@article{holcomb_mathis_staples_fischer_barker_beard_nett_keyel_marcantonio_childs_et al._2023, title={Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction}, DOI={10.1186/s13071-022-05630-y}, abstractNote={West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement.We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill.Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill.Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases).}, journal={Parasites & Vectors}, author={Holcomb, Karen M. and Mathis, Sarabeth and Staples, J. Erin and Fischer, Marc and Barker, Christopher M. and Beard, Charles B. and Nett, Randall J. and Keyel, Alexander C. and Marcantonio, Matteo and Childs, Marissa L. and et al.}, year={2023}, month={Jan} }
 @article{prade_sandhi_elzay_arnold_pickens_freedman_dillard_gresham_morris_pezzini_et al._2023, title={Transforming entomology to adapt to global concerns: 2021 student debates}, DOI={10.1093/jisesa/iead064}, abstractNote={Abstract The 2021 Student Debates of the Entomological Society of America (ESA) were held at the Annual Meeting in Denver, CO. The event was organized by the Student Debates Subcommittee (SDS) of the Student Affairs Committee (SAC). The theme of the 2021 Student Debates was “Transforming Entomology to Adapt to Global Concerns”, with 3 topics. Each topic had an unbiased introduction and 2 teams. The debate topics were (i) Nonnative insect introduction is an ethical approach for counteracting proliferation and overpopulation of consumers, (ii) What is the best technology to control undesirable insect pests in urban and agricultural settings? and (iii) Compared to other solutions, like plant-based diets, insect farming is the best method to address rising human global food and nutrient supply demands. Unbiased introduction speakers and teams had approximately 6 months to prepare for their presentations.}, journal={Journal of Insect Science}, author={Prade, Patricia and Sandhi, Ramandeep Kaur and Elzay, Sarah DePaolo and Arnold, Katherine and Pickens, Victoria and Freedman, Andrew and Dillard, DeShae and Gresham, Sean and Morris, Ashley and Pezzini, Daniela and et al.}, year={2023}, month={Jul} }