Background. Analysis Cross-correlation. Outcome Optimal time lags for the use of climate data. Analysis

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1 Seasonality in the proportions of domestic cats shedding Toxoplasma gondii is associated with climatic factors relevance for epidemiological studies Schares, G. 1,*, Ziller, M. 1, Herrmann, D.C. 1, Globokar, M.V. 2, Pantchev, N. 2, Conraths, F.J. 1 Climate Background Examination of 61,224 feline faecal samples (flotation) over a period of 55 months (June 2007-December 2011; mean sample number 1113/month (Min. 688 Max. 1666) PCR to differentiate between T. gondii and H. hammondi oocysts Seasonality in proportion of cats shedding oocysts of T. gondii and H. hammondi 1 Friedrich-Loeffler-Institut, Greifswald-Insel Riems, Germany 2 IDEXX Laboratories, Ludwigsburg, Germany Results stratification by season Seasonality in cats shedding oocysts Toxoplasma gondii: mainly from summer to autumn Hammondia hammondi: mainly in winter Hypothesis: Climate parameters are able to explain this seasonality Is it possible to predict monthly proportions of cats shedding oocysts by using climate parameters? Analysis Cross-correlation Outcome Optimal time lags for the use of climate data Analysis Data used to fit generalised linear models (GLMs) Proportions of cats shedding oocysts Temperature (Temp a ) Precipitation (Rain a )? Optimal time lags Outcome Models to predict monthly proportions of cats shedding oocysts North-Atlantic- Ocillation- Index (NAO b ) a Climate Data Center (CDC) of the German Weather Service b Climatic Research Unit, University of East Anglia, Norwich, UK 1

2 North Atlantic Oscillation Results cross correlation NAO index positive NAO index negative Cross correlation analysis monthly proportions of oocyst shedding cats vs monthly climate data Dierke, Globus online Different optimal time lags depending on the parasite species T. gondii (A) Temperature (Temp): 2 months Precipitation (Rain): 3 months NAO: 7 months H. hammondi (B) Temperature (Temp): 6 months Precipitation (Rain): 5 months NAO: 11 months Results generalised linear models Results generalised linear models GLM to predict monthly proportions of cats shedding T. gondii parameters tested individually Model name (AIC, Pseudo R 2 ) a Parameter b Value S.E. Pr(> z ), Significance Temp-2 GLM to predict monthly proportions of cats shedding T. gondii parameters tested in combination Model name (AIC, Pseudo R 2 ) a Parameter b Value S.E. Pr(> z ), Significance Temp-2, NAO-7 TG5 (154.50, 23.3%) Intercept < 2e-16 c TG2 (150.0, 39.3%) Intercept < 2e-16 c Temp d Temp e TG6 (155.53, 25.9%) (Intercept) < 2e-16 c NAO e NAO d a Akaike s Information Criterion (AIC) and Pseudo R 2 characterizing the level of the explained variance. b Temp-2, temperature data of 2 months prior; Rain-3, rain data of 3 months prior; NAO-7, North Atlantic TG7 ( %) (Intercept) < 2e-16 c Oscillation (NAO) index data of 7 months prior to the observation of oocysts in faecal samples of cats. c Statistically significant at P < d Statistically significant at P < e Statistically significant at P < Rain e a Akaike s Information Criterion (AIC) and Pseudo R 2 characterizing the level of the explained variance. b Temp-2, temperature data of 2 months prior; Rain-3, rain data of 3 months prior; NAO-7, North Atlantic Oscillation (NAO) index data of 7 months prior to the observation of oocysts in faecal samples of cats. c Statistically significant at P < d Statistically significant at P < e Statistically significant at P <

3 Results generalised linear models GLMs to predict monthly proportions of cats shedding H. hammondi Model name (AIC, Pseudo R 2 ) a Parameter b Value S.E. Pr(> z ), Significance HH2 (138.7, 40.2%) Intercept < 2e-16 c Temp e NAO d HH1.2.1 (133.7, 52.4%) (A) Intercept < 2e-16 c Temp-6, Rain-5:NAO-11 Discussion Models to predict monthly proportions of cats shedding - T. gondii (summer-autumn, A) and - H. hammondi (winter, B) had similarities NAO winter data: High Mild winter More oocysts survive? Temperature rise in summer: Triggers breeding in birds, rodents Sporulation of oocysts faster More infected hosts Temp e Rain-5:NAO c HH5 (145.2, 15.1%) (B) Intercept < 2e-16 c Temp d HH6 (142.3, 31.3%) Intercept < 2e-16 c NAO c HH7 (150.0, 11.0%) Intercept < 2e-16 c Temp-6 Rain e a Akaike s Information Criterion (AIC) and Pseudo R 2 characterizing the level of the explained variance. b Temp-6, temperature data of 6 months prior; Rain-5, rain data of 5 months prior; NAO-11, North Atlantic Oscillation (NAO) index data of 11 months prior to the observation of oocysts in faecal samples of cats. c Statistically significant at P < d Statistically significant at P < e Statistically significant at P < Conclusions (1 st part) Relevance of seasonality. for humans? In both parasites climate data can be used to predict monthly proportions of cats shedding oocysts models for T. gondii and H. hammondi differ largely to explain differences between years, North Atlantic Oscillation (NAO) seems to be essential This suggests that global warming, which is associated with a high winter NAO, can influence the infection risk for animals and humans with T. gondii and H. hammondi in Europe. Germany cases reported to Robert-Koch-Institut - accessible via SurvStat RKI (period of time analysed: Jan Dec. 2014) Time lag - Time between shedding of oocysts and uptake by intermediate hosts - lifetime of livestock animal Germany actually most children are born during summer (based on data provided by Statistisches Bundesamt, 2012) Time lag - disease development - duration of pregnancy - lag between diagnosis and report 3

4 Proportion of cases No. cases 10/06/2016 Relevance of seasonality. for humans? Relevance of seasonality. for humans? Are there further reports on seasonality for human cases of toxoplasmosis? Serbia (Bobic et al., 2010) o o o majority of symptomatic patients were diagnosed between October and March (p=0.049). most asymptomatic acute infections were diagnosed between February and July (p=0.0037) (avidity analysis suggests earlier infection). Undercooked meat consumption was shown as a risk factor for symptomatic infection in the October March period (odds ratio 7.67, 95% CI ). * The Netherlands, significantly more children with ocular toxoplasmosis in May? (Meenken et al., 1991) * Germany cases reported to Robert-Koch-Institut - accessible via SurvStat RKI (data limited to the Federal State of Saxony, period of time analysed: Jan Dec. 2014) Germany acute cases of toxoplasmosis in humans from (Braveny et al., 1973) Slovenia, increased infection risk in winter and spring? (Logar et al., 2005) majority of cases in the first half of a year. Relevance of seasonality. in animals? Jokelainen et al., 2012: Most of the cases of fatal toxoplasmosis in brown hares were diagnosed during the cold winter months, which is consistent with observations from other Nordic countries (Hülphers et al., 1947; Christiansen and Siim, 1951). Schulzig & Fehlhaber, 2005: Comparing the results gained in different seasons significant more pigs were found to be infected during the autumn/winter than in the spring/summer period. Relevance of NAO. for humans? Hubálek, Z., North Atlantic weather oscillation and human infectious diseases in the Czech Republic, Eur. J. Epidemiol. 20, Winter NAO, mean Dec-March Toxoplasmosis in hares 8% 6% 4% 2% 0% Dec-Feb Mar-May Jun-Aug Sep-Nov Hülphers et al., 1947 (Sweden) Toxoplasmosis in brown hares Dec-Feb Mar-May Jun-Aug Sep-Nov Jokelainen et al., 2012 (Finland) Proportion of positives 8.00% 6.00% 4.00% 2.00% 0.00% Seropositivity in fattening pigs Spring/Summer Autumn/Winter Schulzig & Fehlhaber, 2005 (Germany) 4

5 Relevance of NAO. for animals? Relevance. for planning studies on T. gondii? Afonso, E., et al Environmental determinants of spatial and temporal variations in the transmission of Toxoplasma gondii in its definitive hosts. International Journal for Parasitology. Parasites and Wildlife 2, Of course Outcome affected by period of sampling within a year Cross-sectional studies (sampling usually during a short period) Case-control studies (problem: cases and controls sampled during different periods of time) Short-term intervention studies Differences in outcome between different years (NAO) Long-term studies (e.g. intervention studies) We would like to thank. Aline Maksimov, Diana Herold, Andrea Bärwald and Susann Schares for their excellent technical assistance. Dr. Pavlo Maksimov for helpful suggestions Further we want to thank Dr. Christian Imholt, Vertebrate Research Group, Julius-Kühn-Institut, Federal Research Institute for Cultivated Plants, Münster, Germany, for helpful discussions on rodent biology. The German Federal Ministry of Education and Research (BMBF) for funding (01 KI0765 and 01 KI F). Thank you for your attention. Proportion of cases 0.20% 0.15% 0.10% 0.05% 0.00% T. gondii positive cats Proportion of cases H. hammondi positive cats 0.15% 0.10% 0.05% 0.00% 5

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