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SPECIES DISTRIBUTION MODELING OF DENGUE MOSQUITOES IN TWO ENVIRONMENTAL REGIMES, LAHORE AND SWAT: IMPLICATIONS IN VECTOR BIOLOGY

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dc.contributor.author Fatima, Syeda Hira
dc.date.accessioned 2025-02-26T09:11:54Z
dc.date.available 2025-02-26T09:11:54Z
dc.date.issued 2025-02-26
dc.identifier.other NUST201261099MSCEE62512F
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/50228
dc.description Supervisor: Dr. Salman Atif en_US
dc.description.abstract Pakistan is recently experiencing a wave of Dengue epidemics that has claimed numerous lives. Lahore the provincial metropolis of Punjab and Swat a major city in Khyber Pakhtunkhwa are among the hard hit areas. The present study targeted the two cities for determining spatial distribution of Dengue mosquitoes; a task essential for an effective control strategy and predicting near future outbreaks of the dengue fever. We used general-purpose ( "Maxent") maximum entropy model; undertaking an assembly of mosquitos' occurrence records, associated environmental covariates also taking into account the issue of multi-collinearity. Our results suggest: 1. Spatial patterns of species occupancy has a widespread distribution in Lahore. This is perhaps due to the ecological homogeneity of the study area 2. Aedes aegypti has a fragmented population structure in Swat where the urban patches provide refuge to the species in an otherwise hostile heterogenous environment. Perhaps the ecological overlap of vector and human population has led to the invasion of this species in Swat. Thus the distribution and spread of Aedes aegpti in this area can be traced back to anthropogenic activities. 3. Modeling results reveal that Maxent tends to perform better in dynamic regimes like Swat (AUC=0.98) that are characterized by vast landscape diversity and biogeographic gradients as compared to homogenous areas like Lahore (AUC=0.85). 3. Species distribution models are sensitive to multi-collinearity, but sometimes changes in collinearity structure of Predictors can lead to dramatic loss of prediction accuracy (both the training AUC (AUC=0.923 (for all variables) >AUC= 0.882(for few variables)) and Test AUC (AUC= 0.881 (for all variables) >AUC=0.850 (for Jew variables)) decreased as we remove so-called correlated variables, and use rest of the plain variables both for Lahore. en_US
dc.language.iso en en_US
dc.publisher Institute of Geographical Information Systems (IGIS) en_US
dc.subject Aedes aegypti, Maxent, Multi-collinearity, AUC en_US
dc.title SPECIES DISTRIBUTION MODELING OF DENGUE MOSQUITOES IN TWO ENVIRONMENTAL REGIMES, LAHORE AND SWAT: IMPLICATIONS IN VECTOR BIOLOGY en_US
dc.type Thesis en_US


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