Seasonal temperatures and hydrological conditions improve the prediction of West Nile virus infection rates in Culex mosquitoes and human case counts in New York and Connecticut

Keyel, Alexander C.; Timm, O. Elison; Backenson, P. Bryon; Prussing, Catharine; Quiñones, Sarah; McDonough, Kathleen A.; Vuille, Mathias; Conn, Jan E.; Armstrong, Philip M.; Andreadis, Theodore G.; Kramer, Laura D.

doi:10.1371/journal.pone.0217854

Cited by 46 publications

(60 citation statements)

References 101 publications

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“…Meteorological data was obtained from a weather station that was located 1.3 km east and 3.2 km north of the Hayward Marsh using the US National Centers for Environmental Information database (www.ncdc.noaa.gov/cdo-web; [29]). Cumulative degree-days (DD) for each week was calculated as described previously for Culex mosquitoes [30] by comparing the daily average temperature to a baseline of 10°C (See Equation 1). If the DD calculation resulted in a negative value, zero was used instead.…”

Section: Methodsmentioning

confidence: 99%

Culex erythrothorax: Insecticide Susceptibility and Mosquito Control

Esterly

Alemayehu

Rusmisel

et al. 2020

Preprint

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28 Culex erythrothorax Dyar is a West Nile virus (WNV) vector that breeds in wetland habitats with 29 emergent vegetation. Urbanization and recreational activities near wetlands place humans and 30 birds in close proximity to Cx. erythrothorax, increasing the risk of WNV transmission. High 31 adult Cx. erythrothorax abundance peaked in a marsh bordering the San Francisco Bay of 32 California (USA) during the first 3 hours after sunset (5527 ± 4070 mosquitoes / trap night) 33 during which adult mosquito control efforts are likely most effective. These adult mosquitoes 34 were highly sensitive to permethrin, resmethrin, naled, and etofenprox insecticides when 35 tested in a bottle bioassay (LC50 = 0.35, 0.68, 0.71, and 4.1 µg/bottle, respectively). The 36 synergist piperonyl butoxide increased the sensitivity of the mosquitoes to a low concentration 37 of permethrin (0.5 µg/bottle) while also reducing knock down time, but did not have similar 38 effects with a higher permethrin concentration (2.0 µg/bottle). Biochemical enzyme assays 39 measuring bulk mixed-function oxidase, alpha-esterase, or beta-esterase activities in mosquito 40 homogenates were significantly higher in Cx. erythrothorax relative to a strain of Culex pipiens 41 that is sensitive to permethrin. Larvicide that was applied to the site had limited impact on 42 reducing the abundance of adult Cx. erythrothorax. Subsequent removal of emergent 43 vegetation in concert with reduced daily temperature in the environment substantially reduced 44 Cx. erythrothorax abundance. Land managers who have a need to control Cx. erythrothorax in 45 wetlands should consider vegetation removal over applying larvicide, while vector control 46 agencies are likely to successfully control viremic Cx. erythrothorax that enter nearby 47 neighborhoods by applying insecticides that target the adult stage of the mosquito within 3 h of 48 sunset. 3 49 Introduction 50 51 Culex erythrothorax Dyar, commonly known as the tule mosquito, is endemic to the 52 western southwestern states of the US [1]. The larvae breed in heavily vegetated regions of 53 shallow ponds and can be highly abundant in marsh habitats that contain dense clusters of 54 Schoenoplectus spp (common tule), Typha spp. (bulrush), or Myriophyllum aquaticum (parrot 55 feather) [2-4]. Unlike many species of mosquito, adult Cx. erythrothorax do not disperse 56 distantly from where they emerge [3, 5, 6]. The time of host-seeking is well documented for 57 Culex tarsalis Coquillett, another mosquito species found marsh habitats, which is reported to 58 be most active 1 -4 h after sunset [7, 8]. The time of day that Cx. erythrothorax is most likely 59 to seek a blood meal and would be best controlled by insecticides that target the adult 60 mosquito is not reported. Larvicide applications to constructed marsh habitats can markedly 61 reduce the abundance of adult Cx. erythrothorax [9]. However, the duration of reduction is 62 short, likely because adult mosquitoes immigrate from nearby sites that are not treated [5] and 63 d...

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Section: Methodsmentioning

confidence: 99%

Culex erythrothorax: Insecticide Susceptibility and Mosquito Control

Esterly

Alemayehu

Rusmisel

et al. 2020

Preprint

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“…The RF model is a new regression method and can address the limitations of ARIMA/X models in the prediction of diarrhea incidence [11][12][13][14]. It can effectively extract non-linear relationships from data.…”

Section: Introductionmentioning

confidence: 99%

“…Using the RF model, the training set for each tree is randomly selected from the data, and the final predicted value is the average of all CART outputs. RF model has been widely used for infectious-disease prediction such as West Nile virus infection and Bovine viral diarrhea [12,13]. Notably, Michael et al [14] reported that an RF model has advantages over the ARIMA model in predicting avian influenza H5N1 outbreaks.…”

Section: Introductionmentioning

confidence: 99%

Forecasting incidence of infectious diarrhea using random forest in Jiangsu Province, China

Fang

et al. 2020

BMC Infect Dis

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Background: Infectious diarrhea can lead to a considerable global disease burden. Thus, the accurate prediction of an infectious diarrhea epidemic is crucial for public health authorities. This study was aimed at developing an optimal random forest (RF) model, considering meteorological factors used to predict an incidence of infectious diarrhea in Jiangsu Province, China. Methods: An RF model was developed and compared with classical autoregressive integrated moving average (ARIMA)/X models. Morbidity and meteorological data from 2012 to 2016 were used to construct the models and the data from 2017 were used for testing. Results: The RF model considered atmospheric pressure, precipitation, relative humidity, and their lagged terms, as well as 1-4 week lag morbidity and time variable as the predictors. Meanwhile, a univariate model ARIMA (1,0,1)(1,0, 0) 52 (AIC = − 575.92, BIC = − 558.14) and a multivariable model ARIMAX (1,0,1)(1,0,0) 52 with 0-1 week lag precipitation (AIC = − 578.58, BIC = − 578.13) were developed as benchmarks. The RF model outperformed the ARIMA/X models with a mean absolute percentage error (MAPE) of approximately 20%. The performance of the ARIMAX model was comparable to that of the ARIMA model with a MAPE reaching approximately 30%. Conclusions: The RF model fitted the dynamic nature of an infectious diarrhea epidemic well and delivered an ideal prediction accuracy. It comprehensively combined the synchronous and lagged effects of meteorological factors; it also integrated the autocorrelation and seasonality of the morbidity. The RF model can be used to predict the epidemic level and has a high potential for practical implementation.

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“…Random forest (RF) model can effectively extract nonlinear relationships in data, which starts by creating classification and regression trees and each constituent tree trains on a potentially nonlinear regression space and is then combined with others. It has been widely used in infectious diseases prediction such as to predict West Nile virus infection and avian influenza incidence [10][11].…”

Section: Introductionmentioning

confidence: 99%

Forecasting incidence of infectious diarrhea using Random forest in Jiangsu province, China

Fang

et al. 2019

Preprint

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Background: Infectious diarrhea caused considerable disease burden around the world. An accurate forecast of infectious diarrhea epidemic based on predictive models is crucial for public health authorities. We aimed to develop an optimal random forest（RF）model to predict infectious diarrhea incidence using meteorological factors in Jiangsu province, China. Methods: A RF model was constructed to predict infectious diarrhea incidence in Jiangsu province base on the morbidity during 2012-2017 and synchronous meteorological data, then compared with classical ARIMA and ARIMAX model to evaluate the model prediction effect. Results: The RF model was established including atmosphere pressure, precipitation, relative humidity and their lagged terms, one to four weeks lagged morbidity and time variable as predictors. Meanwhile, a univariate model ARIMA(1,0,1)(1,0,0) 52 (AIC=-575.92, BIC=-558.14) and a multivariable model ARIMAX(1,0,1)(1,0,0) 52 with precipitation and its one-week lagged term as external variables (AIC=-578.58, BIC=-578.13) were developed as benchmark models. Predictive values of RF model matched the real morbidity very well, with a mean absolute percentage (MAPE) about 20%. The performance of the multivariate ARIMAX model was similar to that of the univariate ARIMA model. Both of them performed much worse than the RF model, with a MAPE as high as near to 30%. Conclusions: In brief, RF model well integrated autocorrelation and seasonality of morbidity. It also comprehensively combined meteorological factors and their hysteresis effects. This model well fitted the dynamic of infectious diarrhea epidemic and achieved ideal predication accuracy. It could be used to predict the epidemic level, and has a good prospect of practical application.

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Seasonal temperatures and hydrological conditions improve the prediction of West Nile virus infection rates in Culex mosquitoes and human case counts in New York and Connecticut

Cited by 46 publications

References 101 publications

Culex erythrothorax: Insecticide Susceptibility and Mosquito Control

Culex erythrothorax: Insecticide Susceptibility and Mosquito Control

Forecasting incidence of infectious diarrhea using random forest in Jiangsu Province, China

Forecasting incidence of infectious diarrhea using Random forest in Jiangsu province, China

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