Guidance for Studies Evaluating the Accuracy of Biomarker-Based Nonsputum Tests to Diagnose Tuberculosis.

The World Health Organization's (WHO) "End TB" strategy calls for development and implementation of novel tuberculosis (TB) diagnostics. Sputum-based diagnostics are challenging to implement and often less sensitive in high-priority populations. Nonsputum, biomarker-based tests may facilitate TB testing at lower levels of the healthcare system, accelerate treatment initiation, and improve outcomes. We provide guidance on the design of diagnostic accuracy studies evaluating nonsputum, biomarker-based tests within the context of WHO's target product profile for such tests. Study designs should account for the intended use when choosing the study population, setting, and reference standards. Although adults with respiratory symptoms may be an initial target population, other high-priority populations regardless of symptoms-including people living with human immunodeficiency virus, those unable to produce sputum samples or with extrapulmonary TB, household contacts, and children-should be considered. Studies beyond diagnostic accuracy that evaluate feasibility and population-level impacts are also needed. A biomarker-based diagnostic may be critical to ending the TB epidemic, but requires appropriate validation before implementation.

Glycoside Hydrolase Genes Are Required for Virulence of Agrobacterium tumefaciens on Bryophyllum daigremontiana and Tomato.

Agrobacterium tumefaciens is a rhizosphere bacterium that can infect wound sites on plants. The bacterium transfers a segment of DNA (T-DNA) from the Ti plasmid to the plant host cell via a type IV secretion system where the DNA becomes integrated into the host cell chromosomes. The expression of T-DNA in the plant results in tumor formation. Although the binding of the bacteria to plant surfaces has been studied previously, there is little work on possible interactions of the bacteria with the plant cell wall. Seven of the 48 genes encoding putative glycoside hydrolases (Atu2295, Atu2371, Atu3104, Atu3129, Atu4560, Atu4561, and Atu4665) in the genome of A. tumefaciens C58 were found to play a role in virulence on tomato and Bryophyllum daigremontiana Two of these genes (pglA and pglB; Atu3129 and Atu4560) encode enzymes capable of digesting polygalacturonic acid and, thus, may play a role in the digestion of pectin. One gene (arfA; Atu3104) encodes an arabinosylfuranosidase, which could remove arabinose from the ends of polysaccharide chains. Two genes (bglA and bglB; Atu2295 and Atu4561) encode proteins with ß-glycosidase activity and could digest a variety of plant cell wall oligosaccharides and polysaccharides. One gene (xynA; Atu2371) encodes a putative xylanase, which may play a role in the digestion of xylan. Another gene (melA; Atu4665) encodes a protein with α-galactosidase activity and may be involved in the breakdown of arabinogalactans. Limited digestion of the plant cell wall by A. tumefaciens may be involved in tumor formation on tomato and B. daigremontianaIMPORTANCEA. tumefaciens is used in the construction of genetically engineered plants, as it is able to transfer DNA to plant hosts. Knowledge of the mechanisms of DNA transfer and the genes required will aid in the understanding of this process. Manipulation of glycoside hydrolases may increase transformation and widen the host range of the bacterium. A. tumefaciens also causes disease (crown gall tumors) on a variety of plants, including stone fruit trees, grapes, and grafted ornamentals such as roses. It is possible that compounds that inhibit glycoside hydrolases could be used to control crown gall disease caused by A. tumefaciens.

COVID-19 Vaccine Perceptions Survey for Real-Time Vaccine Outreach in Marin County, California.

BACKGROUND: Understanding and addressing coronavirus disease 2019 (COVID-19) vaccine hesitancy is crucial to informing vaccination outreach strategies and achieving high vaccination coverage. Marin County, California, United States, has a history of vaccine hesitancy regarding childhood vaccinations required for school entry. OBJECTIVES: We aimed to describe and address COVID-19 vaccine hesitancy in Marin County to inform outreach and messaging. Our objectives were to identify subgroups with high COVID-19 vaccine hesitancy early in distribution, better understand local concerns and feedback about the COVID-19 vaccine distribution process, and inform tailored vaccine messaging to increase vaccination confidence and coverage. METHODS: The survey, which was administered from January 3 to May 10, 2021, queried demographics, vaccine acceptance, reasons for hesitancy, and reasons for acceptance. Open-ended questions were used for respondents to report additional reasons for hesitancy and for general feedback about the vaccine distribution process. We conducted quantitative and qualitative analyses stratified by COVID-19 vaccine acceptance to identify subgroups with high hesitancy. Results were shared weekly in real-time with leadership and key community partners working on vaccine outreach. RESULTS: Among the 5,618 survey responses, there were differences in vaccine hesitancy by sociodemographic characteristics with the highest hesitancy reported among subgroups identifying as Black/African American and young adult, and within the lowest family income grouping. The most common reason for vaccine hesitancy was "uncertain about the side effects of the vaccine" (67.3% endorsement) and responses varied by race and ethnicity. Qualitative data revealed equity-related, vaccine distribution, and vaccine access themes that were not present in structured responses. Vaccine hesitancy survey results were paired with vaccination coverage and COVID-19 case data to inform tailored outreach strategies and priorities week-to-week. CONCLUSIONS: Marin County had some of the highest COVID-19 vaccination rates in the United States during the pandemic and met equity goals aimed at ensuring vulnerable populations received vaccinations. Presenting real-time survey findings with leadership and key community partners informed a timely and tailored COVID-19 vaccine outreach and delivery strategy.

Life Expectancy and Causes of Premature Death by Subgroup for Community-Based Action in Marin County, California, 2017-2021.

INTRODUCTION: Marin is a medium-sized county in California's San Francisco Bay Area. Despite its historically higher-than-average life expectancy and socioeconomic level, known economic and health disparities by race, ethnicity, and geography became more visible during the COVID-19 pandemic.  Methods: We calculated life expectancy, measured years of potential life lost (YPLLs), and described premature mortality for the five years of 2017-2021 by race, ethnicity, census tract, and resource level (as measured by Healthy Places Index [HPI]) to provide data on inequities to guide community-centered action to reduce premature mortality.  Results: Life expectancy for the county was 85.2 years. The non-Hispanic African American/Black population experienced the lowest life expectancy of 77.1 years, 11.6 years lower than the non-Hispanic Asian population which had the highest life expectancy (88.7 years). There was a 14.9-year difference in life expectancy between the census tracts with the lowest (77.1 years) and highest (92.0 years) estimates. We found a moderate, positive association between census tract resource level (HPI) and life expectancy (r=0.58, p<0.01). The leading causes of premature death were cancer, diseases of the circulatory system, and accidental overdoses, with variation by subgroup.  Conclusion: These data highlight health disparities that persist in Marin County and can inform data-driven public health strategies to narrow gaps in longevity between communities.

Emergency Medical Service Utilization and Response Following COVID-19 Emergency and Stay-at-Home Policies: An Interrupted Time-Series Analysis.

Objective Examine changing emergency medical services (EMS) utilization and response patterns associated with coronavirus disease 2019 (COVID-19) emergency declaration and stay-at-home orders during the first year of the COVID-19 pandemic. Methods We conducted an uncontrolled interrupted time series analysis of EMS calls (January 1, 2019 - March 1, 2021) in Marin County, California analyzing call volume (All calls, n=46,055); patient refusal of EMS care or transport and patient care resolved on scene (Calls with opportunity for transport; n=37,401); and call severity (Transported calls; n=27,887). Results Pre-COVID-19 (1/1/2019-3/2/2020), EMS transported patients were predominately female (50.6%), 80+ years old (31.6%), and Marin County residents (68.0%). During COVID-19 (3/3/2020-3/1/2021), EMS transported patients were predominately male (52.7%), 35-64 years old (29.8%), and Marin County residents (70.4%). After the first stay-at-home order on 3/17/2020, call volume immediately decreased by 48% (adjusted incidence rate ratio [aIRR]=0.52; 95% CI=0.35,0.79) for children (0-15 years) and 34% for adults 80+ years (aIRR=0.66;95% CI=0.46,0.95). The odds of a transported call being prioritized as severe doubled (adjusted odds ratio [aOR]=2.26; 95% CI=1.11,4.59). Though transport refusals increased by 69% for children after the first order (aOR, 1.69 [95% CI, 1.13-2.52]), immediately following the second order on 12/8/2020, transport refusals decreased by 30% for children but increased 38-40% for adults 35-79 years (aOR=1.40 [95% CI=1.04-1.89] for 35-64 years; 1.38 [95% CI=1.02-1.87] for 65-79 years). Calls resolved on scene by EMS increased after the first order among all ages and after the second order for adults 16-79 years.  Conclusions Call volume reduced for children and older adults after the first COVID-19 stay-at-home order. Changes in call severity, patient care refusals, and on-scene care provided by EMS indicated a changing role for EMS during the outbreak.

Field-based evaluation of malaria outbreak detection and response in Mudzi and Goromonzi districts, Zimbabwe - 2017.

National-level evaluations may fail to identify capacity improvements for detecting and responding to outbreaks which begin and are first detected at the local level. In response to this issue, we conducted a field-based assessment of the malaria outbreak surveillance system in Mashonaland East, Zimbabwe. We visited eleven clinics in Mudzi and Goromonzi districts. Twenty-one interviews were conducted with key informants from the provincial (n = 2), district (n = 7), and clinic (n = 12) levels. Interviews focused on surveillance system activities, preparedness, data quality, timeliness, stability, and usefulness. Main themes were captured utilising standard qualitative data analysis techniques. While the surveillance system detects malaria outbreaks at all levels, we identified several gaps. Clinics experience barriers to timely and reliable reporting of outbreaks to the district level and staff cross-training. Stability of resources, including transportation (33% of informants, n = 7) and staff capacity (48% of informants, n = 10), presented barriers. Strengthening these surveillance barriers may improve staff readiness to detect malaria outbreaks, resulting in timelier outbreak response and a reduction in malaria outbreaks, cases, and deaths. By focusing at the local level, our assessment approach provides a framework for identifying and addressing gaps that may be overlooked when utilising tools that evaluate surveillance capacity at the national level.

Sociodemographic and Clinical Risk Factors Associated With Tuberculosis Mortality in the United States, 2009-2013.

OBJECTIVES: The objectives of our study were (1) to determine risk factors associated with tuberculosis (TB)-specific and non-TB-specific mortality among patients with TB and (2) to examine whether risk factors for TB-specific mortality differed from those for non-TB-specific mortality. METHODS: We obtained data from the National Tuberculosis Surveillance System and included all patients who had TB between 2009 and 2013 in the United States and its territories. We used multinomial logistic regression analysis to determine the adjusted odds ratio (aOR) of each risk factor for TB-specific and non-TB-specific mortality. RESULTS: Of 52 175 eligible patients with TB, 1404 died from TB, and 2413 died from other causes. Some of the risk factors associated with the highest odds of TB-specific mortality were multidrug-resistant TB diagnosis (aOR = 3.42; 95% CI, 1.95-5.99), end-stage renal disease (aOR = 3.02; 95% CI, 2.23-4.08), human immunodeficiency virus infection (aOR = 2.63; 95% CI, 2.02-3.42), age 45-64 years (aOR = 2.57; 95% CI, 2.01-3.30) or age ≥65 years (aOR = 5.76; 95% CI, 4.37-7.61), and immunosuppression (aOR = 2.20; 95% CI, 1.71-2.83). All of these risk factors except multidrug-resistant TB were also associated with increased odds of non-TB-specific mortality. CONCLUSION: TB patients with certain risk factors have an elevated risk of TB-specific mortality and should be monitored before, during, and after treatment. Identifying the predictors of TB-specific mortality may help public health authorities determine which subpopulations to target and where to allocate resources.