Leveraging Collective Impact to Address Structural Racism in Buncombe County, North Carolina.

Buncombe County, North Carolina, was recognized in 2014 as a Robert Wood Johnson Foundation Culture of Health Prize Winner for its work fostering collaboration and partnership to address community health needs. As part of this work, Buncombe County Health and Human Services (HHS) convened a cross-sector Public Health Advisory Council that supported community-based initiatives and ensured that community members were involved in identifying and implementing solutions to issues such as poverty and child well-being. Leveraging existing relationships and past efforts, Buncombe County has continued to build collaborative networks for systems change using a collective impact framework. Bringing together partners across sectors, including the faith community, Black fraternities and sororities, community health workers, consulates, and others, Buncombe County HHS is supporting efforts to train and equip community members to lead health promotion efforts and community conversations on historical trauma and racial healing; engage community members in the policymaking process through town halls; and archive the community's pandemic journey through storytelling. The collective impact framework has shaped an environment that supports community change by centering community aspirations and values. This environment informed recent declarations by Buncombe County HHS and the Board of Commissioners that racism is a public health crisis, as well as a resolution by the city of Asheville supporting community reparations. This article explores how the collective impact framework has been used in Buncombe County to engage and continually invest in communities of color and reviews steps taken to develop and implement an equity action plan to address structural racism.

An IMS/ATP Assay for the Detection of Mycobacterium tuberculosis in Urine.

Background. Although sputum smears are the gold standard for diagnosis of tuberculosis, sensitivity in HIV/TB coinfection cases is low, indicating a need for alternative methods. Urine is being increasingly evaluated. Materials and Methods. A novel method for detecting Mycobacterium tuberculosis (MTB) in synthetic urine using a combined IMS/ATP assay was evaluated. Preliminary work established standard ATP conditions and the sensitivity and specificity of the MTB antibody. Eighty-four blinded samples in four replicate assays were evaluated for the presence of MTB using labeled immunomagnetic beads for capture. Beads were separated, washed, and resuspended in broth and added to a microtiter plate. Bioluminescent output was measured and signal-to-noise ratios were calculated. All samples were plated on Middlebrook 7H10 agar or trypticase soy agar to determine limit of detection and recoveries. Results and Conclusions. MTB was distinguished from common bacteriuria isolates and other nontarget bacteria by its ATP results. IMS/ATP successfully detected 19 of 28 samples of MTB in synthetic urine with a limit of detection of 10(4) CFU/ml. Sensitivity and specificity were 67.9% and 82.1%, respectively. This assay offers a possible rapid screening method for HIV-positive patients with suspected coinfection to improve MTB diagnosis.

Dead-end ultrafiltration concentration and IMS/ATP-bioluminescence detection of Escherichia coli O157:H7 in recreational water and produce wash.

The purpose of this study was to develop a detection method for viable E. coli O157:H7 in fresh produce and recreational water. The method was evaluated using eight samples of produce wash and recreational water with or without spiked E. coli O157:H7 at ≤10(2) CFU·ml(-1) and concentrated using dead-end ultrafiltration (DEUF) to produce primary and secondary retentates. Fifty-four matrix replicates of undiluted secondary retentates or dilutions (1:2 or 1:10 in buffer) were evaluated using an IMS/ATP bioluminescence assay (IMS/ATP). Combining primary and secondary DEUF yielded a 2-4 log(10) increase in E. coli O157:H7 concentrations in spiked samples and resulted in signal-to-noise ratios 2-219 fold higher than controls, depending on the sample type. DEUF increased the concentration of E. coli O157:H7 to within the detectable limits of IMS/ATP. The combined assay provided detection of viable E. coli O157:H7 in produce and recreational water. Accurate detection of microbial pathogens using DEUF and IMS/ATP could reduce disease outbreaks from contaminated water sources and food products.

Rapid detection and identification of bacterial pathogens by using an ATP bioluminescence immunoassay.

Rapid identification of viable bacterial contaminants in food products is important because of their potential to cause disease. This study examined a method for microbial detection by using a combined ATP bioluminescence immunoassay. Escherichia coli O157:H7 and Salmonella enterica serovar Typhimurium were selected as target organisms because of their implication in foodborne illness. Various matrices containing the target cells were examined, including ground beef homogenate, apple juice, milk, and phosphate-buffered saline. Specific antibodies were immobilized on the surface of 96-well plates, and then the sample matrices containing target cells in the wells were incubated. Sample matrix (no cells) was used to establish background. The plates were washed, and the wells were incubated with BacTiter-Glo reagent in Mueller-Hinton II broth. Bioluminescent output was measured with the GloMax 96 luminometer. Signal-to-noise ratios were calculated, resulting in a limit of detection of 10(4) CFU/ml for both E. coli O157:H7 and Salmonella Typhimurium. The limit of detection for both species was not affected by the presence of nontarget cells. The various sample matrices did not affect signal-to-noise ratios when E. coli O157:H7 was the target. A weak matrix effect was observed when Salmonella Typhimurium was the target. A strong linear correlation was observed between the number of cells and luminescent output over 4 orders of magnitude for both species. This method provides a means of simultaneously detecting and identifying viable pathogens in complex matrices, and could have wider application in food microbiology.