Introducing the Outbreak Threshold in Epidemiology
When a pathogen is rare in a host population, there is a chance that it will die out because of stochastic effects instead of causing a major epidemic. Yet no criteria exist to determine when the pathogen increases to a risky level, from which it has a large chance of dying out, to when a major outbreak is almost certain. We introduce such an outbreak threshold (T0), and find that for large and homogeneous host populations, in which the pathogen has a reproductive ratio R0, on the order of 1/Log(R0) infected individuals are needed to prevent stochastic fade-out during the early stages of an epidemic. We also show how this threshold scales with higher heterogeneity and R0 in the host population. These results have implications for controlling emerging and re-emerging pathogens.
Vyšlo v časopise:
Introducing the Outbreak Threshold in Epidemiology. PLoS Pathog 9(6): e32767. doi:10.1371/journal.ppat.1003277
Kategorie:
Opinion
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.ppat.1003277
Souhrn
When a pathogen is rare in a host population, there is a chance that it will die out because of stochastic effects instead of causing a major epidemic. Yet no criteria exist to determine when the pathogen increases to a risky level, from which it has a large chance of dying out, to when a major outbreak is almost certain. We introduce such an outbreak threshold (T0), and find that for large and homogeneous host populations, in which the pathogen has a reproductive ratio R0, on the order of 1/Log(R0) infected individuals are needed to prevent stochastic fade-out during the early stages of an epidemic. We also show how this threshold scales with higher heterogeneity and R0 in the host population. These results have implications for controlling emerging and re-emerging pathogens.
Zdroje
1. MorensDM, FolkersGK, FauciAS (2004) The challenge of emerging and re-emerging infectious diseases. Nature 430: 242–249.
2. WoolhouseM, ScottF, HudsonZ, HoweyR, Chase-ToppingM (2012) Human viruses: discovery and emergence. Philos Trans R Soc Lond B Biol Sci 367: 2864–2871.
3. FargetteD, KonateG, FauquetC, MullerE, PeterschmittM, et al. (2006) Molecular ecology and emergence of tropical plant viruses. Annu Rev Phytopathol 44: 235–260.
4. Anderson RM, May RM (1991) Infectious diseases of humans. Dynamics and control. Oxford: Oxford University Press. 757 p.
5. Diekmann O, Heesterbeek JAP (2000) Mathematical epidemiology of infectious diseases: model building, analysis and interpretation. Chichester: John Wiley. 303 p.
6. Allen L (2008) An introduction to stochastic epidemic models. In: Brauer F, van den Driessche P, Wu J, editors. Mathematical epidemiology. Berlin/Heidelberg: Springer. pp. 81–130.
7. BartlettMS (1960) The critical community size for measles in the United States. J R Stat Soc Ser A Stat Soc 123: 37–44.
8. Keeling MJ, Rohani P (2007) Modelling infectious diseases in humans and animals. Princeton: Princeton University Press. 408 p.
9. AntiaR, RegoesRR, KoellaJC, BergstromCT (2003) The role of evolution in the emergence of infectious diseases. Nature 426: 658–661.
10. YatesA, AntiaR, RegoesRR (2006) How do pathogen evolution and host heterogeneity interact in disease emergence? Proc Biol Sci 273: 3075–3083.
11. Lloyd-SmithJO, SchreiberSJ, KoppPE, GetzWM (2005) Superspreading and the effect of individual variation on disease emergence. Nature 438: 355–359.
12. KubiakRJ, ArinaminpathyN, McLeanAR (2010) Insights into the evolution and emergence of a novel infectious disease. PLoS Comput Biol 6: e1000947 doi:10.1371/journal.pcbi.1000947
13. FergusonNM, FraserC, DonnellyCA, GhaniAC, AndersonRM (2004) Public health risk from the avian H5N1 influenza epidemic. Science 304: 968–969.
14. KaplanNL, HudsonRR, LangleyCH (1989) The “hitchhiking effect” revisited. Genetics 123: 887–889.
15. BartonNH (2000) Genetic hitchhiking. Philos Trans R Soc Lond B Biol Sci 355: 1553–1562.
16. DesaiMM, FisherDS (2007) Beneficial mutation-selection balance and the effect of linkage on positive selection. Genetics 176: 1759–1798.
17. GalvaniAP, MayRM (2005) Epidemiology: dimensions of superspreading. Nature 438: 293–295.
18. AlexanderHK, DayT (2010) Risk factors for the evolutionary emergence of pathogens. J R Soc Interface 7: 1455–1474.
19. Wolfram Research, Inc. (2010) Mathematica Edition: Version 8.0. Champaign, Illinois: Wolfram Research, Inc.
20. Shooter RA (1980) Report of the investigation into the cause of the 1978 Birmingham smallpox occurrence. London: HM Stationery Office. 231 p.
21. LeoYS, ChenM, HengBH, LeeCC, PatonN, et al. (2003) Severe acute respiratory syndrome — Singapore, 2003. MMWR Morb Mortal Wkly Rep 52: 405–411.
22. GillespieDT (1977) Exact stochastic simulation of coupled chemical reactions. J Phys Chem 81: 2340–2361.
Štítky
Hygiena a epidemiológia Infekčné lekárstvo LaboratóriumČlánok vyšiel v časopise
PLOS Pathogens
2013 Číslo 6
- Očkování proti virové hemoragické horečce Ebola experimentální vakcínou rVSVDG-ZEBOV-GP
- Parazitičtí červi v terapii Crohnovy choroby a dalších zánětlivých autoimunitních onemocnění
- Koronavirus hýbe světem: Víte jak se chránit a jak postupovat v případě podezření?
Najčítanejšie v tomto čísle
- Asthma and the Diversity of Fungal Spores in Air
- Streptolysin O and its Co-Toxin NAD-glycohydrolase Protect Group A from Xenophagic Killing
- A Type IV Pilus Mediates DNA Binding during Natural Transformation in
- Cryotomography of Budding Influenza A Virus Reveals Filaments with Diverse Morphologies that Mostly Do Not Bear a Genome at Their Distal End