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Sharp increases in UK Fasciola hepatica abundance: driven by climate change? Jan van Dijk Cyril Caminade Diana Williams Matthew Baylis DELIVER 01/07/2010 The life cycle of Fasciola hepatica 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) 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. Trends: Chronic GB fasciolosis (VIDA database 1977-2008) 2.5 2 1.5 Cattle 1 rs = 0.829, p < 0.001 0.5 0 1975 1980 1985 1990 1995 2000 2005 2010 4 3.5 3 Sheep 2.5 2 1.5 rs = 0.771, p < 0.001 1 0.5 0 1975 1980 1985 1990 1995 2000 2005 2010 NB: Other parasites appear to do well too… Teladorsagiosis/ Trichostrongylosis Round worms infecting sheep Haemonchosis Nematodirosis All trends rs≥0.540, p≤0.004 Veterinary Surveillance (VIDA) dataset Causal web Stocking density Motivation farmer (Lamb price) Laboratory submissions Diagnoses Tests available Anthelmintic resistance Climate change Analysis of confounders: only climate (change), and perhaps anthelmintic resistance, likely to significantly influence diagnostic rate (van Dijk et al. 2008) 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 Back to basics - Summer infection Ollerenshaw (1959) Disease Metacercariae (herbage) Multiplication in snail Start Egg development Egg output January June e.g. Acute disease in autumn mainly resulting from eggs which developed during April-June and cercariae developed (in snail) during July-September December Back to basics - Winter infection Disease Metacercariae (herbage) - year 2 Multiplication in snail - year 2 Multiplication in snail - year 1 Egg development Egg output January June Ollerenshaw (1959) December Chronic fasciolosis (1977-2007) 0.25 0.2 0.15 0.1 Cattle 0.05 0 Jan Spearman: Feb Mar Apr - - - May Jun Jul + Aug Sep Oct Nov Dec Increased over-winter survival snails? 0.25 Decrease in over-winter survival metacercariae? (NB: van Dijk et al. 2008 reported the same for nematodes) 0.2 0.15 0.1 Sheep 0.05 0 Jan Spearman: Feb - - Mar Apr May Jun Jul Aug Sep Oct Nov Dec Acute fasciolosis (1977-2007) -Sheep 2 1.8 1.6 1.4 1.2 1 rs = 0.616, p < 0.001 0.8 0.6 0.4 First significant: 2001 0.2 0 1975 1980 1985 1990 1995 2000 2005 2010 Earlier start to the summer infection? 0.35 0.3 0.25 Increased overwinter survival snails? 0.2 0.15 0.1 0.05 0 Jan Spearman: Feb Mar Apr May Jun + Jul Aug Sep + + Oct Nov Dec The timing of development of various stages Egg development Results: In-snail development (release of first cercaria) SW- Scotland 76 +/- 28 days SW-England 37 +/- 10 days April 5th - June 25th June 11th – July 28th 88 +/- 33 days 37 +/- 8 days March 25th - June 28th June 8th – July 23rd 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. Validation timing development: add in-host development and predict outbreaks 0.45 Frequency distribution of VIDArecorded first outbreaks of summer infection-related acute fasciolosis, Scotland, 1977-2007 0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 August September October Predicted: 95% CI Mean 95% CI November December 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, 19772007 • Correlate summed April-June (egg development), July-September (cercarial development) and JanOctober periods (all development) Building a simple regression model (2) • In all 4 regions peak disease incidence always significantly correlated to minimum temperature in April-June (rs ≥ 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 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 ): UK and Ireland divided into 25 km squares Each square expressed as a ~ 40 year anomaly of itself (red: ‘more fluke’, blue: ‘less fluke’) But if fluke is rain-dependent, why is there so much more of it? λ(T) PM1(T) PSI1(R,S) PSS1 PSM MS(T,R) PMC PEH β H q F0 = (μC(T) + βH) μA F0 = 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 Model output Blue = predicted success Red = measured (disease) validation sensitivity analysis (temperature) Fasciola: trade- off in the effects of temperature and rainfall Fasciola offspring → Scotland Horizontal (dotted) line: current situation Sloped lines: 1°C increase Southwest Loss of rainy days (per month) → 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 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 questions? answers?