Category: MASON

New Paper: ABM Applied to the Spread of Cholera

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Cholera transmission through the interaction
of host and the environment
We are pleased to announce we have just had a paper published in Environmental Modelling and Software entitled “An Agent-based Modeling Approach Applied to the Spread of Cholera“
Research highlights include:
  • An agent-based model was developed to explore the spread of cholera.
  • The progress of cholera transmission is represented through a Susceptible-Exposed-Infected-Recovered (SEIR) model. 
  • The model integrates geographical data with agents’ daily activities within a refugee camp.
  • Results show cholera infections are impacted by agents’ movement and source of contamination. 
  • The model has the potential for aiding humanitarian response with respect to disease outbreaks.
Cholera dynamics when rainfall is introduced.

Spatial spread of cholera over the course of a year.
Study area
If the research highlights have not turned you off, the abstract to the paper is below:
“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.”
Finally to aide replication, experimentation or just explore how you can link raster and vector data in GeoMason, we have a dedicated website where you can download executables of the model along with the source code and associated data. Moreover we have provide a really detailed Overview, Design concepts, and Details (ODD) Protocol document of the model.

Full Reference:

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
DOI: 10.1016/j.envsoft.2014.08.027 (pdf)

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ABM, Disease, GeoMason, GIS, MASON

New Paper: ABM Applied to the Spread of Cholera

Posted on by
Cholera transmission through the interaction
of host and the environment
We are pleased to announce we have just had a paper published in Environmental Modelling and Software entitled “An Agent-based Modeling Approach Applied to the Spread of Cholera“
Research highlights include:
  • An agent-based model was developed to explore the spread of cholera.
  • The progress of cholera transmission is represented through a Susceptible-Exposed-Infected-Recovered (SEIR) model. 
  • The model integrates geographical data with agents’ daily activities within a refugee camp.
  • Results show cholera infections are impacted by agents’ movement and source of contamination. 
  • The model has the potential for aiding humanitarian response with respect to disease outbreaks.
Cholera dynamics when rainfall is introduced.

Spatial spread of cholera over the course of a year.
Study area
If the research highlights have not turned you off, the abstract to the paper is below:
“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.”
Finally to aide replication, experimentation or just explore how you can link raster and vector data in GeoMason, we have a dedicated website where you can download executables of the model along with the source code and associated data. Moreover we have provide a really detailed Overview, Design concepts, and Details (ODD) Protocol document of the model.

Full Reference:

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
DOI: 10.1016/j.envsoft.2014.08.027 (pdf)

Continue reading »
ABM, Disease, GeoMason, GIS, MASON

Modeling the outbreak, spread, and containment of tuberculosis

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It seems my interest into disease models is growing. While the development of the cholera model is still underway, over the summer I have had been working with a very talented high school student looking at the outbreak, spread and containment of tuberculosis (TB). Why might you ask? TB is a global problem with 1.8 billion people having a TB Infection, 8.8 million people infected with the TB disease, and around 1.5 million annual deaths. It is the second most common form of death from an infectious disease with the majority of cases in developing countries.

So we have been developing a model that explores how TB might manifest itself, spread within an urban setting and the potential to contain the disease. We have chosen as our test case the Kibera slum within Nairobi, Kenya. Agents in this model represent the residents of the Kibera slum. They are mobile and goal-orientated, seeking to fulfill one goal before moving on to the next. Goals are determined based on the agent’s characteristics (age, sex, etc.) as well as their needs (water, food, health etc.). The exact location they choose to go to is also affected by the distance. When agents interact with one another, they can be infected with TB. Infection is determined upon the amount of bacilli absorbed by agents and their immune response. The transition from infection to disease for HIV positive patients is also dependent on the patient’s CD4 cell count.  What you see below is a poster we presented at Krasnow Institute Retreat.

To give a sense of the dynamics of the model, the movie below shows agents moving around the slum and how their health status changes as time progresses.

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Agent Based Models, Disease, GeoMason, GIS, MASON, Slums

Modeling the outbreak, spread, and containment of tuberculosis

Posted on by
It seems my interest into disease models is growing. While the development of the cholera model is still underway, over the summer I have had been working with a very talented high school student looking at the outbreak, spread and containment of tuberculosis (TB). Why might you ask? TB is a global problem with 1.8 billion people having a TB Infection, 8.8 million people infected with the TB disease, and around 1.5 million annual deaths. It is the second most common form of death from an infectious disease with the majority of cases in developing countries.

So we have been developing a model that explores how TB might manifest itself, spread within an urban setting and the potential to contain the disease. We have chosen as our test case the Kibera slum within Nairobi, Kenya. Agents in this model represent the residents of the Kibera slum. They are mobile and goal-orientated, seeking to fulfill one goal before moving on to the next. Goals are determined based on the agent’s characteristics (age, sex, etc.) as well as their needs (water, food, health etc.). The exact location they choose to go to is also affected by the distance. When agents interact with one another, they can be infected with TB. Infection is determined upon the amount of bacilli absorbed by agents and their immune response. The transition from infection to disease for HIV positive patients is also dependent on the patient’s CD4 cell count.  What you see below is a poster we presented at Krasnow Institute Retreat.

To give a sense of the dynamics of the model, the movie below shows agents moving around the slum and how their health status changes as time progresses.

Continue reading »
Agent Based Models, Disease, GeoMason, GIS, MASON, Slums

New Publication: GIS and Agent-Based models for Humanitarian Assistance

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Inputs to the model
 
As the readers of the blog know, we have an interest in GIS, agent-based modeling and crowdsourcing. Now we have a paper that combines all these three elements. Its entitled “GIS and Agent-Based models for Humanitarian Assistance” and is published in Computers, Environment and Urban Systems. 
 
The model itself was written in MASON and uses extensively GeoMASON. Data comes from several different sources (both raster and vector) including OpenStreetMap and LandScan. Below you can read an abstract of the paper and see a movie of one of the scenarios.

“Natural disasters such as earthquakes and tsunamis occur all over the world, altering the physical landscape and often severely disrupting people’s daily lives. Recently researchers’ attention has focused on using crowds of volunteers to help map the damaged infrastructure and devastation caused by natural disasters, such as those in Haiti and Pakistan. This data is extremely useful, as it is allows us to assess damage and thus aid the distribution of relief, but it tells us little about how the people in such areas will react to the devastation. This paper demonstrates a prototype spatially explicit agent-based model, created using crowdsourced geographic information and other sources of publicly available data, which can be used to study the aftermath of a catastrophic event. The specific case modelled here is the Haiti earthquake of January 2010. Crowdsourced data is used to build the initial populations of people affected by the event, to construct their environment, and to set their needs based on the damage to buildings. We explore how people react to the distribution of aid, as well as how rumours relating to aid availability propagate through the population. Such a model could potentially provide a link between socio-cultural information about the people affected and the relevant humanitarian relief organizations.”

Full Reference: 

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

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ABM, ABM Examples, Crowdsourcing, GeoMason, GIS, MASON, social media, VGI

New Publication: GIS and Agent-Based models for Humanitarian Assistance

Posted on by
Inputs to the model
 
As the readers of the blog know, we have an interest in GIS, agent-based modeling and crowdsourcing. Now we have a paper that combines all these three elements. Its entitled “GIS and Agent-Based models for Humanitarian Assistance” and is published in Computers, Environment and Urban Systems. 
 
The model itself was written in MASON and uses extensively GeoMASON. Data comes from several different sources (both raster and vector) including OpenStreetMap and LandScan. Below you can read an abstract of the paper and see a movie of one of the scenarios.

“Natural disasters such as earthquakes and tsunamis occur all over the world, altering the physical landscape and often severely disrupting people’s daily lives. Recently researchers’ attention has focused on using crowds of volunteers to help map the damaged infrastructure and devastation caused by natural disasters, such as those in Haiti and Pakistan. This data is extremely useful, as it is allows us to assess damage and thus aid the distribution of relief, but it tells us little about how the people in such areas will react to the devastation. This paper demonstrates a prototype spatially explicit agent-based model, created using crowdsourced geographic information and other sources of publicly available data, which can be used to study the aftermath of a catastrophic event. The specific case modelled here is the Haiti earthquake of January 2010. Crowdsourced data is used to build the initial populations of people affected by the event, to construct their environment, and to set their needs based on the damage to buildings. We explore how people react to the distribution of aid, as well as how rumours relating to aid availability propagate through the population. Such a model could potentially provide a link between socio-cultural information about the people affected and the relevant humanitarian relief organizations.”

Full Reference: 

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

Continue reading »
ABM, ABM Examples, Crowdsourcing, GeoMason, GIS, MASON, social media, VGI

Distributed MASON

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Last week, the Center for Social Complexity at GMU, hosted Prof. Vittorio Scarano and Carmine Spagnuolo from the ISISLab of the Università degli Studi di Salerno who have been working on a distributed version of MASON (DMason). The idea is that one can create an agent-based model in MASON and then use the framework to easily distribute it over many machines. The movie below shows an example of what can be done. More information can be found here.

However, if you don’t use MASON, you might also be interested in Repast for High Performance Computing

Continue reading »
ABM, ABM Platforms, MASON

Distributed MASON

Posted on by
Last week, the Center for Social Complexity at GMU, hosted Prof. Vittorio Scarano and Carmine Spagnuolo from the ISISLab of the Università degli Studi di Salerno who have been working on a distributed version of MASON (DMason). The idea is that one can create an agent-based model in MASON and then use the framework to easily distribute it over many machines. The movie below shows an example of what can be done. More information can be found here.

However, if you don’t use MASON, you might also be interested in Repast for High Performance Computing

Continue reading »
ABM, ABM Platforms, MASON
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