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Browsing by Author "Barker, Christopher M."

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    Bionomics of Ochlerotatus triseriatus Say (Diptera: Culicidae) and Aedes albopictus Skuse (Diptera: Culicidae) in emerging La Crosse virus foci in Virginia
    Barker, Christopher M. (Virginia Tech, 2001-07-10)
    Recently, the number of human cases of La Crosse encephalitis (LACE), an illness caused by mosquito-borne La Crosse (LAC) virus, has increased in southwestern Virginia, resulting in a need for better understanding of the virus cycle and the biology of its vectors in the region. This project examined the spatial and temporal distributions of the primary vector of LAC virus, Ochlerotatus triseriatus, and a potential secondary vector, Aedes albopictus. Ovitrapping surveys were conducted in 1998 and 1999 to determine distributions and oviposition habitat preferences of the two species in southwestern Virginia. For virus assay, adult mosquitoes were collected at a tire dump and a human case site during 1998 and 1999, and ovitrap samples were taken from a human case site in 2000. In a separate study, a landcover map of Wise County was created by supervised classification of Landsat Enhanced Thematic Mapper imagery, and maps indicating posterior probabilities of high mosquito abundance were created by combining ovitrap survey-derived, landcover-based prior and conditional probabilities for high and low mosquito abundance using remote sensing techniques and Bayesian decision-making rules. Both Oc. triseriatus and Ae. albopictus were collected from all ovitrap sites surveyed in Wise, Scott, and Lee Counties during 1998. Numbers of Oc. triseriatus remained high from late June through late August, while Ae. albopictus numbers increased gradually through June and July, reaching a peak in late August and declining thereafter. Overall, Oc. triseriatus accounted for 90.1% of eggs collected during this period, and Ae. albopictus made up the remaining 9.9%. Abundance of the two species differed among the sites, and in Wise County, relative Ae. albopictus abundance was highest in sites with traps placed in open residential areas. Lowest numbers of both species were found in densely forested areas. Ovitrapping at a human LACE case site during 1998 and 1999 revealed that Aedes albopictus was well-established and overwintering in the area. An oviposition comparison between yard and adjacent forest at the Duncan Gap human LACE case site in 1999 showed that Ae. albopictus preferentially oviposited in the yard surrounding the home over adjacent forested areas, but Oc. triseriatus showed no preference. LAC virus was isolated from 1 larval and 1 adult collection of Oc. triseriatus females from the Duncan Gap human case site, indicating the occurrence of transovarial transmission at this site. The supervised landcover classification for Wise County yielded a landcover map with an overall accuracy of 98% based on comparison of output classification with user-defined ground truth data. Posterior probability maps for Oc. triseriatus and Ae. albopictus abundance reflected seasonal and spatial fluctuations in mosquito abundance with an accuracy of 55-79% for Oc. triseriatus (Kappa=0.00-0.53) and 70-94% for Ae. albopictus (Kappa=0.00-0.49) when model output was compared with results of an ovitrapping survey. Other accuracy measures were also considered, and suggestions were offered for improvement of the model.
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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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    Habitat preferences and phenology of Ochlerotatus triseriatus and Aedes albopictus (Diptera : Culicidae) in southwestern Virginia
    Barker, Christopher M.; Paulson, Sally L.; Cantrell, Sue; Davis, Brent S. (Oxford University Press, 2003-07-01)
    Recently, the number of reported human cases of La Crosse encephalitis, an illness caused by mosquito-borne La Crosse virus (LAC), has increased in southwestern Virginia, resulting in a need for better understanding of the virus cycle and the biology of its vectors in the region. This study examined the spatial and temporal distributions of the primary vector of LAC, Ochlerotatus triseriatus (Say), and a potential secondary vector, Aedes albopictits (Skuse). Ovitrapping surveys were conducted in 1998 and 1999 to determine distributions and oviposition habitat preferences of the two species in southwestern Virginia. Mosquitoes also were collected for virus assay from a tire dump and a human La Crosse encephalitis case site between 1998 and 2000. Oc. triseriatus and Ae. albopictus were collected from all ovitrap sites surveyed, and numbers of Oc. triseriatus eggs generally were higher than those of Ae. albopictus. Numbers of Oc. triseriatus remained high during most of the summer, while Ae. albopictus numbers increased gradually, reaching a peak in late August and declining thereafter. In Wise County, relative Ae. albopictus abundance was highest in sites with traps placed in open residential areas. Lowest numbers of both species were found in densely forested areas. Ovitrapping during consecutive years revealed that Ae. albopictus was well established and overwintering in the area. An oviposition comparison between the yard and adjacent forest at a human LaCrosse encephalitis case site in 1999 showed that Ae. albopictus preferentially oviposited in the yard surrounding the home, but Oc. triseriatus showed no preference. LAC isolations from larval and adult collections of Oc. triseriatus females from the same case site indicated the occurrence of transovarial transmission.
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    An open challenge to advance probabilistic forecasting for dengue epidemics
    Johansson, Michael A.; Apfeldorf, Karyn M.; Dobson, Scott; Devita, Jason; Buczak, Anna L.; Baugher, Benjamin; Moniz, Linda J.; Bagley, Thomas; Babin, Steven M.; Guven, Erhan; Yamana, Teresa K.; Shaman, Jeffrey; Moschou, Terry; Lothian, Nick; Lane, Aaron; Osborne, Grant; Jiang, Gao; Brooks, Logan C.; Farrow, David C.; Hyun, Sangwon; Tibshirani, Ryan J.; Rosenfeld, Roni; Lessler, Justin; Reich, Nicholas G.; Cummings, Derek AT T.; Lauer, Stephen A.; Moore, Sean M.; Clapham, Hannah E.; Lowe, Rachel; Bailey, Trevor C.; Garcia-Diez, Markel; Carvalho, Marilia Sa; Rodo, Xavier; Sardar, Tridip; Paul, Richard; Ray, Evan L.; Sakrejda, Krzysztof; Brown, Alexandria C.; Meng, Xi; Osoba, Osonde; Vardavas, Raffaele; Manheim, David; Moore, Melinda; Rao, Dhananjai M.; Porco, Travis C.; Ackley, Sarah; Liu, Fengchen; Worden, Lee; Convertino, Matteo; Liu, Yang; Reddy, Abraham; Ortiz, Eloy; Rivero, Jorge; Brito, Humberto; Juarrero, Alicia; Johnson, Leah R.; Gramacy, Robert B.; Cohen, Jeremy M.; Mordecai, Erin A.; Murdock, Courtney C.; Rohr, Jason R.; Ryan, Sadie J.; Stewart-Ibarra, Anna M.; Weikel, Daniel P.; Jutla, Antarpreet; Khan, Rakibul; Poultney, Marissa; Colwell, Rita R.; Rivera-Garcia, Brenda; Barker, Christopher M.; Bell, Jesse E.; Biggerstaff, Matthew; Swerdlow, David; Mier-y-Teran-Romero, Luis; Forshey, Brett M.; Trtanj, Juli; Asher, Jason; Clay, Matt; Margolis, Harold S.; Hebbeler, Andrew M.; George, Dylan; Chretien, Jean-Paul (National Academy of Sciences, 2019-11-26)
    A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue.