Understanding Mosquito Surveillance Data for Analytic Efforts: A Case Study

Abstract

Mosquito surveillance data can be used for predicting mosquito distribution and dynamics as they relate to human disease. Often these data are collected by independent agencies and aggregated to state and national level portals to characterize broad spatial and temporal dynamics. These larger repositories may also share the data for use in mosquito and/or disease prediction and forecasting models. Assumed, but not always confirmed, is consistency of data across agencies. Subtle differences in reporting may be important for development and the eventual interpretation of predictive models. Using mosquito vector surveillance data from Arizona as a case study, we found differences among agencies in how trapping practices were reported. Inconsistencies in reporting may interfere with quantitative comparisons if the user has only cursory familiarity with mosquito surveillance data. Some inconsistencies can be overcome if they are explicit in the metadata while others may yield biased estimates if they are not changed in how data are recorded. Sharing of metadata and collaboration between modelers and vector control agencies is necessary for improving the quality of the estimations. Efforts to improve sharing, displaying, and comparing vector data from multiple agencies are underway, but existing data must be used with caution.

Keywords: data sharing; disease prediction; mosquito-borne disease; vector surveillance.

Fig. 1.

Weekly mosquito abundance counts plotted by week to compare restricting to only those traps characterized in the database as ‘routine surveillance’ (dark bars) with all other adult trapping (dashed bars). (a) Plotted using data from one county with a robust sampling program. This county accounts for 93% of the reported data in the database, of which 83.1% of the data was labeled as routine surveillance. (b) Plotted using data from all other counties combined, where 59.6% of the data were labeled as ‘routine surveillance’? (c) Is a comparison of only routine surveillance (solid) and only response trapping (dashed)? Note that this is for illustrative purposes and includes all mosquito species together and all trap types except ovi-traps. Outliers are not plotted.

Fig. 2.

Weekly mosquito abundance counts plotted by week for one submitting county to illustrate the impact of recording empty traps. Dark bars indicate weekly trap counts with all data included. Dashed bars indicate weekly trap counts when zero values (e.g., empty traps) were artificially removed from the dataset. Outliers are not plotted.