scholarly journals Measuring the Outreach Efforts of Public Health Authorities and the Public Response on Facebook During the COVID-19 Pandemic in Early 2020: Cross-Country Comparison (Preprint)

10.2196/19334 ◽  
2020 ◽  
Author(s):  
Aravind Sesagiri Raamkumar ◽  
Soon Guan Tan ◽  
Hwee Lin Wee
Keyword(s):  
Public Health ◽  
Public Response ◽  
The Public ◽  
Country Comparison ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Cross Country

scholarly journals Measuring the Outreach Efforts of Public Health Authorities and the Public Response on Facebook During the COVID-19 Pandemic in Early 2020: Cross-Country Comparison (Preprint)

2020 ◽  
Author(s):  
Aravind Sesagiri Raamkumar ◽  
Soon Guan Tan ◽  
Hwee Lin Wee
Keyword(s):  
Public Health ◽  
United States ◽  
Social Media ◽  
Communication Strategies ◽  
The United States ◽  
Media Analysis ◽  
Public Response ◽  
The Public ◽  
Health Authorities ◽  
Public Health Authorities

BACKGROUND The coronavirus disease (COVID-19) pandemic presents one of the most challenging global crises at the dawn of a new decade. Public health authorities (PHAs) are increasingly adopting the use of social media such as Facebook to rapidly communicate and disseminate pandemic response measures to the public. Understanding of communication strategies across different PHAs and examining the public response on the social media landscapes can help improve practices for disseminating information to the public. OBJECTIVE This study aims to examine COVID-19-related outreach efforts of PHAs in Singapore, the United States, and England, and the corresponding public response to these outreach efforts on Facebook. METHODS Posts and comments from the Facebook pages of the Ministry of Health (MOH) in Singapore, the Centers for Disease Control and Prevention (CDC) in the United States, and Public Health England (PHE) in England were extracted from January 1, 2019, to March 18, 2020. Posts published before January 1, 2020, were categorized as pre-COVID-19, while the remaining posts were categorized as peri-COVID-19 posts. COVID-19-related posts were identified and classified into themes. Metrics used for measuring outreach and engagement were frequency, mean posts per day (PPD), mean reactions per post, mean shares per post, and mean comments per post. Responses to the COVID-19 posts were measured using frequency, mean sentiment polarity, positive to negative sentiments ratio (PNSR), and positive to negative emotions ratio (PNER). Toxicity in comments were identified and analyzed using frequency, mean likes per toxic comment, and mean replies per toxic comment. Trend analysis was performed to examine how the metrics varied with key events such as when COVID-19 was declared a pandemic. RESULTS The MOH published more COVID-19 posts (n=271; mean PPD 5.0) compared to the CDC (n=94; mean PPD 2.2) and PHE (n=45; mean PPD 1.4). The mean number of comments per COVID-19 post was highest for the CDC (mean CPP 255.3) compared to the MOH (mean CPP 15.6) and PHE (mean CPP 12.5). Six major themes were identified, with posts about prevention and safety measures and situation updates being prevalent across the three PHAs. The themes of the MOH’s posts were diverse, while the CDC and PHE posts focused on a few themes. Overall, response sentiments for the MOH posts (PNSR 0.94) were more favorable compared to response sentiments for the CDC (PNSR 0.57) and PHE (PNSR 0.55) posts. Toxic comments were rare (0.01%) across all PHAs. CONCLUSIONS PHAs’ extent of Facebook use for outreach purposes during the COVID-19 pandemic varied among the three PHAs, highlighting the strategies and approaches that other PHAs can potentially adopt. Our study showed that social media analysis was capable of providing insights about the communication strategies of PHAs during disease outbreaks.

The Public Health Police

2017 ◽  
Author(s):  
Trevor Hoppe
Keyword(s):  
Public Health ◽  
Hiv Positive ◽  
Local Health ◽  
Health Departments ◽  
Adherence To Treatment ◽  
The Public ◽  
Treatment Regimens ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Local Health Authorities

As the HIV epidemic wore on in the 2000s, public health authorities became enamored with the idea of “ending AIDS.” That is, if they could just get HIV-positive people to take their pills and stop infecting other people. Health departments began to track HIV-positive clients more closely, aiming to control their behavior and ensure their adherence to treatment regimens. This chapter explores how local health authorities ensure that HIV-positive clients behave in a manner officials deem responsible—and how they catch and punish those who do not. While the state maintains that the work of local health officials is done solely in the interests of promoting public health, their efforts to control HIV-positive clients reveal that they are also engaged in policing and law enforcement.

scholarly journals Rational trust in resilient health systems

2019 ◽  
Vol 34 (7) ◽  
pp. 553-557 ◽  
Author(s):  
Sonja Kristine Kittelsen ◽  
Vincent Charles Keating
Keyword(s):  
Public Health ◽  
Health System ◽  
Health Systems ◽  
The Public ◽  
Public Health Emergencies ◽  
Health Authorities ◽  
Cast Doubt ◽  
Public Health Authorities ◽  
System Resilience ◽  
Relevant Component

AbstractThe 2014–15 Ebola epidemic in West Africa highlighted the significance of trust between the public and public health authorities in the mitigation of health crises. Since the end of the epidemic, there has been a focus amongst scholars and practitioners on building resilient health systems, which many see as an important precondition for successfully combatting future outbreaks. While trust has been acknowledged as a relevant component of health system resilience, we argue for a more sustained theoretical engagement with underlying models of trust in the literature. This article takes a first step in showing the importance of theoretical engagement by focusing on the appeal to rational models of trust in particular in the health system resilience literature, and how currently unconsidered assumptions in this model cast doubt on the effectiveness of strategies to generate trust, and therein resilience, during acute public health emergencies.

scholarly journals Geographic Information Systems (GIS), an Informative Start for Challenging Process of Etiologic Investigation of Diseases and Public Health Policy Making

2017 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Alireza Mosavi Jarrahi ◽  
M Zare ◽  
A Sadeghi
Keyword(s):  
Public Health ◽  
Policy Making ◽  
Population Characteristics ◽  
Environment Interaction ◽  
Gis Technology ◽  
The Public ◽  
Technological Disasters ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Health And Disease

Background: The public health has been always concerned of the immediate environment of human as causal factors for different diseases and health outcomes. Epidemiology, as one of the fundamental basis of public health, is concerned of how diseases are distributed in terms of geographical, chronological, and human population characteristics and employees the descriptive nature of such spread to draw conclusion on the etiology of health or disease utcome for further policy making on prevention of disease or promotion of health.Methods: In this paper, we present the importance of GIS technology in epidemiology from both descriptive and etiologic standpoints and elaborate how this technology can stand in the forefront of disease and health outcome measures in the coming decades. The paper will address the history of geo-related health and disease issues. The mapping tool as a traditionally strong resource in the public health will be explored. The advances in Information Technology and one of its best utilized offshoot, GIS, in Health and disease will be discussed. How the huge repository of generated or ever generating geo-related data and information is utilized to address etiology of diseases or to help public health authorities in making informed policy making decisions are explored.Results: The utilization of GIS technology in diseases with intermittent host such as malaria, yellow fever, or other parasitic diseases has already been well established. The GIS technology and its utilization in chronic and degenerative diseases such as cancer, diabetes, and aging are under development and new frontiers are discovering. The limitation of GIS technology in addressing host environment interaction in micro-environment (at the molecular biology and tissue pathogenicity level) and gene–environment interaction (at the individual level) will further be discussed.Conclusion: We then distress on the efficient use of GIS both in the etiologic investigation of diseases and health events as well as the utilization of the GIS technology as a administrative tool in the help of public health authorities and policy makers in strategic management of health of a community or emergency management of man-made or technological disasters (e.g., wars) or naturally occurring disasters (e.g., earthquake and floods).

scholarly journals Outbreak of norovirus infection in a nursing home in northern Slovenia, July 2007

2007 ◽  
Vol 12 (41) ◽  
Author(s):  
I Grmek Kosnik ◽  
B Peternelj ◽  
M Pohar ◽  
A Kraigher
Keyword(s):  
Public Health ◽  
Nursing Home ◽  
Gastrointestinal Infection ◽  
The Public ◽  
Health Authorities ◽  
Public Health Authorities

On 27 July 2007, an outbreak of gastrointestinal infection in a nursing home was reported to the public health authorities in Kranj (25 km northwest of Ljubljana).

scholarly journals Acceptance and Attitudes Toward COVID-19 Vaccines: A Cross-Sectional Study from Jordan

2020 ◽  
Author(s):  
Tamam El-Elimat ◽  
Mahmoud M. AbuAlSamen ◽  
Basima A. Almomani ◽  
Nour A. Al-Sawalha ◽  
Feras Q. Alali
Keyword(s):  
Public Health ◽  
Healthcare Providers ◽  
Vaccine Hesitancy ◽  
Sources Of Information ◽  
Cross Sectional ◽  
The Public ◽  
Awareness Campaigns ◽  
Health Authorities ◽  
Public Acceptability ◽  
Public Health Authorities

AbstractBackgroundVaccines are effective interventions that can reduce the high burden of diseases globally. However, public vaccine hesitancy is a pressing problem for public health authorities. With the availability of COVID-19 vaccines, little information is available on the public acceptability and attitudes towards the COVID-19 vaccines in Jordan. This study aimed to investigate the acceptability of COVID-19 vaccines and its predictors in addition to the attitudes towards these vaccines among public in Jordan.MethodsAn online, cross-sectional, and self-administered questionnaire was instrumentalized to survey adult participants from Jordan on the acceptability of COVID-19 vaccines. Logistic regression analysis was used to find the predictors of COVID-19 vaccines’ acceptability.ResultsA total of 3,100 participants completed the survey. The public acceptability of COVID-19 vaccines was fairly low (37.4%) in Jordan. Males (OR=2.488, 95CI%=1.834–3.375, p<.001) and those who took the seasonal influenza vaccine (OR=2.036, 95CI%=1.306–3.174, p=.002) were more likely to accept Covid-19 vaccines. Similarly, participants who believed that vaccines are generally safe (OR=9.258, 95CI%=6.020–14.237, p<.001) and those who were willing to pay for vaccines (OR=19.223, 95CI%=13.665–27.042, p<.001), once available, were more likely to accept the COVID-19 vaccines. However, those above 35 years old (OR=0.376, 95CI%=0.233-0.607, p<.001) and employed participants (OR=0.542, 95CI%=0.405-0.725, p<.001) were less likely to accept the COVID-19 vaccines. Moreover, participants who believed that there was a conspiracy behind COVID-19 (OR=0.502, 95CI%=0.356- 0.709, p<.001) and those who do not trust any source of information on COVID-19 vaccines (OR=0.271, 95CI%=0.183 – 0.400, p<.001), were less likely to have acceptance towards them. The most trusted sources of information on COVID-19 vaccines were healthcare providers.ConclusionSystematic interventions are required by public health authorities to reduce the levels of vaccines’ hesitancy and improve their acceptance. We believe these results and specifically the low rate of acceptability is alarming to Jordanian health authorities and should stir further studies on the root causes and the need of awareness campaigns. These interventions should take the form of reviving the trust in national health authorities and structured awareness campaigns that offer transparent information about the safety and efficacy of the vaccines and the technology that was utilized in their production.

scholarly journals Online Information on Electronic Cigarettes: Comparative Study of Relevant Websites From Baidu and Google Search Engines

10.2196/14725 ◽  
2020 ◽  
Vol 22 (1) ◽  
pp. e14725
Author(s):  
Ting Chen ◽  
Sarah Gentry ◽  
Dechao Qiu ◽  
Yan Deng ◽  
Caitlin Notley ◽  
...  
Keyword(s):  
Public Health ◽  
Search Engines ◽  
Electronic Cigarettes ◽  
Online Information ◽  
Web Based ◽  
The Public ◽  
Health Authorities ◽  
Cigarette Advertising ◽  
Public Health Authorities ◽  
Google Search

Background Online information on electronic cigarettes (e-cigarettes) may influence people’s perception and use of e-cigarettes. Websites with information on e-cigarettes in the Chinese language have not been systematically assessed. Objective The aim of this study was to assess and compare the types and credibility of Web-based information on e-cigarettes identified from Google (in English) and Baidu (in Chinese) search engines. Methods We used the keywords vaping or e-cigarettes to conduct a search on Google and the equivalent Chinese characters for Baidu. The first 50 unique and relevant websites from each of the two search engines were included in this analysis. The main characteristics of the websites, credibility of the websites, and claims made on the included websites were systematically assessed and compared. Results Compared with websites on Google, more websites on Baidu were owned by manufacturers or retailers (15/50, 30% vs 33/50, 66%; P<.001). None of the Baidu websites, compared to 24% (12/50) of Google websites, were provided by public or health professional institutions. The Baidu websites were more likely to contain e-cigarette advertising (P<.001) and less likely to provide information on health education (P<.001). The overall credibility of the included Baidu websites was lower than that of the Google websites (P<.001). An age restriction warning was shown on all advertising websites from Google (15/15) but only on 10 of the 33 (30%) advertising websites from Baidu (P<.001). Conflicting or unclear health and social claims were common on the included websites. Conclusions Although conflicting or unclear claims on e-cigarettes were common on websites from both Baidu and Google search engines, there was a lack of online information from public health authorities in China. Unbiased information and evidence-based recommendations on e-cigarettes should be provided by public health authorities to help the public make informed decisions regarding the use of e-cigarettes.

scholarly journals Acceptance and attitudes toward COVID-19 vaccines: A cross-sectional study from Jordan

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250555
Author(s):  
Tamam El-Elimat ◽  
Mahmoud M. AbuAlSamen ◽  
Basima A. Almomani ◽  
Nour A. Al-Sawalha ◽  
Feras Q. Alali
Keyword(s):  
Public Health ◽  
Healthcare Providers ◽  
Vaccine Hesitancy ◽  
Sources Of Information ◽  
Cross Sectional ◽  
The Public ◽  
Awareness Campaigns ◽  
Health Authorities ◽  
Public Acceptability ◽  
Public Health Authorities

Vaccines are effective interventions that can reduce the high burden of diseases globally. However, public vaccine hesitancy is a pressing problem for public health authorities. With the availability of COVID-19 vaccines, little information is available on the public acceptability and attitudes towards the COVID-19 vaccines in Jordan. This study aimed to investigate the acceptability of COVID-19 vaccines and its predictors in addition to the attitudes towards these vaccines among public in Jordan. An online, cross-sectional, and self-administered questionnaire was instrumentalized to survey adult participants from Jordan on the acceptability of COVID-19 vaccines. Logistic regression analysis was used to find the predictors of COVID-19 vaccines’ acceptability. A total of 3,100 participants completed the survey. The public acceptability of COVID-19 vaccines was fairly low (37.4%) in Jordan. Males (OR = 2.488, 95CI% = 1.834–3.375, p < .001) and those who took the seasonal influenza vaccine (OR = 2.036, 95CI% = 1.306–3.174, p = .002) were more likely to accept COVID-19 vaccines. Similarly, participants who believed that vaccines are generally safe (OR = 9.258, 95CI% = 6.020–14.237, p < .001) and those who were willing to pay for vaccines (OR = 19.223, 95CI% = 13.665–27.042, p < .001), once available, were more likely to accept the COVID-19 vaccines. However, those above 35 years old (OR = 0.376, 95CI% = 0.233–0.607, p < .001) and employed participants (OR = 0.542, 95CI% = 0.405–0.725, p < .001) were less likely to accept the COVID-19 vaccines. Moreover, participants who believed that there was a conspiracy behind COVID-19 (OR = 0.502, 95CI% = 0.356–0.709, p < .001) and those who do not trust any source of information on COVID-19 vaccines (OR = 0.271, 95CI% = 0.183–0.400, p < .001), were less likely to have acceptance towards them. The most trusted sources of information on COVID-19 vaccines were healthcare providers. Systematic interventions are required by public health authorities to reduce the levels of vaccines’ hesitancy and improve their acceptance. We believe these results and specifically the low rate of acceptability is alarming to Jordanian health authorities and should stir further studies on the root causes and the need of awareness campaigns. These interventions should take the form of reviving the trust in national health authorities and structured awareness campaigns that offer transparent information about the safety and efficacy of the vaccines and the technology that was utilized in their production.

scholarly journals Use of Health Belief Model–Based Deep Learning Classifiers for COVID-19 Social Media Content to Examine Public Perceptions of Physical Distancing: Model Development and Case Study (Preprint)

2020 ◽  
Author(s):  
Aravind Sesagiri Raamkumar ◽  
Soon Guan Tan ◽  
Hwee Lin Wee
Keyword(s):  
Public Health ◽  
Social Media ◽  
Public Perceptions ◽  
Perceived Barriers ◽  
Classification Models ◽  
Perceived Severity ◽  
The Public ◽  
Health Authorities ◽  
Public Health Authorities

BACKGROUND Public health authorities have been recommending interventions such as physical distancing and face masks, to curtail the transmission of coronavirus disease (COVID-19) within the community. Public perceptions toward such interventions should be identified to enable public health authorities to effectively address valid concerns. The Health Belief Model (HBM) has been used to characterize user-generated content from social media during previous outbreaks, with the aim of understanding the health behaviors of the public. OBJECTIVE This study is aimed at developing and evaluating deep learning–based text classification models for classifying social media content posted during the COVID-19 outbreak, using the four key constructs of the HBM. We will specifically focus on content related to the physical distancing interventions put forth by public health authorities. We intend to test the model with a real-world case study. METHODS The data set for this study was prepared by analyzing Facebook comments that were posted by the public in response to the COVID-19–related posts of three public health authorities: the Ministry of Health of Singapore (MOH), the Centers for Disease Control and Prevention, and Public Health England. The comments made in the context of physical distancing were manually classified with a Yes/No flag for each of the four HBM constructs: perceived severity, perceived susceptibility, perceived barriers, and perceived benefits. Using a curated data set of 16,752 comments, gated recurrent unit–based recurrent neural network models were trained and validated for text classification. Accuracy and binary cross-entropy loss were used to evaluate the model. Specificity, sensitivity, and balanced accuracy were used to evaluate the classification results in the MOH case study. RESULTS The HBM text classification models achieved mean accuracy rates of 0.92, 0.95, 0.91, and 0.94 for the constructs of perceived susceptibility, perceived severity, perceived benefits, and perceived barriers, respectively. In the case study with MOH Facebook comments, specificity was above 96% for all HBM constructs. Sensitivity was 94.3% and 90.9% for perceived severity and perceived benefits, respectively. In addition, sensitivity was 79.6% and 81.5% for perceived susceptibility and perceived barriers, respectively. The classification models were able to accurately predict trends in the prevalence of the constructs for the time period examined in the case study. CONCLUSIONS The deep learning–based text classifiers developed in this study help to determine public perceptions toward physical distancing, using the four key constructs of HBM. Health officials can make use of the classification model to characterize the health behaviors of the public through the lens of social media. In future studies, we intend to extend the model to study public perceptions of other important interventions by public health authorities.

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