METHODS: We downloaded COVID-19 outbreak data of the number of confirmed cases in all countries as of October 19, 2020. The IRT-based predictive model was built to determine the pandemic IP for each country. A model building scheme was demonstrated to fit the number of cumulative infected cases. Model parameters were estimated using the Solver add-in tool in Microsoft Excel. The absolute advantage coefficient (AAC) was computed to track the IP at the minimum of incremental points on a given ogive curve. The time-to-event analysis (a.k.a. survival analysis) was performed to compare the difference in IPs among continents using the area under the curve (AUC) and the respective 95% confidence intervals (CIs). An online comparative dashboard was created on Google Maps to present the epidemic prediction for each country.
RESULTS: The top 3 countries that were hit severely by COVID-19 were France, Malaysia, and Nepal, with IP days at 263, 262, and 262, respectively. The top 3 continents that were hit most based on IP days were Europe, South America, and North America, with their AUCs and 95% CIs at 0.73 (0.61-0.86), 0.58 (0.31-0.84), and 0.54 (0.44-0.64), respectively. An online time-event result was demonstrated and shown on Google Maps, comparing the IP probabilities across continents.
CONCLUSION: An IRT modeling scheme fitting the epidemic data was used to predict the length of IP days. Europe, particularly France, was hit seriously by COVID-19 based on the IP days. The IRT model incorporated with AAC is recommended to determine the pandemic IP.
METHODS: The probiotic characteristics of Ld45E were evaluated by examining its morphology, pH tolerance, adhesive ability onto HeLa cells, hemolytic activity, antibiotic susceptibility, and autoaggregation ability. Then, the antimicrobial activity of Ld45E was determined using Ld45E culture, cell-free supernatant, and crude bacteriocin solution. Co-aggregation and competition ability assays against various pathogens were conducted. The immunoregulatory effects of Ld45E were analyzed by measuring the proinflammatory cytokine IL-17. A p-value less than 0.05 was considered statistical significance.
RESULTS: Ld45E is 3-5 mm in diameter and round with a flat-shaped colony. pH 4 and 4.5 were the most favorable range for Ld45E growth within 12 h of incubation. Ld45E showed a strong adhesion ability onto HeLa cells (86%) and negative hemolytic activities. Ld45E was also sensitive to ceftriaxone, cefuroxime, ciprofloxacin, and doxycycline. We found that it had a good autoaggregation ability of 80%. Regarding antagonistic properties, Ld45E culture showed strong antimicrobial activity against GBS, E. coli, and Klebsiella spp. but only a moderate effect on C. parapsilosis. Cell-free supernatant of Ld45E exerted the most potent inhibitory effects at 40 °C against all genital pathogens, whereas bacteriocin showed a robust inhibition at 37 °C and 40 °C. The highest co-aggregation affinity was observed with GBS (81%) and E. coli (40%). Competition ability against the adhesion of GBS (80%), E. coli (76%), Klebsiella (72%), and C. parapsilosis (58%) was found. Ld45E was able to reduce the induction of the proinflammatory protein IL-17.
CONCLUSIONS: Ld45E possessed antimicrobial and immunoregulatory properties, with better cell-on-cell activity than supernatant activity. Thus, Ld45E is a potential probiotic candidate for adjunct therapy to address vaginal infections.
METHOD: Through an online survey, we used Coronavirus Anxiety Scale (CAS) to measure the level of anxiety associated with the COVID-19 crisis and Brief Coping Orientation to Problems Experienced (COPE) to assess the coping responses adopted to handle stressful life events. Coping strategies were classified as adaptive and maladaptive, for which the aggregate sores were calculated. Multiple linear regression was used to determine the predictors of anxiety adjusted for potentially confounding variables. Results from 434 participants were available for analysis.
RESULTS: The mean score (SD) of the CAS was 1.1 (1.8). The mean scores of adaptive and maladaptive coping strategies were 35.69 and 19.28, respectively. Multiple linear regression revealed that maladaptive coping [Adjusted B coefficient = 4.106, p-value < 0.001] and presence of comorbidities [Adjusted B coefficient = 1.376, p-value = 0.025] significantly predicted anxiety.
CONCLUSION: Maladaptive coping and presence of comorbidities were the predictors of coronavirus anxiety. The apparent lack of anxiety in relation to COVID-19 and movement restriction is reflective of the reported high level of satisfaction with the support and services provided during the COVID-19 outbreak in Malaysia. Adaptive coping strategies were adopted more frequently than maladaptive. Nevertheless, public education on positive coping strategies and anxiety management may be still be relevant to provide mental health support to address the needs of the general population.