Impact of JIA on parents' work absences.

OBJECTIVE: Children with JIA have long-term morbidity and require extensive parental assistance. This study aimed to evaluate the impact of having a child with JIA on parents' missed work time, which can lead to decreased work productivity. METHODS: The Truven Health MarketScan Commercial Database (2000-9) was accessed to identify a cohort of parents having a child with newly diagnosed JIA. For comparison, a cohort of parents having no children with JIA was identified and matched with the preceding cohort. Parents' work absences were analysed using descriptive statistics and multivariable regression. Estimates were weighted to be generalizable to the US employer-sponsored insurance population. RESULTS: The study identified 108 parents having a child with newly diagnosed JIA (mean age 42.5 years), representing an estimated 3335 (weighted) parents nationally. Most of them were from the South (45%), male (71%) and employed in the transportation and utilities industry (58%). The demographic characteristics of the control cohort of parents were generally similar. Children with JIA (mean age 10.6 years) represented an estimated 3528 cases nationally. The mean number of reported missed work-time hours was 281.81 (s.e. 40.50) in a 9 year period for parents having a child with JIA compared with other parents 183.36 (28.55). Work-time loss was significantly related to having a child with JIA, sex and geographical region of residence. Parents having a child with JIA were 2.78 times more likely to report work-time loss [odds ratio (OR) 2.78 (95% CI 1.47, 5.26)] than those having no children with JIA. CONCLUSION: Parents having a child with JIA report significant work-time loss compared with parents with no children having JIA, particularly during the year following the child's diagnosis.

Epidemiology and Clinical Characteristics of Individuals with Hepatitis C Virus Infection in the United States, 2017-2019.

INTRODUCTION: Hepatitis C virus (HCV) is the most common bloodborne chronic infection in the US. Following approval of highly effective, direct-acting antivirals in 2014, the diagnostic and treatment rates for HCV infection in the US have evolved. This study assessed the number of individuals with HCV screening or diagnostic testing and the clinical characteristics and treatment of HCV-infected individuals between 2017 and 2019. METHODS: Individuals screened for HCV antibody and/or tested for HCV ribonucleic acid (RNA) from 2017 to 2019 by two large US laboratory companies were included in this analysis. Clinical characteristics, such as HCV genotype, fibrosis stage, HIV coinfection and demographics, were assessed in HCV RNA-positive individuals. HCV treatment and subsequent achievement of sustained virologic response were imputed using data-driven algorithms based on successive viral load decline and negativity. RESULTS: From 2017 to 2019, the number of individuals tested for HCV antibody increased by 5.7%, from 7,580,303 in 2017 to 8,009,081 in 2019. The percentage of individuals tested who were HCV antibody positive was stable, ranging from 5.0% in 2017 to 4.9% in 2018 and 2019. The number of HCV RNA-positive individuals decreased by 5.0% from 382,500 in 2017 to 363,532 in 2019. Of HCV RNA-positive individuals, the proportions with genotype (GT) 3 and minimal fibrosis increased over time; proportions of individuals aged < 40 years increased, while the proportion aged 50 to 59 years decreased. Treatment rates increased from 23.4% in 2017 to 26.8% in 2019. CONCLUSIONS: The percentage of HCV antibody-positive individuals remained stable from 2017 to 2019. The number of individuals tested HCV RNA positive decreased over the years. Demographics shifted toward a younger population with less fibrosis and higher rates of GT3. More than 70% of diagnosed individuals were not treated during this interval, highlighting a need for unfettered access to treatment.

Improving geocoding practices: evaluation of geocoding tools.

This study examined the sources of error involved in geocoding, by systematically evaluating the strengths and weaknesses of three widely used tools for geocoding. We tested them against a random sample of addresses from a state administrative address master file and found considerable variation in identification of census block geocodes of addresses. This high variation was mainly attributable to differences in preprocessing of addresses before geocoding and the reference street data used for geocoding. Preprocessing includes not only parsing and standardizing, but also correcting addresses against the US Postal Service Zip+4 Database, the master mailing address database maintained and updated regularly by USPS.