The Zagreb index, which is defined as the sum of squares of degrees of the nodes of a tree, was studied in previous works by martingale techniques for random non-plane recursive trees and classes of random trees which are close to random plane recursive trees. These techniques are not easily amended to the generalized Zagreb index, which is defined similarly but with squares replaced by higher powers. We use the moment-transfer approach to (i) obtain the first-order asymptotics of moments and (ii) prove limit laws for the (suitably normalized) generalized Zagreb index for random non-plane and plane recursive trees. For the former, we show that for all higher powers the limit law is normal; for the latter, we show for cubes and fourth powers that it is a non-normal law.

Commonly used components of health risk assessments and outbreak investigations are the proportion of the general population exposed to potential sources, often coming from national surveys collected with one reference period, such as 7 days. However, risk assessors may need this value for a different period of time (e.g. 1 day, a full year, etc.) and outbreak investigators may need a reference period that matches their case questionnaire. Use of these proportions is biased if the reference period does not match what is needed. Three surveys that collected exposure information with more than one reference group were used to fit six models that were developed to estimate the relationship between proportion and reference period length, and thus, convert proportions collected with one reference period to any desired reference period. A practical implementation of the best model is provided in a spreadsheet for health practitioners, such as those working in risk assessment or outbreaks who need to convert proportions to a new reference period. The conversion method can be used in any subject matter across the sciences, where surveys collect the proportion of respondents who experienced an event in a defined reference period.

Rabies is a fatal zoonotic disease causing an estimated 59000 annual human deaths globally and approximately 523 in Kenya, with children disproportionately affected. Despite evidence that school-based educational interventions effectively increase rabies awareness and prevention among children, its implementation in Kenya is limited. This study aimed at utilizing an education programme to increase rabies awareness among primary school learners and evaluate their knowledge uptake. A quasi-experimental study was conducted among 210 learners from four primary schools (two urban, two rural). Pre-tested questionnaires assessed rabies awareness before and after rabies training sessions. Differences between urban and rural schools were assessed using χ2 tests, while Wilcoxon signed-rank test was used for pre- and post-training scores. Post-training, overall knowledge scores improved from 6.14 to 7.61(p < 0.001), with significant increase in learners’ knowledge on rabies transmission, zoonosis, and the importance of annual dog vaccination. Attitudes and perceptions improved from 3.23 to 4.03 (p < 0.001), particularly health-seeking behaviour and reporting post dog bite. In conclusion, school-based rabies education significantly improved learners’ awareness. Being the first report of such intervention in Kenya, it could serve as a model for other zoonoses.

We consider the problem of estimating and deriving confidence intervals for change points in linear models with heteroscedastic errors. A CUSUM process-based estimator is proposed, and we establish its asymptotic properties when the linear regression model exhibits change points in both the regression parameters and the distribution of the errors. This theory motivates the construction of confidence sets for multiple change points by refining preliminary change point estimators and approximating their distribution in a way that is robust to heteroscedasticity. Monte Carlo experiments indicate that the proposed confidence intervals achieve accurate empirical coverage for change-point locations under both homoscedastic and heteroscedastic error structures. In two data applications, we apply the proposed confidence intervals to examine changes in the flattening of the New Keynesian Phillips curve and in cryptocurrency risk factors.

Blockchain technology has gained immense popularity in enhancing the security and privacy of Information Systems (IS), reflected in exponential increases in published research articles. The rapid proliferation of published research presents significant challenges for manual analysis and synthesis due to the vast volume of information. To this end, we adopted the Computational Literature Review (CLR) and Latent Dirichlet Allocation (LDA) topic modeling techniques to analyze the impact of the pertinent literature. This study is among the first studies in the IS field to apply the CLR technique in the Legal-Tech context, focusing on security, privacy, and governance in blockchain systems. Using CLR and LDA topic modeling, we identified 10 topics related to security and privacy, each accompanied by an in-depth description aligned with relevant policies and regulations. Our findings identify both the strengths and current gaps in the literature, providing valuable insights into ongoing scholarly discourse. Through our analysis, we outline future research directions that align with the evolving dynamics of blockchain technology, data management, and policy implications, aiming to guide further academic and practical advancements in the IS field.

Syphilis remains a significant transfusion-transmitted infection. In Colombia, routine epidemiological surveillance primarily targets pregnant women, leaving the burden of infection among the apparently healthy population. This study determined the incidence of Treponema pallidum and its associated factors in donors at a blood centre in Colombia between 2012 and 2024. A retrospective cohort study was conducted, analyzing 64,166 repeat blood donors. Incidence was calculated using 95% confidence intervals. Associations with demographic and donation-related variables were assessed using Chi-square test and potential confounders were adjusted using a multivariable regression model. The overall incidence of syphilis was 5.1 per 1,000 donors. The associated factors included age, sex, occupation, collection site, and donor type. Higher incidence proportions were observed in male donors (RR = 1.76), individuals aged between 60 and 65 years (RR = 2.43), unemployed individuals (RR = 3), donors collected at the centre (RR = 1.45), and replacement donors (RR = 3.51). These incidences indicate ongoing transmission within a low-risk population. The highest incidence in some groups enabled the generation of hypotheses about differential exposure patterns, guiding subsequent aetiological studies, and optimizing donor selection. Understanding local epidemiology is essential for designing public health interventions tailored to the specific epidemiological profile.