Agent-based Models for Disease Modeling

Agent-based models (ABMs) offer an alternative approach to classical mathematical models or discrete choice models when it comes to disease models. Compared to other modeling approaches (e.g. system dynamics, bayesian networks) ABMs allow us to focus on the dynamic interactions between individuals and their impact on the system under study. Moreover, ABMs are particularly suitable when the purpose of the model is for developing an understanding of the system under investigation, where assumptions about processes and interactions can be explored through simulation. Also by linking agent-based models  to  GIS  allows  us  to  explore  and  understand  the complexity  of  disease  transmission  over  space and time.

Over the last several years we have been exploring how one can utilize ABMs and GIS to explore a range of disease, from the spread of cholera in refugee camps, or Tuberculosis (TB) in slums or to the recent Ebola outbreak in West Africa.

Cholera in Refugee Camps

Cholera is an intestinal disease and is characterized by diarrhea and severe dehydration. While cholera has mainly been eliminated in regions that can provide clean water, adequate hygiene and proper sanitation; it remains a constant threat in many parts of Africa and Asia. Within this paper, we develop an agent-based model that explores the spread of cholera in the Dadaab refugee camp in Kenya. Poor sanitation and housing conditions contribute to frequent incidents of cholera outbreaks within this camp. We model the spread of cholera by explicitly representing the interaction between humans and their environment, and the spread of the epidemic using a Susceptible-Exposed-Infected-Recovered model. Results from the model show that the spread of cholera grows radially from contaminated water sources and seasonal rains can cause the emergence of cholera outbreaks. This modeling effort highlights the potential of agent-based modeling to explore the spread of cholera in a humanitarian context.

To find out more click here.

Tuberculosis (TB) in Slums

Tuberculosis (TB) is a global problem and especially in developing countries. After human immunodeficiency virus (HIV) it is the most common form of death from an infectious disease. However, it is still unknown exactly how it spreads within a population. A geographic explicit agent-based model, with humans as agents, was created and applied to study the TB problem. Specifically the model was developed to see what epidemiological dynamics may occur, and what could be learned about the spreading of the disease. The model was developed in MASON and utilizes the GeoMason GIS extension. A Susceptible-Exposed-Infectious-Recovered (SEIR) submodel was created to model TB progression and linked to daily human activities. Th e slum of Kibera, Kenya (the largest urban slum in Africa, and an area where TB and HIV is particularly rampant) was chosen as a test-case. Detailed geospatial and demographic information from Kibera was used for the instantiation of the models spatial environment and demographic properties of the agents. Preliminary results obtained from standard model runs show that TB epidemics progress in staircase patterns of emergence and stabilization. Furthermore, it was found that TB was creating hotspots, or pockets of dense disease concentration, from where it was spreading. The results and lessons gleaned from the model can be easily incorporated into current health policies to mitigate TB's negative impact. Furthermore, the research shows the potential of ABMs in investigating infectious diseases.

To find out more click here.

Ebola outbreak in West Africa

While we know how Ebola spreads and infects people from an epidemiological standpoint much less is known about how to satisfactorily model it. Common approaches are to use mathematical or statistical models which, while useful, have been criticized for being ill-suited vis-a-vis complex natural-human systems because they (1) do not incorporate direct contact between individuals or their environment but rather use uniform mixing, (2) treat people as aggregate individuals, (3) miss the heterogeneity of the human population and (4) do a poor job representing behavior. By focusing on heterogeneous individuals operating over different social and geographical spaces we can capture a fundamentally different view of the dynamics of the disease. In this model we  link ABMs to GIS, allowing exploration and understanding of disease transmission over space. The goal of this model is to develop projections of Ebola-spread trajectories within realistic environments (i.e. Sierra Leone, Liberia and Guinea) for use supporting humanitarian interventions.

This model is being developed with Rohan Suri and the prototype model can be downloaded from here.

Selected Publications:
Jacobsen, K.H., Aguirre, A.A., Bailey, C.L., Baranova, A.V., Crooks, A.T., Croitoru, A., Delamater, P.L., Gupta, J., Kehn-Hall, K., Narayanan, A., Pierobon, M., Rowan K.E., Schwebach, J.R., Seshaiyer, P., Sklarew, D.M., Stefanidis, A. and Agouris, P. (2016), Lessons from the Ebola Outbreak: Action Items for Emerging Infectious Disease Preparedness and Response, EcoHealth, 13(1): 200-212 (pdf)
Radzikowski, J., Stefanidis, A., Jacobsen K.H., Croitoru, A., Crooks, A.T. and Delamater, P.L. (2016), The Measles Vaccination Narrative in Twitter: A Quantitative Analysis, JMIR Public Health and Surveillance, 2(1): e1. (pdf)

Crooks, A.T. and Hailegiorgis, A.B. (2014), An Agent-based Modeling Approach Applied to the Spread of Cholera, Environmental Modelling and Software, 62: 164-177 (pdf)

Crooks, A.T. and Chopra, P. (2014), An Agent-based Model for the Spread and Containment of Tuberculosis, The Association of American Geographers (AAG) Annual Meeting, 8th-12th April, Tampa, FL. (pdf)

Crooks, A.T. and Hailegiorgis, A. (2013), Disease Modeling Within Refugee Camps: A Multi-agent Systems Approach, in Pasupathy, R., Kim, S.-H., Tolk, A., Hill, R. and Kuhl, M. E. (eds.), Proceedings of the 2013 Winter Simulation Conference, Washington, DC, pp 1697-1706. (pdf)

Crooks, A.T. and Wise, S. (2013),
GIS and Agent-Based models for Humanitarian Assistance, Computers, Environment and Urban Systems, 41: 100-111. (pdf)

Gulden, T., Harrison, J. F. and Crooks, A.T. (2011), Modeling Cities and Displacement through an Agent-based Spatial Interaction Model. The Computational Social Science Society of America Conference (2011), Santa Fe, NM. (pdf)

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