2014Unpublished venueOpen access

Agent based modeling of malaria

Chathura Illangakoon, R.D. McLeod, Marcia Friesen

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Abstract

This work explores the utility of an agent based model (ABM) for studying malaria prevalence and transmission. Malaria is a life-threatening disease caused by Plasmodium parasites that are transmitted to humans through the bites of infected female mosquitoes of the genus Anopheles. According to the WHO, malaria caused an estimated 627,000 deaths in 2012 (with an uncertainty range of 473,000 to 789,000), mostly among African children [1][2]. Increased malaria prevention and control measures are the focus of much research and have already dramatically reduced the malaria burden in many places. Through the use of technology and high-resolution modeling and simulation, an even better understanding of prevention and control measures may be obtained.

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What this paper is about

This work explores the utility of an agent based model (ABM) for studying malaria prevalence and transmission. Malaria is a life-threatening disease caused by Plasmodium parasites that are transmitted to humans through the bites of infected female mosquitoes of the genus Anopheles. According to the WHO, malaria caused an estimated 627,000 deaths in 2012 (with an uncertainty range of 473,000 to 789,000), mostly among African children [1][2]. Increased malaria prevention and control measures are the focus of much research and have already dramatically reduced the malaria burden in many places. Through the use of technology and high-resolution modeling and simulation, an even better understanding of prevention and control measures may be obtained.

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Available abstract

This work explores the utility of an agent based model (ABM) for studying malaria prevalence and transmission. Malaria is a life-threatening disease caused by Plasmodium parasites that are transmitted to humans through the bites of infected female mosquitoes of the genus Anopheles. According to the WHO, malaria caused an estimated 627,000 deaths in 2012 (with an uncertainty range of 473,000 to 789,000), mostly among African children [1][2]. Increased malaria prevention and control measures are the focus of much research and have already dramatically reduced the malaria burden in many places. Through the use of technology and high-resolution modeling and simulation, an even better understanding of prevention and control measures may be obtained.

Key concepts: Malaria, Anopheles, Transmission (telecommunications), Environmental health, Plasmodium (life cycle), Disease control, Malaria prevention, Computer science

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