Determinants of adherence to personal preventive behaviours based on the health belief model: a cross-sectional study in South Korea during the initial stage of the COVID-19 pandemic.

BACKGROUND: Along with the rapid transmission of COVID-19, adherence to preventive behaviours plays a crucial role with respect to the control of COVID-19. However, different individuals' psychological characteristics and risk perception result in various forms of response to preventive behaviours. Based on the Health Belief Model, this study identifies the factors associated with preventive behaviours towards COVID-19 in South Korea during the initial stage of the COVID-19 pandemic. METHODS: A cross-sectional study was conducted in April 2020 through an anonymous online survey. A total of 1207 people in the age bracket of 20-59 years participated in the survey. Single and multiple linear regression analyses were conducted to identify the determinants of preventive behaviours against COVID-19. RESULTS: The following factors were associated with preventive behaviours towards COVID-19: female gender (ß = .124, p < 0.001), has a master's degree or above (ß = 0.065, p = 0.010), perceived susceptibility (ß = .197, p < 0.001), self-efficacy (ß = .404, p < 0.001), trust in radio (ß = -.080, p = .006), trust in official government website (ß = .057, p = .045), trust in social networks (ß = .054, p = .033), and trust in family and friends (ß = .068, p = .009), with an explanatory power of 41.5% (R2 = 0.415). CONCLUSIONS: To flatten the epidemic curve, it is important to understand the public's risk perception and the motivation behind behavioural responses that aim to promote preventive behaviours among the public. Thus, this study calls for the provision of accessible and credible information sources and demonstrates a public health campaign that encourages the public's engagement in preventive behaviours towards COVID-19.

Socioeconomic disparity and the risk of contracting COVID-19 in South Korea: an NHIS-COVID-19 database cohort study.

BACKGROUND: The relationship between socioeconomic status and the risk of contracting coronavirus disease (COVID-19) remains controversial. We aimed to investigate whether socioeconomic status affected the risk of contracting COVID-19 in the South Korean population. METHODS: The NHIS-COVID-19 database cohort was used in this population-based study. We collected the data of COVID-19 patients who were diagnosed between January 1, 2020 and June 4, 2020 and those of the control population. The income levels of all individuals as of February 2020 were extracted, and study participants were classified into four groups based on quartiles: Q1 (the lowest) to Q4 (the highest). Data were statistically analyzed using multivariable logistic regression modeling. RESULTS: In total, 122,040 individuals-7669 and 114,371 individuals in the COVID-19 and control groups, respectively-were included in the final analysis. The multivariable logistic regression model showed that the Q1 group had a 1.19-fold higher risk of contracting COVID-19 than the Q4 group, whereas the Q2 and Q3 groups showed no significant differences. In the 20-39 years age group, compared with the Q4 group, the Q3 and Q2 groups showed 11 and 22% lower risks of contracting COVID-19, respectively. In the ≥60 years age group, compared with the Q4 group, the Q1, Q2, and Q3 groups showed a 1.39-, 1.29-, and 1.14-fold higher risks of COVID-19, respectively. CONCLUSIONS: Lower socioeconomic status was associated with a higher risk of contracting COVID-19 in South Korea. This association was more evident in the older population (age ≥ 60 years), whereas both lower and higher socioeconomic statuses were associated with higher risks of contracting COVID-19 in the young adult population (in the 20-39 year age group). Strategies for the prevention of COVID-19 should focus on individuals of lower socioeconomic status and on young adults of higher and lower socioeconomic status.

Clinical Features of COVID-19 in Uzbekistan.

BACKGROUND: As of April 30, 2020, a total of 2,039 cases of the novel coronavirus disease 2019 (COVID-19) were confirmed in the Republic of Uzbekistan after the first detection on March 15. Reports on symptoms of COVID-19 are non-specific and known to vary from asymptomatic, mild to severe, or fatal. This study aimed to analyze the symptomatic and clinical characteristics of study participants based on the medical records of participants hospitalized with COVID-19 in Uzbekistan. METHODS: We collected all data from medical records of COVID-19 confirmed patients in 19 hospitals from 13 regions of Uzbekistan between March 15 and April 30. We selected 1,030 patients discharged from the hospitals after COVID-19 treatment as study participants, excluding those with missing data. Further, we collected demographics, symptoms, clinical outcomes, and treatment data through medical records. RESULTS: More than half (57.6%) of confirmed cases of COVID-19 were males, and the median age was 36.0 years. The most frequent symptoms at the first inspection on hospital admission of all patients were fatigue (59.7%), dry cough (54.1%), pharyngalgia (31.6%), headache (20.6%), and anorexia (12.5%). Compared to the oldest group, the youngest group showed a lower frequency of symptoms. About half of the group aged 18-49 years reported that they came from abroad. One-fifth of patients in group 50-84 received oxygen support, while no patients in group aged 0-17 years received oxygen support. About two-thirds of the participants from intensive care unit (ICU) came from abroad, whereas 42.1% of the non-ICU group returned from other countries. Regarding symptoms, 16.9% of the patients in the ICU group were asymptomatic, while 5.8% in the non-ICU group were asymptomatic. CONCLUSION: This study suggests that the medical delivery system and resource distribution need to be implemented based on clinical characteristics by age and severity to delay and effectively respond to the spread of infections in the future. This study analyzed symptoms of COVID-19 patients across Uzbekistan, which is useful as primary data for policies on COVID-19 in Uzbekistan.