46 Modeling the Impact of Antibiotic Expansion in Moderately Symptomatic Children under Five during Cholera Outbreaks​

Faculty Mentor: Lindsay Keegan (Internal Medicine, University of Utah)

Cholera is an acute diarrheal infection caused by the bacterium Vibrio cholerae (WHO, 2024). It is primarily transmitted through the consumption of contaminated food and water or via environmental exposure. It is prevalent in developing countries, particularly in regions with poor sanitation, rapid urbanization, conflict zones, and famine (WHO, 2025). The primary treatment for cholera is rehydration therapy, which uses either oral rehydration solutions or intravenous fluids in severe cases. Antibiotics can shorten illness duration and reduce bacterial shedding, helping limit transmission. However, they are generally reserved for severe cases to lower the risk of developing antibiotic resistance (Das et al., 2020). Recent studies show that expanding antibiotic treatment to moderately symptomatic individuals could further reduce overall transmission and outbreak size and may result in fewer total antibiotic doses used under specific conditions (LaPrete et al., 2025).

Children under five are the most vulnerable age group that experiences disproportionately high infection and mortality rates due to underdeveloped immune systems and a high prevalence of malnutrition (Siamalube & Ehinmitan, 2025). Despite the fact that children have a ten times greater risk of death than adults, they are often underrepresented in cholera surveillance and research, which limits understanding of pediatric transmission dynamics (Williams & Berkley, 2018). Addressing this gap is crucial for designing targeted intervention strategies and improving outcomes of children during cholera outbreaks. The objective of my research is to evaluate the impact of prioritizing children under five when expanding antibiotic treatment to moderately symptomatic cases.

The Susceptible-Exposed-Infected-Removed (SEIR) model is a mathematical framework that describes the transmission of infectious diseases within a population. It divides the population into compartments based on their disease status and tracks how individuals move between these states. To account for age-based differences in transmission and outcomes, I modified the SEIR model developed by LaPrete et al. (2025) by separating children under five into their own set of compartments.

This summer, my primary focus was on expanding the SEIR model to better reflect age-based differences in cholera transmission and outcomes. I introduced an age-structured framework by dividing the population into two groups: children under five and individuals five and older. To simulate a scenario in low-resource settings where antibiotic availability and access to treatment are limited, I set the moderate infection treatment effort parameter q for five and older to zero. This allowed me to assess the potential public health impact of prioritizing antibiotic treatment for moderately symptomatic children under five, a group that often bears the highest burden during cholera outbreaks.

To break the model by age, I duplicated each disease state in the SEIR structure to create parallel compartments for children under five. This resulted in separate compartments for exposed, infected (mild, moderate, severe), asymptomatic, recovered, and deceased individuals in each age group. I then assigned different parameter values to children and adults based on findings from the literature. These included the aging rate (ω), relative infectiousness of adults (vₒ), pediatric probability of being asymptomatic (εₐ,ᵧ), pediatric probability of developing severe symptoms (εn,ᵧ), pediatric probability of seeking treatment when severely ill (εn,n,ᵧ), pediatric mortality rates for both moderate (μn,ᵧ) and severe (μn,ᵧ) infections, and relative reduction in infectiousness among moderately symptomatic children (δᵧ). In general, children under five had higher probabilities of developing symptoms, seeking care, and experiencing mortality after getting infected. These values were varied using Latin Hypercube Sampling to simulate a wide range of outbreak scenarios and reflect uncertainty in the literature.

The updated model was built in R to include age-specific compartments and treatment strategies. This structure allows for testing how expanded treatment focused on children under five affects outbreak outcomes, compared to treating the entire population. It sets up a foundation for exploring whether prioritizing treatment for children can shift outbreak dynamics and guide public health decisions. Currently, I am refining parameter values and running simulations in R. My next steps include evaluating results with the updated parameters, exploring the long-term impact of targeted treatment on antimicrobial resistance, and learning more about bifurcation points and Filippov models to better understand cholera transmission dynamics.

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