scholarly journals COVID-19 Pandemic: Questioning Conspiracy Theories, Beliefs or Claims that Have Potential Negative Impact on Public Health Interventions and Proposal for Integrated Communication and Information Dissemination Strategies (ICIDS)

2021 ◽  
Vol 8 (1) ◽  
pp. 1-21
Author(s):  
Aceme Nyika ◽  
Geraldine Taponeswa Nyika ◽  
Jeffrey Tonderai Nyika ◽  
Jeremy Tashinga Nyika ◽  
Trenah Nyika
Keyword(s):  
Public Health ◽  
Information Dissemination ◽  
Viral Infections ◽  
Negative Impact ◽  
Care Delivery ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Conspiracy Theories ◽  
The World ◽  
Integrated Communication

The COVID-19 outbreak that started in Wuhan, China, in December 2019 spread across the world causing a pandemic that infected and killed thousands of people globally. Countries made frantic efforts to put in place measures to curb the spread of the viral infections. The measures included social distancing, regular washing of hands with soap, applying sanitizers to hands and surfaces, use of personal protective equipment, screening, testing, isolation of suspected cases, quarantine of cases, lockdowns, treatment of cases and controlled burial of deceased cases.Almost all affected countries experienced four main hindrances to their efforts to control the COVID-19 pandemic; (i) challenges in implementing preventative measures effectively, (ii) health care delivery systems that could not cope with the pandemic, (iii) limited resources, and (iv) negative socio-economic impact caused by the pandemic. One of the challenges that hindered efforts to prevent the spread of the pandemic or to manage it are various conspiracy theories, beliefs, and or unproven claims, some of which are contradictory, that were circulated across the world.2This article gives an overview of the covid-19 pandemic, some conspiracy theories, beliefs and claims that were circulated as unofficial information, and questions the unofficial information. The article ends with an outline of some potential negative impact of conspiracy theories, beliefs and claims on public health interventions aimed at controlling the pandemic. In order to counter disinformation and misinformation, the article recommends the establishment of well-coordinated Integrated Communication and Information Dissemination Strategies (ICIDS) at global, continental, regional and national levels.

scholarly journals Leveraging Rich Data and Machine Learning to Facilitate Policy Making on Public Health Interventions in Fighting to Contain the COVID-19 Pandemic

2020 ◽  
Author(s):  
Robin Qiu
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Public Health Intervention ◽  
Research Direction ◽  
Health Interventions ◽  
Mitigation Measures ◽  
Public Health Interventions ◽  
Short Article ◽  
The World ◽  
Rich Data

<p>This is a short article, focusing on promoting more study on SEIR modeling by leveraging rich data and machine learning. We believe that this is extremely critical as many regions at the country or state/provincial levels have been struggling with their public health intervention policies on fighting the COVID-19 pandemic. Some recent published papers on mitigation measures show promising SEIR modeling results, which could shred the light for other policymakers at different community levels. We present our perspective on this research direction. Hopefully, we can stimulate more studies and help the world win this “war” against the invisible enemy “coronavirus” sooner rather than later. </p>

COVID-19 Misinformation and Polarization on Twitter

2021 ◽  
Vol 13 (1) ◽  
pp. 19-36
Author(s):  
Rebecca Godard ◽  
Susan Holtzman
Keyword(s):  
Public Health ◽  
Social Network ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Conspiracy Theories ◽  
Connected Network ◽  
Network Analyses ◽  
The Stability ◽  
Social Network Analyses ◽  
Over Time

This study investigated polarization on Twitter related to the COVID-19 pandemic by examining tweets containing #Plandemic (suggests the pandemic is a hoax) or #StayHome (encourages compliance with health recommendations). Over 35,000 tweets from over 25,000 users were collected in April 2020 and examined using sentiment and social network analyses. Compared to #StayHome tweets, #Plandemic tweets came from a more tightly connected network, were higher in negative emotional content, and could be sub-divided into specific categories of misinformation and conspiracy theories. To evaluate the stability of users' COVID-related perspectives, the prevalence of pro- and anti-mask sentiment was measured in same users' tweets approximately four months later. Results revealed substantial stability over time, with 40% of #Plandemic users tweeting anti-mask hashtags compared to just 2% of #StayHome users. Findings demonstrate COVID-related polarization on Twitter and have implications for public health interventions to quell the propagation of misinformation.

scholarly journals Leveraging Rich Data and Machine Learning to Facilitate Policy Making on Public Health Interventions in Fighting to Contain the COVID-19 Pandemic

2020 ◽  
Author(s):  
Robin Qiu
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Public Health Intervention ◽  
Research Direction ◽  
Health Interventions ◽  
Mitigation Measures ◽  
Public Health Interventions ◽  
Short Article ◽  
The World ◽  
Rich Data

<p>This is a short article, focusing on promoting more study on SEIR modeling by leveraging rich data and machine learning. We believe that this is extremely critical as many regions at the country or state/provincial levels have been struggling with their public health intervention policies on fighting the COVID-19 pandemic. Some recent published papers on mitigation measures show promising SEIR modeling results, which could shred the light for other policymakers at different community levels. We present our perspective on this research direction. Hopefully, we can stimulate more studies and help the world win this “war” against the invisible enemy “coronavirus” sooner rather than later. </p>

The role of the World Bank and WHO Model Disability Survey in public health

2017 ◽  
Vol 25 (4) ◽  
pp. 262-264
Author(s):  
Carla Sabariego
Keyword(s):  
Public Health ◽  
World Bank ◽  
Population Level ◽  
Health Interventions ◽  
World Health ◽  
Public Health Interventions ◽  
The World Bank ◽  
The World ◽  
Health Organization

Abstract: The Model Disability Survey (MDS) is the tool recommended by the world health organization (WHO) to collect data on disability at the population level. It consciously promotes a narrative of inclusion, as disability is understood as a continuum, ranging from low to high levels. Public health currently faces the challenge of responding to demographic and health shifts leading to an increase in disability in the population. The MDS provides the information needed to meet these challenges and develop targeted public health interventions.

Strategies and structures for public health interventions

2021 ◽  
pp. 659-684
Author(s):  
Sian Griffiths ◽  
Kevin A. Fenton
Keyword(s):  
Public Health ◽  
Public Health Intervention ◽  
Monitoring And Evaluation ◽  
Health Interventions ◽  
Public Health Workforce ◽  
Public Health Interventions ◽  
The Public ◽  
The World ◽  
Different Levels ◽  
Different Parts

This chapter describes strategies for public health intervention and structures that support them. It uses examples of strategies in different parts of the world and at different levels—global, national, local, and individual—to illustrate various strategic approaches. The key elements of strategy are those of vision, mission, values, aims, plans, and their implementation, monitoring, and evaluation. The examples chosen provide descriptions of how these are articulated and also how interventions are made towards their achievement of better public health. The importance of the way health services are structured, the public health workforce, and underpinning research and use of evidence are emphasized.

scholarly journals Precipitous Fall in Common Respiratory Viral Infections During COVID-19

2020 ◽  
Vol 7 (11) ◽  
Author(s):  
Michael F Parry ◽  
Asha K Shah ◽  
Merima Sestovic ◽  
Selma Salter
Keyword(s):  
Public Health ◽  
Hand Hygiene ◽  
Viral Infections ◽  
Winter Season ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Control And Prevention ◽  
Continued Use ◽  
Respiratory Viral Infections ◽  
The Difference

Abstract In the midst of the coronavirus disease 2019 (COVID-19) pandemic, we were surprised to find that all other respiratory viral infections fell precipitously. The difference in respiratory viral infections during the 16-week period of our peak COVID-19 activity in 2020 (Centers for Disease Control and Prevention weeks 14–29) was significantly lower than during the same period in the previous 4 years (a total of 4 infections vs an average of 138 infections; P &lt; .0001). We attribute this to widespread use of public health interventions including wearing face masks, social distancing, hand hygiene, and stay-at-home orders. As these interventions are usually ignored by the community during most influenza seasons, we anticipate that their continued use during the upcoming winter season could substantially blunt the case load of influenza and other respiratory viral infections.

scholarly journals Significant and sustained decrease in non-SARS-CoV-2 respiratory viral infections during COVID-19 public health interventions.

2021 ◽  
Author(s):  
Jeffrey D. Whitman ◽  
Phong Pham ◽  
Caryn Bern ◽  
Elaine M. Dekker ◽  
Barbara L. Haller ◽  
...  
Keyword(s):  
Public Health ◽  
San Francisco ◽  
Viral Infections ◽  
Respiratory Infections ◽  
The United States ◽  
Health Interventions ◽  
Respiratory Pathogen ◽  
Public Health Interventions ◽  
Bay Area ◽  
Respiratory Viral Infections

Public health interventions to decrease the spread of SARS-CoV-2 were largely implemented in the United States during spring 2020. This study evaluates the additional effects of these interventions on non-SARS-CoV-2 respiratory viral infections from a single healthcare system in the San Francisco Bay Area. The results of a respiratory pathogen multiplex polymerase chain reaction panel intended for inpatient admissions were analyzed by month between 2019 and 2020. We found major decreases in the proportion and diversity of non-SARS-CoV-2 respiratory viral illnesses in all months following masking and shelter-in-place ordinances. These findings suggest real-world effectiveness of nonpharmaceutical interventions on droplet-transmitted respiratory infections.

scholarly journals A Noel Intervention Recurrent autoencoder for real time forecasting and non-pharmaceutical intervention selection to curb the spread of Covid-19 in the world

2020 ◽  
Author(s):  
Qiyang Ge ◽  
Zixin Hu ◽  
Shudi Li ◽  
Wei Lin ◽  
Li Jin ◽  
...  
Keyword(s):  
Public Health ◽  
Causal Inference ◽  
Real Time ◽  
Health Planning ◽  
Health Interventions ◽  
List Type ◽  
Public Health Interventions ◽  
Peak Number ◽  
Additional Intervention ◽  
The World

ABSTRACTObjectiveDevelop the AI and casual inference-inspired methods for forecasting and evaluating the effects of public health interventions on curbing the spread of Covid-19.MethodsWe developed recurrent neural network (RNN) for modeling the transmission dynamics of the epidemics and Counterfactual-RNN (CRNN) for evaluating and exploring public health intervention strategies to slow down the spread of Covid-19 worldwide. We applied the developed methods to real-time forecasting the confirmed cases of Covid-19 across the world. The data were collected from January 22 to April 18, 2020 by John Hopkins Coronavirus Resource Center (https://coronavirus.jhu.edu/MAP.HTML).ResultsThe average errors of 1-step to 10-step forecasting were 2.9%. In the absence of a COVID-19 vaccine, we evaluated the potential effects of a number of public health measures. We found that the estimated peak number of new cases and cumulative cases, and the maximum number of cumulative cases worldwide with one week later additional intervention were reduced to 103,872, 2,104,800, and 2,271,648, respectively. The estimated total peak number of new cases and cumulative cases would be the same as the above and the maximum number of cumulative cases would be 3,864,872 in the world with 3 week later additional intervention. Duration time of the Covid-19 spread would be increased from 91 days to 123 days. Our estimation results showed that we were in the eve of stopping the spread of COVID-19 worldwide. However, we observed that transmission would quickly rebound if interventions were relaxed.ConclusionsThe accuracy of the AI-based methods for forecasting the trajectory of Covid-19 was high. The AI and causal inference-inspired methods are a powerful tool for helping public health planning and policymaking. We concluded that the spread of COVID-19 would be stopped very soon.HighlightsAs the Covid-19 pandemic soars around the world, there is urgent need to forecast the number of cases worldwide at its peak, the length of the pandemic before receding and implement public health interventions to significantly stop the spread of Covid-19.Develop artificial intelligence (AI) and causal inference inspired methods for real-time forecasting and evaluation of interventions on the worldwide trajectory of the spread of Covid-19.We estimated the maximum number of cumulative cases under immediate additional intervention to be 2,271,648; under later additional intervention the number increased to 3,864,872 and the case ending time would be May 25, 2020.Without additional intervention, the spread of COVID-19 would be stopped on July 6, 2020.

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