A large-scale stochastic spatiotemporal model for Aedes albopictus-borne chikungunya epidemiology.

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Published in PLoS One on March 31, 2017

Authors

Kamil Erguler1, Nastassya L Chandra2, Yiannis Proestos1, Jos Lelieveld3,1, George K Christophides4,5, Paul E Parham6

Author Affiliations

1: Energy, Environment and Water Research Center, The Cyprus Institute, 2121 Aglantzia, Nicosia, Cyprus.
2: Department of Infectious Disease Epidemiology, Faculty of Medicine, Imperial College London, London W2 1PG, United Kingdom.
3: Department of Atmospheric Chemistry, Max Planck Institute for Chemistry, D-55128 Mainz, Germany.
4: Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom.
5: Computation-based Science and Technology Research Center, The Cyprus Institute, 2121 Aglantzia, Nicosia, Cyprus.
6: Department of Public Health and Policy, Faculty of Health and Life Sciences, University of Liverpool, Liverpool L69 3GL, United Kingdom.

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