Browsing by Author "Staples, J. Erin"

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    Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction
    Holcomb, Karen M.; Mathis, Sarabeth; Staples, J. Erin; Fischer, Marc; Barker, Christopher M.; Beard, Charles B.; Nett, Randall J.; Keyel, Alexander C.; Marcantonio, Matteo; Childs, Marissa L.; Gorris, Morgan E.; Rochlin, Ilia; Hamins-Puértolas, Marco; Ray, Evan L.; Uelmen, Johnny A.; DeFelice, Nicholas; Freedman, Andrew S.; Hollingsworth, Brandon D.; Das, Praachi; Osthus, Dave; Humphreys, John M.; Nova, Nicole; Mordecai, Erin A.; Cohnstaedt, Lee W.; Kirk, Devin; Kramer, Laura D.; Harris, Mallory J.; Kain, Morgan P.; Reed, Emily M. X.; Johansson, Michael A. (2023-01-12)
    Background 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. Methods 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. Results 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. Conclusions 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).
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    Heartland Virus Epidemiology, Vector Association, and Disease Potential
    Brault, Aaron C.; Savage, Harry M.; Duggal, Nisha K.; Eisen, Rebecca J.; Staples, J. Erin (MDPI, 2018-09-14)
    First identified in two Missouri farmers exhibiting low white-blood-cell and platelet counts in 2009, Heartland virus (HRTV) is genetically closely related to severe fever with thrombocytopenia syndrome virus (SFTSV), a tick-borne phlebovirus producing similar symptoms in China, Korea, and Japan. Field isolations of HRTV from several life stages of unfed, host-seeking Amblyomma americanum, the lone star tick, implicated it as a putative vector capable of transstadial transmission. Laboratory vector competence assessments confirmed transstadial transmission of HRTV, demonstrated vertical infection, and showed co-feeding infection between A. americanum. A vertical infection rate of 33% from adult females to larvae in the laboratory was observed, while only one of 386 pools of molted nymphs (1930) reared from co-feeding larvae was positive for HRTV (maximum-likelihood estimate of infection rate = 0.52/1000). Over 35 human HRTV cases, all within the distribution range of A. americanum, have been documented. Serological testing of wildlife in areas near the index human cases, as well as in widely separated regions of the eastern United States where A. americanum occur, indicated many potential hosts such as raccoons and white-tailed deer. Attempts, however, to experimentally infect mice, rabbits, hamsters, chickens, raccoons, goats, and deer failed to produce detectable viremia. Immune-compromised mice and hamsters are the only susceptible models. Vertical infection augmented by co-feeding transmission could play a role in maintaining the virus in nature. A more complete assessment of the natural transmission cycle of HRTV coupled with serosurveys and enhanced HRTV disease surveillance are needed to better understand transmission dynamics and human health risks.