in vitro diagnostics industry: a pandemic case study'/>
Objectives This study evaluated the effectiveness of government epidemic control policies centered on diagnostic testing and examined their impact on the in vitro diagnostics (IVD) industry. It also analyzed the complex interplay among policy interventions, epidemic dynamics, and the IVD industry’s value chain to identify key leverage points for managing future public health crises. Methods: A system dynamics (SD) model calibrated using national data from the Republic of Korea simulated the interactions between epidemic progression and the IVD value chain. We conducted a scenario analysis encompassing 6 policy interventions: research and development (R&D) investment, public–private collaboration, regulatory easing, diagnostic test performance, testing intensity, and social distancing. Results: Policies promoting investment, public–private collaboration, and regulatory easing accelerated the market entry of diagnostics, thereby reducing infections and deaths. However, these interventions were associated with lower overall industry revenue, attributable to increased market competition and a reduced patient population. A critical trade-off was noted: although regulatory speed is advantageous, using low-sensitivity diagnostics substantially worsened public health outcomes. Aggressive testing strategies and stringent social distancing were also confirmed to be effective in reducing both infections and mortality. Conclusion: This study provides a strategic framework for understanding interactions between pandemic control policies and the IVD industry. Sustained pre-crisis investment in R&D, public–private networks, and public health infrastructure is essential for effective pandemic preparedness. During a crisis, policymakers must carefully manage the critical trade-off between regulatory speed and diagnostic quality to ensure that rapid responses do not compromise public health outcomes.
Objectives Mortality statistics during the coronavirus disease 2019 (COVID-19) pandemic are crucial for the allocation of medical care resources and public health decision-making. This study was initiated to investigate the excess mortality among older adults during the pandemic. Our research focuses on 2 primary areas. First, we analyzed the cumulative excess mortality across all age groups to assess the global impact and specifically examined the top 20 countries with the highest mortality rates during the pandemic. Second, we explored excess deaths among older adults by categorizing data from the years 2020 and 2021 into age groups: 65–74, 75–84, and above 85.
Methods We analyzed data from the top 20 countries with the highest mortality rates globally, focusing on 3 components: all-cause mortality means, expected deaths mean, and excess deaths mean for both older men and women.
Results Although excess mortality is higher among older men and women across all 3 age groups (65–74, 75–84, and >85), the highest mean excess mortality was observed in women over the age of 85.
Conclusion The results indicate that the severe acute respiratory syndrome coronavirus 2 virus had a disproportionately intense impact on older women. We developed 2 types of statistical models using the data: a binomial distribution model and a correlation coefficient model, both considering the mean excess deaths in older men and women across these 3 age groups. Estimating the excess mortality among older adults will aid in the formulation of healthcare policies for this demographic.
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Methods This cross-sectional study of 57 patients with CAM was conducted over 6 months using a semi-structured standard questionnaire (the abbreviated World Health Organization Quality of Life questionnaire [WHO-BREF]) and a self-rated improvement (SRI) scale ranging from 0 to 9. Cut-off values of ≤52 and <7 were considered to indicate poor QOL and poor improvement, respectively. The correlations of QOL and SRI scores were evaluated using Spearman rho values.
Results In total, 27 patients (47.4%; 95% confidence interval [CI], 34.9%–60.1%) and 26 patients (45.6%; 95% CI, 33.4%–58.4%) had poor QOL and poor SRI scores, respectively. The overall median (interquartile range) QOL score was 52 (41–63). Headache (adjusted B, −12.3), localized facial puffiness (adjusted B , −16.4), facial discoloration (adjusted B, −23.4), loosening of teeth (adjusted B, −18.7), and facial palsy (adjusted B, −38.5) wer e significantly associated with the QOL score in patients with CAM.
Conclusion Approximately 1 in 2 patients with CAM had poor QOL and poor improvement. Various CAM symptoms were associated with QOL in these patients. Early recognition is the key to optimal treatment, improved outcomes, and improved QOL in patients with CAM.
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