Oak acorn crop and Google search volume predict Lyme disease risk in temperate Europe

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Abstract

Lyme disease is a major zoonosis in the northern hemisphere. It is caused by the spirochete Borrelia burgdorferi, transmitted by ticks (genus Ixodes), and the abundance of infected tick nymphs determines the risk of the disease in humans. In eastern USA, fluctuations in oak (Quercus spp.) acorn production (including mast seeding) determine rodent abundance, which has been linked with Lyme borreliosis risk in humans. However, the predictive power of masting on Lyme disease risk in other systems has never been tested. We used a combination of field and Internet data to trace the ecological chain reaction that links acorn production by oaks and Lyme borreliosis risk in European forests. We found a positive relationship between oak acorn production (Q. robur and Q. petraea) in year T and the number of Lyme borreliosis incidences in year T + 2. Acorn production was also positively correlated with Google search volume for the terms “tick” and “Lyme disease” two years later. Our results suggest that acorn production influences tick population, leading to fluctuations in the intensity of interactions between humans and ticks that can be seen in Google search dynamics. Thus, mast seeding together with the volume of specific Internet web searches appears to be a promising tool that could be used to alert public.

Zusammenfassung

Die Lyme-Borreliose ist eine bedeutende Zoonose der nördlichen Hemisphäre. Sie wird von dem Spirochäten Borrelia burgdorferi verursacht und von Zecken (Gattung Ixodes) übertragen. Mit der Abundanz infizierter Zeckennymphen steigt das Krankheitsrisiko für den Menschen. In den östlichen USA bestimmen die Schwankungen der Eichelproduktion (Quercus spp.) mit dem Auftreten von Mastjahren die Abundanz der Kleinsäuger, die mit dem Lyme-Borreliose-Risiko für den Menschen in Zusammenhang gebracht wurde. In anderen Gegenden wurde die Vorhersagekraft der Mastjahre noch nicht getestet. Wir nutzten eine Kombination aus Freiland- und Internetdaten, um die ökologische Wirkungskette aufzuspüren, die Eichelproduktion und das Lyme-Borreliose-Risiko in europäischen Wäldern verbindet. Wir fanden eine positive Korrelation zwischen Eichelproduktion (Q. robur and Q. petraea) im Jahr T und der Anzahl von Lyme-Borreliose-Fällen im Jahr T + 2. Die Eichelproduktion war auch positiv mit dem Google-Suchvolumen für “Zecke” und “Lyme-Borreliose” im Jahr T + 2 korreliert. Unsere Ergebnisse legen nahe, dass die Eichelproduktion die Zeckenpopulation beeinflusst, was zu Schwankungen der Intensität der Interaktionen zwischen Mensch und Zecke führt, wie wir sie bei der Google-Suche beobachten können. Damit scheinen Eichelmast und Internet-Recherchen ein vielversprechendes Mittel zu sein, das für Warnungen an die Bevölkerung genutzt werden kann.

Introduction

Lyme borreliosis is the most common zoonosis and a major health concern in the northern hemisphere (Barbour and Fish, 1993, Pfäffle et al., 2013). It is caused by Borrelia burgdorferi sensu lato transmitted by hard–bodied ticks (genus Ixodes), and the abundance of infected tick nymphs is a good predictor of the disease risk in humans (Barbour and Fish, 1993, Ostfeld, 2010, Stafford et al., 1998). In the eastern United States temporal fluctuations in oak (Quercus spp.) acorn production (mast seeding: Crone and Rapp, 2014, Kelly, 1994) cause temporal variation in food provision for granivorous rodents, which shapes their population dynamics (McShea, 2000, Wolff, 1996). This in turn influences the abundance of infected tick nymphs and the risk of Lyme disease in humans (Jones, Ostfeld, Richard, Schauber& Wolff 1998a; Ostfeld, 2010, Ostfeld et al., 2006, Ostfeld et al., 1996, Schauber et al., 2005). However, the connection between masting and Lyme disease in the eastern United States has been disputed, given the variety of factors that may contribute to the disease risk (Estrada-Pena, 2009, Randolph, 1998).

The ecological link between mast seeding and Lyme disease in eastern United States is as follows. In summer after a good acorn year, host-seeking larvae of the blacklegged tick (Ixodes scapularis) co-occur with high abundance of rodents caused by previous year surplus food supply (Jones et al., 1998a, Ostfeld et al., 2006, Ostfeld et al., 2001). High rodent numbers increase larval feeding chances and survival, which leads to high nymph densities next season (Keesing et al., 2009, Ostfeld, 2010, Ostfeld et al., 2006). Moreover, high reservoir-competence of rodent hosts increases B. burgdorferi prevalence among tick nymphs (Ostfeld et al., 2001, Ostfeld et al., 2006). Next spring, numerous infected nymphs search for vertebrate hosts, including humans (Schauber et al. 2005). Nymphs are mostly responsible for transmitting Lyme disease to humans because their small size makes them difficult to detect. Moreover, their summer peak in activity coincides with the peak of human outdoor activity (Ostfeld, 2010, Barbour and Fish, 1993). Thus, oak acorn production in year T influences rodent abundance next year (T + 1), which subsequently affects infected nymph abundance and Lyme disease risk in year T + 2 (Barbour and Fish, 1993, Ostfeld et al., 2001, Ostfeld et al., 2006, Schauber et al., 2005).

Fluctuations in oak acorn production have similar effects on wildlife in Europe (Bogdziewicz et al., 2016, Jędrzejewska and Jędrzejewski, 1998, Pucek et al., 1993), but the effects of oak masting on the incidence of Lyme disease have not been studied. Seed fall in autumn determines rodent abundance next summer (Jensen, 1982, Pucek et al., 1993, Zwolak et al., 2016), and small mammals are a good reservoir for the Borrelia spirochete (Franke et al., 2013, Gern, 2008, Michalik et al., 2003, Siński et al., 2006). Moreover, the sheep tick (Ixodes ricinus), ecological equivalent of I. scapularis in the European host–tick–pathogen system, has similar ecology to the blacklegged tick (Barbour and Fish, 1993, Beytout et al., 2007, Hubálek et al., 2003, Korenberg et al., 2002, Siński et al., 2006). Thus, we hypothesize that a similar chain of ecological events linking acorn production and Lyme borreliosis risk might occur in Europe.

Traditional methods of gathering ecological data can be supplemented with new technologies. Temporal fluctuations in Google search volume and Wikipedia logs have been used to forecast influenza, dengue or tuberculosis outbreaks (Generous et al., 2014, Ginsberg et al., 2008, McIver and Brownstein, 2014). In a recent study, Google Trends were successfully used to collect national–scale data on fluctuations in rodent numbers, to study the role of rodent predation pressure in wood warbler (Phylloscopus sibilatrix) habitat selection (Szymkowiak & Kuczyński 2015). Indices of rodent abundance obtained using Google search engine were positively validated with field data (see details in Szymkowiak & Kuczyński 2015). Here, we used temporal changes in Google search volume to trace ecological chain reactions linking acorn production with Lyme disease risk. We assumed that people use the Internet as a source of information about ticks and Lyme disease. Hence, an increase in number of interactions between humans and ticks should lead to increase in the search volume of focal keywords. We selected two unambiguous keywords i.e., “kleszcz” (which stands for tick in Polish) and “borelioza” (Lyme disease), and calculated search volumes for each year of the study period. Moreover, we calculated search volumes for the term “na myszy” (in Polish: something for/against mice, hereafter “mice”) for each year as this appears to provide a reliable index of annual fluctuations in rodent numbers (cf. Szymkowiak & Kuczyński 2015).

We used our dataset to test the predictions derived from Ostfeld et al.’s works (referenced above). First, acorn production should positively influence rodent numbers (e.g. Pucek et al. 1993). Thus, we tested whether acorn production in year T positively correlates with Google index of mice abundance in year T + 1. Second, the positive effect of acorn production (year T) on rodent numbers (year T + 1) should translate into increase in intensity of tick-human interactions and, consequently, Lyme disease cases (in year T + 2). Thus, we tested whether Google index of rodent abundance in year T + 1 correlates positively with Google search volume for “tick” in year T + 2. Next, we tested whether acorn production (year T) correlates positively with Lyme disease-related key words (“tick” and “Lyme disease”), and Lyme disease casesin year T + 2. To our knowledge, this is the first study linking temporal fluctuations in acorn production with Lyme disease risk in Europe. Our research answers the call of Jones et al. (1998b), “Nevertheless, we hope that epidemiologists will test the power of acorn production as a predictor of Lyme disease risk in European oak forests”, which stayed ignored for almost 20 years.

Section snippets

Data collection

We extracted the epidemiological data on the number of reported cases of Lyme disease in Poland from annual (2006–2013) reports on infectious diseases (Fig. 1B). These data were collected by the Provincial Sanitary–Epidemiological Stations and provided by the National Institute of Public Health–National Institute of Hygiene in Poland (http://www.pzh.gov.pl/).

Data on annual acorn production of pedunculate (Quercus robur) and sessile oak (Q. petraea) were collected in years 2005–2011 for the

Results

As hypothesized, acorn production in year T was a good predictior of the number of Lyme disease cases in year T + 2 (Table 1 and Fig. 2C). We also found a postivie correlation between acorn production in year T and Google search volume for “tick” in year T + 2 (Table 1 and Fig. 2B). Moreover, there was a positive correlation between acorn production in year T and Google search volume for “mice” (T + 1) and “Lyme disease” (T + 2) (Fig. 2A and D), but both relationships were not significant at α = 0.05

Discussion

Risk of acquiring Lyme disease by humans is directly linked with the abundance and distribution of questing ticks. Thus, it is essential to understand factors shaping tick population dynamics. We used a combination of three sources of the data: National Institute of Hygiene in Poland on Lyme disease incidence, Polish State Forests on oak acorn crop, and Google Trends, and demonstrated that oak acorn production is associated with the Lyme disease risk in humans. The increase in Google searches

Acknowledgements

We would like to thank Rafał Zwolak and Anonymous Reviewers for critical comments on previous versions of our manuscript. The work was done while MB was supported by Polish National Science Centre grant “Harmonia” no. 2012/04/M/NZ8/00674, Adam Mickiewicz Foundation Scholarschip awarded in 2014, and NCN “Etiuda” grant no. 2015/16/T/NZ8/00018. JSZ was supported by Polish National Science Centre grant “Preludium” no. 2012/07/N/NZ8/00129. We are grateful to Jerzyna Przypaśniak from the State

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