COVID-19 Vaccine Acceptability Among Clients and Staff of Homeless Shelters in Detroit, Michigan, February 2021.

Understanding COVID-19 vaccine acceptability among clients and staff of homeless shelters can inform public health efforts focused on communicating with and educating this population about COVID-19 vaccines and thus improve vaccine uptake. The objective of this study was to assess COVID-19 vaccine acceptability and uptake among people in homeless shelters in Detroit, Michigan. A cross-sectional study was conducted from February 9 to 23, 2021. Seventeen homeless shelters were surveyed: seven male-only, three male/female, and seven women and family shelters. All clients and staff aged ≥18 years and able to complete a verbal survey in English or with a translator were eligible to participate; of the 168 individuals approached, 26 declined, leaving a total sample of 106 clients and 36 staff participating in the study. The median client and staff ages were 44 and 54 years, respectively. Most participants (>80%) identified as non-Hispanic Black or African American. Sixty-one (57.5%) clients and 27 (75.5%) staff had already received or planned to receive a COVID-19 vaccination. Twelve (11.3%) clients and four (11.1%) staff were unsure, and 33 (31.1%) clients and five (13.9%) staff did not plan to get vaccinated. Reasons for hesitancy were concerns over side effects (29 clients [64.4%] and seven staff [77.8%]) and unknown long-term health impacts (26 clients [57.8%] and six staff [66.7%]). More than half of the clients had already received or planned to receive the vaccine. Continuing efforts such as vaccine education for hesitant clients and staff and having accessible vaccine events for this population may improve acceptability and uptake.

Factors Associated with Legionella Detection in the Water Systems of National Lodging Organization Facilities with Water Management Programs in the United States.

A better understanding of risk factors and the predictive capability of water management program (WMP) data in detecting Legionella are needed to inform the efforts aimed at reducing Legionella growth and preventing outbreaks of Legionnaires' disease. Using WMPs and Legionella testing data from a national lodging organization in the United States, we aimed to (1) identify factors associated with Legionella detection and (2) assess the ability of WMP disinfectant and temperature metrics to predict Legionella detection. We conducted a logistic regression analysis to identify WMP metrics associated with Legionella serogroup 1 (SG1) detection. We also estimated the predictive values for each of the WMP metrics and SG1 detection. Of 5435 testing observations from 2018 to 2020, 411 (7.6%) had SG1 detection, and 1606 (29.5%) had either SG1 or non-SG1 detection. We found failures in commonly collected WMP metrics, particularly at the primary test point for total disinfectant levels in hot water, to be associated with SG1 detection. These findings highlight that establishing and regularly monitoring water quality parameters for WMPs may be important for preventing Legionella growth and subsequent disease. However, while unsuitable water quality parameter results are associated with Legionella detection, this study found that they had poor predictive value, due in part to the low prevalence of SG1 detection in this dataset. These findings suggest that Legionella testing provides critical information to validate if a WMP is working, which cannot be obtained through water quality parameter measurements alone.

Effects of the COVID-19 Pandemic on Legionella Water Management Program Performance across a United States Lodging Organization.

Legionella, the bacterium that causes Legionnaires' disease, can grow and spread in building water systems and devices. The COVID-19 pandemic impacted building water systems through reductions in water usage. Legionella growth risk factors can be mitigated through control measures, such as flushing, to address stagnation, as part of a water management program (WMP). A national lodging organization (NLO) provided WMP data, including Legionella environmental testing results for periods before and during the pandemic. The statistical analysis revealed an increased risk of water samples testing positive for Legionella during the pandemic, with the greatest increase in risk observed at the building's cold-water entry test point. Sample positivity did not vary by season, highlighting the importance of year-round Legionella control activities. The NLO's flushing requirements may have prevented an increased risk of Legionella growth during the pandemic. However, additional control measures may be needed for some facilities that experience Legionella detections. This analysis provides needed evidence for the use of flushing to mitigate the impacts of building water stagnation, as well as the value of routine Legionella testing for WMP validation. Furthermore, this report reinforces the idea that WMPs remain the optimal tool to reduce the risk of Legionella growth and spread in building water systems.

Spatial epidemiology of eastern equine encephalitis in Florida.

BACKGROUND: Eastern Equine Encephalitis virus (EEEV) is an alphavirus with high pathogenicity in both humans and horses. Florida continues to have the highest occurrence of human cases in the USA, with four fatalities recorded in 2010. Unlike other states, Florida supports year-round EEEV transmission. This research uses GIS to examine spatial patterns of documented horse cases during 2005-2010 in order to understand the relationships between habitat and transmission intensity of EEEV in Florida. METHODS: Cumulative incidence rates of EEE in horses were calculated for each county. Two cluster analyses were performed using density-based spatial clustering of applications with noise (DBSCAN). The first analysis was based on regional clustering while the second focused on local clustering. Ecological associations of EEEV were examined using compositional analysis and Euclidean distance analysis to determine if the proportion or proximity of certain habitats played a role in transmission. RESULTS: The DBSCAN algorithm identified five distinct regional spatial clusters that contained 360 of the 438 horse cases. The local clustering resulted in 18 separate clusters containing 105 of the 438 cases. Both the compositional analysis and Euclidean distance analysis indicated that the top five habitats positively associated with horse cases were rural residential areas, crop and pastureland, upland hardwood forests, vegetated non-forested wetlands, and tree plantations. CONCLUSIONS: This study demonstrates that in Florida tree plantations are a focus for epizootic transmission of EEEV. It appears both the abundance and proximity of tree plantations are factors associated with increased risk of EEE in horses and therefore humans. This association helps to explain why there is are spatially distinct differences in the amount of EEE horse cases across Florida.

Risk of exposure to eastern equine encephalomyelitis virus increases with the density of northern cardinals.

For a variety of infectious diseases, the richness of the community of potential host species has emerged as an important factor in pathogen transmission, whereby a higher richness of host species is associated with a lowered disease risk. The proposed mechanism driving this pattern is an increased likelihood in species-rich communities that infectious individuals will encounter dead-end hosts. Mosquito-borne pathogen systems potentially are exceptions to such "dilution effects" because mosquitoes vary their rates of use of vertebrate host species as bloodmeal sources relative to host availabilities. Such preferences may violate basic assumptions underlying the hypothesis of a dilution effect in pathogen systems. Here, we describe development of a model to predict exposure risk of sentinel chickens to eastern equine encephalitis virus (EEEV) in Walton County, Florida between 2009 and 2010 using avian species richness as well as densities of individual host species potentially important to EEEV transmission as candidate predictor variables. We found the highest support for the model that included the density of northern cardinals, a highly preferred host of mosquito vectors of EEEV, as a predictor variable. The highest-ranking model also included Culiseta melanura abundance as a predictor variable. These results suggest that mosquito preferences for vertebrate hosts influence pathogen transmission.