Statistical Tools for West Nile Virus Disease Analysis

Ward, Matthew J.; Sorek–Hamer, Meytar; Vemuri, Krishna Karthik; DeFelice, Nicholas

doi:10.1007/978-1-0716-2760-0_16

Cited by 2 publications

(6 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We determined infection rates of mosquitoes at the NLDAS grid cell scale (0.125° or ∼13 km 2 ) using the presence/absence of mosquito pools and a statistical method (maximum likelihood estimator [MLE]) to estimate the annual infection rate of mosquitoes per 1,000 mosquitoes tested ( I M ) (Ward, Sorek‐Hamer, et al., 2023). The MLE was chosen because it takes advantage of changes within pool size and estimates a higher infection level by assuming that if a pool tests positive, one or more mosquitoes are WNV positive.…”

Section: Methodsmentioning

confidence: 99%

“…The MLE was chosen because it takes advantage of changes within pool size and estimates a higher infection level by assuming that if a pool tests positive, one or more mosquitoes are WNV positive. This is a more appropriate estimate as the number of mosquitoes tested increases and the true infection rate is small (Walter et al., 1980; Ward, Sorek‐Hamer, et al., 2023). All traps were assigned an NLDAS grid, all pools within each grid were combined from CDC weeks 20–45, and the annual infection rate was calculated (Table S2 in Supporting Information ).…”

Section: Methodsmentioning

confidence: 99%

“…All traps were assigned an NLDAS grid, all pools within each grid were combined from CDC weeks 20-45, and the annual infection rate was calculated (Table S2 in Supporting Information S1). For methodology on calculating the annual I M using the MLE see Ward, Sorek-Hamer, et al (2023).…”

Section: Mosquito Datamentioning

confidence: 99%

Section: Conflict Of Interestmentioning

confidence: 99%

“…NLDAS data is freely available from NASA (NLDAS, 2012). Our code, figures, data, and methodology can be accessed via (Ward, Patel, & DeFelice, 2023), and the statistical software R and cited packages can be obtained from the R Project for Statistical Computing (R Core Team, 2023). Mosquito data supporting this research are available from the Coachella Valley Mosquito and Vector Control District through VectorSurv under memorandum of understanding and are not accessible to the public or research community without prior approval (VectorSurv [Database].…”

Section: Data Availability Statementmentioning

confidence: 99%

See 4 more Smart Citations

A Spatially Resolved and Environmentally Informed Forecast Model of West Nile Virus in Coachella Valley, California

Ward,

Sorek‐Hamer,

Henke

et al. 2023

GeoHealth

Self Cite

View full text Add to dashboard Cite

West Nile virus (WNV) is the most significant arbovirus in the United States in terms of both morbidity and mortality. West Nile exists in a complex transmission cycle between avian hosts and the arthropod vector, Culex spp. mosquitoes. Human spillover events occur when humans are bitten by an infected mosquito and predicting these rates of infection and therefore the risk to humans may be associated with fluctuations in environmental conditions. In this study, we evaluate the hydrological and meteorological drivers associated with mosquito biology and viral development to determine if these associations can be used to forecast seasonal mosquito infection rates with WNV in the Coachella Valley of California. We developed and tested a spatially resolved ensemble forecast model of the WNV mosquito infection rate in the Coachella Valley using 17 years of mosquito surveillance data and North American Land Data Assimilation System‐2 environmental data. Our multi‐model inference system indicated that the combination of a cooler and dryer winter, followed by a wetter and warmer spring, and a cooler than normal summer was most predictive of the prevalence of West Nile positive mosquitoes in the Coachella Valley. The ability to make accurate early season predictions of West Nile risk has the potential to allow local abatement districts and public health entities to implement early season interventions such as targeted adulticiding and public health messaging before human transmission occurs. Such early and targeted interventions could better mitigate the risk of WNV to humans.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Mosquito Datamentioning

confidence: 99%

Section: Conflict Of Interestmentioning

confidence: 99%

Section: Data Availability Statementmentioning

confidence: 99%

See 3 more Smart Citations

A Spatially Resolved and Environmentally Informed Forecast Model of West Nile Virus in Coachella Valley, California

Ward,

Sorek‐Hamer,

Henke

et al. 2023

GeoHealth

Self Cite

View full text Add to dashboard Cite

show abstract

A spatially resolved and environmentally informed forecast model of West Nile virus in Coachella Valley, California.

Ward

Sorek–Hamer

Henke

et al. 2023

Preprint

View full text Add to dashboard Cite

West Nile virus is the most significant arbovirus in the United States in terms of both morbidity and mortality. West Nile exists in a complex transmission cycle between avian hosts and the arthropod vector, Culex spp. mosquitoes. Human spillover events occur when humans are in close proximity to vector populations with high rates of infection. Predicting these rates of infection and therefore the risk to humans is not straightforward. In this study, we evaluate the hydrological and meteorological drivers associated with mosquito biology and viral development to determine if these associations can be used to forecast seasonal West Nile risk in the Coachella Valley of California. To test this, we developed and tested a spatially-resolved ensemble forecast model of West Nile virus transmission in the Coachella Valley using 17 years of mosquito surveillance data and NLDAS-2 environmental data. Our multi-model inference system indicated that the combination of a cooler and dryer winter followed by a wetter and warmer spring and a cooler than normal summer was most predictive of West Nile positive mosquitoes in the Coachella Valley. The ability to make accurate early season predictions of West Nile risk could allow local abatement districts and public health entities to implement early season interventions such as targeted adulticiding and public messaging before human transmission occurs. Such early and targeted interventions could better mitigate the risk of West Nile virus to humans in the Coachella Valley.

show abstract

Statistical Tools for West Nile Virus Disease Analysis

Cited by 2 publications

References 9 publications

A Spatially Resolved and Environmentally Informed Forecast Model of West Nile Virus in Coachella Valley, California

A Spatially Resolved and Environmentally Informed Forecast Model of West Nile Virus in Coachella Valley, California

A spatially resolved and environmentally informed forecast model of West Nile virus in Coachella Valley, California.

Contact Info

Product

Resources

About