1. Jan van Dijk Cyril Caminade Diana Williams Matthew Baylis 01/07/2010 Sharp increases in UK Fasciola hepatica abundance: driven by climate change? DELIVER

2. The life cycle of Fasciola hepatica

3. Fasciola as a zoonosis Worldwide 2.5 million people infected (mainly southern America, France/Portugal and Egypt) 180 million people thought to be at risk of infection Especially women and children affected Infection associated with consumption of raw vegetables/salad leaves grown on irrigated pasture Severe fluke infection has been described in children in the Lake District (wild watercress)

4. Fasciola in livestock Chronic wasting/ production losses in cattle and sheep Acute death also observed in sheep Worldwide, economic losses estimated at $US 3 billion Evidence of infection in 70% of UK dairy herds Losses in UK cattle alone total £40 million p.a.

5. Trends: Chronic GB fasciolosis (VIDA database 1977-2008) Cattle r s = 0.829, p < 0.001 Sheep r s = 0.771, p < 0.001

6. NB: Other parasites appear to do well too… Teladorsagiosis/ Trichostrongylosis Haemonchosis Nematodirosis All trends r s ≥0.540, p≤0.004 Round worms infecting sheep

7. Diagnoses Laboratory submissions Stocking density Motivation farmer (Lamb price) Anthelmintic resistance Tests available Climate change Veterinary Surveillance (VIDA) dataset Causal web Analysis of confounders: only climate (change), and perhaps anthelmintic resistance, likely to significantly influence diagnostic rate (van Dijk et al. 2008)

8. Recent UK trends (past 5-10 years) Sharp overall UK increase in fasciolosis incidence Many reports on increase coming from Scotland Emergence in (south) east Scotland Emergence in East Anglia (2002) Acute fasciolosis in calves and adult pigs Emergence of the rumen fluke Paramphistomum Hypotheses: “It must be climate change” Increase in animal movements Resistance to wormers

9. JanuaryDecemberJune Egg output Egg development Ollerenshaw (1959) Multiplication in snail Metacercariae (herbage) Disease Back to basics - Summer infection Start e.g. Acute disease in autumn mainly resulting from eggs which developed during April-June and cercariae developed (in snail) during July-September

10. JanuaryDecemberJune Egg output Egg development Ollerenshaw (1959) Multiplication in snail - year 1 Metacercariae (herbage) - year 2 Disease Back to basics - Winter infection Multiplication in snail - year 2

11. Chronic fasciolosis (1977-2007) --- + - - Cattle Sheep Spearman: Increased over-winter survival snails? Decrease in over-winter survival metacercariae? (NB: van Dijk et al. 2008 reported the same for nematodes)

12. Acute fasciolosis (1977-2007) -Sheep r s = 0.616, p < 0.001 First significant: 2001 Spearman: +++ Increased over- winter survival snails? Earlier start to the summer infection?

13. The timing of development of various stages Results: Egg developmentIn-snail development (release of first cercaria) SW- Scotland76 +/- 28 days April 5 th - June 25 th 37 +/- 10 days June 11 th – July 28 th SW-England88 +/- 33 days March 25 th - June 28 th 37 +/- 8 days June 8 th – July 23 rd Egg development mainly April-June; But June also appears to be an important month for the development of cercaria. The rate of development of cercaria is relatively independent of temperature.

14. Validation timing development: add in-host development and predict outbreaks Frequency distribution of VIDA- recorded first outbreaks of summer infection-related acute fasciolosis, Scotland, 1977-2007 Mean 95% CI Predicted:

15. Building a simple regression model (1) For the 4 most sheep-dense regions, calculate mean minimum and maximum monthly temperature, total rainfall and rainydays (>1mm rain) from surrounding weather stations and correlate with disease abundance data, 1977- 2007 Correlate summed April-June (egg development), July-September (cercarial development) and Jan- October periods (all development)

16. Building a simple regression model (2) In all 4 regions peak disease incidence always significantly correlated to minimum temperature in April-June (r s ≥ 0.495, p ≤ 0.01) Rainydays (April-June) stronger correlated than total rainfall In Southwest/Wales stronger correlations with rainydays than in North/Scotland In Scotland and North stronger correlations with temperature

17. A simple regression model (y = ax + b) mean monthly minimum temperature April-June and total rainydays in April-June explain approx. 50% of the annual variation in diagnostic rate in all 4 regions Run this model on 40 year’s worth of UK ‘GIS data’ (state-of-the-art Ensembles models, Geography department, University of Liverpool ):

18. UK and Ireland divided into 25 km squares Each square expressed as a ~ 40 year anomaly of itself (red: ‘more fluke’, blue: ‘less fluke’)

19. But if fluke is rain-dependent, λ (T) P M1(T) P SI1(R,S) P SS1 P SM M S(T,R) P MC P EH β H q (μ C(T) + βH) μ A F 0 = why is there so much more of it? F 0 = basic reproduction quotient for fluke = the predicted number of adult offspring of a single fluke being present in a non-immune host for one year

20. Model output validation sensitivity analysis (temperature) Blue = predicted success Red = measured (disease)

21. Loss of rainy days (per month) → Fasciola offspring → Southwest Scotland Fasciola: trade- off in the effects of temperature and rainfall Horizontal (dotted) line: current situation Sloped lines: 1°C increase

22. Fasciola: trade- off in the effects of temperature and rainfall In the UK, temperature strongly limits developmental success ‘parasite success’ increases on a logarithmic scale with increasing temperatures, almost regardless of rainfall

23. Fasciolosis- Conclusions Together, temperature and rainfall can explain all observed UK changes in parasite abundance Climate change will alter seasonality and spatial distribution in ways which may be counter-intuitive In the UK, the effect of increasing temperature is likely to outweigh the effect of decreasing rainfall It appears that prevalence of acute autumn fasciolosis can be predicted in early summer

24. questions?answers?