Reporting of Child Maltreatment During the COVID-19 Pandemic in a Southern State in the United States.

OBJECTIVES: COVID-19-related stay-at-home orders (SAHOs) created an immediate physical barrier between children and professionals such as pediatricians and teachers, who are often first to identify and report signs of child maltreatment. Our objective was to determine how the SAHO in a southern state was associated with reports of child maltreatment and whether this association was modified by sociodemographic characteristics. METHODS: We linked data on reports of child maltreatment from a southern state in the United States from October 1, 2018, through September 30, 2020, to data from the US Census Bureau to obtain data on county-level socioeconomic characteristics. We fit a segmented regression model to evaluate changes in reports before and after the SAHO, March 20, 2020. We evaluated potential disparities by child age, case and allegation severity, and socioeconomic characteristics. RESULTS: Of 374 885 hotline calls, 276 878 (73.9%) were made before the SAHO and 98 007 (26.1%) after it. Although an immediate decrease in reports of child maltreatment occurred on the day of the SAHO, the rates of reporting within socioeconomic groups started increasing thereafter. While we found no significant change in the overall rate of change in hotline calls after versus before the SAHO (0.23; 95% CI, -0.11 to 0.58), stratified analyses indicate that the rates at which reporting increased varied by education level, health insurance coverage, median annual household income, and unemployment. CONCLUSIONS: Evaluating these trends is important for policy makers and practitioners to understand how policies enforced during the pandemic influence child maltreatment reporting and how these policies may affect reporting differently across socioeconomic groups.

Risk factors for delirium among hospitalized patients in Zambia.

OBJECTIVE: To identify risk factors for delirium among hospitalized patients in Zambia. METHODS: We conducted a prospective cohort study at the University Teaching Hospital in Lusaka, Zambia, from October 2017 to April 2018. We report associations of exposures including sociodemographic and clinical factors with delirium over the first three days of hospital admission, assessed using a modified Brief Confusion Assessment Method (bCAM). FINDINGS: 749 patients were included for analysis (mean age, 42.9 years; 64.8% men; 47.3% with HIV). In individual regression analyses of potential delirium risk factors adjusted for age, sex and education, factors significantly associated with delirium included being divorced/widowed (OR 1.64, 95% CI 1.09-2.47), lowest tercile income (OR 1.58, 95% CI 1.04-2.40), informal employment (OR 1.97, 95% CI 1.25-3.15), untreated HIV infection (OR 2.18, 95% CI 1.21-4.06), unknown HIV status (OR 2.90, 95% CI 1.47-6.16), history of stroke (OR 2.70, 95% CI 1.15-7.19), depression/anxiety (OR 1.52, 95% CI 1.08-2.14), alcohol overuse (OR 1.96, 95% CI 1.39-2.79), sedatives ordered on admission (OR 3.77, 95% CI 1.70-9.54), severity of illness (OR 2.00, 95% CI 1.82-2.22), neurological (OR 7.66, 95% CI 4.90-12.24) and pulmonary-system admission diagnoses (OR 1.91, 95% CI 1.29-2.85), and sepsis (OR 2.44, 95% CI 1.51-4.08). After combining significant risk factors into a multivariable regression analysis, severity of illness, history of stroke, and being divorced/widowed remained predictive of delirium (p<0.05). CONCLUSION: Among hospitalized adults at a national referral hospital in Zambia, severity of illness, history of stroke, and being divorced/widowed were independently predictive of delirium. Extension of this work will inform future efforts to prevent, detect, and manage delirium in low- and middle-income countries.