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(2020) 369 science SARS-CoV-2, to immunity herd on heterogeneity population of influence the reveals model mathematical al., et t britton transmissionreading: COVID-19 in children of role controlexample: outbreak for modelingimplications mixingage-specific of model heterogeneitySEIR population of mixingconcept 355-359. heterogeneous (2005) 438 nature emergence, disease on variation individual of effect the and superspreading al., et jo lloyd-smith reading: factories   meat and churches in events superspreading controlexample: outbreak for COVID-19implications of events ksuperspreading parameter heterogeneitydispersion of superspreadingconcept topics            additional 100921. potentially (2020) 40 lett. mech extr learned. lessons - COVID-19 of modeling data-driven e. kuhl reading: reopening safe for critical is quarantinetesting than effective more be can reopening modelsselective for suited always not but data, of ton a generates COVID-19 unreported  and asymptomatic are cases COVID-19 weeksmost two of delay a with mobility to correlated is effectivereproduction but drastic is mobility itconstraining model and curve the flatten can timewe long a for us with be will COVID-19 vaccination, without coronaviruses previous as contagious as is COVID-19 uncontrolled if exponentially spreads is learnedCOVID-19 lessons                         2541-2550.    (2006) 273 b soc royal proc epidemiology, disease infectious seasonal c, fraser nc, grassly reading:                    COVID-19 of seasonality changesexample: behavioral tourism, workers, seasonal mobility, of diseaseseasonality infectious seasonal of number reproduction modelbasic SEIR seasonalityseasonal of waveconcept second the 1053-1060. VI.3. 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