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By-degree Health and Economic Impacts of Lyme Disease, Eastern and Midwestern United States.

Haisheng YangCaitlin A GouldRuss JonesAlexis St JulianaMarcus SarofimMatt RissingMicah B Hahn
Published in: EcoHealth (2024)
Lyme disease (LD) is the most common vector-borne disease in the United States (U.S.). This paper assesses how climate change may influence LD incidence in the eastern and upper Midwestern U.S. and the associated economic burden. We estimated future Ixodes scapularis habitat suitability and LD incidence with a by-degree approach using variables from an ensemble of multiple climate models. We then applied estimates for present-day and projected habitat suitability for I. scapularis, present-day presence of Borrelia burgdorferi, and projected climatological variables to model reported LD incidence at the county level among adults, children, and the total population. Finally, we applied an estimate of healthcare expenses to project economic impacts. We show an overall increase in LD cases with regional variation. We estimate an increase in incidence in New England and the upper Midwestern U.S. and a concurrent decrease in incidence in Virginia and North Carolina. At 3°C of national warming from the 1986-2015 baseline climate, we project approximately 55,000 LD cases, a 38-percent increase from present-day estimates. At 6°C of warming, our most extreme scenario, we project approximately 92,000 LD cases in the region, an increase of 145 percent relative to current levels. Annual LD-related healthcare expenses at 3°C of warming are estimated to be $236 million (2021 dollars), approximately 38 percent greater than present-day. These results may inform decision-makers tasked with addressing climate risks, the public, and healthcare professionals preparing for treatment and prevention of LD.
Keyphrases
  • climate change
  • healthcare
  • human health
  • risk factors
  • quality improvement
  • mental health
  • young adults
  • public health
  • south africa
  • machine learning
  • tertiary care
  • locally advanced
  • convolutional neural network