lt;0.01), as confirmed by multivariate regression analysis, suggesting a confounding influence of population. It is crucial to emphasize that correlation does not automatically imply a direct cause-and-effect relationship. Moreover, to minimize the impact of population, we employ rates (COVID-19 cases/population of States), demonstrating that the rate of COVID-19 cases is independent of PM2.5 and population. Additionally, the rate of COVID-19 infection is not correlated with population density, implying the population's influence on infection is more likely due to probability rather than being a direct cause. In summary, while many studies report a correlation between air pollution and COVID-19 cases, the influence of confounding factors like population density necessitates further investigation to establish a definitive causal relationship. In conclusion, while many studies report a correlation between air pollution and COVID-19 cases, the influence of confounding factors like population density necessitates further investigation to establish a definitive causal relationship.

An epidemiological survey of COVID-19 serology and its association with clinical infection among older adults– does antibody titer matter?

BackgroundOlder adults are at increased risk of severe SARS-CoV-2 infection. In this study we assessed the response to COVID-19 vaccination and infection rates among nursing homes (NH) and assisted-living care home (ALCH) residents.MethodsThe study was conducted between August 2021 and January 2022, after widespread population vaccination with the third dose of Pfizer-BioNtech mRNA COVID-19 vaccine in Israel. Three groups were addressed: hospitalized older patients; NH and ALCH residents. Demographic data, COVID-19 serology (anti-spike IgG antibodies) and PCR test results were obtained to assess the dynamics of antibody titers and its correlation to infection rates.ResultsTwo-hundred eighty-five individuals were evaluated; 92 hospitalized patients; 100 ALCH residents and 93 NH residents. In the latter two groups two serology surveys were conducted three months apart. Hospitalized patients were younger than ALCH and NH residents (mean age 80.4 ± 8 versus 82.6 ± 8 and 83.6 ± 5, respectively, p = 0.01), and had more comorbidities (p = 0.003). The degree of decline in the antibody level overtime was similar in ALCH and NH residents. Infection rates were higher among NH residents than ALCH residents [35/91 (38.4%) versus 11/100 (11%), p < 0.001]. Antibody level was lower among those infected [2113 (1271–3512) Au/ml versus 4113 (3364–5029) Au/ml, p < 0.001]. Adjusted analysis showed that NH residence, but not antibody levels, were significantly associated with infection.ConclusionAmong older adults, infection rates inversely correlated with antibody level. However, only nursing home residence was significantly associated with infection, suggesting that other factors such as crowding considerably contribute to the risk of infection.

Impact of COVID-19 on essential service provision for reproductive, maternal, neonatal, and child health in the Southeast Asia region: a systematic review

There is increasing evidence that the COVID-19 pandemic has impacted adversely on the provision of essential health services globally. The Southeast Asia region (SEAR) has experienced extremely high rates of COVID-19 infection, with potential adverse impacts on provision of reproductive, maternal, neonatal, and child health (RMNCH) services. We conducted a systematic literature review of quantitative evidence to characterise the impact of COVID-19 on the provision of essential RMNCH services across the SEAR. Studies published between December 2019 and May 2022 were included in the study. The quality of studies was evaluated using the Joanna Briggs Institute Critical Appraisal Checklist. We reviewed 1924 studies and analysed data from 20 peer-reviewed studies and three reports documenting quantitative pre-post estimates of RMNCH service disruption because of the COVID-19 pandemic. Eleven studies were of low methodological quality, in addition to seven and five studies of moderate and high methodological qualities respectively. Six countries in the region were represented in the included studies: India (11 studies), Bangladesh (4), Nepal (3), Sri Lanka (1), Bhutan (1) and Myanmar (1). These countries demonstrated a wide reduction in antenatal care services (-1.6% to-69.6%), facility-based deliveries (-2.3% to-52.4%), child immunisation provision (-13.5% to-87.7%), emergency obstetric care (+4.0% to-76.6%), and family planning services (-4.2% to-100%). There have been large COVID-19 pandemic related disruptions for a wide range of RMNCH essential health service indicators in several SEAR countries. Notably, we found a higher level of service disruption than the WHO PULSE survey estimates. If left unaddressed, such disruptions may set back hard-fought gains in RMNCH outcomes across the region. The absence of studies in five SEAR countries is a priority evidence gap that needs addressing to better inform policies for service protection. WHO Sri Lanka Country Office.

Recommendations Related to Visitor and Movement Restrictions in Long-Term Care and Retirement Homes in Ontario during the COVID-19 Pandemic: Perspectives of Residents, Families, and Staff.

In Canada, long-term care and retirement home residents have experienced high rates of COVID-19 infection and death. Early efforts to protect residents included restricting all visitors as well as movement inside homes. These restrictions, however, had significant implications for residents' health and well-being. Engaging with those most affected by such restrictions can help us to better understand their experiences and address their needs. In this qualitative study, 43 residents of long-term care or retirement homes, family members and staff were interviewed and offered recommendations related to infection control, communication, social contact and connection, care needs, and policy and planning. The recommendations were examined using an ethical framework, providing potential relevance in policy development for public health crises. Our results highlight the harms of movement and visiting restrictions and call for effective, equitable, and transparent measures. The design of long-term care and retirement policies requires ongoing, meaningful engagement with those most affected.

Course of COVID-19 infection in patients with congenital adrenal hyperplasia.

Patients with primary adrenal insufficiency due to congenital adrenal hyperplasia (CAH) are at risk for adrenal crisis during infectious illnesses. Increased risk of infection including COVID-19 has been variably reported. To evaluate COVID-19 illness outcomes and stress dose practices in a large cohort of patients with CAH during the first two years of the pandemic and compare observations of COVID-19 infection in patients with CAH to the general USA population. Between March 2020 and November 2022, patients with CAH followed at the National Institutes of Health Clinical Center were queried about COVID-19 infection during their routine visits. Cases of COVID-19 were compared to controls. COVID-19 infection rates and symptoms were compared to general USA population data from the Centers for Disease Control and Prevention. Of 168 patient visits, there were 54 (32%) cases of COVID-19 infection, and 15 (28%) were pediatric. Overall an association was found between acquiring COVID-19 and obesity (p=0.018), and adults acquiring COVID-19 were on lower doses of fludrocortisone (p=0.008). Fewer cases of COVID-19 infection were reported in those receiving hydrocortisone or modified-release hydrocortisone compared to longer acting glucocorticoids (p=0.0018). In our CAH population, the pattern of COVID-19 infection rates and COVID-related symptomatology were similar to those observed in the general USA population. Most patients with the presumed alpha variant reported anosmia and ageusia, while gastrointestinal symptoms were commonly reported during the delta and omicron waves. Stress dosing occurred in 30/54 cases, and 7 received parenteral hydrocortisone. Two hospitalizations occurred; one pediatric and one adult, both with co-morbidities. There were 5 emergency room visits and no reported deaths. Patients with CAH with close follow-up do not appear to be at increased risk of acquiring COVID-19 or to have a more severe course of COVID-19 compared to the general USA population. Obesity may increase risk of acquiring COVID-19 in patients with CAH, and overall infection risk may be lower in those receiving short-acting and circadian glucocorticoid replacement therapy. Established age-appropriate guidelines for stress dosing during infectious illnesses should be used for patients with CAH and COVID-19. COVID-19 specific guidelines are not indicated. Clinical Trial Registration: ClinicalTrials.gov, identifier NCT00250159.

Does the resumption of international tourism heighten COVID-19 transmission?

Reopening countries also carries the risk of another wave of infections in many parts of the world, raising the question of whether we are ready to reopen our countries. This study examines the impact of reopening countries to receive foreign tourists on the spread of COVID-19 in 2022, encompassing 83 countries worldwide. We employ spatial quantile models capable of analyzing the spatial impact of tourism on the spread of the virus at different quantile levels. The research categorizes countries into three groups: low infection rate (10th-30th quantiles), moderate infection rate (40th-60th quantiles), and high infection rate (70th-90th quantiles). This allows for a more comprehensive and detailed comparison of the impacts. Additionally, considering the spatial dimension enables the explanation of both the direct and indirect effects of tourists on the country itself and neighboring countries. The findings reveal that the number of international tourists has a significant effect on the COVID-19 infection rate, particularly in countries with high initial infection rates. However, countries that effectively controlled their infection rates at a low level could maintain a low infection rate even after reopening to foreign tourists. It is also observed that reopening a country's borders negatively impacts the infection rate of neighboring countries. These important findings imply that governments of highly infected countries should shift their focus towards bolstering their economy by promoting domestic tourism and should delay reopening until the number of infections decreases.

Factors Associated with the Incidence of COVID-19 Infectious Disease in Muang Pattani District, Thailand

Objective: This study aimed to investigate the COVID-19 incidence in Muang Pattani district; from April 2021 and September 2022, Specifically, the main objective was to study the varying distribution by demographic, area and period of COVID-19.Material and Methods: COVID-19 data, with 15,807 reported cases was obtained from the Muang Pattani District Health Office. A descriptive analysis was used to describe the characteristics of the COVID-19 cases. A negative binomial model was used to investigate COVID-19 incidence.Results: The overall incidence of COVID-19 was around 1,188.9 cases per 100,000 of the population. Females had a higher incidence rate of COVID-19 infection than males. People aged from 20 to 39 years old had significantly higher incidence rates than the average, with the highest rate being found in the Barohom sub-district. In 2021, the highest rates were in the month of October, followed by July and August; while March was reported as the highest rate in 2022.Conclusion: The findings of this study can be used by the public health organizations and others involved in COVID-19 for direct prevention and control in those high-incidence areas. This study has also proven that its findings can be applied to cases related to the prevention programs of other infectious diseases in Thailand.

Variation in occupational exposure risk for COVID-19 workers’ compensation claims across pandemic waves in Ontario

ObjectivesTo understand rates of work-related COVID-19 (WR-C19) infection by occupational exposures across waves of the COVID-19 pandemic in Ontario, Canada.MethodsWe combined workers’ compensation claims for COVID-19 with data from Statistics...