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Reference Manager
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Collinge SK, Johnson WC, Ray C, Matchett R, Grensten J, Cully JF, Gage KL, Kosoy M, Loye JE, Martin A, 2005. Testing the generality of the tropic-cascade model for plague. EcoHealth 2: 102– 112.
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Ari TB, Gershunov A, Tristan R, Cazelles B, Gage K, Stenseth NC, 2010. Interannual variability of human plague occurrence in the Western United States explained by tropical and North Pacific Ocean climate variability. Am J Trop Med Hyg 83: 624– 632.
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Climate Predictors of the Spatial Distribution of Human Plague Cases in the West Nile Region of Uganda
Katherine MacMillan
Katherine MacMillan
Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado; National Center for Atmospheric Research, Boulder, Colorado; Uganda Virus Research Institute, Entebbe, Uganda
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Andrew J. Monaghan
Andrew J. Monaghan
Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado; National Center for Atmospheric Research, Boulder, Colorado; Uganda Virus Research Institute, Entebbe, Uganda
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Titus Apangu
Titus Apangu
Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado; National Center for Atmospheric Research, Boulder, Colorado; Uganda Virus Research Institute, Entebbe, Uganda
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Kevin S. Griffith
Kevin S. Griffith
Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado; National Center for Atmospheric Research, Boulder, Colorado; Uganda Virus Research Institute, Entebbe, Uganda
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Paul S. Mead
Paul S. Mead
Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado; National Center for Atmospheric Research, Boulder, Colorado; Uganda Virus Research Institute, Entebbe, Uganda
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Sarah Acayo
Sarah Acayo
Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado; National Center for Atmospheric Research, Boulder, Colorado; Uganda Virus Research Institute, Entebbe, Uganda
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Rogers Acidri
Rogers Acidri
Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado; National Center for Atmospheric Research, Boulder, Colorado; Uganda Virus Research Institute, Entebbe, Uganda
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Sean M. Moore
Sean M. Moore
Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado; National Center for Atmospheric Research, Boulder, Colorado; Uganda Virus Research Institute, Entebbe, Uganda
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Joseph Tendo Mpanga
Joseph Tendo Mpanga
Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado; National Center for Atmospheric Research, Boulder, Colorado; Uganda Virus Research Institute, Entebbe, Uganda
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Russel E. Enscore
Russel E. Enscore
Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado; National Center for Atmospheric Research, Boulder, Colorado; Uganda Virus Research Institute, Entebbe, Uganda
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Kenneth L. Gage
Kenneth L. Gage
Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado; National Center for Atmospheric Research, Boulder, Colorado; Uganda Virus Research Institute, Entebbe, Uganda
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Rebecca J. Eisen
Rebecca J. Eisen
Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado; National Center for Atmospheric Research, Boulder, Colorado; Uganda Virus Research Institute, Entebbe, Uganda
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East Africa has been identified as a region where vector-borne and zoonotic diseases are most likely to emerge or re-emerge and where morbidity and mortality from these diseases is significant. Understanding when and where humans are most likely to be exposed to vector-borne and zoonotic disease agents in this region can aid in targeting limited prevention and control resources. Often, spatial and temporal distributions of vectors and vector-borne disease agents are predictable based on climatic variables. However, because of coarse meteorological observation networks, appropriately scaled and accurate climate data are often lacking for Africa. Here, we use a recently developed 10-year gridded meteorological dataset from the Advanced Weather Research and Forecasting Model to identify climatic variables predictive of the spatial distribution of human plague cases in the West Nile region of Uganda. Our logistic regression model revealed that within high elevation sites (above 1,300 m), plague risk was positively associated with rainfall during the months of February, October, and November and negatively associated with rainfall during the month of June. These findings suggest that areas that receive increased but not continuous rainfall provide ecologically conducive conditions for Yersinia pestis transmission in this region. This study serves as a foundation for similar modeling efforts of other vector-borne and zoonotic disease in regions with sparse observational meteorologic networks.
Author Notes
Financial support: This work was supported in part by funds from the CDC Climate Change Program.
Authors' addresses: Katherine MacMillan, Kevin S. Griffith, Paul S. Mead, Russell E. Enscore, Kenneth L. Gage, and Rebecca J. Eisen, Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, CO, E-mail: iky4@cdc.gov. Andrew J. Monaghan and Sean M. Moore, National Center for Atmospheric Research, Boulder, CO. Titus Apangu, Sara Acayo, Rogers Acidri, and Joseph Tendo Mpanga, Uganda Virus Research Institute, Entebbe, Uganda.
ProCite
RefWorks
Reference Manager
BibTeX
Zotero
EndNote
-
1.
Gage KL, Kosoy MY, 2005. Natural history of plague: perspectives from more than a century of research. Annu Rev Entomol 50: 505– 528.
-
2.
Eisen RJ, Gage KL, 2009. Adaptive strategies of Yersinia pestis to persist during inter-epizootic and epizootic periods. Vet Res 40: 1.
-
3.
Dennis DT, Chow CC, 2004. Plague. Pediatr Infect Dis J 23: 69– 71.
-
4.
Crook LD, Tempest B, 1992. Plague. A clinical review of 27 cases. Arch Intern Med 152: 1253– 1256.
-
5.
Poland JD, Dennis DT, 1999. Diagnosis and clinical manifestations. Plague Manual: Epidemiology, Distribution, Surveillance and Control. Geneva: World Health Organization, 43– 54.
-
6.
Neerinckx S, Bertherat E, Leirs H, 2010. Human plague occurrences in Africa: an overview from 1877 to 2008. Trans R Soc Trop Med Hyg 104: 97– 103.
-
7.
Neerinckx SB, Peterson AT, Gulinck H, Deckers J, Leirs H, 2008. Geographic distribution and ecological niche of plague in sub-Saharan Africa. Int J Health Geogr 7: 54.
-
8.
WHO, 2005. Outbreak news index 2005. Wkly Epidemiol Rec 80: 433– 440.
-
9.
WHO, 2009. Human plague: review of regional morbidity and mortality, 2004–2009. Wkly Epidemiol Rec 85: 40– 45.
-
10.
Kilonzo BS, 1999. Plague epidemiology and control in eastern and southern Africa during the period 1978 to 1997. Cent Afr J Med 45: 70– 76.
-
11.
Eisen RJ, Griffith KS, Borchert JN, MacMillan K, Apangu T, Owor N, Acayo S, Acidri R, Zielinski-Gutierrez E, Winters AM, Enscore RE, Schriefer ME, Beard CB, Gage KL, Mead PS, 2010. Assessing human risk of exposure to plague bacteria in northwestern Uganda based on remotely sensed predictors. Am J Trop Med Hyg 82: 904– 911.
-
12.
Winters AM, Staples JE, Ogen-Odoi A, Mead PS, Griffith K, Owor N, Babi N, Enscore RE, Eisen L, Gage KL, Eisen RJ, 2009. Spatial risk models for human plague in the West Nile region of Uganda. Am J Trop Med Hyg 80: 1014– 1022.
-
13.
MacMillan K, Enscore RE, Ogen-Odoi A, Borchert JN, Babi N, Amatre G, Atiku LA, Mead PS, Gage KL, Eisen RJ, 2011. Landscape and residential variables associated with plague-endemic villages in the West Nile region of Uganda. Am J Trop Med Hyg 84: 435– 442.
-
14.
Eisen RJ, Borchert JN, Holmes JL, Amatre G, Van Wyk K, Enscore RE, Babi N, Atiku LA, Wilder AP, Vetter SM, Bearden SW, Montenieri JA, Gage KL, 2008. Early-phase transmission of Yersinia pestis by cat fleas (Ctenocephalides felis) and their potential role as vectors in a plague-endemic region of Uganda. Am J Trop Med Hyg 78: 949– 956.
-
15.
Parmenter RR, Yadav EP, Parmenter CA, Ettestad P, Gage KL, 1999. Incidence of plague associated with increased winter-spring precipitation in New Mexico. Am J Trop Med Hyg 61: 814– 821.
-
16.
Enscore RE, Biggerstaff BJ, Brown TL, Fulgham RE, Reynolds PJ, Engelthaler DM, Levy CE, Parmenter RR, Montenieri JA, Cheek JE, Grinnell RK, Ettestad PJ, Gage KL, 2002. Modeling relationships between climate and the frequency of human plague cases in the southwestern United States, 1960–1997. Am J Trop Med Hyg 66: 186– 196.
-
17.
Davis S, Calvet E, Leirs H, 2005. Fluctuating rodent populations and risk to humans from rodent-borne zoonoses. Vector Borne Zoonotic Dis 5: 305– 314.
-
18.
Kausrud KL, Viljugrein H, Frigessi A, Begon M, Davis S, Leirs H, Dubyanskiy V, Stenseth NC, 2007. Climatically driven synchrony of gerbil populations allows large-scale plague outbreaks. Proc Biol Sci 274: 1963– 1969.
-
19.
Collinge SK, Johnson WC, Ray C, Matchett R, Grensten J, Cully JF, Gage KL, Kosoy M, Loye JE, Martin A, 2005. Testing the generality of the tropic-cascade model for plague. EcoHealth 2: 102– 112.
-
20.
Mann JM, Martone WJ, Boyce JM, Kaufmann AF, Barnes AM, Weber NS, 1979. Endemic human plague in New Mexico: risk factors associated with infection. J Infect Dis 140: 397– 401.
-
21.
Akiev AK, 1982. Epidemiology and incidence of plague in the world, 1958–79. Bull World Health Organ 60: 165– 169.
-
22.
Gratz N, 1999. Control of plague transmission. Plague Manual: Epidemiology, Distribution, Surveillance and Control. Geneva: World Health Organization, 97– 134.
-
23.
Cavanaugh DC, Marshall JD Jr, 1972. The influence of climate on the seasonal prevalence of plague in the Republic of Vietnam. J Wildl Dis 8: 85– 94.
-
24.
Gage KL, Burkot TR, Eisen RJ, Hayes EB, 2008. Climate and vector-borne diseases. Am J Prev Med 35: 436– 450.
-
25.
Davis S, Begon M, De Bruyn L, Ageyev VS, Klassovskiy NL, Pole SB, Viljugrein H, Stenseth NC, Leirs H, 2004. Predictive thresholds for plague in Kazakhstan. Science 304: 736– 738.
-
26.
Davis S, Trapman P, Leirs H, Begon M, Heesterbeek JA, 2008. The abundance threshold for plague as a critical percolation phenomenon. Nature 454: 634– 637.
-
27.
Hirst LF, 1953. The Conquest of Plague. Oxford, UK: Clarendon Press, 478.
-
28.
Krasnov BR, Khokhlova IS, 2001. The effect of behavioral interactions on the transfer of fleas (Siphonaptera) between two rodent species. J Vector Ecol 26: 181– 190.
-
29.
Krasnov BR, Shenbrot GI, Mouillot D, Khokhlova IS, Poulin R, 2006. Ecological characteristics of flea species relate to their suitability as plague vectors. Oecologia 149: 474– 481.
-
30.
Brown HE, Ettestad P, Reynolds PJ, Brown TL, Hatton ES, Holmes JL, Glass GE, Gage KL, Eisen RJ, 2010. Climatic predictors of the intra- and inter-annual distributions of plague cases in New Mexico based on 29 years of animal-based surveillance data. Am J Trop Med Hyg 82: 95– 102.
-
31.
Ari TB, Gershunov A, Tristan R, Cazelles B, Gage K, Stenseth NC, 2010. Interannual variability of human plague occurrence in the Western United States explained by tropical and North Pacific Ocean climate variability. Am J Trop Med Hyg 83: 624– 632.
-
32.
Ari TB, Gershunov A, Gage KL, Snall T, Ettestad P, Kausrud KL, Stenseth NC, 2008. Human plague in the USA: the importance of regional and local climate. Biol Lett 4: 737– 740.
-
33.
Amatre G, Babi N, Enscore RE, Ogen-Odoi A, Atiku LA, Akol A, Gage KL, Eisen RJ, 2009. Flea diversity and infestation prevalence on rodents in a plague-endemic region of Uganda. Am J Trop Med Hyg 81: 718– 724.
-
34.
Chu MC, 2000. Laboratory Training Manual of Plague Diagnostic Tests. Atlanta, GA: Centers for Disease Control and Prevention and Geneva: World Health Organization.
-
35.
Skamarock WC, Klemp JB, 2008. A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. J Comput Phys 227: 3465– 3485.
-
36.
Chen F, Dudhia J, 2001. Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon Weather Rev 129: 569– 585.
-
37.
Kanamitsu M, Ebisuzaki W, Woollen J, Yang SK, Hnilo JJ, Fiorino M, Potter GL, 2002. Ncep-Doe Amip-Ii Reanalysis (R-2). Bull Am Meteorol Soc 83: 1631– 1643.
-
38.
Monaghan AJ, Rife DL, Pinto JO, Davis CA, Hannan JR, 2010. Global precipitation extremes associated with diurnally varying low-level jets. J Clim 23: 5065– 5084.
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