Dataset Information

Social Determinants in Self-Protective Behavior Related to COVID-19: Association Rule-Mining Study.

ABSTRACT:

Background

Human behavior is crucial in health outcomes. Particularly, individual behavior is a determinant of the success of measures to overcome critical conditions, such as a pandemic. In addition to intrinsic public health challenges associated with COVID-19, in many countries, some individuals decided not to get vaccinated, streets were crowded, parties were happening, and businesses struggling to survive were partially open, despite lockdown or stay-at-home instructions. These behaviors contrast with the instructions for potential benefits associated with social distancing, use of masks, and vaccination to manage collective and individual risks.

Objective

Considering that human behavior is a result of individuals' social and economic conditions, we investigated the social and working characteristics associated with reports of appropriate protective behavior in Brazil.

Methods

We analyzed data from a large web survey of individuals reporting their behavior during the pandemic. We selected 3 common self-care measures: use of protective masks, distancing by at least 1 m when out of the house, and handwashing or use of alcohol, combined with assessment of the social context of respondents. We measured the frequency of the use of these self-protective measures. Using a frequent pattern-mining perspective, we generated association rules from a set of answers to questions that co-occur with at least a given frequency, identifying the pattern of characteristics of the groups divided according to protective behavior reports.

Results

The rationale was to identify a pool of working and social characteristics that might have better adhesion to behaviors and self-care measures, showing these are more socially determined than previously thought. We identified common patterns of socioeconomic and working determinants of compliance with protective self-care measures. Data mining showed that social determinants might be important to shape behavior in different stages of the pandemic.

Conclusions

Identification of context determinants might be helpful to identify unexpected facilitators and constraints to fully follow public policies. The context of diseases contributes to psychological and physical health outcomes, and context understanding might change the approach to a disease. Hidden social determinants might change protective behavior, and social determinants of protective behavior related to COVID-19 are related to work and economic conditions.

Trial registration

Not applicable.

SUBMITTER: Urbanin G

PROVIDER: S-EPMC9202654 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe COVID-19 pandemic is a significant public health crisis that is hitting hard on people's health, well-being, and freedom of movement, and affecting the global economy. Scientists worldwide are competing to develop therapeutics and vaccines; currently, three drugs and two vaccine candidates have been given emergency authorization use. However, there are still questions of efficacy with regard to specific subgroups of patients and the vaccine's scalability to the general public. Under such circumstances, understanding COVID-19 symptoms is vital in initial triage; it is crucial to distinguish the severity of cases for effective management and treatment. This study aimed to discover symptom patterns and overall symptom rules, including rules disaggregated by age, sex, chronic condition, and mortality status, among COVID-19 patients.MethodsThis study was a retrospective analysis of COVID-19 patient data made available online by the Wolfram Data Repository through May 27, 2020. We applied a widely used rule-based machine learning technique called association rule mining to identify frequent symptoms and define patterns in the rules discovered.ResultIn total, 1,560 patients with COVID-19 were included in the study, with a median age of 52 years. The most frequently occurring symptom was fever (67%), followed by cough (37%), malaise/body soreness (11%), pneumonia (11%), and sore throat (8%). Myocardial infarction, heart failure, and renal disease were present in less than 1% of patients. The top ten significant symptom rules (out of 71 generated) showed cough, septic shock, and respiratory distress syndrome as frequent consequents. If a patient had a breathing problem and sputum production, then, there was higher confidence of that patient having a cough; if cardiac disease, renal disease, or pneumonia was present, then there was a higher confidence of septic shock or respiratory distress syndrome. Symptom rules differed between younger and older patients and between male and female patients. Patients who had chronic conditions or died of COVID-19 had more severe symptom rules than those patients who did not have chronic conditions or survived of COVID-19. Concerning chronic condition rules among 147 patients, if a patient had diabetes, prerenal azotemia, and coronary bypass surgery, there was a certainty of hypertension.ConclusionThe most frequently reported symptoms in patients with COVID-19 were fever, cough, pneumonia, and sore throat; while 1% had severe symptoms, such as septic shock, respiratory distress syndrome, and respiratory failure. Symptom rules differed by age and sex. Patients with chronic disease and patients who died of COVID-19 had severe symptom rules more specifically, cardiovascular-related symptoms accompanied by pneumonia, fever, and cough as consequents.

Project description:PurposeThe COVID-19 pandemic largely suspended in-person scientific meetings because of risk of disease spread. In the era of vaccination and social distancing practices, meetings have begun returning to in-person formats. We surveyed attendees and potential attendees of 2 oncology meetings in the United States to identify rates of mixing behavior and the subsequent rate of self-reported COVID-19 infection.Methods and materialsWe collected via survey reported social mixing behavior and COVID-19 positivity (within 21 days of meeting conclusion) of actual and potential in-person attendees of the American Society of Clinical Oncology (ASCO) Quality Care Symposium held September 24 to 25, 2021, and the American Society for Radiation Oncology (ASTRO) Annual Meeting held October 24 to 27, 2021. Conference speakers and other participants were identified through publicly available meeting materials and targeted via e-mail when possible. Recruitment of additional attendees and potential attendees was also conducted through a sharable link promoted via oncology newsletters and social media. Descriptive statistics alone were performed owing to low COVID-19 event rates.ResultsResponse rates from targeted conference participants with publicly available e-mails were 27.4% for the ASCO and 14.3% for the ASTRO meetings. The ASCO survey produced 94 responses (48 in-person attendees). The ASTRO survey produced 370 responses (267 in-person attendees). Across both meetings, 3 of 308 (1.0%) in-person attendees versus 2 of 141 (1.4%) nonattendees tested positive for COVID-19. Low COVID-19 positivity rates were reported among in-person attendees spending more (>20) versus fewer (≤20) hours attending live sessions (2.2% vs 0%) and among indoor social event participants versus nonparticipants (0.8% vs 1.9%). Attendees largely felt comfortable attending additional in-person meetings after experiencing ASCO (87.5%) or ASTRO (91.9%) and felt mask compliance was good or excellent at ASCO (100%) and ASTRO (94.6%) meetings.ConclusionsIn-person meetings do not seem to be contributing to high rates of new COVID-19 infections in the setting of vaccine and social distancing mandates, supporting paths forward for at least partially in-person conferences as COVID-19 becomes endemic.