Web Algorithm search engine based network modelling of Malaria Transmission

Malaria has been described as one of the most dangerous and widest spread tropical diseases, with an estimated 247 million cases around the globe in the year 2006 alone. This calls for urgent scientific interventions. Since malaria is a vector borne disease, this research tackled the issue of malar...

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Main Author: Eze, Monday Okpoto
Format: Thesis
Language:English
English
Published: Universiti Malaysia Sarawak, (UNIMAS) 2013
Subjects:
Online Access:http://ir.unimas.my/id/eprint/8344/
http://ir.unimas.my/id/eprint/8344/2/Web%20Algorithm%20Abstract.pdf
http://ir.unimas.my/id/eprint/8344/1/Web%20Algorithm..ft.pdf
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author Eze, Monday Okpoto
author_facet Eze, Monday Okpoto
author_sort Eze, Monday Okpoto
building UNIMAS Institutional Repository
collection Online Access
description Malaria has been described as one of the most dangerous and widest spread tropical diseases, with an estimated 247 million cases around the globe in the year 2006 alone. This calls for urgent scientific interventions. Since malaria is a vector borne disease, this research tackled the issue of malaria transmission from the angle of vector detection through a search engine. There are observed cases of attempting vector control on a trial and errors basis, with no scientific way of determining the locations of critical vector densities. Unfortunately, such a practice leads to waste of resources on the wrong places, while ignoring the areas of critical vector existence. This research formalizes a contact network using a number of attributes of the malaria vectors, the public places, and the human beings that affect malaria transmission. The resulting structure is a heterogeneous bipartite contact network of two node types - the public places and the human beings nodes. The human beings are those who have suffered from malaria, even when their residential homes were under reliable vector control. Such an exclusion principle makes it obvious that these people, most probably contacted the disease from outside their residential homes. The Hypertext Induced Topical Search (HITS) web search algorithm was adapted to implement a search engine, which uses the bipartite contact network as the input. MATLAB was used to implement the model system. The output shows the public places which habour the infected malaria vectors, and their corresponding vector densities. The model output was validated with UCINET 6.0 as the benchmark system. A root mean square error (RMSE) value of 0.0023 was obtained when the output of the benchmark system is compared with that of the search engine model. This result indicates a high and acceptable level of accuracy.
first_indexed 2025-11-15T06:22:34Z
format Thesis
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institution Universiti Malaysia Sarawak
institution_category Local University
language English
English
last_indexed 2025-11-15T06:22:34Z
publishDate 2013
publisher Universiti Malaysia Sarawak, (UNIMAS)
recordtype eprints
repository_type Digital Repository
spelling unimas-83442025-04-11T02:42:27Z http://ir.unimas.my/id/eprint/8344/ Web Algorithm search engine based network modelling of Malaria Transmission Eze, Monday Okpoto T Technology (General) Malaria has been described as one of the most dangerous and widest spread tropical diseases, with an estimated 247 million cases around the globe in the year 2006 alone. This calls for urgent scientific interventions. Since malaria is a vector borne disease, this research tackled the issue of malaria transmission from the angle of vector detection through a search engine. There are observed cases of attempting vector control on a trial and errors basis, with no scientific way of determining the locations of critical vector densities. Unfortunately, such a practice leads to waste of resources on the wrong places, while ignoring the areas of critical vector existence. This research formalizes a contact network using a number of attributes of the malaria vectors, the public places, and the human beings that affect malaria transmission. The resulting structure is a heterogeneous bipartite contact network of two node types - the public places and the human beings nodes. The human beings are those who have suffered from malaria, even when their residential homes were under reliable vector control. Such an exclusion principle makes it obvious that these people, most probably contacted the disease from outside their residential homes. The Hypertext Induced Topical Search (HITS) web search algorithm was adapted to implement a search engine, which uses the bipartite contact network as the input. MATLAB was used to implement the model system. The output shows the public places which habour the infected malaria vectors, and their corresponding vector densities. The model output was validated with UCINET 6.0 as the benchmark system. A root mean square error (RMSE) value of 0.0023 was obtained when the output of the benchmark system is compared with that of the search engine model. This result indicates a high and acceptable level of accuracy. Universiti Malaysia Sarawak, (UNIMAS) 2013 Thesis NonPeerReviewed text en http://ir.unimas.my/id/eprint/8344/2/Web%20Algorithm%20Abstract.pdf text en http://ir.unimas.my/id/eprint/8344/1/Web%20Algorithm..ft.pdf Eze, Monday Okpoto (2013) Web Algorithm search engine based network modelling of Malaria Transmission. PhD thesis, Universiti Malaysia Sarawak, (UNIMAS).
spellingShingle T Technology (General)
Eze, Monday Okpoto
Web Algorithm search engine based network modelling of Malaria Transmission
title Web Algorithm search engine based network modelling of Malaria Transmission
title_full Web Algorithm search engine based network modelling of Malaria Transmission
title_fullStr Web Algorithm search engine based network modelling of Malaria Transmission
title_full_unstemmed Web Algorithm search engine based network modelling of Malaria Transmission
title_short Web Algorithm search engine based network modelling of Malaria Transmission
title_sort web algorithm search engine based network modelling of malaria transmission
topic T Technology (General)
url http://ir.unimas.my/id/eprint/8344/
http://ir.unimas.my/id/eprint/8344/2/Web%20Algorithm%20Abstract.pdf
http://ir.unimas.my/id/eprint/8344/1/Web%20Algorithm..ft.pdf