Advanced child tax credit payments and national child abuse hotline contacts, 2019-2022.

BACKGROUND: Children in households experiencing poverty are disproportionately exposed to maltreatment. Income support policies have been associated with reductions in child abuse and neglect. The advance child tax credit (CTC) payments may reduce child maltreatment by improving the economic security of some families. No national studies have examined the association between advance CTC payments and child abuse and neglect. This study examines the association between the advance CTC payments and child abuse and neglect-related contacts to the Childhelp National Child Abuse Hotline. METHODS: A time series study of contacts to the Childhelp National Child Abuse Hotline between January 2019 and December 2022 was used to examine the association between the payments and hotline contacts. An interrupted time series (ITS) exploiting the variation in the advance CTC payments was estimated using fixed effects. RESULTS: The CTC advance payments were associated with an immediate 13.8% (95% CI -17.5% to -10.0%) decrease in contacts to the hotline in the ITS model. Following the expiration of the advance CTC payments, there was a significant and gradual 0.1% (95% CI +0.0% to +0.2%) daily increase in contacts. Sensitivity analyses found significant reductions in contacts following each payment, however, the reductions were associated with the last three of the six total payments. CONCLUSION: These findings suggest the advance CTC payments may reduce child abuse and neglect-related hotline contacts and continue to build the evidence base for associations between income-support policies and reductions in child abuse and neglect.

Multifaceted Public Health Response to a COVID-19 Outbreak Among Meat-Processing Workers, Utah, March-June 2020.

OBJECTIVE: To identify potential strategies to mitigate COVID-19 transmission in a Utah meat-processing facility and surrounding community. DESIGN/SETTING: During March-June 2020, 502 workers at a Utah meat-processing facility (facility A) tested positive for SARS-CoV-2. Using merged data from the state disease surveillance system and facility A, we analyzed the relationship between SARS-CoV-2 positivity and worker demographics, work section, and geospatial data on worker residence. We analyzed worker survey responses to questions regarding COVID-19 knowledge, beliefs, and behaviors at work and home. PARTICIPANTS: (1) Facility A workers (n = 1373) with specimen collection dates and SARS-CoV-2 RT-PCR test results; (2) residential addresses of all persons (workers and nonworkers) with a SARS-CoV-2 diagnostic test (n = 1036), living within the 3 counties included in the health department catchment area; and (3) facility A workers (n = 64) who agreed to participate in the knowledge, attitudes, and practices survey. MAIN OUTCOME MEASURES: New cases over time, COVID-19 attack rates, worker characteristics by SARS-CoV-2 test results, geospatially clustered cases, space-time proximity of cases among workers and nonworkers; frequency of quantitative responses, crude prevalence ratios, and counts and frequency of coded responses to open-ended questions from the COVID-19 knowledge, attitudes, and practices survey. RESULTS: Statistically significant differences in race (P = .01), linguistic group (P < .001), and work section (P < .001) were found between workers with positive and negative SARS-CoV-2 test results. Geographically, only 6% of cases were within statistically significant spatiotemporal case clusters. Workers reported using handwashing (57%) and social distancing (21%) as mitigation strategies outside work but reported apprehension with taking COVID-19-associated sick leave. CONCLUSIONS: Mitigating COVID-19 outbreaks among workers in congregate settings requires a multifaceted public health response that is tailored to the workforce. IMPLICATIONS FOR POLICY AND PRACTICE: Tailored, multifaceted mitigation strategies are crucial for reducing COVID-19-associated health disparities among disproportionately affected populations.

Trends in County-Level COVID-19 Incidence in Counties With and Without a Mask Mandate - Kansas, June 1-August 23, 2020.

Wearing masks is a CDC-recommended* approach to reduce the spread of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), by reducing the spread of respiratory droplets into the air when a person coughs, sneezes, or talks and by reducing the inhalation of these droplets by the wearer. On July 2, 2020, the governor of Kansas issued an executive order† (state mandate), effective July 3, requiring masks or other face coverings in public spaces. CDC and the Kansas Department of Health and Environment analyzed trends in county-level COVID-19 incidence before (June 1-July 2) and after (July 3-August 23) the governor's executive order among counties that ultimately had a mask mandate in place and those that did not. As of August 11, 24 of Kansas's 105 counties did not opt out of the state mandate§ or adopted their own mask mandate shortly before or after the state mandate was issued; 81 counties opted out of the state mandate, as permitted by state law, and did not adopt their own mask mandate. After the governor's executive order, COVID-19 incidence (calculated as the 7-day rolling average number of new daily cases per 100,000 population) decreased (mean decrease of 0.08 cases per 100,000 per day; net decrease of 6%) among counties with a mask mandate (mandated counties) but continued to increase (mean increase of 0.11 cases per 100,000 per day; net increase of 100%) among counties without a mask mandate (nonmandated counties). The decrease in cases among mandated counties and the continued increase in cases in nonmandated counties adds to the evidence supporting the importance of wearing masks and implementing policies requiring their use to mitigate the spread of SARS-CoV-2 (1-6). Community-level mitigation strategies emphasizing wearing masks, maintaining physical distance, staying at home when ill, and enhancing hygiene practices can help reduce transmission of SARS-CoV-2.