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Abstract Background Asia’s elderly Baby Boomer demographic (born between 1946 and 1964) faced a huge problem during the COVID-19 pandemic due to increased all-cause mortality. We aimed to provide a unique Taiwan situation regarding the impact of Baby Boomers on excess mortalities from all causes relative to non-Baby Boomers throughout distinct times of SARS-CoV-2 mutations during the COVID-19 pandemic. Methods We used the Poisson time series design with a Bayesian directed acyclic graphic approach to build the background mortality prior to the COVID-19 pandemic between 2015 and 2019. It was then used for predicting the expected all-cause deaths compared to the reported figures during the COVID-19 pandemic period based on Taiwan residents, an Omicron-naïve cohort. Results Baby Boomers experienced a 2% negative excess mortality in 2020 (Wuhan/D614G) and a 4% excess mortality in 2021 (Alpha/Delta) with a rising background mortality trend whereas non-Baby Boomers showed the corresponding figures of 4% negative excess and 1% excess with a stable trend. Baby Boomer and non-Baby Boomer excess mortality soared to 9% (95% CI: 7-10%) and 10% (95% CI: 9-11%), respectively, during the epidemic Omicron period from January to June 2022. Surprisingly, Baby Boomers aged 58–76 experienced the same 9% excess mortality as non-Baby Boomers aged 77 and beyond. Non-COVID-19 deaths were more prevalent among Baby Boomers than non-Baby Boomers (33% vs. 29%). Conclusion Baby Boomers were more likely to die from COVID-19 in early pandemic and had more non-COVID-19 deaths in late pandemic than older non-Baby Boomers demonstrated in Taiwan Omicron-naïve cohort. For this vulnerable population, adequate access to medical care and medical capacity require more consideration.

Background: The trajectories of all-cause deaths linked to omicron infections are rarely studied, especially in relation to the efficacy of booster shots. For assessing three epidemiological death trajectories, including dying from COVID-19, dying with COVID-19, and non-COVID-19 death, we offer a new COVID-19-and-death competing risk model that deals with the primary pathway (e.g., dying from COVID-19) competing with two other pathways. Methods: We applied this model to track three trajectories: deaths directly from COVID-19, deaths with COVID-19 as a contributing factor, and indirect non-COVID-19 deaths. The study used data from a Taiwanese cohort, covering periods of Omicron subvariants BA.2, BA.5, and BA.2.75. It focused on the effectiveness of monovalent and bivalent booster vaccines against these death trajectories. Results: The highest mortality was observed during the BA.2 phase, which decreased in the BA.5 period and increased again in the BA.2.75 period. Analyzing each trajectory, we noted similar trends in deaths directly from and with COVID-19, while non-COVID-19 deaths remained stable across subvariants. Booster vaccines reduced all-cause mortality by 58% (52%−62%) for BA.2, 70% (65%−75%) for BA.5%, and 75% (70%−80%) for BA.2.75, compared to incomplete vaccination. The reduction in deaths directly from COVID-19 was 66% (61%−72%) for BA.2, 78% (72%−84%) for BA.5%, and 85% (76%−93%) for BA.2.75. For deaths with COVID-19, the figures were 46% (36%−55%), 76% (68%−84%), and 90% (86%−95%). Additionally, the booster shots decreased non-COVID-19 deaths by 64% (63%−66%) for BA.2, 38% (36%−40%) for BA.5, and 19% (17%−21%) for BA.2.75. Conclusion: Our competing risk analysis is effective for monitoring all-cause death trajectories amidst various Omicron infections. It provides insights into the impact of booster vaccines, especially bivalent ones, and highlights the consequences of inadequate healthcare for vulnerable groups.

BackgroundPrevious studies have highlighted the importance of viral shedding using cycle threshold (Ct) values obtained via reverse transcription polymerase chain reaction to understand the epidemic trajectories of SARS-CoV-2 infections. However, it is rare to elucidate the transition kinetics of Ct values from the asymptomatic or presymptomatic phase to the symptomatic phase before recovery using individual repeated Ct values. ObjectiveThis study proposes a novel Ct-enshrined compartment model to provide a series of quantitative measures for delineating the full trajectories of the dynamics of viral load from infection until recovery. MethodsThis Ct-enshrined compartment model was constructed by leveraging Ct-classified states within and between presymptomatic and symptomatic compartments before recovery or death among people with infections. A series of recovery indices were developed to assess the net kinetic movement of Ct-up toward and Ct-down off recovery. The model was applied to (1) a small-scale community-acquired Alpha variant outbreak under the “zero-COVID-19” policy without vaccines in May 2021 and (2) a large-scale community-acquired Omicron variant outbreak with high booster vaccination rates following the lifting of the “zero-COVID-19” policy in April 2022 in Taiwan. The model used Bayesian Markov chain Monte Carlo methods with the Metropolis-Hastings algorithm for parameter estimation. Sensitivity analyses were conducted by varying Ct cutoff values to assess the robustness of the model. ResultsThe kinetic indicators revealed a marked difference in viral shedding dynamics between the Alpha and Omicron variants. The Alpha variant exhibited slower viral shedding and lower recovery rates, but the Omicron variant demonstrated swifter viral shedding and higher recovery rates. Specifically, the Alpha variant showed gradual Ct-up transitions and moderate recovery rates, yielding a presymptomatic recovery index slightly higher than 1 (1.10), whereas the Omicron variant had remarkable Ct-up transitions and significantly higher asymptomatic recovery rates, resulting in a presymptomatic recovery index much higher than 1 (152.5). Sensitivity analysis confirmed the robustness of the chosen Ct values of 18 and 25 across different recovery phases. Regarding the impact of vaccination, individuals without booster vaccination had a 19% higher presymptomatic incidence rate compared to those with booster vaccination. Breakthrough infections in boosted individuals initially showed similar Ct-up transition rates but higher rates in later stages compared to nonboosted individuals. Overall, booster vaccination improved recovery rates, particularly during the symptomatic phase, although recovery rates for persistent asymptomatic infection were similar regardless of vaccination status once the Ct level exceeded 25. ConclusionsThe study provides new insights into dynamic Ct transitions, with the notable finding that Ct-up transitions toward recovery outpaced Ct-down and symptom-surfacing transitions during the presymptomatic phase. The Ct-up against Ct-down transition varies with variants and vaccination status. The proposed Ct-enshrined compartment model is useful for the surveillance of emerging infectious diseases in the future to prevent community-acquired outbreaks.

Abstract Background Predicting mortality in the emergency department (ED) is imperative to guide palliative care and end-of-life decisions. However, the clinical usefulness of utilizing the existing screening tools still leaves something to be desired. Methods We advanced the screening tool with the A-qCPR (Age, qSOFA (quick sepsis-related organ failure assessment), cancer, Performance Status Scale, and DNR (Do-Not-Resuscitate) risk score model for predicting one-year mortality in the emergency department of Taipei City Hospital of Taiwan with the potential of hospice need and evaluated its performance compared with the existing screening model. We adopted a large retrospective cohort in conjunction with in-time (the trained and the holdout validation cohort) for the development of the A-qCPR model and out-of-time validation sample for external validation and model robustness to variation with the calendar year. Results A total of 10,474 patients were enrolled in the training cohort and 33,182 patients for external validation. Significant risk scores included age (0.05 per year), qSOFA ≥ 2 (4), Cancer (5), Eastern Cooperative Oncology Group (ECOG) Performance Status score ≥ 2 (2), and DNR status (2). One-year mortality rates were 13.6% for low (score ≦ 3 points), 29.9% for medium (3 9 points). The AUROC curve for the in-time validation sample was 0.76 (0.74–0.78). However, the corresponding figure was slightly shrunk to 0.69 (0.69–0.70) based on out-of-time validation. The accuracy with our newly developed A-qCPR model was better than those existing tools including 0.57 (0.56–0.57) by using SQ (surprise question), 0.54 (0.54–0.54) by using qSOFA, and 0.59 (0.59–0.59) by using ECOG performance status score. Applying the A-qCPR model to emergency departments since 2017 has led to a year-on-year increase in the proportion of patients or their families signing DNR documents, which had not been affected by the COVID-19 pandemic. Conclusions The A-qCPR model is not only effective in predicting one-year mortality but also in identifying hospice needs. Advancing the screening tool that has been widely used for hospice in various scenarios is particularly helpful for facilitating the end-of-life decision-making process in the ED.

Abstract Background The benefits of mammographic screening have been shown to include a decrease in mortality due to breast cancer. Taiwan’s Breast Cancer Screening Program is a national screening program that has offered biennial mammographic breast cancer screening for women aged 50–69 years since 2004 and for those aged 45–69 years since 2009, with the implementation of mobile units in 2010. The purpose of this study was to compare the performance results of the program with changes in the previous (2004–2009) and latter (2010–2020) periods. Methods A cohort of 3,665,078 women who underwent biennial breast cancer mammography screenings from 2004 to 2020 was conducted, and data were obtained from the Health Promotion Administration, Ministry of Health and Welfare of Taiwan. We compared the participation of screened women and survival rates from breast cancer in the earlier and latter periods across national breast cancer screening programs. Results Among 3,665,078 women who underwent 8,169,869 examinations in the study population, the screened population increased from 3.9% in 2004 to 40% in 2019. The mean cancer detection rate was 4.76 and 4.08 cancers per 1000 screening mammograms in the earlier (2004–2009) and latter (2010–2020) periods, respectively. The 10-year survival rate increased from 89.68% in the early period to 97.33% in the latter period. The mean recall rate was 9.90% (95% CI: 9.83–9.97%) in the early period and decreased to 8.15% (95%CI, 8.13–8.17%) in the latter period. Conclusions The evolution of breast cancer screening in Taiwan has yielded favorable outcomes by increasing the screening population, increasing the 10-year survival rate, and reducing the recall rate through the participation of young women, the implementation of a mobile unit service and quality assurance program, thereby providing historical evidence to policy makers to plan future needs.

Background/purpose: An understanding of self-protection related factors is important for dental infection control. This study aimed to investigate factors associated with personal self-protection in infection control among dental care workers. Materials and methods: A cross-sectional survey with self-report questionnaire was conducted between Jan and Dec, 2018.275 dentists and 298 dental assistants were enrolled from randomly selected dental care settings. Results: Compliance with wearing hair caps, facial masks, and hand washing is not as high as oral masks and gloves (over 90%). For dentists, the level of clinical setting (aOR = 3.1, P

Abstract Facing the emerging COVID viral variants and the uneven distribution of vaccine worldwide, imported pre-symptomatic COVID-19 cases play a pivotal role in border control strategies. A stochastic disease process and computer simulation experiments with Bayesian underpinning was therefore developed to model pre-symptomatic disease progression during incubation period on which we were based to provide precision strategies for containing the resultant epidemic caused by imported COVID-19 cases. We then applied the proposed model to data on 1051 imported COVID-19 cases among inbound passengers to Taiwan between March 2020 and April 2021. The overall daily rate (per 100,000) of pre-symptomatic COVID-19 cases was estimated as 106 (95% credible interval (CrI): 95–117) in March–June 2020, fell to 37 (95% CrI: 28–47) in July–September 2020 (p

BackgroundAlthough early dementia detection is crucial to optimize the treatment outcomes and the management of associated symptoms, the published literature is scarce regarding the effectiveness of active screening protocols in enhancing dementia awareness and increasing the rate of early detection. The present study compared the detection ratio of an active community-based survey for dementia detection with the detection ratio of passive screening during routine clinical practice. Data for passive screening were obtained from the National Health Insurance (NHI) system, which was prospectively collected during the period from 2000 to 2003.DesignA population-based cohort study with historical control.SettingTaiwan.ParticipantsA total of 183 participants aged 65 years or older were involved in a community-based survey. Data from 1,921,308 subjects aged 65 years or older were retrieved from the NHI system.MeasurementsAn adjusted detection ratio, defined as a ratio of dementia prevalence to incidence was used.ResultsThe results showed that the dementia prevalence during the 2000–2003 period was 2.91% in the elderly population, compared with a prevalence of 6.59% when the active survey was conducted. The incidence of dementia in the active survey cohort was 1.83%. Overall, the dementia detection ratio was higher using active surveys [4.23, 95% confidence interval (CI): 2.68–6.69] than using passive detection (1.45, 95% CI: 1.43–1.47) for those aged 65–79 years. Similar findings were observed for those aged 80 years and older.ConclusionThe implementation of an active community-based survey led to a 3-fold increase in the detection rate of early dementia detection compared to passive screening during routine practice.

Background: Mass screening of high-risk populations for oral cancer has proven to be effective in reducing oral cancer mortality. However, the magnitude of the effectiveness of the various screening scenarios has rarely been addressed. Methods: We developed a simulation algorithm for a prospective cohort under various oral cancer screening scenarios. A hypothetical cohort of 8 million participants aged ≥30 years with cigaret smoking and/or betel quid chewing habits was constructed based on parameters extracted from studies on oral cancer screening. The results of a population-based screening program in Taiwan and a randomized controlled trial in India were used to validate the fitness; then, the effectiveness of the model was determined by changing the screening parameters. Results: There was a reduction in the risk of advanced oral cancer by 40% (relative risk [RR] = 0.60, 95% confidence interval [CI]:0.59-0.62) and oral cancer mortality by 29% (RR = 0.71, 95% CI: 0.69-0.73) at the 6-year follow-up in a screening scenario similar to the biennial screening in Taiwan, with a 55.1% attendance rate and 92.6% referral rate. The incremental effect in reducing advanced oral cancer was approximately 5% with a short 1-year screening frequency, and the corresponding reduction in mortality was, on average, 6.5%. The incremental reduction in advanced oral cancer per 10% increase in the compliance rate was 3% to 4%, while only 1% to 2% reduction was noted per 10% increase in the referral rate. The effectiveness of screening in reducing advanced oral cancer was 5% to 6% less when both betel quid chewing and alcohol drinking habits were present. Conclusion: Our computer simulation model demonstrated the effect of screening on the reduction in oral cancer mortality under various scenarios. The results provide screening policymakers with the necessary guidance to implement screening programs to save lives.

BackgroundGlobal transmission from imported cases to domestic cluster infections is often the origin of local community-acquired outbreaks when facing emerging SARS-CoV-2 variants. ObjectiveWe aimed to develop new surveillance metrics for alerting emerging community-acquired outbreaks arising from new strains by monitoring the risk of small domestic cluster infections originating from few imported cases of emerging variants. MethodsWe used Taiwanese COVID-19 weekly data on imported cases, domestic cluster infections, and community-acquired outbreaks. The study period included the D614G strain in February 2020, the Alpha and Delta variants of concern (VOCs) in 2021, and the Omicron BA.1 and BA.2 VOCs in April 2022. The number of cases arising from domestic cluster infection caused by imported cases (Dci/Imc) per week was used as the SARS-CoV-2 strain-dependent surveillance metric for alerting local community-acquired outbreaks. Its upper 95% credible interval was used as the alert threshold for guiding the rapid preparedness of containment measures, including nonpharmaceutical interventions (NPIs), testing, and vaccination. The 2 metrics were estimated by using the Bayesian Monte Carlo Markov Chain method underpinning the directed acyclic graphic diagram constructed by the extra-Poisson (random-effect) regression model. The proposed model was also used to assess the most likely week lag of imported cases prior to the current week of domestic cluster infections. ResultsA 1-week lag of imported cases prior to the current week of domestic cluster infections was considered optimal. Both metrics of Dci/Imc and the alert threshold varied with SARS-CoV-2 variants and available containment measures. The estimates were 9.54% and 12.59%, respectively, for D614G and increased to 14.14% and 25.10%, respectively, for the Alpha VOC when only NPIs and testing were available. The corresponding figures were 10.01% and 13.32% for the Delta VOC, but reduced to 4.29% and 5.19% for the Omicron VOC when NPIs, testing, and vaccination were available. The rapid preparedness of containment measures guided by the estimated metrics accounted for the lack of community-acquired outbreaks during the D614G period, the early Alpha VOC period, the Delta VOC period, and the Omicron VOC period between BA.1 and BA.2. In contrast, community-acquired outbreaks of the Alpha VOC in mid-May 2021, Omicron BA.1 VOC in January 2022, and Omicron BA.2 VOC from April 2022 onwards, were indicative of the failure to prepare containment measures guided by the alert threshold. ConclusionsWe developed new surveillance metrics for estimating the risk of domestic cluster infections with increasing imported cases and its alert threshold for community-acquired infections varying with emerging SARS-CoV-2 strains and the availability of containment measures. The use of new surveillance metrics is important in the rapid preparedness of containment measures for averting large-scale community-acquired outbreaks arising from emerging imported SARS-CoV-2 variants.

Abstract Background Dental students have encountered changes in the teaching format amid the SARS CoV-2 pandemic. This study aims to evaluate the attitudes of dental students of one medical university toward online courses and compare them with those of non-dental students amid the SARS CoV-2 pandemic. Methods A cross-sectional survey with a self-report online questionnaire was conducted at the medical university in May 2020 in Taipei. Students from the School of Dentistry, School of Dental Technology, and School of Oral Hygiene Study were enrolled in our survey. Results In total, 473 students responded to the survey, 318 (67.2%) of whom were dental students. Overall, 366 (77%) students agreed with the change to online learning. Only 10.4% of students thought that dental professional courses with a laboratory format could be changed to online courses. Dental students were significantly more worried than non-dental students about being infected with COVID-19 and about the COVID-19 pandemic continuing. Conclusions In conclusion, changing to online learning seems to be perceived as feasible by students. However, more discussion about changing dental professional courses with a laboratory format to online courses considering the attitudes from students is needed.

BackgroundUnderstanding renal function state transition risk and associated factors in community residences is vital for appropriate preventive and care actions. We aim to investigate factors affecting renal function state transitions through 10-year longitudinal community screening surveys.MethodsThe prospective cohort study included participants who attended the screening program ≥2 times from 2001 to 2009 and were divided into two cohorts: those with baseline estimated glomerular filtration rate (eGFR) ≥60 (n = 46,278) and those with eGFR 59–30 mL/min/1.73 m2 (n = 4,656). We applied the illness-death model to identify associated factors with eGFR

Very few studies have been conducted to assess the potential preventive role of vaccines, particularly mRNA vaccines, in the improvement of survival among moderate and severe hospitalized patients with COVID-19. After community-acquired outbreaks of the Omicron variant from 18 March until 31 May 2022, occurred in Taiwan, this retrospective cohort of 4090 moderate and 1378 severe patients admitted to hospital was classified according to whether they were administered an mRNA-based vaccine, and followed up to ascertain rates of death in both the vaccinated (≥2 doses) and unvaccinated (no or 1 dose) groups. The age-adjusted hazard ratio (aHR) of less than 1 was used to assess the preventive role of mRNA vaccines in reducing deaths among moderate and severe Omicron-infected patients. Survival was statistically significantly better for the ≥2 dose jab group (aHR, 0.75, 95% confidence interval [CI], 0.60 to 0.94) and even higher among those who had received a booster jab (aHR, 0.71; 95% CI, 0.55 to 0.91) compared with the unvaccinated group among moderate patients, but not among severe patients. In conclusion, unveiling the role of mRNA vaccines in preventing moderate but not severe COVID-19 patients from death provides new insights into how mRNA vaccines play a role in the pathway leading to a severe outcome due to Omicron COVID-19.

Background/purpose: Patient safety is a major healthcare challenge. Due to a lack of safety culture knowledge among dental professionals, our objectives were to measure the level of patient safety culture using the Safety Attitude Questionnaire in Chinese (SAQ-C) and identify factors associated with positive attitudes toward patient safety. Materials and methods: A nationwide cross-sectional survey was conducted within dentistry departments of 20 hospitals and in 40 dental clinics, from which were randomly chosen. The survey (SAQ-C) comprised of 32 items and reflects five dimensions of patient safety culture. The second section collects demographic information that supposedly affects attitudes toward patient safety. Logistic regression analyses were used to identify factors that supposedly influenced positive attitudes toward patient safety. Results: Mean SAQ-C scores were significantly higher in respondents who were male, older, dentists, supervisors, and working in clinics. Positive attitudes toward patient safety were found in 172 participants (55.7%). Multivariate analyses revealed age and place of work are significantly associated with positive safety attitudes. A limitation of this study is that the association between SAQ-C scores and patient outcomes could not be examined. Conclusion: With a lack of research in the dental field, our study provides important information on patient safety attitudes for dental healthcare workers. Results from this study present the current status of patient safety culture and help raise awareness of it. Most notably, the study identified several factors associated with positive attitudes toward patient safety. The information can be used to improve patient safety in the future. Keywords: Cross-sectional study, Dental healthcare workers, Nationwide survey, Patient safety, Risk factors

Background: The surge of COVID-19 pandemic has caused severe respiratory conditions and a large number of deaths due to the shortage of intensive care unit (ICU) in many countries. Methods: We developed a compartment queue model to describe the process from case confirmation, home-based isolation, hospitalization, ICU, recovery, and death. By using public assessed data in Lombardy, Italy, we estimated two congestion indices for isolation wards and ICU. The excess ICU needs were estimated in Lombardy, Italy, and other countries when data were available, including France, Spain, Belgium, New York State in the USA, South Korea, and Japan. Results: In Lombardy, Italy, the congestion of isolation beds had increased from 2.2 to the peak of 6.0 in March and started to decline to 3.9 as of 9th May, whereas the demand for ICU during the same period has not decreased yet with an increasing trend from 2.9 to 8.0. The results showed the unmet ICU need from the second week in March as of 9th May. The same situation was shown in France, Spain, Belgium, and New York State, USA but not for South Korea and Japan. The results with data until December 2020 for Lombardy, Italy were also estimated to reflect the demand for hospitalization and ICU after the occurrence of viral variants. Conclusion: Two congestion indices for isolation wards and ICU beds using open assessed tabulated data with a compartment queue model underpinning were developed to monitor the clinical capacity in hospitals in response to the COVID-19 pandemic.

Background/purpose: A synthesis design and multistate analysis is required for assessing the clinical efficacy of antiviral therapy on dynamics of multistate disease progression and in reducing the mortality and enhancing the recovery of patients with COVID-19. A case study on remdesivir was illustrated for the clinical application of such a novel design and analysis. Methods: A Bayesian synthesis design was applied to integrating the empirical evidence on the one-arm compassion study and the two-arm ACTT-1 trial for COVID-19 patients treated with remdesivir. A multistate model was developed to model the dynamics of hospitalized COVID-19 patients from three transient states of low, medium-, and high-risk until the two outcomes of recovery and death. The outcome measures for clinical efficacy comprised high-risk state, death, and discharge. Results: The efficacy of remdesivir in reducing the risk of death and enhancing the odds of recovery were estimated as 31% (95% CI, 18–44%) and 10% (95% CI, 1–18%), respectively. Remdesivir therapy for patients with low-risk state showed the efficacy in reducing subsequent progression to high-risk state and death by 26% (relative rate (RR), 0.74; 95% CI, 0.55–0.93) and 62% (RR, 0.38; 95% CI, 0.29–0.48), respectively. Less but still statistically significant efficacy in mortality reduction was noted for the medium- and high-risk patients. Remdesivir treated patients had a significantly shorter period of hospitalization (9.9 days) compared with standard care group (12.9 days). Conclusion: The clinical efficacy of remdesvir therapy in reducing mortality and accelerating discharge has been proved by the Bayesian synthesis design and multistate analysis.

Background: Vaccine is supposed to be the most effective means to prevent COVID-19 as it may not only save lives but also reduce productivity loss due to resuming pre-pandemic activities. Providing the results of economic evaluation for mass vaccination is of paramount importance for all stakeholders worldwide. Methods: We developed a Markov decision tree for the economic evaluation of mass vaccination against COVID-19. The effectiveness of reducing outcomes after the administration of three COVID-19 vaccines (BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna), and AZD1222 (Oxford-AstraZeneca)) were modelled with empirical parameters obtained from literatures. The direct cost of vaccine and COVID-19 related medical cost, the indirect cost of productivity loss due to vaccine jabs and hospitalization, and the productivity loss were accumulated given different vaccination scenarios. We reported the incremental cost-utility ratio and benefit/cost (B/C) ratio of three vaccines compared to no vaccination with a probabilistic approach. Results: Moderna and Pfizer vaccines won the greatest effectiveness among the three vaccines under consideration. After taking both direct and indirect costs into account, all of the three vaccines dominated no vaccination strategy. The results of B/C ratio show that one dollar invested in vaccine would have USD $13, USD $23, and USD $28 in return for Moderna, Pfizer, and AstraZeneca, respectively when health and education loss are considered. The corresponding figures taking value of the statistical life into account were USD $176, USD $300, and USD $443. Conclusion: Mass vaccination against COVID-19 with three current available vaccines is cost-saving for gaining more lives and less cost incurred.

The spread of the emerging pathogen, named as SARS-CoV-2, has led to an unprecedented COVID-19 pandemic since 1918 influenza pandemic. This review first sheds light on the similarity on global transmission, surges of pandemics, and the disparity of prevention between two pandemics. Such a brief comparison also provides an insight into the potential sequelae of COVID-19 based on the inference drawn from the fact that a cascade of successive influenza pandemic occurred after 1918 and also the previous experience on the epidemic of SARS and MERS occurring in 2003 and 2015, respectively. We then propose a systematic framework for elucidating emerging infectious disease (EID) such as COVID-19 with a panorama viewpoint from natural infection and disease process, public health interventions (non-pharmaceutical interventions (NPIs) and vaccine), clinical treatments and therapies (antivirals), until global aspects of health and economic loss, and economic evaluation of interventions with emphasis on mass vaccination. This review not only concisely delves for evidence-based scientific literatures from the origin of outbreak, the spread of SARS-CoV-2 to three surges of pandemic, and NPIs and vaccine uptakes but also provides a new insight into how to apply big data analytics to identify unprecedented discoveries through COVID-19 pandemic scenario embracing from biomedical to economic viewpoints.

Objectives We aimed to assess the effect of metabolic syndrome (MetS) on incident oral potentially malignant disorder (OPMD).Design We conducted a prospective cohort study of the Changhua community-based integrated screening (CHCIS) programme and nationwide oral cancer screening programme during the period between 2005 and 2014.Setting CHCIS, Taiwan.Participants We enrolled 17 590 participants aged 30 years and older.Main outcomes and measures We assessed the impact of MetS on the outcome measured by incident OPMD.Results The incidences of OPMD among subjects with and without MetS were 7.68 ‰ and 5.38 ‰, respectively. After adjusting for confounders, subjects with MetS exhibited a statistically greater risk of developing OPMD compared with those who were free of MetS by 33% (adjusted rate ratio, aRR=1.33, 95% CI 1.14 to 1.55). Individual components of MetS still remained significant, including central obesity (aRR=1.22, 95% CI 1.04 to 1.44), hypertriglyceridaemia (aRR=1.26, 95% CI 1.07 to 1.49) and hyperglycaemia (aRR=1.20, 95% CI 1.02 to 1.41). Central obesity and hypertriglyceridaemia were also statistically associated with a subtype of OPMD, namely, leukoplakia.Conclusion The temporal influence of MetS on the risk of incident OPMD was noted in our prospective cohort study. Therefore, promoting an MetS prevention and control programme might reduce the occurrence of OPMD and oral cancer.

Background. Emergency department (ED) crowding and prolonged lengths of stay continue to be important medical issues. It is difficult to apply traditional methods to analyze multiple streams of the ED patient management process simultaneously. The aim of this study was to develop a statistical model to delineate the dynamic patient flow within the ED and to analyze the effects of relevant factors on different patient movement rates. Methods. This study used a retrospective cohort available with electronic medical data. Important time points and relevant covariates of all patients between January and December 2013 were collected. A new five-state Markov model was constructed by an expert panel, including three intermediate states: triage, physician management, and observation room and two final states: admission and discharge. A day was further divided into four six-hour periods to evaluate dynamics of patient movement over time. Results. A total of 149,468 patient records were analyzed with a median total length of stay being 2.12 (interquartile range = 6.51) hours. The patient movement rates between states were estimated, and the effects of the age group and triage level on these movements were also measured. Patients with lower acuity go home more quickly (relative rate (RR): 1.891, 95% CI: 1.881–1.900) but have to wait longer for physicians (RR: 0.962, 95% CI: 0.956–0.967) and admission beds (RR: 0.673, 95% CI: 0.666–0.679). While older patients were seen more quickly by physicians (RR: 1.134, 95% CI: 1.131–1.139), they spent more time waiting for the final state (for admission RR: 0.830, 95% CI: 0.821–0.839; for discharge RR: 0.773, 95% CI: 0.769–0.776). Comparing the differences in patient movement rates over a 24-hour day revealed that patients wait longer before seen by physicians during the evening and that they usually move from the ED to admission afternoon. Predictive dynamic illustrations show that six hours after the patients’ entry, the probability of still in the ED system ranges from 28% in the evening to 38% in the morning. Conclusions. The five-state model well described the dynamic ED patient flow and analyzed the effects of relevant influential factors at different states. The model can be used in similar medical settings or incorporate different important covariates to develop individually tailored approaches for the improvement of efficiency within the health professions.

Abstract Background To develop an individually-tailored dynamic risk assessment model following a multistep, multifactorial process of the Correa’s gastric cancer model. Methods First, we estimated the state-to-state transition rates following Correa’s five-step carcinogenic model and assessed the effect of risk factors, including Helicobacter pylori infection, history of upper gastrointestinal disease, lifestyle, and dietary habits, on the step-by-step transition rates using data from a high-risk population in Matsu Islands, Taiwan. Second, we incorporated information on the gastric cancer carcinogenesis affected by genomic risk factors (including inherited susceptibility and irreversible genomic changes) based on literature to generate a genetic and epigenetic risk assessment model by using a simulated cohort identical to the Matsu population. The combination of conventional and genomic risk factors enables us to develop the personalized transition risk scores and composite scores. Results The state-by-state transition rates per year were 0.0053, 0.7523, 0.1750, and 0.0121 per year from normal mucosa to chronic active gastritis, chronic active gastritis to atrophic gastritis, atrophic gastritis to intestinal metaplasia, and intestinal metaplasia to gastric cancer, respectively. Compared with the median risk group, the most risky decile had a 5.22-fold risk of developing gastric cancer, and the least risky decile around one-twelfth of the risk. The median 10-year risk for gastric cancer incidence was 0.77%. The median lifetime risk for gastric cancer incidence was 5.43%. By decile, the 10-year risk ranged from 0.06 to 4.04% and the lifetime risk ranged from 0.42 to 21.04%. Conclusions We demonstrate how to develop a personalized dynamic risk assessment model with the underpinning of Correa’s cascade to stratify the population according to their risk for progression to gastric cancer. Such a risk assessment model not only facilitates the development of an individually-tailored preventive strategy with treatment for H. pylori infection and endoscopic screening but also provides short-term and long-term indicators to evaluate the program effectiveness.

Abstract Background Previous studies have found that polymorphisms of the DNA repair gene X-ray repair cross-complementing group 1(XRCC1) and environmental factors are both associated with an increased risk of stomach cancer, but no study has reported on the potential additive effect of these factors among Thai people. The aim of this study was to investigate whether the risk of stomach cancer from XRCC1 gene polymorphisms was modified by environmental factors in the Thai population. Methods Hospital-based matched case-control study data were collected from 101 new stomach cancer cases and 202 controls, which were recruited from2002 to 2006 and were matched for gender and age. Genotype analysis was performed using real-time PCR-HRM. The data were analysed by the chi-square test and conditional logistic regression. Results The Arg/Arg homozygote polymorphism of the XRCC1 gene was associated with an increased risk of stomach cancer in the Thai population (OR adj, 3.7; 95%CI, 1.30–10.72) compared with Gln/Gln homozygosity. The effect of the XRCC1gene on the risk of stomach cancer was modified by both a high intake of vegetable oils and salt (p = 0.036 and p = 0.014), particularly for the Arg/Arg homozygous genotype. There were, however, no additive effects on the risk of stomach cancer between variants of the XRCC1gene and smoking,alcohol or pork oil consumption. Conclusions The effect of the XRCC1 gene homozygosity, particularly Arg/Arg, on the risk for stomach cancer was elevated by a high intake of vegetable oils and salt.

Background: The risk factors responsible for breast cancer have been well documented, but the roles of risk factors as initiators, causing the occurrence of screen-detected breast cancer, or promoters, responsible for the progression of the screen-detected to the clinically-detected breast cancer, have been scarcely evaluated. Methods: We used data from women in a cohort in Kopparberg (Dalarna), Sweden between 1977 and 2010. Conventional risk factors, breast density, and tumor-specific biomarkers are superimposed to the temporal course of the natural history of the disease. Results: The results show that older age at first full-term pregnancy, dense breast, and a family history of breast cancer increased the risk of entering the preclinical screen-detectable phase of breast cancer by 23%, 41%, and 89%, respectively. Overweight/obesity (body mass index ≥25 kg/m2) was a significant initiator (adjusted relative risk [aRR] 1.15; 95% confidence interval [CI], 0.99–1.33), but was inversely associated with the role of promoter (aRR 0.65; 95% CI, 0.51–0.82). Dense breast (aRR 1.46; 95% CI, 1.12–1.91), triple-negative (aRR 2.07; 95% CI, 1.37–3.15), and Ki-67 positivity (aRR 1.66; 95% CI, 1.19–2.30) were statistically significant promoters. When the molecular biomarkers were considered collectively as one classification, the basal-like subtype was the most influential subtype on promoters (aRR 4.24; 95% CI, 2.56–7.02) compared with the Luminal A subtype. Discussion: We ascertained state-dependent covariates of initiators and promoters to classify the risk of the two-step progression of breast cancer. The results of the current study are useful for individuallytailored screening and personalized clinical surveillance of patients with breast cancer that was detected at an early stage.

BACKGROUND:Emergency department (ED) crowding continues to be an important health care issue in modern countries. Among the many crucial quality indicators for monitoring the throughput process, a patient's length of stay (LOS) is considered the most important one since it is both the cause and the result of ED crowding. The aim of this study is to identify and quantify the influence of different patient-related or diagnostic activities-related factors on the ED LOS of discharged patients. METHODS:This is a retrospective electronic data analysis. All patients who were discharged from the ED of a tertiary teaching hospital in 2013 were included. A multivariate accelerated failure time model was used to analyze the influence of the collected covariates on patient LOS. RESULTS:A total of 106,206 patients were included for analysis with an overall medium ED LOS of 1.46 (interquartile range = 2.03) hours. Among them, 96% were discharged by a physician, 3.5% discharged against medical advice, 0.5% left without notice, and only 0.02% left without being seen by a physician. In the multivariate analysis, increased age (>80 vs

Introduction A screening program provides a teachable moment for primary prevention such as encouraging smoking cessation. However, little is known about the efficacy of smoking cessation intervention delivered to the general population through a community-based screening program. Material and Methods A quasi-experimental untreated control design with pre-test and post-test was conducted with 42 subjects receiving advice from physician and nurses (the PNA group), 39 receiving an informational leaflet (the leaflet group), and 308 control subjects. Results The overall rate of reaching the action stage was 25 %, 5.7 %, and 7.8 in the PNA group, the leaflet group, and the control group, respectively. In approximately 45–60 % of all participants, the stage remained unchanged. Such an association between the intervention groups and stage changes was statistically significant (p = 0.02). The PNA group was more likely to have the improvement of stage (forward transition toward action stage) than the control group [adjusted odds ratio (aOR) = 2.27 (1.07–4.84)]. Deterioration (backward transition toward precontemplation) in the PNA intervention group was 37 % lower than that in the control group [aOR = 0.63 (0.20–2.01)]. Conclusions This study demonstrated that smoking cessation advice from physician and nurse is conducive to smoking cessation, as shown by greater movement toward and less movement away from smoking cessation through a community-based integrated screening platform.

BACKGROUND:Outreach (i.e., to invite those who do not use, or who under use screening services) and inreach (i.e., to invite an existing population who have already accessed the medical system) approaches may influence people to increase their use of screening test; however, whether their outcomes would be equivalent remains unclear. METHODS:A total of 3,363,896 subjects, 50-69 years of age, participated in a colorectal cancer (CRC) screening program using biennial fecal immunochemical tests; 34.5% participated during 2004-2009 when the outreach approach alone was used, and 65.5% participated from 2010-2013 when outreach was integrated with an inreach approach. We compared the outcomes of the two approaches in delivery of screening services. RESULTS:Coverage rates increased from 21.4% to 36.9% and the positivity rate increased from 4.0% to 7.9%, while referral for confirmatory diagnostic examinations declined from 80.0% to 53.3%. The first period detected CRC in 0.20% of subjects screened, with a positive predictive value (PPV) of 6.1%, and the second detected CRC in 0.34% of subjects, with a PPV of 8.0%. After adjusting for confounders, differences were observed in the PPV for CRC (adjusted relative risk, 1.50; 95% confidence interval [CI], 1.41-1.60), cancer detection rate (1.20; 95% CI, 1.13-1.27), and interval cancer rate (0.72; 95% CI, 0.65-0.80). When we focused on the comparison between two approaches during the same study period of 2010-2013, the positivity rate of fecal testing (8.2% vs. 7.6%) and the PPV for CRC detection remained higher (1.07; 95% CI, 1.01-1.12) in subjects who were recruited from the inreach approach. CONCLUSIONS:Outcomes of screening were equivalent or better after integration of outreach and inreach approaches. IMPACT:The results will encourage makers of health-care policy to adopt the integration approach to deliver screening services.