Population-Based Evaluation of Vaccine Effectiveness against SARS-CoV-2 Infection, Severe Illness, and Death, Taiwan.

Taiwan provided several COVID-19 vaccine platforms: mRNA (BNT162b2, mRNA-1273), adenoviral vector-based (AZD1222), and protein subunit (MVC-COV1901). After Taiwan shifted from its zero-COVID strategy in April 2022, population-based evaluation of vaccine effectiveness (VE) became possible. We conducted an observational cohort study of 21,416,151 persons to examine VE against SARS-CoV-2 infection, moderate and severe illness, and death during March 22, 2021-September 30, 2022. After adjusting for age and sex, we found that persons who completed 3 vaccine doses (2 primary, 1 booster) or received MVC-COV1901 as the primary series had the lowest hospitalization incidence (0.04-0.20 cases/100,000 person-days). We also found 95.8% VE against hospitalization for 3 doses of BNT162b2, 91.0% for MVC-COV1901, 81.8% for mRNA-1273, and 65.7% for AZD1222, which had the lowest overall VE. Our findings indicated that protein subunit vaccines provide similar protection against SARS-CoV-2---associated hospitalization as mRNA vaccines and can inform mix-and-match vaccine selection in other countries.

Factors Influencing the Effectiveness of Adopting Electronic Medical Record-Based Reporting Systems for Notifiable Disease Surveillance: A Quantitative Analysis.

The coronavirus disease 2019 (COVID-19) pandemic has led to greater attention being given to infectious disease surveillance systems and their notification functionalities. Although numerous studies have explored the benefits of integrating functionalities with electronic medical record (EMR) systems, empirical studies on the topic are rare. The current study assessed which factors influence the effectiveness of EMR-based reporting systems (EMR-RSs) for notifiable disease surveillance. This study interviewed staff from hospitals with a coverage that represented 51.39% of the notifiable disease reporting volume in Taiwan. Exact logistic regression was employed to determine which factors influenced the effectiveness of Taiwan's EMR-RS. The results revealed that the influential factors included hospitals' early participation in the EMR-RS project, frequent consultation with the information technology (IT) provider of the Taiwan Centers for Disease Control (TWCDC), and retrieval of data from at least one internal database. They also revealed that using an EMR-RS resulted in more timely, accurate, and convenient reporting in hospitals. In addition, developing by an internal IT unit instead of outsourcing EMR-RS development led to more accurate and convenient reporting. Automatically loading the required data enhanced the convenience, and designing input fields that may be unavailable in current databases to enable physicians to add data to legacy databases also boosted effectiveness of the reporting system.

Applying Machine Learning Models with An Ensemble Approach for Accurate Real-Time Influenza Forecasting in Taiwan: Development and Validation Study.

BACKGROUND: Changeful seasonal influenza activity in subtropical areas such as Taiwan causes problems in epidemic preparedness. The Taiwan Centers for Disease Control has maintained real-time national influenza surveillance systems since 2004. Except for timely monitoring, epidemic forecasting using the national influenza surveillance data can provide pivotal information for public health response. OBJECTIVE: We aimed to develop predictive models using machine learning to provide real-time influenza-like illness forecasts. METHODS: Using surveillance data of influenza-like illness visits from emergency departments (from the Real-Time Outbreak and Disease Surveillance System), outpatient departments (from the National Health Insurance database), and the records of patients with severe influenza with complications (from the National Notifiable Disease Surveillance System), we developed 4 machine learning models (autoregressive integrated moving average, random forest, support vector regression, and extreme gradient boosting) to produce weekly influenza-like illness predictions for a given week and 3 subsequent weeks. We established a framework of the machine learning models and used an ensemble approach called stacking to integrate these predictions. We trained the models using historical data from 2008-2014. We evaluated their predictive ability during 2015-2017 for each of the 4-week time periods using Pearson correlation, mean absolute percentage error (MAPE), and hit rate of trend prediction. A dashboard website was built to visualize the forecasts, and the results of real-world implementation of this forecasting framework in 2018 were evaluated using the same metrics. RESULTS: All models could accurately predict the timing and magnitudes of the seasonal peaks in the then-current week (nowcast) (ρ=0.802-0.965; MAPE: 5.2%-9.2%; hit rate: 0.577-0.756), 1-week (ρ=0.803-0.918; MAPE: 8.3%-11.8%; hit rate: 0.643-0.747), 2-week (ρ=0.783-0.867; MAPE: 10.1%-15.3%; hit rate: 0.669-0.734), and 3-week forecasts (ρ=0.676-0.801; MAPE: 12.0%-18.9%; hit rate: 0.643-0.786), especially the ensemble model. In real-world implementation in 2018, the forecasting performance was still accurate in nowcasts (ρ=0.875-0.969; MAPE: 5.3%-8.0%; hit rate: 0.582-0.782) and remained satisfactory in 3-week forecasts (ρ=0.721-0.908; MAPE: 7.6%-13.5%; hit rate: 0.596-0.904). CONCLUSIONS: This machine learning and ensemble approach can make accurate, real-time influenza-like illness forecasts for a 4-week period, and thus, facilitate decision making.

Region-wide synchrony and traveling waves of dengue across eight countries in Southeast Asia.

Dengue is a mosquito-transmitted virus infection that causes epidemics of febrile illness and hemorrhagic fever across the tropics and subtropics worldwide. Annual epidemics are commonly observed, but there is substantial spatiotemporal heterogeneity in intensity. A better understanding of this heterogeneity in dengue transmission could lead to improved epidemic prediction and disease control. Time series decomposition methods enable the isolation and study of temporal epidemic dynamics with a specific periodicity (e.g., annual cycles related to climatic drivers and multiannual cycles caused by dynamics in population immunity). We collected and analyzed up to 18 y of monthly dengue surveillance reports on a total of 3.5 million reported dengue cases from 273 provinces in eight countries in Southeast Asia, covering ∼ 10(7) km(2). We detected strong patterns of synchronous dengue transmission across the entire region, most markedly during a period of high incidence in 1997-1998, which was followed by a period of extremely low incidence in 2001-2002. This synchrony in dengue incidence coincided with elevated temperatures throughout the region in 1997-1998 and the strongest El Niño episode of the century. Multiannual dengue cycles (2-5 y) were highly coherent with the Oceanic Niño Index, and synchrony of these cycles increased with temperature. We also detected localized traveling waves of multiannual dengue epidemic cycles in Thailand, Laos, and the Philippines that were dependent on temperature. This study reveals forcing mechanisms that drive synchronization of dengue epidemics on a continental scale across Southeast Asia.

Oseltamivir use and outcomes during the 2009 influenza A H1N1 pandemic in Taiwan.

BACKGROUND: The Taiwan CDC provided free oseltamivir to all patients with influenza infections confirmed by rapid testing or who had clinical warning symptoms during the 2009 H1N1 influenza pandemic in Taiwan. However, oseltamivir utilization patterns, cost, and outcomes among oseltamivir-treated patients remained unclear. METHOD: A population-level, observational cohort study was conducted using the Taiwan National Health Insurance Database from January to December 2009 to describe the use of oseltamivir. RESULT: Prescription trend over weeks increased after a change in government policy and responded to the influenza virus activity. The overall prescription rate was 22.33 per 1000 persons, with the highest prescription rate of 116.5 for those aged 7-12 years, followed by 69.0 for those aged 13-18 years, while the lowest rate was 1.7 for those aged ≥ 65 years. As influenza virus activity increased, the number of prescriptions for those aged ≤18 years rose significantly, whereas no substantial change was observed for those aged ≥65 years. There were also regional variations in terms of oseltamivir utilization and influenza complication rates. CONCLUSIONS: Oseltamivir was widely used in the 2009 H1N1 influenza pandemic in Taiwan, particularly in those aged 7-18 years. The number of prescriptions for oseltamivir increased with a change in government policy and with increasing cases of pandemic influenza. Further study is needed to examine whether there is an over- or under-use of anti-influenza drugs in different age groups or regions and to examine the current policy of public use of anti-influenza drugs to reduce influenza-associated morbidity and mortality.

Influenza vaccination is associated with a reduced risk of invasive aspergillosis in high-risk individuals in Taiwan: a population-based cohort study.

Invasive aspergillosis (IA) has become the emerging life-threatening disease in recent years. Influenza has been identified as an independent risk factor for IA. Vaccination is the most effective way to prevent influenza, while whether it can reduce IA in high-risk population still uncertain. We aimed to investigate the association between influenza vaccination and the risk of IA in high-risk population. We performed a population-based cohort study of people who qualified for government-funded influenza vaccination and were at high risk for IA at the start of the influenza season each year between 2016 and 2019. We utilized Taiwan's National Health Insurance Research Database to identify the influenza vaccination status and IA diagnosis during the follow-up period. We compared the risk of IA between people with and without vaccination using multivariable logistic regression analysis. Out of total 8,544,451 people who were eligible during the 3 influenza seasons, 3,136,477 (36.7%) were vaccinated. A total of 1179 IA cases with the incidence of 13.8 cases per 100,000 high-risk individuals were identified during the follow-up. Compared to non-vaccinated group, vaccinated individuals had a 21% risk reduction of IA (adjusted odds ratio 0.79, 95% confidence interval 0.70-0.90). Influenza vaccination was associated with a lower risk of IA among males, immunosuppressive conditions, malignancy, diabetes, and those having host factors according to the European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium. Influenza vaccination is recommended for high-risk population to reduce the risk of IA.

Acute reactions after a homologous primary COVID-19 vaccination series: Analysis of Taiwan V-Watch data.

INTRODUCTION: The ChAdOx1 nCoV-19 (ChAd), mRNA-1273 (m1273), MVC-COV1901 (MVC), and BNT162b2 (BNT) COVID-19 vaccines received authorization for emergency use in Taiwan beginning in February 2021. We investigated acute reactions to homologous primary COVID-19 vaccination series in adults aged ≥ 18 years. METHODS: In this prospective observational study based on smartphone data (Taiwan V-Watch), we calculated the frequencies of self-reported local and systemic acute reactions within 7 days of a COVID-19 vaccination, and the health effects up to 3 weeks after each dose. Those who reported adverse reactions after both doses were assessed by the McNemar test. RESULTS: During 22 March 2021-13 December 2021, 77,468 adults were enrolled; 59.0 % were female and 77.8 % were aged 18-49 years. For both doses of all four vaccines, the local and systemic reactions were minor in severity and highest on days 1 and 2 after vaccination, and declined markedly until day 7. For 65,367 participants who provided data after the first and second doses, systemic reactions were more frequent after dose 2 of the BNT and m1273 vaccines (McNemar tests: both p < 0.001), while local reactions were more frequent after dose 2 of the m1273 and MVC vaccines (both p < 0.001), compared with dose 1 of the homologous vaccine. Among the participants aged 18-49 years, the percentage who missed work on the day after vaccination was slightly higher among women (9.3 %) than among men (7.0 %). CONCLUSIONS: Acute reactogenicity and impact of work absenteeism for the four COVID vaccines in the V-Watch survey were mild and of short duration.

Risk of myocarditis and pericarditis following coronavirus disease 2019 messenger RNA Vaccination-A nationwide study.

BACKGROUND: An extended interval between the two primary doses may reduce the risk of myocarditis/pericarditis after COVID-19 mRNA vaccination. Taiwan has implemented a two-dose regimen with a 12-week interval for adolescents. Here we present nationwide data of myocarditis/pericarditis following COVID-19 vaccinations. METHODS: Data on adverse events of myocarditis/pericarditis were from the Taiwan Vaccine Adverse Events Reporting System between March 22, 2021, and February 9, 2022. The reporting rates according to sex, age, and vaccine type were calculated. We investigated the rates among young individuals under different two-dose intervals and among those who received two doses of different vaccines. RESULTS: Among 204 cases who met the case definition of myocarditis/pericarditis, 75 cases occurred after the first dose and 129 after the second. The rate of myocarditis/pericarditis after COVID-19 vaccination varied across sex and age groups and was highest after the second dose in males aged 12-17 years (126.79 cases per million vaccinees) for the BNT162b2 vaccine and in males aged 18-24 years (93.84 cases per million vaccinees) for the mRNA-1273 vaccine. The data did not suggest an association between longer between-dose interval and lower rate of myocarditis/pericarditis among males and females aged 18-24 or 25-29 years who received two doses of the BNT162b2 or mRNA-1273 vaccine. Rates of myocarditis/pericarditis in males and females aged 18-49 years after receiving ChAdOx1-S - mRNA-1273 vaccination was significantly higher than after ChAdOx1-S - ChAdOx1-S vaccination. CONCLUSIONS: Myocarditis and pericarditis are rare following mRNA vaccination, with higher risk occurring in young males after the second dose.

Completeness and timeliness of tuberculosis notification in Taiwan.

UNLABELLED: Tuberculosis (TB) is a notifiable disease by the Communicable Disease Control Law in Taiwan. Several measures have been undertaken to improve reporting of TB but the completeness and timeliness of TB notification in Taiwan has not yet been systemically evaluated. METHODS: To assess completeness and timeliness of TB notification, potential TB cases diagnosed by health care facilities in the year 2005-2007 were identified using the reimbursement database of national health insurance (NHI), which has 99% population coverage in Taiwan. Potential TB patients required notification were defined as those who have TB-related ICD-9 codes (010-018) in the NHI reimbursement database in 2005-2007, who were not diagnosed with TB in previous year, and who have been prescribed with 2 or more types of anti-TB drugs. Each potential TB case was matched to the national TB registry maintained at Taiwan Centers for Disease Control (CDC) by using national identity number or, if non-citizen, passport number to determine whether the patients had been notified to local public health authorities and Taiwan CDC. The difference in the number of days between date of anti-tuberculosis treatment and date of notification was calculated to determine the timeliness of TB reporting. RESULTS: Of the 57,405 TB patients who were prescribed with 2 or more anti-tuberculosis drugs, 55,291 (96.3%) were notified to National TB Registry and 2,114 (3.7%) were not. Of the 55,291 notified cases, 45,250 (81.8%) were notified within 7 days of anti-tuberculosis treatment (timely reporting) and 10,041(18.2%) after 7 days (delayed reporting). Factors significantly associated with failure of notification are younger age, previously notified cases, foreigner, those who visited clinics and those who visited health care facilities only once or twice in 6 months. CONCLUSION: A small proportion of TB cases were not notified and a substantial proportion of notified TB cases had delayed reporting, findings with implication for strengthening surveillance of tuberculosis in Taiwan. Countries where the completeness and timeliness of TB notification has not yet been evaluated should take similar action to strengthen surveillance of TB.

A dynamic estimation of the daily cumulative cases during infectious disease surveillance: application to dengue fever.

BACKGROUND: In infectious disease surveillance, when the laboratory confirmation of the cases is time-consuming, there is often a time lag between the number of suspect cases and the number of confirmed cases. This study proposes a dynamic statistical model to estimate the daily number of new cases and the daily cumulative number of infected cases, which was then applied to historic dengue fever data. METHODS: The duration between the date of disease onset and date of laboratory confirmation was assumed to follow a gamma distribution or a nonparametric distribution. A conditional probability of a case being a real case among the unconfirmed cases on a given date was then calculated. This probability along with the observed confirmed cases was integrated to estimate the daily number of new cases and the cumulative number of infected cases. RESULTS: The distribution of the onset-to-confirmation time for the positive cases was different from that of the negative cases. The daily new cases and cumulative epidemic curves estimated by the proposed method have a lower absolute relative bias than the values estimated solely based on the available daily-confirmed cases. CONCLUSION: The proposed method provides a more accurate real-time estimation of the daily new cases and daily cumulative number of infected cases. The model makes use of the most recent "moving window" of information relative to suspect cases and dynamically updates the parameters. The proposed method will be useful for the real-time evaluation of a disease outbreak when case classification requires a time-consuming laboratory process to identify a confirmed case.

Assessment of Expert-Level Automated Detection of Plasmodium falciparum in Digitized Thin Blood Smear Images.

Importance: Decades of effort have been devoted to establishing an automated microscopic diagnosis of malaria, but there are challenges in achieving expert-level performance in real-world clinical settings because publicly available annotated data for benchmark and validation are required. Objective: To assess an expert-level malaria detection algorithm using a publicly available benchmark image data set. Design, Setting, and Participants: In this diagnostic study, clinically validated malaria image data sets, the Taiwan Images for Malaria Eradication (TIME), were created by digitizing thin blood smears acquired from patients with malaria selected from the biobank of the Taiwan Centers for Disease Control from January 1, 2003, to December 31, 2018. These smear images were annotated by 4 clinical laboratory scientists who worked in medical centers in Taiwan and trained for malaria microscopic diagnosis at the national reference laboratory of the Taiwan Centers for Disease Control. With TIME, a convolutional neural network-based object detection algorithm was developed for identification of malaria-infected red blood cells. A diagnostic challenge using another independent data set within TIME was performed to compare the algorithm performance against that of human experts as clinical validation. Main Outcomes and Measures: Performance on detecting Plasmodium falciparum-infected blood cells was measured by average precision, and performance on detecting P falciparum infection at the image level was measured using sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Results: The TIME data sets contained 8145 images of 36 blood smears from patients with suspected malaria (30 P falciparum-positive and 6 P falciparum-negative smears) that had reliable annotations. For clinical validation, the average precision was 0.885 for detecting P falciparum-infected blood cells and 0.838 for ring form. For detecting P falciparum infection on blood smear images, the algorithm had expert-level performance (sensitivity, 0.995; specificity, 0.900; AUC, 0.997 [95% CI, 0.993-0.999]), especially in detecting ring form (sensitivity, 0.968; specificity, 0.960; AUC, 0.995 [95% CI, 0.990-0.998]) compared with experienced microscopists (mean sensitivity, 0.995 [95% CI, 0.993-0.998]; mean specificity, 0.955 [95% CI, 0.885-1.000]). Conclusions and Relevance: The findings suggest that a clinically validated expert-level malaria detection algorithm can be developed by using reliable data sets.

Spatiotemporal analysis of air pollution and asthma patient visits in Taipei, Taiwan.

BACKGROUND: Buffer analyses have shown that air pollution is associated with an increased incidence of asthma, but little is known about how air pollutants affect health outside a defined buffer. The aim of this study was to better understand how air pollutants affect asthma patient visits in a metropolitan area. The study used an integrated spatial and temporal approach that included the Kriging method and the Generalized Additive Model (GAM). RESULTS: We analyzed daily outpatient and emergency visit data from the Taiwan Bureau of National Health Insurance and air pollution data from the Taiwan Environmental Protection Administration during 2000-2002. In general, children (aged 0-15 years) had the highest number of total asthma visits. Seasonal changes of PM10, NO2, O3 and SO2 were evident. However, SO2 showed a positive correlation with the dew point (r = 0.17, p < 0.01) and temperature (r = 0.22, p < 0.01). Among the four pollutants studied, the elevation of NO2 concentration had the highest impact on asthma outpatient visits on the day that a 10% increase of concentration caused the asthma outpatient visit rate to increase by 0.30% (95% CI: 0.16%~0.45%) in the four pollutant model. For emergency visits, the elevation of PM10 concentration, which occurred two days before the visits, had the most significant influence on this type of patient visit with an increase of 0.14% (95% CI: 0.01%~0.28%) in the four pollutants model. The impact on the emergency visit rate was non-significant two days following exposure to the other three air pollutants. CONCLUSION: This preliminary study demonstrates the feasibility of an integrated spatial and temporal approach to assess the impact of air pollution on asthma patient visits. The results of this study provide a better understanding of the correlation of air pollution with asthma patient visits and demonstrate that NO2 and PM10 might have a positive impact on outpatient and emergency settings respectively. Future research is required to validate robust spatiotemporal patterns and trends.

The development of an incident event reporting system for nursing students.

Incident events may occur when nursing students are present in the clinical setting. Their inexperience and unfamiliarity with clinical practice put them at risk for making mistakes that could potentially harm patients and themselves. However, there are deficiencies with incident event reporting systems, including incomplete data and delayed reports. The purpose of this study was to develop an incident event reporting system for nursing students in clinical settings and evaluate its effectiveness. This study was undertaken in three phases. In the first phase, a literature review and focus groups were used to develop the architecture of the reporting system. In the second phase, the reporting system was implemented. Data from incident events that involved nursing students were collected for a 12-month period. In the third phase, a pre-post trial was undertaken to evaluate the performance of the reporting system. The ASP.NET software and Microsoft Access 2003 were used to create an interactive web-based interface and design a database for the reporting system. Email notifications alerted the nursing student's teacher when an incident event was reported. One year after installing the reporting system, the number of reported incident events increased tenfold. However, the time to report the incident event and the time required to complete the reporting procedures were shorter than before implementation of the reporting system. The incident event reporting system appeared to be effective in more comprehensively reporting the number of incident events and shorten the time required for reporting them compared to traditional written reports.

Balancing geo-privacy and spatial patterns in epidemiological studies.

To balance the protection of geo-privacy and the accuracy of spatial patterns, we developed a geo-spatial tool (GeoMasker) intended to mask the residential locations of patients or cases in a geographic information system (GIS). To elucidate the effects of geo-masking parameters, we applied 2010 dengue epidemic data from Taiwan testing the tool's performance in an empirical situation. The similarity of pre- and post-spatial patterns was measured by D statistics under a 95% confidence interval. In the empirical study, different magnitudes of anonymisation (estimated Kanonymity ≥10 and 100) were achieved and different degrees of agreement on the pre- and post-patterns were evaluated. The application is beneficial for public health workers and researchers when processing data with individuals' spatial information.

Toward Automatic Reporting of Infectious Diseases.

Accurate, complete, and timely disease surveillance data are vital for disease control. We report a national scale effort to automatically extract information from electronic medical records as well as electronic laboratory systems. The extracted information is then transferred to the centers of disease control after a proper confirmation process. The coverage rates of the automated reporting systems are over 50%. Not only is the workload of surveillance greatly reduced, but also reporting is completed in near real-time. From our experiences, a system sustainable strategy, well-defined working plan, and multifaceted team coordination work effectively. Knowledge management reduces the cost to maintain the system. Training courses with hands-on practice and reference documents are useful for LOINC adoption.

National Trend and Characteristics of Acute Hepatitis C among HIV-Infected Individuals: A Matched Case-Control Study-Taiwan, 2001-2014.

BACKGROUND: Hepatitis C virus (HCV) infection has been increasingly recognized among HIV-infected men who have sex with men (MSM) worldwide. We investigated the trend of and factors associated with acute hepatitis C (AHC) among HIV-infected individuals in Taiwan. METHODS: The National Disease Surveillance System collects characteristics of AHC, HIV, syphilis, and gonorrhea cases through mandatory reports and patient interviews. Reported AHC patients in 2014 were interviewed additionally on sexual and parenteral exposures. Information on HCV genotypes were collected from the largest medical center serving HIV-infected Taiwanese. We defined an HIV/AHC case as a documented negative HCV antibody test result followed within 12 months by a positive test in a previously reported HIV-infected individual. Each case was matched to two HIV-infected, non-AHC controls for age, age of HIV diagnosis, sex, transmission route, HIV diagnosis date, and county/city. Conditional logistic regression was used to identify associated characteristics. RESULTS: During 2001-2014, 93 of 6,624 AHC reports were HIV/AHC cases; the annual case count increased from one in 2009 to 34 in 2014. All were males (81 [87%] MSM) aged 21-49 years with AHC diagnosed 2-5,923 days after HIV diagnoses. Sixty-eight (73%) lived in the Taipei metropolitan area. Detected HCV genotypes were 2a (n = 6), 1b (n = 5), 1b + 2a (n = 1) and 2b (n = 1). Among 28 HIV/AHC patients interviewed in 2014, 13 (46%) reported engaging in unprotected sex ≤3 months before AHC diagnosis. Seventy-nine HIV/AHC cases were matched to 158 controls. HIV/AHC was associated with recent syphilis (adjusted odds ratio [aOR], 10.9; 95% confidence interval [CI], 4.2-28.6) and last syphilis >6 months (aOR, 2.9; 95% CI, 1.2-6.9). CONCLUSIONS: HIV/AHC cases continued to increase particularly among sexually active HIV-infected MSM with a syphilis diagnosis in northern Taiwan. We recommend surveillance of associated behavioral and virologic characteristics and HCV counseling and testing for HIV-infected men in Taiwan.