Social vulnerability and county stay-at-home behavior during COVID-19 stay-at-home orders, United States, April 7-April 20, 2020.

PURPOSE: Early COVID-19 mitigation relied on people staying home except for essential trips. The ability to stay home may differ by sociodemographic factors. We analyzed how factors related to social vulnerability impact a community's ability to stay home during a stay-at-home order. METHODS: Using generalized, linear mixed models stratified by stay-at-home order (mandatory or not mandatory), we analyzed county-level stay-at-home behavior (inferred from mobile devices) during a period when a majority of United States counties had stay-at-home orders (April 7-April 20, 2020) with the Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI). RESULTS: Counties with higher percentages of single-parent households, mobile homes, and persons with lower educational attainment were associated with lower stay-at-home behavior compared with counties with lower respective percentages. Counties with higher unemployment, higher percentages of limited-English-language speakers, and more multi-unit housing were associated with increases in stay-at-home behavior compared with counties with lower respective percentages. Stronger effects were found in counties with mandatory orders. CONCLUSIONS: Sociodemographic factors impact a community's ability to stay home during COVID-19 stay-at-home orders. Communities with higher social vulnerability may have more essential workers without work-from-home options or fewer resources to stay home for extended periods, which may increase risk for COVID-19. Results are useful for tailoring messaging, COVID-19 vaccine delivery, and public health responses to future outbreaks.

Differences in rapid increases in county-level COVID-19 incidence by implementation of statewide closures and mask mandates - United States, June 1-September 30, 2020.

BACKGROUND AND OBJECTIVE: Community mitigation strategies could help reduce COVID-19 incidence, but there are few studies that explore associations nationally and by urbanicity. In a national county-level analysis, we examined the probability of being identified as a county with rapidly increasing COVID-19 incidence (rapid riser identification) during the summer of 2020 by implementation of mitigation policies prior to the summer, overall and by urbanicity. METHODS: We analyzed county-level data on rapid riser identification during June 1-September 30, 2020 and statewide closures and statewide mask mandates starting March 19 (obtained from state government websites). Poisson regression models with robust standard error estimation were used to examine differences in the probability of rapid riser identification by implementation of mitigation policies (P-value< .05); associations were adjusted for county population size. RESULTS: Counties in states that closed for 0-59 days were more likely to become a rapid riser county than those that closed for >59 days, particularly in nonmetropolitan areas. The probability of becoming a rapid riser county was 43% lower among counties that had statewide mask mandates at reopening (adjusted prevalence ratio = 0.57; 95% confidence intervals = 0.51-0.63); when stratified by urbanicity, associations were more pronounced in nonmetropolitan areas. CONCLUSIONS: These results underscore the potential value of community mitigation strategies in limiting the COVID-19 spread, especially in nonmetropolitan areas.

EXAMINING SOCIODEMOGRAPHIC DATA REPORTING REQUIREMENTS IN STATE DISEASE SURVEILLANCE SYSTEMS.

Law plays an important role in the collection of data related to disease and injury in a population. A robust system of laws sets out requirements for the collection, analysis, and dissemination of disease reporting data from local, state, territorial, and federal public health institutions. Occurrence of disease, including outbreaks of novel infectious agents like coronaviruses, influenza viruses, and others that have arisen in recent years, often require epidemiologists and others to understand not only the etiology and specific context of diseases and conditions, but also the trajectory of their spread among and across communities. Capturing sociodemographic data is critical to identifying the disproportionate impacts of diseases and conditions on diverse populations and determining an appropriate public health response. This Article discusses a legal epidemiological scan of state disease reporting laws that require the capture and reporting of sociodemographic information. Analyzing these state laws can serve as a potential starting point to assist in understanding why gaps in data exist and can help address these challenges in anticipation of future disease outbreaks or spread.

Timing of State and Territorial COVID-19 Stay-at-Home Orders and Changes in Population Movement - United States, March 1-May 31, 2020.

SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is thought to spread from person to person primarily by the respiratory route and mainly through close contact (1). Community mitigation strategies can lower the risk for disease transmission by limiting or preventing person-to-person interactions (2). U.S. states and territories began implementing various community mitigation policies in March 2020. One widely implemented strategy was the issuance of orders requiring persons to stay home, resulting in decreased population movement in some jurisdictions (3). Each state or territory has authority to enact its own laws and policies to protect the public's health, and jurisdictions varied widely in the type and timing of orders issued related to stay-at-home requirements. To identify the broader impact of these stay-at-home orders, using publicly accessible, anonymized location data from mobile devices, CDC and the Georgia Tech Research Institute analyzed changes in population movement relative to stay-at-home orders issued during March 1-May 31, 2020, by all 50 states, the District of Columbia, and five U.S. territories.* During this period, 42 states and territories issued mandatory stay-at-home orders. When counties subject to mandatory state- and territory-issued stay-at-home orders were stratified along rural-urban categories, movement decreased significantly relative to the preorder baseline in all strata. Mandatory stay-at-home orders can help reduce activities associated with the spread of COVID-19, including population movement and close person-to-person contact outside the household.

Selective serotonin-reuptake inhibitors in the treatment of premature ejaculation.

OBJECTIVE: To review the use of selective serotonin-reuptake inhibitors (SSRIs) in the treatment of premature ejaculation. DATA SOURCES: Articles were retrieved through a MEDLINE search (1966-January 2004). Search terms used to identify articles included serotonin uptake inhibitors, premature ejaculation, rapid ejaculation, and sexual behavior, as well as the generic names of currently available SSRIs: fluoxetine, fluvoxamine, paroxetine, sertraline, citalopram, and escitalopram. The literature search was limited to articles published in the English language containing human subjects. STUDY SELECTION AND DATA EXTRACTION: Articles obtained through the literature search were evaluated, and randomized controlled trials were included in this review. Information from noncontrolled trials or case reports was considered for inclusion if it contributed to the completeness of this review and if it was the highest level of evidence available. DATA SYNTHESIS: Premature ejaculation is a commonly reported sexual difficulty. Delayed ejaculation is a widely reported sexual adverse effect of SSRIs. In some men exhibiting premature ejaculation, the ability of the SSRIs to delay ejaculation has been therapeutic. Trials evaluating the ejaculation-delaying ability of SSRIs demonstrated that paroxetine, fluoxetine, sertraline, and citalopram produce a statistically significant increase in the ejaculation latency time compared with placebo. CONCLUSIONS: Taking advantage of the ejaculation-delaying effects of SSRIs increases the treatment options available to prescribers and patients. Convenience and minimal adverse effect profile make these agents an alternative to previously used behavior modalities and older pharmacologic agents. Although some questions still surround the details of their use, SSRIs have the potential to improve the quality of life for men with premature ejaculation and their partners.