The longitudinal impact of the SARS-CoV-2 pandemic on participants from the Boston Puerto Rican Health Study

Objective to investigate the impact of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic on older Hispanic adults. Methods A total of 522 participants (or their family member, if deceased) from the Boston Puerto Rican Health Study were asked whether they had been diagnosed with SARS-CoV-2, across 2 survey phases. In phase 1 (May – Aug 2020, n=497), participants answered survey questions related to SARS-CoV-2 exposure, diagnosis, and transmission and 5 family members reported deaths. In phase 2, participants were again surveyed (January – June 2021;n=420, and 2 family members reported deaths). SARS-CoV-2 diagnosis and/or death apparently from SARS-CoV-2 was self-reported. Results In 2020, 5.2% reported that they had been SARS-CoV-2 positive;by June 2021, a cumulative 11.0% reported having been SARS-CoV-2 positive (including cases and deaths in the first survey). A total of 7 participants (1.3%) reportedly died from SARS-CoV-2. Language acculturation was significantly lower among participants with SARS-CoV-2 (13.7 ± 17.9) vs. without SARS-CoV-2 (20.0 ± 21.4;P = 0.049). Mean length of return to usual health was 28 ± 38 days (range: 0-210 days;median = 15 days). Depressive symptomatology was significantly lower during the pandemic (CES-D score: 13.4 ± 11.6) compared to the same participants pre-pandemic (17.8 ± 11.7;P = 0.001). Compared to the months before the pandemic, 32% (n=135) of participants reported greater communication with friends and family, and 41% (n=172) reported no change. Conclusions Public health models should be personalized to communities, considering their unique structures and cultural beliefs. Social resiliency may be key for future programmatic responses to pandemics to reduce the mental health burden.

Association between adverse experiences during Hurricane María and mental and emotional distress among adults in Puerto Rico.

OBJECTIVES: To evaluate the association between adverse experiences during Hurricane María and mental and emotional distress in Puerto Rico. METHODS: This cross-sectional study used baseline data from adult (30-75 years) participants of the Puerto Rico Observational Study of Psychosocial, Environmental, and Chronic Disease Trends (PROSPECT). Enrolled individuals prior to COVID-19 who completed a 33-item questionnaire on Hurricane María-related experiences (sub-categorized as personal, service, or property losses), depression symptomatology, post-traumatic stress disorder (PTSD), and anxiety were included for analysis (n = 456). RESULTS: Most participants experienced fear for their family's safety, damage to their home and personal items, communication outages, and water shortages. Each additional stressor was significantly associated with higher odds of depression symptoms, PTSD, and anxiety. Personal losses were significantly associated with higher likelihood of all outcomes, while services losses were associated with depression symptoms and anxiety; property loss was not significantly associated with any outcome. CONCLUSIONS: Adverse experiences during a major natural disaster are associated with mental and emotional distress. Strategies to minimize hardships during natural disasters, especially personal and service losses, are essential to preserve mental health. Post-disaster psychological support to individuals is crucial.

Open Source Digital Health Software for Resilient, Accessible and Equitable Healthcare Systems.

OBJECTIVE: To assess the impact of open-source projects on making healthcare systems more resilient, accessible and equitable. METHODS: In response to the International Medical Informatics Association (IMIA) call for working group contributions for the IMIA Yearbook, the Open Source Working Group (OSWG) conducted a rapid review of current open source digital health projects to illustrate how they can contribute to making healthcare systems more resilient, accessible and equitable. We sought case studies from the OSWG membership to illustrate these three concepts and how open source software (OSS) addresses these concepts in the real world. These case studies are discussed against the background of literature identified through the rapid review. RESULTS: To illustrate the concept of resilience, we present case studies from the adoption of District Health Information Software version 2 (DHIS2) for managing the Covid pandemic in Rwanda, and the adoption of the OpenEHR open Health IT standard. To illustrate accessibility, we show how open source design systems for user interface design have been used by governments to ensure accessibility of digital health services for patients and healthy individuals, and by the OpenMRS community to standardise their user interface design. Finally, to illustrate the concept of equity, we describe the OpenWHO framework and two open source digital health projects, GNU Health and openIMIS, that both aim to reduce health inequities through the use of open source digital health software. CONCLUSION: This review has demonstrated that open source software addresses many of the challenges involved in making healthcare more accessible, equitable and resilient in high and low income settings.

Using Open Source, Open Data, and Civic Technology to Address the COVID-19 Pandemic and Infodemic.

OBJECTIVES: The emerging COVID-19 pandemic has caused one of the world's worst health disasters compounded by social confusion with misinformation, the so-called "Infodemic". In this paper, we discuss how open technology approaches - including data sharing, visualization, and tooling - can address the COVID-19 pandemic and infodemic. METHODS: In response to the call for participation in the 2020 International Medical Informatics Association (IMIA) Yearbook theme issue on Medical Informatics and the Pandemic, the IMIA Open Source Working Group surveyed recent works related to the use of Free/Libre/Open Source Software (FLOSS) for this pandemic. RESULTS: FLOSS health care projects including GNU Health, OpenMRS, DHIS2, and others, have responded from the early phase of this pandemic. Data related to COVID-19 have been published from health organizations all over the world. Civic Technology, and the collaborative work of FLOSS and open data groups were considered to support collective intelligence on approaches to managing the pandemic. CONCLUSION: FLOSS and open data have been effectively used to contribute to managing the COVID-19 pandemic, and open approaches to collaboration can improve trust in data.