Malaria
  Malaria has distinct
			environmental drivers.  Rainfall defines the
			transmission season by provided breeding sites
			for the mosquitoes that are the vectors of the
			disease, while temperature impacts both the
			vector larva and adult lifecycles.  Many other
			environmental factors play a role, from soil
			type and terrain topography which affect the
			surface hydrology, as well as the land cover
			type.  Socio-economic factors should not be
			neglected.  Interventions can depress
			transmission or eradicate it altogether in a
			region, but population migration can
			reintroduce the disease. Understanding what
			drives malaria transmission in this complex
			web of factors could be aided by accurate
			models of the disease transmission that
			operate over regional scales.
 Malaria has distinct
			environmental drivers.  Rainfall defines the
			transmission season by provided breeding sites
			for the mosquitoes that are the vectors of the
			disease, while temperature impacts both the
			vector larva and adult lifecycles.  Many other
			environmental factors play a role, from soil
			type and terrain topography which affect the
			surface hydrology, as well as the land cover
			type.  Socio-economic factors should not be
			neglected.  Interventions can depress
			transmission or eradicate it altogether in a
			region, but population migration can
			reintroduce the disease. Understanding what
			drives malaria transmission in this complex
			web of factors could be aided by accurate
			models of the disease transmission that
			operate over regional scales.
VECTRI Malaria Model
  VECTRI is a mathematic dynamical
	model for malaria transmission that accounts for the impact of
	climate variability and population.  It was written in the
	early period of 2011 and officially launched at the second
	workshop for East Africa Climate and impacts at the university
	of Addis Ababa in November 2011.  The underlying aim of the
	model is to provide a research tool to understand what drives
	malaria transmission that can be applied on a regional scale
	but at spatial resolutions of 10km or less.
        THE DOCUMENTATION IS CURRENTLY BEING UPDATED AND
	MIGRATED TO GITHUB.IO - DURING THIS PROCESS THE ONLINE
	DOCUMENTATION IS FROZEN AND SOMEWHAT OUT OF DATE.  PLEASE HAVE
	PATIENCE AND WE AIM TO RELEASE THE NEW PLATFORM IN SUMMER 2023.
 VECTRI is a mathematic dynamical
	model for malaria transmission that accounts for the impact of
	climate variability and population.  It was written in the
	early period of 2011 and officially launched at the second
	workshop for East Africa Climate and impacts at the university
	of Addis Ababa in November 2011.  The underlying aim of the
	model is to provide a research tool to understand what drives
	malaria transmission that can be applied on a regional scale
	but at spatial resolutions of 10km or less.
        THE DOCUMENTATION IS CURRENTLY BEING UPDATED AND
	MIGRATED TO GITHUB.IO - DURING THIS PROCESS THE ONLINE
	DOCUMENTATION IS FROZEN AND SOMEWHAT OUT OF DATE.  PLEASE HAVE
	PATIENCE AND WE AIM TO RELEASE THE NEW PLATFORM IN SUMMER 2023.
 
What is new in VECTRI?
  VECTRI attempts to incorporate a simple but physically based
	treatment of surface hydrology, and more importantly it
	accounts for the population density when calculating biting
	rates and transmission probabilities.  This is important,
	since it allows the model to represent the difference in
	transmission rates between rural and peri-urban locations.
	Moreover, the link to population means that the model can be
	actively developed to incorporate immunity, migration,
	socioeconomic status, urbanisation and interventions. It does
	this in a framework that allows regional or even
	continental-wide simulations.
 VECTRI attempts to incorporate a simple but physically based
	treatment of surface hydrology, and more importantly it
	accounts for the population density when calculating biting
	rates and transmission probabilities.  This is important,
	since it allows the model to represent the difference in
	transmission rates between rural and peri-urban locations.
	Moreover, the link to population means that the model can be
	actively developed to incorporate immunity, migration,
	socioeconomic status, urbanisation and interventions. It does
	this in a framework that allows regional or even
	continental-wide simulations. 
			
		
							
		
 
		
		