Disease burden due to COVID-19 in Taiwan: Disability-adjusted life years (DALYs) with implication of Monte Carlo simulations.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) has affected a large number of countries. Informing the public and decision makers of the COVID-19's economic burdens is essential for understanding the real pandemic impact. METHODS: COVID-19 premature mortality and disability impact in Taiwan was analyzed using the Taiwan National Infectious Disease Statistics System (TNIDSS) by estimating the sex/age-specific years of life lost through death (YLLs), the number of years lived with disability (YLDs), and the disability-adjusted life years (DALYs) from January 2020 to November 2021. RESULTS: Taiwan recorded 1004.13 DALYs (95% CI: 1002.75-1005.61) per 100,000 population for COVID-19, with YLLs accounting for 99.5% (95% CI: 99.3%99.6%) of all DALYs, with males suffering more from the disease than females. For population aged ≥ 70 years, the disease burdens of YLDs and YLLs were 0.1% and 99.9%, respectively. Furthermore, we found that duration of disease in critical state contributed 63.9% of the variance in DALY estimations. CONCLUSIONS: The nationwide estimation of DALYs in Taiwan provides insights into the demographic distributions and key epidemiological parameter for DALYs. The essentiality of enforcing protective precautions when needed is also implicated. The higher YLLs percentage in DALYs also revealed the fact of high confirmed death rates in Taiwan. To reduce infection risks and disease, it is crucial to maintain moderate social distancing, border control, hygiene measures, and increase vaccine coverage levels.

Disease burden due to COVID-19 in Taiwan: disability-adjusted life years (DALYs) with implication of Monte Carlo simulations

Background The novel coronavirus disease 2019 (COVID-19) has affected a large number of countries. Informing the public and decision makers of the COVID-19's economic burdens is essential for understanding the real pandemic impact. Methods COVID-19 premature mortality and disability impact in Taiwan was analyzed using the Taiwan National Infectious Disease Statistics System (TNIDSS) by estimating the sex/age-specific years of life lost through death (YLLs), the number of years lived with disability (YLDs), and the disability-adjusted life years (DALYs) from January 2020 to November 2021. Results Taiwan recorded 1,004.13 DALYs (95% CI: 1,002.75–1,005.61) per 100,000 population for COVID-19, with YLLs accounting for 99.5% (95% CI: 99.3%—99.6%) of all DALYs, with males suffering more from the disease than females. For population aged ≥ 70 years, the disease burdens of YLDs and YLLs were 0.1% and 99.9%, respectively. Furthermore, we found that duration of disease in critical state contributed 63.9% of the variance in DALY estimations. Conclusions The nationwide estimation of DALYs in Taiwan provides insights into the demographic distributions and key epidemiological parameter for DALYs. The essentiality of enforcing protective precautions when needed is also implicated. The higher YLLs percentage in DALYs also revealed the fact of high confirmed death rates in Taiwan. To reduce infection risks and disease, it is crucial to maintain moderate social distancing, border control, hygiene measures, and increase vaccine coverage levels.

Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects.

The Wells-Riley model invokes human physiological and engineering parameters to successfully treat airborne transmission of infectious diseases. Applications of this model would have high potentiality on evaluating policy actions and interventions intended to improve public safety efforts on preventing the spread of COVID-19 in an enclosed space. Here, we constructed the interaction relationships among basic reproduction number (R0) - exposure time - indoor population number by using the Wells-Riley model to provide a robust means to assist in planning containment efforts. We quantified SARS-CoV-2 changes in a case study of two Wuhan (Fangcang and Renmin) hospitals. We conducted similar approach to develop control measures in various hospital functional units by taking all accountable factors. We showed that inhalation rates of individuals proved crucial for influencing the transmissibility of SARS-CoV-2, followed by air supply rate and exposure time. We suggest a minimum air change per hour (ACH) of 7 h-1 would be at least appropriate with current room volume requirements in healthcare buildings when indoor population number is < 10 and exposure time is < 1 h with one infector and low activity levels being considered. However, higher ACH (> 16 h-1) with optimal arranged-exposure time/people and high-efficiency air filters would be suggested if more infectors or higher activity levels are presented. Our models lay out a practical metric for evaluating the efficacy of control measures on COVID-19 infection in built environments. Our case studies further indicate that the Wells-Riley model provides a predictive and mechanistic basis for empirical COVID-19 impact reduction planning and gives a framework to treat highly transmissible but mechanically heterogeneous airborne SARS-CoV-2.

Pharmacological Mechanism of NRICM101 for COVID-19 Treatments by Combined Network Pharmacology and Pharmacodynamics.

Symptom treatments for Coronavirus disease 2019 (COVID-19) infection and Long COVID are one of the most critical issues of the pandemic era. In light of the lack of standardized medications for treating COVID-19 symptoms, traditional Chinese medicine (TCM) has emerged as a potentially viable strategy based on numerous studies and clinical manifestations. Taiwan Chingguan Yihau (NRICM101), a TCM designed based on a medicinal formula with a long history of almost 500 years, has demonstrated its antiviral properties through clinical studies, yet the pharmacogenomic knowledge for this formula remains unclear. The molecular mechanism of NRICM101 was systematically analyzed by using exploratory bioinformatics and pharmacodynamics (PD) approaches. Results showed that there were 434 common interactions found between NRICM101 and COVID-19 related genes/proteins. For the network pharmacology of the NRICM101, the 434 common interacting genes/proteins had the highest associations with the interleukin (IL)-17 signaling pathway in the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Moreover, the tumor necrosis factor (TNF) was found to have the highest association with the 30 most frequently curated NRICM101 chemicals. Disease analyses also revealed that the most relevant diseases with COVID-19 infections were pathology, followed by cancer, digestive system disease, and cardiovascular disease. The 30 most frequently curated human genes and 2 microRNAs identified in this study could also be used as molecular biomarkers or therapeutic options for COVID-19 treatments. In addition, dose-response profiles of NRICM101 doses and IL-6 or TNF-α expressions in cell cultures of murine alveolar macrophages were constructed to provide pharmacodynamic (PD) information of NRICM101. The prevalent use of NRICM101 for standardized treatments to attenuate common residual syndromes or chronic sequelae of COVID-19 were also revealed for post-pandemic future.