Influence of anti-coronavirus disease 2019 policies on 10 pediatric infectious diseases.

BACKGROUND: To combat the coronavirus disease 2019 pandemic, many countries, including Japan, implemented policies limiting social activities and encouraging preventive behaviors. This study examines the influence of such policies on the trends of 10 infectious pediatric diseases: pharyngoconjunctival fever; group A streptococcal pharyngitis; infectious gastroenteritis; chickenpox; erythema infectiosum; hand, foot, and mouth disease; herpangina; respiratory syncytial virus; exanthem subitum; and mumps. METHODS: The research adopted a retrospective cohort study design. We collected data from Japan's National Epidemiological Surveillance Program detailing the incidences of the 10 diseases per pediatric sentinel site for a period beginning at 9 weeks before government-ordered school closures and ending at 9 weeks after the end of the state of emergency. We obtained corresponding data for the equivalent weeks in 2015-2019. We estimated the influence of the policies using a difference-in-differences regression model. RESULTS: For seven diseases (pharyngoconjunctival fever; group A streptococcal pharyngitis; infectious gastroenteritis; chickenpox; erythema infectiosum; hand, foot, and mouth disease; and herpangina), the incidence in 2020 decreased significantly during and after the school closures. Sensitivity analysis, in which the focus area was limited to the policy-implementation period or existing trend patterns, replicated these significant decreases for one of the above mentioned seven diseases - infectious gastroenteritis. CONCLUSIONS: Policies such as school closures and encouragement of preventive behaviors were associated with significant decreases in the incidences of most of the 10 diseases, which sensitivity analysis replicated in infectious gastroenteritis. To determine the long-term effects of these policies, prospective cohort studies are needed.

Development and Initial Psychometric Validation of the COVID-19 Pandemic Burden Index for Healthcare Workers.

BACKGROUND: The burden of COVID-19 on healthcare workers (HCWs) is reported to be increasing, yet the psychometric scales now in use evaluate only single aspects; few measure the pandemic-specific burden on HCWs comprehensively. OBJECTIVE: To develop a scale to quantify the physical, mental, and socioeconomic burden of the COVID-19 pandemic on HCWs. DESIGN: Scale development and cross-sectional survey. PARTICIPANTS: Consenting HCWs aged ≥20. MAIN MEASURES: Development of an item-list based on literature reviews and HCW panel input, evaluation of content validity and item selection using the Delphi method, psychometric testing conducted on HCWs, validity assessment by factor analyses and hypothesis verification, internal consistency evaluation by Cronbach's alpha, test-retest analysis, and interpretability assessment. KEY RESULTS: Through the Delphi process, a 29-item pilot scale was generated. In psychometric testing, data from 863 HCWs contributed to the development of the final version of this scale, called Pandemic Burden Index twenty for HCWs (PBI-20), a 20-item scale to measure six domains: fatigue, fear of infection, inadequacy as a medical professional, mental health concerns, prejudice or discrimination, and anxiety about one's livelihood and daily life. Factor analysis showed each factor corresponded to the six domains of this scale. Hypothesis verification showed the PBI-20 total score to be moderately to highly correlated with the Short Form 36 vitality score and mental health score and with intention of turnover. The PBI-20 had good internal consistency (Cronbach's alpha 0.92). Test-retest analysis showed the intraclass correlation coefficient to be 0.70 and the minimal important change to be -7.0. CONCLUSIONS: The psychometrically sound questionnaire we developed to measure pandemic-specific burdens for HCWs provides an understanding of comprehensive burdens on HCWs and may serve to evaluate interventions to reduce the burdens.

The Fragility of Statistically Significant Results in Randomized Clinical Trials for COVID-19.

Importance: Interpreting results from randomized clinical trials (RCTs) for COVID-19, which have been published rapidly and in vast numbers, is challenging during a pandemic. Objective: To evaluate the robustness of statistically significant findings from RCTs for COVID-19 using the fragility index. Design, Setting, and Participants: This cross-sectional study included COVID-19 trial articles that randomly assigned patients 1:1 into 2 parallel groups and reported at least 1 binary outcome as significant in the abstract. A systematic search was conducted using PubMed to identify RCTs on COVID-19 published until August 7, 2021. Exposures: Trial characteristics, such as type of intervention (treatment drug, vaccine, or others), number of outcome events, and sample size. Main Outcomes and Measures: Fragility index. Results: Of the 47 RCTs for COVID-19 included, 36 (77%) were studies of the effects of treatment drugs, 5 (11%) were studies of vaccines, and 6 (13%) were of other interventions. A total of 138 235 participants were included in these trials. The median (IQR) fragility index of the included trials was 4 (1-11). The medians (IQRs) of the fragility indexes of RCTs of treatment drugs, vaccines, and other interventions were 2.5 (1-6), 119 (61-139), and 4.5 (1-18), respectively. The fragility index among more than half of the studies was less than 1% of each sample size, although the fragility index as a proportion of events needing to change would be much higher. Conclusions and Relevance: This cross-sectional study found a relatively small number of events (a median of 4) would be required to change the results of COVID-19 RCTs from statistically significant to not significant. These findings suggest that health care professionals and policy makers should not rely heavily on individual results of RCTs for COVID-19.