The geographic spread of infectious diseases: Models and applications

The Geographic Spread of Infectious Diseases: Models and Applications

Volumn , Issue , 2009, Pages

  Sattenspiel, Lisa ^a  

^a NONE

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EID: 72849114814     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Book

References (523)

1. Abdullah, A. S. M., Tomlinson, B., Cockram, C. S., and Thomas, G. N. (2003). Lessons from the severe acute respiratory syndrome outbreak in Hong Kong. Emerging Infectious Diseases, 9(9):1042-1045.
2. Ackerman, E., Elveback, L., and Fox, J. P. (1984). Simulation of Infectious Disease Epidemics. Charles C. Thomas, Springfield, IL.
3. Adesina, H. O. (1984). Identification of the cholera diffusion process in Ibadan, 1971. Social Science and Medicine, 18(5):429-440.
4. Adler, F. R. (1992). The effects of averaging on the basic reproduction ratio. Mathematical Biosciences, 111(1):89-98.
5. Aguirre, A. and Gonzalez, E. (1992). The feasibility of forecasting influenza epidemics in Cuba. Memorias do Instituto Oswaldo Cruz, 87(3):429-432.
6. Albert, R., Jeong, H., and Barabási, A. L. (2000). Error and attack tolerance of complex networks. Nature, 406:378-382.
7. Anderson, D. and Watson, R. (1980). On the spread of a disease with gamma distributed latent and infectious periods. Biometrika, 67:191-198.
8. Anderson, R. M. (1982). Transmission dynamics and control of infectious disease agents. In Anderson, R. M. and May, R. M., editors, Population Biology of Infectious Diseases, pages 149-176. Springer-Verlag, New York.
9. Anderson, R. M., Grenfell, B. T., and May, R. M. (1984). Oscillatory fluctuations in the incidence of infectious disease and the impact of vaccination: Time series analysis. Journal of Hygiene-Cambridge, 93(3):587-608.
10. Anderson, R. M., Jackson, H. C., May, R. M., and Smith, A. M. (1981). Population dynamics of fox rabies in Europe. Nature, 289(5800):765-771.
11. Anderson, R. M. and May, R. M. (1991). Infectious Diseases of Humans: Dynamics and Control. Oxford University Press, Oxford.
12. Anderson, R. M., May, R. M., and McLean, A. R. (1988). Possible demographic consequences of AIDS in developing countries. Nature, 332(6161):228-234.
13. Anderson, R. M., Medley, G. F., May, R. M., and Johnson, A. M. (1986). A preliminary study of the transmission dynamics of the human immunodeficiency virus (HIV), the causative agent of AIDS. IMA Journal of Mathematics Applied in Medicine and Biology, 3(4):229-263.
14. Anderson, R. M., Ng, T. W., Boily, M. C., and May, R. M. (1989). The influence of different sexual-contact patterns between age classes on the predicted demographic impact of AIDS in developing countries. Annals of the New York Academy of Science, 569:240-274.
15. Andersson, H. (1997). Epidemics in a population with social structures. Mathematical Biosciences, 140:79-84.
16. Andersson, H. (1998). Limit theorems for a random graph epidemic model. Annals of Applied Probability, 8:1331-1349.
17. Andersson, H. and Britton, T. (2000a). Stochastic Epidemic Models and Their Analysis. Springer-Verlag, New York.
18. Andersson, H. and Britton, T. (2000b). Stochastic epidemics in dynamic populations: Quasi-stationarity and extinction. Journal of Mathematical Biology, 41(6):559-580.
19. Andreasen, V. and Christiansen, F. B. (1989). Persistence of an infectious disease in a subdivided population. Mathematical Biosciences, 96:239-253.
20. Angulo, J. J., Haggett, P., Megale, P., and Pederneiras, A. A. (1977). Variola minor in Braganca Paulista county, 1956: A trend-surface analysis. American Journal of Epidemiology, 105(3):272-278.
21. Antonovics, J., Iwasa, Y., and Hassell, M. P. (1995). A generalized model of parasitoid, venereal, and vector-based transmission processes. American Naturalist, 145:661-675.
22. Aparicio, J. P. and Solari, H. G. (2001a). Population dynamics: Poisson approximation and its relation to the Langevin process. Physical Review Letters, 86(18):4183-4186.
23. Aparicio, J. P. and Solari, H. G. (2001b). Sustained oscillations in stochastic systems. Mathematical Biosciences, 169(1):15-25.
24. Arino, J., Davis, J. R., Hartley, D., Jordan, R., Miller, J. M., and van den Driessche, P. (2005). A multi-species epidemic model with spatial dynamics. Mathematical Medicine and Biology, 22:129-142.
25. Arino, J. and van den Driessche, P. (2003). A multi-city epidemic model. Mathematical Population Studies, 10(3):175-193.
26. Aron, J. L. and May, R. M. (1982). The population dynamics of malaria. In Anderson, R. M., editor, Population Dynamics of Infectious Diseases: Theory and Applications, pages 139-179.Chapman and Hall, London.
27. Assunçao, R. M., Reis, I. A., and Oliveira, C. D. (2001). Diffusion and prediction of Leishmaniasis in a large metropolitan area in Brazil with a Bayesian space-time model. Statistics in Medicine, 20(15):2319-2335.
28. Bailey, N. T. J. (1964). Some stochastic models for small epidemics in large populations. Journal of the Royal Statistical Society, Series C, Applied Statistics, 13:9-19.
29. Bailey, N. T. J. (1975). The Mathematical Theory of Infectious Diseases and Its Applications. Hafner, New York.
30. Ball, F. and Neal, P. (2008). Network epidemic models with two levels of mixing. Mathematical Biosciences, 212:69-87.
31. Ball, F. G. (1985). Spatial models for the spread and control of rabies incorporating group size. In Bacon, P., editor, Population Dynamics of Rabies in Wildlife, pages 197-221. Academic Press, London.
32. Ball, F. G. (1991). Dynamic population epidemic models. Mathematical Biosciences, 107(2):299-324.
33. Ball, F. G. (1995). Coupling methods in epidemic theory. In Mollison, D., editor, Epidemic Models: Their Structure and Relation to Data, pages 34-52. Cambridge University Press, Cambridge.
34. Ball, F. G., Mollison, D., and Scalia-Tomba, G. (1997). Epidemics with two levels of mixing. Annals of Applied Probability, 7:46-89.
35. Barabási, A. L. (2003). Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life. Plume, New York.
36. Barabási, A. L. and Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439):509-512.
37. Barbour, A. and Mollison, D. (1990). Epidemics and random graphs. In Gabriel, J.-P., Lefévre, C., and Picard, P., editors, Stochastic Processes in Epidemic Theory, Lecture Notes in Biomathematics 86, pages 86-89. Springer-Verlag, New York.
38. Barbour, A. D. (1978). Macdonald's model and the transmission of bilharzia. Transactions of the Royal Society of Tropical Medicine and Hygiene, 72(1):6-15.
39. Baroyan, O. V., Basilevsky, U. V., Ermakov, V. V., Frank, K. D., Rvachev, L. A., and Shashkov, V. A. (1970). Computer modelling of influenza epidemics for large-scale systems of cities and territories. Working paper for WHO Symposium on Quantitative Epidemiology.
40. Baroyan, O. V., Genchikov, L. A., Rvachev, L. A., and Schaschkov, V. A. (1969). An attempt at large-scale influenza modelling by means of a computer. Bulletin of the International Epidemiological Association, 18:22-31.
41. Baroyan, O. V. and Rvachev, L. A. (1967). Deterministic models of epidemics for a territory with a transport network. Kibernetika (Cybernetics), 3:67-74.
42. Baroyan, O. V. and Rvachev, L. A. (1978). Prediction of influenza epidemics in the USSR. (in Russian). Voprosy Virusologii, 2:131-137.
43. Baroyan, O. V., Rvachev, L. A., Basilevsky, U. V., Ermakov, V. V., Frank, K. D., Rvachev, M. A., and Shashkov, V. A. (1971). Computer modelling of influenza epidemics for the whole country (USSR). Advances in Applied Probability, 3:224-226.
44. Baroyan, O. V., Rvachev, L. A., Frank, K., and et al. (1978). Model of influenza epidemics spread through the territory of Bulgaria and its significance. (in Bulgarian). Journal of Epidemiology, Microbiology, and Infectious Diseases (Sofia), 3:168-173.
45. Bartlett, M. S. (1954). Processus stochastiques ponctuels. Annales de l'Institut Henri Poincare, 14:35.
46. Bartlett, M. S. (1956). Deterministic and stochastic models for recurrent epidemics. Proceedings of the 3rd Berkeley Symposium on Mathematics, Statistics, and Probability, 4:81-109.
47. Bartlett, M. S. (1957). Measles periodicity and community size. Journal of the Royal Statistical Society, Series A, Statistics in Society, 120:48-70.
48. Bartlett, M. S. (1960a). The critical community size for measles in the United States. Journal of the Royal Statistical Society, Series A, Statistics in Society, 123:37-44.
49. Bartlett, M. S. (1960b). Stochastic Population Models in Ecology and Epidemiology. Methuen, London.
50. Bartlett, M. S. (1964). The relevance of stochastic models for large-scale epidemic phenomena. Journal of the Royal Statistical Society, Series C, Applied Statistics, 13:2-8.
51. Bates, T. W., Thurmond, M. C., and Carpenter, T. E. (2003a). Description of an epidemic simulation model for use in evaluating strategies to control an outbreak of foot-and-mouth disease. American Journal of Veterinary Research, 64(2):195-204.
52. Bates, T. W., Thurmond, M. C., and Carpenter, T. E. (2003b). Epidemiologic information for modeling foot-and-mouth disease. In Banks, H. T. and Castillo-Chavez, C., editors, Bioterrorism: Mathematical Modeling Applications in Homeland Security, pages 107-127. Society for Industrial and Applied Mathematics, Philadelphia.
53. Bates, T. W., Thurmond, M. C., and Carpenter, T. E. (2003c). Results of epidemic simulation modeling to evaluate strategies to control an outbreak of foot-and-mouth disease. American Journal of Veterinary Research, 64(2):205-210.
54. Bauch, C. (2002). A versatile ODE approximation to a network model for the spread of sexually transmitted diseases. Journal of Mathematical Biology, 45(5):375-395.
55. Bauch, C. (2005). The spread of infectious diseases in spatially structured populations: An invasory pair approximation. Mathematical Biosciences, 198:217-237.
56. Bauch, C. and Rand, D. A. (2001). A moment closure model for sexually transmitted disease transmission through a concurrent partnership network. Proceedings of the Royal Society of London, Series B, Biological Sciences, 267(1485):2019-2027.
57. Bauch, C. T. and Earn, D. J. (2003). Transients and attractors in epidemics. Proceedings of the Royal Society of London, Series B, Biological Sciences, 270(1524):1573-1578.
58. Bauch, C. T., Lloyd-Smith, J. O., Coffee, M. P., and Galvani, A. P. (2005). Dynamically modeling SARS and other newly emerging respiratory illnesses - past, present, and future. Epidemiology, 16(6):791-801.
59. Becker, N. G. (1989). Analysis of Infectious Disease Data. Chapman and Hall, London.
60. Becker, N. G. (1993). Martingale methods for the analysis of epidemic data. Statistical Methods in Medical Research, 2(1):93-112.
61. Becker, N. G. and Hopper, J. L. (1983). Assessing the heterogeneity of disease spread through a community. American Journal of Epidemiology, 117(3):362-374.
62. Becker, N. G. and Marschner, I. (1990). The effect of heterogeneity on the spread of disease. In Gabriel, J.-P., Lefévre, C., and Picard, P., editors, Stochastic Processes in Epidemic Theory, Lecture Notes in Biomathematics 86, pages 90-103. Springer-Verlag, New York.
63. Begon, M., Bennett, M., Bowers, R. G., French, N. P., Hazel, S. M., and Turner, J. (2002). A clarification of transmission terms in host-microparasite models: Numbers, densities and areas. Epidemiology and Infection, 129:147-153.
64. Bell, D. M. and WGICTS. (2004). Public health interventions and SARS spread, 2003. Emerging Infectious Diseases, 10(11):1900-1906. WGICTS = World Health Organization Working Group on International and Community Transmission of SARS.
65. Belova, L. A., Vasilyeva, V. I., Rvachev, L. A., and et al. (1982). New influenza epidemic model for the USSR territory (in Russian). Presented at the Seventh International Symposium on Influenza, Leningrad.
66. Bickerstaff, K. and Simmons, P. (2004). The right tool for the job? Modeling, spatial relationships, and styles of scientific practice in the UK foot and mouth crisis. Environment and Planning D, Society and Space, 22:393-412.
67. Bjørnstad, O. N., Finkenstädt, B. F., and Grenfell, B. T. (2002). Dynamics of measles epidemics: Estimating scaling of transmission rates using a time series SIR model. Ecological Monographs, 72(2):169-184.
68. Black, F. L. (1966). Measles endemicity in insular populations: Critical community size and its evolutionary implication. Journal of Theoretical Biology, 11:207-211.
69. Blythe, S. P. and Anderson, R. M. (1988). Variable infectiousness in HIV transmission models. IMA Journal of Mathematics Applied in Medicine and Biology, 5:181-200.
70. Blythe, S. P. and Castillo-Chavez, C. (1989). Like-with-like preference and sexual mixing models. Mathematical Biosciences, 96(2):221-238.
71. Blythe, S. P., Castillo-Chavez, C., Palmer, J., and Cheng, M. (1991). Towards unified theory of mixing and pair formation. Mathematical Biosciences, 107:379-405.
72. Bolker, B. M. and Grenfell, B. T. (1993). Chaos and biological complexity in measles dynamics. Proceedings of the Royal Society of London, Series B, Biological Sciences, 251(1330):75-81.
73. Bolker, B. M. and Grenfell, B. T. (1995). Space, persistence and dynamics of measles epidemics. Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences, 348(1325):309-320.
74. Bolker, B. M. and Grenfell, B. T. (1996). Impact of vaccination on the spatial correlation and persistence of measles dynamics. Proceedings of the National Academy of Sciences of the United States of America, 93(22):12648-12653.
75. Bolker, B. M. and Pacala, S. W. (1997). Using moment equations to understand stochastically driven spatial pattern formation in ecological systems. Theoretical Population Biology, 52(3):179-197.
76. Bollobás, B. (1985). Random Graphs. Academic Press, London.
77. Bonabeau, E., Toubiana, L., and Flahault, A. (1998). The geographical spread of influenza. Proceedings of the Royal Society of London, Series B, Biological Sciences, 265(1413):2421-2425.
78. Boone, J. D., McGwire, K. C., Otteson, E. W., DeBaca, R. S., Kuhn, E. A., Villard, P., Brussard, P. F., and St Jeor, S. C. (2000). Remote sensing and geographic information systems: Charting Sin Nombre virus infections in deer mice. Emerging Infectious Diseases, 6(3):248-258.
79. Brauer, F. and Castillo-Chavez, C. (2001). Mathematical Models in Population Biology and Epidemiology. Springer-Verlag, New York.
80. Breugelmans, J. G., Zucs, P., Porten, K., Broll, S., Niedrig, M., Ammon, A., and Krause, G. (2004). SARS transmission and commercial aircraft. Emerging Infectious Diseases, 10(8):1502-1503.
81. Brimblecombe, F. S. W., Cruickshank, R., Masters, F. W., Reid, D. D., and Stewart, G. T. (1958). Family studies of respiratory infections. British Medical Journal, 1:119-128.
82. Broadbent, S. R. and Hammersley, J. M. (1957). Percolation processes, I: Crystals and mazes. Proceedings of the Cambridge Philosophical Society, 53:629-641.
83. Brockmann, D., Hufnagel, L., and Geisel, T. (2006). The scaling laws of human travel. Nature, 439:462-465.
84. Bron, C. and Kerbosch, J. (1973). Finding all cliques of an undirected graph - algorithm. Communications of the ACM, 16:575-577.
85. Brownstein, J. S., Wolfe, C. J., and Mandl, K. D. (2006). Empirical evidence for the effect of airline travel on inter-regional influenza spread in the United States. PLOS Medicine, 3(10):1826-1835.
86. Busenberg, S. N. and Castillo-Chavez, C. (1991). A general solution of the problem of mixing sub-populations, and its application to risk-and age-structured epidemic models for the spread of AIDS. IMA Journal of Mathematics Applied in Medicine and Biology, 8:1-29.
87. Cairns, A. J. (1990). Epidemics in heterogeneous populations, II: Nonexponential incubation periods and variable infectiousness. IMA Journal of Mathematics Applied in Medicine and Biology, 7(4):219-230.
88. Carrat, F. and Valleron, A. J. (1992). Epidemiologic mapping using the "kriging" method: Application to an influenza-like illness epidemic in France. American Journal of Epidemiology, 135(11):1293-1300.
89. Castillo-Chavez, C. and Busenberg, S. N. (1990). On the solution of the two-sex mixing problem. In Busenberg, S. N. and Martelli, M., editors, Proceedings of the International Conference on Differential Equations and Applications to Biology and Population Dynamics, Lecture Notes in Biomathematics 92, pages 80-98. Springer-Verlag, New York.
90. Castillo-Chavez, C., Cooke, K., Huang, W., and Levin, S. A. (1989a). On the role of long incubation periods in the dynamics of acquired immunodeficiency syndrome (AIDS), part 1: Single population models. Journal of Mathematical Biology, 27(4):373-398.
91. Castillo-Chavez, C., Cooke, K., Huang, W., and Levin, S. A. (1989b). The role of long incubation periods in the dynamics of HIV/AIDS, part 2: Multiple group models. In Castillo-Chavez, C., editor, Mathematical and Statistical Approaches to AIDS Epidemiology, Lecture Notes in Biomathematics 83, pages 200-217. Springer-Verlag, New York.
92. Cayley, A. L. (1857). On the theory of analytical forms called trees. Philosophical Magazine, 13:19-30. Reprinted in Mathematical Papers, Cambridge, 3:242-246, 1891.
93. Cayley, A. L. (1874). On the mathematical theory of isomers. Philosophical Magazine, 67:444-446. Reprinted in Mathematical Papers, Cambridge, 9:202-204, 1895.
94. Chaput, E. K., Meek, J. I., and Heimer, R. (2002). Spatial analysis of human granulocytic ehrlichiosis near Lyme, Connecticut. Emerging Infectious Diseases, 8(9):943-948.
95. Chau, P. H. and Yip, P. S. (2003). Monitoring the severe acute respiratory syndrome epidemic and assessing effectiveness of interventions in Hong Kong Special Administrative Region. Journal of Epidemiology and Community Health, 57(10):766-769.
96. Chick, S. E., Adams, A. L., and Koopman, J. S. (2000). Analysis and simulation of a stochastic, discrete-individual model of STD transmission with partnership concurrency. Mathematical Biosciences, 166(1):45-68.
97. Chowell, G., Castillo-Chavez, C., Fenimore, P. W., Kribs-Zaleta, C. M., Arriola, L., and Hyman, J. M. (2004). Model parameters and outbreak control for SARS. Emerging Infectious Diseases, 10(7):1258-1263.
98. Chowell, G., Fenimore, P. W., Castillo-Garsow, M. A., and Castillo-Chavez, C. (2003). SARS outbreaks in Ontario, Hong Kong and Singapore: The role of diagnosis and isolation as a control mechanism. Journal of Theoretical Biology, 224:1-8.
99. Chung, F. and Lu, L. (2001). The diameter of random sparse graphs. Advances in Applied Mathematics, 26:257-279.
100. Chung, F. and Lu, L. (2002). The average distances in random graphs with given expected degrees. Proceedings of the National Academy of Sciences of the United States of America, 99(25):15879-15882.
101. Clarke, K. C., McLafferty, S. L., and Tempalski, B. J. (1996). On epidemiology and geographic information systems: A review and discussion of future directions. Emerging Infectious Diseases, 2(2):85-92.
102. Cliff, A. D. (1995). Analysing geographically-related disease data. Statistical Methods in Medical Research, 4(2):93-101.
103. Cliff, A. D. and Haggett, P. (1980). Changes in the seasonal incidence of measles in Iceland, 1896-1974. Journal of Hygiene-Cambridge, 85(3):451-457.
104. Cliff, A. D. and Haggett, P. (1983). Changing urban-rural contrasts in the velocity of measles epidemics in an island community. In Mc-Glashan, N., editor, Geographical Aspects of Health: Essays in Honour of Andrew Learmonth, pages 335-348. Academic Press, London.
105. Cliff, A. D. and Haggett, P. (1984). Island epidemics. Scientific American, 250(5):138-147.
106. Cliff, A. D. and Haggett, P. (1985). The Spread of Measles in Fiji and the Pacific: Spatial Components in the Transmission of Epidemic Waves Through Island Communities. Australian National University, Canberra.
107. Cliff, A. D. and Haggett, P. (1988). Atlas of Disease Distributions. Blackwell, Oxford.
108. Cliff, A. D. and Haggett, P. (1993). Statistical modelling of measles and influenza outbreaks. Statistical Methods in Medical Research, 2(1):43-73.
109. Cliff, A. D., Haggett, P., and Graham, R. (1983a). Reconstruction of diffusion processes at local scales: The 1846, 1882 and 1904 measles epidemics in northwest Iceland. Journal of Historical Geography, 9(4):347-368.
110. Cliff, A. D., Haggett, P., and Ord, J. K. (1983b). Forecasting epidemic pathways for measles in Iceland: The use of simultaneous equation and logit models. Ecology of Disease, 2(4):377-396.
111. Cliff, A. D., Haggett, P., Ord, J. K., and Versey, J. R. (1981). Spatial Diffusion: An Historical Geography of Epidemics in an Island Community. Cambridge University Press, Cambridge.
112. Cliff, A. D., Haggett, P., and Smallman-Raynor, M. R. (1993). Measles: An Historical Geography of a Major Human Viral Disease from Global Expansion to Local Retreat, 1840-1990. Blackwell, London.
113. Cliff, A. D., Haggett, P., Smallman-Raynor, M. R., Stroup, D. F., and Williamson, G. D. (1995). The application of multidimensional scaling methods to epidemiological data. Statistical Methods in Medical Research, 4(2):102-123.
114. Cliff, A. D., Haggett, P., and Stroup, D. F. (1992a). The geographic structure of measles epidemics in the northeastern United States. American Journal of Epidemiology, 136(5):592-602.
115. Cliff, A. D., Haggett, P., Stroup, D. F., and Cheney, E. (1992b). The changing geographical coherence of measles morbidity in the United States, 1962-88. Statistics in Medicine, 11(11):1409-1424.
116. Cliff, A. D. and Ord, J. K. (1978). Forecasting the progress of an epidemic. In Martin, R. L., Thrift, N. J., and Bennett, R. J., editors, Towards the Dynamic Analysis of Spatial Systems, pages 191-204. Pion, London.
117. Cliff, A. D. and Ord, J. K. (1985). Forecasting the spread of an epidemic. In Anderson, O. D., Ord, J. K., and Robinson, E. A., editors, Time Series Analysis, Theory and Practice 6: Hydrological, Geophysical, and Spatial Applications, pages 297-308. North-Holland, Amsterdam.
118. Cockburn, T. A. (1971). Infectious diseases in ancient populations. Current Anthropology, 12:45-62.
119. Colizza, V., Barrat, A., Barthelemy, M., and Vespignani, A. (2006a). The modeling of global epidemics: Stochastic dynamics and predictability. Bulletin of Mathematical Biology, 68(8):1893-1921.
120. Colizza, V., Barrat, A., Barthelemy, M., and Vespignani, A. (2006b). The role of the airline transportation network in the prediction and predictability of global epidemics. Proceedings of the National Academy of Sciences of the United States of America, 103(7):2051-2020.
121. Cooke, K. L., Calef, D. F., and Level, E. V. (1977). Stability or chaos in discrete epidemic models. In Lakshmikantham, V., editor, Nonlinear Systems and Applications, pages 73-93. Academic Press, New York.
122. Cooper, B. S., Pitman, R. J., Edmunds, W. J., and Gay, N. J. (2006). Delaying the international spread of pandemic influenza. PLOS Medicine, 3(6):845-855.
123. Cox, D. R. and Miller, H. D. (1965). The Theory of Stochastic Processes. Wiley, New York.
124. Cox, S. J., Barnett, P. V., Dani, P., and Salt, J. S. (1999). Emergency vaccination of sheep against foot-and-mouth disease: Protection against disease and reduction in contact transmission. Vaccine, 17(15-16):1858-1868.
125. Crosby, A. W. (1989). America's Forgotten Pandemic: The Influenza of 1918. Cambridge University Press, New York.
126. Cushing, J. M. (1998). An Introduction to Structured Population Dynamics. CBMS-NSF Regional Conference Series in Applied Mathematics 71. Society for Industrial and Applied Mathematics, Philadelphia.
127. Daniels, H. E. (1977). The advancing wave in a spatial birth process. Journal of Applied Probability, 14:689-701.
128. Davies, G. (2002). Foot and mouth disease. Research in Veterinary Science, 73(3):195-199.
129. Davis, A., Gardner, B. B., and Gardner, M. R. (1941). Deep South. University of Chicago Press, Chicago.
130. Davis, J. A. and Leinhardt, S. (1972). The structure of positive interpersonal relations in small groups. In Berger, J., Zelditch, Jr., M., and Anderson, B., editors, Sociological Theories in Progress, Volume II, pages 218-251. Houghton Mifflin, Boston.
131. de Jong, M. C. M., Diekmann, O., and Heesterbeek, J. A. P. (1995). How does transmission of infection depend on population size? In Mollison, D., editor, Epidemic Models: Their Structure and Relation to Data, pages 84-94. Cambridge University Press, Cambridge.
132. DeAngelis, D. L. and Gross, L. J. (1992). Individual-based Models and Approaches in Ecology: Populations, Communities, and Ecosystems. Chapman and Hall, New York.
133. Diekmann, O. (1978). Thresholds and travelling waves for the geographical spread of infection. Journal of Mathematical Biology, 6(2):109-130.
134. Diekmann, O., de Jong, M. C. M., and Metz, J. A. J. (1998a). A deterministic epidemic model taking account of repeated contacts between the same individuals. Journal of Applied Probability, 35:448-462.
135. Diekmann, O., Gyllenberg, M., Metz, J. A., and Thieme, H. R. (1998b). On the formulation and analysis of general deterministic structured population models, I: Linear theory. Journal of Mathematical Biology, 36:349-388.
136. Diekmann, O. and Heesterbeek, J. A. P. (2000). Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis, and Interpretation. John Wiley, New York.
137. Diekmann, O., Heesterbeek, J. A. P., and Metz, J. A. J. (1990). On the definition and the computation of the basic reproduction rate R0 in models for infectious diseases in heterogeneous populations. Journal of Mathematical Biology, 28:365-382.
138. Diekmann, O., Heesterbeek, J. A. P., and Metz, J. A. J. (1995). The legacy of Kermack and McKendrick. In Mollison, D., editor, Epidemic Models: Their Structure and Relation to Data, Publications of the Newton Institute, pages 95-115. Cambridge University Press, Cambridge.
139. Dietz, K. (1980). Models for vector-borne parasitic diseases. In Berigozzi, C., editor, Vito Volterra Symposium on Mathematical Models in Biology, Lecture Notes in Biomathematics 39, pages 264-277. Springer-Verlag, Berlin.
140. Dietz, K. (1982). Overall patterns in the transmission cycle of infectious disease agents. In Anderson, R. M. and May, R. M., editors, Population Biology of Infectious Diseases, pages 87-102. Springer-Verlag, Berlin.
141. Dietz, K. (1988). The first epidemic model: A historical note on P. D. En'ko. Australian Journal of Statistics, 30A:56-65.
142. Dietz, K. and Hadeler, K. P. (1988). Epidemiological models for sexually transmitted diseases. Journal of Mathematical Biology, 26:1-25.
143. Dietz, K. and Schenzle, D. (1985). Mathematical models for infectious disease statistics. In Atkinson, A. C. and Feinberg, S. E., editors, A Celebration of Statistics: The ISI Centenary Volume, pages 167-204. Springer-Verlag, New York.
144. Doel, T. R., Williams, L., and Barnett, P. V. (1994). Emergency vaccination against foot-and-mouth disease: Rate of development of immunity and its implications for the carrier state. Vaccine, 12(7):592-600.
145. Doering, C. R. (1991). Modeling complex systems: Stochastic processes, stochastic differential equations, and Fokker-Planck equations. In Nadel, L. and Stein, D. L., editors, 1990 Lectures in Complex Systems: The Proceedings of the 1990 Complex Systems Summer School, Santa Fe, New Mexico, June 1990, Santa Fe Institute Studies in the Sciences of Complexity, Lectures v. 3. Addison-Wesley, Redwood City, CA.
146. Doherty, I. A., Shiboski, S., Ellen, J. M., Adimora, A. A., and Padian, N. S. (2006). Sexual bridging socially and over time: A simulation model exploring the relative effects of mixing and concurrency on viral sexually transmitted infection transmission. Sexually Transmitted Diseases, 33:368-373.
147. Donnelly, C. A., Ghani, A. C., Leung, G. M., Hedley, A. J., Fraser, C., Riley, S., Abu-Raddad, L. J., Ho, L. M., Thach, T. Q., Chau, P., Chan, K. P., Lam, T. H., Tse, L. Y., Tsang, T., Liu, S. H., Kong, J. H., Lau, E. M., Ferguson, N. M., and Anderson, R. M. (2003). Epidemiological determinants of spread of causal agent of severe acute respiratory syndrome in Hong Kong. Lancet, 361(9371):1761-1766.
148. Dorolle, P. (1968). Old plagues in the jet age: International aspects of present and future control of communicable disease. British Medical Journal, 4:789-792.
149. Dunn, F. L., Carey, D. E., Cohen, A., and Martin, J. D. (1959). Epidemiologic studies of Asian influenza in a Louisiana parish. American Journal of Hygiene, 70:351-371.
150. Dushoff, J., Plotkin, J. B., Viboud, C., Simonsen, L., Miller, M., Loeb, M., and Earn, D. J. D. (2007). Vaccinating to protect a vulnerable subpopulation. PLOS Medicine, 4(5):0921-0927.
151. Dye, C. and Gay, N. (2003). Modeling the SARS epidemic. Science, 300:1884-1885.
152. Dye, C. and Hasibeder, G. (1986). Population dynamics of mosquito-borne disease: Effects of flies which bite some people more frequently than others. Transactions of the Royal Society of Tropical Medicine and Hygiene, 80:69-77.
153. Eames, K. T. and Keeling, M. J. (2002). Modeling dynamic and network heterogeneities in the spread of sexually transmitted diseases. Proceedings of the National Academy of Sciences of the United States of America, 99(20):13330-13335.
154. Earn, D. J. D. and Levin, S. A. (2006). Global asymptotic coherence in discrete dynamical systems. Proceedings of the National Academy of Sciences of the United States of America, 103(11):3968-3971.
155. Earn, D. J. D., Levin, S. A., and Rohani, P. (2000a). Coherence and conservation. Science, 290(5495):1360-1364.
156. Earn, D. J. D., Rohani, P., Bolker, B. M., and Grenfell, B. T. (2000b). A simple model for complex dynamical transitions in epidemics. Science, 287(5453):667-670.
157. Eguiluz, V. M. and Klemm, K. (2002). Epidemic threshold in structured scale-free networks. Physical Review Letters, 89(10):108-701.
158. Ellner, S. P. (2001). Pair approximation for lattice models with multiple interaction scales. Journal of Theoretical Biology, 210(4):435-447.
159. Ellner, S. P., Bailey, B. A., Bobashev, G. V., Gallant, A. R., Grenfell, B. T., and Nychka, D. W. (1998a). Noise and nonlinearity in measles epidemics: Combining mechanistic and statistical approaches to population modeling. American Naturalist, 151(5):425-440.
160. Ellner, S. P., Sasaki, A., Haraguchi, Y., and Matsuda, H. (1998b). Speed of invasion in lattice population models: Pair-edge approximation. Journal of Mathematical Biology, 36:469-484.
161. Elveback, L., Ackerman, E., Gatewood, L. G., and Fox, J. P. (1971). Stochastic two-agent epidemic simulation models for a community of families. American Journal of Epidemiology, 93(4):267-280.
162. Elveback, L. R., Fox, J. P., Ackerman, E., Langworthy, A., Boyd, M., and Gatewood, L. G. (1976). An influenza simulation model for immunization studies. American Journal of Epidemiology, 103:152-165.
163. En'ko, P. D. (1889). On the course of epidemics of some infectious diseases. Vrach St. Petersburg, 10:1008-1010, 1039-1042, 1061-1063.
164. Eubank, S., Guclu, H., Kumar, A., Marathe, M. V., Srinivasan, A., Toroczkai, Z., and Wang, N. (2004). Modelling disease outbreaks in realistic urban social networks. Nature, 429(6988):180-184.
165. Ewy, W., Ackerman, E., Gatewood, L. G., Elveback, L., and Fox, J. P. (1972). A generalized stochastic model for simulation of epidemics in a heterogeneous population (Model VI). Computers in Biology and Medicine, 2:45-58.
166. Fararo, T. J. and Sunshine, M. (1989). A Study of a Biased Friendship Network. Syracuse University Press, Syracuse, NY.
167. Feld, S. L. (1991). Why your friends have more friends than you do. American Journal of Sociology, 96:1464-1477.
168. Ferguson, N. M., Cummings, D. A. T., Cauchemez, S., Fraser, C., Riley, S., Meeyai, A., Iamsirithaworn, S., and Burke, D. S. (2005). Strategies for containing an emerging influenza pandemic in Southeast Asia. Nature, 437(7056):209-214.
169. Ferguson, N. M., Cummings, D. A. T., Fraser, C., Cajka, J. C., Cooley, P. C., and Burke, D. S. (2006). Strategies for mitigating an influenza pandemic. Nature, 442:448-451.
170. Ferguson, N. M., Donnelly, C. A., and Anderson, R. M. (2001a). The foot-and-mouth epidemic in Great Britain: Pattern of spread and impact of interventions. Science, 292(5519):1155-1160.
171. Ferguson, N. M., Donnelly, C. A., and Anderson, R. M. (2001b). Transmission intensity and impact of control policies on the foot and mouth epidemic in Great Britain. Nature, 413(6855):542-548.
172. Ferguson, N. M., May, R. M., and Anderson, R. M. (1997). Measles: Persistence and synchronicity in disease dynamics and interspecific interactions. In Tilman, D. and Kareiva, P. M., editors, Spatial Ecology: The Role of Space in Population Dynamics and Interspecific Interactions, pages 137-157. Princeton University Press, Princeton, NJ.
173. Ferguson, N. M., Nokes, D. J., and Anderson, R. M. (1996). Dynamical complexity in age-structured models of the transmission of the measles virus: Epidemiological implications at high levels of vaccine uptake. Mathematical Biosciences, 138(2):101-130.
174. Ferrari, M. J., Grais, R. F., Bharti, N., Conlan, A. J. K., Bjørnstad, O. N., Wolfson, L. J., Guerin, P. J., Djibo, A., and Grenfell, B. T. (2008). The dynamics of measles in sub-Saharan Africa. Nature, 451:679-684.
175. Fiennes, R. (1978). Zoonoses and the Origins and Ecology of Human Disease.Academic Press, London.
176. Fine, P. E. (1982). Applications of mathematical models to the epidemiology of influenza: A critique. In Selby, P., editor, Influenza Models: Prospects for Development and Use, pages 15-85. MTP Press Limited, Lancaster.
177. Fine, P. E. and Clarkson, J. A. (1982). Measles in England and Wales, I: An analysis of factors underlying seasonal patterns. International Journal of Epidemiology, 11(1):5-14.
178. Fine, P. E. M. (2003). The interval between successive cases of an infectious disease. American Journal of Epidemiology, 158(11):1039-1047.
179. Finkenstädt, B. F. and Grenfell, B. T. (1998). Empirical determinants of measles metapopulation dynamics in England and Wales. Proceedings of the Royal Society of London, Series B, Biological Sciences, 265(1392):211-220.
180. Finkenstädt, B. F. and Grenfell, B. T. (2000). Time series modelling of childhood diseases: A dynamical systems approach. Journal of the Royal Statistical Society, Series C, Applied Statistics, 49:187-205.
181. Fisher, R. A. (1937). The wave of advance of advantageous genes. Annals of Eugenics, 7:355-369.
182. Flahault, A., Deguen, S., and Valleron, A. J. (1994). A mathematical model for the European spread of influenza. European Journal of Epidemiology, 10(4):471-474.
183. Flahault, A., Letrait, S., Blin, P., Hazout, S., Menares, J., and Valleron, A. J. (1988). Modelling the 1985 influenza epidemic in France. Statistics in Medicine, 7(11):1147-1155.
184. Flahault, A., Vergu, E., Coudeville, L., and Grais, R. F. (2006). Strategies for containing a global influenza pandemic. Vaccine, 24(44-46):6751-6755.
185. Freeman, R. (2002). A mathematical model for the geographic spread of infectious disease via air travel. PhD thesis, Johns Hopkins University.
186. Fulford, G. R., Roberts, M. G., and Heesterbeek, J. A. P. (2002). The metapopulation dynamics of an infectious disease: Tuberculosis in possums. Theoretical Population Biology, 61(1):15-29.
187. Gani, R. and Leach, S. (2001). Transmission potential of smallpox in contemporary populations. Nature, 414(6865):748-751.
188. Gardner, L. I., Brundage, J. F., Burke, D. S., McNeil, J. G., Visintine, R., and Miller, R. N. (1989). Spatial diffusion of the human immunodeficiency virus infection epidemic in the United States, 1985-1987. Annals of the Association of American Geographers, 79:25-43.
189. Gatrell, A. C., Bailey, T. C., Diggle, P. J., and Rowlingson, B. S. (1996). Spatial point pattern analysis and its application in geographical epidemiology. Transactions of the Institute of British Geographers, 21(1):256-274.
190. Gatrell, A. C. and Löytönen, M. (1998). GIS and health research: An introduction. In Gatrell, A. C. and Löytönen, M., editors, GIS and Health, pages 3-16. Taylor and Francis, Philadelphia.
191. Germann, T. C., Kadau, K., Longini, Jr., I. M., and Macken, C. A. (2006). Mitigation strategies for pandemic influenza in the United States. Proceedings of the National Academy of Sciences of the United States of America, 103(15):5935-5940.
192. Ghani, A. C., Donnelly, C. A., and Garnett, G. P. (1998). Sampling biases and missing data in explorations of sexual partner networks for the spread of sexually transmitted diseases. Statistics in Medicine, 17:2079-2097.
193. Ghani, A. C. and Garnett, G. P. (1998). Measuring sexual partner networks for transmission of sexually transmitted diseases. Journal of the Royal Statistical Society, Series A, Statistics in Society, 161:227-238.
194. Ghani, A. C. and Garnett, G. P. (2000). Risks of acquiring and transmitting sexually transmitted diseases in sexual partner networks. Sexually Transmitted Diseases, 27(10):579-587.
195. Gibbens, J. C., Sharpe, C. E., Wilesmith, J. W., Mansley, L. M., Michalopoulou, E., Ryan, J. B., and Hudson, M. (2001). Descriptive epidemiology of the 2001 foot-and-mouth disease epidemic in Great Britain: The first five months. Veterinary Record, 149(24):729-743.
196. Gibson, M. A. and Bruck, J. (2000). Efficient exact stochastic simulation of chemical systems with many species and many channels. Journal of Physical Chemistry A, 104:1876-1889.
197. Gillespie, D. T. (1977). Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry A, 81:2340-2361.
198. Girvan, M., Callaway, D. S., Newman, M. E. J., and Strogatz, S. H. (2002). A simple model of epidemics with pathogen mutation. Physical Review E, 63:031915.
199. Glavanakov, S., White, D. J., Caraco, T., Lapenis, A., Robinson, G. R., Szymanski, B. K., and Maniatty, W. A. (2001). Lyme disease in New York State: Spatial pattern at a regional scale. American Journal of Tropical Medicine and Hygiene, 65(5):538-545.
200. Glezen, W. P. (1996). Emerging infections: Pandemic influenza. Epidemiologic Reviews, 18:64-76.
201. Gloster, J., Blackall, R. M., Sellers, R. F., and Donaldson, A. I. (1981). Forecasting the airborne spread of foot-and-mouth disease. Veterinary Record, 108(17):370-374.
202. Golub, A., Gorr, W. L., and Gould, P. R. (1993). Spatial diffusion of the HIV/AIDS epidemic: Modeling implications and case study of AIDS incidence in Ohio. Geographical Analysis, 25(2):85-100.
203. Gould, P. R. (1989). Geographic dimension of the AIDS epidemic. Professional Geographer, 41:71-78.
204. Gould, P. R., Kabel, J., Gorr, W. L., and Golub, A. (1991). AIDS: Predicting the next map. Interfaces, 21(3):80-92.
205. Grais, R. F., Ellis, J. H., and Glass, G. E. (2003). Assessing the impact of airline travel on the geographic spread of pandemic influenza. European Journal of Epidemiology, 18(11):1065-1072.
206. Grais, R. F., Ellis, J. H., Kress, A., and Glass, G. E. (2004). Modeling the spread of annual influenza epidemics in the U.S.: The potential role of air travel. Health Care Management Science, 7(2):127-134.
207. Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78:1360-1380.
208. Grassberger, P. (1983). On the critical behavior of the general epidemic process and dynamical percolation. Mathematical Biosciences, 63:157-172.
209. Gray, R. H., Wawer, M. J., Brookmeyer, R., Sewankambo, N. K., Serwadda, D., Wabwire-Mangen, F., Lutalo, T., Lin, X., vanCott, T., Quinn, T. C., and the Rakai Project Team. (2001). Probability of HIV-1 transmission per coital act in monogamous, heterosexual, HIV-1-discordant couples in Rakai, Uganda. Lancet, 357:1149-1153.
210. Green, L. E. and Medley, G. F. (2002). Mathematical modelling of the foot and mouth disease epidemic of 2001: Strengths and weaknesses. Research in Veterinary Science, 73(3):201-205.
211. Greenwood, M. (1931). On the statistical measure of infectiousness. Journal of Hygiene-Cambridge, 31:336-351.
212. Grenfell, B. T. (1992). Chance and chaos in measles dynamics. Journal of the Royal Statistical Society, Series B, Statistical Methodology, 54(2):383-398.
213. Grenfell, B. T. (2002). Rivers dam waves of rabies. Proceedings of the National Academy of Sciences of the United States of America, 99(6):3365-3367.
214. Grenfell, B. T., Bjørnstad, O. N., and Finkenstädt, B. F. (2002). Dynamics of measles epidemics: Scaling noise, determinism, and predictability with the TSIR model. Ecological Monographs, 72(2):185-202.
215. Grenfell, B. T., Bjørnstad, O. N., and Kappey, J. (2001). Travelling waves and spatial hierarchies in measles epidemics. Nature, 414(6865):716-723.
216. Grenfell, B. T. and Bolker, B. M. (1998). Cities and villages: Infection hierarchies in a measles metapopulation. Ecology Letters, 1(1):63-70.
217. Grenfell, B. T. and Harwood, J. (1997). (Meta)population dynamics of infectious diseases. Trends in Ecology and Evolution, 12(10):395-399.
218. Grimmett, G. (1999). Percolation. Grundlehren der Mathematischen Wissenschaften 321. Springer, New York, 2nd edition.
219. Grossman, Z. (1980). Oscillatory phenomena in a model of infectious diseases. Theoretical Population Biology, 18:204-243.
220. Guimerà, R. and Amaral, L. A. N. (2004). Modeling the world-wide airport network. European Physical Journal B, 38(2):381-385.
221. Gumel, A. B., Ruan, S., Day, T., Watmough, J., Brauer, F., van den Driessche, P., Gabrielson, D., Bowman, C., Alexander, M. E., Ardal, S., Wu, J., and Sahai, B. M. (2004). Modelling strategies for controlling SARS outbreaks. Proceedings of the Royal Society of London, Series B, Biological Sciences, 271(1554):2223-2232.
222. Gupta, S., Anderson, R. M., and May, R. M. (1989). Networks of sexual contacts: Implications for the pattern of spread of HIV. AIDS, 3:807-817.
223. Gwaltney Jr., J. M., Hendley, J. O., Simon, G., and Jordan Jr., W. S. (1966). Rhinovirus infections in an industrial population, I: The occurrence of illness. New England Journal of Medicine, 275(23):1261-1268.
224. Haggett, P. (1982). Building geographic components into epidemiological models. In Selby, P., editor, Influenza Models, pages 203-212. MTP Press Limited, Lancaster.
225. Haining, R. P. (2003). Spatial Data Analysis: Theory and Practice. Cambridge University Press, Cambridge.
226. Hamer, W. H. (1906). Epidemic disease in England - the evidence of variability and of persistency of type. Lancet, 1:733-739.
227. Hammersley, J. M. (1957). Percolation processes: Lower bounds for the critical probability. Annals of Mathematics and Statistics, 28:790-795.
228. Hammersley, J. M. (1959). Bornes superieures de la probabilite critique dans un process de filtration. In Le Calcul des Probabilities et Ses Applications, Paris, 15-20 Juillet, 1958. Centre National de la Recherche Scientifique (CNRS).
229. Hannay, D. and Jones, R. (2002). The effects of foot-and-mouth on the health of those involved in farming and tourism in Dumfries and Galloway. European Journal of General Practice, 8:83-89.
230. Harary, F. and Norman, R. Z. (1953). Graph Theory as a Mathematical Model in Social Science. University of Michigan Institute of Social Research, Ann Arbor.
231. Harary, F., Norman, R. Z., and Cartwright, D. (1965). Structural Models: An Introduction to the Theory of Directed Graphs. John Wiley & Sons, New York.
232. Harris, T. E. (1974). Contact interactions on a lattice. Annals of Probability, 2:969-988.
233. Hawryluk, L., Gold, W. L., Robinson, S., Pogorski, S., Galea, S., and Styra, R. (2004). SARS control and psychological effects of quarantine, Toronto, Canada. Emerging Infectious Diseases, 10(7):1206-1212.
234. Haydon, D. T., Kao, R. R., and Kitching, R. P. (2004). The UK foot-and-mouth-disease outbreak - the aftermath. Nature Reviews Microbiology, 2(8):675-681.
235. He, D. H. and Stone, L. (2003). Spatio-temporal synchronization of recurrent epidemics. Proceedings of the Royal Society of London, Series B, Biological Sciences, 270(1523):1519-1526.
236. Heasman, M. A. and Reid, D. D. (1961). Theory and observation in family epidemics of the common cold. British Journal of Preventive and Social Medicine, 15:12-16.
237. Heesterbeek, J. A. P. and Dietz, K. (1996). The concept of R0 in epidemic theory. Statistica Neerlandica, 50:89-110.
238. Heil, G. H. and White, H. C. (1976). An algorithm for finding simultaneous homomorphic correspondences between graphs and their image graphs. Behavioral Science, 21:26-35.
239. Hendley, J. O., Gwaltney Jr., J. M., and Jordan Jr., W. S. (1969). Rhi-novirus infections in an industrial population, IV: Infections within families of employees during two fall peaks of respiratory illness. American Journal of Epidemiology, 89(2):184-196.
240. Herring, D. A. and Sattenspiel, L. (2003). Death in winter: The Spanish flu in the Canadian Subarctic. In Phillips, H. and Killingray, D., editors, The Spanish Influenza Pandemic of 1918-19, pages 156-172. Routledge, London.
241. Hethcote, H. W. (1974). Asymptotic behaviour and stability in epidemic models. In van den Driessche, P., editor, Mathematical Problems in Biology, Lecture Notes in Biomathematics 2, pages 83-92. Springer-Verlag, New York.
242. Hethcote, H. W. (1978). An immunization model for a heterogeneous population. Theoretical Population Biology, 14:338-349.
243. Hethcote, H. W. (1989). A model for HIV transmission and AIDS. In Castillo-Chavez, C., Levin, S. A., and Shoemaker, C., editors, Mathematical Approaches to Resource Management and Epidemiology, Lecture Notes in Biomathematics 81, pages 164-176. Springer-Verlag, Berlin.
244. Hethcote, H. W. (1998). Oscillations in an endemic model for pertussis. Canadian Applied Mathematics Quarterly, 6:61-88.
245. Hethcote, H. W. and Thieme, H. R. (1985). Stability of the endemic equilibrium in epidemic models with subpopulations. Mathematical Biosciences, 75:205-227.
246. Hethcote, H. W. and Tudor, D. W. (1980). Integral equation models for endemic infectious diseases. Journal of Mathematical Biology, 9(1):37-47.
247. Hethcote, H. W. and Van Ark, J. W. (1987). Epidemiological models for heterogeneous populations: Proportionate mixing, parameter estimation, and immunization programs. Mathematical Biosciences, 84:85-118.
248. Hethcote, H. W., Yorke, J. A., and Nold, A. (1982). Gonorrhea modelling: A comparison of control methods. Mathematical Biosciences, 58:93-109.
249. Heymann, D. L., editor. (2004). Control of Communicable Diseases Manual. The American Public Health Association, Washington, DC, 18th edition.
250. Higham, D. J. (2001). An algorithmic introduction to numerical simulation of stochastic differential equations. SIAM Review, 43(3):525-546.
251. Hill, A. V., Allsopp, C. E., Kwiatkowski, D., Anstey, N. M., Twu-masi, P., Rowe, P. A., Bennett, S., Brewster, D., McMichael, A. J., and Greenwood, B. M. (1991). Common West African HLA antigens are associated with protection from severe malaria. Nature, 352(6336):595-600.
252. Hilleman, M. R. (2002). Realities and enigmas of human viral influenza: Pathogenesis, epidemiology and control. Vaccine, 20:3068-3087.
253. Holland, P. W. and Leinhardt, S. (1971). Transitivity in structural models of small groups. Comparative Group Studies, 2:107-124.
254. Holland, P. W. and Leinhardt, S. (1976). Local structure in social networks. Sociological Methodology, 7:1-45.
255. Honhold, N., Taylor, N. M., Mansley, L. M., and Paterson, A. D. (2004). Relationship of speed of slaughter on infected premises and intensity of culling of other premises to the rate of spread of the foot-and-mouth disease epidemic in Great Britain, 2001. Veterinary Record, 155(10):287-294.
256. Hope Simpson, R. E. (1952). Infectiousness of communicable diseases in the household. The Lancet, 2:549-554.
257. Hoppensteadt, F. (1974). An age dependent epidemic model. Journal of the Franklin Institute, Engineering and Applied Mathematics, 297:325-333.
258. Hsieh, Y. H., Chen, C. W. S., and Hsu, S. B. (2004). SARS outbreak, Taiwan, 2003. Emerging Infectious Diseases, 10(2):201-206.
259. Hsieh, Y. H., King, C. C., Chen, C. W. S., Ho, M. S., Lee, J. Y., Liu, F. C., Wu, Y. C., and JulianWu, J. S. (2005). Quarantine for SARS, Taiwan. Emerging Infectious Diseases, 11(2):278-282.
260. Hufnagel, L., Brockmann, D., and Geisel, T. (2004). Forecast and control of epidemics in a globalized world. Proceedings of the National Academy of Sciences of the United States of America, 101(42):15124-15129.
261. Hugh-Jones, M. E. and Wright, P. B. (1970). Studies on the 1967-8 foot-and-mouth disease epidemic: The relation of weather to the spread of disease. Journal of Hygiene-Cambridge, 68(2):253-271.
262. Hyman, J. M. and LaForce, T. (2003). Modeling the spread of influenza among cities. In Banks, H. T. and Castillo-Chavez, C., editors, Bioterrorism: Mathematical Modeling Applications in Homeland Security, pages 211-236. Society for Industrial and Applied Mathematics, Philadelphia.
263. Hyman, J. M. and Stanley, E. A. (1988). Using mathematical models to understand the AIDS epidemic. Mathematical Biosciences, 90:415-474.
264. Isham, V. (1991). Assessing the variability of stochastic epidemics. Mathematical Biosciences, 107(2):209-224.
265. Jacquez, G. M., Grimson, R., Waller, L. A., and Wartenberg, D. (1996a). The analysis of disease clusters, part II: Introduction to techniques. Infection Control and Hospital Epidemiology, 17(6):385-397.
266. Jacquez, G. M., Waller, L. A., Grimson, R., and Wartenberg, D. (1996b). The analysis of disease clusters, part I: State of the art. Infection Control and Hospital Epidemiology, 17(5):319-327.
267. Jacquez, J. A. (1996). Compartmental Models in Medicine and Biology. BioMedware, Ann Arbor, MI, 3rd edition.
268. Jacquez, J. A., Koopman, J. S., Simon, C. P., Sattenspiel, L., and Perry, T. (1988). Modeling and analyzing HIV transmission: The effect of contact patterns. Mathematical Biosciences, 92:119-199.
269. Jagers, P. (1975). Branching Processes with Biological Applications. Wiley, New York.
270. Jalvingh, A. W., Nielen, M., Maurice, H., Stegeman, A. J., Elbers, A. R., and Dijkhuizen, A. A. (1999). Spatial and stochastic simulation to evaluate the impact of events and control measures on the 1997-1998 classical swine fever epidemic in the Netherlands, I: Description of simulation model. Preventive Veterinary Medicine, 42(3-4):271-295.
271. Jansen, V. A. A. and Lloyd, A. L. (2000). Local stability analysis of spatially homogeneous solutions of multi-patch systems. Journal of Mathematical Biology, 41(3):232-252.
272. Jeffery, K. J., Usuku, K., Hall, S. E., Matsumoto, W., Taylor, G. P., Procter, J., Bunce, M., Ogg, G. S., Welsh, K. I., Weber, J. N., Lloyd, A. L., Nowak, M. A., Nagai, M., Kodama, D., Izumo, S., Osame, M., and Bangham, C. R. (1999). HLA alleles determine human T-lymphotropic virus-I (HTLV-I) proviral load and the risk of HTLV-I-associated myelopathy. Proceedings of the National Academy of Sciences of the United States of America, 96(7):3848-3853.
273. Jeltsch, F., Muller, M. S., Grimm, V., Wissel, C., and Brandl, R. (1997). Pattern formation triggered by rare events: Lessons from the spread of rabies. Proceedings of the Royal Society of London, Series B, Biological Sciences, 264(1381):495-503.
274. Jensen, A. (1948). An elucidation of Erlang's statistical works through the theory of stochastic processes. In Brockmeyer, E., Halstr0m, H. L., and Jensen, A., editors, The Life and Works of A. K. Erlang, pages 23-100. The Copenhagen Telephone Company, Copenhagen.
275. Johnson, N. P. A. S. and Mueller, J. (2002). Updating the accounts: Global mortality of the 1918-1920 "Spanish" influenza pandemic. Bulletin of the History of Medicine, 76:105-115.
276. Jones, J. H. and Handcock, M. S. (2003). Sexual contacts and epidemic thresholds. Nature, 423:605-606.
277. Jorde, L. B., Pitkänen, K., Mielke, J. H., Fellman, J. O., and Eriksson, A. W. (1990). Historical epidemiology of smallpox in Kitee, Finland. In Swedlund, A. C. and Armelagos, G., editors, The Health and Disease of Populations in Transition, pages 183-200. Bergin & Garvey, New York.
278. Kao, R. R. (2002). The role of mathematical modelling in the control of the 2001 FMD epidemic in the UK. Trends in Microbiology, 10(6):279-286.
279. Kao, R. R. (2003). The impact of local heterogeneity on alternative control strategies for foot-and-mouth disease. Proceedings of the Royal Society of London, Series B, Biological Sciences, 270(1533):2557-2564.
280. Kaplan, E. H. (1989). Can bad models suggest good policies? Sexual mixing and the AIDS epidemic. Journal of Sex Research, 26:301-314.
281. Kaplan, E. H. and Lee, Y. S. (1990). How bad can it get? Bounding worst case endemic heterogeneous mixing models of HIV/AIDS. Mathematical Biosciences, 99:157-180.
282. Kaplan, M. and Webster, R. G. (1977). The epidemiology of influenza. Scientific American, 237(6):88-106.
283. Karatzas, I. and Shreve, S. E. (1991). Brownian Motion and Stochastic Calculus. Graduate Texts in Mathematics 113. Springer-Verlag, New York, 2nd edition.
284. Karinthy, F. (1929). Chains. In Everything is the Other Way. Atheneum Press, Budapest.
285. Keeling, M., Tildesley, M., Savill, N., Woolhouse, M., Shaw, D., Dear-don, R., Brooks, S., and Grenfell, B. (2006). FMD control strategies (reply). Veterinary Record, 158(20):707-708.
286. Keeling, M. J. (1999a). Correlation equations for endemic diseases: Externally imposed and internally generated heterogeneity. Proceedings of the Royal Society of London, Series B, Biological Sciences, 266(1422):953-960.
287. Keeling, M. J. (1999b). The effects of local spatial structure on epidemiological invasions. Proceedings of the Royal Society of London, Series B, Biological Sciences, 266(1421):859-867.
288. Keeling, M. J. (2000a). Metapopulation moments: Coupling, stochas-ticity and persistence. Journal of Animal Ecology, 69(5):725-736.
289. Keeling, M. J. (2000b). Multiplicative moments and measures of persistence in ecology. Journal of Theoretical Biology, 205(2):269-281.
290. Keeling, M. J. (2005). Models of foot-and-mouth disease. Proceedings of the Royal Society of London, Series B, Biological Sciences, 272(1569):1195-1202.
291. Keeling, M. J. and Grenfell, B. T. (1997). Disease extinction and community size: Modeling the persistence of measles. Science, 275(5296):65-67.
292. Keeling, M. J. and Grenfell, B. T. (1998). Effect of variability in infection period on the persistence and spatial spread of infectious diseases. Mathematical Biosciences, 147(2):207-226.
293. Keeling, M. J., Rand, D. A., and Morris, A. J. (1997). Correlation models for childhood epidemics. Proceedings of the Royal Society of London, Series B, Biological Sciences, 264(1385):1149-1156.
294. Keeling, M. J. and Rohani, P. (2002). Estimating spatial coupling in epidemiological systems: A mechanistic approach. Ecology Letters, 5(1):20-29.
295. Keeling, M. J. and Rohani, P. (2007). Modeling Infectious Diseases in Humans and Animals. Princeton University Press, Princeton, NJ.
296. Keeling, M. J., Woolhouse, M. E. J., May, R. M., Davies, G., and Grenfell, B. T. (2003). Modelling vaccination strategies against foot-and-mouth disease. Nature, 421(6919):136-142.
297. Keeling, M. J., Woolhouse, M. E. J., Shaw, D. J., Matthews, L., Chase-Topping, M., Haydon, D. T., Cornell, S. J., Kappey, J., Wile-smith, J., and Grenfell, B. T. (2001). Dynamics of the 2001 UK foot and mouth epidemic: Stochastic dispersal in a heterogeneous landscape. Science, 294(5543):813-817.
298. Kermack, W. O. and McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London, Series A, Mathematical and Physical Sciences, 115:700-721.
299. Kirchoff, G. (1847). Über die auflösung der gleichungen, auf welche man bei der untersuchung der linearen Vertheilung galvanischer ströme geführt wird. Annalen der Physik, 148:497-508.
300. Kitching, R. P., Hutber, A. M., and Thrusfield, M. V. (2005). A review of foot-and-mouth disease with special consideration for the clinical and epidemiological factors relevant to predictive modelling of the disease. Veterinary Journal, 169(2):197-209.
301. Kitching, R. P., Taylor, N. M., and Thrusfield, M. V. (2007). Vaccination strategies for foot-and-mouth disease. Nature, 445:E12.
302. Kitching, R. P., Thrusfield, M. V., and Taylor, N. M. (2006). Use and abuse of mathematical models: An illustration from the 2001 foot and mouth epidemic in the United Kingdom. Revue Scientifique et Technique de L'Office International des Epizooties, 25(1):293-311.
303. Kitron, U. and Kazmierczak, J. J. (1997). Spatial analysis of the distribution of Lyme disease in Wisconsin. American Journal of Epidemiology, 145(6):558-566.
304. Klauber, M. R. and Angulo, J. J. (1976). Variola minor in Braganca Paulista county, 1956. Attack rates in various population units of the two schools including most students with the disease. American Journal of Epidemiology, 103(1):112-125.
305. Klemm, K. and Eguiluz, V. M. (2002). Growing scale-free networks with small-world behavior. Physical Review E, 65(5 Pt 2):057102.
306. Kloeden, P. E. and Platen, E. (1999). Numerical Solution of Stochastic Differential Equations. Applications of Mathematics 23. Springer, New York.
307. Klovdahl, A. S. (1985). Social networks and the spread of infectious diseases: The AIDS example. Social Science and Medicine, 21:1203-1216.
308. Knox, E. G. (1980). Strategy for rubella vaccination. International Journal of Epidemiology, 9:13-23.
309. Kolmogoroff, A. N., Petrovsky, I. G., and Piscounoff, N. S. (1937). Etude de l'equation de la diffusion avec croissance de la quantite de matiere et son application a un probleme biologique. Bulletin de l'Universite a Moscou (ser intern), A1:1-25.
310. Koopman, J. S., Chick, S. E., Riolo, C. S., Adams, A. L., Wilson, M. L., and Becker, M. P. (2000). Modeling contact networks and infection transmission in geographic and social space using GERMS. Sexually Transmitted Diseases, 27(10):617-626.
311. Kretzschmar, M. (2000). Sexual network structure and sexually transmitted disease prevention: A modeling perspective. Sexually Transmitted Diseases, 27(10):627-635.
312. Kretzschmar, M. (2002). Mathematical epidemiology of Chlamydia trachomatis infections. Netherlands Journal of Medicine, 60(7 Suppl):35-43.
313. Kretzschmar, M. and Morris, M. (1996). Measures of concurrency in networks and the spread of infectious disease. Mathematical Biosciences, 133(2):165-195.
314. Kretzschmar, M., Reinking, D. P., Brouwers, H., van Zessen, G., and Jager, J. C. (1994). Network models: From paradigm to mathematical tool. In Kaplan, E. H. and Brandeau, M. L., editors, Modeling the AIDS Epidemic: Planning, Policy, and Prediction, pages 561-583. Raven Press, New York.
315. Kretzschmar, M., van Duynhoven, Y. T., and Severijnen, A. J. (1996). Modeling prevention strategies for gonorrhea and chlamydia using stochastic network simulations. American Journal of Epidemiology, 144(3):306-317.
316. Kulldorff, M. (1998). Statistical methods for spatial epidemiology: Tests for randomness. In Gatrell, A. C. and Löytönen, M., editors, GIS and Health, pages 49-62. Taylor and Francis, Philadelphia.
317. Kulldorff, M. and Nagarwalla, N. (1995). Spatial disease clusters: Detection and inference. Statistics in Medicine, 14(8):799-810.
318. Kuperman, M. and Abramson, G. (2001). Small world effect in an epidemiological model. Physical Review Letters, 86:2909-2912.
319. Kurtz, T. G. (1970). Solutions of ordinary differential equations as limits of pure jump Markov processes. Journal of Applied Probability, 7:49-58.
320. Kurtz, T. G. (1971). Limit theorems for sequences of jump Markov processes approximating ordinary differential equations. Journal of Applied Probability, 8:344-356.
321. Kuulasmaa, K. (1982). The spatial general epidemic and locally dependent random graphs. Journal of Applied Probability, 19:745-758.
322. Lam, N. S. N., Fan, M., and Liu, K. B. (1996). Spatial-temporal spread of the AIDS epidemic, 1982-1990: A correlogram analysis of four regions of the United States. Geographical Analysis, 28(2):93-107.
323. Leinhardt, S., editor. (1977). Social Networks: A Developing Paradigm. Academic Press, New York.
324. Lewis, M. A. (2000). Spread rate for a nonlinear stochastic invasion. Journal of Mathematical Biology, 41:430-454.
325. Lewis, M. A. and Pacala, S. (2000). Modeling and analysis of stochastic invasion processes. Journal of Mathematical Biology, 41(5):387-429.
326. Li, W. and Cai, X. (2004). Statistical analysis of airport network of China. Physical Review E, 69:046106.
327. Lidwell, O. M. and Williams, R. E. (1961). The epidemiology of the common cold. Journal of Hygiene-Cambridge, 59:309-319.
328. Liljeros, F., Edling, C. R., Amaral, L. A., Stanley, H. E., and Aberg, Y. (2001). The web of human sexual contacts. Nature, 411(6840):907-908.
329. Liljeros, F., Edling, C. R., Stanley, H. E., Aberg, Y., and Amaral, L. A. (2003). Sexual contacts and epidemic thresholds: Reply. Nature, 423:606.
330. Lipsitch, M., Cohen, T., Cooper, B., Robins, J. M., Ma, S., James, L., Gopalakrishna, G., Chew, S. K., Tan, C. C., Samore, M. H., Fisman, D., and Murray, M. (2003). Transmission dynamics and control of severe acute respiratory syndrome. Science, 300:1966-1970.
331. Lloyd, A. L. (2001a). Destabilization of epidemic models with the inclusion of realistic distributions of infectious periods. Proceedings of the Royal Society of London, Series B, Biological Sciences, 268(1470):985-993.
332. Lloyd, A. L. (2001b). Realistic distributions of infectious periods in epidemic models: Changing patterns of persistence and dynamics. Theoretical Population Biology, 60(1):59-71.
333. Lloyd, A. L. (2004). Estimating variability in models for recurrent epidemics: Assessing the use of moment closure techniques. Theoretical Population Biology, 65(1):49-65.
334. Lloyd, A. L. and Jansen, V. A. A. (2004). Spatiotemporal dynamics of epidemics: Synchrony in metapopulation models. Mathematical Biosciences, 188:1-16.
335. Lloyd, A. L. and May, R. M. (1996). Spatial heterogeneity in epidemic models. Journal of Theoretical Biology, 179(1):1-11.
336. Lloyd, A. L. and May, R. M. (2001). How viruses spread among computers and people. Science, 292(5520):1316-1317.
337. Lloyd-Smith, J. O., Galvani, A. P., and Getz, W. M. (2003). Controlling transmission of severe acute respiratory syndrome within a community and its hospital. Proceedings of the Royal Society of London, Series B, Biological Sciences, 270:1979-1989.
338. London, W. P. and Yorke, J. A. (1973). Recurrent outbreaks of measles, chickenpox, and mumps, I: Seasonal variation in contact rates. American Journal of Epidemiology, 98:453-468.
339. Longini, Jr., I. M. (1988). A mathematical model for predicting the geographic spread of new infectious agents. Mathematical Biosciences, 90(1-2):367-383.
340. Longini, Jr., I. M., Clark, W. S., Byers, R. H., Ward, J. W., Darrow, W. W., Lemp, G. F., and Hethcote, H. W. (1989). Statistical analysis of the stages of HIV infection using a Markov model. Statistics in Medicine, 8(7):831-843.
341. Longini, Jr., I. M., Fine, P. E., and Thacker, S. B. (1986). Predicting the global spread of new infectious agents. American Journal of Epidemiology, 123(3):383-391.
342. Longini, Jr., I. M., Nizam, A., Xu, S., Ungchusak, K., Han-shaoworakul, W., Cummings, D. A. T., and Halloran, M. (2005). Containing pandemic influenza at the source. Science, 309(5737):1083-1087.
343. Löytönen, M. (1991). The spatial diffusion of human immunodeficiency virus type 1 in Finland, 1982-1997. Annals of the Association of American Geographers, 81:127-151.
344. Löytönen, M. (1994). Growth models and the HIV epidemic in Finland. Social Science and Medicine, 38(1):179-185.
345. Löytönen, M. and Arbona, S. I. (1996). Forecasting the AIDS epidemic in Puerto Rico. Social Science and Medicine, 42(7):997-1010.
346. Löytönen, M. and Maasilta, P. (1997). Forecasting the HIV epidemic in Finland by using functional small area units. GeoJournal, 41(3):215-222.
347. Luce, R. D. (1950). Connectivity and generalized cliques in sociometric group structure. Psychometrika, 15:169-190.
348. Macdonald, G. (1952). The analysis of equilibrium in malaria. Tropical Diseases Bulletin, 49:813-829.
349. Malice, M. P. and Kryscio, R. J. (1989). On the role of variable incubation periods in simple epidemic models. IMA Journal of Mathematics Applied in Medicine and Biology, 6(4):233-242.
350. Markel, H. (1997). QUARANTINE! East European Jewish Immigrants and the New York City Epidemics of 1892. The Johns Hopkins University Press, Baltimore.
351. Marshall, R. J. (1991). A review of methods for the statistical analysis of spatial patterns of disease. Journal of the Royal Statistical Society, Series A, Statistics in Society, 154(3):421-441.
352. Matinovic, J. (1969). A short history of quarantine. University of Michigan Medical Journal, 35:224-228.
353. Matsuda, M., Ogita, N., Sasaki, A., and Sato, K. (1992). Statistical mechanisms of population. Progress in Theoretical Physics, 88:1035-1049.
354. Matthews, L., Haydon, D. T., Shaw, D. J., Chase-Topping, M. E., Keeling, M. J., and Woolhouse, M. E. (2003). Neighbourhood control policies and the spread of infectious diseases. Proceedings of the Royal Society of London, Series B, Biological Sciences, 270(1525):1659-1666.
355. May, R. M. and Anderson, R. M. (1984). Spatial heterogeneity and the design of immunization programs. Mathematical Biosciences, 72:83-111.
356. May, R. M. and Anderson, R. M. (1988). The transmission dynamics of human immunodeficiency virus (HIV). Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences, 321:565-607.
357. May, R. M. and Lloyd, A. L. (2001). Infection dynamics on scale-free networks. Physical Review E, 64:066112.
358. McCallum, H., Barlow, N., and Hone, J. (2001). How should pathogen transmission be modelled? Trends in Ecology and Evolution, 16:295-300.
359. McKee Jr., K. T., Shields, T. M., Jenkins, P. R., Zenilman, J. M., and Glass, G. E. (2000). Application of a geographic information system to the tracking and control of an outbreak of shigellosis. Clinical Infectious Diseases, 31(3):728-733.
360. Meade, M. S. and Earickson, R. J. (2000). Medical Geography. Guilford Press, New York.
361. Metz, J. A. J. and Diekmann, O. (1986). The Dynamics of Physiologically Structured Populations. Lecture Notes in Biomathematics 68. Springer-Verlag, New York.
362. Metz, J. A. J., Mollison, D., and van den Bosch, F. (2000). The dynamics of invasion waves. In Dieckmann, U., Law, R., and Metz, J. A. J., editors, The Geometry of Ecological Interactions: Simplifying Spatial Complexity. Cambridge University Press, Cambridge.
363. Meyers, L. A., Pourbohloul, B., Newman, M. E., Skowronski, D. M., and Brunham, R. C. (2005). Network theory and SARS: Predicting outbreak diversity. Journal of Theoretical Biology, 232(1):71-81.
364. Mielke, J. H., Jorde, L. B., Trapp, P. G., Anderton, D. L., Pitkanen, K., and Eriksson, A. W. (1984). Historical epidemiology of smallpox in Åland, Finland: 1751-1890. Demography, 24:271-295.
365. Milgram, S. (1967). The small world problem. Psychology Today, 2:60-67.
366. Miller, J. M. (1993). Vignette of medical history: Lazaretto Point. Maryland Medical Journal, 42:1123-1125.
367. Mollison, D. (1977). Spatial contact models for ecological and epidemic spread. Journal of the Royal Statistical Society, Series B, Statistical Methodology, 39:283-326.
368. Mollison, D. (1991). Dependence of epidemic and population velocities on basic parameters. Mathematical Biosciences, 107:255-287.
369. Mollison, D. and Kuulasmaa, K. (1985). Spatial epidemic models: Theory and simulations. In Bacon, P., editor, Population Dynamics of Rabies in Wildlife, pages 291-309. Academic Press, London.
370. Moncayo, A. C., Edman, J. D., and Finn, J. T. (2000). Application of geographic information technology in determining risk of eastern equine encephalomyelitis virus transmission. Journal of the American Mosquito Control Association, 16(1):28-35.
371. Monto, A. S. (1968). A community study of respiratory infections in the tropics, 3: Introduction and transmission of infections within families. American Journal of Epidemiology, 88(1):69-79.
372. Moore, D. A. and Carpenter, T. E. (1999). Spatial analytical methods and geographic information systems: Use in health research and epidemiology. Epidemiologic Reviews, 21(2):143-161.
373. Moreno, J. L. (1934). Who Shall Survive?: A New Approach to the Problem of Human Interrelations. Nervous and Mental Disease Publishing Company, Washington, DC.
374. Morris, M. (1993). Epidemiology and social networks: Modeling structured diffusion. Sociological Methods and Research, 22(1):99-126.
375. Morris, M., editor. (2004a). Network Epidemiology: A Handbook for Survey Design and Data Collection. Oxford University Press, Oxford.
376. Morris, M. (2004b). Overview of network survey designs. In Morris, M., editor, Network Epidemiology: A Handbook for Survey Design and Data Collection, pages 8-21. Oxford University Press, Oxford.
377. Morris, M. and Kretzschmar, M. (1995). Concurrent partnerships and transmission dynamics in networks. Social Networks, 17(3-4):299-318.
378. Morris, M. and Kretzschmar, M. (1997). Concurrent partnerships and the spread of HIV. AIDS, 11(5):641-648.
379. Morris, M., Podhisita, C., Wawer, M. J., and Handcock, M. S. (1996). Bridge populations in the spread of HIV/AIDS in Thailand. AIDS, 10(11):1265-1271.
380. Morris, R. S., Wilesmith, J. W., Stern, M. W., Sanson, R. L., and Stevenson, M. A. (2001). Predictive spatial modelling of alternative control strategies for the foot-and-mouth disease epidemic in Great Britain, 2001. Veterinary Record, 149(5):137-144.
381. Morrison, A. C., Getis, A., Santiago, M., Rigau-Perez, J. G., and Reiter, P. (1998). Exploratory space-time analysis of reported dengue cases during an outbreak in Florida, Puerto Rico, 1991-1992. American Journal of Tropical Medicine and Hygiene, 58(3):287-298.
382. Mort, M., Convery, I., Baxter, J., and Bailey, C. (2005). Psychosocial effects of the 2001 UK foot and mouth disease epidemic in a rural population: Qualitative diary based study. British Medical Journal, 331:1234-1238.
383. Moutou, F. (2002). Epidemiological basis useful for the control of foot-and-mouth disease. Comparative Immunology, Microbiology, and Infectious Diseases, 25(5-6):321-330.
384. Moutou, F. and Durand, B. (1994). Modelling the spread of foot-and-mouth disease virus. Veterinary Research, 25(2-3):279-285.
385. Murray, G. D. and Cliff, A. D. (1977). A stochastic model for measles epidemics in a multi-region setting. Transactions of the Institute of British Geographers, 2:158-174.
386. Murray, J. D. (1987). Modeling the spread of rabies. American Scientist, 75:280-284.
387. Murray, J. D. (1989). Mathematical Biology. Springer-Verlag, New York.
388. Murray, J. D., Stanley, E. A., and Brown, D. L. (1986). On the spatial spread of rabies among foxes. Proceedings of the Royal Society of London, Series B, Biological Sciences, 229(1255):111-150.
389. Musto, D. F. (1988). Quarantine and the problem of AIDS. In Fee, E. and Fox, D. M., editors, AIDS: The Burdens of History, pages 67-84. University of California Press, Los Angeles.
390. Nåsell, I. (1999). On the time to extinction in recurrent epidemics. Journal of the Royal Statistical Society, Series B, Statistical Methodology, 61:309-330.
391. Newman, M. E. J. (2002a). Assortative mixing in networks. Physical Review Letters, 89:208701.
392. Newman, M. E. J. (2002b). Spread of epidemic diseases on networks. Physical Review E, 66:016128.
393. Newman, M. E. J. (2003a). Ego-centered networks and the ripple effect. Social Networks, 25:83-95.
394. Newman, M. E. J. (2003b). Mixing patterns in networks. Physical Review E, 67:026126.
395. Newman, M. E. J. (2003c). Properties of highly clustered networks. Physical Review E, 68:026121.
396. Newman, M. E. J. (2003d). The structure and function of complex networks. SIAM Review, 45:167-256.
397. Nielen, M., Jalvingh, A. W., Meuwissen, M. P., Horst, S. H., and Dijkhuizen, A. A. (1999). Spatial and stochastic simulation to evaluate the impact of events and control measures on the 1997-1998 classical swine fever epidemic in the Netherlands, II: Comparison of control strategies. Preventive Veterinary Medicine, 42(3-4):297-317.
398. Nisbet, R. M. and Gurney, W. S. C. (1982). Modelling Fluctuating Populations. Wiley, New York.
399. Nisbet, R. M. and Gurney, W. S. C. (1986). The formulation of age-structured models. In Hallam, T. G. and Levin, S. A., editors, Mathematical Ecology: An Introduction, Biomathematics 17. Springer-Verlag, New York.
400. Noble, J. V. (1974). Geographic and temporal development of plagues. Nature, 250(5469):726-729.
401. Nold, A. (1980). Heterogeneity in disease-transmission modeling. Mathematical Biosciences, 52:227-240.
402. North, M. J., Collier, N. T., and Vos, J. R. (2006). Experiences creating three implementations of the Repast agent modeling toolkit. ACM Transactions on Modeling and Computer Simulation, 16:1-25.
403. Nowak, M. A., Lloyd, A. L., Vasquez, G. M., Wiltrout, T. A., Wahl, L. M., Bischofberger, N., Williams, J., Kinter, A., Fauci, A. S., Hirsch, V. M., and Lifson, J. D. (1997). Viral dynamics of primary viremia and antiretroviral therapy in simian immunodeficiency virus infection. Journal of Virology, 71(10):7518-7525.
404. Øksendal, B. K. (1998). Stochastic Differential Equations: An Introduction with Applications. Springer, New York, 5th edition.
405. Olff, M., Koeter, M. W. J., Van Haaften, E. H., Kersten, P. H., and Gersons, B. P. R. (2005). Impact of a foot and mouth disease crisis on post-traumatic stress symptoms in farmers. British Journal of Psychiatry, 186:165-166.
406. Olsen, L. F., Truty, G. L., and Schaffer, W. M. (1988). Oscillations and chaos in epidemics: A nonlinear dynamic study of six childhood diseases in Copenhagen, Denmark. Theoretical Population Biology, 33(3):344-370.
407. Olson, D. R., Simonsen, L., Edelson, P. J., and Morse, S. S. (2005). Epidemiological evidence of an early wave of the 1918 influenza pandemic in New York City. Proceedings of the National Academy of Sciences of the United States of America, 102(31):11059-11063.
408. Ooi, P. L., Lim, S., and Chew, S. K. (2005). Use of quarantine in the control of SARS in Singapore. American Journal of Infection Control, 33(5):252-257.
409. Oxford, J. S. (2001). The so-called Great Spanish Influenza Pandemic of 1918 may have originated in France in 1916. Philosophical Transactions of the Royal Society of London, B, 356:1857-1859.
410. Oxford, J. S., Sefton, A., Jackson, R., Innes, W., Daniels, R. S., and Johnson, N. P. A. S. (2002). World War I may have allowed the emergence of 'Spanish" influenza. The Lancet Infectious Diseases, 2:111-114.
411. Palese, P. (1993). Evolution of influenza and RNA viruses. In Morse, S. J., editor, Emerging Viruses, pages 226-233. Oxford University Press, Oxford.
412. Pang, X., Zhu, Z., Xu, F., Guo, J., Gong, X., Liu, D., Liu, Z., Chin, D. P., and Felkin, D. R. (2003). Evaluation of control measures implemented in the Severe Acute Respiratory Syndrome outbreak in Beijing, 2003. Journal of the American Medical Association, 290(24):3215-3221.
413. Pantaleo, G., Graziosi, C., and Fauci, A. S. (1993). New concepts in the immunopathogenesis of human immunodeficiency virus infection. New England Journal of Medicine, 328(5):327-335.
414. Panum, P. L. (1847). Iagttagelser anstillede under maeslinge-epidermien paa Faeroerne i Aaret 1846. Bibliothek for Laeger, 1:270-344.
415. Panum, P. L. (1939). Observations made during the epidemic of measles in the Faeroe Islands in the year 1846. Medical Classics, 3:803-886.
416. Pastor-Satorras, R. and Vespignani, A. (2001a). Epidemic dynamics and endemic states in complex networks. Physical Review E, 63:066117.
417. Pastor-Satorras, R. and Vespignani, A. (2001b). Epidemic spreading in scale-free networks. Physical Review Letters, 86(14):3200-3203.
418. Pastor-Satorras, R. and Vespignani, A. (2002). Immunization of complex networks. Physical Review E, 65:036104.
419. Peiris, J. S. M., Yuen, K. Y., Osterhaus, A. D. M. E., and Stohr, K. (2003). Current concepts: The severe acute respiratory syndrome. The New England Journal of Medicine, 349(25):2431-2441.
420. Peterman, T. A., Stoneburner, R. L., Allen, J. R., Jaffe, H. W., and Curran, J. W. (1988). Risk of human immunodeficiency virus transmission from heterosexual adults with transfusion-associated infections. Journal of the American Medical Association, 259:55-58.
421. Pfeiffer, D. U. and Hugh-Jones, M. (2002). Geographical information systems as a tool in epidemiological assessment and wildlife disease management. Revue Scientifique et Technique de L'Office International des Épizooties, 21(1):91-102.
422. Pool, I. and Kochen, M. (1978). Contacts and influence. Social Networks, 1:1-48.
423. Post, W. M., DeAngelis, D. L., and Travis, C. C. (1983). Endemic disease in environments with spatially heterogeneous host populations. Mathematical Biosciences, 63:289-302.
424. Potter, C. W. (2001). A history of influenza. Journal of Applied Microbiology, 91:572-579.
425. Potterat, J. J., Woodhouse, D. E., Muth, S. Q., Rothenberg, R. B., Darrow, W. W., Klovdahl, A. S., and Muth, J. B. (2004). Network dynamism: History and lessons of the Colorado Springs study. In Morris, M., editor, Network Epidemiology: A Handbook for Survey Design and Data Collection, pages 87-114. Oxford University Press, Oxford.
426. Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P. (1996). Numerical Recipes in FORTRAN: The Art of Scientific Computing. Cambridge University Press, Cambridge, 2nd edition.
427. Rand, D. (1999). Correlation equations and pair approximations for spatial ecologies. In McGlade, E., editor, Advanced Ecological Theory: Principles and Applications, pages 100-142. Blackwell Science, Oxford.
428. Rapoport, A. (1957). Contribution to the theory of random and biased nets. Bulletin of Mathematical Biophysics, 19:257-277.
429. Rapoport, A. and Horvath, W. J. (1961). A study of a large sociogram. Behavioral Sciences, 6:279-291.
430. Rass, L. and Radcliffe, J. (2003). Spatial Deterministic Epidemics. American Mathematical Society, Providence, RI.
431. Reid, A. H., Taubenberger, J. K., and Fanning, T. G. (2004). Evidence of an absence: The genetic origins of the 1918 pandemic influenza virus. Nature Reviews Microbiology, 2:909-914.
432. Renshaw, E. (1991). Modelling Biological Populations in Space and Time. Cambridge Studies in Mathematical Biology 11. Cambridge University Press, Cambridge.
433. Rhodes, C. J. and Anderson, R. M. (1996). A scaling analysis of measles epidemics in a small population. Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences, 351:1679-1688.
434. Riley, S., Fraser, C., Donnelly, C. A., Ghani, A. C., Abu-Raddad, L. J., Hedley, A. J., Leung, G. M., Ho, L.-M., Lam, T.-H., Thach, T. Q., Chau, P., Chan, K.-P., Lo, S.-V., Leung, P.-Y., Tsang, T., Ho, W., Lee, K.-H., Lau, E. M. C., Ferguson, N. M., and Anderson, R. M. (2003). Transmission dynamics of the etiological agent of SARS in Hong Kong: Impact of public health interventions. Science, 300:1961-1966.
435. Rivas, A. L., Tennenbaum, S. E., Aparicio, J. P., Hoogesteijn, A. L., Mohammed, H. O., Castillo-Chavez, C., and Schwager, S. J. (2003). Critical response time (time available to implement effective measures for epidemic control): Model building and evaluation. Canadian Journal of Veterinary Research, 67(4):307-311.
436. Roberts, F. S. (1976). Discrete Mathematical Models with Applications to Social, Biological, and Environmental Problems. Prentice-Hall, Englewood Cliffs, NJ.
437. Roberts, F. S. (1979). Graph theory and the social sciences. In Wilson, R. J. and Beineke, L. W., editors, Applications of Graph Theory, pages 255-291. Academic Press, New York.
438. Robinson, T. P. (2000). Spatial statistics and geographical informa-tion systems in epidemiology and public health. Advances in Parasitology, 47:81-128.
439. Roethlisberger, F. J. and Dickson, W. J. (1939). Management and the Worker. Harvard University Press, Cambridge, MA.
440. Rohani, P., Earn, D. J., Finkenstädt, B. F., and Grenfell, B. T. (1998). Population dynamic interference among childhood diseases. Proceedings of the Royal Society of London, Series B, Biological Sciences, 265(1410):2033-2041.
441. Rohani, P., Earn, D. J., and Grenfell, B. T. (1999). Opposite patterns of synchrony in sympatric disease metapopulations. Science, 286(5441):968-971.
442. Rohani, P., Green, C. J., Mantilla-beniers, N. B., and Grenfell, B. T. (2003). Ecological interference between fatal diseases. Nature, 422(6934):885-888.
443. Rohani, P., Keeling, M. J., and Grenfell, B. T. (2002). The interplay between determinism and stochasticity in childhood diseases. American Naturalist, 159(5):469-481.
444. Rozenfeld, A. F., Cohen, R., Ben-Avraham, D., and Havlin, S. (2002). Scale-free networks on lattices. Physical Review Letters, 89(21):218-701.
445. Rushton, G. (1998). Improving the geographic basis of health surveillance using GIS. In Gatrell, A. C. and Löytönen, M., editors, GIS and Health, pages 63-79. Taylor and Francis, Philadelphia.
446. Rushton, S. P. and Mautner, A. (1955). The deterministic model of a simple epidemic for more than one community. Biometrika, 42:126-132.
447. Rvachev, L. A. and Longini, Jr., I. M. (1985). A mathematical model for the global spread of influenza. Mathematical Biosciences, 75(1):1-22.
448. Salt, J. S., Barnett, P. V., Dani, P., and Williams, L. (1998). Emergency vaccination of pigs against foot-and-mouth disease: Protection against disease and reduction in contact transmission. Vaccine, 16(7):746-754.
449. Sanson, R. L., Morris, R. S., and Stern, M. W. (1999). EpiMAN-FMD: A decision support system for managing epidemics of vesicular disease. Revue Scientifique et Technique de L'Office International des Épizooties, 18(3):593-605.
450. Sartwell, P. E. (1950). The distribution of incubation periods of infectious disease. American Journal of Hygiene, 51:310-318.
451. Sartwell, P. E. (1966). The incubation period and dynamics of infectious disease. American Journal of Epidemiology, 83:204-216.
452. Sato, K., Matsuda, H., and Sasaki, A. (1994). Pathogen invasion and host extinction in lattice structured populations. Journal of Mathematical Biology, 32(3):251-268.
453. Sattenspiel, L. (1987a). Epidemics in nonrandomly mixing populations: A simulation. American Journal of Physical Anthropology, 73(2):251-265.
454. Sattenspiel, L. (1987b). Population structure and the spread of disease. Human Biology, 59(3):411-438.
455. Sattenspiel, L. and Dietz, K. (1995). A structured epidemic model incorporating geographic mobility among regions. Mathematical Biosciences, 128(1-2):71-91.
456. Sattenspiel, L. and Herring, D. A. (1998). Structured epidemic models and the spread of influenza in the central Canadian subarctic. Human Biology, 70(1):91-115.
457. Sattenspiel, L. and Herring, D. A. (2003). Simulating the effect of quarantine on the spread of the 1918-19 flu in central Canada. Bulletin of Mathematical Biology, 65(1):1-26.
458. Sattenspiel, L., Mobarry, A., and Herring, D. A. (2000). Modeling the influence of settlement structure on the spread of influenza among communities. American Journal of Human Biology, 12(6):736-748.
459. Sattenspiel, L. and Simon, C. (1988). The spread and persistence of infectious diseases in structured populations. Mathematical Biosciences, 90:341-366.
460. Schaffer, W. M. (1985). Can nonlinear dynamics elucidate mechanisms in ecology and epidemiology? IMA Journal of Mathematics Applied in Medicine and Biology, 2(4):221-252.
461. Schaffer, W. M. and Kot, M. (1985). Nearly one dimensional dynamics in an epidemic. Journal of Theoretical Biology, 112:403-427.
462. Schenzle, D. (1984). An age-structured model of pre- and postvaccination measles transmission. IMA Journal of Mathematics Applied in Medicine and Biology, 1(2):169-191.
463. Schenzle, D. and Dietz, K. (1987). Critical population sizes for endemic virus transmission. In Fricke, W. and Hinz, E., editors, Räumliche Persistenz und Diffusion von Krankheiten, pages 31-42. Heidelberger Geographische Arbeiten, Heidelberg.
464. Schneeberger, A., Mercer, C. H., Gregson, S. A. J., Ferguson, N. M., Nyamukapa, C. A., Anderson, R. M., Johnson, A. M., and Garnett, G. P. (2004). Scale-free networks and sexually transmitted diseases - a description of observed patterns of sexual contacts in Britain and Zimbabwe. Sexually Transmitted Diseases, 31(6):380-387.
465. Scholtissek, C. (1994). Source for influenza pandemics. European Journal of Epidemiology, 10(4):455-458.
466. Schrag, S. J., Brooks, J. T., Van Beneden, C., Parashar, U. D., Griffin, P. M., Anderson, L. J., Bellini, W. J., Benson, R. F., Erdman, D. D., Klimov, A., Ksiazek, T. G., Peret, T. C. T., Talkington, D. F., Thacker, W. L., Tondella, M. L., Sampson, J. S., Hightower, A. W., Nordenberg, D. F., Plikaytis, B. D., Khan, A. S., Rosenstein, N. E., Treadwell, T. A., Whitney, C. G., Fiore, A. E., Durant, T. M., Perz, J. F., Wasley, A., Feikin, D., Herndon, J. L., Bower, W. A., Kilbourn, B. W., Levy, D. A., Coronado, V. G., Buffington, J., Dykewicz, C. A., Khabbaz, R. F., and Chamberland, M. E. (2004). SARS surveillance during emergency public health response, United States, March-July 2003. Emerging Infectious Diseases, 10(2):185-194.
467. Schwartz, I. B. (1992). Small amplitude, long period outbreaks in seasonally driven epidemics. Journal of Mathematical Biology, 30(5):473-491.
468. Simonsen, L., Clarke, M. J., Schonberger, L. B., Arden, N. H., Cox, N. J., and Fukuda, K. (1998). Pandemic versus epidemic influenza mortality: A pattern of changing age distribution. Journal of Infectious Diseases, 178(1):53-60.
469. Smallman-Raynor, M. R. and Cliff, A. D. (1991). Civil war and the spread of AIDS in Central Africa. Epidemiology and Infection, 107(1):69-80.
470. Smallman-Raynor, M. R. and Cliff, A. D. (1998a). Deciphering Global Epidemics: Analytical Approaches to the Disease Records of World Cities, 1888-1912. Cambridge University Press, Cambridge.
471. Smallman-Raynor, M. R. and Cliff, A. D. (1998b). The Philippines insurrection and the 1902-4 cholera epidemic, part I: Epidemiological diffusion processes in war. Journal of Historical Geography, 24(1):69-89.
472. Smallman-Raynor, M. R. and Cliff, A. D. (1998c). The Philippines insurrection and the 1902-4 cholera epidemic, part II: Diffusion patterns in war and peace. Journal of Historical Geography, 24(2):188-210.
473. Smallman-Raynor, M. R. and Cliff, A. D. (2001a). Epidemic diffusion processes in a system of US military camps: Transfer diffusion and the spread of typhoid fever in the Spanish-American War, 1898. Annals of the Association of American Geographers, 91(1):71-91.
474. Smallman-Raynor, M. R. and Cliff, A. D. (2001b). Epidemiological spaces: The use of multidimensional scaling to identify cholera diffusion processes in wake of the Philippines insurrection, 1899-1902. Transactions of the Institute of British Geographers, 26(3):288-305.
475. Smith, D. L., Lucey, B., Waller, L. A., Childs, J. E., and Real, L. A. (2002). Predicting the spatial dynamics of rabies epidemics on heterogeneous landscapes. Proceedings of the National Academy of Sciences of the United States of America, 99(6):3668-3672.
476. Smith, P. and Thomas, R. (2001). Epidemic modelling of HIV/AIDS transfers between eastern and western Europe. GeoJournal, 53(4):373-383.
477. Soper, M. A. (1929). The interpretation of periodicity in disease prevalence. Journal of the Royal Statistical Society, Series A, Statistics in Society, 92:34-61.
478. Sorensen, J. H., Mackay, D. K. J., Jensen, C. O., and Donaldson, A. I. (2000). An integrated model to predict the atmospheric spread of foot-and-mouth disease virus. Epidemiology and Infection, 124(3):577-590.
479. Spencer, F. (1967). Port health services through the ages. Royal Institute of Public Health and Hygiene Journal, 30:88-91.
480. Spicer, C. C. (1979). The mathematical modelling of influenza epidemics. British Medical Bulletin, 35(1):23-28.
481. Stauffer, D. and Aharony, A. (1992). Introduction to Percolation Theory. Taylor and Francis, London, 2nd edition.
482. Stone, L., Olinky, R., and Huppert, A. (2007). Seasonal dynamics of recurrent epidemics. Nature, 446:533-536.
483. Taneyhill, D. E., Dunn, A. M., and Hatcher, M. J. (1999). The Galton-Watson branching process as a quantitative tool in parasitology. Parasitology Today, 15(4):159-165.
484. Taubenberger, J. K. and Morens, D. M. (2006a). 1918 influenza: The mother of all pandemics. Emerging Infectious Diseases, 12(1):15-22.
485. Taubenberger, J. K. and Morens, D. M. (2006b). Influenza revisited. Emerging Infectious Diseases, 12(1):1-2.
486. Taubenberger, J. K., Reid, A. H., and Fanning, T. G. (2000). The 1918 influenza virus: A killer comes into view. Virology, 274:241245.
487. Thomas, R. W. (2001). Estimated population mixing by country and risk cohort for the HIV/AIDS epidemic in Western Europe. Journal of Geographic Systems, 3:283-301.
488. Thompson, D., Muriel, P., Russell, D., Osborne, P., Bromley, A., Rowland, M., Creigh-tyte, S., and Brown, C. (2002). Economic costs of the foot and mouth disease outbreak in the United Kingdom in 2001. Revue Scientifique et Technique de L'Office International des Épizooties, 21:675-687.
489. Thompson, W. W., Shay, D. K., Weintraub, E., Brammer, L., Cox, N. J., Anderson, L. J., and Fukuda, K. (2003). Mortality associated with influenza and respiratory syncytial virus in the United States. Journal of the American Medical Association, 289(2):179-186.
490. Thrusfield, M., Mansley, L., Dunlop, P., Taylor, J., and Pawson, A. (2005). The foot-and-mouth disease epidemic in Dumfries and Galloway, 2001, 2: Serosurveillance, and efficiency and effectiveness of control procedures after the national ban on animal movements. Veterinary Record, 156:269-278.
491. Tildesley, M. J., Savill, N. J., Shaw, D. J., Deardon, R., Brooks, S. P., Woolhouse, M. E. J., Grenfell, B. T., and Keeling, M. J. (2006). Optimal reactive vaccination strategy for a foot-and-mouth outbreak in the UK. Nature, 440:83-86.
492. Tildesley, M. J., Savill, N. J., Shaw, D. J., Deardon, R., Brooks, S. P., Woolhouse, M. E. J., Grenfell, B. T., and Keeling, M. J. (2007). Vaccination strategies for foot-and-mouth disease (reply). Nature, 445:E12-E13.
493. Travers, J. and Milgram, S. (1969). An experimental study of the small world problem. Sociometry, 32:425-443.
494. Tsang, T. and Lam, T. H. (2003). SARS: Public health measures in Hong Kong. Respirology, 8:S46-S48.
495. Tuckel, P., Sassler, S., Maisel, R., and Leykam, A. (2006). The diffusion of the influenza pandemic of 1918 in Hartford, Connecticut. Social Science History, 30(2):167-196.
496. Turelli, M. (1977). Random environments and stochastic calculus. Theoretical Population Biology, 12(2):140-178.
497. Turing, A. M. (1952). The chemical basis of morphogenesis. Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences, 237:37-72.
498. van den Bosch, F., Metz, J. A. J., and Diekmann, O. (1990). The velocity of spatial population expansion. Journal of Mathematical Biology, 28:529-565.
499. van den Driessche, P. and Watmough, J. (2002). Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Mathematical Biosciences, 180:29-48.
500. Varia, M., Wilson, S., Sarwal, S., McGeer, A., Gournis, E., Galanis, E., Henry, B., and for the Hospital Outbreak Investigation Team. (2003). Investigation of a nosocomial outbreak of severe acute respiratory syndrome (SARS) in Toronto, Canada. Canadian Medical Association Journal, 169(4):285-292.
501. Viboud, C., Bjørnstad, O. N., Smith, D. L., Simonsen, L., Miller, M. A., and Grenfell, B. T. (2006). Synchrony, waves, and spatial hierarchies in the spread of influenza. Science, 312:447-451.
502. Waller, L. A. and Jacquez, G. M. (1995). Disease models implicit in statistical tests of disease clustering. Epidemiology, 6(6):584-590.
503. Waller, L. A. and Lawson, A. B. (1995). The power of focused tests to detect disease clustering. Statistics in Medicine, 14(21-22):2291-2308.
504. Wallinga, J. and Teunis, P. (2004). Different epidemic curves for severe acute respiratory syndrome reveal similar impacts of control measures. American Journal of Epidemiology, 160(6):509-516.
505. Walter, S. D. (2000). Disease mapping: A historical perspective. In Elliott, P., Wakefield, J., Best, N., and Briggs, D., editors, Spatial Epidemiology: Methods and Applications, pages 223-239. Oxford University Press, Oxford.
506. Warren, C. P., Sander, L. M., and Sokolov, I. M. (2002). Geography in a scale-free network model. Physical Review E, 66(5 Pt 2):056105.
507. Wasserman, S. and Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge.
508. Watts, D. J., Muhamad, R., Medina, D. C., and Dodds, P. S. (2005). Multiscale, resurgent epidemics in a hierarchical metapopulation model. Proceedings of the National Academy of Sciences of the United States of America, 102:11157-11162.
509. Watts, D. J. and Strogatz, S. H. (1998). Collective dynamics of'small-world' networks. Nature, 393(6684):440-442.
510. Wawer, M. J., Podhisita, C., Kanungsukkasem, U., Pramualratana, A., and McNamara, R. (1996). Origins and working conditions of female sex workers in urban Thailand: Consequences of social context for HIV transmission. Social Science and Medicine, 42(3):453-462.
511. Webb, G. F., Blaser, M. J., Zhu, H., Ardal, S., and Wu, J. (2004). Critical role of nosocomial transmission in the Toronto SARS outbreak. Mathematical Biosciences and Engineering, 1(1):1-13.
512. Whittle, P. (1955). The outcome of a stochastic epidemic - a note on Bailey's paper. Biometrika, 42:116-122.
513. Whittle, P. (1957). On the use of the normal approximation in the treatment of stochastic processes. Journal of the Royal Statistical Society, Series B, Statistical Methodology, 19:268-281.
514. Williams, J. S. and Rees, P. H. (1994). A simulation of the transmission of HIV and AIDS in regional populations within the United Kingdom. Transactions of the Institute of British Geographers, 19(3):311-330.
515. Wilson, E. B. and Burke, M. H. (1942). The epidemic curve. Proceedings of the National Academy of Sciences of the United States of America, 28:361-367.
516. Wilson, E. B. and Worcester, J. (1945a). Damping of epidemic waves. Proceedings of the National Academy of Sciences of the United States of America, 31:294-298.
517. Wilson, E. B. and Worcester, J. (1945b). The spread of an epidemic. Proceedings of the National Academy of Sciences of the United States of America, 31:327-333.
518. Wingfield, A., Miller, H., and Honhold, N. (2006). FMD control strategies. Veterinary Record, 158(20):706-707.
519. Woolhouse, M. and Donaldson, A. (2001). Managing foot-and-mouth. Nature, 410(6828):515-516.
520. Woolhouse, M. E. (2003). Foot-and-mouth disease in the UK: What should we do next time? Journal of Applied Microbiology, 94(Suppl):126S-130S.
521. Woolhouse, M. E. J., Etard, J.-F., Dietz, K., Ndhlovu, P. D., and Chandiwana, S. K. (1998). Heterogeneities in schistosome transmission dynamics and control. Parasitology, 117:475-482.
522. Xia, Y. C., Bjørnstad, O. N., and Grenfell, B. T. (2004). Measles metapopulation dynamics: A gravity model for epidemiological coupling and dynamics. American Naturalist, 164(2):267-281.
523. Yorke, J. A., Hethcote, H. W., and Nold, A. (1978). Dynamics and control of the transmission of gonorrhea. Sexually Transmitted Diseases, 5(2):51-56.