An agent-based approach for modeling dynamics of contagious disease spread

Pérez, Liliana; Dragićević, Suzana

doi:10.1186/1476-072x-8-50

Cited by 298 publications

(221 citation statements)

References 27 publications

(25 reference statements)

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“…A MAS splits processes into many components, thus relying on empirical studies and an extensive literature review to parameterise the decision rules (Kostova et al, 2004). MASs have seldom been used to study the epidemiology of infectious diseases, with notable exceptions however (Bonnell et al, 2010;Linard et al, 2009;Perez and Dragicevic, 2009;Roche et al, 2008). The subtle interplay of causes and effects, and the presence of feedbacks in MASs, allow exploration of the mechanisms driving disease dynamics better than with classical continuous (differential equations) and discrete (discrete-time equations) dynamics system models (Bithell et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

The landscape epidemiology of foot-and-mouth disease in South Africa: A spatially explicit multi-agent simulation

Dion

VanSchalkwyk

Lambin

2011

Ecological Modelling

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a b s t r a c tThis study aimed at understanding how landscape heterogeneity influences outbreaks of contagious diseases in southern Africa. Landscape attributes influence patterns of movement and behaviour of animal hosts, virus spread and survival, as well as land use practices. A multi-agent simulation was developed to represent the spatial and temporal dynamics of pathogens between human-livestock and wildlife interfaces at the fringe of large wildlife conservation areas. The model represents the three main elements associated with epidemics -populations, space, and time -to simulate direct contacts between wildlife and livestock. The dynamics of these populations emerge from interactions between agents and the landscape. The model was calibrated to represent the transmission of foot-and-mouth disease through direct contact at the border of the Kruger National Park in South Africa. In the region, African buffaloes (Syncerus caffer) act as reservoirs of the virus and spread the infection to domestic cattle bordering the park. We tested the sensitivity of various factors influencing contact rate between buffaloes and cattle, and thus the risk of foot-and-mouth disease transmission. Results show that cattle-buffalo contacts mostly depend on the range of displacements of cattle and buffaloes, as influenced by the landscape configuration, and on the number of fence breakages multiplied by the time between breakage and repair. Contacts take place not only close to water-points but also in grazing areas, within an area up to 6 km from the fence.

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Section: Introductionmentioning

confidence: 99%

The landscape epidemiology of foot-and-mouth disease in South Africa: A spatially explicit multi-agent simulation

Dion

VanSchalkwyk

Lambin

2011

Ecological Modelling

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“…The spread of infectious diseases has been simulated using two major classes of models: multi-agent models which aim at studying the phenomenon at the individual level [26,27] and meta-population models that operate at an aggregate level [2]. The plausibility and usefulness of individual-based models and simulations can be questioned since it is a quasi-impossible task to try to plausibly model and simulate the activities and mobility behaviours of individuals in an urban area.…”

Section: Resultsmentioning

confidence: 99%

Integrated epidemiologic simulation for person to person contagion through urban mobility within GIS

Haddad

Moulin

Thériault

et al. 2012

Proceedings of the First ACM SIGSPATIAL International Workshop on Use of GIS in Public Health

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In recent years, advances in Health Geography, Geographical Epidemiology and Public Health Informatics have led to an extensive use of Geographic Information Systems (GIS) to study a variety of public health issues. Considering infectious disease outbreaks, time becomes a critical factor and Public Health officers require tools to support rapid decision making. In this context, GIS technology presents some limits. Mainly, the study of communicable diseases requires the development of complicated spatial-temporal models which is often time and effort consuming. In addition, this type of dynamic analysis is hard to realize by means of the GIS functionalities commonly available. Addressing such limits, we present in this paper a new GIS-based spatial-temporal simulation approach and software to support public health decision making in the context of communicable diseases. Our approach stands out by the integrative perspective and the explicit spatial aspect that it offers. On the one hand, it fully integrates epidemiological, mobility and GIS-data models at an aggregate population level in order to support public health decision making. This is made possible because our approach is built on data automatically processed from transportation surveys that are widely available, at least in North America and Europe. Our approach is thus simple and can be promptly put into use. On the other hand, our approach particularly aims at supporting decision makers with respect to "spatialized" intervention policies. Mainly, it allows for the assessment of different public intervention actions in different spatial locations of the studied area and the evaluation of their effects on the disease spatial evolution and distribution.

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“…In Canada, a GIS has been developed that can simulate the spread of a communicable disease, such as measles, within a populated area. The system is built on a complex algorithm that describes both the communicable disease stages and the life paths of people responsible for the transmission of disease within an urban area [41]. This system is composed of multiple layers including information on population density, the transportation network and different types of land use.…”

Section: Discussionmentioning

confidence: 99%

Use of a geographic information system to map cases of measles in real-time during an outbreak in Dublin, Ireland, 2011

et al. 2012

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In 2011, there was a large measles outbreak in Dublin. Nationally 285 cases were notified to the end of December 2011, and 250 (88%) were located in the Dublin region. After the first case was notified in week 6, numbers gradually increased, with 25 notified in June and a peak of 53 cases in August. Following public health intervention including a measles-mumps-rubella (MMR) vaccination campaign, no cases were reported in the Dublin region in December 2011. Most cases (82%) were children aged between 6 months and 14 years, and 46 cases (18%) were under 12 months-old. This is the first outbreak in Dublin to utilise a geographic information system for plotting measles cases on a digital map in real time. This approach, in combination with the analysis of case notifications, assisted the department of public health in demonstrating the extent of the outbreak. The digital mapping documented the evolution of two distinct clusters of 87 (35%) cases. These measles cases were infected with genotype D4-Manchester recently associated with large outbreaks across Europe. The two clusters occurred in socio-economically disadvantaged areas and were attributable to inadequate measles vaccination coverage due in part to the interruption of a school-based MMR2 vaccination programme.

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An agent-based approach for modeling dynamics of contagious disease spread

Cited by 298 publications

References 27 publications

The landscape epidemiology of foot-and-mouth disease in South Africa: A spatially explicit multi-agent simulation

The landscape epidemiology of foot-and-mouth disease in South Africa: A spatially explicit multi-agent simulation

Integrated epidemiologic simulation for person to person contagion through urban mobility within GIS

Use of a geographic information system to map cases of measles in real-time during an outbreak in Dublin, Ireland, 2011

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