Background: The COVID-19 pandemic resulted in a massive disruption in access to care and thus passive, hospital- and clinic-based surveillance programs. In 2020, the reported cases of Lyme disease were the lowest both across the United States and North Carolina in recent years. During this period, human contact patterns began to shift with higher rates of greenspace utilization and outdoor activities, putting more people into contact with potential vectors and associated vector-borne diseases. Lyme disease reporting relies on passive surveillance systems, which were likely disrupted by changes in health care–seeking behavior during the pandemic. Objective: This study aimed to quantify the likely under-ascertainment of cases of Lyme disease during the COVID-19 pandemic in the United States and North Carolina. Methods: We fitted publicly available, reported Lyme disease cases for both the United States and North Carolina prior to the year 2020 to predict the number of anticipated Lyme disease cases in the absence of the pandemic using a Bayesian modeling approach. We then compared the ratio of reported cases divided by the predicted cases to quantify the number of likely under-ascertained cases. We then fitted geospatial models to further quantify the spatial distribution of the likely under-ascertained cases and characterize spatial dynamics at local scales. Results: Reported cases of Lyme Disease were lower in 2020 in both the United States and North Carolina than prior years. Our findings suggest that roughly 14,200 cases may have gone undetected given historical trends prior to the pandemic. Furthermore, we estimate that only 40% to 80% of Lyme diseases cases were detected in North Carolina between August 2020 and February 2021, the peak months of the COVID-19 pandemic in both the United States and North Carolina, with prior ascertainment rates returning to normal levels after this period. Our models suggest both strong temporal effects with higher numbers of cases reported in the summer months as well as strong geographic effects. Conclusions: Ascertainment rates of Lyme disease were highly variable during the pandemic period both at national and subnational scales. Our findings suggest that there may have been a substantial number of unreported Lyme disease cases despite an apparent increase in greenspace utilization. The use of counterfactual modeling using spatial and historical trends can provide insight into the likely numbers of missed cases. Variable ascertainment of cases has implications for passive surveillance programs, especially in the trending of disease morbidity and outbreak detection, suggesting that other methods may be appropriate for outbreak detection during disturbances to these passive surveillance systems.

The emergence of highly pathogenic avian influenza A H ₅ N ₁ in dairy cattle raises many questions related to animal health and changes to the risk of an epidemic in humans. We synthesized information currently published to fit a compartment model of H ₅ N ₁ transmission within a dairy herd. An accompanying web application allows users to run simulations for specific outbreak scenarios. We estimated R ₀ near 1.2 with a short duration of infectiousness and fast time course of an epidemic within a farm, which we discuss in the context of possible on-farm control strategies. The web application allows users to simulate consequences of an epidemic using herd-specific information, a tool we propose will help inform stakeholders about potential consequences of uncontrolled H ₅ N ₁ spread. Our modeling work has identified several key information gaps that would strengthen our understanding and control of this emerging infectious disease.

Background/Objectives: The COVID-19 pandemic disproportionately impacted rural areas across the United States, including rural North Carolina (NC). Consistent with national patterns, COVID-19 vaccination coverage as of December 2022 was higher for non-rural (72%) than rural (58%) NC counties. The role of trusted sources of vaccine information used by rural and non-rural residents is unknown. Methods: Using data from two surveys distributed by the COVID-19 Community Research Partnership from 8 June 2021 through 21 December 2021, we compared self-reported sources of trusted COVID-19 vaccine information by non-rural and rural counties and by county-level predominant political vote in the 2020 Presidential election. Results: While NC respondents were highly vaccinated (94%), fewer residents from rural counties self-reported COVID-19 vaccination than those from non-rural counties (91% versus 95%). The most common reported source of trusted vaccine information was federal health agencies. The proportion citing a federal health agency was higher for respondents from non-rural (80%) than rural (72%) counties and was higher for vaccinated (75%) than unvaccinated (42%) rural respondents. The next two most trusted sources of vaccine information were state/local health officials (48%) and health care providers (42%). Among trusted resources reported by 10–15% of respondents, those from rural counties were less likely to use hospital websites, employers, or news sources than those from non-rural counties. More respondents from counties with >60% vote for the 2020 Democratic Presidential candidate cited federal health agencies, state and local officials, and new sources than respondents from counties with >60% vote for the 2020 Republican Presidential candidate. Conclusions: By identifying the trusted sources of vaccine information for residents in non-rural and rural NC counties, future vaccine implementation efforts can tailor communication efforts to increase vaccine uptake and potentially reduce the rates of hospitalizations and death from vaccine-preventable diseases such as COVID-19 or other future pandemics.

Background: Core groups, characterized by high levels of sexual activity and disease prevalence, are critical to the transmission dynamics of sexually transmitted infections (STIs) like gonorrhea. Understanding core group dynamics is essential for developing targeted interventions and understanding their potential effect on outcomes for gonorrhea. We assessed core group composition among gonorrhea cases in Guilford County, North Carolina, where gonorrhea rates are elevated, and antimicrobial resistance is a growing concern. Methods: We used Neisseria gonorrhoeae surveillance data collected in both public health clinics and emergency departments in Guilford County to characterize core groups. Data including demographics, behavioral risks, and longitudinal gonorrhea test results, were reviewed for specimens submitted for gonorrhea testing. Statistical analyses, including descriptive statistics and univariate logistic regression, were performed to assess factors influencing core group membership within three subpopulations: teens, adult men who have sex with men (MSM), and adult heterosexuals. Results: The study included 25,520 patients, with 1,718 (6.7%) classified as part of the core group. The core group accounted for 68% of all gonorrhea cases, with subgroups such as teen, adult MSM, and adult heterosexual core groups contributing disproportionately to their respective gonorrhea cases (66%, 79%, and 67%, respectively). Demographic and behavioral risk factors are explored and factors increasing odds ratios of core group inclusion are identified among the general population as well as three subpopulations: teens, adult MSM, and adult heterosexual core groups. Notable risk factors for gonorrhea core group inclusion across all subgroups include increased number of sexual partners, drug use, and HIV status. Notably, there is variation in some risk factors among subpopulations including race/ethnicity and sex while traveling internationally. Discussion: Among other factors, variations in public health policies and population level behavioral norms change the way gonorrhea spreads through a population. We report gonorrhea core group composition for a region with high gonorrhea rates. In particular, we discuss the role of teenagers in gonorrhea transmission dynamics, a typically under reported group. Understanding population specific dynamics is essential for formulating effective and targeted interventions.

Anonymous online surveys using financial incentives are an essential tool for understanding sexual networks and risk factors including attitudes, sexual behaviors, and practices. However, these surveys are vulnerable to bots attempting to exploit the incentive. We deployed an in-person, limited audience survey via QR code at select locations in North Carolina to assess geolocation application use among men who have sex with men to characterize the role of app usage on infection risk and behavior. The survey was unexpectedly posted on a social media platform and went viral. Descriptive statistics were performed on repeat responses, free-text length, and demographic consistency. Between August 2022 and March 2023, we received 4,709 responses. Only 13 responses were recorded over a 6-month period until a sharp spike occurred: over 500 responses were recorded in a single hour and over 2,000 in a single day. Although free-text responses were often remarkably sophisticated, many multiple-choice responses were internally inconsistent. To protect data quality, all online surveys must incorporate defensive techniques such as response time validation, logic checks, and IP screening. With the rise of large language models, bot attacks with sophisticated responses to open-ended questions pose a growing threat to the integrity of research studies.

Background: In the United States, Neisseria gonorrhoeae is the second most common reportable sexually transmitted infection amassing 601,319 cases in 2023. Notably, N. gonorrhoeae has developed antimicrobial resistance, necessitating ongoing surveillance. In response to this threat, the U.S. Centers for Disease Control and Prevention has established antimicrobial resistance surveillance networks including Strengthening the US Response to Resistant Gonorrhea (SURRG) and the Antibiotic Resistance Lab Network (ARLN). The SURRG project performs testing using a gradient strip method, the Etest, whereas ARLN laboratories perform testing by agar dilution, for determining minimum inhibitory concentration (MIC) values for N. gonorrhoeae . Methods: We compared the concordance of MIC values obtained using the Etest gradient strip method at a SURRG site in North Carolina compared with ARLN using the agar dilution method for 3 antibiotics: azithromycin, cefixime, and ceftriaxone. The MIC values and the corresponding interpretations for each agent were analyzed according to the recommendations of the Clinical and Laboratory Standards Institute and the Centers for Disease Control and Prevention. The essential agreements were assessed. Results: Between January 2018 and December 2024, a total of 1951 N. gonorrhoeae had corresponding isolates from the ARLN laboratory available for comparison, of which 1892 had corresponding Etest and agar dilution results for all 3 antibiotics. We found high levels of MIC agreement between both testing methods for each antimicrobial agent tested (azithromycin 95%, cefixime 98%, ceftriaxone 95%) over 6 years including for strains isolated from distinct anatomical sampling sites. Conclusions: The Etest method provides a robust alternative for accurately detecting antibiotic-resistant N. gonorrhoeae for public health surveillance, which may make them particularly useful in resource- or labor-limited settings.