Van scenario naar werkelijkheid, het belang van One Health surveillance: een arbovirus case-study

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Emmanuel Meijer
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1 Centre for Infectious Disease Control Van scenario naar werkelijkheid, het belang van One Health surveillance: een arbovirus case-study Chantal Reusken

2 Source CDC, 2019

An arbo virus case study Essential background Vector capacity: efficiency of virus X transmission by mosquito species Y in defined context V = vector competence M = vector density vs competent host a

3 An arbo virus case study Essential background Vector capacity: efficiency of virus X transmission by mosquito species Y in defined context V = vector competence M = vector density vs competent host a P n density = vector daily blood feeding rate (host preferences) = vector daily survival rate = extrinsic incubation period (days) Arthropods are cold-blooded (ectothermic) -> sensitive to climatic factors. Climate affects: survival and reproduction rates vectors (vector abundance) habitat suitability; vector distribution (higher altitudes, latitudes) Intensity and temporal activity vector (biting rates) Rate of amplification/survival pathogens in vector Weaver and Barret, 2004 Dobler et al., 2010

An arbo virus case study Essential background Arboviruses (arthropod-borne) grouped based on common mode of transmission between vertebrates by bite of

Arthropods are cold-blooded (ectothermic) -> sensitive to climatic factors.

4 An arbo virus case study Essential background Arboviruses (arthropod-borne) grouped based on common mode of transmission between vertebrates by bite of infected arthropod. (biological vs mechanical transmisison). Arthropods like midges, mosquitoes, sandflies and ticks. Arthropods are cold-blooded (ectothermic) -> sensitive to climatic factors. Climate affects: survival and reproduction rates vectors (vector abundance) habitat suitability; vector distribution (higher altitudes, latitudes) Intensity and temporal activity vector (biting rates) Rate of amplification/survival pathogens in vector Multiple angles

5 An arbo virus case study Essential background Arboviruses (arthropod-borne) grouped based on common mode of transmission between vertebrates by bite of infected arthropod. (biological vs mechanical transmisison). Arthropods like midges, mosquitoes, sandflies and ticks. Arthropods are cold-blooded (ectothermic) -> sensitive to climatic factors. Climate affects: survival and reproduction rates vectors (vector abundance) habitat suitability; vector distribution (higher altitudes, latitudes) Intensity and temporal activity vector (biting rates) Rate of amplification/survival pathogens in vector Weaver and Barret, 2004 Dobler et al., 2010

6 An arbo virus case study Essential background Arboviruses (arthropod-borne) grouped based on common mode of transmission between vertebrates by bite of infected arthropod. (biological vs mechanical transmisison). Arthropods like midges, mosquitoes, sandflies and ticks. Weaver and Barret, 2004 Dobler et al., 2010

Multiple Determinants and Drivers of Infectious Disease Threat Events in Europe A combination of factors increases the threat of vector-borne diseases: changing social, political and economic

7 Multiple Determinants and Drivers of Infectious Disease Threat Events in Europe A combination of factors increases the threat of vector-borne diseases: changing social, political and economic conditions; Food-borne globalized travel and trade => pathogen and vector advances in technology increased urbanization; population growth environmental and ecosystem changes. climate change; Vector/rodent-borne Pathogen adaptation to vector/host Semenza et al., 2016

8 Human disease is result of complex interactions between human, pathogen, vector-related risk factors with spation-temporal variation: CONTEXT Drivers of global change considered in relation to potential changes in the status of vector-borne diseases. Sutherst et al., 2004

9 Reusken et al., 2018; adapted from Worldbank, 2012; Braks et al., 2014 Liefting et al., in prep Karesh et al., 2012 Prediction (Early) Detection => Prevention/Control

10 Zoonotic avian arboviruses Usutu virus West Nile virus

11 Live bird surveillance ECO-Alert Project-based, not sustainable monitoring Using a system of volunteers: bird-ringers: Broad geographic coverage throat swab; cloaca swab; bloodspots/whole blood; ticks Birds: swabs tested for USUV, WNV, JEV (PCR) For : 4149 birds Dead bird surveillance Live DWHC, SOVON Notifications by public diseased/deceased birds Subset to DWHC for autopsy USUV detection diagnostic lab

Time-line USUV outbreak the Netherlands Start notifications unusual die-off black birds at DWHC Start

and blackbirds submitted to EMC; First geographic map Capture 2 retrospectively positive blackbirds

2016 signals die-off black birds and owls in France, Germany Signal die-off/illness black birds on

12 Time-line USUV outbreak the Netherlands Start notifications unusual die-off black birds at DWHC Start submission of dead Great grey owls to DWHC Live birds dead bird Confirmation USUV in Great grey owls and blackbirds submitted to EMC; First geographic map Capture 2 retrospectively positive blackbirds First indication presence USUV testing owls France, NL; testing black birds apr mei jun jul aug sep 2016 signals die-off black birds and owls in France, Germany Signal die-off/illness black birds on Belgian TV, USUV suggested Multiple independent confirmation USUV presence in two blackbirds sampled in April

grey owl specimens tested for Usutu virus infection and common blackbird mortality

13 Outbreak 2016 First evidence: 2 April 2016 Rijks et al., Eurosurveillance 2016 Spatial distribution of the common blackbird and great grey owl specimens tested for Usutu virus infection and common blackbird mortality as reported by the public, the Netherlands, 1 August 23 September 2016 (inset: common blackbird density )

14 Passive surveillance: reported dead blackbirds per year, The Netherlands Source : SOVON

15 Homo sapiens USUV pos species in NL Culiseta annulata Culex pipiens Braamsluiper Chileense flamingo grasmus houtduif huismus ijsvogel kea knobbelzwaan kramsvogel Laplanduil merel pimpelmees roodhalsgans ruigpootuil smient sneeuwuil Vlaamse gaai zanglijster zwarte zee-eend zwartkop

16 2016 multi-country, multiple lineage outbreak FIGURE 1. Number (panel A) and cumulative percentage (panel B) of outbreak-related USUVpositive live and dead birds, western Europe a, 2016 FIGURE 3. Monthly temperature anomalies and distribution of outbreakrelated USUV-positive birds, western Europe a, 2016 Cadar et al., Eurosurveillance 2016

17 Figure 2. Mean daily basic reproduction number and distribution of outbreak-related USUV-positive birds, western Europe, 2016 The map represents the spatial distribution of the potential risk for a USUV outbreak between June and September 2016 and the laboratory-confirmed USUV-positive live and dead birds (the black dots) in western Europe. The temperature-dependent transmission model by Rubel et al. [5] was used on the base of daily mean temperature data on a 0.25 regular latitudelongitude grid downloaded from The spatial distribution of the majority of positive cases in 2016 fell in an area with a mean basic reproduction number larger than one (R 0 > 1)

(171 deaths) Week 25-31 14-17: 5-25 cases 18: 168 cases Early start (2

18 West Nile virus in 2018 West Nile virus notification human cases EU/EEA and pre-accession countries Until 08/11/2018: 1914 cases (171 deaths) Week : 5-25 cases 18: 168 cases Early start (2 wks) Infection in May! 30/10/2018 Source: ECDC West Nile virus NVMM 15 November 2018

West Nile virus drivers Key determinants for WNV

winter/spring -high summer temperatures -summer drought

replication rates ( EIP) human exposure Marcantonio et

19 West Nile virus drivers Key determinants for WNV incidence: 2018: mild winter wet, warm spring dry, hot summer a.o. Climate anomalies: -high precipitation in late winter/spring -high summer temperatures -summer drought mosquito biting rates mosquito development rates virus replication rates ( EIP) human exposure Marcantonio et al., 2015 Paz et al., 2013 Tran et al., 2014 Fros et al., 2015 Vogels et al., 2016 Mean diurnal summer temp (Jul-Aug)

Arbovirussen vaak genoemd in relatie tot klimaatverandering door centrale rol koudbloedige geleedpotigen in transmissie cyclus Klimaat (verandering) is slechts 1 (belangrijke) factor: opduiken van

20 Arbovirussen vaak genoemd in relatie tot klimaatverandering door centrale rol koudbloedige geleedpotigen in transmissie cyclus Klimaat (verandering) is slechts 1 (belangrijke) factor: opduiken van arbovirussen is resultaat van complexiteit aan interacties tussen een breed scala van aandrijvers van wereldwijde veranderingen in (a)biotische factoren die in tijd en plaats variëren. Adequate response op basis van vroegsignalering (in One Health context) en voorspellingen op geleide van geïdentificeerde risicofactoren. Voorbeelden van klimatologische parameters als risicofactor voor het opduiken van USUV en WNV maar meer puzzelstukjes dienen op hun plaats te vallen!

21 Public health action Vector, animal surveillance Disease surveillance Monitoring drivers for prediction Early warning prompt implementation control measures Laboratory preparedness and response Source : WHO World Health Day 2014 Vector-borne diseases

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