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Modern Geomatics Technologies and Applications

Simulation of malaria spreading using an agent-based model: Applying environmental
factors

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Navid Mahdizadeh Gharakhanlou , Navid Hooshangi 2*

1 Faculty of Geodesy and Geomatics Engineering, K.N. Toosi University of Technology, No. 1346, ValiAsr
Street, Mirdamad cross, Tehran, Iran
2 Department of Surveying Engineering, College of Earth Sciences Engineering, Arak University of Technology,
Daneshgah St., Arak, Iran
* Hooshangi@arakut.ac.ir

Abstract: Malaria is currently considered as one of the major health problems due to its spread, incidence rate, and
mortality. The spread of malaria is a complex phenomenon that is affected by many factors, especially environmental
factors. Agent-based modelling is a new approach in the field of complex phenomena modelling so that simulates
phenomena with the help of agents, the environment, as well as considering interactions between agents and also agents
with the environment according to reality. The main objective of this paper is to simulate the spread of malaria by using
an agent-based model (ABM) in which the effects of environmental factors are considered. The process of doing this paper
was carried out in several steps: first, several analyses were performed on each environmental factor of air temperature,
relative humidity, land vegetation, altitude, and distance from water sources. Next, the implementation of the proposed
ABM was explicitly explained. Then, the susceptible-exposed-infectious-recovered-susceptible (SEIRS) model was
described. After that, the calculation of malaria-transmission probability was explained, and finally, the assumptions
considered in the model were expressed as well as the calibration and validation of the proposed ABM. The results of the
model demonstrated the great potential of ABM in simulating the spread of vector-borne diseases such as malaria.
Regarding the results of this research, agent-based modelling, as a robust approach in predicting malaria spreading, can
assist health policymakers in designing health-related policies.

1. Introduction
Given the importance of epidemics in humans’ health, many interdisciplinary efforts have been made to study the process
of disease transmission. In this case, the science of epidemiology has gone through the modelling of epidemic diseases spreading
in society so that its main goal is to comprehend the time as well as the way they spread [1].
Malaria, as one of the most concerned parasitic diseases, affects 200 to 300 million people worldwide annually, of which
1.5 to 2.7 million die [2]. Malaria is a parasitic disease caused by protozoan parasites of the genus Plasmodium so that the
pathogen is transmitted to humans by the bites of infected Anopheles mosquitoes [3].
Transmission of many diseases through vectors (i.e., an infected animal or insect carrying an infectious pathogen and
transmitting it into another person or animal), including malaria, is strongly influenced by environmental factors [4]. Humans,
in order to control disease-spreading as well as be protected against diseases, need to study the environment and also factors
affecting disease spreading.
Extensive research has been conducted around the world in order to investigate the relationship of environmental factors
with the incidence and prevalence of malaria [5-8]. The results of most studies represented a strong and significant correlation
between meteorological elements including air temperature, relative humidity, altitude, land vegetation, as well as the distance
from water sources with cases of malaria. Alternatively, several modelling approaches including the ordinary differential
equation (ODE) [9], cellular automata (CA) [10], and agent-based modelling (ABM) [11, 12] have been used to simulate the
spread of diseases. Among these approaches, ABM has been commonly used due to its capabilities in simulating the interactions
as well as movements of individuals.
ABM is one of the complex-phenomena modelling approaches. Various sciences have always tried to break systems down
into smaller components and analyse them, while the method used in the ABM approach is to put simple components together
to create complex behaviours [13]. In the ABM approach, each individual (i.e., agent) in interaction with other agents, according
to the behaviours and rules defined for it, senses the environment and decides to perform the appropriate action [14]. ABM is
used to overcome problems such as population heterogeneity as well as complex interaction problems [11]. In fact, ABM uses a
variety of interactions between agents as well as between agent and environment to provide a realistic simulation of processes
[11, 12].
The main aim of this research is to develop an agent-based model using the Susceptible-Exposed-Infected-Recovered-
Susceptible (SEIRS) model that the effects of various environmental factors of air temperature, relative humidity, land vegetation,
altitude, and distance from water sources were applied in the model.

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