scholarly journals Ethics and informatics in the age of COVID-19: challenges and recommendations for public health organization and public policy

2020 ◽  
Author(s):  
Vignesh Subbian ◽  
Anthony Solomonides ◽  
Melissa Clarkson ◽  
Vasiliki Nataly Rahimzadeh ◽  
Carolyn Petersen ◽  
...  
Keyword(s):  
Public Health ◽  
Information Systems ◽  
Ethical Issues ◽  
Care Delivery ◽  
The United States ◽  
Contact Tracing ◽  
Public Health Decision ◽  
Public Health Organization ◽  
Public Health Reporting ◽  
Health Organization

Abstract The COVID-19 pandemic response in the United States has exposed significant gaps in information systems and processes that prevent timely clinical and public health decision-making. Specifically, the use of informatics to mitigate the spread of SARS-CoV-2, support COVID-19 care delivery, and accelerate knowledge discovery bring to the forefront issues of privacy, surveillance, limits of state powers, and interoperability between public health and clinical information systems. Using a consensus-building process, we critically analyze informatics-related ethical issues in light of the pandemic across 3 themes: (1) public health reporting and data sharing, (2) contact tracing and tracking, and (3) clinical scoring tools for critical care. We provide context and rationale for ethical considerations and recommendations that are actionable during the pandemic and conclude with recommendations calling for longer-term, broader change (beyond the pandemic) for public health organization and policy reform.

Persons with Disabilities and Public Health Ethics

2019 ◽  
pp. 218-231
Author(s):  
Monika Mitra ◽  
Linda Long-Bellil ◽  
Robyn Powell
Keyword(s):  
Public Health ◽  
Health Policy ◽  
Public Health Policy ◽  
Ethical Issues ◽  
The United States ◽  
Policy And Practice ◽  
Persons With Disabilities ◽  
Public Health Decision ◽  
Health Decision ◽  
Health Policy And Practice

This chapter draws on medical, social, and legal perspectives to identify and highlight ethical issues pertaining to the treatment, representation, and inclusion of persons with disabilities in public health policy and practice. A brief history of disability in the United States is provided as a context for examining the key ethical issues related to public health policy and practice. Conceptual frameworks and approaches to disability are then described and applied. The chapter then discusses the imperativeness of expanding access to public health programs by persons with disabilities, the need to address implicit and structural biases, and the importance of including persons with disabilities in public health decision-making.

scholarly journals Can auxiliary indicators improve COVID-19 forecasting and hotspot prediction?

2021 ◽  
Vol 118 (51) ◽  
pp. e2111453118 ◽  
Author(s):  
Daniel J. McDonald ◽  
Jacob Bien ◽  
Alden Green ◽  
Addison J. Hu ◽  
Nat DeFries ◽  
...  
Keyword(s):  
Public Health ◽  
Predictive Accuracy ◽  
The United States ◽  
Ar Model ◽  
Search Activity ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Public Health Reporting ◽  
Health Decision ◽  
Google Search

Short-term forecasts of traditional streams from public health reporting (such as cases, hospitalizations, and deaths) are a key input to public health decision-making during a pandemic. Since early 2020, our research group has worked with data partners to collect, curate, and make publicly available numerous real-time COVID-19 indicators, providing multiple views of pandemic activity in the United States. This paper studies the utility of five such indicators—derived from deidentified medical insurance claims, self-reported symptoms from online surveys, and COVID-related Google search activity—from a forecasting perspective. For each indicator, we ask whether its inclusion in an autoregressive (AR) model leads to improved predictive accuracy relative to the same model excluding it. Such an AR model, without external features, is already competitive with many top COVID-19 forecasting models in use today. Our analysis reveals that 1) inclusion of each of these five indicators improves on the overall predictive accuracy of the AR model; 2) predictive gains are in general most pronounced during times in which COVID cases are trending in “flat” or “down” directions; and 3) one indicator, based on Google searches, seems to be particularly helpful during “up” trends.

scholarly journals Public health response to two incidents of confirmed MERS-CoV cases travelling on flights through London Heathrow Airport in 2014 – lessons learnt

2015 ◽  
Vol 20 (18) ◽  
Author(s):  
F Parry-Ford ◽  
N Boddington ◽  
R Pebody ◽  
N Phin ◽  
Collective on behalf of the Incident Management Team
Keyword(s):  
Public Health ◽  
International Health ◽  
The United States ◽  
World Health ◽  
Contact Tracing ◽  
Public Health Response ◽  
The Public ◽  
Health Response ◽  
Health Organization

In May 2014, Public Health England was alerted to two separate laboratory-confirmed cases of Middle East respiratory syndrome coronavirus (MERS-CoV) infection who transited through London Heathrow Airport while symptomatic on flights from Saudi Arabia to the United States of America. We present the rationale for the public health response to both incidents, and report results of contact tracing. Following a risk assessment, passengers seated two seats around the cases were prioritised for contact tracing and a proactive media approach was used to alert all passengers on the planes of their possible exposure in both incidents. In total, 64 United Kingdom (UK) residents were successfully contacted, 14 of whom were sat in the priority area two seats all around the case(s). Five passengers reported respiratory symptoms within 14 days of the flight, but all tested were negative for MERS-CoV. Details of non-UK residents were passed on to relevant World Health Organization International Health Regulation focal points for follow-up, and no further cases were reported back. Different approaches were used to manage contact tracing for each flight due to variations in the quality and timeliness of the passenger contact information provided by the airlines involved. No evidence of symptomatic onward transmission was found.

(Mis)Information on Digital Platforms: Lessons from Twitter and Sina Weibo in the COVID-19 Pandemic (Preprint)

2021 ◽  
Author(s):  
Sarah Kreps
Keyword(s):  
Public Health ◽  
World Health Organization ◽  
Public Discourse ◽  
The United States ◽  
World Health ◽  
Sina Weibo ◽  
Digital Platforms ◽  
The World ◽  
Health Organization ◽  
Relative Prevalence

BACKGROUND Misinformation about COVID-19 has presented challenges to public health authorities during pandemics. Understanding the prevalence and type of misinformation across contexts offers a way to understand the discourse around COVID-19 while informing potential countermeasures. OBJECTIVE The aim of the study was to study COVID-19 content on two prominent microblogging platform, Twitter, based in the United States, and Sina Weibo, based in China, and compare the content and relative prevalence of misinformation to better understand public discourse of public health issues across social media and cultural contexts. METHODS A total of 3,579,575 posts were scraped from both Weibo and Twitter, focusing on content from January 30th, 2020, when the World Health Organization (WHO) declared COVID-19 a “Public Health Emergency of International Concern” and February 6th, 2020. A 1% random sample of tweets that contained both the English keywords “coronavirus” and “covid-19” and the equivalent Chinese characters was extracted and analyzed based on changes in the frequencies of keywords and hashtags. Misinformation on each platform was compared by manually coding and comparing posts using the World Health Organization fact-check page to adjudicate accuracy of content. RESULTS Both platforms posted about the outbreak and transmission but posts on Sina Weibo were less likely to reference controversial topics such as the World Health Organization and death and more likely to cite themes of resisting, fighting, and cheering against the coronavirus. Misinformation constituted 1.1% of Twitter content and 0.3% of Weibo content. CONCLUSIONS Quantitative and qualitative analysis of content on both platforms points to cross-platform differences in public discourse surrounding the pandemic and informs potential countermeasures for online misinformation.

scholarly journals Can the Health-Care System Meet the Challenge of Pandemic Flu? Planning, Ethical, and Workforce Considerations

2007 ◽  
Vol 122 (5) ◽  
pp. 573-578 ◽  
Author(s):  
Peter J. Levin ◽  
Eric N. Gebbie ◽  
Kristine Qureshi
Keyword(s):  
Public Health ◽  
Health Care ◽  
Ethical Issues ◽  
Care Delivery ◽  
Care Staff ◽  
Health Care Staff ◽  
Accurate Information ◽  
The Public ◽  
Health Care Delivery Systems ◽  
The Impact

The federal pandemic influenza plan predicts that 30% of the population could be infected. The impact of this pandemic would quickly overwhelm the public health and health-care delivery systems in the U.S. and throughout the world. Surge capacity for staffing, availability of drugs and supplies, and alternate means to provide care must be included in detailed plans that are tested and drilled ahead of time. Accurate information on the disease must be made available to health-care staff and the public to reduce fear. Spokespersons must provide clear, consistent messages about the disease, including actions to be taken to contain its spread and treat the afflicted. Home care will be especially important, as hospitals will be quickly overwhelmed. Staff must be prepared ahead of time to assure their ability and willingness to report to work, and public health must plan ahead to adequately confront ethical issues that will arise concerning the availability of treatment resources. The entire community must work together to meet the challenges posed by an epidemic. Identification and resolution of these challenges and issues are essential to achieve adequate public health preparedness.

scholarly journals Guiding Principle of Innovation in a Multipurpose Public Health Organization

2016 ◽  
Vol 3 (1) ◽  
pp. 51-62
Author(s):  
Marcelino José Jorge ◽  
Maria Inês Fernandes Pimentel ◽  
Frederico A. de Carvalho ◽  
Patrícia Santos Cavalheiro Silva
Keyword(s):  
Public Health ◽  
Public Health Organization ◽  
Guiding Principle ◽  
Health Organization

scholarly journals A collaborative multiyear, multimodel assessment of seasonal influenza forecasting in the United States

2019 ◽  
Vol 116 (8) ◽  
pp. 3146-3154 ◽  
Author(s):  
Nicholas G. Reich ◽  
Logan C. Brooks ◽  
Spencer J. Fox ◽  
Sasikiran Kandula ◽  
Craig J. McGowan ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Real Time ◽  
Forecast Accuracy ◽  
The United States ◽  
Public Health Response ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Health Response ◽  
Health Decision

Influenza infects an estimated 9–35 million individuals each year in the United States and is a contributing cause for between 12,000 and 56,000 deaths annually. Seasonal outbreaks of influenza are common in temperate regions of the world, with highest incidence typically occurring in colder and drier months of the year. Real-time forecasts of influenza transmission can inform public health response to outbreaks. We present the results of a multiinstitution collaborative effort to standardize the collection and evaluation of forecasting models for influenza in the United States for the 2010/2011 through 2016/2017 influenza seasons. For these seven seasons, we assembled weekly real-time forecasts of seven targets of public health interest from 22 different models. We compared forecast accuracy of each model relative to a historical baseline seasonal average. Across all regions of the United States, over half of the models showed consistently better performance than the historical baseline when forecasting incidence of influenza-like illness 1 wk, 2 wk, and 3 wk ahead of available data and when forecasting the timing and magnitude of the seasonal peak. In some regions, delays in data reporting were strongly and negatively associated with forecast accuracy. More timely reporting and an improved overall accessibility to novel and traditional data sources are needed to improve forecasting accuracy and its integration with real-time public health decision making.

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