Rabies is a fatal encephalitic disease affecting all mammals. This report describes identification of raccoon rabies virus variant isolated from a stray kitten in an urban Midwestern city that is nonendemic for this virus variant. The kitten originally presented with nonspecific neurologic abnormalities. Astute veterinary, wildlife, and public health professionals played a critical role in the identification of this fatal zoonotic disease and the extensive public health and wildlife management response that ensued. This case serves as an important reminder of the risk of rabies in unvaccinated animals or those without known vaccination status, including stray animals.

In low and middle-income countries, a large proportion of animal rabies investigations end without a conclusive diagnosis leading to epidemiologic interpretations informed by clinical, rather than laboratory data. We compared Extreme Gradient Boosting (XGB) with Logistic Regression (LR) for their ability to estimate the probability of rabies in animals investigated as part of an Integrated Bite Case Management program (IBCM). To balance our training data, we used Random Oversampling (ROS) and Synthetic Minority Oversampling Technique. We developed a risk stratification framework based on predicted rabies probabilities. XGB performed better at predicting rabies cases than LR. Oversampling strategies enhanced the model sensitivity making them the preferred technique to predict rare events like rabies in a biting animal. XGB-ROS classified most of the confirmed rabies cases and only a small proportion of non-cases as either high (confirmed cases = 85.2%, non-cases = 0.01%) or moderate (confirmed cases = 8.4%, non-cases = 4.0%) risk. Model-based risk stratification led to a 3.2-fold increase in epidemiologically useful data compared to a routine surveillance strategy using IBCM case definitions. Our study demonstrates the application of machine learning to strengthen zoonotic disease surveillance under resource-limited settings.

On September 28, 2023, a kitten aged approximately 6 weeks found in Omaha, Nebraska, had test results positive for rabies at the Nebraska Veterinary Diagnostic Center (NVDC) after dying with neurologic signs and having bitten and scratched its caretakers. Preliminary investigation identified 10 exposed persons for whom postexposure prophylaxis (PEP)(†) was recommended. Subsequent variant-typing by NVDC yielded a presumptive positive result for the Eastern raccoon rabies virus variant (RRVV), which CDC confirmed on October 6.

OBJECTIVE: To provide comprehensive epidemiological information about the distribution and occurrence of rabies during 2022 in the US, Canada, and Mexico. METHODS: The US National Rabies Surveillance System collected 2022 animal rabies data from US state and territorial public health departments and USDA Wildlife Services. Temporal and geographic analyses were conducted to evaluate trends in animal rabies cases. RESULTS: During 2022, 54 US jurisdictions reported 3,579 animal rabies cases, reflecting a 2.3% decline from 3,663 cases reported in 2021. Six states collectively reported > 50% of animal rabies cases: Texas (395 [11.0%]), Virginia (337 [9.4%]), Pennsylvania (329 [9.2%]), New York (267 [7.5%]), North Carolina (264 [7.4%]), and California (241 [6.7%]). Out of the total reported rabies animal cases, 3,234 (90.4%) were attributed to wildlife, with bats (1,218 [34.0%]), raccoons (1,014 [28.3%]), skunks (660 [18.4%]), and foxes (269 [7.5%]) representing the primary hosts confirmed with rabies. Rabid cats (222 [6.2%]), cattle (42 [1.2%]), and dogs (50 [1.4%]) constituted > 90% of reported domestic animal rabies cases. CONCLUSIONS: In 2022, there was an increase in the number of animal samples submitted for rabies testing in the US and Canada. A notable geographic expansion of gray fox rabies virus variant was detected in the US. Three human rabies deaths due to vampire bat rabies infection occurred in Mexico; none were reported from the US and Canada. CLINICAL RELEVANCE: Laboratory diagnosis of rabies in animals is critical to ensure judicious use of human rabies postexposure prophylaxis.

Objective: To examine associations between comfort eating in response to loneliness or stress and weight change during the COVID-19 pandemic among U.S. adults. Design(s): Quantitative, cross-sectional study. Setting(s): The 2021 SummerStyles survey data. Subjects: U.S. adults (>=18 years; N = 4068). Measures: The outcome was reported weight changes since the start of the COVID-19 pandemic with four responses: lost weight, weight remained the same, gained weight, and don't know. The exposure variable was frequency of comfort eating in response to loneliness or stress during the past year with three responses: never/rarely, sometimes, or often/always. Analysis: We used chi-square analysis to examine the independence of survey variables related to weight changes, and comfort eating in response to loneliness or stress during the COVID-19 pandemic. Next, we used a multinomial logistic regression to estimate adjusted odds ratios for weight changes by comfort eating in response to loneliness or stress frequency. Result(s): Overall, 20.1% of adults reported losing weight, 39.9% remained about the same weight, 30.4% gained weight, and 9.4% did not know about their weight change during the COVID-19 pandemic. Taking comfort by eating in response to loneliness or stress was reported by over 33% of participants (often/always = 8.3%; sometimes = 25.3%). Weight change and comfort eating during the COVID-19 pandemic significantly varied by sociodemographic factors. Respondents that sometimes or often/always reported taking comfort by eating in response to loneliness or stress were more likely to report losing weight (Adjusted Odds Ratio ranges: 1.62-2.99) or gaining weight (Adjusted Odds Ratio ranges: 3.10-4.61) than those who never/rarely took comfort by eating in response to loneliness or stress. Conclusion(s): Taking comfort by eating when stressed/lonely was significantly associated with reported weight changes during the COVID-19 pandemic. Weight changes may lead to additional health complications. Implementing evidence-based strategies to reduce loneliness or stress and support healthy eating during the COVID-19 pandemic may benefit weight management and future well-being. Copyright © 2023

Historical targets for country-level animal rabies testing volumes were abandoned due to ethical and welfare concerns, and interpretation challenges of testing healthy animals. To-date, no quantitative threshold has been established for evaluating adequate surveillance capacity specific to suspected rabid animals. The purpose here is to establish quantitative testing thresholds for rabies suspected animals to assess a country's rabies surveillance capacity. Animal rabies testing data was obtained from official and unofficial rabies surveillance platforms from 2010 to 2019 and supplemented with official country reports and published literature. Testing rates were determined for all-animal and domestic animals, and standardized per 100,000 estimated human population; the domestic animal rate was also standardized per 100,000 estimated dog population. There were 113 countries that reported surveillance data eligible for analysis. Countries reporting the most data were under WHO categories as having endemic human rabies or no dog rabies. The annual median all-animal testing rate for all countries was 1.53 animals/100,000 human population (IQR 0.27-8.78). Three proposed testing rate thresholds are an all-animal rate of 1.9 animals/100,000 humans, a domestic animal per human rate of 0.8 animals/100,000 humans, and a domestic animal per dog rate of 6.6 animals/100,000 dogs. These three peer-derived rabies testing thresholds for passive surveillance can be used to facilitate assessment of a country's rabies surveillance capacity.