COVID Border Accountability Project, a hand-coded global database of border closures introduced during 2020.

Quantifying the timing and content of policy changes affecting international travel and immigration is key to ongoing research on the spread of SARS-CoV-2 and the socioeconomic impacts of border closures. The COVID Border Accountability Project (COBAP) provides a hand-coded dataset of >1000 policies systematized to reflect a complete timeline of country-level restrictions on movement across international borders during 2020. Trained research assistants used pre-set definitions to source, categorize and verify for each new border policy: start and end dates, whether the closure is "complete" or "partial", which exceptions are made, which countries are banned, and which air/land/sea borders were closed. COBAP verified the database through internal and external audits from public health experts. For purposes of further verification and future data mining efforts of pandemic research, the full text of each policy was archived. The structure of the COBAP dataset is designed for use by social and biomedical scientists. For broad accessibility to policymakers and the public, our website depicts the data in an interactive, user-friendly, time-based map.

Analysis of the relationship between psoriasis symptom severity and quality of life, work productivity, and activity impairment among patients with moderate-to-severe psoriasis using structural equation modeling.

BACKGROUND: Plaque psoriasis is a chronic disease characterized by scaly plaques on the skin that can itch and bleed. Psoriasis covering over 10% of the body is classified as moderate to severe, and can impact patient quality of life. OBJECTIVES: To assess the relationship between plaque psoriasis self-reported severity symptoms and health-related quality of life, work productivity, and activity impairment among patients with moderate-to-severe psoriasis. METHODS: The study sample included 199 patients recruited from internet panels, of which 179 respondents had plaque psoriasis and 20 had plaque and inverse psoriasis. Itching, pain, and scaling symptoms were studied. A structural equation modeling framework was used to estimate the effect of these symptoms on patient outcomes. First, each severity variable was regressed on a set of covariates to generate a predicted severity score. These predicted values were placed in a second-stage model with patient mental and physical scores (Short-Form 12 questionnaire), work productivity, and activity impairment indicators as dependent variables. RESULTS: Itching severity had a marginal negative effect (P < 0.06) on patients' Short-Form 12 physical and mental component scores. Pain severity also negatively affected physical and mental health scores (P < 0.02). Patients were more likely to miss work because of itching (odds ratio [OR]: 2.31, 95% confidence interval [CI]: 1.30, 4.10), pain (OR: 1.78, 95% CI: 1.25, 2.52), and scaling (OR: 2.15, 95% CI: 1.31, 3.52) symptoms. These symptoms also lowered self-reported productivity. As itching (OR: 1.74, 95% CI: 1.03, 2.95), scaling (OR: 1.84, 95% CI: 1.16, 2.90), and pain symptoms (OR: 1.53, 95% CI: 1.12, 2.09) increased, so did the odds that a patient would be less productive at work. CONCLUSION: Plaque psoriasis significantly affects patient quality of life. In addition to greater mental and physical pain, patients are more likely to miss work and have diminished productivity as symptom severity increases.

Applied Comparison of Meta-analysis Techniques.

Background: Meta-analysis is an approach that combines findings from similar studies. The aggregation of study level data can provide precise estimates for outcomes of interest, allow for unique treatment comparisons, and explain the differences arising from conflicting study results. Proper meta-analysis includes five basic steps: identify relevant studies; extract summary data from each paper; compute study effect sizes, perform statistical analysis; and interpret and report the results. Objectives: This study aims to review meta-analysis methods and their assumptions, apply various meta-techniques to empirical data, and compare the results from each method. Methods: Three different meta-analysis techniques were applied to a dataset looking at the effects of the bacille Calmette-Guerin (BCG) vaccine on tuberculosis (TB). First, a fixed-effects model was applied; then a random-effects model; and third meta-regression with study-level covariates were added to the model. Overall and stratified results, by geographic latitude were reported. Results: All three techniques showed a statistically significant effects from the vaccination. However, once covariates were added, efficacy diminished. Independent variables, such as the latitude of the location in which the study was performed, appeared to be partially driving the results. Conclusions: Meta-analysis is useful for drawing general conclusions from a variety of studies. However, proper study and model selection are important to ensure the correct interpretation of results. Basic meta-analysis models are fixed-effects, random-effects, and meta-regression.