Opposing Patterns of Spatial Synchrony in Lyme Disease Incidence

TL;DR

Lyme disease incidence shows opposing patterns of spatial synchrony in the Northeast and upper Midwest, influenced by factors like land cover and poverty.

Contribution

The study identifies two distinct regions with opposing synchrony patterns and explores how ecological and social factors influence these patterns.

Findings

Lyme disease incidence shows spatial synchrony in the Northeast and upper Midwest with opposing temporal fluctuations.

Land cover, weather, poverty, and awareness of tick-borne illness partly explain spatial synchrony patterns.

The two regions may be becoming more synchronous over time, leading to larger nationwide disease fluctuations.

Abstract

Incidence of Lyme disease, a tick-borne illness prevalent in the US, is increasing in endemic regions and regions with no previous history of the disease, significantly impacting public health. We examined space–time patterns of Lyme disease incidence and the influence of ecological and social factors on spatial synchrony, i.e., correlated incidence fluctuations across US counties. Specifically, we addressed these questions: Does Lyme disease incidence exhibit spatial synchrony? If so, what geographic patterns does Lyme disease synchrony exhibit? Are geographic patterns of disease synchrony related to weather, land cover, access to health care, or tick-borne disease awareness? How do effects of these variables on Lyme disease synchrony differ geographically? We used network analysis and matrix regression to examine geographical patterns of Lyme disease synchrony and their potential mechanisms in 399 counties in the eastern and Midwestern US. We found two distinct regions of synchrony in Northeast and upper Midwest regions exhibiting opposing temporal fluctuations in incidence. Spatial patterns of Lyme disease synchrony were partly explained by land cover, weather, poverty, and awareness of tick-borne illness, with significant predictive variables changing regionally. However, the two regions may have become more synchronous over time, potentially leading to higher-amplitude nation-wide fluctuations in disease incidence.

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