/BioComplexity

Notes and Opinion on Complex Systems in Biology

Apache License 2.0Apache-2.0

EMOD compile from source

Visual Studio 2012.5

Simulations in Biocomplexity

loss of water habitat: evaporation runoff everything else

Calibration

  • HBR human biting rate, EIR biting rate that carries risk of infection
  • HBR is fit first, then EIR

06 Sep 2015

29 Sep 2015

24 Sep 2015

  • 5 500 000 000 what is the Temporary Rainfall Parameter; scales the EIR up or down. And does something else
  • change Parasite Params from 0.02 ,0.1, and the smear sensitivity to 0.01 Simulation|Parameter | Setting | ----------|----------|---------| Base0 | | |
  • | New Diagnostic Detection | 0.02
  • | Parasite Smear Sensitivity | 0.02
  • | x_Temporary_Larval_Habitat | 1

Note: time steps between repetitions ... what are the units ? And what is the Delta t?

22 Sep 2015

Simulations

  • simulating the productivity of the breeding sites
  • Reviews of Vecnet simulations
  • Bugs:
  • Future fixes:
    • sweep

15 Sept 2015

Proposal

  • Define the system

    • Define the system elements and the relationships (interactions)
    • Identify the drivers and inputs
    • Which elements are knowable and well measured
  • Abstract and Simplify

    • What do we want to estimate or predict
  • Design an operational model of the system

    • what are all the dependent and independent variables

10 Sept. 2015

  • We start with 3 locations

A Summary of Complex Systems, Emergence, and Self-Organization

Emergence is a global property of a complex system exhibited as a function of self-organization that occurs at the local level. Emergent properties of the system can often be categorized as bad (unpredictable or uncontrollable) or good (adaptable, flexible, or robust). Self-organization is often described as a property that ‘spontaneously’ may occur, but I believe that self-organization (is another emergent property of a complex system) at the local level occurs as a function of the environment and doesn’t simply occur as a function of time. The complex interactions between all agents at the microscopic (or local) scale or level react and evolve to the environment leading to a self-organization that is in synchrony with the system as whole.

08 Sept. 2015

  • Feedback: Thursday

    • Eckhoff paper 1st 6 pages, until about the adult population; prepare to explain it. (2011)
    • Summarize Complex Systems / Emergence / Self-organization
  • The Model: EMOD

Week 1

References

Introduction to the Modeling and Analysis of Complex Systems

Entomological Inoculation Rate (EIR)

Per year the flow of parasites from mosq to people

parasites

  • human parasites

EMOD Universe - IS Arc Sec No internal space

Notes

  • 40 or so diff. vectors pass on disease (agricultural water management practices)
  • vector model is specific
  • 2 species contribute to
  • Common measures (EIR) # of times per year that a person ifece
  • Sporozoite Rate (2-4pct. are byting have sporozoite in their salivary glands)

Input parameters

  • Temperature
  • Rain fall
  • Geo-location

Mosquito biology

  • The mosq Has to feed on people
  • Human blood meal choise is an important phenom
  • Mosq has to live long enough to do it's 1st blood meanl
  • The model operates in time steps (1 day).
  • Fem. mosq lay eggs in aquatic habitat
    • Hatch and develop
    • Adults emerge, mote, seek blood, digest blod and make more eggs
    • lay eggs (repeat)
    • Probability (length of the event), but while taking a meal, the propb. of death increases.
  • Other factors, rain, humid. , and temp (daily)
  • Assumes loss of habitat is mainly due to evaporation
  • The events occur faster with high temp

4 + constant Vector Habitats

Factors responding to

  • constant
  • temporary rain fall
  • water vegetation
  • human population
  • brackis_swamp ?

sporozoite

The

agents are defined independently of space.

Curve Prevalence vs EIR

The lower the EIR, the lower the prevalence

Sections of the Text

emergence self organization see figure