Background
A severe dengue epidemic occurred in 2015 which resulted in over 22,000 laboratory-confirmed cases. A cross-sectional seroprevalence study was conducted during the ending phase of this epidemic to evaluate the true incidence of dengue virus (DENV) infection and the level of herd immunity.
Methods
Adult residents in three administrative districts with high dengue incidence were recruited; workers in two districts with intermediate dengue incidence were also recruited for comparison. DENV-specific IgM and IgG were tested using commercial enzyme-linked immunosorbent assays. DENV RNA was detected using commercial quantitative real-time reverse transcriptase polymerase chain reaction assay. Univariate and multivariate logistic regressions were performed to identify risk factors for recent and past DENV infection.
Results
The overall seroprevalence of anti-DENV IgM and IgG in 1391 participants was 6.8 and 17.4%, respectively. The risk of recent DENV infection increased with age, with the elderly having the highest risk of infection. Living in areas with high incidence of reported dengue cases and having family members being diagnosed with dengue in 2015 were also independent risk factors for recent DENV infection. One sample was found to have asymptomatic viremia with viral load as high as 10
5
PFU/ml.
Conclusions
Comparing the seroprevalence of anti-DENV IgM with the incidence of reported dengue cases in 2015, we estimated that 1 out of 3.7 dengue infections were reported to the surveillance system; widespread use of rapid diagnostic tests might contribute to this high reporting rate. The results also indicate that the overall herd immunity remains low and the current approved Dengvaxia® is not quite suitable for vaccination in Taiwan.
BackgroundCharacteristics associated with acceptance of dataset linkages and health data linkage data quality were analyzed.MethodsParticipants from the 2011 Taiwan Longitudinal Study on Aging were asked to link their epidemiological data with concurrent and future medical claim datasets. Characteristics associated with acceptance of data linkage, data consistency, under-reporting, and over-reporting of disease conditions were identified.ResultsAmong the 3727 respondents, 3601 (96.6%) accepted data linkage. Middle-aged adults with worse functional health accepted data linkage. Older adults (65+) with better health behavior and social support were more likely to accept data linkage. Consistency between self-reports and medical data was very good to satisfactory (Kappa = 0.80 and 0.67, respectively, for diabetes and hypertension). Comorbidities were common risk factors resulting in inconsistency between self-reports and medical data (OR = 1.58 and 1.27, respectively, for diabetes and hypertension). Living alone was another risk factor resulting in inconsistency for diabetes. Male, older, and not living alone were other risk factors resulting in inconsistencies for hypertension. Under-reporting of illness was associated with poor health and older age. Over-reporting of illness was associated with better health and younger age.DiscussionThe findings suggest different adjustment methods for middle-aged versus older respondents when considering self-report data validity.
A Rayleigh surface acoustic wave (RSAW) resonator with Cu2+-PANI-SnO2 nanocomposite thin film is investigated as a gas sensor for detecting the presence of nitric oxide (NO) in air. The sensor developed in this work was sensitive to NO gas at room temperature. It is shown that the sensor had a frequency shift of 0.45 ppm when it was exposed to 12 ppb NO. This RSAW sensor also exhibited repeatability to the presence of NO gas. Especially, the presented sensor showed highly selectivity with NO gas to separate from NO2 and CO2 gases.
Background
This study analyzed the interactions between agencies, policies, and the interest of the public using a social network analysis.
Methods
Open data on the 2017 Facebook fan page of the Ministry of Health and Welfare (MoHW) in Taiwan, including 18,193 messages, were analyzed by conducting a social network analysis, NodeXL (Network Overview, Discovery and Exploration for Excel), creating visualized explorations using size volumes to present the degree of strength between agencies and policies to further calculate the network centrality indicators of agencies and policies.
Results
Agencies of the “Social and Family Affairs Administration” and “Health Promotion Administration” contributed the most policy posts. The policy of “Physical and mental health promotion” entailed the most agencies to be involved. The “Department of Nursing and Health Care” received the largest public response, for which “Long-term care” received the most public interest.
Conclusions
A social network analysis of fan page of Taiwan’s top level health government agency can reveal the government’s most emphasized core policies, the strength of correlations between agencies and policies, and provide an understanding of public interest toward the policies.
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