Optimized Mosquito Surveillance in St . Tammany ’ s Parish

Since its emergence in the United States in 1999, West Nile Virus has caused hundreds of deaths and has been spreading geographically. In order to efficiently control West Nile Virus outbreaks, it is necessary to monitor the spread of its primary mosquito vectors. This report contains a new computational method to optimize the surveillance methods of West Nile Virus vectors at St. Tammany Parish, Louisiana. Based on multiple years of data, the distribution of mosquito density was thoroughly anazlyed. The results include the identification of multi-year patterns and high-risk zones for West Nile Virus in the parish and correlations in mosquito prevalence across these zones. A spatial statistical model was developed for the surveillance network regarding the West Nile Virus vector Culex Quinquefasciatus. An approximation algorithm was applied to determine the optimal location of surveillance sites that provide the most informative locations for Culex Quinquefasciatus surveillance in the parish. The results of this paper indicate that a greedy algorithm, thus far, is the best possible solution to determine the optimal surveillance sites. In its current state, the algorithm is simplified as the most informative locations as those that decrease the variance the most. An improved algorithm involving more variables such as rainfall will enhance the ability to determine an optimal mosquito surveillance network. Optimizing mosquito surveillance methods can improve the ability to monitor mosquito vectors and significantly reduce costs.