Novel sampling method for assessing human-pathogen interactions in the natural environment using boot socks and citizen scientists, with application to Campylobacter seasonality

This paper introduces a novel method for sampling pathogens in natural environments. It uses fabric boot socks worn over walkers' shoes to allow the collection of composite samples over large areas. Wide-area sampling is better suited to studies focusing on human exposure to pathogens (e.g., recreational walking). This sampling method is implemented using a citizen science approach: groups of three walkers wearing boot socks undertook one of six routes, 40 times over 16 months in the North West (NW) and East Anglian (EA) regions of England. To validate this methodology, we report the successful implementation of this citizen science approach, the observation that Campylobacter bacteria were detected on 47% of boot socks, and the observation that multiple boot socks from individual walks produced consistent results. The findings indicate higher Campylobacter levels in the livestock-dominated NW than in EA (55.8% versus 38.6%). Seasonal differences in the presence of Campylobacter bacteria were found between the regions, with indications of winter peaks in both regions but a spring peak in the NW. The presence of Campylobacter bacteria on boot socks was negatively associated with ambient temperature (P = 0.011) and positively associated with precipitation (P < 0.001), results consistent with our understanding of Campylobacter survival and the probability of material adhering to boot socks. Campylobacter jejuni was the predominant species found; Campylobacter coli was largely restricted to the livestock-dominated NW. Source attribution analysis indicated that the potential source of C. jejuni was predominantly sheep in the NW and wild birds in EA but did not differ between peak and nonpeak periods of human incidence

Climate, human behaviour or environment: individual-based modelling of Campylobacter seasonality and strategies to reduce disease burden

Acknowledgements: We thank colleagues within the Modelling, Evidence and Policy Research Group for useful feedback on this manuscript. Competing interests: The authors declare that they have no competing interests. Availability of data and materials: The R code used in this research is available at https://gitlab.com/rasanderson/campylobacter-microsimulation; it is platform independent, R version 3.3.0 and above. Funding: This research was funded by Medical Research Council Grant, Natural Environment Research Council, Economic and Social Research Council, Biotechnology and Biological Sciences Research Council, and the Food Standards Agency through the Environmental and Social Ecology of Human Infectious Diseases Initiative (Sources, seasonality, transmission and control: Campylobacter and human behaviour in a changing environment (ENIGMA); Grant Reference G1100799-1). PRH, SJO’B, and IRL are funded in part by the NIHR Health Protection Research Unit in Gastrointestinal Infection, at the University of Liverpool. PRH and IRL are also funded in part by the NIHR Health Protection Research Unit in Emergency Preparedness and Response, at King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health or Public Health England.Peer reviewedPublisher PD