Difference between revisions of "Epidemics"
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* workplaces not explicitly included | * workplaces not explicitly included | ||
| + | * transmission model: probability of the infection of the individual ''i'', <math>p_i=1-\exp^{-\lambda_i(t) \Delta T}</math>, where <math>\lambda_i</math> is the instantaneous infection risk of the individual ''i''. | ||
* transmission rate in a household <math>= \beta^{a}_{hous} f(t)/n</math>, where ''a'' - age (''A''dult(>=18) or ''C''hild), ''f(t)'' - relative infectiousness according to time ''t'' since infection, ''n'' - the size of the household. | * transmission rate in a household <math>= \beta^{a}_{hous} f(t)/n</math>, where ''a'' - age (''A''dult(>=18) or ''C''hild), ''f(t)'' - relative infectiousness according to time ''t'' since infection, ''n'' - the size of the household. | ||
* transmission rates for: within household infection (A,C), within school, within community (A->A,C->C,A<->C). Hence, the overall risk of infection includes: the household risk, the within school risk, the community risk | * transmission rates for: within household infection (A,C), within school, within community (A->A,C->C,A<->C). Hence, the overall risk of infection includes: the household risk, the within school risk, the community risk | ||
* time step = 6h | * time step = 6h | ||
| − | * annual variations of influenza infections modeled via: the strength of transmission during the year and the relative contribution of children to transmission during the year | + | * annual variations of influenza infections modeled via: the strength of transmission during the year and the relative contribution of children to transmission during the year (included in <math>\lambda_{i,y}(t)</math>), where ''y'' - year |
=== Ferguson's, in UK and USA<ref name="ferguson2006">FERGUSON N M, Cummings D A T, Fraser C, Cajka J C, Cooley P C, and Burke D S, ''Strategies for mitigating an influenza pandemic'', Nature, 442 (2006), pp. 448-452</ref> === | === Ferguson's, in UK and USA<ref name="ferguson2006">FERGUSON N M, Cummings D A T, Fraser C, Cajka J C, Cooley P C, and Burke D S, ''Strategies for mitigating an influenza pandemic'', Nature, 442 (2006), pp. 448-452</ref> === | ||
* households, schools, workplaces included in the model | * households, schools, workplaces included in the model | ||
| − | * commuting data also included (the average distances | + | * commuting data also included (the average distances traveled from hh to wp); the UK distance distribution more-less like power law, that of USA - surprisingly a bit different |
* air travel data included | * air travel data included | ||
| − | * transmission model: probability of the infection of the individual ''i'', <math>p_i=1-\exp^{-\lambda_i \Delta T}</math>, where | + | * time step = 6h |
| + | * transmission model: probability of the infection of the individual ''i'', <math>p_i=1-\exp^{-\lambda_i(t) \Delta T}</math>, where <math>\lambda_i</math> is the instantaneous infection risk of the individual ''i''. | ||
Revision as of 12:21, 4 November 2008
| Virtual society | Virus spread | Literature | Version 
|
|---|---|---|---|
| Polish virtual society epidemics model | |||
| Guinea pigs epidemics model | |||
| Virus genetic evolution epidemics model | |||
Pandemics history info on the Internet
Past Pandemic Timeline in Nature
H5N1 outbreaks in birds and other animals in Nature
Human cases of avian flu in Nature
Review of epidemics models
Ferguson's, in France[1]
Quite large amount of data on epidemics in France from Sentinel and Centre National de Reference de la Grippe, region Sud, Laboratoire de Virology.
- workplaces not explicitly included
- transmission model: probability of the infection of the individual i,
, where 
is the instantaneous infection risk of the individual i. - transmission rate in a household
, where a - age (Adult(>=18) or Child), f(t) - relative infectiousness according to time t since infection, n - the size of the household. - transmission rates for: within household infection (A,C), within school, within community (A->A,C->C,A<->C). Hence, the overall risk of infection includes: the household risk, the within school risk, the community risk
- time step = 6h
- annual variations of influenza infections modeled via: the strength of transmission during the year and the relative contribution of children to transmission during the year (included in
), where y - year
Ferguson's, in UK and USA[2]
- households, schools, workplaces included in the model
- commuting data also included (the average distances traveled from hh to wp); the UK distance distribution more-less like power law, that of USA - surprisingly a bit different
- air travel data included
- time step = 6h
- transmission model: probability of the infection of the individual i, , where is the instantaneous infection risk of the individual i.
Ferguson's in Thailand[3]
Ferguson's in ...[4]
Ferguson's in UK[5]
Dunham's general model - MASON[6]
Germann's, in USA[7]
Stroud's, in southern California, USA[8]
References
- ↑ CAUCHEMEZ S, Valleron A J, Boelle P Y, Flahault A, and Ferguson N M, Estimating the impact of school closure on influenza transmission from Sentinel data, Nature, 452 (2008), pp.750-754
- ↑ FERGUSON N M, Cummings D A T, Fraser C, Cajka J C, Cooley P C, and Burke D S, Strategies for mitigating an influenza pandemic, Nature, 442 (2006), pp. 448-452
- ↑ FERGUSON N M, Cummings D, Cauchemez S, Fraser C, Riley S, Meeyai A, Iamsirithaworn S, and Burke D, Strategies for containing an emerging influenza pandemic in Southeast Asia, Nature, 437 (2005), pp. 209-214
- ↑ FERGUSON N M, Galvani A P, and Bush R M, Ecological and immunological determinants of influenza evolution, Nature, 422 (2003), pp. 428-433
- ↑ FERGUSON N M, Donnelly C, and Anderson R A, Transmission intensity and impact of control policies on the foot and mouth epidemic in Great Britain, Nature, 413 (2001), pp. 542-548
- ↑ DUNHAM J B, An Agent-Based Spatially Explicit Epidemiological Model in MASON Journal of Artificial Societies and Social Simulation,2005, 9(1)3
- ↑ GERMANN T C, Kadau K, Longini I, and Macken C, Mitigation strategies for pandemic influenza in the United States, Proc. Nat. Acad. Sci., 103 (2006), pp.5935-5940
- ↑ STROUD P, Del Valle S, Sydoriak S, Riese J and Mniszewski S (2007). Spatial Dynamics of Pandemic Influenza in a Massive Artificial Society,Journal of Artificial Societies and Social Simulation 10(4)9
