Evaluation of Factors Related to the Survival of Hospitalized Patients With COVID-19: Survival Analysis With Frailty Approach.

OBJECTIVE: Considering that coronavirus disease 2019 (COVID-19) is an emerging disease and results in very different outcomes, from complete recovery to death, it is important to determine the factors affecting the survival of patients. Given the lack of knowledge about effective factors and the existence of differences in the outcome of individuals with similar values of the observed covariates, this study aimed to investigate the factors affecting the survival of patients with COVID-19 by the parametric survival model with the frailty approach. METHODS: The data of 139 patients with COVID-19 hospitalized in Imam Reza Hospital in Tabriz were analyzed by the Gompertz survival model with gamma frailty effect. At first, variables with P < 0.1 in univariable analysis were included in the multivariable analysis, and then the stepwise method was used for variable selection. RESULTS: Diabetes mellitus was significantly related to the survival of hospitalized patients (P = 0.021). The rest of the investigated variables were not significant. The frailty effect was significant (P = 0.019). CONCLUSIONS: In the investigated sample of patients with COVID-19, diabetes was an important variable related to patient survival. Also, the significant frailty effect indicates the existence of unobserved heterogeneity that causes individuals with a similar value of the observed covariates to have different survival distributions.

Individuals With SARS-CoV-2 Infection During the First and Second Waves in Catalonia, Spain: Retrospective Observational Study Using Daily Updated Data.

BACKGROUND: A description of individuals with SARS-CoV-2 infection comparing the first and second waves could help adapt health services to manage this highly transmissible infection. OBJECTIVE: We aimed to describe the epidemiology of individuals with suspected SARS-CoV-2 infection, and the characteristics of patients with a positive test comparing the first and second waves in Catalonia, Spain. METHODS: This study had 2 stages. First, we analyzed daily updated data on SARS-CoV-2 infection in individuals from Girona (Catalonia). Second, we compared 2 retrospective cohorts of patients with a positive reverse-transcription polymerase chain reaction or rapid antigen test for SARS-CoV-2. The severity of patients with a positive test was defined by their admission to hospital, admission to intermediate respiratory care, admission to the intensive care unit, or death. The first wave was from March 1, 2020, to June 24, 2020, and the second wave was from June 25, 2020, to December 8, 2020. RESULTS: The numbers of tests and cases were lower in the first wave than in the second wave (26,096 tests and 3140 cases in the first wave versus 140,332 tests and 11,800 cases in the second wave), but the percentage of positive results was higher in the first wave than in the second wave (12.0% versus 8.4%). Among individuals with a positive diagnostic test, 818 needed hospitalization in the first wave and 680 in the second; however, the percentage of hospitalized individuals was higher in the first wave than in the second wave (26.1% versus 5.8%). The group that was not admitted to hospital included older people and those with a higher percentage of comorbidities in the first wave, whereas the characteristics of the groups admitted to hospital were more alike. CONCLUSIONS: Screening systems for SARS-CoV-2 infection were scarce during the first wave, but were more adequate during the second wave, reflecting the usefulness of surveillance systems to detect a high number of asymptomatic infected individuals and their contacts, to help control this pandemic. The characteristics of individuals with SARS-CoV-2 infection in the first and second waves differed substantially; individuals in the first wave were older and had a worse health condition.

Five consecutive epidemiological waves of COVID-19: a population-based cross-sectional study on characteristics, policies, and health outcome.

BACKGROUND: This study was conducted with the intension of providing a more detailed view about the dynamics of COVID-19 pandemic. To this aim, characteristics, implemented public health measures, and health outcome of COVID-19 patients during five consecutive waves of the disease were assessed. METHODS: This study was a population-based cross-sectional analysis of data on adult patients who were diagnosed with COVID-19 during five waves of the disease in Iran. Chi-squared test, One-way ANOVA, and Logistic Regression analysis were applied. A detailed literature review on implemented public health policies was performed by studying published documents and official websites responsible for conveying information about COVID-19. RESULTS: Data on 328,410 adult patients was analyzed. Main findings indicated that the probability of dying with COVID-19 has increased as the pandemic wore on, showing its highest odd during the third wave (odds ratio: 1.34, CI: 1.283-1.395) and has gradually decreased during the next two waves. The same pattern was observed in the proportion of patients requiring ICU admission (P < 0.001). First wave presented mainly with respiratory symptoms, gastrointestinal complaints were added during the second wave, neurological manifestations with peripheral involvement replaced the gastrointestinal complaints during the third wave, and central nervous system manifestations were added during the fourth and fifth waves. A significant difference in mean age of patients was revealed between the five waves (P < 0.001). Moreover, results showed a significant difference between men and women infected with COVID-19, with men having higher rates of the disease at the beginning. However, as the pandemic progressed the proportion of women gradually increased, and ultimately more women were diagnosed with COVID-19 during the fifth wave. Our observations pointed to the probability that complete lockdowns were the key measures that helped to mitigate the virus spread during the first twenty months of the pandemic in the country. CONCLUSION: A changing pattern in demographic characteristics, clinical manifestations, and severity of the disease has been revealed as the pandemic unfolded. Reviewing COVID-19-related public health interventions highlighted the importance of immunization and early implementation of restrictive measures as effective strategies for reducing the acute burden of the disease.

Pandemic COVID-19: An Analysis of Impact on Demographic Bonus Through Population Characteristics Based on 2016-2020 Data (Case Study in Sleman Regency, DIY)

Demographic bonus is a condition when productive force is more than non-productive force. The COVID-19 pandemic in Indonesia has affected many areas, including Sleman Regency, DIY. The purpose of this study was to determine the effect of COVID-19 on demographic bonus and the steps to maximize the demographic bonus to improve the development of Sleman Regency. The method used is population data collection for 2016-2020 from Badan Pusat Statistik of Sleman Regency and quantitative descriptive analysis based on trends in population statistics. This study found that the dependency ratio increased in 2019, followed by a significant decline in 2020. It was because the number of the productive population declined drastically in 2019 (114,276 people) and increased again in 2020 (85,854 people). The number of heads of poor families and the poor increased during the COVID-19 pandemic in 2019-2020 because many formal-informal sectors weren’t running due to government policies. It can be concluded that the demographic bonus of Sleman Regency isn’t affected by COVID-19 from the population structure point of view. Utilization of the demographic bonus can be done by increasing soft skills and hard skills to compete competitively and increasing the number of jobs.

How We Can Reap the Full Benefit of Teleconsultations: Economic Evaluation Combined With a Performance Evaluation Through a Discrete-Event Simulation

Background: In recent years, the rapid development of information and communications technology enabled by innovations in videoconferencing solutions and the emergence of connected medical devices has contributed to expanding the scope of application and expediting the development of telemedicine. Objective: This study evaluates the use of teleconsultations (TCs) for specialist consultations at hospitals in terms of costs, resource consumption, and patient travel time. The key feature of our evaluation framework is the combination of an economic evaluation through a cost analysis and a performance evaluation through a discrete-event simulation (DES) approach. Methods: Three data sets were used to obtain detailed information on the characteristics of patients, characteristics of patients’ residential locations, and usage of telehealth stations. A total of 532 patients who received at least one TC and 18,559 patients who received solely physical consultations (CSs) were included in the initial sample. The TC patients were recruited during a 7-month period (ie, 2020 data) versus 19 months for the CS patients (ie, 2019 and 2020 data). A propensity score matching procedure was applied in the economic evaluation. To identify the best scenarios for reaping the full benefits of TCs, various scenarios depicting different population types and deployment strategies were explored in the DES model. Associated break-even levels were calculated. Results: The results of the cost evaluation reveal a higher cost for the TC group, mainly induced by higher volumes of (tele)consultations per patient and the substantial initial investment required for TC equipment. On average, the total cost per patient over 298 days of follow-up was €356.37 (US $392) per TC patient and €305.18 (US $336) per CS patient. However, the incremental cost of TCs was not statistically significant: €356.37 – €305.18 = €51.19 or US $392 – US $336 = US $56 (95% CI –35.99 to 114.25;P=.18). Sensitivity analysis suggested heterogeneous economic profitability levels within subpopulations and based on the intensity of use of TC solutions. In fact, the DES model results show that TCs could be a cost-saving strategy in some cases, depending on population characteristics, the amortization speed of telehealth equipment, and the locations of telehealth stations. Conclusions: The use of TCs has the potential to lead to a major organizational change in the health care system in the near future. Nevertheless, TC performance is strongly related to the context and deployment strategy involved.

The Effect of the COVID-19 Pandemic on Patient Selection, Surgical Procedures, and Postoperative Complications in a Specialized Dental Implant Clinic.

During the coronavirus disease 2019 (COVID-19) pandemic, aerosol-generating procedures, including dental implant treatments, are considered high-risk. With dental implant treatment mostly an elective procedure, we aimed to assess whether the pandemic influenced patient selection, surgical procedures, and postoperative complications. We compared dental implant treatments during (March to December 2020) and before (December 2018 to February 2020) the COVID-19 pandemic based on patient and implant parameters, as well as postoperative complications. For analysis, we used the Chi-squared test with the Holm-Sidak correction for multiple comparisons. The number of implants placed during the COVID-19 pandemic (696 implants in 406 patients, 70 implants per month) was comparable to pre-pandemic levels (1204 implants in 616 patients, 80 implants per month). Regarding patient parameters, there were no significant differences in respiratory (p = 0.69) and cardiovascular conditions (p = 0.06), diabetes (p = 0.69), and smoking (p = 0.68). Regarding implant parameters, there was a significant difference in the distribution of augmentative procedures (no augmentation, guided bone regeneration, and sinus floor elevation, p = 0.01), but no significant differences in the types of edentulous spaces (p = 0.19) and the timing of implant placement (p = 0.52). Regarding complications, there were significantly fewer minor complications (p < 0.001) and early (i.e., before loading) implant failures (p = 0.02) compared with pre-pandemic levels. Our results suggest that the COVID-19 pandemic had no effect on patient selection and only a slight effect on the surgical procedures. However, postoperative complications, including early failures, were significantly less prevalent during the pandemic.

Characteristics, Comorbidities, and Data Gaps for Coronavirus Disease Deaths, Tennessee, USA.

As of March 2021, coronavirus disease (COVID-19) had led to >500,000 deaths in the United States, and the state of Tennessee had the fifth highest number of cases per capita. We reviewed the Tennessee Department of Health COVID-19 surveillance and chart-abstraction data during March 15‒August 15, 2020. Patients who died from COVID-19 were more likely to be older, male, and Black and to have underlying conditions (hereafter comorbidities) than case-patients who survived. We found 30.4% of surviving case-patients and 20.3% of deceased patients had no comorbidity information recorded. Chart-abstraction captured a higher proportion of deceased case-patients with >1 comorbidity (96.3%) compared with standard surveillance deaths (79.0%). Chart-abstraction detected higher rates of each comorbidity except for diabetes, which had similar rates among standard surveillance and chart-abstraction. Investing in public health data collection infrastructure will be beneficial for the COVID-19 pandemic and future disease outbreaks.

Associations Between Compliance With Non-pharmaceutical Interventions and Social-distancing Policies in Korea During the COVID-19 Pandemic.

OBJECTIVES: This study explored changes in individuals' behavior in response to social distancing (SD) levels and the "no gatherings of more than 5 people" (NGM5) rule in Korea during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: Using survey data from the COVID-19 Behavior Tracker, exploratory factor analysis extracted 3 preventive factors: maintenance of personal hygiene, avoiding going out, and avoiding meeting people. Each factor was used as a dependent variable. The chi-square test was used to compare differences in distributions between categorical variables, while binary logistic regression was performed to identify factors associated with high compliance with measures to prevent transmission. RESULTS: In men, all 3 factors were significantly associated with lower compliance. Younger age groups were associated with lower compliance with maintenance of personal hygiene and avoiding meeting people. Employment status was significantly associated with avoiding going out and avoiding meeting people. Residence in the capital area was significantly associated with higher compliance with personal hygiene and avoiding venturing out. Increasing SD levels were associated with personal hygiene, avoiding going out, and avoiding meeting people. The NGM5 policy was not significantly associated with compliance. CONCLUSIONS: SD levels, gender, age, employment status, and region had explanatory power for compliance with non-pharmaceutical interventions (NPIs). Strengthening social campaigns to inspire voluntary compliance with NPIs, especially focused on men, younger people, full-time workers, and residents of the capital area is recommended. Simultaneously, efforts need to be made to segment SD measures into substrategies with detailed guidance at each level.

Geography of COVID-19 in Denmark.

Aim: To investigate the COVID-19 situation across geographical areas of Denmark over time. Methods: We used COVID-19 data from the Danish State Serum Institute on national, regional and municipality level. Cumulative number of tests, incidence, hospitalizations and deaths per 100,000 inhabitants were analysed for the five Danish regions and for all of Denmark. The cumulative number of tested and incidence of COVID-19 per 100,000 was compared for the two municipalities, Lolland and Gentofte. A sensitivity analysis of the COVID-19 indicators on a regional level was performed using number of tested as the denominator. Results: The Capital Region ranked highest on all analysed COVID-19 indicators with 10,849 tested, 365 cases, 63 hospitalized and 18 deaths per 100,000 by 2 June 2020. The three regions in western Denmark all had low levels, while Region Zealand ranked second highest. Despite general low health status in Lolland municipality, the cumulative incidence of COVID-19 was consistently below that of Gentofte. Sensitivity analysis showed that the Capital Region had the highest number of COVID-19 cases per 100,000 tested, but Region Zealand had a higher number of hospitalized and similar number of deaths per 100,000 tested as the Capital Region over time. Conclusion: COVID-19 had affected eastern Denmark, especially the Capital Region, considerably more than western Denmark. The difference may relate to population density and housing conditions.