The Effect of Chronic Diseases, Age and Gender on Morbidity and Mortality of COVID-19 Infection

Acceptance of COVID-19 Vaccination and Vaccine Hesitancy Among People with Chronic Diseases in Thailand: Role of Attitudes and Vaccine Literacy Towards Future Implications

Introduction

Vaccination is an important strategy to prevent or reduce hospitalizations and mortality caused by COVID-19 infection. However, some people with chronic diseases are hesitant to get the COVID-19 vaccination.

Objective

This study aimed to assess the acceptance of COVID-19 vaccination and associated factors among people with chronic diseases.

Methods

A cross-sectional online survey was conducted between May and August 2021. A sample of 457 Thai adults living with one or more chronic diseases was drawn from a larger online survey.

Results

Participants were 19 to 89 years old. The three most commonly reported chronic diseases were hypertension, diabetes, and obesity. The acceptance rate of COVID-19 vaccination was 89.1%. Forty-six percent of respondents had received the COVID-19 vaccination, and 43.1% intended to get the vaccine. Reasons for vaccine hesitancy/refusal included concerns about adverse side effects from the vaccines including long-term effects that might complicate their disease condition. Multiple logistic regression analyses revealed that having a bachelor's degree or higher [aOR 4.40; 95% CI: 2.12-9.14], being employed [aOR 2.11; 95% CI: 1.03-4.39], and having positive attitudes [aOR 2.36; 95% CI: 1.69-3.29] and negative attitudes [aOR 0.38; 95% CI: 0.27-0.55] predicted acceptance of the COVID-19 vaccination. Vaccine literacy was significantly associated with acceptance of COVID-19 vaccination in binary logistic regression analyses, but it was not retained in the multiple logistic regression model.

Conclusion

Vaccine literacy and attitudes influence acceptance of COVID-19 vaccination in people with chronic diseases.

Clinical outcomes of COVID-19 in patients with chronic diseases

OBJECTIVE

This study was carried out to evaluate the clinical outcomes of patients having chronic diseases (CD) and COVID-19 infection.

METHODS

The study was carried out retrospectively by including 1.516 patients with CDs who applied to two education and research hospitals between June 01, 2021, and August 01, 2021, and were diagnosed with COVID-19. As CDs; cardiovascular diseases, diabetes mellitus (DM), hyperlipidemia, asthma, chronic obstructive pulmonary diseases, rheumatological diseases, malignancy, cerebrovascular disease, and chronic kidney diseases (CKD) were screened and evaluated statistically.

RESULTS

A total of 1.516 patients with a mean age of 58.05±18.51 years were included in the study. It has been observed that 68.9% of COVID-19 patients have at least one CD. Women were more tend to have CDs than men (73.8% vs. 64.8%). Patients with a history of CD were significantly older and had a longer hospital stay than those without. Patients with CDs were 5.49 times more likely to be hospitalized in the intensive care unit (ICU) and their death rate was 2.52 times higher than the other patients. After the regression analysis, while hypertension (HT) (Odds Ratio [OR]: 2.39), DM (OR: 3.64), and any type of cancer (OR: 2.75) were seen as independent risk factors in hospitalizations in the ICU, cardiovascular diseases (OR: 2.27), CKD (OR: 3.69) and psychiatric disorders (OR: 2.18) were seen as independent risk factors associated with mortality.

CONCLUSION

The follow-up of COVID-19 patients with CDs should be done more cautiously than others. It should be kept in mind that patients with HT, DM, and cancer may need intensive care at any time of hospitalization, while those with cerebrovascular disease, CKD, and psychiatric problems may have a higher mortality rate than other patients.

COVID-19 activity risk calculator as a gamified public health intervention tool

The Coronavirus disease 2019 (COVID-19) pandemic, caused by the virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has impacted over 200 countries leading to hospitalizations and deaths of millions of people. Public health interventions, such as risk estimators, can reduce the spread of pandemics and epidemics through influencing behavior, which impacts risk of exposure and infection. Current publicly available COVID-19 risk estimation tools have had variable effectiveness during the pandemic due to their dependency on rapidly evolving factors such as community transmission levels and variants. There has also been confusion surrounding certain personal protective strategies such as risk reduction by mask-wearing and vaccination. In order to create a simple easy-to-use tool for estimating different individual risks associated with carrying out daily-life activity, we developed COVID-19 Activity Risk Calculator (CovARC). CovARC is a gamified public health intervention as users can "play with" how different risks associated with COVID-19 can change depending on several different factors when carrying out routine daily activities. Empowering the public to make informed, data-driven decisions about safely engaging in activities may help to reduce COVID-19 levels in the community. In this study, we demonstrate a streamlined, scalable and accurate COVID-19 risk calculation system. Our study also demonstrates the quantitative impact of vaccination and mask-wearing during periods of high case counts. Validation of this impact could inform and support policy decisions regarding case thresholds for mask mandates, and other public health interventions.

A runtime alterable epidemic model with genetic drift, waning immunity and vaccinations

We present methods for building a Java Runtime-Alterable-Model Platform (RAMP) of complex dynamical systems. We illustrate our methods by building a multivariant SEIR (epidemic) RAMP. Underlying our RAMP is an individual-based model that includes adaptive contact rates, pathogen genetic drift, waning and cross-immunity. Besides allowing parameter values, process descriptions and scriptable runtime drivers to be easily modified during simulations, our RAMP can used within R-Studio and other computational platforms. Process descriptions that can be runtime altered within our SEIR RAMP include pathogen variant-dependent host shedding, environmental persistence, host transmission and within-host pathogen mutation and replication. They also include adaptive social distancing and adaptive application of vaccination rates and variant-valency of vaccines. We present simulation results using parameter values and process descriptions relevant to the current COVID-19 pandemic. Our results suggest that if waning immunity outpaces vaccination rates, then vaccination rollouts may fail to contain the most transmissible variants, particularly if vaccine valencies are not adapted to deal with escape mutations. Our SEIR RAMP is designed for easy use by others. More generally, our RAMP concept facilitates construction of highly flexible complex systems models of all types, which can then be easily shared as stand-alone application programs.

COVID-19 Vaccine Intention among Healthcare Workers in Saudi Arabia: A Cross-Sectional Survey

The COVID-19 pandemic has caused largescale morbidity and mortality and a tremendous burden on the healthcare system. Healthcare workers (HCWs) require adequate protection to avoid onward transmission and minimize burden on the healthcare system. Moreover, HCWs can also influence the general public into accepting the COVID-19 vaccine. Therefore, determining COVID-19 vaccine intention among HCWs is of paramount importance to plan tailor-made public health strategies to maximize vaccine coverage. A structured questionnaire was administered in February and March 2021 among HCWs in Saudi Arabia using convenience sampling, proceeding the launch of the vaccination campaign. HCWs from all administrative regions of Saudi Arabia were included in the study. In total, 674 out of 1124 HCWs responded and completed the survey (response rate 59.9%). About 65 percent of the HCWs intended to get vaccinated. The intention to vaccinate was significantly higher among HCWs 50 years of age or older, Saudi nationals and those who followed the updates about COVID-19 vaccines (p < 0.05). The high percentage (26 percent) of those who were undecided in getting vaccinated is a positive sign. As the vaccination campaign gathers pace, the attitude is expected to change over time. Emphasis should be on planning healthcare strategies to convince the undecided HCWs into accepting the vaccine in order to achieve the coverage required to achieve herd immunity.