Abstract
For the evaluation of infectious-diseases interventions, the transmissible nature of such diseases plays a central role. Agent-based models (ABM) allow for dynamic transmission modeling but publications are limited. We aim to provide an overview of important characteristics of ABM for decision-analytic modeling of infectious diseases. A case study of dengue epidemics illustrates model characteristics, conceptualization, calibration and model analysis. First, major characteristics of ABM are outlined and discussed based on ISPOR and ISPOR-SMDM Good Practice guidelines. Second, in our case study, we modeled a dengue outbreak in Cebu City (Philippines) to assess the impact interventions to control the relative growth of the mosquito population. Model outcomes include prevalence and incidence of infected persons. The modular ABM simulates persons and mosquitoes over an annual time horizon considering daily time steps. The model was calibrated and validated. ABM is a dynamic, individual-level modeling approach that is capable to reproduce direct and indirect effects of interventions for infectious diseases. The ability to replicate emerging behavior and to include human behavior or the behavior of other agents is a distinguishing modeling characteristic (e.g., compared to Markov models). Modeling behavior may, however, require extensive calibration and validation. The analyzed hypothetical effectiveness of dengue interventions showed that a reduced human-mosquito ratio of 1:2.5 during rainy seasons leads already to a substantial decrease of infected persons. ABM can support decision-analyses for infectious diseases including disease dynamics, emerging behavior, and providing a high level of reusability due to modularity.
Highlights
Decision analysis is a systematic approach to decision making under uncertainty [1]
Herd immunity refers to the effect that a partly vaccinated population can prevent the spread of an infectious disease, and thereby protect unvaccinated persons
The impact of potential mosquito control strategies on the number of new infections per week is displayed in Fig 2, it shows that a reduced human-mosquito ratio of 1:2.5 and 1:3 leads already to a substantial decrease of infected humans and smaller epidemics
Summary
The application of decision-analytic models (i.e. simulation models) allows the evaluation of new technologies (e.g., treatments, vaccinations, interventions against the spread of the disease) with respect to benefits, risks, harms and costs. Such computer simulation models are necessary where randomized controlled clinical trials or observational studies are missing, or not feasible [2]. The infectious disease may even be eliminated if the number of infected individuals decreases below a critical number It is paramount for decision-analytic models to capture the direct effect of interventions on the individuals under intervention and indirect effects on the population level including herd immunity [4,5,6,7]. The possibility of acquiring natural immunity following recovery from infection should be considered
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