Using undergraduate researchers to build vector and West Nile virus surveillance capacity

Rapid Discovery and Detection of Haemaphysalis longicornis through the Use of Passive Surveillance and Collaboration: Building a State Tick-Surveillance Network

Between March 2019 and February 2020, Asian long-horned ticks (Haemaphysalis longicornis Neumann, 1901) were discovered and collected for the first time in one middle and seven eastern Tennessee counties, facilitated by a newly developed passive and collaborative tick-surveillance network. Network collaborators included federal, state, county, university, and private resource personnel working with companion animals, livestock, and wildlife. Specimens were collected primarily from dogs and cattle, with initial detections of female adult stage ticks by stakeholders associated with parasitology positions (e.g., entomologists and veterinary parasitologists). Initial county tick detections were confirmed with morphological and molecular identifications, and then screened for the presence of animal-associated pathogens (Anaplasma marginale, Babesia species, Ehrlichia species, and Theileria orientalis), for which all tests were negative. Herein, we describe the identification and confirmation of these tick specimens as well as other results of the surveillance collaboration.

A Taxonomic Checklist of the Mosquitoes of Montana With Notes On New Geographic Distributions

An updated checklist of 50 species of mosquitoes found in Montana is presented and includes 2 new records (Aedes niphadopsis and Anopheles walkeri) that can be added to the 2005 state list by Darsie and Ward. The results of a statewide mosquito surveillance program, conducted annually from 2004 to 2015, facilitated the establishment of an abundance rating of the species in the state and expanded the known geographic range for Coquillettidia perturbans, Ae. nigromaculis, and Culiseta minnesotae.

Predicting West Nile Virus Infection Risk From the Synergistic Effects of Rainfall and Temperature

Mosquito-based surveillance is a practical way to estimate the risk of transmission of West Nile virus (WNV) to people. Variations in temperature and precipitation play a role in driving mosquito infection rates and transmission of WNV, motivating efforts to predict infection rates based on prior weather conditions. Weather conditions and sequential patterns of meteorological events can have particularly important, but regionally distinctive, consequences for WNV transmission, with high temperatures and low precipitation often increasing WNV mosquito infection. Predictive models that incorporate weather can thus be used to provide early indications of the risk of WNV infection. The purpose of this study was first, to assess the ability of a previously published model of WNV mosquito infection to predict infection for an area within the region for which it was developed, and second, to improve the predictive ability of this model by incorporating new weather factors that may affect mosquito development. The legacy model captured the primary trends in mosquito infection, but it was improved considerably when calibrated with local mosquito infection rates. The use of interaction terms between precipitation and temperature improved model performance. Specifically, temperature had a stronger influence than rainfall, so that lower than average temperature greatly reduced the effect of low rainfall on increased infection rates. When rainfall was lower, high temperature had an even stronger positive impact on infection rates. The final model is practical, stable, and operationally valid for predicting West Nile virus infection rates in future weeks when calibrated with local data.