Hesitant or not: A cross-sectional study of socio-demographics, conspiracy theories, trust in public health information, social capital and vaccine hesitancy among older adults in Ghana.

Vaccination is an effective strategy to reduce the coronavirus disease 2019 (COVID-19) burden, but its effectiveness hinges on timely vaccine uptake. Addressing concerns among vaccine-hesitant individuals is critical to preventing the immunization program from failing. This study analyzes the determinants of vaccine hesitance among older adults (aged 50 years and older) in Ghana. We adopted a cross-sectional survey with a quantitative approach that accessed data from 400 older adults from the Accra and Kumasi metropolitan areas using purposive and snowball sampling techniques. Multivariate logistic regressions were used to estimate the socio-demographic, social capital, conspiracy theories about COVID-19, and public health information factors associated with vaccine hesitance within the sample. The study found that only minority (5%) of respondents had been vaccinated, with 79% indicating willingness to be vaccinated. The study found that females (AOR: 0.734, CI: 0.019-0.036, p = .027) and those who have retired (AOR: 0.861, CI: 0.003-0.028, p = .034) were significantly less likely to engage in COVID-19 vaccine hesitance. Furthermore, the study revealed that participants who trust public health information (AOR: 0.065, CI: 0.022-0.049, p = .031) and have social capital (AOR: 0.886, CI: 0.017-0.032, p = .001) were significantly less likely to present COVID-19 vaccine hesitance. Finally, participants who believe in conspiracy theories about COVID-19 and vaccines (AOR: 3.167, CI: 1.021-2.043, p = .004) were significantly more likely to engage in COVID-19 vaccine hesitance. Efforts to convey vaccination benefits and address issues through evidence-based information are needed to strengthen and preserve the public's trust in vaccines in Ghana.

A deep learning approach for classification of COVID and pneumonia using DenseNet-201.

In the present paper, our model consists of deep learning approach: DenseNet201 for detection of COVID and Pneumonia using the Chest X-ray Images. The model is a framework consisting of the modeling software which assists in Health Insurance Portability and Accountability Act Compliance which protects and secures the Protected Health Information . The need of the proposed framework in medical facilities shall give the feedback to the radiologist for detecting COVID and pneumonia though the transfer learning methods. A Graphical User Interface tool allows the technician to upload the chest X-ray Image. The software then uploads chest X-ray radiograph (CXR) to the developed detection model for the detection. Once the radiographs are processed, the radiologist shall receive the Classification of the disease which further aids them to verify the similar CXR Images and draw the conclusion. Our model consists of the dataset from Kaggle and if we observe the results, we get an accuracy of 99.1%, sensitivity of 98.5%, and specificity of 98.95%. The proposed Bio-Medical Innovation is a user-ready framework which assists the medical providers in providing the patients with the best-suited medication regimen by looking into the previous CXR Images and confirming the results. There is a motivation to design more such applications for Medical Image Analysis in the future to serve the community and improve the patient care.

Exploring How Vaccine Information is Communicated in NSW Public Libraries: A Study on Perceptions and Practice

With COVID-19’s global impact and the increased demand for accurate, accessible vaccine messaging, public libraries–equipped with pre-existing infrastructure and trained information professionals–are uniquely positioned to address this need. However, studies have shown that these expectations rarely align with both past and current practice. This small exploratory study examines library practices alongside librarian perceptions in New South Wales, Australia with the goal of identifying whether they align and what key factors influence the communication of vaccine information. It reports on the findings of a three-strand investigation of library catalogues, websites, and interviews with current NSW public librarians. Ultimately, findings suggested that public libraries had taken few steps towards effectively communicating vaccine information during the early stages of the pandemic. While vaccine collections existed, they were limited in size, outdated, and predominantly print-based. Additionally, cataloguing practices made it difficult to discern anti-vaccine from pro-vaccine resources, while library websites offered minimal vaccine information and lacked accessibility for low literacy or non-English speaking users. These findings largely aligned with the perspectives of the interviewed librarians, who raised concerns regarding the size and accessibility of vaccine resource collections, the importance of expanding digital resources, and improving the communication of vaccine information. © 2022 Kayla Stephanie Wallace.

Enhancing SARS-CoV-2 variants Research with Blockchain Architecture

The emergence of the novel SARS-CoV-2 (Covid-19) virus in 2019 has led to continuous monitoring of the outbreak attempting to generate accurate reports of people's health information to understand the pandemic's impact. It is likely that more variants will emerge since not all countries and populations have been vaccinated. Thus, with SARS-CoV-2's constant mutation, researchers need to collect individuals' health data to study these variants and vaccine efficacy, especially those who show symptoms. However, researchers have difficulties building comprehensive datasets because people are unwilling to release their health information or have no way to report their health statuses (i.e., at-home testing). This problem stems from a lack of complete control over who assesses their health data. Hence, they cannot guarantee the security, privacy, and integrity of the disclosed health information. As the problem of building secure databases persists, researchers find it challenging to accurately report any evolving variants within a short period. This problem has resulted in several new outbreaks of the pandemic. In this work, we propose a blockchain architecture that can guarantee patients' health data integrity, privacy, and security, encouraging individuals to disclose their health information freely. This solution gives patients complete control over who assesses their health information. The framework proposed access management to patients' health data for researchers and contact tracers. This solution classifies patient health information to different sensitivity levels and manages access based on this sensitivity. In case of unauthorized access, the proposed solution detects and prevents such access, thereby ensuring the patient's health information's security, integrity, and privacy. Based on the classification, contact tracers can quickly assess the information needed from patients while the patients will be confident that no sensitive information is disclosed, reducing the burden on contact tracers. © 2022 IEEE.

A near real-time electronic health record-based COVID-19 surveillance system: An experience from a developing country.

CONTEXT: Access to real-time data that provide accurate and timely information about the status and extent of disease spread could assist management of the COVID-19 pandemic and inform decision-making. AIM: To demonstrate our experience with regard to implementation of technical and architectural infrastructure for a near real-time electronic health record-based surveillance system for COVID-19 in Iran. METHOD: This COVID-19 surveillance system was developed from hospital information and electronic health record (EHR) systems available in the study hospitals in conjunction with a set of open-source solutions; and designed to integrate data from multiple resources to provide near real-time access to COVID-19 patients' data, as well as a pool of health data for analytical and decision-making purposes. OUTCOMES: Using this surveillance system, we were able to monitor confirmed and suspected cases of COVID-19 in our population and to automatically notify stakeholders. Based on aggregated data collected, this surveillance system was able to facilitate many activities, such as resource allocation for hospitals, including managing bed allocations, providing and distributing equipment and funding, and setting up isolation centres. CONCLUSION: Electronic health record systems and an integrated data analytics infrastructure are effective tools to enable policymakers to make better decisions, and for epidemiologists to conduct improved analyses regarding COVID-19. IMPLICATIONS: Improved quality of clinical coding for better case finding, improved quality of health information in data sources, data-sharing agreements, and increased EHR coverage in the population can empower EHR-based COVID-19 surveillance systems.

Exploring differences in crisis literacy and efficacy on behavioral responses during infectious disease outbreaks

This study examined the effects of literacy and efficacy on individuals' protective action taking and information seeking during the early phase of infectious disease outbreaks through a nationally representative survey of 1164 U.S. adults. New measures of disaster literacy and crisis efficacy were tested. Overall, results revealed that crisis efficacy and organizational efficacy drove protective action taking and information seeking intentions, while health literacy did not. Disaster literacy negatively predicted both protective action advice seeking and information seeking. The findings highlight the importance of strengthening public efficacy and improving relationships between health authorities and the public, which is greatly influenced by the public's confidence in the health authority's management of the crisis.

COVID-19 vaccine website accessibility dashboard.

BACKGROUND: The COVID-19 pandemic has exacerbated historical inequities for people with disabilities including barriers in accessing online information and healthcare appointment websites. These barriers were brought to the foreground during the vaccine rollout and registration process. OBJECTIVE: This cross-sectional study aimed to examine accessibility of U.S. state and territory COVID-19 information and registration centralized websites. METHODS: The Johns Hopkins Disability Health Research Center created a COVID-19 Vaccine Dashboard compiling COVID-19 information and vaccine registration web pages from 56 states and territories in the United States (U.S.) reviewed between March 30 through April 5, 2021 and analyzed accessibility using WAVE Web Accessibility Evaluation Tool (WAVE). WAVE identifies website accessibility barriers, including insufficient contrast, alternative text, unlabeled buttons, total number of errors, and error density. Web pages were ranked and grouped into three groups by number of errors, creating comparisons between states on accessibility barriers for people with disabilities. RESULTS: All 56 U.S states and territories had COVID-19 information web pages and 29 states had centralized state vaccine registration web pages. Total errors, error density, and alert data were utilized to generate accessibility scores for each web page, the median score was 259 (range = 14 to 536 and IQR = 237) for information pages, and 146 (range = 10 to 281 and IQR = 105) for registration pages. CONCLUSIONS: These results highlight barriers people with disabilities may encounter when accessing information and registering for the COVID-19 vaccine, which underscore inequities in the pandemic response for the disability community and elevate the need to prioritize accessibility of public health information.

Information-seeking patterns during the COVID-19 pandemic across the United States: Longitudinal analysis of Google trends data

Background: The COVID-19 pandemic has impacted people's lives at unprecedented speed and scale, including how they eat and work, what they are concerned about, how much they move, and how much they can earn. Traditional surveys in the area of public health can be expensive and time-consuming, and they can rapidly become outdated. The analysis of big data sets (such as electronic patient records and surveillance systems) is very complex. Google Trends is an alternative approach that has been used in the past to analyze health behaviors;however, most existing studies on COVID-19 using these data examine a single issue or a limited geographic area. This paper explores Google Trends as a proxy for what people are thinking, needing, and planning in real time across the United States. Objective: We aimed to use Google Trends to provide both insights into and potential indicators of important changes in information-seeking patterns during pandemics such as COVID-19. We asked four questions: (1) How has information seeking changed over time? (2) How does information seeking vary between regions and states? (3) Do states have particular and distinct patterns in information seeking? (4) Do search data correlate with-or precede-real-life events? Methods: We analyzed searches on 38 terms related to COVID-19, falling into six themes: social and travel;care seeking;government programs;health programs;news and influence;and outlook and concerns. We generated data sets at the national level (covering January 1, 2016, to April 15, 2020) and state level (covering January 1 to April 15, 2020). Methods used include trend analysis of US search data;geographic analyses of the differences in search popularity across US states from March 1 to April 15, 2020;and principal component analysis to extract search patterns across states. Results: The data showed high demand for information, corresponding with increasing searches for coronavirus linked to news sources regardless of the ideological leaning of the news source. Changes in information seeking often occurred well in advance of action by the federal government. The popularity of searches for unemployment claims predicted the actual spike in weekly claims. The increase in searches for information on COVID-19 care was paralleled by a decrease in searches related to other health behaviors, such as urgent care, doctor's appointments, health insurance, Medicare, and Medicaid. Finally, concerns varied across the country;some search terms were more popular in some regions than in others. Conclusions: COVID-19 is unlikely to be the last pandemic faced by the United States. Our research holds important lessons for both state and federal governments in a fast-evolving situation that requires a finger on the pulse of public sentiment. We suggest strategic shifts for policy makers to improve the precision and effectiveness of non-pharmaceutical interventions and recommend the development of a real-time dashboard as a decision-making tool. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

How did individuals on Instagram discuss COVID-19 in the month following official pandemic status? A examination of user content.

OBJECTIVES: Instagram is a popular social media site used by high numbers of young people. This study was designed to investigate COVID-19 content on Instagram during the month following official pandemic status from the World Health Organization (WHO). METHODS: A total of 200 posts were collected and analyzed over a four-week period between mid-February and mid-March 2020. RESULTS: The vast majority of posts did not address recommended prevention measures. Further, only approximately one-third of the posts referenced a reputable source. Finally, the nature of posts changed over time was impacted by type of poster and reflected a tone of anxiety. CONCLUSIONS: The findings underscore the urgent need for public health officials to be aware of and address social media content on novel health threats. Furthermore, it is imperative that communicating risk on social media, such as Instagram be geared to young people. Failure to do so may hinder prevention, mitigation, and suppression strategies.