A nowcast model to predict outdoor flea activity in real time for the contiguous United States.

Stella Self, Yuan Yang, Heather Walden, Michael J Yabsley, Christopher McMahan, Brian H Herrin
Author Information
  1. Stella Self: Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, USA.
  2. Yuan Yang: School of Mathematical and Statistical Sciences, Clemson University, Clemson, USA.
  3. Heather Walden: Department of Comparative, Diagnostic and Population Medicine, College of Veterinary Medicine, University of Florida, Gainesville, USA.
  4. Michael J Yabsley: Southeastern Cooperative Wildlife Disease Study, Department of Population Health, College of Veterinary Medicine, University of Georgia, Athens, USA.
  5. Christopher McMahan: School of Mathematical and Statistical Sciences, Clemson University, Clemson, USA.
  6. Brian H Herrin: Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, USA. bhh@vet.k-state.edu.

Abstract

BACKGROUND: The cat flea (Ctenocephalides felis), a parasite commonly found on both dogs and cats, is a competent vector for several zoonotic pathogens, including Dipylidium caninum (tapeworms), Bartonella henselae (responsible for cat scratch disease) and Rickettsia felis (responsible for flea-borne spotted fever). Veterinarians recommend that both cats and dogs be routinely treated with medications to prevent flea infestation. Nevertheless, surveys suggest that nearly one third of pet owners do not routinely administer appropriate preventatives.
METHODS: A mathematical model based on weighted averaging over time is developed to predict outdoor flea activity from weather conditions for the contiguous United States. This 'nowcast' model can be updated in real time as weather conditions change and serves as an important tool for educating pet owners about the risks of flea-borne disease. We validate our model using Google Trends data for searches for the term 'fleas.' This Google Trends data serve as a proxy for true flea activity, as validating the model by collecting fleas over the entire USA is prohibitively costly and time-consuming.
RESULTS: The average correlation (r) between the nowcast outdoor flea activity predictions and the Google Trends data was moderate: 0.65, 0.70, 0.66, 0.71 and 0.63 for 2016, 2017, 2018, 2019 and 2020, respectively. However, there was substantial regional variation in performance, with the average correlation in the East South Atlantic states being 0.81 while the average correlation in the Mountain states was only 0.45. The nowcast predictions displayed strong seasonal and geographic patterns, with predicted activity generally being highest in the summer months.
CONCLUSIONS: The nowcast model is a valuable tool by which to educate pet owners regarding the risk of fleas and flea-borne disease and the need to routinely administer flea preventatives. While it is ideal for domestic cats and dogs to on flea preventatives year-round, many pets remain vulnerable to flea infestation. Alerting pet owners to the local increased risk of flea activity during certain times of the year may motivate them to administer appropriate routine preventives.

Keywords

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MeSH Term

Animals
Cats
Dogs
Siphonaptera
Cat Diseases
Dog Diseases
Flea Infestations
Ctenocephalides

Word Cloud

Created with Highcharts 10.0.0fleamodel0activitypetownersdatanowcastdogscatsdiseaseflea-borneroutinelyadministerpreventativestimeoutdoorGoogleTrendsaveragecorrelationcatCtenocephalidesfelisresponsibleinfestationappropriatepredictweatherconditionscontiguousUnitedStatesrealtoolfleaspredictionsstatesriskBACKGROUND:parasitecommonlyfoundcompetentvectorseveralzoonoticpathogensincludingDipylidiumcaninumtapewormsBartonellahenselaescratchRickettsiaspottedfeverVeterinariansrecommendtreatedmedicationspreventNeverthelesssurveyssuggestnearlyonethirdMETHODS:mathematicalbasedweightedaveragingdeveloped'nowcast'canupdatedchangeservesimportanteducatingrisksvalidateusingsearchesterm'fleas'serveproxytruevalidatingcollectingentireUSAprohibitivelycostlytime-consumingRESULTS:rmoderate:657066716320162017201820192020respectivelyHoweversubstantialregionalvariationperformanceEastSouthAtlantic81Mountain45displayedstrongseasonalgeographicpatternspredictedgenerallyhighestsummermonthsCONCLUSIONS:valuableeducateregardingneedidealdomesticyear-roundmanypetsremainvulnerableAlertinglocalincreasedcertaintimesyearmaymotivateroutinepreventivesFleaForecastMathematicalMeteorological

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