thing entity continuant dependent_continuant specifically_dependent_continuant realizable_entity...

thingentity

continuantdependent_continuant

specifically_dependent_continuantrealizable_entity

disposition

vector_borne_diseasevector_borne_disease

OntologiesOntologies

&&

Disease estim. popul. infected in SSA (milion)

esti. % of SSA population infected

estim % of Global disease burden in SSA

HookwormHookworm 198 198 29%29% 34%34%

SchistosomiasisSchistosomiasis 192192 25%25% 93%93%

AscariasisAscariasis 173173 25%25% 21%21%

TrichuriasisTrichuriasis 162162 24%24% 27%27%

Lymph. filariasisLymph. filariasis 46-5146-51 6-9%6-9% 37-44%37-44%

OnchocerciasisOnchocerciasis 3737 5%5% >99%>99%

Active trachomaActive trachoma 3030 3%3% 48%48%

LoiasisLoiasis ≤ ≤ 1313 1-2%1-2% 100%100%

Yellow feverYellow fever 0.180.18 0.02%0.02% 90%90%

H.A.T.H.A.T. 0.50-0.700.50-0.70 <0.01%<0.01% 100%100%

LeprosyLeprosy 0.300.30 <0.01%<0.01% 14%14%

Visc. LeishmaniasisVisc. Leishmaniasis 0.19-0.240.19-0.24 <0.01%<0.01% NDND

DracunculiasisDracunculiasis 0.0010.001 <0.01%<0.01% 100%100%

Buruli ulcerBuruli ulcer > 0.0004> 0.0004 <0.01%<0.01% 57%57%

Tropical disease burden in SSATropical disease burden in SSA

   Population At risk suspected

casesconfirmed

casesinpatient

cases deaths

AfricaAfrica

 833,633 K833,633 K 704,798 K704,798 K

110,824 K110,824 K80,394 K80,394 K 5,400 K5,400 K 596 K 596 K

(-> 400 M)(-> 400 M)

AmericaAmerica   550,594 K550,594 K 160,146 K160,146 K 8,796 K8,796 K 674 K674 K 7.2 K7.2 K 1.2 K 1.2 K

EuropeEurope   277,042 K277,042 K 00 00 356356 00 00

SE AsiaSE Asia   1.807,278 K1.807,278 K 1,252,518 K1,252,518 K 117,239 K117,239 K 4,417 K4,417 K 57 K57 K 38 K 38 K

World

 5,647,741 K 3,248,885 K 266,184 K 94,265 K 5,645 K

655 K

539-906 K

(-> 2.7 M)

Global malaria burdenGlobal malaria burden

Malaria incidence rateMalaria incidence rate

Dengue incidenceDengue incidence

VBD in the USAVBD in the USA

BacterialDiseases   ArboviralDiseases •    Lyme Disease   •    Chikungunya •    Plague   •    Dengue •    Tick-borne Relapsing Fever   •    Eastern Equine Encephalitis •    Tularemia   •    Japanese Encephalitis

  •    LaCrosse Encephalitis

Rickettsial Zoonoses   •    Saint Louis Encephalitis

•    Rocky Mountain Spotted Fever  

•    West Nile Encephalitis

•    Anaplasmosis   •    Western Equine Encephalitis •    Ehrlichiosis   •    Yellow Fever

MalariaMalaria

The Malaria triadThe Malaria triad

- Good drugs exist, but pathogens are increasingly resistant.

-Most drugs are too expensive: a typical disease of poverty.

-No vaccine available.

-Chemotherapy works well for individual patient but not for area-wide control.

The Malaria problemThe Malaria problem

With the exception of the yellow With the exception of the yellow fever, for which an effective fever, for which an effective vaccine exists, vector-borne vaccine exists, vector-borne diseases have only been controlled diseases have only been controlled through the control of their through the control of their arthropod vectors (insecticides, arthropod vectors (insecticides, physical protection, environmental physical protection, environmental management).management).

Examples range from Malaria (Anopheline Examples range from Malaria (Anopheline mosquitoes - e.g. Europe, Latin America, etc.), mosquitoes - e.g. Europe, Latin America, etc.), to American trypanosomiasis (Chagasto American trypanosomiasis (Chagas’’ disease - disease - kissing bugs), to Onchocerciasis (River kissing bugs), to Onchocerciasis (River blindness - simulid flies), to…blindness - simulid flies), to…

The historic solution:

DDT

(and other insecticides)

Spread of Insecticide ResistanceSpread of Insecticide Resistance

Insecticide Resistance Insecticide Resistance is a heritable change

in the sensitivity of a pest population that is

reflected in the repeated failure of a product

to achieve the expected level of control when

used according to the label recommendation

for that pest species.

Insecticide resistance is a population Insecticide resistance is a population

phenotype, it is the result of phenotype, it is the result of natural natural

selectionselection!!

Insecticide Resistance: managementInsecticide Resistance: management

(Develop new insecticides with a different (Develop new insecticides with a different mode of action).mode of action).

Use more than one insecticides with a Use more than one insecticides with a different mode of action (alternating, different mode of action (alternating, combinatorial, chessboard).combinatorial, chessboard).

Efficient monitoring in combination with Efficient monitoring in combination with above.above.

MIRO & IRBaseMIRO & IRBase

Originally non-BFO, now also integrated into Originally non-BFO, now also integrated into IDOMAL. Stand-alone MIRO is being expanded to IDOMAL. Stand-alone MIRO is being expanded to cover agricultural pests. cover agricultural pests.

Domains: Insecticides (ChEBI), biological Domains: Insecticides (ChEBI), biological material, resistance mechanisms, methods material, resistance mechanisms, methods (future: OBI?), Geo and environment (GAZ & (future: OBI?), Geo and environment (GAZ & ENVO)ENVO)

IRBase: has been integrated into the new PopGen IRBase: has been integrated into the new PopGen section of VectorBase (cross-talk to transmission, section of VectorBase (cross-talk to transmission, population genetics, genome, etc.) population genetics, genome, etc.)

IRBase

The example of Insecticide Resistance:The example of Insecticide Resistance:

Aedes aegypti,Aedes aegypti, 2098 records 2098 records

The example of Insecticide Resistance:The example of Insecticide Resistance:

Aedes aegypti,Aedes aegypti, 2098 records 2098 records

The example of Insecticide Resistance:The example of Insecticide Resistance:

Aedes aegypti - DDT,Aedes aegypti - DDT, 133 records 133 records

IDO

IDOMAL

IDODEN

IDOCHA EuPathDB

VIPR

VectorBase

MDSS

DDSS

GO, ChEBI, GAZ, ENVO, OBI, etc.

IDOMAL

malaria immunology

remedies &natural products

vectorbiology

antimalarial drugs, resistance

symptoms & signs

vectorcontrol

insecticideresistance

malaria epidemiology

etc...

malaria transmission

vector pop.biol. & genet.

insecticidalsubstances

IR methodology

geographyGAZ

environmentENVO

and more…and more…

OBI/MIRO: assayOBI/MIRO: assay MIRO: resistance assay

MIRO: resistance assay

CHEBI: insecticideCHEBI: insecticideis_a participates_in

MIRO: OrganismMIRO: Organism

MIRO: resistanceMIRO: resistance

VB_CV: genotypeVB_CV: genotype

PATO: PhenotypePATO: Phenotype

VB_CV/MIRO: Mosquito population

VB_CV/MIRO: Mosquito population

GAZ: GeolocationGAZ: Geolocation

IDOMAL: Human population

IDOMAL: Human population

IDOMAL: Transmission

detection assay

IDOMAL: Transmission

detection assay

IDOMAL:Human biting rate

Sporozoite rateParous rate

Vectorial capacity

IDOMAL:Human biting rate

Sporozoite rateParous rate

Vectorial capacity

ENVO : Environmental conditions

e.g.Rice field,

Irrigation scheme,swamp,altitude,

av. temperature,annual rainfall,

av. humidity

ENVO : Environmental conditions

e.g.Rice field,

Irrigation scheme,swamp,altitude,

av. temperature,annual rainfall,

av. humidity

GAZ:Country,Province,District,

GPS coordinates

GAZ:Country,Province,District,

GPS coordinates

OBI/MIRO: collection assay

OBI/MIRO: collection assay

IDOMAL:Season

IDOMAL:Season

Season +

Geolocation +

Human population +

Mosq. population

is_ahas_input

has_output is_a

has_output

has_outputis_a

has_input

has_member

has_quality

is_a

has_qualityis_about

located_in

IDOMAL: Malaria control measuresIDOMAL: Malaria control measures

OBI/MIRO: assayOBI/MIRO: assay MIRO: resistance assay

MIRO: resistance assay

CHEBI: insecticideCHEBI: insecticideis_a participates_in

MIRO: OrganismMIRO: Organism

MIRO: resistanceMIRO: resistance

VB_CV: genotypeVB_CV: genotype

PATO: PhenotypePATO: Phenotype

VB_CV/MIRO: Mosquito population

VB_CV/MIRO: Mosquito population

GAZ: GeolocationGAZ: Geolocation

IDOMAL: Human population

IDOMAL: Human population

IDOMAL: Transmission

detection assay

IDOMAL: Transmission

detection assay

IDOMAL:Human biting rate

Sporozoite rateParous rate

Vectorial capacity

IDOMAL:Human biting rate

Sporozoite rateParous rate

Vectorial capacity

ENVO : Environmental conditions

e.g.Rice field,

Irrigation scheme,swamp,altitude,

av. temperature,annual rainfall,

av. humidity

ENVO : Environmental conditions

e.g.Rice field,

Irrigation scheme,swamp,altitude,

av. temperature,annual rainfall,

av. humidity

GAZ:Country,Province,District,

GPS coordinates

GAZ:Country,Province,District,

GPS coordinates

OBI/MIRO: collection assay

OBI/MIRO: collection assay

IDOMAL:Season

IDOMAL:Season

Season +

Geolocation +

Human population +

Mosq. population

is_ahas_input

has_output is_a

has_output

has_outputis_a

has_input

has_member

has_quality

is_a

has_qualityis_about

located_in

IDOMAL: Malaria control measuresIDOMAL: Malaria control measures

"IDOVBD":Additional data

models

"IDOVBD":Additional data

models

“Oth_Ont2”:Additional data

models

“Oth_Ont2”:Additional data

models

“Oth_Ont1”:Additional data

models

“Oth_Ont1”:Additional data

models

Chris Stoeckert, David Roos et al., pers. communic.Chris Stoeckert, David Roos et al., pers. communic.

AcknowledgementsAcknowledgements

• The people who did the work:Ioana Bujila, Elena Deligianni, Emmanuel Dialynas, Vicky Dritsou, Elvira Mitraka, Inga Siden-Kiamos, Pantelis Topalis

• Our collaborators:All members of VectorBase (esp. Frank Collins), Marita Troye-Blomberg (malaria immunology/U. Stockholm), all PIs of Transmalariabloc (esp. George Christophides), John Vontas (Insecticide resistance/U. Crete)

• The hands that fed us:

VectorBase (NIAID), BioMalPar, EVIMalR and

Transmalariabloc (EU-DG XII)

• The people who did the work:Ioana Bujila, Elena Deligianni, Emmanuel Dialynas, Vicky Dritsou, Elvira Mitraka, Inga Siden-Kiamos, Pantelis Topalis

• Our collaborators:All members of VectorBase (esp. Frank Collins), Marita Troye-Blomberg (malaria immunology/U. Stockholm), all PIs of Transmalariabloc (esp. George Christophides), John Vontas (Insecticide resistance/U. Crete)

• The hands that fed us:

VectorBase (NIAID), BioMalPar, EVIMalR and

Transmalariabloc (EU-DG XII)

Τέλος

Ευχαριστώ!

Τέλος

Ευχαριστώ!