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Quantifying the population-level impact of expanded antibiotic treatment for cholera outbreak management

Publié
Serveur de preprints
medRxiv
DOI
10.1101/2024.11.04.24316579

Background

Since 2021, there has been a resurgence in the number of cholera cases, countries affected, and the case fatality risk. Partly due to concerns about antibiotic resistance, current cholera treatment guidelines reserve antibiotics for severely symptomatic cases, recommending only supportive care (e.g., oral rehydration) for non-severe cases. However, it has been suggested that the reduction in transmissibility from antibiotic treatment may result in circumstances under which treating mild or moderate cases with antibiotics may have population-level benefits. We developed a compartmental model of cholera transmission in a non-endemic setting to quantify the potential impact of expanded antibiotic treatment on disease burden and antibiotic use. Through simulations, we evaluated different outbreak scenarios, by varying the reproductive number, care-seeking behavior, and proportion of non-severe cases receiving antibiotics. We found that expanding antibiotic treatment could significantly reduce the final outbreak size under certain outbreak characteristics. Under these different transmission scenarios, treating non-severe symptomatic infections with antibiotics decreased cholera transmission and, in some cases, the total number of antibiotic doses used. In high transmission settings, the benefits of expanded treatment are less pronounced and the strategy may lead to increased antibiotic use, potentially increasing the risk of antibiotic resistance. We show that the effectiveness of expanded antibiotic treatment is highly dependent on achieving high care-seeking rates among non-severely symptomatic infections and tailoring the approach to specific outbreak conditions. While expanding antibiotic eligibility could enhance outbreak control in some settings, careful consideration of antibiotic resistance risks is necessary in high-transmission contexts.

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