Comparison of Active and Passive Vector Surveillance Systems in Lyme Endemic Minnesota and their Correlation to Human Disease (Preprint)

Abstract

Vector surveillance is often used to predict tickborne diseases in endemic regions. Active and passive vector surveillance systems offer differing benefits and limitations, understanding how the outputs of these systems differ and how they correlate to human disease is essential to public health decision making. Active and passive vector surveillance systems in place in Minnesota between 2018 and 2023 present an opportunity for comparison between these surveillance methods.

To (i) analyze, compare, and contrast the results of active and passive vector surveillance programs; and (ii) explore how well these sources predict human risk of Lyme disease.

Descriptive statistics were performed to evaluate characteristics of each surveillance method with chi square tests or repeated-ANOVA to assess differences in seasonality, life stage, and genus of ticks between different datasets. Correlation to human cases of Lyme disease was analyzed using negative binomial regression models.

There are differences between the data sources in tick life stage and genus proportions as well as seasonality of tick rates. Active surveillance conducted by the Metropolitan Mosquito Control District (MMCD) using small mammal trapping had a majority of larval I. scapularis ticks. In contrast, passive surveillance by iNaturalist had a majority of adult D. variabilis ticks. Observations in both data sources were skewed to the early third of the tick season, although this was more exaggerated in iNaturalist data. Observations of ticks from both data sources positively correlated with human cases of Lyme disease.

Observed differences in tick characteristics between the two data sources may represent real differences between tick populations and human encounters with them. Some differences may be explained by observation, reporting, and sampling biases. Increased observations of ticks at the beginning of the season indicates potential utility of enhanced human Lyme disease surveillance at that time and may apply to other tick-borne disease risk management. These One Health findings signal an opportunity for early identification of high tickborne disease years through integrated active and passive tick surveillance that informs the conduct of human disease surveillance.