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Effects of Temperature on Emergence and Seasonality of West Nile Virus in California
David M. Hartley
David M. Hartley
Fogarty International Center, National Institutes of Health, Bethesda, Maryland; Imaging Science and Information Systems Center and Departments of Microbiology and Immunology and Radiology, Georgetown University Medical Center, Washington, District of Columbia; Center for Vectorborne Diseases, University of California, Davis, California; Center for Disease Dynamics, Economics and Policy, Resources for the Future, Washington, District of Columbia; Department of Biological Sciences, Old Dominion University, Norfolk, Virginia
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Christopher M. Barker
Christopher M. Barker
Fogarty International Center, National Institutes of Health, Bethesda, Maryland; Imaging Science and Information Systems Center and Departments of Microbiology and Immunology and Radiology, Georgetown University Medical Center, Washington, District of Columbia; Center for Vectorborne Diseases, University of California, Davis, California; Center for Disease Dynamics, Economics and Policy, Resources for the Future, Washington, District of Columbia; Department of Biological Sciences, Old Dominion University, Norfolk, Virginia
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Arnaud Le Menach
Arnaud Le Menach
Fogarty International Center, National Institutes of Health, Bethesda, Maryland; Imaging Science and Information Systems Center and Departments of Microbiology and Immunology and Radiology, Georgetown University Medical Center, Washington, District of Columbia; Center for Vectorborne Diseases, University of California, Davis, California; Center for Disease Dynamics, Economics and Policy, Resources for the Future, Washington, District of Columbia; Department of Biological Sciences, Old Dominion University, Norfolk, Virginia
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Tianchan Niu
Tianchan Niu
Fogarty International Center, National Institutes of Health, Bethesda, Maryland; Imaging Science and Information Systems Center and Departments of Microbiology and Immunology and Radiology, Georgetown University Medical Center, Washington, District of Columbia; Center for Vectorborne Diseases, University of California, Davis, California; Center for Disease Dynamics, Economics and Policy, Resources for the Future, Washington, District of Columbia; Department of Biological Sciences, Old Dominion University, Norfolk, Virginia
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Holly D. Gaff
Holly D. Gaff
Fogarty International Center, National Institutes of Health, Bethesda, Maryland; Imaging Science and Information Systems Center and Departments of Microbiology and Immunology and Radiology, Georgetown University Medical Center, Washington, District of Columbia; Center for Vectorborne Diseases, University of California, Davis, California; Center for Disease Dynamics, Economics and Policy, Resources for the Future, Washington, District of Columbia; Department of Biological Sciences, Old Dominion University, Norfolk, Virginia
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William K. Reisen
William K. Reisen
Fogarty International Center, National Institutes of Health, Bethesda, Maryland; Imaging Science and Information Systems Center and Departments of Microbiology and Immunology and Radiology, Georgetown University Medical Center, Washington, District of Columbia; Center for Vectorborne Diseases, University of California, Davis, California; Center for Disease Dynamics, Economics and Policy, Resources for the Future, Washington, District of Columbia; Department of Biological Sciences, Old Dominion University, Norfolk, Virginia
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Temperature has played a critical role in the spatiotemporal dynamics of West Nile virus transmission throughout California from its introduction in 2003 through establishment by 2009. We compared two novel mechanistic measures of transmission risk, the temperature-dependent ratio of virus extrinsic incubation period to the mosquito gonotrophic period (BT), and the fundamental reproductive ratio (R0) based on a mathematical model, to analyze spatiotemporal patterns of receptivity to viral amplification. Maps of BT and R0 were created at 20-km scale and compared throughout California to seroconversions in sentinel chicken flocks at half-month intervals. Overall, estimates of BT and R0 agreed with intensity of transmission measured by the frequency of sentinel chicken seroconversions. Mechanistic measures such as these are important for understanding how temperature affects the spatiotemporal dynamics of West Nile virus transmission and for delineating risk estimates useful to inform vector control agency intervention decisions and communicate outbreak potential.
Author Notes
Financial support: This study was supported by the Research and Policy for Infectious Disease Dynamics program of the Science and Technology Directorate, Department of Homeland Security and the Fogarty International Center, National Institutes of Health. Christopher M. Barker and William K. Reisen are supported, in part, by Centers for Disease Control and Prevention grant U01EH000418 to study the impacts of climate change on mosquitoborne virus transmission, and National Institutes of Allergy and Infectious Diseases, National Institues of Health grant R01 AI55607 to model amplification of WNV.
Authors' addresses: David M. Hartley and Tianchan Niu, Georgetown University Medical Center, Washington DC, E-mails: Hartley@isis.georgetown.edu and Niu@isis.georgetown.edu. Christopher M. Barker and William K. Reisen, Center for Vectorborne Diseases, University of California, Davis, CA, E-mails: cmbarker@ucdavis.edu and wkreisen@ucdavis.edu. Arnaud Le Menach, Resources for the Future, Center for Disease Dynamics, Economics and Policy, Washington, DC, E-mail: arnaudlemenach@gmail.com. Holly D. Gaff, Department of Biological Sciences, Old Dominion University, Norfolk, VA, E-mail: hgaff@odu.edu.
ProCite
RefWorks
Reference Manager
BibTeX
Zotero
EndNote
-
1.
Lanciotti RS, Roehrig JT, Deubel V, Smith J, Parker M, Steele K, Crise B, Volpe KE, Crabtree MB, Scherret JH, Hall RA, Mackenzie JS, Cropp CB, Panigrahy B, Ostlund E, Schmitt B, Malkinson M, Banet C, Weissman J, Komar N, Savage HM, Stone W, McNamara T, Gubler DJ, 1999. Origin of the West Nile virus responsible for an outbreak of encephalitis in the northeastern United States. Science 286: 2333– 2337.
-
2.
Reisen W, Lothrop H, Chiles R, Madon M, Cossen C, Woods L, Husted S, Kramer V, Edman J, 2004. West Nile virus in California. Emerg Infect Dis 10: 1369– 1378.
-
3.
Hom A, Marcus L, Kramer VL, Cahoon BE, Glaser C, Cossen C, Baylis E, Jean C, Tu EH, Eldridge BF, Carney R, Padgett K, Sun B, Reisen WK, Woods L, Husted S, 2005. Surveillance for mosquito-borne encephalitis virus activity and human disease, including West Nile virus in California, 2004. Proc Mosq Vector Control Assoc Calif 73: 66– 77.
-
4.
Wheeler SS, Barker CM, Fang Y, Armijos MV, Carroll BD, Husted S, Johnson WO, Reisen WK, 2009. Differential impacts of West Nile virus on California birds. Condor 111: 1– 20.
-
5.
California Department of Public Health, 2010. California West Nile Virus. Available at: http://westnile.ca.gov. Accessed March 24, 2011.
-
6.
Reisen WK, Fang Y, Martinez VM, 2006. Effects of temperature on the transmission of West Nile virus by Culex tarsalis (Diptera: Culicidae). J Med Entomol 43: 309– 317.
-
7.
Liu A, Lee V, Galusha D, Slade MD, Diuk-Wasser M, Andreadis T, Scotch M, Rabinowitz PM, 2009. Risk factors for human infection with West Nile virus in Connecticut: a multi-year analysis. Int J Hlth Geograph 8: 67.
-
8.
Ruiz MO, Chaves LF, Hamer GL, Sun T, Brown WM, Walker ED, Haramis L, Goldberg TL, Kitron UD, 2010. Local impact of temperature and precipitation on West Nile virus infection in Culex species mosquitoes in northeast Illinois, USA. Parasites and Vectors 19: 19.
-
9.
Soverow JE, Wellenius GA, Fisman DN, Mittleman MA, 2009. Infectious disease in a warming world: how weather influenced West Nile virus in the United States (2001–2005). Environ Health Perspect 117: 1049– 1052.
-
10.
Reisen WK, Milby MM, Presser SB, Hardy JL, 1992. Ecology of mosquitoes and St. Louis encephalitis virus in the Los Angeles Basin of California, 1987–1990. J Med Entomol 29: 582– 598.
-
11.
Kilpatrick AM, Meola MA, Moudy RM, Kramer LD, 2008. Temperature, viral genetics, and the transmission of West Nile virus by Culex pipiens mosquitoes. PLoS Pathogens 27 e1000092.
-
12.
Bowman C, Gumel AB, van den Driessche P, Wu J, Zhu H, 2005. A mathematical model for assessing control strategies against West Nile virus. Bull Math Biol 67: 1107– 1133.
-
13.
Blayneh KW, Gumel AB, Lenhart S, Clayton T, 2010. Backward bifurcation and optimal control in transmission dynamics of West Nile virus. Bull Math Biol 72: 1006– 1028.
-
14.
Liu RS, Shuai JP, Wu JH, Zhu HP, 2006. Modeling spatial spread of West Nile virus and impact of directional dispersal of birds. Math Biosci Eng 3: 145– 160.
-
15.
Cruz-Pacheco G, Esteva L, Montano-Hirose JA, Vargas C, 2005. Modeling the dynamics of West Nile virus. Bull Math Biol 67: 1157– 1172.
-
16.
Hartemink NA, Davis SA, Reiter P, Hubalek Z, Heesterbeek JAP, 2007. Importance of bird-to-bird transmission for the establishment of West Nile virus. Vector Borne Zoonotic Dis 7: 575– 584.
-
17.
Jiang JF, Qiu ZP, 2009. The complete classification for dynamics in a nine-dimensional West Nile virus model. SIAM J Appl Math 69: 1205– 1227.
-
18.
Jiang JF, Qiu ZP, Wu JH, Zhu HP, 2009. Threshold conditions for West Nile virus outbreaks. Bull Math Biol 71: 627– 647.
-
19.
Kenkre VM, Parmenter RR, Peixoto LD, Sadasiv L, 2005. A theoretical framework for the analysis of the West Nile virus epidemic. Math Comput Model 42: 313– 324.
-
20.
Lewis M, Renclawowicz J, Van den Driessche P, 2006. Traveling waves and spread rates for a West Nile virus model. Bull Math Biol 68: 3– 23.
-
21.
Lewis MA, Renclawowicz J, van den Driessche P, Wonham M, 2006. A comparison of continuous and discrete-time West Nile virus models. Bull Math Biol 68: 491– 509.
-
22.
Lord CC, Day JF, 2001. Simulation studies of St. Louis encephalitis and West Nile viruses: the impact of bird mortality. Vector Borne Zoonotic Dis 1: 317– 329.
-
23.
Rappole JH, Compton BW, Leimgruber P, Robertson J, King DI, Renner SC, 2006. Modeling movement of West Nile virus in the western hemisphere. Vector Borne Zoonotic Dis 6: 128– 139.
-
24.
Thomas DM, Urena B, 2001. A model describing the evolution of West Nile-like encephalitis in New York City. Math Comput Model 34: 771– 781.
-
25.
Wan H, Zhu HP, 2010. The backward bifurcation in compartmental models for West Nile virus. Math Biosci 227: 20– 28.
-
26.
Wonham MJ, Camino-Beck T, Lewis MA, 2004. An epidemiological model for West Nile virus: invasion analysis and control applications. Proc R Soc Lond B Biol Sci 271: 501– 507.
-
27.
Wonham MJ, Lewis MA, 2008. A comparative analysis of models for West Nile virus. Brauer F, van den Driessche P, Wu J, eds. Mathematical Epidemiology. Berlin: Springer-Verlag, 365– 390.
-
28.
Wonham MJ, Lewis MA, Renclawowicz J, Van den Driessche P, 2006. Transmission assumptions generate conflicting predictions in host-vector disease models: a case study in West Nile virus. Ecol Lett 9: 706– 725.
-
29.
California Department of Public Health, 2011. Mosquito and Vector Control Association of California, University of California. California Mosquito-Borne Virus Surveillance and Response Plan. Available at: http://westnile.ca.gov/downloads.php?download_id=820&filename=2008_CA_Mosq_Surv.pdf. Accessed March 3, 2012.
-
30.
Barker CM, Kramer VL, Reisen WK, 2010. Decision Support System for Mosquito and Arbovirus Control in California. Earthzine: an IEEE Publication. Available at: http://www.earthzine.org/2010/09/24/decision-support-system-for-mosquito-and-arbovirus-control-in-california/. Accessed January 14, 2012.
-
31.
Nemani R, Votava P, Michaelis A, White M, Melton F, Milesi C, Pierce L, Golden K, Hashimoto H, Ichii K, Johnson L, Jolly M, Myneni R, Tague C, Coughlan J, Running S, 2007. Remote sensing methodologies for ecosystem management. Aswathanarayana U, ed. Food and Water Security. Oxford, UK: Taylor & Francis, 1– 19.
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