Interdisciplinary Perspectives on Health Literacy Research Around the World: More Important Than Ever in a Time of COVID-19

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Abstract

As we write our editorial for a health literacy special issue in the midst of the international COVID-19 crisis, we take this opportunity to highlight the importance of individual, community, and population health literacy. We are not only in a “pandemic” but also an “infodemic”. Health literacy is more important than ever in the face of these global health threats, which have impacted outcomes across the levels of the socio-ecological model (SEM), including individual health behaviors, family relationships, organizational behavior, state policy-making, national mortality statistics, and the international economy in the span of weeks. Our special issue sought to pull together interdisciplinary threads guided by two principles. The first was defining health literacy as essential skills and situational resources needed for people to find, understand, evaluate, communicate, and use information and services in a variety of forms across various settings throughout their life course to promote health and wellbeing. The second was the idea that enhancing health literacy in populations and systems is critical to achieving health equity. In this time of public health need across traditional borders, the inter-sectoral and international perspectives of special issue articles are more urgent than ever. A greater understanding, appreciation, and application of health literacy can support policy action on multiple levels to address major public health challenges. Health literacy should be built deliberately as a population-level resource and community asset. We have summarized the set of articles in this special issue across the levels of the SEM, hoping their thoughtful considerations and interesting findings will help to support global health and wellness and inspire future research, policy, and practice in this global public health emergency and beyond.

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An interactive web-based dashboard to track COVID-19 in real time

Ensheng Dong, Hongru Du, Lauren Gardner (2020)

In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.

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A Trial of Lopinavir–Ritonavir in Adults Hospitalized with Severe Covid-19

Bin Cao, Yeming Wang, Danning Wen … (2020)

Abstract Background No therapeutics have yet been proven effective for the treatment of severe illness caused by SARS-CoV-2. Methods We conducted a randomized, controlled, open-label trial involving hospitalized adult patients with confirmed SARS-CoV-2 infection, which causes the respiratory illness Covid-19, and an oxygen saturation (Sao 2) of 94% or less while they were breathing ambient air or a ratio of the partial pressure of oxygen (Pao 2) to the fraction of inspired oxygen (Fio 2) of less than 300 mm Hg. Patients were randomly assigned in a 1:1 ratio to receive either lopinavir–ritonavir (400 mg and 100 mg, respectively) twice a day for 14 days, in addition to standard care, or standard care alone. The primary end point was the time to clinical improvement, defined as the time from randomization to either an improvement of two points on a seven-category ordinal scale or discharge from the hospital, whichever came first. Results A total of 199 patients with laboratory-confirmed SARS-CoV-2 infection underwent randomization; 99 were assigned to the lopinavir–ritonavir group, and 100 to the standard-care group. Treatment with lopinavir–ritonavir was not associated with a difference from standard care in the time to clinical improvement (hazard ratio for clinical improvement, 1.24; 95% confidence interval [CI], 0.90 to 1.72). Mortality at 28 days was similar in the lopinavir–ritonavir group and the standard-care group (19.2% vs. 25.0%; difference, −5.8 percentage points; 95% CI, −17.3 to 5.7). The percentages of patients with detectable viral RNA at various time points were similar. In a modified intention-to-treat analysis, lopinavir–ritonavir led to a median time to clinical improvement that was shorter by 1 day than that observed with standard care (hazard ratio, 1.39; 95% CI, 1.00 to 1.91). Gastrointestinal adverse events were more common in the lopinavir–ritonavir group, but serious adverse events were more common in the standard-care group. Lopinavir–ritonavir treatment was stopped early in 13 patients (13.8%) because of adverse events. Conclusions In hospitalized adult patients with severe Covid-19, no benefit was observed with lopinavir–ritonavir treatment beyond standard care. Future trials in patients with severe illness may help to confirm or exclude the possibility of a treatment benefit. (Funded by Major Projects of National Science and Technology on New Drug Creation and Development and others; Chinese Clinical Trial Register number, ChiCTR2000029308.)

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Viral dynamics in mild and severe cases of COVID-19

Yang Liu, Li-Meng Yan, Lagen Wan … (2020)

Coronavirus disease 2019 (COVID-19) is a new pandemic disease. We previously reported that the viral load of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) peaks within the first week of disease onset.1, 2 Findings from Feb, 2020, indicated that the clinical spectrum of this disease can be very heterogeneous. 3 Here, we report the viral RNA shedding patterns observed in patients with mild and severe COVID-19. 76 patients admitted to the First Affiliated Hospital of Nanchang University (Nanchang, China) from Jan 21 to Feb 4, 2020, were included in the study. All patients were confirmed to have COVID-19 at the time of admission by RT-PCR. The viral loads of their nasopharyngeal swab samples were estimated with the DCt method (Ctsample – Ctref). Patients who had any of the following features at the time of, or after, admission were classified as severe cases: (1) respiratory distress (≥30 breaths per min); (2) oxygen saturation at rest ≤93%; (3) ratio of partial pressure of arterial oxygen to fractional concentration of oxygen inspired air ≤300 mm Hg; or (4) severe disease complications (eg, respiratory failure, requirement of mechanical ventilation, septic shock, or non-respiratory organ failure). 46 (61%) individuals were classified as mild cases and 30 (39%) were classified as severe cases. The basic demographic data and initial clinical symptoms of these patients are shown in the appendix. Parameters did not differ significantly between the groups, except that patients in the severe group were significantly older than those in the mild group, as expected. 4 No patient died from the infection. 23 (77%) of 30 severe cases received intensive care unit (ICU) treatment, whereas none of the mild cases required ICU treatment. We noted that the DCt values of severe cases were significantly lower than those of mild cases at the time of admission (appendix). Nasopharyngeal swabs from both the left and right nasal cavities of the same patient were kept in a sample collection tube containing 3 mL of standard viral transport medium. All samples were collected according to WHO guidelines. 5 The mean viral load of severe cases was around 60 times higher than that of mild cases, suggesting that higher viral loads might be associated with severe clinical outcomes. We further stratified these data according to the day of disease onset at the time of sampling. The DCt values of severe cases remained significantly lower for the first 12 days after onset than those of corresponding mild cases (figure A ). We also studied serial samples from 21 mild and ten severe cases (figure B). Mild cases were found to have an early viral clearance, with 90% of these patients repeatedly testing negative on RT-PCR by day 10 post-onset. By contrast, all severe cases still tested positive at or beyond day 10 post-onset. Overall, our data indicate that, similar to SARS in 2002–03, 6 patients with severe COVID-19 tend to have a high viral load and a long virus-shedding period. This finding suggests that the viral load of SARS-CoV-2 might be a useful marker for assessing disease severity and prognosis. Figure Viral dynamics in patients with mild and severe COVID-19 (A) DCT values (Ctsample-Ctref) from patients with mild and severe COVID-19 at different stages of disease onset. Median, quartile 1, and quartile 3 are shown. (B) DCT values of serial samples from patients with mild and severe COVID-19. COVID-19=coronavirus disease 2019. *p<0·005.

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Author and article information

Journal

Journal ID (nlm-ta): Int J Environ Res Public Health

Journal ID (iso-abbrev): Int J Environ Res Public Health

Journal ID (publisher-id): ijerph

Title: International Journal of Environmental Research and Public Health

Publisher: MDPI

ISSN (Print): 1661-7827

ISSN (Electronic): 1660-4601

Publication date (Electronic): 26 April 2020

Publication date (Print): May 2020

Volume: 17

Issue: 9

Electronic Location Identifier: 3010

Affiliations

[1 ]Office of Public Health Studies, University of Hawai’i at Mānoa, Honolulu, HI 96822, USA

[2 ]School of Interdisciplinary Health Programs, Western Michigan University, Kalamazoo, MI 49008, USA

[3 ]Interdisciplinary Center for Health Literacy Research, Bielefeld University, 33615 Bielefeld, Germany

Author notes

[* ]Correspondence: tsentell@ 123456hawaii.edu

Author information

Sandra Vamos https://orcid.org/0000-0003-3049-506X

Orkan Okan https://orcid.org/0000-0003-1714-4783

Article

Publisher ID: ijerph-17-03010

DOI: 10.3390/ijerph17093010

PMC ID: 7246523

PubMed ID: 32357457

SO-VID: d13413a7-a299-42b3-a528-133129a62629

License:

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

History

Date received : 01 April 2020

Date accepted : 22 April 2020

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Interdisciplinary Perspectives on Health Literacy Research Around the World: More Important Than Ever in a Time of COVID-19

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Novel Coronavirus Disease COVID-19

Most cited references 86

An interactive web-based dashboard to track COVID-19 in real time

A Trial of Lopinavir–Ritonavir in Adults Hospitalized with Severe Covid-19

Viral dynamics in mild and severe cases of COVID-19

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