Zoonotic visceral leishmaniasis (ZVL) is a serious neglected tropical disease that is endemic in 98 countries. ZVL is primarily transmitted via a sand fly vector. In the United States, it is enzootic in some canine populations; it is transmitted from infectious mother to pup transplacentally, and vector-borne transmission is absent. This absence affords a unique opportunity to study (1) vertical transmission dynamics in dogs and (2) the importance of vertical transmission in maintaining an infectious reservoir in the presence of a vector. In this paper, we present Bayesian compartmental models and reproductive number formulations to examine (1) and (2), providing a mechanism to plan and evaluate interventions in regions where both transmission modes are present. First, we propose an individual-level susceptible, infectious, removed (SIR) model to study the effect of maternal infection status during pregnancy on pup infection progression. We provide evidence that pups born to diagnostically positive mothers during pregnancy are more likely to become diagnostically positive both earlier in life, and at some point during their lifetime, than those born to diagnostically negative mothers. Second, we propose a population-level SIR model to study the impact of a vertically maintained reservoir on propagating infection in a naive canine population through emergent vector transmission using simulation studies. We also present reproductive numbers to quantify contributions of vertically infected and vector-infected dogs to maintaining infection in the population. We show that a vertically maintained canine reservoir can propagate infection in a theoretical naive population in the presence of a vector.
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http://dx.doi.org/10.1111/biom.13192 | DOI Listing |
Eur J Drug Metab Pharmacokinet
November 2024
School of Pharmacy, University of Eastern Finland, Yliopistonranta 1 C, 70210, Kuopio, Finland.
Background And Objective: For neonates and infants receiving intermittent vancomycin infusions, the area under the concentration-time curve during 24 h (AUC24) is often estimated with Bayesian forecasting using one or more measured vancomycin concentrations. When practical peak and trough concentrations are measured at steady state, AUC24 can also be calculated with first-order steady-state equations for a one-compartment model (Sawchuk-Zaske method), but previously this method has been applied only for adults. The objective of this study was to compare AUC24 values obtained with the Sawchuk-Zaske method and two Bayesian models.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
October 2024
Division of Viral Diseases, Centers for Disease Control and Prevention, Atlanta, GA 30329.
Mumps outbreaks among fully vaccinated young adults have raised questions about potential waning of immunity over time and need for a third dose of the measles, mumps, rubella (MMR) vaccine. However, there are currently limited data on real-life effectiveness of the third-dose MMR vaccine in preventing mumps. Here, we used a deterministic compartmental model to infer the effectiveness of the third-dose MMR vaccine in preventing mumps cases by analyzing the mumps outbreak that occurred at the University of Iowa between August 24, 2015, and May 13, 2016.
View Article and Find Full Text PDFHeliyon
October 2024
Laboratory of Applied Physics Informatics and Statistics (LPAIS), Faculty of Sciences, Sidi Mohamed Ben Abdellah University, Fez, Morocco.
Compartmental models have emerged as robust computational frameworks and have yielded remarkable success in the fight against COVID-19. This study proposes a vaccination-based compartmental model for COVID-19 transmission dynamics. The model reflects the specific stages of COVID-19 infection and integrates a vaccination strategy, allowing for a comprehensive analysis of how vaccination rates influence the disease spread.
View Article and Find Full Text PDFInfect Dis Model
March 2025
Laboratoire de Biomathématiques et d'Estimations Forestières, University of Abomey-Calavi, Cotonou, Benin.
Am J Epidemiol
September 2024
Department of Epidemiology and Population Health, School of Medicine, Stanford University.
Understanding whether influenza vaccine promotion strategies produce community-wide indirect effects is important for establishing vaccine coverage targets and optimizing vaccine delivery. Empirical epidemiologic studies and mathematical models have been used to estimate indirect effects of vaccines but rarely for the same estimand in the same dataset. Using these approaches together could be a powerful tool for triangulation in infectious disease epidemiology because each approach is subject to distinct sources of bias.
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