Matthew Baylis Liverpool University Climate and Infectious Diseases of Animals School of Veterinary Science

1. Zoonoses & climate change; NCZS 1/7/2010 Climate change and vector-borne diseases Matthew Baylis Liverpool University Climate and Infectious Diseases of Animals School of Veterinary Science

2. Who’s who? Black fly Mosquito Biting midge Tsetse fly Blowfly Sand fly Bot fly Horse fly Screwworm Louse Kissing bug

3. Arthropod vectors of human & animal disease zoonotic

4. Impact of human vector-borne diseasedeaths, 2004, thousands http://www.who.int/healthinfo/global_burden_disease/GBD_report_2004update_AnnexA.pdf

5. Impact of human vector-borne diseaseDALYS, 2004, thousands Filariasis & Onchocercosis – important causes of morbidity

6. Impact of animal vector-borne disease

7. Climate and disease • “We must understand how climate affects infectious diseases today before we can predict climate change’s impacts of the future” • (Foresight DIID, Future Threats, Appendix A) • Climate may affect: • Spatial distribution of outbreaks • Timing of disease outbreaks • Intensity or severity of outbreaks • Via effects on • Pathogens (when outside of host) • Hosts • Vectors • Epidemiological dynamics • Indirect effects

8. Climate-disease links: Trypanosomosis • Trypanosomosis • Trypanosomosis, spread by tsetse flies, imposes a huge burden on African people and livestock. • Vectors’ life cycles are sensitive to climate, and spatial distributions can be predicted using satellite-derived proxies for climate variables Source: David Rogers

9. Climate-disease links: AHS • African horse sickness • Lethal infectious disease of horses caused by a virus transmitted by Culicoides biting midges. • Large outbreaks of AHS are associated El Niño Southern Oscillation (ENSO)

10. Climate-disease links: Bluetongue • Vectorial capacity linked to temperature; • Vector-competence may be linked to temperature; • When larval stages are reared at high, sub-lethal temperatures, innate resistance to viral infection is overcome. • Non-vectors can be turned into vectors. Proportion of females positive for BTV 10 Rearing temperature /ºC

11. Climate change and vectors • Climate change will affect vector distributions, population sizes and seasonality; • Higher temperatures will affect vectorial capacity via effects on longevity, biting rate and EIP; • Higher temperatures may increase vector competence; • Climate change may affect vector dispersal; • Change in the frequency of extreme events (eg ENSO) may favour some vector-borne disease (RVF, AHS) Cattle being vaccinated against RVF in northeast Kenya, 2007

12. Bluetongue in Europe: recent history

13. Constant in time and space Mapping of BT’s past, present and future R0 • AIM: assess spatial & temporal • variations in BT R0 • under climate change scenarios • Two host species (Gubbins 2007) b: Prob. transmission of vector to host β: Prob. transmission of host to vector a: biting rate p: vector mortality rate n: 1/extrinsic incubation period m: ratio vectors to host (C: cattle, S: sheep) r:1/duration of viraemia in host (C,S) d: disease induced mortality rate (C,S) Φ: proportion of bites on each host species Constant in time

14. Vector to host transmission 20 MIDGES 5 MIDGES 1 MIDGE A bite from a single infected midge is able to transmit BTV to naïve sheep with 80-100% efficiency Host to vector transmission Of 3929 surviving midges, only 23 (0.6%) were infected with BTV

15. Vectors and host densities C. imicola Obsoletus (Gubbins 2007) Estimated by trap catches b: Prob. transmission of vector to host β: Prob. transmission of host to vector a: biting rate p: vector mortality rate n: 1/extrinsic incubation period m: ratio vectors to host (C: cattle, S: sheep) r:1/duration of viraemia in host (C,S) d: disease induced mortality rate (C,S) Φ: proportion of bites on each host species • . FAO: data set of livestock densities

16. Climate-sensitive variables in R0 • Lab or field studies: (Gubbins 2007) b: Prob. transmission of vector to host β: Prob. transmission of host to vector a: biting rate p: vector mortality rate n: 1/extrinsic incubation period m: ratio vectors to host (C: cattle, S: sheep) r:1/duration of viraemia in host (C,S) d: disease induced mortality rate (C,S) Φ: proportion of bites on each host species 80% 0.6%

17. Malaria changing links to climate Pre-intervention Contemporary PW Gethinget al.Nature465, 342-345 (2010) doi:10.1038/nature09098

18. Malaria’s changing R0 Pre-intervention Contemporary Decrease (order of magnitude) PW Gethinget al.Nature465, 342-345 (2010) doi:10.1038/nature09098

19. Malaria’s changing endemicity Changing global malaria endemicity since 1900. Pre-intervention endemicity Contemporary endemicity Change in endemicity (orders of magnitude) PW Gethinget al.Nature465, 342-345 (2010) doi:10.1038/nature09098

20. Predicting the future – malaria in SSA in 2030 Source: Simon Hay et al. Modelling review T8.2. Foresight DIID. Climate change increases human population at risk (PAR) by14.5% by 2030. Human population growth - increases PAR by 61% by 2030

21. With thanks to Institute for Animal Health Simon Carpenter Simon Gubbins Philip Mellor Peter Mertens Lelia O’Connell Beth Purse Funders Leverhulme Trust BBSRC EU Royal Society • University of Liverpool: • Cyril Caminade • Georgette Kluiters • Andrew Morse • CIRAD/UMR TETIS, France • Helene Guis • Annelise Tran • CITA, Zaragoza, Spain • Carlos Calvete