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Malaria Control

by Erin Flanagan (Submitted: 08/05/2009)

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WHAT IS IT?

This model relates the number of people infected with malaria with the use of various control measures such as bed-nets, insecticide, and medicine within a population. This model was created for elementary students to use and thus the actual transmission rate of the virus has been simplified so that students may interpret the results with no prior knowledge of the disease and limited graphing skills.

HOW IT WORKS

People contact malaria when bitten by a mosquito carrying the plasmodium parasite. Infected people bitten by mosquitoes transmit the plasmodium parasite back to the mosquito - propagating the cycle. This model seeks to demonstrate that relationship as well as the affects of control measures in place to combact the disease.

HOW TO USE IT

Users choose the initial number of parasite-transmitting mosquitoes to reflect a location as well as the initial number of infected people in the population. Users also determine a bite-likelihood, which is basically the chance a given person will be in the same space as a mosquito and be bitten. The graph records the amount of infected people over time within the selected constraints. Users can also turn on/off three different control measures (or a combination of the three) that will influence the transmission of the disease and affect the amount of sick people in the population.

THINGS TO NOTICE

This model has several major assumptions:

1. Humans do not reproduce or die.
2. Bed-nets are 100% effective at preventing malaria.
3. Mosquitoes and people interact homogeneously.
4. Cured people (by medicine) cannot get sick again.
5. There is no delay in the mosquito acquiring the parasite and becoming infectious.

These assumptions were necessary to keep the program simple and straightforward, but do affect the accuracy of the results. However, infection trends and the overall effectiveness of control methods while generalized, does give students a sense of the relationships.

THINGS TO TRY

Here are three scenarios I used with my own class:

1.A person returns to Anytown, USA from a trip to Africa where he has contacted malaria. Should we people worried? Use the model to demonstrate why or why not. (Students should set initial infected to 1, bite likelihood low, and initial # mosquitoes low).

2.What variables affect the number sick people the most? (Students should test different variables one at a time. This is great way for students to understand the concept of variables and controls).

3.Malaria in endemic in areas with tropical climates. Endemic means lots of people have gotten the disease and continue to get the disease today. Why would people living in tropical areas get malaria more often? Set up the model so that lots of people get the disease over time. What do you notice? (Student should set the model so that the number of initial people infected is high, with a lot of mosquitoes and a high bite-likelihood and little controls in place...this will produce "endemic" results).

CREDITS AND REFERENCES

This model was created as a project in conjunction with Virginia Commonwealth
Univerity Bioinformatics and Bioengineering Summer Institute.

Copyright 2008 by Erin S. Flanagan. All rights reserved.

Permission to use, modify or redistribute this model is hereby granted,
a) this copyright notice is included.
b) this model will not be redistributed for profit without permission
from Erin S. Flanagan.
Contact Erin S. Flanagan for appropriate licenses for redistribution for
profit.

To refer to this model in academic publications, please use:

Flanagan, E.S. (2008). NetLogo Malaria Control model.
Mary Munford Elementary School
Richmond Public Schools, Richmond, VA

In other publications, please use:
Copyright 2008 Erin S. Flanagan. All rights reserved.

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