Graduation Year

2017

Document Type

Thesis

Degree

M.S.P.H.

Degree Name

MS in Public Health (M.S.P.H.)

Degree Granting Department

Global Health

Major Professor

Thomas Unnasch, Ph.D.

Committee Member

Benjamin Jacob, Ph.D.

Committee Member

Carl Boohene, Ph.D.

Keywords

Mosquitoes, Vectors, LULC, GIS, Negative Binomial Regression

Abstract

Although mosquito monitoring systems in the form of dry-ice bated CDC light traps and sentinel chickens are used by mosquito control personnel in Polk County, Florida, the placement of these are random and do not necessarily reflect prevalent areas of vector mosquito populations. This can result in significant health, economic, and social impacts during disease outbreaks. Of these vector mosquitoes Culex nigripalpus, Culex erraticus, Coquillettidia perturbans, and Aedes vexans are present in Polk County and known to transmit multiple diseases, posing a public health concern. This study seeks to evaluate the effect of Land use Land cover (LULC) unique features and precipitation on spatial and temporal distribution of Cx. nigripalpus, Cx. erraticus, Cq. perturbans, and Ae. vexans in Polk County, Florida, during 2013 and 2014, using negative binomial regression on count data from eight environmentally unique light traps retrieved from Polk County Mosquito Control. The negative binomial regression revealed a statistical association among mosquito species for precipitation and LULC features during the two-year study period, with precipitation proving to be the most significant factor in mosquito count numbers. The findings from this study can aid in more precise targeting of mosquito species, saving time and resources on already stressed public health services.

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