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Methods A selective literature review was conducted to provide “proof of concept” for the value of the BPS ecological model in specifying risk pathways.A geospatial approach was used to visualize associations across key aspects of the model in relation to Lyme disease (LD), a significant zoonosis in the U.S. Due to increasing Lyme incidence in Pennsylvania, data representing key environmental, animal and human dimensions in this state were used. Data were aggregated to the county level and risk assessed using a total score. Maps were generated using QGISⓇ and ArcProⓇ. An accompanying Story Map web narrative, “One Health Connections” was produced as an interactive, public-facing intervention (accessed via QR Code, below).

data can be used to assess risk by generating ‘hotspots’ (see map to the right); however, integrated approaches are needed to fully understand risk and disease pathways. The biopsychosocial (BPS) model is broadly applied in medicine to understand causes and optimize management of mostly non-communicable disease. A recent ecological extension of the BPS model outlines determinants of health in a broad, ecological context 1. The BPS ecological framework identifies general biological/physical, psychological/behavioral, and social pathways that interact temporally across levels, from microorganisms to distal environments and socio-economic constructs. The high resolution of BPS pathways may add value to EH in elucidating zoonosis mechanisms.

Works Cited 1. Maier KJ, al'Absi M. Toward a Biopsychosocial Ecology of the Human Microbiome, Brain-Gut Axis, and Health. Psychosomatic Medicine 2017;79:947-957.2. Rupprecht TA et al. The pathogenesis of lyme neuroborreliosis: from infection to inflammation. Molecular Medicine (Cambridge, Mass) 2008;14:205-212.3. Pachner AR et al. Genotype determines phenotype in experimental Lyme borreliosis. Annals of Neurology 2004;56:361-370.4. Reisen WK. Landscape epidemiology of vector-borne diseases. Annual Review of Entomology 2010;55:461-483.5. Ogden NH et al. The emergence of Lyme disease in Canada. CMAJ: Canadian Medical Association Journal = Journal De L'association Medicale Canadienne 2009;180:1221-1224.6. Ebi KL et al. Detecting and Attributing Health Burdens to Climate Change. Environmental Health Perspectives 2017;125:085004-085004.7. Mitschler A et al. Knowledge & prevention of tick-bite borreliosis: survey of the population in Alsace, an endemic area (abstract). Annales De Dermatologie Et De Venereologie 2004;131:547-553.8. van der Heijden A et al. Social-cognitive determinants of the tick check: a cross-sectional study on self-protective behavior in combating Lyme disease. BMC Public Health 2017;17:900-900.9. Aenishaenslin C et al. Evidence of rapid changes in Lyme disease awareness in Canada. Ticks And Tick-Borne Diseases 2016;7:1067-1074.

10. Aenishaenslin C et al. Acceptability of tick control interventions to prevent Lyme disease in Switzerland and Canada: a mixed-method study. BMC Public Health 2016;16:12-12.11. Smith FD et al. Estimating Lyme disease risk using pet dogs as sentinels. Comparative Immunology, Microbiology and Infectious Diseases 2012;35:163-167.12. Little SE et al. Lyme borreliosis in dogs and humans in the USA. Trends in Parasitology 2010;26:213-218.13. Beaujean DJMA et al. Education on tick bite and Lyme borreliosis prevention, aimed at schoolchildren in the Netherlands: .... BMC Public Health 2016;16:1163-1163.14. Cetin E et al. Paradigm Burgenland: risk of B. burgdorferi sensu lato infection indicated by variable seroprevalence rates in hunters (abstract). Wiener Klinische Wochenschrift 2006;118:677-681.15. Schwartz BS, Goldstein MD. Lyme disease in outdoor workers: risk factors, preventive measures, and tick removal methods. American Journal of Epidemiology 1990;131:877-885.16. Šmit R, Postma MJ. Vaccines for tick-borne diseases and cost-effectiveness of vaccination: a public health challenge to reduce the diseases' burden. Expert Review of Vaccines 2016;15:5-7.17. Aronowitz RA. The rise and fall of the lyme disease vaccines: a cautionary tale for risk interventions in American medicine and public health. The Milbank Quarterly 2012;90:250-277.18. Nigrovic LE, Thompson KM. The Lyme vaccine: a cautionary tale. Epidemiology and Infection 2007;135:1-8.19. Clayton JL et al. Enhancing Lyme Disease Surveillance by Using Administrative Claims Data, Tennessee, USA. Emerging Infectious Diseases 2015;21:1632-1634.20. van den Wijngaard CC et al. The cost of Lyme borreliosis. European Journal of Public Health 2017;27:538-547.

HUMAN Proportion of outdoor workers (agriculture,forestry, fishing, hunting) out of total workforce (US Census, 2016)

ANIMAL Rate of Lyme in domestic dogs based onprevalence of cases (Companion Animal Parasite Council, 2017) and number of licences sold (PA Dept of Ag., 2017)

Reema Persad-Clem, Ph.D. reema_persadclem@berkeley.edu +15106647979 Karl Maier, Ph.D. kjmaier@salisbury.edu +14105436374

Conclusions Integrated approaches to infectious disease are needed to more fully understand pathwaysof zoonosis across humans, animals, and environments. The BPS ecological model helps specify plausible routes across the relevant disciplinary domains of biology, psychology/behavior, and other social sciences, and represents a unifying framework for a range of EH stakeholders to better conceptualize zoonosis prevention and intervention. The high resolution of interacting factors outlined in this ecological framework provides added value to currently available models for elucidating pathways of zoonotic disease. The utility of this ecological framework is enhanced using geospatial techniques that visualize the intricate and dynamic pathways of zoonoses in concrete terms that easily translate for broad use in various research, educational, and public health policy and outreach efforts.

c

Distal

Intermediate

Proximal

Micro(Infection)

Google Trends searches by county (e.g., Lyme symptoms)Social support by zipcode (e.g., PA Lyme Resource Network)

FUTURE DATA OPTIONS

Municipality/suburban development (e.g., PASDA, PA-DEP)Landscape markers (e.g., National Land Cover Database)

Migratory bird citizen science surveillance data (e.g., eBird)Hunting licence sales (e.g., PA Game Commission)

ENVIRONMENT Density of green leafy vegetation‘level of greeness’ in 2014 using remote sensing data (Normalized Difference Vegetation Index, 2014)

GIS DATA USED

ECOHEALTH RISK INDICATORS

Risk of Lyme disease for outdoor workers in Pennsylvania using an EcoHealth approach. Based on the total score, individuals in this population are at high risk of exposure in Jefferson, Huntingdon, Montour and Wyoming counties (left to right) (Source: US Census, USGS, PDA, NDVI, CAPC)

*Scan this QR Code to access anaccompanying Story Map webnarrative that includes a space-timecube animation showing humanLyme incidence data in Pennsylvaniafrom 2000-2016

Biolog

ical/

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Time*

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Psychological/Behavioral

Emerging hot spots of Lyme disease in Pennsylvania based on incidence data from 2000-16. (Source: CDC)

Acknowledgements C. Smith, J. Casey, S., S. Mukhtyar (UC Berkeley), PA Dept. of Agriculture

Select Literature Identifying Biopsychosocial Pathways of Lyme Disease Infection RiskMOVING BEYOND INCIDENCE:

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Add to this literature: Proximal Intermediate Distal

Biological/Physical

Pathogenesis from infection to neural dysfunction 2

Genetic heterogeneity of B. burgdorferi may impact clinical presentation 3Human effects on ecosystems facilitate pathogen transmission 4 Infections in Canada linked to I. scapularis 5

Landscape epidemiology 4 & climate change 6

Psychological/Behavioral

Pathogenesis from infection to neural dysfunction 2

Fear & preventive behavior 7Knowledge & preventive behavior 7 self-efficacy & intention to tick check 8 Public awareness 9

Perceived efficacy & acceptability of PH interventions 10

Social

Ticks on dogs 11 & B. burgdorferi antibodies in dogs 12 identify risk areasSocio-cognitive (perceived norms) correlates of tick checking 8

Awareness/education interventions 9,13

Hunting 14 & occupational 15 exposureLD vaccine-related cost effectiveness 16 public opinion, media, & policy 17,18 Insurance claims data may help identify cases 19

Economic cost 20

Public opinion & media on LD vaccines 17,18

Specifying Ecohealth Pathways of Zoonotic Disease Through a Unifying Biopsychosocial Ecological Framework and Geospatial Mapping

TRADITIONAL INCIDENCE DATA Introduction EcoHealth (EH) has heuristic value for its ability to convey the interdependence of ecosystem, human, and animal health. Incidence

Citation: Persad-Clem, R. A., Maier, K. J. (2018, June). Specifying ecohealth pathways of zoonotic disease through a unifying biopsychosocial ecological framework and geospatial mapping. Poster presented at the 5th International One Health Congress, Saskatoon, Canada.

Specifying ecohealth pathways of zoonotic disease through a unifying biopsychosocial ecological framework and geospatial mapping.