Behavioral Health Providers' Experience with Changes in Services for People Experiencing Homelessness During COVID-19, USA, August-October 2020.

The COVID-19 pandemic caused disruptions in behavioral health services (BHS), essential for people experiencing homelessness (PEH). BHS changes created barriers to care and opportunities for innovative strategies for reaching PEH. The authors conducted 50 qualitative interviews with behavioral health providers in the USA during August-October 2020 to explore their observations of BHS changes for PEH. Interviews were transcribed and entered into MAXQDA for analysis and to identify salient themes. The largest impact from COVID-19 was the closure or limited hours for BHS and homeless shelters due to mandated "stay-at-home" orders or staff working remotely leading to a disconnection in services and housing linkages. Most providers initiated telehealth services for clients, yielding positive outcomes. Implications for BHS are the need for long-term strategies, such as advances in communication technology to support BHS and homeless services and to ensure the needs of underserved populations are met during public health emergencies.

Clinic- and Community-Based SARS-CoV-2 Testing Among People Experiencing Homelessness in the United States, March-November 2020.

OBJECTIVE: SARS-CoV-2 testing is a critical component of preventing the spread of COVID-19. In the United States, people experiencing homelessness (PEH) have accessed testing at health clinics, such as those provided through Health Care for the Homeless (HCH) clinics or through community-based testing events at homeless service sites or encampments. We describe data on SARS-CoV-2 testing among PEH in US clinic- and community-based settings from March through November 2020. METHODS: We conducted a descriptive analysis of data from HCH clinics and community testing events. We used a standardized survey to request data from HCH clinics. We developed and made publicly available an online data entry portal to collect data from community-based organizations that provided testing for PEH. We assessed positivity rates across clinics and community service sites serving PEH and used generalized linear mixed models to account for clustering. RESULTS: Thirty-seven HCH clinics reported providing 280 410 tests; 3.2% (n = 8880) had positive results (range, 1.6%-4.9%). By race, positivity rates were highest among people who identified as >1 race (11.6%; P < .001). During the reporting period, 22 states reported 287 community testing events and 14 116 tests; 7.1% (n = 1004) had positive results. Among facility types, day shelters (380 of 2697; 14.1%) and inpatient drug/alcohol rehabilitation facilities (32 of 251; 12.7%) reported the highest positivity rates. CONCLUSIONS: While HCH clinic data provided results for a larger number of patients, community-based testing data showed higher positivity rates. Clinic data demonstrated racial disparities in positivity. Community-based testing data provided information about SARS-CoV-2 transmission settings. Although these data provide information about testing, standard surveillance systems are needed to better understand the incidence of disease among PEH.

Morbidity and Mortality Among Adults Experiencing Homelessness Hospitalized With COVID-19.

People experiencing homelessness (PEH) are at higher risk for chronic health conditions, but clinical characteristics and outcomes for PEH hospitalized with coronavirus disease 2019 (COVID-19) are not known. We analyzed population-based surveillance data of COVID-19-associated hospitalizations during 1 March to 31 May 2020. Two percent of the people hospitalized with COVID-19 for whom a housing status was recorded were homeless. Of 199 cases in the analytic sample, most were of racial/ethnic minority groups and had underlying health conditions. Clinical outcomes such as ICU admission, respiratory support including mechanical ventilation, and deaths were documented. Hispanic and non-Hispanic black persons accounted for most mechanical ventilation and deaths. Severe illness was common among persons experiencing homelessness who were hospitalized with COVID-19.

Assessment of contact tracing for COVID-19 among people experiencing homelessness, Salt Lake County Health Department, March-May 2020.

PURPOSE: Contact tracing is intended to reduce the spread of coronavirus disease 2019 (COVID-19), but it is difficult to conduct among people who live in congregate settings, including people experiencing homelessness (PEH). This analysis compares person-based contact tracing among two populations in Salt Lake County, Utah, from March-May 2020. METHODS: All laboratory-confirmed positive cases among PEH (n = 169) and documented in Utah's surveillance system were included in this analysis. The general population comparison group (n = 163) were systematically selected from all laboratory-confirmed cases identified during the same period. RESULTS: Ninety-three PEH cases (55%) were interviewed compared to 163 (100%) cases among the general population (P < .0001). PEH were more likely to be lost to follow-up at end of isolation (14.2%) versus the general population (0%; P-value < .0001) and provided fewer contacts per case (0.3) than the general population (4.7) (P-value < .0001). Contacts of PEH were more often unreachable (13.0% vs. 7.1%; P-value < .0001). CONCLUSIONS: These findings suggest that contact tracing among PEH should include a location-based approach, along with a person-based approach when resources allow, due to challenges in identifying, locating, and reaching cases among PEH and their contacts through person-based contact tracing efforts alone.

Trends in Nonfatal Falls and Fall-Related Injuries Among Adults Aged ≥65 Years - United States, 2012-2018.

Falls are the leading cause of injury among adults aged ≥65 years (older adults) in the United States. In 2018, an estimated 3 million emergency department visits, more than 950,000 hospitalizations or transfers to another facility (e.g., trauma center), and approximately 32,000 deaths resulted from fall-related injuries among older adults.* Deaths from falls are increasing, with the largest increases occurring among persons aged ≥85 years (1). To describe the percentages and rates of nonfatal falls by age group and demographic characteristics and trends in falls and fall-related injuries over time, data were analyzed from the 2018 Behavioral Risk Factor Surveillance System (BRFSS) and were compared with data from 2012, 2014, and 2016. In 2018, 27.5% of older adults reported falling at least once in the past year, and 10.2% reported an injury from a fall in the past year. The percentages of older adults reporting a fall increased between 2012 and 2016 and decreased slightly between 2016 and 2018. Falls are preventable, and health care providers can help their older patients reduce their risk for falls. Screening older patients for fall risk, assessing modifiable risk factors (e.g., use of psychoactive medications or poor gait and balance), and recommending interventions to reduce this risk (e.g., medication management or referral to physical therapy) can prevent older adult falls (https://www.cdc.gov/steadi).

Low head circumference during early childhood and its predictors in a semi-urban settlement of Vellore, Southern India.

BACKGROUND: Stunting in developing countries continues to be a major public health problem. Measuring head circumference (HC) during clinical anthropometric assessment can help predict stunting. The aim of this study was to assess burden and determine the predictors of low HC (<- 2 SD) at birth and during first 2 years of life in a semi- urban settlement of Vellore. METHODS: The study uses baseline data and serial HC measurements from the birth cohort of MAL-ED study, where 228 children from Vellore completed follow-up between March 2010 to February 2014. Analysis of baseline, maternal and paternal characteristics, micro-nutrient status and cognition with HC measurements was performed using STATA version 13.0 software. RESULTS: The mean HC (±SD) at 1st, 12th and 24th month were 33.37 (1.29) cm, 42.76 (1.23) cm and 44.9 (1.22) cm respectively. A third of the infants (75/228) had HC less than - 2 SD at first month of life, and on follow-up, 50% of the cohort had HC ≤ -2 SD both at 12th and 24th month. Low HC measurements at all three time-points were observed for 21.6% (46/222) infants. Low HC was significantly associated with stunting in 37.3% (OR = 10.8), 57.3% (OR = 3.1) and 44.4% (OR = 2.6) children at 1st, 12th and 24th month respectively. Bivariate analysis of low HC (<- 2 SD) at 12th month showed a statistically significant association with lower socioeconomic status, low paternal and maternal HC and low maternal IQ. Multivariable logistic regression analysis showed maternal (AOR = 0.759, 95% CI = 0.604 to 0.954) and paternal (AOR = 0.734, 95% CI = 0.581 to 0.930) HC to be significantly associated with HC attained by the infant at the end of 12 months. CONCLUSIONS: One-third of the children in our cohort had low head circumference (HC) at birth, with one-fifth recording low HC at all time-points until 2 years of age. Low HC was significantly associated with stunting. Paternal and maternal HC predicted HC in children. HC measurement, often less used, can be a simple tool that can be additionally used by clinicians as well as parents/caregivers to monitor child growth.

Measuring Poverty in Southern India: A Comparison of Socio-Economic Scales Evaluated against Childhood Stunting.

INTRODUCTION: Socioeconomic status (SES) scales measure poverty, wealth and economic inequality in a population to guide appropriate economic and public health policies. Measurement of poverty and comparison of material deprivation across nations is a challenge. This study compared four SES scales which have been used locally and internationally and evaluated them against childhood stunting, used as an indicator of chronic deprivation, in urban southern India. METHODS: A door-to-door survey collected information on socio-demographic indicators such as education, occupation, assets, income and living conditions in a semi-urban slum area in Vellore, Tamil Nadu in southern India. A total of 7925 households were categorized by four SES scales-Kuppuswamy scale, Below Poverty Line scale (BPL), the modified Kuppuswamy scale, and the multidimensional poverty index (MDPI) and the level of agreement compared between scales. Logistic regression was used to test the association of SES scales with stunting. FINDINGS: The Kuppuswamy, BPL, MDPI and modified Kuppuswamy scales classified 7.1%, 1%, 5.5%, and 55.3% of families as low SES respectively, indicating conservative estimation of low SES by the BPL and MDPI scales in comparison with the modified Kuppuswamy scale, which had the highest sensitivity (89%). Children from low SES classified by all scales had higher odds of stunting, but the level of agreement between scales was very poor ranging from 1%-15%. CONCLUSION: There is great non-uniformity between existing SES scales and cautious interpretation of SES scales is needed in the context of social, cultural, and economic realities.