Why should we apply ABM for decision analysis for infectious diseases?-An example for dengue interventions

Autor: Kurt Junshean Espinosa, Jagpreet Chhatwal, Nikolas Popper, Beate Jahn, Florian Miksch, Uwe Siebert
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Viral Diseases
Systems Analysis
Time Factors
Computer science
Epidemiology
Philippines
Psychological intervention
Social Sciences
Disease
Disease Vectors
Mosquitoes
Systems Science
Dengue fever
Dengue Fever
Dengue
Geographical Locations
0302 clinical medicine
Agent-Based Modeling
Medicine and Health Sciences
Psychology
Public and Occupational Health
Multidisciplinary
Transmission (medicine)
030503 health policy & services
Incidence
Simulation and Modeling
Eukaryota
Infectious Disease Epidemiology
Vaccination and Immunization
Insects
Infectious Diseases
Risk analysis (engineering)
Calibration
Physical Sciences
Medicine
0305 other medical science
Research Article
Neglected Tropical Diseases
Computer and Information Sciences
Asia
Arthropoda
Science
030231 tropical medicine
Immunology
Markov model
Research and Analysis Methods
Communicable Diseases
Decision Support Techniques
03 medical and health sciences
medicine
Humans
Animals
Behavior
Organisms
Biology and Life Sciences
medicine.disease
Tropical Diseases
Invertebrates
Dengue outbreak
Insect Vectors
Species Interactions
People and Places
Preventive Medicine
Mathematics
Decision analysis
Zdroj: PLoS ONE, Vol 14, Iss 8, p e0221564 (2019)
PLoS ONE
ISSN: 1932-6203
Popis: 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.
Databáze: OpenAIRE
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