Natalie Hofmann Surrogate markers of transmission X-sectional - - PowerPoint PPT Presentation

Investigating micro-heterogeneity in malaria transmission

Natalie Hofmann

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X-sectional

• Prevalence
• MOI (multiplicity of infection)
• % single clone infections
• Allelic diversity
• …

Longitudinal

• molecular force of infection

(incidence of new infections

• bserved in blood)
• …
• P. falciparum

molFOI

All new infections from mosquito bites

• P. vivax

molFOB

New infections from

• mosquito bites
• relapsing hypnozoites

Surrogate markers of transmission

Assessing molFOI/molFOB in natural infections

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Antimalarial

Parasite Positivity (qPCR) Clonal positivity (genotyping PCR) molecular Force of Infection (molFOI)  Measure of individual exposure!

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Albinama study cohort

East Sepik Province, PNG, 2009/10 504 children, 5-10 years 2 treatment arms: CQd1-3 / ALd15-18/ PQd1-28, 0.5mg/kg CQd1-3 / ALd15-18/ Placebod1-28 2-/4-weekly ACD for 9 months PCD implemented in villages Molecular detection and high-resolution genotyping: (Pf-msp2, Pv-msp1F3)  P. vivax relapse  molFOI / molFOB

Child 1 Child 2 Child 3

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3 km N=70 N=93 N=99 N=119 N=31 N=54

Albinama study - geography

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Markers of exposure by village

p-values by Chi2 test, Fisher’s exact test and ANOVA

p<0.001 p<0.001 p=0.157 p=0.008 p=0.031 p=0.100

Prevalence MOI

molFOI

(P.v. – PQ arm)

• P. vivax
• P. falciparum

% single clone

p<0.001 p<0.001

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• P. falciparum
• P. vivax

r = 0.99

r – Pearson’s correlation coefficient

r = 0.53 r = - 0.37 r = 0.72 r = 0.59 r = - 0.36

molFOI molFOI molFOI molFOB (PQ arm) molFOB (PQ arm) molFOB (PQ arm)

Correlation of surrogate markers for exposure

Prevalence MOI % single-clone

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Spatial (micro-) heterogeneity in exposure

• P. falciparum molFOI
• P. vivax molFOB

Individual

molFOI/molFOB

(new inf/pyr)

PvPQ 0 – 23 PvPlacebo 0 – 36 PfOverall 0 – 18

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• P. falciparum
• P. vivax

IRR p-value IRR p-value PQ treament ns 0.2 <0.001 Age ns 0.9 0.02 Village Amahup Balanga Balif Bolumita Numangu 0.6 1.8 0.8 4.8 2.4 <0.001 0.3 1.4 0.7 2.3 0.7 <0.001 Enrolment status 1.7 0.003 1.4 0.01

Negative binomial regression also adjusted for sex, average bednet use and distance to health center. ns: not significant

Other predictors of exposure

Multivariate regression of total molFOI per child PvPlacebo 5.3 [4.9-5.8] PvPQ 1.6 [1.4-1.8] PfOverall 1.4 [1.2-1.6] Mean molFOI [CI95] (new infections/pyr) How do differences in exposure translate e.g. to risk for episodes?

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molFOI as predictor for clinical episodes?

• P. falciparum

Mueller et al., PNAS (2012)

 Aquisition of new clones determines risk for clinial episodes

• P. vivax

Koepfli et al., Plos NTD (2013)

 High number of new infections drives rapid aquisition of clinical immunity

molFOI/molFOB

Episode incidence

Cohort Eask Sepik, children 1-4 years

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molFOI as predictor for clinical episodes?

Cohort Eask Sepik, children 5-10 years

molFOI/molFOB

Episode incidence

• P. falciparum
• P. vivax

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molFOI as predictor for clinical episodes?

• Highest episode incidence was highest in villages of high molFOI/molFOB
• No association of individual exposure (molFOB) with odds of clinical P.

vivax episode

• Age was single significant predictor for odds of clinical P. vivax episode

(OR = 0.73, p=0.02)

• Association of individual exposure (molFOI) with odds of clinical P.

falciparum episode (OR = 0.85, p=0.01)

• Other predictors for odds of P. falciparum clinical episode

Pf density (qPCR) OR = 1.42, p<0.01 Pv positivity (qPCR) OR = 0.29, p<0.01 Cohort Eask Sepik, children 5-10 years

Parameter estimates from binomial GEE with logit link

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 Genotyping and tracking of individual parasite clones in cohort studies allows assessing detailed patterns of exposure on individual level (molFOI/molFOB)  High heterogeneity in exposure for both Plasmodium species over very small spatial scales (<3km) in a cohort of 5-10 year old children from Papua New Guinea  Increase understanding of effects of exposure on various outcomes  Application for planning of control measures, evaluation of vaccine trials, drug trials, …

Summary

Ingrid Felger Rahel Wampfler Tom Smith Mariah Silkey Amanda Ross Leanne Robinson Peter Siba Inoni Betuela The field team The Goroka lab team Ivo Mueller Stephan Karl Connie Li Wai Suen Andreea Waltmann

Financial support

Swiss National Science Foundation Brazilian-Swiss Joint Research Partnership ICEMR TRANSEPI Bill and Melinda Gates Foundation

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Acknowledgements

The study participants and their families