Noise is not error: Detecting parametric heterogeneity between epidemiologic time series

Frontiers in Microbiology

Volumn 9, Issue JUL, 2018, Pages

  Romero Severson, Ethan O ^a   Ribeiro, Ruy M ^a,b   Castro, Mario ^c,d  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

^b INSTITUTO DE MEDICINA MOLECULAR   (Portugal)

^c UNIVERSIDAD PONTIFICIA COMILLAS   (Spain)

^d UNIVERSITY OF LEEDS   (United Kingdom)

Author keywords

Deterministic; Epidemiology; Fixed effects; Panel data; Random effects; Stochastic

Indexed keywords

ARTICLE; DEATH; EBOLA HEMORRHAGIC FEVER; EBOLAVIRUS; ERROR; GENETIC HETEROGENEITY; HUMAN; MATHEMATICAL MODEL; MOTIVATION; NOISE; TIME SERIES ANALYSIS;

EID: 85049862027     PISSN: None     EISSN: 1664302X     Source Type: Journal    
DOI: 10.3389/fmicb.2018.01529     Document Type: Article

References (22)

1. Allen, L. J. (2010). An Introduction to Stochastic Processes With Applications to Biology. CRC Press
2. Althaus, C. L. (2014). Estimating the reproduction number of ebola virus (ebov) during the 2014 outbreak in west africa. PLoS Curr. 6:ecurrents.outbreaks.91afb5e0f279e7f29e7056095255b288. doi: 10.1371/currents.outbreaks.91afb5e0f279e7f29e7056095255b288
3. Bressloff, P. C., and Newby, J. M. (2013). Stochastic models of intracellular transport. Rev. Mod. Phys. 85:135. doi: 10.1103/RevModPhys.85.135
4. Chowell, G., Hengartner, N. W., Castillo-Chavez, C., Fenimore, P. W., and Hyman, J. M. (2004). The basic reproductive number of ebola and the effects of public health measures: the cases of congo and uganda. J. Theor. Biol. 229, 119-126. doi: 10.1016/j.jtbi.2004.03.006
5. Dietz, K. (1993). The estimation of the basic reproduction number for infectious diseases. Stat. Methods Med. Res. 2, 23-41
6. Ganusov, V. V. (2016). Strong inference in mathematical modeling: a method for robust science in the twenty-first century. Front. Microbiol. 7:1131. doi: 10.3389/fmicb.2016.01131
7. Gelman, A., and Hill, J. (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. New York, NY: Cambridge University Press
8. Hartemink, N., Vanwambeke, S. O., Heesterbeek, H., Rogers, D., Morley, D., Pesson, B., et al. (2011). Integrated mapping of establishment risk for emerging vector-borne infections: a case study of canine leishmaniasis in southwest france. PLoS ONE 6:e20817. doi: 10.1371/journal.pone.0020817
9. Heffernan, J. M., Smith, R. J., and Wahl, L. M. (2005). Perspectives on the basic reproductive ratio. J. R. Soc. Interface 2, 281-293. doi: 10.1098/rsif.2005.0042
10. Heesterbeek, J. (2000). Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation, Vol. 5. Sussex: John Wiley & Sons
11. Krauer, F., Gsteiger, S., Low, N., Hansen, C. H., and Althaus, C. L. (2016). Heterogeneity in district-level transmission of ebola virus disease during the 2013-2015 epidemic in west africa. PLoS Negl. Trop. Dis. 10:e0004867. doi: 10.1371/journal.pntd.0004867
12. Karlin, S. (2014). A first Course in Stochastic Processes. New York, NY: Academic press
13. King, A. A., Nguyen, D., and Ionides, E. L. (2016). Statistical inference for partially observed markov processes via the r package pomp. J. Stat. Softw. 69, 1-43. doi: 10.18637/jss.v069.i12
14. King, A. A., Domenech de Cellès M, Magpantay, F. M., and Rohani, P. (2015). Avoidable errors in the modelling of outbreaks of emerging pathogens, with special reference to ebola. Proc. R. Soc. B. 282:20150347. doi: 10.1098/rspb.2015.0347
15. Kucharski, A. J., Camacho, A., Flasche, S., Glover, R. E., Edmunds, W. J., and Funk, S. (2015). Measuring the impact of ebola control measures in sierra leone. Proc. Natl. Acad. Sci. U.S.A. 112, 14366-14371. doi: 10.1073/pnas.1508814112
16. Molina-París, C., and Lythe, G. (2011). Mathematical Models and Immune Cell Biology. New York, NY: Springer Science & Business Media
17. Perelson, A. S., Neumann, A. U., Markowitz, M., Leonard, J. M., and Ho, D. D. (1996). Hiv-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time. Science 271, 1582
18. Roberts, M., Andreasen, V., Lloyd, A., and Pellis, L. (2015). Nine challenges for deterministic epidemic models. Epidemics 10 49-53. doi: 10.1016/j.epidem.2014.09.006
19. Ribeiro, R. M., Qin, L., Chavez, L. L., Li, D., Self, S. G., and Perelson, A. S. (2010). Estimation of the initial viral growth rate and basic reproductive number during acute hiv-1 infection. J. Virol. 84, 6096-6102. doi: 10.1128/JVI.00127-10
20. Romero-Severson, E. O., Volz, E., Koopman, J. S., Leitner, T., and Ionides, E. L. (2015). Dynamic Variation in Sexual Contact Rates in a Cohort of HIV-Negative Gay Men. Am. J. Epidemiol. 182, 255-262. doi: 10.1093/aje/kwv044
21. Romero-Severson, E., Skar, H., Bulla, I., Albert, J., and Leitner, T. (2014). Timing and order of transmission events is not directly reflected in a pathogen phylogeny. Mol. Biol. Evol. 31, 2472-2482. doi: 10.1093/molbev/msu179
22. Süel, G. M., Garcia-Ojalvo, J., Liberman, L. M., and Elowitz, M. B. (2006). An excitable gene regulatory circuit induces transient cellular differentiation. Nature 440, 545-550. doi: 10.1038/nature04588