A practical generation-interval-based approach to inferring the strength of epidemics from their speed

Epidemics

Volumn 27, Issue , 2019, Pages 12-18

  Park, Sang Woo ^a   Champredon, David ^a,b   Weitz, Joshua S ^c   Dushoff, Jonathan ^a  

^a MCMASTER UNIVERSITY   (Canada)

^b YORK UNIVERSITY   (Canada)

^c GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Basic reproduction number; Generation interval; Infectious disease modeling

Indexed keywords

ARTICLE; BASIC REPRODUCTION NUMBER; CONTACT EXAMINATION; EBOLA HEMORRHAGIC FEVER; EPIDEMIC; HUMAN; INCIDENCE; MEASLES; POPULATION; PRIORITY JOURNAL; RABIES; TIME;

BASIC REPRODUCTION NUMBER; DISEASE OUTBREAKS; HEMORRHAGIC FEVER, EBOLA; HUMANS; INCIDENCE; MEASLES; RABIES; TIME;

EID: 85061792477     PISSN: 17554365     EISSN: 18780067     Source Type: Journal    
DOI: 10.1016/j.epidem.2018.12.002     Document Type: Article

References (47)

1. Aldis, G.K., Roberts, M.G., An integral equation model for the control of a smallpox outbreak. Math. Biosci. 195 (2005), 1–22.
2. Althaus, C.L., Estimating the reproduction number of Ebola Virus (EBOV) during the 2014 outbreak in West Africa. PLoS Curr., 6, 2014.
3. Anderson, D., Watson, R., On the spread of a disease with gamma distributed latent and infectious periods. Biometrika 67 (1980), 191–198.
4. Anderson, R.M., May, R.M., Directly transmitted infections diseases: control by vaccination. Science 215 (1982), 1053–1060.
5. Anderson, R.M., May, R.M., Infectious Diseases of Humans: Dynamics and Control. 1991, Oxford University Press, Oxford.
6. Aylward, B., et al. Ebola virus disease in West Africa – the first 9 months of the epidemic and forward projections. N. Engl. J. Med. 371 (2014), 1481–1495.
7. Champredon, D., Dushoff, J., Intrinsic and realized generation intervals in infectious-disease transmission. Proc. Biol. Sci. 282 (2015), 2015–2026.
8. Chowell, G., Viboud, C., Hyman, J.M., Simonsen, L., The Western Africa Ebola virus disease epidemic exhibits both global exponential and local polynomial growth rates. PLoS Curr., 7, 2015.
9. Chowell, G., Viboud, C., Simonsen, L., Moghadas, S.M., Characterizing the reproduction number of epidemics with early subexponential growth dynamics. J. R. Soc. Interface, 13, 2016, 20160659.
10. Diekmann, O., Heesterbeek, J.A.P., Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation, Vol. 5. 2000, John Wiley & Sons.
11. Diekmann, O., Heesterbeek, J.A., Metz, J.A., On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations. J. Math. Biol. 28 (1990), 365–382.
12. Eaton, J.W., Hallett, T.B., Why the proportion of transmission during early-stage HIV infection does not predict the long-term impact of treatment on HIV incidence. Proc. Natl. Acad. Sci. U. S. A. 111 (2014), 16202–16207.
13. Ferguson, N.M., et al. Strategies for containing an emerging influenza pandemic in Southeast Asia. Nature, 437, 2005, 209.
14. Hampson, K., Dushoff, J., Cleaveland, S., Haydon, D.T., Kaare, M., Packer, C., Dobson, A., Transmission dynamics and prospects for the elimination of canine rabies. PLoS Biol., 7, 2009, e53.
15. 0 in epidemic theory. Stat. Neerl. 50 (1996), 89–110.
16. Huber, J.H., Johnston, G.L., Greenhouse, B., Smith, D.L., Perkins, T.A., Quantitative, model-based estimates of variability in the generation and serial intervals of Plasmodium falciparum malaria. Malar. J., 15, 2016, 490.
17. Keeling, M.J., Grenfell, B.T., Disease extinction and community size: modeling the persistence of measles. Science 275 (1997), 65–67.
18. King, A.A., Domenech de Celles, M., Magpantay, F.M.G., Rohani, P., Avoidable errors in the modelling of outbreaks of emerging pathogens, with special reference to Ebola. Proc. Biol. Sci., 282, 2015, 20150347.
19. Lessler, J., Reich, N.G., Brookmeyer, R., Perl, T.M., Nelson, K.E., Cummings, D.A.T., Incubation periods of acute respiratory viral infections: a systematic review. Lancet Infect. Dis. 9 (2009), 291–300.
20. Lessler, J., et al. Times to key events in Zika virus infection and implications for blood donation: a systematic review. Bull. World Health Organ. 94 (2016), 841–849.
21. Lloyd, A.L., Realistic distributions of infectious periods in epidemic models: changing patterns of persistence and dynamics. Theor. Popul. Biol. 60 (2001), 59–71.
22. Lotka, A.J., Relation between birth rates and death rates. Science 26 (1907), 21–22.
23. Ma, J., Dushoff, J., Bolker, B.M., Earn, D.J.D., Estimating initial epidemic growth rates. Bull. Math. Biol. 76 (2014), 245–260.
24. McBryde, E.S., et al. Early transmission characteristics of influenza A (H1N1)v in Australia: Victorian state, 16 May–3 June 2009. Euro Surveill., 14, 2009, 19363.
25. McCallum, H., et al. Transmission dynamics of Tasmanian devil facial tumor disease may lead to disease-induced extinction. Ecology 90 (2009), 3379–3392.
26. Mills, C.E., Robins, J.M., Lipsitch, M., Transmissibility of 1918 pandemic influenza. Nature 432 (2004), 904–906.
27. Nishiura, H., Time variations in the generation time of an infectious disease: implications for sampling to appropriately quantify transmission potential. Math. Biosci. Eng., 7, 2010, 2010.
28. Nishiura, H., Castillo-Chavez, C., Safan, M., Chowell, G., Transmission potential of the new influenza A(H1N1) virus and its age-specificity in Japan. Euro Surveill., 14, 2009 2009 Jun 04.
29. Nishiura, H., Chowell, G., Theoretical perspectives on the infectiousness of Ebola virus disease. Theor. Biol. Med. Model., 12, 2015, 1.
30. Powers, K.A., Kretzschmar, M.E., Miller, W.C., Cohen, M.S., Impact of early-stage HIV transmission on treatment as prevention. Proc. Natl. Acad. Sci. U. S. A. 111 (2014), 15867–15868.
31. Pybus, O.G., Charleston, M.A., Gupta, S., Rambaut, A., Holmes, E.C., Harvey, P.H., The epidemic behavior of the hepatitis C virus. Science 292 (2001), 2323–2325.
32. R Core Team, R: A Language and Environment for Statistical Computing. 2018, R Foundation for Statistical Computing, Vienna, Austria url: https://www.R-project.org/.
33. Rivers, C.M., Lofgren, E.T., Marathe, M., Eubank, S., Lewis, B.L., Modeling the impact of interventions on an epidemic of Ebola in Sierra Leone and Liberia. PLoS Curr., 6, 2014 2014 Oct 16.
34. Roberts, M.G., Modelling strategies for minimizing the impact of an imported exotic infection. Proc. Biol. Sci. 271 (2004), 2411–2415.
35. Roberts, M.G., Heesterbeek, J.A.P., Model-consistent estimation of the basic reproduction number from the incidence of an emerging infection. J. Math. Biol., 55, 2007, 803.
36. Roberts, M.G., Nishiura, H., Early estimation of the reproduction number in the presence of imported cases: pandemic influenza H1N1-2009 in New Zealand. PLoS One, 6, 2011, e17835.
37. Simpson, R.E., Infectiousness of communicable diseases in the household (measles, chickenpox, and mumps). Lancet, 1952, 549–554.
38. Svensson, A., A note on generation times in epidemic models. Math. Biosci. 208 (2007), 300–311.
39. Svensson, A., The influence of assumptions on generation time distributions in epidemic models. Math. Biosci. 270 (2015), 81–89.
40. Taylor, B.P., Dushoff, J., Weitz, J.S., Stochasticity and the limits to confidence when estimating R0 of Ebola and other emerging infectious diseases. J. Theor. Biol. 408 (2016), 145–154.
41. Trichereau, J., et al. Estimation of the reproductive number for A (H1N1) pdm09 influenza among the French armed forces, September 2009–March 2010. J. Infect. 64 (2012), 628–630.
42. Tsallis, C., What are the numbers that experiments provide?. Quim. Nova 17 (1994), 468–471.
43. Viboud, C., Simonsen, L., Chowell, G., A generalized-growth model to characterize the early ascending phase of infectious disease outbreaks. Epidemics 15 (2016), 27–37.
44. Wallinga, J., Lipsitch, M., How generation intervals shape the relationship between growth rates and reproductive numbers. Proc. Biol. Sci. 274 (2007), 599–604.
45. Wearing, H.J., Rohani, P., Keeling, M.J., Appropriate models for the management of infectious diseases. PLoS Med., 2, 2005, e174.
46. Weitz, J.S., Dushoff, J., Modeling post-death transmission of Ebola: challenges for inference and opportunities for control. Sci. Rep., 5, 2015, 8751.
47. Yan, P., Separate roles of the latent and infectious periods in shaping the relation between the basic reproduction number and the intrinsic growth rate of infectious disease outbreaks. J. Theor. Biol. 251 (2008), 238–252.