The utility of a Bayesian predictive model to forecast neuroinvasive West Nile virus disease in the United States of America, 2022.

Arboviruses (arthropod-borne-viruses) are an emerging global health threat that are rapidly spreading as climate change, international business transport, and landscape fragmentation impact local ecologies. Since its initial detection in 1999, West Nile virus has shifted from being a novel to an established arbovirus in the United States of America. Subsequently, more than 25,000 cases of West Nile neuro-invasive disease have been diagnosed, cementing West Nile virus as an arbovirus of public health importance. Given its novelty in the United States of America, high-risk ecologies are largely underdefined making targeted population-level public health interventions challenging. Using the Centers for Disease Control and Prevention ArboNET neuroinvasive West Nile virus data from 2000-2021, this study aimed to predict neuroinvasive West Nile virus human cases at the county level for the contiguous USA using a spatio-temporal Bayesian negative binomial regression model. The model includes environmental, climatic, and demographic factors, as well as the distribution of host species. An integrated nested Laplace approximation approach was used to fit our model. To assess model prediction accuracy, annual counts were withheld, forecasted, and compared to observed values. The validated models were then fit to the entire dataset for 2022 predictions. This proof-of-concept mathematical, geospatial modelling approach has proven utility for national health agencies seeking to allocate funding and other resources for local vector control agencies tackling West Nile virus and other notifiable arboviral agents.

A statewide, cross-sectional evaluation of the knowledge and level of concern of rabies among South Carolina residents.

Animal rabies cases have increased steadily in South Carolina (SC) for the past decade. An understanding of the population's awareness and understanding of the disease is needed to tailor public health interventions. A marketing list-serv of SC residents' email addresses was used to recruit anonymous respondents for a Knowledge Attitudes and Practices (KAP) electronic survey. A total 516 South Carolinians completed the 31-question survey. Quantile regression and a Pearson's correlation evaluated potential associations between respondent's rabies knowledge and their attitudes and practices. Knowledge was assessed on topics of rabies biology, state animal case counts and rabies pet-related laws. Level of concern and level of knowledge were positively correlated. Additionally, statewide hotspot analysis revealed geographic areas warranting targeted public health interventions; counties with low public concern juxtapositioned with high animal rabies case counts. This study demonstrates the utility of statewide KAPs to gauge populations rabies perception and related preventative actions to tailor appropriate educational programs to limit human-animal rabies exposures.

Building-level wastewater surveillance of SARS-CoV-2 is associated with transmission and variant trends in a university setting.

The University of South Carolina (UofSC) was among the first universities to include building-level wastewater surveillance of SARS-CoV-2 to complement clinical testing during its reopening in the Fall 2020 semester. In the Spring 2021 semester, 24h composite wastewater samples were collected twice per week from 10 residence halls and the on-campus student isolation and quarantine building. The isolation and quarantine building served as a positive control site. The wastewater was analyzed using RT-ddPCR for the quantification of nucleocapsid genes (N1 and N2) to identify viral transmission trends within residence halls. Log10 SARS-CoV-2 RNA concentrations were compared to both new clinical cases identified in the days following wastewater collection and recovered cases returning to sites during the days preceding sample collection to test temporal and spatial associations. There was a statistically significant positive relationship between the number of cases reported from the sites during the seven-day period following wastewater sampling and the log10 viral RNA copies/L (overall IRR 1.08 (1.02, 1.16) p-value 0.0126). Additionally, a statistically significant positive relationship was identified between the number of cases returning to the residence halls after completing isolation during the seven-day period preceding wastewater sampling and the log10 viral RNA copies/L (overall 1.09 (1.01, 1.17) p-value 0.0222). The statistical significance of both identified cases and recovered return cases on log10 viral RNA copies/L in wastewater indicates the importance of including both types of clinical data in wastewater-based epidemiology (WBE) research. Genetic mutations associated with variants of concern (VOCs) were also monitored. The emergence of the Alpha variant on campus was identified, which contributed to the second wave of COVID-19 cases at UofSC. The study was able to identify sub-community transmission hotspots for targeted intervention in real-time, making WBE cost-effective and creating less of a burden on the general public compared to repeated individual testing methods.

Determinants of COVID-19 Vaccinations among a State-Wide Year-Long Surveillance Initiative in a Conservative Southern State.

By the end of 2021, the COVID-19 pandemic resulted in over 54 million cases and more than 800,000 deaths in the United States, and over 350 million cases and more than 5 million deaths worldwide. The uniqueness and gravity of this pandemic have been reflected in the public health guidelines poorly received by a growing subset of the United States population. These poorly received guidelines, including vaccine receipt, are a highly complex psychosocial issue, and have impacted the successful prevention of disease spread. Given the intricate nature of this important barrier, any single statistical analysis methodologically fails to address all convolutions. Therefore, this study utilized different analytical approaches to understand vaccine motivations and population-level trends. With 12,975 surveys from a state-wide year-long surveillance initiative, we performed three robust statistical analyses to evaluate COVID-19 vaccine hesitancy: principal component analysis, survival analysis and spatial time series analysis. The analytic goal was to utilize complementary mathematical approaches to identify overlapping themes of vaccine hesitancy and vaccine trust in a highly conservative US state. The results indicate that vaccine receipt is influenced by the source of information and the population's trust in the science and approval process behind the vaccines. This multifaceted statistical approach allowed for methodologically rigorous results that public health professionals and policy makers can directly use to improve vaccine interventions.

Incidence and risk factors associated with early death in patients with emergency department septic shock.

BACKGROUND: Limited research has explored early mortality among patients presenting with septic shock. The objective of this study was to determine the incidence and factors associated with early death following emergency department (ED) presentation of septic shock. METHODS: A prospective registry of patients enrolled in an ED septic shock clinical pathway was used to identify patients. Patients were compared across demographic, comorbid, clinical, and treatment variables by death within 72 hours of ED presentation. RESULTS: Among the sample of 2,414 patients, overall hospital mortality was 20.6%. Among patients who died in the hospital, mean and median time from ED presentation to death were 4.96 days and 2.28 days, respectively. Death at 24, 48, and 72 hours occurred in 5.5%, 9.5%, and 11.5% of patients, respectively. Multivariate regression analysis demonstrated that the following factors were independently associated with early mortality: age (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.03-1.05), malignancy (OR, 1.53; 95% CI, 1.11-2.11), pneumonia (OR, 1.39; 95% CI, 1.02-1.88), urinary tract infection (OR, 0.63; 95% CI, 0.44-0.89), first shock index (OR, 1.85; 95% CI, 1.27-2.70), early vasopressor use (OR, 2.16; 95% CI, 1.60-2.92), initial international normalized ratio (OR, 1.14; 95% CI, 1.07-1.27), initial albumin (OR, 0.55; 95% CI, 0.44-0.69), and first serum lactate (OR, 1.21; 95% CI, 1.16-1.26). CONCLUSIONS: Adult septic shock patients experience a high rate of early mortality within 72 hours of ED arrival. Recognizable clinical factors may aid the identification of patients at risk of early death.

Influence of Socioeconomic Bias on Emergency Medicine Resident Decision Making and Patient Care.

INTRODUCTION: Physician bias impacts clinical decision making, resulting in disparities in patient care. Most existing studies focus on sex and racial bias. This study aimed to investigate disparities in physician decision making among patients of varying socioeconomic status (SES). METHODS: Emergency medicine residents (n = 31) participated in 3 consecutive scenarios of similar disease acuity but with standardized patients of varying SES. Following the scenarios, residents met with a standardized participant acting as an attending physician for a handoff to recount their decision-making processes and care recommendations. Blinded raters evaluated clinical performance using an objective assessment tool. We assessed associations between patient SES and resident-ordered imaging, ordered medication, patient-perceived empathy, and clinical performance. We used qualitative analyses to study residents' decision-making processes. RESULTS: Quantitative analyses revealed no significant relationship between SES and resident-ordered imaging, ordered medications, patient-perceived empathy, and clinical performance. Qualitative analyses revealed 3 themes regarding clinical decision making: (1) overt diagnostic focus, (2) discharge planning, and (3) risk and exposure. CONCLUSIONS: Although quantitative analyses showed that SES did not affect clinical behavior within simulated scenarios, qualitative analyses uncovered 3 themes believed important to physician decision-making processes. Overt diagnostic focus may have resulted from the study environment in addition to organizational factors, policies, and training. Discharge planning, which was not explicitly studied, was often tailored to SES with emphasis placed on risks for patients of low SES. Further research is needed to uncover the nuances of bias, SES, and physician decision making throughout the patient care continuum and within various clinical environments.