A cellular model for pandemic influenza outbreak simulation
and mitigation
Paper Presenter: Satish K Ramchurn, Department of Physics, Faculty of Science,
University of Mauritius
Author(s):
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Satish K Ramchurn, Department of Physics, Faculty of Science, University of
Mauritius
Smita SD Goorah, Department of Medicine, Faculty of Science, University of
Mauritius
B Thakoor, Department of Physics, Faculty of Science, University of Mauritius
RL Roopchund, Department of Physics, Faculty of Science, University of Mauritius
Introduction
Influenza is an airborne infectious disease which has a huge public health impact
worldwide. Only in the twentieth century, there have been three pandemic outbreaks of
influenza: in 1918, 1957 and 1968 causing widespread mortality especially amongst
healthy people. The 1918 outbreak was the most deadly killing 20-40 million people
worldwide with nearly half of these deaths in young adults in the 20-40 year age group. It
is generally agreed that the world is moving closer to another pandemic. The country most
affected by the current avian H5N1 influenza virus is Indonesia where there have been
several suspected cases on the virus being directly transmitted to humans and causing
deaths. Disease surveillance systems have been stepped up throughout the world to act
quickly should there be the beginnings of a new pandemic. Since this infection is
unpredictable and can propagate rapidly, a high state of alert must be maintained and
timely public health action initiated. Measures to mitigate the effects of this pandemic
must necessarily have a strong medical component. However, the simulation of the
dynamical evolution of an outbreak is also crucial to inform on the appropriateness and
timing of public health interventions. This is important particularly for a small island state
like Mauritius where resources (human, financial and others) are limited and should be
utilized to maximal effectiveness.
Method
A cellular model for simulating the spatio-temporal evolution of an airborne viral infection
like influenza was developed. The region of interest was divided into cells. Each cell was
assumed to be homogeneous. The development of the viral infection within a cell was
characterized using an SIR (susceptible-infectious-removed) compartmental approach.
Intercellular interactions depended on the distance between the cells. These interactions
were described by a set of differential equations with time as the independent variable.
The differential equations were computationally integrated to simulate the propagation of
the virus throughout the population for a population homogeneously distributed in the cells
and with one infected person randomly located in one of the cells.
Results
In our model, the wavefront of the infection was found to evolve radially from the cell
containing the index case.
Discussion
The proposed model captures the intuitive radial spread of the airborne infection for a
randomly located index case in homogeneously distributed populations. This is the simplest
application of the model. By ascribing features to each cell to mimic more realistic actual
conditions, one should also be able to describe the spread of the infection in cases such as
in populations distributed inhomogeneously in the cells and for cells with geographic
structures. Since the propagation of airborne infectious diseases is preventable by timely
public health measures, rapid identification of index cases and modeling the potential
spread of the infection in the community can help public health authorities rapidly identify
vulnerable geographic locations and take disease mitigating measures in them. Dynamical
models such as the one proposed here could be vital tools in mitigating the effects of an
influenza pandemic outbreak in Mauritius and in controlling the propagation of infectious
diseases in general.