scholarly journals Chronological association of public face mask usage with the progression of coronavirus disease 2019 (COVID-19) pandemic in a medium-sized Texas city

2021 ◽  
Vol 9 (41) ◽  
pp. 20-27
Author(s):  
Tyler Helton ◽  
Andrés Guerrero-Criado ◽  
Xinyi Huang ◽  
Mark Sigler
Keyword(s):  
Public Health ◽  
Policy Change ◽  
Compliance Rate ◽  
Face Mask ◽  
Disease Spread ◽  
Strong Negative Correlation ◽  
Business Policy ◽  
Area Of Interest ◽  
The Individual ◽  
Over Time

The coronavirus disease 2019 (COVID-19) pandemic has brought many public health issues to the forefront. One area of interest is the use of face masks for disease spread reduction. This observational study aims to survey the trend of public mask usage in Amarillo, TX over two months during the COVID-19 pandemic. We hypothesized that public mask usage would decrease during the data collection period due to “COVID Fatigue” in the region studied. For two hours per week, customers entering a local supermarket were counted and recorded as mask-wearing or not mask-wearing. The percentage of customers wearing masks over time was characterized. The regional COVID-19 incidence rate was analyzed alongside this mask usage trend. A decrease in mask utilization was confirmed throughout May and June before policy interventions in July. Mask utilization was highest with a peak of at 35.5% in May before a decrease to a floor of 13.9% in June. A significant increase in mask utilization following a state mask mandate and private policy change was captured. The mandate alone was not enough to cause a 100% compliance rate in the population and the individual store policy change was what preceded the most significant increase. A strong negative correlation between mask usage and active Coronavirus cases in Amarillo was observed. This study revealed a trend of decreasing compliance with mask utilization over time. The findings suggest that the best method in increasing public compliance is a combination of both public health policy and private business policy implementation.

scholarly journals A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China

10.2196/21685 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e21685
Author(s):  
Zonglin He ◽  
Casper J P Zhang ◽  
Jian Huang ◽  
Jingyan Zhai ◽  
Shuang Zhou ◽  
...  
Keyword(s):  
Public Health ◽  
Information And Communication Technologies ◽  
Ethical Issues ◽  
Rapid Development ◽  
Disease Outbreaks ◽  
Face Mask ◽  
Digital Data ◽  
Disease Spread ◽  
Health Measures ◽  
Digital Epidemiology

A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.

scholarly journals A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China (Preprint)

2020 ◽  
Author(s):  
Zonglin He ◽  
Casper J P Zhang ◽  
Jian Huang ◽  
Jingyan Zhai ◽  
Shuang Zhou ◽  
...  
Keyword(s):  
Public Health ◽  
Information And Communication Technologies ◽  
Ethical Issues ◽  
Rapid Development ◽  
Disease Outbreaks ◽  
Face Mask ◽  
Digital Data ◽  
Disease Spread ◽  
Health Measures ◽  
Digital Epidemiology

UNSTRUCTURED A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.

On the Individual

1999 ◽  
Vol 4 (4) ◽  
pp. 205-218 ◽  
Author(s):  
David Magnusson
Keyword(s):  
School Psychologist ◽  
Real Life ◽  
Psychological Research ◽  
Developmental Research ◽  
Future Directions ◽  
The 1950S ◽  
The Individual ◽  
Over Time

A description of two cases from my time as a school psychologist in the middle of the 1950s forms the background to the following question: Has anything important happened since then in psychological research to help us to a better understanding of how and why individuals think, feel, act, and react as they do in real life and how they develop over time? The studies serve as a background for some general propositions about the nature of the phenomena that concerns us in developmental research, for a summary description of the developments in psychological research over the last 40 years as I see them, and for some suggestions about future directions.

Geographical aspects of the diffusion of passive houses

2013 ◽  
Vol 4 (2) ◽  
pp. 151-156 ◽  
Author(s):  
G. Kozma ◽  
E. Molnár ◽  
K. Czimre ◽  
J. Pénzes
Keyword(s):  
Energy Consumption ◽  
Energy Resources ◽  
Substantial Part ◽  
Renewable Energy Resources ◽  
Passive House ◽  
The Earth ◽  
Passive Houses ◽  
The Individual ◽  
Geographical Locations ◽  
Over Time

Abstract In our days, energy issues belong to the most important problems facing the Earth and the solution may be expected partly from decreasing the amount of the energy used and partly from the increased utilisation of renewable energy resources. A substantial part of energy consumption is related to buildings and includes, inter alia, the use for cooling/heating, lighting and cooking purposes. In the view of the above, special attention has been paid to minimising the energy consumption of buildings since the late 1980s. Within the framework of that, the passive house was created, a building in which the thermal comfort can be achieved solely by postheating or postcooling of the fresh air mass without a need for recirculated air. The aim of the paper is to study the changes in the construction of passive houses over time. In addition, the differences between the geographical locations and the observable peculiarities with regard to the individual building types are also presented.

Personality change and environmental concerns

2020 ◽  
Author(s):  
Christopher James Hopwood ◽  
Ted Schwaba ◽  
Wiebke Bleidorn
Keyword(s):  
Personality Traits ◽  
Personality Change ◽  
Environmental Concerns ◽  
Big Five Personality ◽  
German Population ◽  
Individual Level ◽  
Sustainable Behavior ◽  
Nationally Representative ◽  
The Individual ◽  
Over Time

Personal concerns about climate change and the environment are a powerful motivator of sustainable behavior. People’s level of concern varies as a function of a variety of social and individual factors. Using data from 58,748 participants from a nationally representative German sample, we tested preregistered hypotheses about factors that impact concerns about the environment over time. We found that environmental concerns increased modestly from 2009-2017 in the German population. However, individuals in middle adulthood tended to be more concerned and showed more consistent increases in concern over time than younger or older people. Consistent with previous research, Big Five personality traits were correlated with environmental concerns. We present novel evidence that increases in concern were related to increases in the personality traits neuroticism and openness to experience. Indeed, changes in openness explained roughly 50% of the variance in changes in environmental concerns. These findings highlight the importance of understanding the individual level factors associated with changes in environmental concerns over time, towards the promotion of more sustainable behavior at the individual level.

Understanding Economic and Health Factors Impacting the Spread of COVID-19 Disease (Preprint)

2020 ◽  
Author(s):  
Aleksandr Farseev ◽  
Yu-Yi Chu-Farseeva ◽  
Yang Qi ◽  
Daron Benjamin Loo
Keyword(s):  
Public Health ◽  
Quantitative Research ◽  
Health Indicators ◽  
Initial Study ◽  
Disease Spread ◽  
Factors Affecting ◽  
Country Level ◽  
Development Scenarios ◽  
Health Factors ◽  
Country Clusters

UNSTRUCTURED The rapid spread of the Coronavirus 2019 disease (COVID-19) had drastically impacted life all over the world. While some economies are actively recovering from this pestilence, others are experiencing fast and consistent disease spread, compelling governments to impose social distancing measures that have put a halt on routines, especially in densely-populated areas. Aiming at bringing more light on key economic and public health factors affecting the disease spread, this initial study utilizes a quantitative statistical analysis based on the most recent publicly-available COVID-19 datasets. The study had shown and explained multiple significant relationships between the COVID-19 data and other country-level statistics. We have also identified and statistically profiled four major country-level clusters with relation to different aspects of COVID-19 development and country-level economic and health indicators. Specifically, this study has identified potential COVID-19 under-reporting traits as well as various economic factors that impact COVID-19 Diagnosis, Reporting, and Treatment. Based on the country clusters, we have also described the four disease development scenarios, which are tightly knit to country-level economic and public health factors. Finally, we have highlighted the potential limitation of reporting and measuring COVID-19 and provided recommendations on further in-depth quantitative research.

scholarly journals Predictors of historical change in drug treatment coverage among people who inject drugs in 90 large metropolitan areas in the USA, 1993–2007

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Barbara Tempalski ◽  
Leslie D. Williams ◽  
Brooke S. West ◽  
Hannah L. F. Cooper ◽  
Stephanie Beane ◽  
...  
Keyword(s):  
Public Health ◽  
Drug Treatment ◽  
Resource Availability ◽  
People Who Inject Drugs ◽  
Census Data ◽  
Poverty Rate ◽  
Community Action ◽  
Historical Change ◽  
Treatment Coverage ◽  
Over Time

Abstract Background Adequate access to effective treatment and medication assisted therapies for opioid dependence has led to improved antiretroviral therapy adherence and decreases in morbidity among people who inject drugs (PWID), and can also address a broad range of social and public health problems. However, even with the success of syringe service programs and opioid substitution programs in European countries (and others) the US remains historically low in terms of coverage and access with regard to these programs. This manuscript investigates predictors of historical change in drug treatment coverage for PWID in 90 US metropolitan statistical areas (MSAs) during 1993–2007, a period in which, overall coverage did not change. Methods Drug treatment coverage was measured as the number of PWID in drug treatment, as calculated by treatment entry and census data, divided by numbers of PWID in each MSA. Variables suggested by the Theory of Community Action (i.e., need, resource availability, institutional opposition, organized support, and service symbiosis) were analyzed using mixed-effects multivariate models within dependent variables lagged in time to study predictors of later change in coverage. Results Mean coverage was low in 1993 (6.7%; SD 3.7), and did not increase by 2007 (6.4%; SD 4.5). Multivariate results indicate that increases in baseline unemployment rate (β = 0.312; pseudo-p < 0.0002) predict significantly higher treatment coverage; baseline poverty rate (β = − 0.486; pseudo-p < 0.0001), and baseline size of public health and social work workforce (β = 0.425; pseudo-p < 0.0001) were predictors of later mean coverage levels, and baseline HIV prevalence among PWID predicted variation in treatment coverage trajectories over time (baseline HIV * Time: β = 0.039; pseudo-p < 0.001). Finally, increases in black/white poverty disparity from baseline predicted significantly higher treatment coverage in MSAs (β = 1.269; pseudo-p < 0.0001). Conclusions While harm reduction programs have historically been contested and difficult to implement in many US communities, and despite efforts to increase treatment coverage for PWID, coverage has not increased. Contrary to our hypothesis, epidemiologic need, seems not to be associated with change in treatment coverage over time. Resource availability and institutional opposition are important predictors of change over time in coverage. These findings suggest that new ways have to be found to increase drug treatment coverage in spite of economic changes and belt-tightening policy changes that will make this difficult.

scholarly journals The case for tracking misinformation the way we track disease

2021 ◽  
Vol 8 (1) ◽  
pp. 205395172110138
Author(s):  
Erika Bonnevie ◽  
Jennifer Sittig ◽  
Joe Smyser
Keyword(s):  
Public Health ◽  
Real Time ◽  
Supervised Machine Learning ◽  
Disease Spread ◽  
The Public ◽  
Monitoring Tools ◽  
Core Function ◽  
Public Health Organizations ◽  
Front Line Workers ◽  
Media Data

While public health organizations can detect disease spread, few can monitor and respond to real-time misinformation. Misinformation risks the public’s health, the credibility of institutions, and the safety of experts and front-line workers. Big Data, and specifically publicly available media data, can play a significant role in understanding and responding to misinformation. The Public Good Projects uses supervised machine learning to aggregate and code millions of conversations relating to vaccines and the COVID-19 pandemic broadly, in real-time. Public health researchers supervise this process daily, and provide insights to practitioners across a range of disciplines. Through this work, we have gleaned three lessons to address misinformation. (1) Sources of vaccine misinformation are known; there is a need to operationalize learnings and engage the pro-vaccination majority in debunking vaccine-related misinformation. (2) Existing systems can identify and track threats against health experts and institutions, which have been subject to unprecedented harassment. This supports their safety and helps prevent the further erosion of trust in public institutions. (3) Responses to misinformation should draw from cross-sector crisis management best practices and address coordination gaps. Real-time monitoring and addressing misinformation should be a core function of public health, and public health should be a core use case for data scientists developing monitoring tools. The tools to accomplish these tasks are available; it remains up to us to prioritize them.

scholarly journals An analysis of COVID-19 clusters in India

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Pooja Sengupta ◽  
Bhaswati Ganguli ◽  
Sugata SenRoy ◽  
Aditya Chatterjee
Keyword(s):  
Public Health ◽  
Cluster Analysis ◽  
Population Density ◽  
Case Studies ◽  
Compartment Model ◽  
Health Interventions ◽  
Disease Spread ◽  
Second Phase ◽  
Public Health Interventions ◽  
Homogeneous Groups

Abstract Background In this study we cluster the districts of India in terms of the spread of COVID-19 and related variables such as population density and the number of specialty hospitals. Simulation using a compartment model is used to provide insight into differences in response to public health interventions. Two case studies of interest from Nizamuddin and Dharavi provide contrasting pictures of the success in curbing spread. Methods A cluster analysis of the worst affected districts in India provides insight about the similarities between them. The effects of public health interventions in flattening the curve in their respective states is studied using the individual contact SEIQHRF model, a stochastic individual compartment model which simulates disease prevalence in the susceptible, infected, recovered and fatal compartments. Results The clustering of hotspot districts provide homogeneous groups that can be discriminated in terms of number of cases and related covariates. The cluster analysis reveal that the distribution of number of COVID-19 hospitals in the districts does not correlate with the distribution of confirmed COVID-19 cases. From the SEIQHRF model for Nizamuddin we observe in the second phase the number of infected individuals had seen a multitudinous increase in the states where Nizamuddin attendees returned, increasing the risk of the disease spread. However, the simulations reveal that implementing administrative interventions, flatten the curve. In Dharavi, through tracing, tracking, testing and treating, massive breakout of COVID-19 was brought under control. Conclusions The cluster analysis performed on the districts reveal homogeneous groups of districts that can be ranked based on the burden placed on the healthcare system in terms of number of confirmed cases, population density and number of hospitals dedicated to COVID-19 treatment. The study rounds up with two important case studies on Nizamuddin basti and Dharavi to illustrate the growth curve of COVID-19 in two very densely populated regions in India. In the case of Nizamuddin, the study showed that there was a manifold increase in the risk of infection. In contrast it is seen that there was a rapid decline in the number of cases in Dharavi within a span of about one month.

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