Difference between revisions of "Epidemics"

Revision as of 13:22, 5 November 2008

Virtual society	Virus spread	Literature	Version
Polish virtual society epidemics model
Guinea pigs epidemics model
Virus genetic evolution epidemics model

workplaces not explicitly included
transmission model: probability of the infection of the individual i, $p_i=1-\exp^{-\lambda_{i,y}(t) \Delta T}$ , where $\lambda_i$ is the instantaneous infection risk of the individual i.
transmission rate in a household $= \beta^{a}_{hous} f(t)/n$ , 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 $\lambda_{i,y}(t)$ ), where y - year

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, $p_i=1-\exp^{-\lambda_i(t) \Delta T}$ , where $\lambda_i$ is the instantaneous infection risk of the individual i.

households, schools, workplaces included in the model
travel data - not enormous, but some, generalized into probabilities of commuting within district
seasonality not included (available data suggested that climate changes do not influence the infectivity rate)

no seasonal or environmental factors included, no virus evolution effects included
a community of 2000 individuals: age, household size, and employment status distributions match US census data; agents divided into 5 age groups (0-4, 5-18, 9-29, 30-64, 64+ years)
playgroups or daycare centers, schools, workplaces included; also contacts with people from neighborhood, occasional contacts in churches, supermarket, etc, included
transmission model: probability of infection from a single contact, $p = P_{trans}\cdot c$ , where $c$ is the contact probability (dependent on the age of both contacting people), $P_{trans}$ is the probability of transmission; antiviral treatment of the infectious contact person or the vaccination of the given individual diminish the $P_{trans}$ ;

Total probability of the susceptible person to get infected, $P\;=\;1-\prod_{i}^{N_{ic}}(1-p_{i})$ , where the product

↑ 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, 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

@@ Line 55: / Line 55: @@
 * a community of 2000 individuals: age, household size, and employment status distributions match US census data; agents divided into 5 age groups (0-4, 5-18, 9-29, 30-64, 64+ years)
 * playgroups or daycare centers, schools, workplaces included; also contacts with people from neighborhood, occasional contacts in churches, supermarket, etc, included
-* transmission model: contact probability, <math>c_i</math>,
+* transmission model: probability of infection from a single contact, <math>p = P_{trans}\cdot c</math>, where <math>c</math> is the contact probability (dependent on the age of both contacting people), <math>P_{trans}</math> is the probability of transmission; antiviral treatment of the infectious contact person or the vaccination of the given individual diminish the <math>P_{trans}</math>;
+Total probability of the susceptible person to get infected, <math>P\;=\;1-\prod_{i}^{N_{ic}}(1-p_{i})</math> , where the product
+* time step = 12h
 === Stroud's, in southern California, USA<ref name="stroud2007">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</ref> ===