Development and validation of a multi-lingual online questionnaire for surveying the COVID-19 prevention and control measures used in global workplaces

Policy responses to COVID-19 in Sri Lanka and the consideration of Indigenous Peoples

COVID-19 has had uneven impacts on health and well-being, with Indigenous communities in the Global South facing some of the highest risks. Focusing on the experience of Sri Lanka, this study identifies key policy responses to COVID-19, documents how they evolved over two years of the pandemic, and examines if and how government responses have addressed issues pertaining to Indigenous Peoples. Drawing upon an analysis of policy documents (n = 110) and interviews with policymakers (n = 20), we characterize seven key policy responses implemented by the Sri Lankan government: i) testing for and identifying COVID-19; ii) quarantine procedures; iii) provisional clinical treatments; iv) handling other diseases during COVID-19; v) movement; vi) guidelines to be adhered to by the general public; and vii) health and vaccination. The nature of these responses changed as the pandemic progressed. There is no evidence that policy development or implementation incorporated the voices and needs of Indigenous Peoples.

The Importance of Behavioral and Native Factors on COVID-19 Infection and Severity: Insights from a Preliminary Cross-Sectional Study

The COVID-19 pandemic has had a major impact on a global scale. Understanding the innate and lifestyle-related factors influencing the rate and severity of COVID-19 is important for making evidence-based recommendations. This cross-sectional study aims at establishing a potential relationship between human characteristics and vulnerability/resistance to SARS-CoV-2. We hypothesize that the impact of the virus is not the same due to cultural and ethnic differences. A cross-sectional study was performed using an online questionnaire. The methodology included the development of a multi-language survey, expert evaluation, and data analysis. Data were collected using a 13-item pre-tested questionnaire based on a literature review between 9 December 2020 and 21 July 2021. Data were statistically analyzed using logistic regression. For a total of 1125 respondents, 332 (29.5%) were COVID-19 positive; among them, 130 (11.5%) required home-based treatment, and 14 (1.2%) intensive care. The significant and most influential factors on infection included age, physical activity, and health status (p < 0.05), i.e., better physical activity and better health status significantly reduced the possibility of infection, while older age significantly increased it. The severity of infection was negatively associated with the acceptance (adherence and respect) of preventive measures and positively associated with tobacco (p < 0.05), i.e., smoking regularly significantly increases the severity of COVID-19 infection. This suggests the importance of behavioral factors compared to innate ones. Apparently, individual behavior is mainly responsible for the spread of the virus. Therefore, adopting a healthy lifestyle and scrupulously observing preventive measures, including vaccination, would greatly limit the probability of infection and prevent the development of severe COVID-19.

Mat-O-Covid: Validation of a SARS-CoV-2 Job Exposure Matrix (JEM) Using Data from a National Compensation System for Occupational COVID-19

Background. We aimed to assess the validity of the Mat-O-Covid Job Exposure Matrix (JEM) on SARS-CoV-2 using compensation data from the French National Health Insurance compensation system for occupational-related COVID-19. Methods. Deidentified compensation data for occupational COVID-19 in France were obtained between August 2020 and August 2021. The case acceptance was considered as the reference. Mat-O-Covid is an expert-based French JEM on workplace exposure to SARS-CoV-2. Bi- and multivariable models were used to study the association between the exposure assessed by Mat-O-Covid and the reference, as well as the area under the curve (AUC), sensitivity, specificity, predictive values, and likelihood ratios. Results. In the 1140 cases included, there was a close association between the Mat-O-Covid index and the reference (p < 0.0001). The overall predictivity was good, with an AUC of 0.78 and an optimal threshold at 13 per thousand. Using Youden’s J statistic resulted in 0.67 sensitivity and 0.87 specificity. Both positive and negative likelihood ratios were significant: 4.9 [2.4−6.4] and 0.4 [0.3−0.4], respectively. Discussion. It was possible to assess Mat-O-Covid’s validity using data from the national compensation system for occupational COVID-19. Though further studies are needed, Mat-O-Covid exposure assessment appears to be accurate enough to be used in research.