19 benv january 2015 en

January 2015

Number 19

BENV

Photo by Mark Dumont

National Veterinary Epidemiological Bulletin

COVEPI

Operational Veterinary Centre for Epidemiology Programming and Information -

CESME

National Reference Centre for the study and verification of Foreign Animal Diseases

BENV National Veterinary Epidemiological Bulletin

INDEX

EDITORIAL

IN THESE MONTHS

West Nile Disease: epidemiological situation in Italy, in Europe and in the Countries of the Mediterranean Basin Epidemological situation of Aethina tumida in Italy The national information system for Salmonella control programs in Italy

4 6 10

HAND ON DATA

Number of outbreaks reported to SIMAN in 2014 Number of outbreaks reported by Regions to SIMAN in 2014 Animals involved in outbreaks reported to SIMAN in 2014 -

A LOOK AT THE MAPS

19 20 24 25

AROUND US

Highly Pathogenic Avian Influenza H5N8 â&#x20AC;&#x201C; Epidemiological situation in Europe Lumpy skin disease: still a neglected disease? Mathematical models for the study of microbial growth, survival and inactivation: predictive microbiology between past and future

29 34 41

OFFICIALLY FREE TERRITORIES 46

CONTACTS & EDITORIAL STAFF

2 Index

January 2015 Number 19

EDITORIAL

The BENV as a tool for disseminating information

Dear readers, in this first issue of 2015, the Benv is presenting a lot of interesting articles, ranging from animal health to food safety. The outbreaks of Highly Pathogenic Avian Influenza (AI) H5N8 occurred in Europe in late 2014 is one of the main topics of this issue: H5N8 virus strain have been identified in poultry farms located in an European area encompassing United Kingdom, the Netherlands and Germany. In December, the virus was also identified in a fattening turkeys farm in north-eastern Italy. In the section Around us, an article updates the current epidemiological situation in Europe, with particular attention to the prompt measures applied to limit the spread of AI to neighbouring areas. In the same section, a review on Lumpy skin disease (LSD) is also presented: given the recent and important spread of LSD throughout the Middle East, including Turkey, where it is now considered endemic, this review could be of interest for the readers. In a World experiencing an unprecedented rate of change and globalization, it is often necessary to apply proactive strategies in order to rapidly react to the threats against consumerâ&#x20AC;&#x2122;s safety. Preventing instead of correcting is the preferable approach. To this aim, statistic and mathematical tools specifically designed to predict microbial behaviour in food processing can be indispensable tools. In this framework, an overview on Predictive microbiology is given in the section Around us. It is an interdisciplinary research area that has become more and more used to evaluate, through suitable mathematical models, the responses of pathogenic or spoilage microorganisms to different environmental conditions that could be find in foods during processing and storing. In the section In recent months, you can find the usual update on the trend of the diseases occurred in the national territory and in the Mediterranean area. An article shows the epidemiological situation of West Nile Disease in Italy and in the neighbouring countries. Another article presents the updated situation of the outbreaks due to Aethina tumida in the South of Italy. This parasite of bees has been responsible of 60 confirmed cases in Calabria and one case of infestation in Sicily. It has been responsible for serious damages to the hives and honeycombs, causing fermentation of honey contained in them. Finally, in the same section the Benv introduces the Italian Information System for the collection and management of data on the national Salmonella control programmes (SISalm) in poultry flocks of Gallus gallus and turkeys. This system collects data on official sampling carried out by the official veterinary services and on industry sampling carried out by the food business operator. Therefore, it is a comprehensive system which is integrated with the other national information systems and databases in place in Italy, such as the national information system for the notification of outbreaks of animal diseases (SIMAN) and the national database of animals and holdings (BDN). Regarding the data on outbreaks, in the Hand on data section, you can consult the tables with the data on outbreaks of animal diseases reported to SIMAN in 2014, the health status of the territories and the animal species involved in the outbreaks. The maps show the distribution of the main animal diseases occurred in Italy in 2014. Finally, it our pleasure to inform you that from this year the bulletin is published on Issuu as well, a web service for uploading digital documents (such as books, magazines, newspapers). It is integrated with social networks to endorse the loaded material. Like most of the documents published on the internet, some can also be downloaded and saved. So you can find, display and download this and the previous issues also through the Issuu tool. We wish you all to enjoy a happy new year together with the Benv. Simona Iannetti COVEPI

3 Editorial

BENV National Veterinary Epidemiological Bulletin

IN THESE MONTHS

The main events of epidemiological interest in the last months in Italy and in the European Union

West Nile Disease: epidemiological situation in Italy, in Europe and in the Countries of the Mediterranean Basin in 2014 Introduction West Nile virus (WNV) is a Flavivirus belonging to the family Flaviviridae and is transmitted by mosquitoes. The infection is maintained in nature through transmission cycles between birds and mosquitoes particularly Culex spp [Komar et al., 2001], however mammals including humans and equidae are also susceptible to the infection and, although considered accidental or dead-end hosts, can show clinical symptoms ranging from a flu-like syndrome to a meningoencephalitis which can cause the death of patient [Komar., 2000]. Furthermore in humans have been described cases of vertical transmission, from mother to foetus or through breast milk or even transmission through blood transfusions or organ transplants from infected donors

Epidemiological situation in Europe and in the Countries of the Mediterranean Basin WNV is one of the most widespread arbovirus in the world, in the last 30 years the increasing incidence of West Nile Disease (WND) in horses and humans in Europe and in the Countries of the Mediterranean Basin, raised the attention on the WNV which nowadays is one of the major causes of viral meningoencephalitis in humans [Calistri et al., 2010; Di Sabatino et al., 2014]. It is difficult to determine if the increasing number of WND cases is due to a wider spread of the virus rather than the growing attention for this infection. Whatever the reasons for its enhanced spread, it is important to clarify the ecological and epidemiological models of infection, which are related to the endemisation of the infection as well as the possible ways of virus introduction. In 2014 during the epidemic of WND that affected Europe and the Countries of the Mediterranean Basin, 210 cases of human infections have been notified in Bosnia Erzegovina, in Greece, in Russian Federation, in Serbia, in Austria, in Italy, in Romania, in Israel, in Palestina and in Hungary as well as 39 cases of infection in equidae in Greece, in Croatia, in Italy, in Spain and in Turkey (figure 1 and and table 1).

4 In these months

January 2015 Number 19

Figura 1. Geographical distribution of WND human and equidae cases (probable and confirmed) in Europe and in Countries of the Mediterranean Basin in 2014 - last updated December 18th, 2014

Table 1. Details of the WND cases (probable and confirmed) in Europe and in the Countries of the Mediterranean Basin in 2014 - last updated December 18 th, 2014

State Bosnia and Herzegovina Greece Russian Federation Serbia Croatia Austria Israel Palestine Italy Romania Hungary Spain Turkey

Source of human date ecdc

Species Human Equidae Human Human Human Equidae Human Human Human Equidae Human Human Human Equidae Equidae Total human Total equidae

No. Probable cases

No. Confirmed cases

13 4 15 29 76 1 1 17 1 27 24 23 11 6 1 210 39

0 4 13 -56 1 1 7 1 27 24 22 3 6 1 127 39

5 In these months

BENV National Veterinary Epidemiological Bulletin

Epidemiological situation in Italy In Italy, the first reported WND outbreak occurred during the late summer of 1998 in the area around the marshes of Fucecchio, in Tuscany Region, with some clinical cases in equidae. Following this epidemic, the Italian Ministry of Health, since 2002, put in place the WND National Surveillance Plan aiming to monitor the introduction and circulation of WNV in the Country. The surveillance program allowed to identify in 2008, 10 years after the first outbreak, the circulation of WNV belonging to Lineage I, in Emilia Romagna, in Veneto and in Lombardy Regions in birds, in mammals and in vectors [Monaco et al., 2010]. Since then the infection has been reported every year in humans and animals involving both new areas of Central and Southern Italy and areas affected by the viral circulation in previous years demonstrating the endemisation of the infection. To complete the epidemiological scenario of the WND in Italy is essential to report the entrance and circulation of a new viral lineage, lineage II, in 2011 in the provinces of Udine and Treviso. During the following epidemic seasons, the new lineage spread also in the areas previously infected by the circulation of WNV lineage I, namely in Sardinia in 2012, in Emilia Romagna and Lombardy in 2013. During the 2014 WND epidemic season, both human cases in Emilia Romagna, in Veneto, in Lombardy Regions and animal cases in Emilia Romagna, in Lombardy, in Veneto, in Friuli Venezia Giulia, in Piedmont, in Puglia, in Sicily and in Liguria Regions were reported. All the regions have been already affected by the viral circulation during the previous years with the exception of Liguria. The first positivity was documented on June 16th in chickens in Sicily Region; followed by the notification of WNV in early July in a pool of mosquitoes in Lombardy and in Veneto Regions and in a Carrion crow in Emilia Romagna Region, while the first clinical cases in equidae and in humans occurred in the same areas of Northern Italy at least 6 weeks later. Once again the veterinary surveillance activities were able to ensure an early warning essential for the rapid implementation of control measures to prevent the transmission of the infection to humans. On 18/12/2014 the National Reference Centre for the study of Foreign Diseases of Animals (CESME) confirmed (Table 2): • 27 WND cases in equidae distributed in 17 outbreaks in Emilia Romagna, in Lombardy, in Veneto, in Friuli Venezia Giulia, in Piedmont and in Puglia Regions. Nervous symptoms referable to WNV infection were reported in 6 horses in Reggio Emilia, in Piacenza, in Lodi, in Mantova and in Vicenza Provinces; • 34 WNV PCR positive target birds from Emilia Romagna and Lombardy Regions. In particular the virus was detected in tissues of 16 Carrion crows (Corvus corone cornix), 17 Magpies (Pica pica) and one Eurasian jay (Garrulus glandarius); • 8 WNV PCR positive in Emilia Romagna Region from tissues of 5 Collared doves (Streptopelia decaocto), one little owl (Athene noctua) and 2 Goshawk (Accipiter gentilis); • 109 WNV PCR positive from 109 mosquitoes pools collected in Lombardy, in Emilia Romagna, in Veneto, in Friuli Venezia Giulia, in Sardinia, in Piedmont and in Liguria Regions; • 7 serological positivity in poultry in Sicily Regions. In 2014 WNV strains circulating in Italy were identified as belonging to the Lineage II with the exception of a viral strain responsible for clinical symptoms in a horse in Vicenza Province. The nucleotide sequences analysis clustered the virus isolated from the tissues of the animal within the Lineage I. Figure 2 shows the geographical distribution of viral circulation in 2014 in Italy up to December 18th. The information related to the evolution of the epidemiological situation in Europe and in the Countries of the Mediterranean Basin are collected and published in the WND Bulletin, constantly updated by the CESME and the National Reference Centre for Veterinary Epidemiology, Programming, Information and Risk Analysis (COVEPI) and freely accessible on the website of the Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “Giuseppe Caporale” (IZSAM).

6 In these months

January 2015 Number 19

Figure 2. Geographical distribution of the WNV circulation in Italy in 2014 - last updated December 18th, 2014 -

7 In these months

BENV National Veterinary Epidemiological Bulletin

Table 2. Details of the 2014 WND cases in animals according to the province - last updated December 18th, 2014 Region

Province

Parma Bologna Modena Reggio Emilia Emilia Romagna Ferrara

Piacenza Ravenna Bologna Cremona

Mantova

Lombardy

Lodi Brescia Bergamo Pavia Milano Lecco Vicenza

Veneto

Sicily Friuli Venezia Giulia

Verona Rovigo Catania Udine

Sardegna

Pordenone Olbia Tempio

Piemonte

Alessandria

Puglia

Lecce Brindisi Genova

Liguria Fonte SIMAN, 29/09/2014

8 In these months

Animals Carrion crow Magpie Mosquitoes pool Goshawk Mosquitoes pool Mosquitoes pool Magpie Magpie Mosquitoes pool Horses Mosquitoes pool Magpie Eurasian Jay Collared dove Little owl Horses Mosquitoes pool Carrion crow Mosquitoes pool Magpie Magpie Carrion crow Mosquitoes pool Carrion crow Magpie Mosquitoes pool Horses Mosquitoes pool Horses Mosquitoes pool Magpie Carrion crow Mosquitoes pool Mosquitoes pool Carrion crow Carrion crow Mosquitoes pool Horses Mosquitoes pool Horses Horses Chicken Mosquitoes pool Horses Mosquitoes pool Mosquitoes pool Mosquitoes pool Horses Horses Horses Mosquitoes pool Total

No. Positive animals 7 1 7 2 10 18 4 1 19 2 21 7 1 5 1 1 7 1 1 1 1 2 5 2 1 3 3 1 7 4 1 2 1 1 1 1 1 1 4 6 1 7 1 2 1 1 2 1 1 2 1 185

January 2015 Number 19

References 1. Autorino GL, Battisti A, Deubel V, Ferrari G, Forletta R, Giovannini A, Lelli R, Murri S, Scicluna MT. West Nile virus epidemic in horses, Tuscany region, Italy. Emerg Infec Dis. 2002. 8, 1372-1378. 2. Monaco F, Lelli R, Teodori L, Pinoni C, Di Gennaro A, Polci A, Calistri P, Savini G. Re-emergence of West Nile virus in Italy. Zoonoses Public Health. 2010.;57(78):476-86. 3. Calistri P, Giovannini A, Hubalek Z, Ionescu A, Monaco F, Savini G, Lelli R. Epidemiology of West Nile in Europe and in the Mediterranean basin. Open Virol J. 2010 Apr 22;4:29-37. 4. Di Sabatino D, Bruno R, Sauro F, Danzetta ML, Cito F, Iannetti S, Narcisi V, De Massis F, Calistri P. Epidemiology of West Nile disease in Europe and in the Mediterranean Basin from 2009 to 2013. Biomed Res Int. 2014;2014:907852. Epub 2014 Sep 11. 5. Komar N, Panella NA, Burns JE, Dusza SW, Mascarenhas TM,Talbot TO. Serologic evidence for West Nile virus infection in birds in the New York City vicinity during an outbreak in 1999. Emerg Infect Dis. 2001; 7:621-5. 6. Komar N. West Nile viral encephalitis. Rev Sci Tech 2000; 19:166-76.

-Edited by: Rossana Bruno COVEPI i Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “G. Caporale”

9 In these months

BENV National Veterinary Epidemiological Bulletin

Epidemological situation of Aethina tumida in Italy Introduction Aethina tumida, often reported with the acronym SHB (Small Hive Beetle) is a beetle of the family Nitidulidae. It â&#x20AC;&#x2DC;s a scavenger of Apis mellifera capensis and Apis mellifera scutellata, two bee populations in sub-Saharan Africa, that have behavioral defenses more marked than European subspecies (Neumann, 2008). Those characteristics make more difficult, in African bees, reproduction and spread of parasite, and make less damaging to hives the impact of the infestation. A. tumida can infest also colonies of insects belonging to the genus Bombus, it can also survive and reproduce on different varieties of ripe fruit. However, its reproduction on fruit occurs at orders of magnitude less than on bee products in hives (Buchholz et al., 2008). The main damages caused to the hive, depend on the presence of the larvae of the parasite that feeds brood, pollen and honey; they also destroy honeycombs, causing fermentation of honey contained in them. The final consequence is often the abandonment of the hive by the colony. The adult parasite is able to flight even several kilometers, facilitating the spread of the infestation in other apiaries in the same area (Cuthbertson, 2013). Through exchanges of bees and beekeeping equipment, A. tumida expanded its range of distribution to the American continent. The first report of A. tumida dates back to 1996 in South Carolina, then it was found in Florida in 1998, in 2000 in Egypt, in Canada and Australia in 2002 (De Guzman, 2010). In 2004 in Portugal, eggs and larvae of the beetle were found in transport cages of queen bees from the US (Texas). In that circumstance were traced and destroyed all the queens belonging to that batch, as welle as the apiaries where the queens were allocated, and the infestation was eradicated (Valerio Da Silva, 2014)). The disease was exotic in EU until September 2014, and subject to notify as provided by Commission Decision (CE) No. 2004/216. It is included in the list OIE (2015). The importation of queen bees from third countries is regulated by strict rules laid down by Commission Regulation (EU) No. 206/2010.

Aethina tumida in southern Italy 2014 On September 5, 2014, in an apiary owned by the University of Reggio Calabria, located near the port of Gioia Tauro, Calabria region, were found three infested hives with numerous adults and larvae specimens of A.tumida. The identification was made by Prof. Palmeri of the University of Reggio Calabria (Palmeri et al., 2014). It was then identified by the National Reference Centre for Beekeeping based on morphology, and confirmed by morphological identification and through molecular techniques by the European Reference Centre of Sophia - Antipolis (Mutinelli et al., 2014). As a result of confirmation of the presence of A. tumida in Italy the Italian Ministry of Health, on September 12, issued a note in which was ordered the tracing and control of the apiaries that had carried out activities of nomadism in Calabria region during 2014 productive season, furthermore were indicated the measures to be taken in case of positivity, as seizure and destruction of bees and of all beekeepingÂ equipment possible vehicles of infection. Treatments with insecticides on the surrounding land to the hives were recommended. On 19 September, by a decree of President of Regional Council of Calabria, was established a protection zone with a 20 km radius from the first outbreak site in the town of Gioia Tauro, and was circumscribed a surveillance zone with a 100 kilometers radius. Within the protection zone was forbidden any movement of colonies or beekeeping material, and in all apiaries present was checked a number of hives statistically appropriate to detect an expected percentage of infestation prevalence of 5% with a 95% confidence interval. Within the surveillance zone, inspected apiaries were chosen based on the presence of risk factors, or in the absence of these, according to a randomness criterion. In this zone were checked a statistically appropriate number of hives to detecting a percentage of infestation expected prevalence of 2% with a 95% confidence interval. Controls were performed through the execution of complete inspections of the hives, furthermore were collocated traps to catch adult beetles in all hives of the apiaries visited (Mutinelli et al., 2014).

10 In these months

January 2015 Number 19

The last update of the epidemiological situation in Calabria region made available by the National Reference Centre for beekeeping, Istituto Zooprofilattico Sperimentale delle Venezie in date 12.01.2015, reports 60 confirmed cases of infestation A.tumida, all included in the protection zone (Figure 1). In six outbreaks were found, in addition to the presence of adults of A.tumida, larvae, and pupae too in one of them. ( !

( !

( ! (! (! ! ( (( ! ! !! ( ( ( (! (! ! (! ( ! (! ! (

Girifalco Cortale Vallefiorita

Polia Monterosso Calabro

Pizzo

Epidemiological situation of confirmed cases in Calabria (map edited by IZS Venezie)

Maierato

Cenadi

( !

San Vito ! ( sullo Ionio

!! ( ( ( !

Stalettì

Palermiti Montauro Gas perina

Centrache

! ( ( !

12/01/2015

( !

Montepaone

( !

Olivadi

( !

Jacurso

Filadelfia

Francavilla Angitola

Figure 1.

( ! ( ! ( ! ( ! ! (! ( (! ( ( ! (! ! (! ! ( (! ! ( (! ! (

Petrizzi

( !

(! ! ( Soverato Briatico Chiaravalle ! Capistrano ( ( ( ! ! Argusto Satriano ( ! Centrale ( ! ! ( Sant'Onofrio ( ( ! (! ! !! ( ( Gagliato ( ! Filogaso Torre di ( ! (! ( ! ! ( ( ! ! ( Vibo ! ( ! Ruggiero (! San Nicola Davoli ( ! ( ! ( ! ( Parghelia Valentia da Criss a Cessaniti Cardinale ( ! (! ! ( (! ! ( ( ! ( Tropea ( ! ! ( ! ( ! ( ! Stefanac oni ( ! ( ! ( ! ( ! ( ! ( ! Vallelonga ( ! ( ! ( ! (! ( ( ! ! ! ( ( ! ( ! ! Zaccanopoli ( ( ! ( ! Zungri ( ! ( ! San ( (! ! CATANZAROSan (! ( Vaz zano (! ! Costantino San Drapia Simbario ( ! Sostene ( Calabro Gregorio Ric adi ! Pizzoni (! ( ! ! Is ca VIBO ( d'Ippona (( ! ( sullo (! ! Sant'Andrea Soriano Francic a ( ( ! (! ! Filandari Ionadi ! VALENTIA Ionio ( ! ! ( ! Apostolo Calabro ( ! ( ! ( (! ! Sorianello ( Spadola (! ! ( dello Ionio Brognaturo Spilinga ( ! ( ! Rombiolo Gerocarne Badolato Joppolo (! ! ( Serra (! ! ( ! ( ( ! ( ! San Bruno (! ! ( Dasà (! ! ( ((! ( ( Limbadi ! ( San Santa Caterina ! (! ! ( ! Mileto ( ! ((! ! (! ! ( ! Dinami dello Ionio ( ! ( Calogero ! ( ! ! ( Candidoni (( ! (! (! ! ( ! ( ! Arena ( (! ! Ac quaro (! (! ! ( ! Nic otera ! ( ( ! ( ! ( ! ( ! ( ( ! ( ! Guardavalle ( ! ( ! (! ! ( ! ( ! (! (! (! ! ( ( ! ( ! ( (! Stilo (! ! Serrata (( ! ( ! ( ! (! ! (! ( ! Mongiana ( ! ( ! (( ! ( ! Bivongi ( ! ( ! ( ! ( ! ( ! ( ! ( ! ( ( ! ! ( (! ! ( ! Fabrizia ( ! ( ! ! ( ! ( ! ( (! ! ( Laureana di ( ! ( ! ( ! Pazz ano Feroleto ( ! ( ! Borrello ( ! San Pietro ( ! ( ! della ( ! ( ! Galatro San di Caridà Chiesa ( ! Ferdinando Monasterace ( ! (! ! (! ( Nardodipace ( ! Zambrone

E E EEEE E EEEEE EEE E E E E E E EE E E E E (! ! ( ! ( ( ! E ( ! ( E ! ( ! E!( E E E ( ( ! (! ! ( ! E ( ( ! ( ! ! E ( ! ( ! ( ! (! ( ( ! ( ! (! ! ( ! ( ! E ( ! ( ! ( ! E (! ! E ( REGGIO DI EE CALABRIA E !( ( ! E E !( E!( ( E ! E EE !( E E EE E Rosarno

Melicucco

Anoia

Gioia Tauro

Martone

Cinquefrondi

( !

Seminara

Cittanova

Melicuccà

MESSINA Villa San Giovanni Campo ( Calabro Fiumara (! !

( ! ! ( (! ! (! (! ( (! ! (

( ! ! ( ( !

San Procopio

Bagnara Calabra

Messina

( !

Palmi

Casignana

Africo

Cardeto

Sant'Agata del Bianco

San Lorenzo Roccaforte del Greco

Bagaladi Montebello Ionic o

Motta San Giovanni

( ! ( ! ! ( ( !

( !

E 60

Cinquefrondi Polistena

San Giorgio Morgeto

( !! (

Positive Negative

20000 m. Province Municipality

Cittanova

E 44

E E 46 E 45 E 49 EE 48 E 55 EE 56 E

( ! ( ! ! ! ( ( ( !

Ferruz zano

Staiti

( !

Giffone

Melicucco

E E 11

Taurianova

E 41

( !

Bruzzano Zeffirio

Bova

Condofuri

Seminara

( ! ! (

( ! ! ( ( ( ! ( ! ! ( ! ( ! ( !

! ( ( !

( !

Samo

Roghudi

E E

Bovalino

Galatro

Maropati

Caraffa del Bianc o Bianc o

Reggio di Calabria

E 23

Anoia

Rizziconi

( !

San Luca

( !

Feroleto della Chiesa

E 33

( ! ( !

( ! Cosoleto

Sant'Ilario dello Ionio

Ardore Careri

( !

E E

Locri

Portigliola

Benestare

Santo Stefano in As promonte

Gioia Tauro

Laureana di Borrello

Rosarno

E E E 6 E 26 29 E 4 E E 18 E 13

( !

( ! Platì

( ! ( !! (

( !

Siderno

E E 1 2 E 3E E E 61 31 E 30 20 14

( ! ! ( ( !

Gerace

( !

d'Aspromonte

Sant'Alessio in Aspromonte

Roccella Ionic a

( !

San Pietro di Caridà

Serrata

Candidoni

Ciminà

Laganadi

Calanna

( !! (

! ( ( !

Oppido ( Santa Mamertina ! Cristina d'Aspromonte

(! ! ( !! ( (! ( ( ! ( ( ! (! ! Sinopoli ( ! Sc ido (! ! Sc illa ( Sant'Eufemia ! ( Delianuova

San Roberto

Antonimina

( !

(! ! (

E E EE E E E

43 19 22 39 8 San 12 21 Ferdinando

( ! (! ! ! ( ( ! (( ! ( ( ! (! ! ( ! ( !

Marina di Gioiosa Ionic a

( !

( ! Agnana Calabra

( !

! ( ( !

Canolo

Molochio

( !

Mammola

Varapodio

( !

San Giovanni di Gerace Gioiosa Ionic a

San Giorgio Morgeto

( !

15 km Dinami

17 E 42 E EE

( !

! ( Caulonia ! (( !

Grotteria

Taurianov a

Palmi

Riace

Polistena

7,5

San Calogero

Limbadi

Nicotera

Placanica Stignano

( Giffone !

3,75

Mileto

Camini

Maropati

Riz ziconi

Melicuccà

Varapodio

E 50

Molochio

Oppido Mamertina

San Sinopoli Procopio Cosoleto Sant'Eufemia d'Aspromonte

E Ciminà

Santa Cristina Delianuova Scido d'Aspromonte

( !

( ( ! !

Two hundred and nineteen apiaries within the protection zone, 419 within the surveillance zone, 338 outside the two areas, a total of 976 apiaries were found negative for the presence of A. tumida (Mutinelli et al., 2014). (! ! (

( !

( ! ! (

( !

On November 7th adults of A. tumida were found in a nomadic apiary in the municipality of Melilli, in the province of Syracuse, Sicily. The epidemiological investigation carried out by the veterinary services showed that these hives had been in the area of Gioia Tauro, site of the first discovery in Calabria, in the period from April to August 2014. On 12 January, 2015, as reported by the National Reference Centre for ‘beekeeping, no further outbreak of A. tumida in Sicily was reported. Were performed checks in 24 apiaries in the protection zone, 164 in the surveillance zone, 10 outside of the two zones for a total of 198 apiaries (Figure 2). ( !

Figure 2.

( ! Adrano

Regalbuto

Epidemiological situation of confirmed cases in Sicily (map edited by IZS Venezie)

Ragalna

Bianc av illa

( Ac i Ac ireale Trecastagni ! Sant'Antonio Pedara ( Viagrande ! ( Ac i ! Mascalucia Ac i ( Bonaccorsi Catena ! ( San Giovanni ! la Punta San Pietro ( ! Tremestieri Clarenza Ac i Etneo Sant'Agata San Castello li Battiati Gregorio Camporotondo di Catania Etneo

Santa Maria di Licodia

( (! ! ( !

Centuripe

ENNA

( !

Catenanuov a Agira

Belpass o

( !

12/01/2015

Nic olos i

Mis terbianco

( ! ( !

( ! Paternò

Castel di Iudic a

( ! ! (

CATANIA Motta

Sant'Anas tas ia

( !

( ! ( ! ( !

( !

3,75

Catania Ramacc a

7,5

15 km

( !

( (! !

( !

Catania

( ! ( !

( !

Lentini

( !

Palagonia

( !

( ! ( ! (! ! (

( ! ( !

(! (! ( !! (

Militello in Val di Catania

( !

Mineo

( ! ( !

( !

( ! ( !

( !! ( ( !

( !

! ( ( !

Sc ordia

( !

! ( ( !

( !

E ( !

( !

Lentini

( !

Augusta

Carlentini

( !

( ! Melilli

Francofonte

Augusta Grammichele

( !

( ! Caltagirone

Vizzini

( !

Bucc heri Licodia Eubea

( !

SIRACUSA

Ferla

Solarino

Cassaro

Floridia

Busc emi Monterosso Almo

Chiaramonte Gulfi

! (

( !

Palaz zolo Ac reide

Carlentini Canicattini Bagni

Giarratana

RAGUSA

( !! (

( !

Avola

! ( ( ! ( !

Positivo

20000 m.

( !

Negativo

Provincia Comune

Rosolini

( ! ( !

Melilli

Siracusa

! ( ( !

Noto

Ragus a

Modica

( !

! ( ( !

Comiso

Priolo Gargallo

Sortino

( !

Sortino

Priolo Gargallo

( !

( ! ( ! ! ( ( ! ( !

( !

( ! ! (

! ( ( !

( ! (! ! (

11 In these months

BENV National Veterinary Epidemiological Bulletin

The note of the Ministry of Health of the 1st of October 2015, established the criteria for the implementation of surveillance activities in the regions in which was not detected the presence of A. tumida. Data on the activity carried out so far on the Italian territory are not yet available, but up to now there are no reports of the presence of the parasite outside the regions of Calabria and Sicily. Figure 3 resumes the surveillance activities carried out in Calabria and in Sicily regions within the two areas of surveillance zones of 100 Km radius areas. !

! ! ! !

! ! ! ! ! ! ! ! !! ! ! !! ! ! ! !! ! !! ! ! ! ! !!!! ! ! ! ! ! ! !! !! ! ! !! !! ! ! !

! ! ! !

! ! ! ! ! ! ! !

!! !

! ! ! !

! ! !

! !

! ! !

! !

! !! !! ! ! ! ! !! ! ! !

! !! !

COSENZA

! ! ! !

!! !! !! !! !!

! ! ! ! !!! ! ! ! !!

12/01/2015

! !! !

! !

! ! ! !! !! !! ! ! !! ! !! ! ! !! ! ! ! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! ! !! !! ! ! ! ! ! !!! !!!! ! ! !! !!

! ! !! !! !!!! ! ! ! ! !! ! ! !

! ! ! !!!! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! !!! ! ! ! !! !! ! ! !! ! !! ! !! ! ! ! !! ! ! ! ! ! ! ! !! ! ! !! ! ! !! !! ! ! ! !! !! !!!! ! !! ! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! !! ! ! ! !! !! ! ! ! ! ! !! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! !! ! ! ! ! ! !! ! ! ! !! ! ! ! !! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! !!! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !! !! ! ! ! ! ! !! ! ! !!! ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! !! ! ! ! !! !! !!!!! ! ! !!!! ! ! ! ! ! ! ! !!!!! ! ! ! !! ! ! ! ! ! ! ! ! ! !!! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !! !! ! ! ! ! ! ! ! ! ! !! !!! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! !! !

CROTONE

ÂŻ

! ! ! !! ! ! ! !

CATANZARO

VIBO VALENTIA

EEE EE EE E E E E EE E E EEE E E EEE E E E EEEE E E EE EE E E EE E EE! EE E E ! ! ! ! !E ! ! ! !! ! !! ! ! ! ! !

!! !! !! !! ! ! ! !

! !

!! !

! !! ! ! ! ! !

! ! ! !! ! ! !! !

! ! ! ! ! ! !

! !

! !! ! ! !! !!!! ! ! ! !! !! ! ! !

! !

! !! !! ! ! ! !

60 km

! !

MESSINA !

! !!

! !

REGGIO DI CALABRIA

!! !

! !

!! ! ! !

! !

! ! ! ! ! !

PALERMO

CATANIA

! !

TRAPANI

! ! ! !

! !!

! !

! ! !

! !! !

! ! !

! !

! ! !!

! !

! ! !

! ! ! ! ! !! !

! !

AGRIGENTO

! !

ENNA !

! ! !

! ! !! ! !! ! ! ! ! !!

! !! !

! ! ! !

!! !

CALTANISSETTA

! ! !

! !

SIRACUSA

! !

! ! ! !! ! ! !!

! ! ! !

! ! ! ! !

! !

RAGUSA !

! !

! !! ! ! ! !! ! !! ! ! !! ! ! ! ! !!! ! ! !!! !! ! !! !!!! ! !! ! ! ! ! ! ! ! ! ! ! !

E !

Positive

100000 m.

Negative

Province Municipality

Public health actions undertaken In accordance with the legislation in force all infested apiaries were destroyed by incineration on the site, after killing the bees with vaporization of sulfur dioxide. The soil around the apiary has been plowed, and further treated with a 1% solution of cypermethrin and tetramethrin. On 19 November, 2014, the Ministry of Health by a decree, reaffirms, pending the identification of the prevalence of the infestation and the availability of alternative measures of containment, the obligation of destruction of all hives present in infested apiary, as well nuclei, bee queens or any biological material capable of conveying eggs, larvae or adults of A. tumida. The same decree states that the owners of the apiaries destroyed will be paid the compensation provided by law June 2, 1988 n. 218. Commission implementing Decision (EU) No. 2014/909 of 12 December 2014, forbids the shipping outside the territory of the regions of Calabria and Sicily to other areas of the Union of bees, bumble bees, bee-products unprocessed, beekeeping equipment and comb honey for human consumption. The effects of this measure will remain in force until 31 May 2015.

Hypothesis on the introduction of A. tumida in Italy The location of the first outbreak of A. tumida in the immediate vicinity of the cargo port of Gioia Tauro did focus initially on this possible source of introduction of the parasite, although the investigations performed have not been confirmed (Mutinelli et al., 2014). Another hypotheses that can be reasonably be considered is through the illegal introduction of bees and of beekeeping material.

12 In these months

Figure 3. Surveillance activities carried out in the protection zones of Calabria and Sicily (map edited by IZS Venezie)

January 2015 Number 19

Unfortunately, there are no certainties over the origin nor the date of introduction, but probably it should not be before the beginning of the production season of 2014 (February-March).

Possible future scenarios In the plain of Gioia Tauro in the months of April and May, coinciding with the flowering period of citrus plants, thousands of hives converge from all parts of Italy. At the end of the harvest these hives return to their territories of origin, often performing even intermediate steps, for purposes of exploitation of blooms in other geographical locations. In light of these considerations it is evident that it cannot be underestimated the risk that the parasites may have spread to other areas of the Italian peninsula. The outbreak in Sicily is the proof . Is therefore essential that the monitoring activities be extended to the whole country by the veterinary services, through the adoption of a surveillance plan dedicated to this parasite. During winter control activities on hives, due to adverse weather conditions, undergoes a sharp slowdown, therefore it is likely that a clearer picture of the prevalence of infestation we will have during the production season 2015. Under the framework that emerge, we will have the elements to decide whether the action of eradication will be brought to completion, or if we have to choose a strategy that points to the containment of the infestation.

References 1. Buchholz S.; Schäfer M.O.; Spiewok S.; Pettis J.S.; Duncan M.; Ritter W.; Spooner-Hart R.; Neumann P. (2008) Alternative food sources of Aethina tumida (Coleoptera: Nitidulidae). Journal of Apicultural Research and Bee World, 47(3): 202–209. 2. COMMISSIONE DELLE COMUNITÀ EUROPEE 2004 DECISIONE n. 2004/216/ CE del 1o marzo 2004 che modifica la direttiva 82/894/CEE del Consiglio concernente la notifica delle malattie degli animali nella Comunità al fine di includere talune malattie degli equidi e talune malattie delle api nell’elenco delle malattie soggette a denuncia. Gazz Uff, L 67, 27-30. 3. COMMISSIONE DELLE COMUNITÀ EUROPEE 2010 REGOLAMENTO (UE) N. 206/2010 del 12 marzo 2010 che istituisce elenchi di paesi terzi, territori o loro parti autorizzati a introdurre nell’Unione europea determinati animali e carni fresche e che definisce le condizioni di certificazione veterinaria. Gazz Uff, L 73, 120 pp. 4. COMMISSIONE DELLE COMUNITÀ EUROPEE 2014 DECISIONE DI ESECUZIONE DELLA COMMISSIONE n. 2014/909/UE del 12 dicembre 2014 relativa ad alcune misure di protezione a seguito della presenza confermata del piccolo scarabeo dell’alveare in Italia. Gazz Uff, L 359, 161-163. 5. CUTHBERTSON, A G S; WAKEFIELD, M E; POWELL, M E; MARRIS, G; ANDERSON, H; BUDGE, G E; MATHERS, J J; BLACKBURN, L F; BROWN, M A (2013) The small hive beetle Aethina tumida: A review of its biology and control measures. Current Zoology, 59(5): 644–653. 6. VALÉRIO DA SILVA, M J (2014) The first report of Aethina tumida in the European Union, Portugal 2004. Bee World, 91(4): 90-91. 7. MUTINELLI F. et al. (2014) Detection of Aethina tumida Murray (Coleoptera: Nitidulidae.) in Italy: outbreaks and early reaction measures. Journal of Apicultural Research 53(5): 569-575. 8. NEUMANN P.; ELLIS J.D. (2008) The small hive beetle (Aethina tumidaMurray, Coleoptera: Nitidulidae): distribution, biology and control of an invasive species. Journal of Apicultural Research and Bee World 47(3): 181–183. 9. PALMERI V.; SCIRTÒ G.; MALACRINÒ A.; LAUDANI F.; CAMPOLO O. (2014) A new pest for European honey bees: first report of Aethina tumida Murray (Coleoptera Nitidulidae) in Europe. Apidologie: http://dx.doi.org/10.1007/s13592014-0343-9. -Edited by: Luciano Ricchiuti1 and Franco Mutinelli2 1 Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “G. Caporale” 2 Centro di referenza Nazionale per l’Apicoltura, Istituto Zooprofilattico Sperimentale delle Venezie

13 In these months

BENV National Veterinary Epidemiological Bulletin

The national information system for Salmonella control programs in Italy The framework Salmonella infections are the main cause of food-borne outbreaks in Italy as well as in other industrialized countries; food of poultry origin is the main source of infection. Salmonella infection continue to be an important public health issue in the European Union (EU) even if it continued to decrease in 2012, with a total of 91,034 confirmed cases reported. This represented a 4.7 % decrease in confirmed cases compared with 2011 (EFSA and ECDC, 2014): in the last published EU Summary Report on zoonoses, zoonotic agents and food-borne outbreaks of the European Food Safety Authority (EFSA), a statistically significant decreasing trend has been observed in the period 2008-2012 in the EU, partly due to the combined and â&#x20AC;&#x153;from farm to forkâ&#x20AC;? approach adopted by the EU, and much due to the successful application of the Salmonella control program in poultry sector, that led the majority of Member states to reach the reduction targets set for 2012. The EU legislation on food safety (White Paper, Commission Regulation (EC) no. 178/2002) identifies in the control of the food chain the more effective approach to ensure food safety for humans, indicating in the primary production a pivotal point for surveillance and control of Salmonella infections. EU Member States, European Commission, European Parliament, EFSA and the European Centre for Disease Prevention and Control (ECDC) are involved each for their expertise in risk management and assessment. This combined approach helped to almost halve in five years (2004-2009) the cases of salmonellosis in humans in the EU. In 2003 the EU, considering the risk of Salmonella a priority, established measures for a broad control of zoonoses. The EU set for the Member States the objectives of reducing the prevalence of Salmonella and of other food-borne zoonotic agents on the basis of specific control programs approved by the Commission (Commission Regulation (EC) no. 2160/2003). Under this Regulation, eradication programs, control and monitoring of salmonellosis (serotypes relevant to public health) in breeding flocks of Gallus gallus, laying hens, broilers, turkeys, breeding pigs and pigs for meat production were approved (table 1). With the subsequent Regulation (EC) No. 1003/2005, implementation of Regulation (EC) No. 2160/2003, the requirement for farmers to implement an industry sampling program was also introduced, thus contributing to the verification of the achievement of the Community objective of reducing the prevalence of infection. In this framework, an information system has become indispensable to collect and manage information and data derived from the application of the Salmonella Control programs in Italy (PNS), in agreement with the community legislation, to standardize data collection and information flows, thus avoiding redundancy and errors. This system, named SISalm, is available at the unique portal of the Italian veterinary information systems and collects detailed data on the activities foreseen by the PNS.

14 In these months

January 2015 Number 19

Table 1. Specified zoonoses and zoonotic agents for which Community targets for the reduction of prevalence are to be established pursuant to Article 4 1. Zoonosis or z zoonotic agent

2. Animal population

3. Stage of food chain

4. Date by which target must be established (*)

5. Date from which testing must take place

All salmonella serotypes with public health significance

Breeding flocks of Gallus gallus

Primary production

12 months after the date of entry into force of this Regulation

18 months after the date referred to in column 4

All salmonella serotypes with public health significance

Laying hens

Primary production

24 months after the date of entry into force of this Regulation

18 months after the date referred to in column 4

All salmonella serotypes with public health significance

Broilers

Primary production

36 months after the date of entry into force of this Regulation

18 months after the date referred to in column 4

All salmonella serotypes with public health significance

Turkeys

Primary production

48 months after the date of entry into force of this Regulation

18 months after the date referred to in column 4

All salmonella serotypes with public health significance

Herds of slaughter pigs

Slaughter

48 months after the date of entry into force of this Regulation

18 months after the date referred to in column 4

All salmonella serotypes with public health significance

Breeding herds of pigs

Primary production

60 months after the date of entry into force of this Regulation

18 months after the date referred to in column 4

(*) These dates are based on the assumption that comparable data on prevalence will be available at least six months before the establishment of the target. If such data were not available, the date for the establishment of the target would be postponed accordingly.

Organization of the information system SISalm collects data on official and industry sampling. Data on industry sampling derives directly from the farmer: in fact, the use of the system became mandatory in 2009 for the collection of data on official and industry sampling in broiler flocks; in 2010 the use of the system became mandatory also for turkey flocks. From 2012, data on industry sampling shall be collected for all the categories of poultry included in the PNS. SISalm is fed by the regional veterinary services and by the Local health authorities, which access the system also for consulting detailed data on their activities, both official and industry, of their territorial competence. Industry sampling is an integral part of the official control: where the food business operator (OSA) is required to apply the relevant legislation, the competent authority has the obligation to ensure its conformity (Regulation (EC) no. 882 / 2004). This principle is valid for all OSA and for all the stages of production, from farm to the sale of food to the consumer, in line with European policy “from farm to fork” (Regulation (EC) no. 178/2002, Regulation (EC) no. 852/2004). The farmers must make a specific request for accessing SISalm. Once logged in through appropriate credentials, the farmer can feed the system, view and download data for its own farm as well as it has been reported in the BDN (Note of the Ministry of Health DGSAF Prot. 12682-P of 08/07/2009).

Functionalities SISalm allows to entry and visualize data of territorial competence on the activities performed in the context of the PNS by form on line, Upload and Web services. The veterinary services can download in Excel format data of their own competence. The epidemiological unit in the PNS is the flock defined as “all poultry of the same health status of the same breeding cycle, with the same date of placement kept on the same premises or in the same enclosure and constituting a single epidemiological unit”. From July

15 In these months

BENV National Veterinary Epidemiological Bulletin

2014, the new national poultry computerized registry has been implemented, and this topic will be examined in depth in one of the next issues of the BENV. Under the new registry, the shed is uniquely identified and recorded. This aspect is crucial because the flock is the unit of reference for the evaluation of the reduction target of the prevalence of Salmonella. SISalm provides users with statistics on its feeding by the users: which Regions feed the system and how, how many samples are entered in the period compared to those expected, how many positive results over the total of the data entered and compared to Salmonella serotypes. All reports are available in Excel format (Figure 1). Recently, SISalm has been implemented with the functionality of managing the list of the private laboratories compliant to the legislation requirements. Private laboratories must sign up by filling out the form available in SISalm indicating the possession of the requirements foreseen by the legislation. To verify the maintenance of these requirements during time, SISalm interfaces with the database of Accredia and with the National Reference Centre for Salmonella, which organizes an annual inter-laboratory circuit, in order to verify the ability of the laboratory to isolate Salmonella at different concentrations from samples of faeces and / or dust. Figure 1. Reports with statistics on official control activities carried out by the Competent Authorities (local health units) and on industry sampling carried out by the farmer

Integration with other information systems In line with the strategies of application cooperation aiming for data sharing, avoiding duplications and inefficiencies due to the need to maintain aligned different archives, SISalm is designed to be integrated as with the BDN as with the Italian Information System for the notification of outbreaks of animal diseases (SIMAN) for the automatic notification of the suspected outbreak (figure 2). The integration with the BDN allows printing sampling models with the registry section already pre-filled with data of the farm as recorded in the BDN. In this way models with handwritten and often illegible information can be avoided and it is possible to the read the barcodes in the models to avoid manual entry of the information, while encoding it in the computer systems. SISalm cooperates with SIMAN querying a web service for the notification of the suspected outbreak to automatically load the suspected outbreak in case of a positive result in one or more of the Salmonella serotypes relevant to the plan (either in case of official and industry sampling).

16 In these months

January 2015 Number 19

Figure 2. SISALM integration with other information systems

In case of the notification of the suspected outbreak, SIMAN send an email alert to the veterinary service of the local health unit (ASL), of the Region and to the Ministry of Health. Each week the email alert is renewed in case of the absence of confirmation/deletion of the suspected outbreak. SISalm feeds also the information system “Rendicontazioni”, that is responsible for collecting and sending official data on the national co-financed programs to fulfil the information debt towards the European Commission, in application of Decision (EC) No. 2008/940 and Decision (EC) No. 2003/886. Data collected by SISalm also feed the Italian information system on zoonoses data collection (SINZoo), which collects data on the monitoring of zoonoses and zoonotic agents in animal health, food and feed, in order to fulfil the information debt towards the EFSA, as required by Directive (EC) no. 2003/99. In particular, data collected by SISalm is aggregated and processed according to the EFSA’s specifications for the evaluation of the reduction target set by the EU legislation. The integration of all the information systems allows a comprehensive reporting with statistics on sampling activities planned and carried out, on the results of the samples taken and on the reported outbreaks. The integration also allows optimizing the fulfilment of the information debts towards the European Commission, the EFSA and the OIE, avoiding double reporting of the same information with different timelines and different levels of aggregation. In this way, data is always uniform and unique because it has been derived from a single source.

17 In these months

BENV National Veterinary Epidemiological Bulletin

Conclusions Through the use of SISalm, the information flow is unique and trace the entire process, from the sampling to the analytical results (both for official and industry sampling). Competent Authorities have always available the updated information on farms and flocks, on industry sampling, on the tested samples, on the analytical results, on the laboratories involved, etc. The data collected also allows the programming of activities, their periodic verification and risk analysis. Finally, thanks to SISalm the number of official and industry sampling has been increased, as well as the state of implementation of the computerized registry of poultry farms and the reporting to SISalm of data related to industry sampling (Figure 3). Moreover, SISalm has played a pivotal role to achieve the reduction target of the prevalence of Salmonella in poultry.

Figure 3. SISALM integration with other information systems

References 1. European Commission, 2005. Regulation (EC) No. 1003/2005 of the Commission of 30 June 2005 implementing Regulation (EC) No. 2160/2003 of the European Parliament and of the Council as regards a Community target for the reduction of the prevalence of certain Salmonella serotypes in breeding flocks of Gallus gallus and amending Regulation (EC) No. 2160/2003. OJ L 170, 1.7.2005, p. 12-17 2. EFSA (European Food Safety Authority) and ECDC (European Centre for Disease Prevention and Control), 2014. The European Union Summary Report on Trends and Sources of Zoonoses, Zoonotic Agents and Food-borne Outbreaks in 2012. EFSA Journal 2014;12(2):3547, 312 pp. doi:10.2903/j.efsa.2014.3547 3. Italian Ministry of Health. Note of the DGSAF Prot. 12682-P, 8th of July 2009 4. European Parliament, Council of the European Union, 2003. Council Regulation (EC) No. 2160/2003 of the European Parliament and of the Council of 17 November 2003 on the control of Salmonella and other specified in foods. OJ L 325, 12.12.2003, p. 1-15

Edited by: Simona Iannetti (COVEPI), Elio Malizia, Patrizia Colangeli Data Processing Center, Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “G. Caporale”

18 In these months

January 2015 Number 19

HAND ON DATA

Processing date: 19th January 2015 Number of outbreaks reported to SIMAN in 2014 Disease

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Aethina tumida African swine fever American foulbrood of honey bees

Bluetongue

1 16

162

Total Oct Nov Dec outbreaks

Antrax Avian typhosis

Sep

87 3

1 295

533

2 232

143

1462

Bovine leucosis

Bovine tuberculosis

328

Brucellosis of cattle, buffalo, sheep, goats and pigs

557

Caprine arthritis/encephalitis

Chlamydiosis Clostridiosis (Enterotoxemia) Contagious agalactia

Contagious bovine mastitis Crayfish plague (Aphanomyces astaci)

41 1 1

1 2

1 3

2 3

Erysipelas

European foulbrood of honey bees

Fowl pox

3 1

1 1

Infectious hematopoietic necrosis

Leishmaniosis 3

Low patogenicity Avian influenza in poultry

Maedi-visna

2 2 3

1 2

Paratuberculosis

Pasteurellosis of cattle, buffalo, sheep, goats and pigs

Rabbit haemorrhagic disease

Salmonellosis (S. abortusovis)

Salmonellosis of animals

Scrapie

12 1

3 1

1 2

2 3

4 9

Swine vescicular disease

Salmonellae equine abortion

Q fever

1 1

Mixomatosis

1 2

Koi herpesvirus disease Leptospirosis

7 4

High patogenicity Avian influenza in poultry

Trichinellosis

Equine rhinopneumonitis

Non-typhoidal avian salmonellosis

Echinococcosis/Idatidosis Equine infectious anaemia

West Nile Disease

32 7

Viral haemorrhagic septicaemia (VHS)

1 20

108 19 Hand on data

BENV National Veterinary Epidemiological Bulletin

Number of outbreaks reported by Regions to SIMAN in 2014 Region

Disease

Trimester I

Avian typhosis Bovine leucosis Bovine tuberculosis

Brucellosis of cattle, buffalo, sheep, goats and pigs

Equine infectious anaemia

BOLZANO

Anemia infettiva degli equini

144

2 2

Bluetongue

1 8

Equine infectious anaemia

Fowl pox

Non-typhoidal avian salmonellosis

Rabbit haemorrhagic disease

Bovine leucosis

Bovine tuberculosis Brucellosis of cattle, buffalo, sheep, goats and pigs

Echinococcosis/Idatidosis

CALABRIA

Bovine tuberculosis Brucellosis of cattle, buffalo, sheep, goats and pigs

Equine infectious anaemia

American foulbrood of honey bees

2 2

Erysipelas

Aethina tumida

324

Bluetongue

288

Bovine tuberculosis

Brucellosis of cattle, buffalo, sheep, goats and pigs

Echinococcosis/Idatidosis

17 27

Salmonellosis of animals

Scrapie

Bluetongue

Bovine leucosis

118 1 1 1

111 3

Bovine tuberculosis

Brucellosis of cattle, buffalo, sheep, goats and pigs

116

Chlamydiosis Equine infectious anaemia

Leptospirosis Non-typhoidal avian salmonellosis

Rabbit haemorrhagic disease

Scrapie

Swine vescicular disease 20 Hand on data

Bluetongue

Swine vescicular disease

CAMPANIA

Antrax

Swine vescicular disease BOLZANO

West Nile Disease

BASILICATA

1 1

American foulbrood of honey bees

APULIA

1 1

Mal rossino Peste americana

Salmonellae equine abortion

Total outbreaks

130

Rabbit haemorrhagic disease AOSTA VALLEY

Bluetongue

ABRUZZO

III

2 1 2

January 2015 Number 19

Region

Disease

Trimester I

American foulbrood of honey bees

III

Total outbreaks

Bluetongue Erysipelas

EMILIA ROMAGNA

European foulbrood of honey bees

Leptospirosis

Low patogenicity Avian influenza in poultry

Mixomatosis

Non-typhoidal avian salmonellosis

Salmonellosis (S. abortusovis)

Scrapie

1 1 2

Low patogenicity Avian influenza in poultry

Bluetongue

Bovine leucosis

Bovine tuberculosis

Equine rhinopneumonitis

274 4 1

Q fever

Salmonellosis (S. abortusovis)

Scrapie

10 1

1 1

3 1

4 1

West Nile Disease

Bovine tuberculosis

Equine infectious anaemia

Low patogenicity Avian influenza in poultry

Non-typhoidal avian salmonellosis

1 1

West Nile Disease

Bluetongue

Clostridiosis (Enterotoxemia) Mixomatosis Non-typhoidal avian salmonellosis

Scrapie

Bluetongue MOLISE

339

Bovine tuberculosis

MARCHE

Mixomatosis Non-typhoidal avian salmonellosis

4 1

1 1

Equine infectious anaemia

23 1

Brucellosis of cattle, buffalo, sheep, goats and pigs

LOMBARDY

American foulbrood of honey bees

Leptospirosis

West Nile Disease

LIGURIA

Mixomatosis

LAZIO

Leptospirosis

Non-typhoidal avian salmonellosis

1 1

Leishmaniosis FRIULI VENEZIA GIULIA

3 1

West Nile Disease Crayfish plague (Aphanomyces astaci)

2 1

Bovine tuberculosis

Brucellosis of cattle, buffalo, sheep, goats and pigs

Equine infectious anaemia Trichinellosis

2 2 1

7 1 2

21 Hand on data

BENV National Veterinary Epidemiological Bulletin

Region

Disease

Trimester I

Bovine tuberculosis Infectious hematopoietic necrosis PIEDMONT

III

1 1

Paratuberculosis West Nile Disease

3 3

Avian typhosis Bluetongue

1 5

Contagious agalactia

Maedi-visna

1 1

Mixomatosis

Non-typhoidal avian salmonellosis

2 1

Paratuberculosis

Pasteurellosis of cattle, buffalo, sheep, goats and pigs

Salmonellosis (S. abortusovis)

Q fever 16

Scrapie

Trichinellosis

Salmonellosis of animals

West Nile Disease

3 2

Aethina tumida

Antrax

Bluetongue

Bovine leucosis

Bovine tuberculosis

224

Brucellosis of cattle, buffalo, sheep, goats and pigs

199

Contagious agalactia

Leptospirosis

1 1

Non-typhoidal avian salmonellosis Pasteurellosis of cattle, buffalo, sheep, goats and pigs

1 1

Scrapie

1 1

West Nile Disease

Contagious agalactia

European foulbrood of honey bees American foulbrood of honey bees

5 6

6 3

Bluetongue Bovine tuberculosis

American foulbrood of honey bees

Paratuberculosis

1 1

Rabbit haemorrhagic disease

Koi herpesvirus disease

1 2

Mixomatosis

2 1

Non-typhoidal avian salmonellosis

Paratuberculosis

Salmonellosis of animals 22 Hand on data

Leptospirosis

TUSCANY

Caprine arthritis/encephalitis

Erysipelas

TRENTO

Brucellosis of cattle, buffalo, sheep, goats and pigs

Contagious bovine mastitis

SICILY

3 30

Bovine tuberculosis

SARDINIA

3 32

Total outbreaks 3

Low patogenicity Avian influenza in poultry

African swine fever

January 2015 Number 19

Region

Disease

Trimester I

Bluetongue UMBRIA

III

Total outbreaks

127

Bovine tuberculosis Equine infectious anaemia

Salmonellosis of animals

American foulbrood of honey bees Erysipelas

High patogenicity Avian influenza in poultry

Infectious hematopoietic necrosis VENETO

Non-typhoidal avian salmonellosis

Rabbit haemorrhagic disease

West Nile Disease

1 1

Mixomatosis

Viral haemorrhagic septicaemia (VHS)

3 4

1 7

23 Hand on data

BENV National Veterinary Epidemiological Bulletin

Animals involved in outbreaks reported to SIMAN in 2014 Disease name

Animals involved

Aethina tumida

Bees

African swine fever

Suidae

American foulbrood of honey bees

Bees

Antrax Avian typhosis Bluetongue Bovine leucosis Bovine tuberculosis Brucellosis of cattle, buffalo, sheep, goats and pigs

No. Of animal in the holding

No. Of diseased animals

No. Of died animals

No. Of culled animals

No. Of destroyed animas

440

423

421

1204

209

118

1078

711

250929

250205

150006

250037

250202

Ruminants

Birds

Poultry

25120

12500

12620

25120

Ruminants

189171

17022

5866

4351

Wild animals Ruminants

2716

140

Ruminants

20580

2335

2463

52870

8031

7587

Wild animals Ruminants Suidae

Caprine arthritis/encephalitis

Ruminants

1049

382

Contagious agalactia

Ruminants

12022

1757

Contagious bovine mastitis

Ruminants

Crayfish plague (Aphanomyces astaci)

Acquatic animals

Echinococcosis/Idatidosis

Ruminants

Equine infectious anaemia

Equidae

145

Equine rhinopneumonitis

Equidae

204

Erysipelas

Suidae

6374

European foulbrood of honey bees

Bees

214

Fowl pox

Poultry

Infectious hematopoietic necrosis

Acquatic animals

43001

Koi herpesvirus disease

Acquatic animals

2807

2840

Leishmaniosis

Domestic carnviores

616

151

Leptospirosis

Low patogenicity Avian influenza in poultry

Equidae Ruminants Suidae

730

Birds

7731

103

7085

7070

Poultry

2141

1765

Maedi-visna

Ruminants

129

Mixomatosis

Lagomorphs

480

122

102

378

478

Non-typhoidal avian salmonellosis

Birds

108814

96737

Poultry

1078245

777856

60344

51886

2860

0 11

Paratuberculosis

Ruminants

Pasteurellosis of cattle, buffalo, sheep, goats and pigs

Ruminants

310

Q fever

Ruminants

548

Rabbit haemorrhagic disease

Lagomorphs

52877

12136

11936

21836

24141

Salmonellae equine abortion

Equidae

Salmonellosis (S. abortusovis)

Ruminants

9600

541

Ruminants

1284

Salmonellosis of animals

Suidae

Scrapie

Ruminants

6599

275

427

Swine vescicular disease

Suidae

690

687

678

Suidae

Wild animals

Trichinellosis Viral haemorrhagic septicaemia (VHS)

Acquatic animals Birds

West Nile Disease

24 Hand on data

200

Equidae

187

Insects

395

121

Poultry

January 2015 Number 19

A LOOK AT THE MAPS

The geographical distribution of the main animal diseases reported to SIMAN in 2014

Equine Infectious Anaemia

-Geographical distribution of the outbreaks

Bluetongue

-Geographical distribution of the outbreaks

25 A look at the maps

BENV National Veterinary Epidemiological Bulletin

Avian Influenza, low patogenicity

-Geographical distribution of the outbreaks

Avian Influenza, high patogenicity

-Geographical distribution of the outbreaks

26 A look at the maps

January 2015 Number 19

African Swine Fever

-Geographical distribution of the outbreaks

Swine vesicular disease

-Geographical distribution of the outbreaks

27 A look at the maps

BENV National Veterinary Epidemiological Bulletin

West Nile Disease

-Geographical distribution of the outbreaks

Aethina tumida

-Geographical distribution of the outbreaks

28 A look at the maps

January 2015 Number 19

AROUND US

The main events of epidemiological interest in the last months in the European Union and in the neighbour countries

Highly Pathogenic Avian Influenza H5N8 â&#x20AC;&#x201C; Epidemiological situation in Europe

Background In late 2014 several outbreaks of Highly Pathogenic Avian Influenza (HPAI) caused by a H5N8 virus strain have been identified in poultry farms located in an European area encompassing United Kingdom, The Netherlands and Germany. In December 2014 a H5N8 HPAI virus was also identified in a fattening turkeys farm in north-eastern Italy, located in a zone highly frequented by wild waterfowl and on the flyway of many migrant bird species (Bodini, 2000). As of 15 January 2015, HPAIV H5N8 has been reported in nine domestic poultry holdings and in a zoo in Europe (Figure 1, Table 1)

Figure 1. Location of H5N8 HPAI outbreaks in poultry farms in Europe

29 Around us

BENV National Veterinary Epidemiological Bulletin

Table 1. Chronological list of H5N8 HPAI outbreaks in Europe)

Notification Date

(1) (2)

Country

Province/Region/County

Farm Type

6 Nov 2014

Germany

Mecklenburg- Vorpommern

Fattening turkeys

15 Nov 2014

Netherlands

Utrecht

Laying hens

16 Nov 2014

United Kindom

East Yorkshire

Fattening ducks

17 Nov 2014

Germany

Mecklenburg- Vorpommern

Anas spp.

20 Nov 2014

Netherlands

Zuid-Holland

Laying hens

21 Nov 2014

Netherlands

Overijssel

Breeders

21 Nov 2014

Netherlands

Overijssel

(1)

30 Nov 2014

Netherlands

Zuid-Holland

Laying hens

16 Dec 2014

Italy

Rovigo (Veneto)

Fattening turkeys

17 Dec 2014

Germany

Lower Saxony

Fattening turkeys

20 Dec 2014

Germany

Lower Saxony

Fattening ducks

20 Dec 2014

Germany

Saxony-Anhalt

Mallard

7 Jan 2015

Germany

Mecklenburg- Vorpommern

White Storks(2)

Farm located within 1 km from the outrbreak in the poultry breeder farm The positive birds were kept in a zoo

H5N8 HPAI Situation in Europe Germany A total of three H5N8 HPAI outbreaks in poultry farms had been detected in Germany between early November and late December; positivity to H5N8 virus has been identified in white storks kept in zoo in January 2015, and in wild waterfowl. The first case was confirmed by the National Reference Laboratory (NRL) at Friedrich Lรถffler Institut on 6 November 2014, in a fattening turkeys farm located in the state of Mecklenburg- Vorpommern. Depopulation was promptly enforced, and control and restriction measures provided in the Council Directive 2005/94/EC were put into force (European Union, 2005). Epidemiological investigations showed no evidence further virus spread from the outbreak to contact farms. Additionally, an active surveillance plan was put into force on wild birds, including sampling of droppings from the environment in the protection zone (ECDC, 2014). The H5N8 virus was identified in a clinically healthy wild duck, shot on 17 November 2014 in the MecklenburgVorpommern state, approximately 100 km from the infected farm. One month later, on 17 December 2014, H5N8 HPAI virus was detected in another fattening turkeys farm, in Lower Saxony. Local authorities promptly applied containment measures to avoid the spread of the disease to neighboring areas, including depopulation of three rural laying hen farms within 1 km. Nevertheless, on 20 December, another H5N8 HPAI outbreak was notified in Lower Saxony, involving a fattening duck farm; on the same date the presence of H5N8 was also confirmed in a mallard duck (Anas platyrhynchos) collected in Saxony-Anhalt. All of the clinical and laboratory tests performed on poultry farms within the restriction and surveillance zones, and no poultry products had been exported toward other European and Third Countries.

30 Around us

January 2015 Number 19

On 7 January 2015, the H5N8 was confirmed in three white storks (Ciconia ciconia) kept in a zoo in Rostock (Mecklenburg- Vorpommern). A total of 496 birds belonging to 85 different species were present in the zoo. Thirty-nine birds were culled, including the three positive storks and the birds exposed to a higher risk of having had contact with them. The Netherlands The first outbreak in the Netherlands was confirmed on 15 November 2014, when the Health Authorities declared the presence of a H5N8 virus in a laying hens farm in Utrecht province. Control measures were promptly enforced, including depopulation of the farm and restriction and control zones were defined. Laboratory tests indicated high similarity with the virus detected in Germany on 6 November. A second laying hens farm was confirmed positive for HPAI H5N8 virus on 20 November; the farm was located in the Zuid-Holland province, at about 24 km south of the first outbreak. Following this occurrence, the Dutch Government proclaimed a ban on poultry and poultry products movement on the entire National territory. On 21 November another poultry farm with 10,000 birds tested positive for HPAIV H5N8. The farm was located in Kamperveen village (Overijssel province), at about 80 km from the previous two outbreaks. Pre-emptive slaughtering was applied in two farms within 1 km, one of which showing symptoms referable to avian influenza. To contain the HPAI spreading and quickly eradicate the disease, the Dutch Government introduced a new series of control measures. The Netherlands were divided into 4 areas and poultry and poultry products movements were possible only within the same area, to reduce the possible contact between farms. A general ban on poultry restocking was also enforced in the whole National territory. On 30 November, a H5 virus was detected in a laying hens located in the Zoeterwoude municipality (Zuid-Holland province); on 2 December the virus was confirmed belonging to the H5N8 strain. Following improved surveillance measures to test the actual role of wild waterfowl in the introduction and spread of the H5N8 HPAI in the Netherlands, on 3 December the Agriculture Ministry proclaimed that some of the samples collected from Eurasian widgeons (Anas penelope) in the Utrecht province, tested positive for H5N8. Moreover, epidemiological investigations and phylogenetic analyses indicated that 4 out of the 5 outbreaks identified resulted being related to different H5N8 virus and only the two in Kamperveen were linked, strongly suggesting a key role of wild birds in the epidemic (European Food Safety Authority, 2014). United Kingdom United Kingdom experienced only one H5N8 HPAI outbreak, confirmed on 16 November 2014. The outbreak involved a fattening ducks farm with 6,000 birds, located in East Yorkshire. The farm was depopulated and restriction and surveillance zones were defined. On 21 November 2014, European Laboratory of Reference at the Animal Plant Health Agency (APHA) confirmed that the isolated H5N8 virus showed high similarity with those detected in the fattening turkey farm in Germany and in laying hens farm in the Netherlands, corroborating the hypothesis of the involvement of wild migratory waterfowl in the introduction and spread of the disease in Europe. Italy On 10 December 2014 an unspecific gastro-enteric syndrome was observed in a fattening turkeys farm in Rovigo province (Veneto Region, north-eastern Italy); on 12 December an increase in the mortality rates was also detected in the farm. On 15 December 2014, the National Reference Laboratory (NRL) for Avian Influenza at the Istituto Zooprofilattico Sperimentale delle Venezie confirmed the presence of a H5N8 HP virus in the premise. The infected farm was located in a relatively low density poultry populated area, in close proximity to large wetlands with highly populated resting sites for migratory birds and wild waterfowls. Phylogenetic analysis showed a high level clustering of the Italian virus with the H5N8 viruses collected in The Netherlands, Germany and UK in November 2014. Moreover a high nucleotide similarity (99.8%) with the strain isolated in UK and in Eurasian widgeons in the Netherlands was also observed, supporting again the hypothesis of

31 Around us

BENV National Veterinary Epidemiological Bulletin

the involvement of wild waterfowl in the disease spreading. No additional glycosilation sites or molecular markers were identified, indicating no adaptation to mammalian hosts. Following the confirmation of the H5N8 HPAI outbreak in Italy, on 16 December 2014, a series of control measures were implemented on the territory of the Veneto Region, as provided for in Council Directive 2005/94/EC (European Union, 2005). Starting on 22 December 2014, further measures were adopted on a National scale. All of the fattening turkeys farms belonging to the poultry company involved in the outbreak were subjected to weekly mandatory submission of virological samples; virological controls were also enforced in contact farms together with enhancement in biosecurity measures to avoid contacts with wild birds, and on restriction of movements of birds and eggs. Turkeys farms located in more densely poultry populated Italian regions had to be virologically tested every 10 days. At a National level, mandatory virological tests have to be performed on pullets and laying hens before loading for transportation. Moreover, any bird fair, bird exhibition, and live bird market has been forbidden up to a date to be defined and no live decoy bird can be used for hunting.

Final remarks The actual route of introduction of the H5N8 HPAI virus into Europe is still not completely ascertained. The virus was already detected in East Asia earlier in 2014, being isolated from wild waterfowl and causing outbreaks in domestic poultry in Korea, China, and Japan. Contacts with migratory birds represent the most likely route of introduction of the virus into Europe; the hypothesis is strongly supported by the results of phylogenetic analyses which show a high similarity (99.5%) between the European viruses and the Korean H5N8 isolates (European Food Safety Authority, 2014). Nevertheless the direct introduction from south-eastern Asia into Europe is quite unlikely, and led to the hypothesis that migratory birds from the East Atlantic Flyway and East Asian-Australasia Flyways had mingled in common breeding grounds such as Siberia (European Food Safety Authority, 2014). The multiple introduction of H5N8 viruses in Europe, and their similarity with those circulating earlier in Asia, indicate the possibility that the disease is spread at very large distances within a limited timeframe. This indicates the threat represented by avian influenza on a global scale, both for the animal health and the poultry industry with potentially huge economical effects. The infection with the virus has been associated with mortality in several wild bird species; nevertheless the H5N8 virus was also detected in wild waterfowl with mild or no symptoms, as in the case of the mallard in Germany and widgeon in the Netherlands (Jeong et al., 2014). Also anti-H5 antibodies were detected in various wild species in south Korea, indicating recovery from the disease (Jeong et al., 2014). This may impair surveillance activities in the wild host, as it is usually related to passive measures. The recent outbreaks of H5N8 HPAI indicate the need for preparedness. Measures, including strict control activities, well defined biosecurity procedures and improved surveillance, represent the only way to early detect any new introduction and possible spill-over of the disease to domestic poultry sector.

References 1. Bodini, A., 2000. A Multimethodological Approach for the Sustainable Management of Perifluvial Wetlands of the Po River (Italy). Environ. Manage. 26, 59â&#x20AC;&#x201C;72. doi:10.1007/s002670010071 2. ECDC, 2014. Outbreaks of highly pathogenic avian influenza A ( H5N8 ) in Europe - 20 November 2014. 3. European Food Safety Authority, 2014. Highly pathogenic avian influenza A subtype H5N8. EFSA J. 12, 3941. doi:10.2903/j.efsa.2014.3941 4. European Union, 2005. Council Directive 2005/94/EC on Community measures for the control of avian influenza and repealing Directive 92/40/EEC. 5. Jeong J, et al., 2014. Highly pathogenic avian influenza virus (H5N8) in domestic poultry and its relationship with migratory birds in South Korea during 2014. Vet. Microbiol. 173, 249â&#x20AC;&#x201C;57. doi:10.1016/j.vetmic.2014.08.002

32 Around us

January 2015 Number 19

6. Lee YJ, 2014. Novel reassortant influenza A(H5N8) viruses, South Korea, 2014. Emerg. Infect. Dis. 20, 1087â&#x20AC;&#x201C;9. doi:10.3201/eid2006.140233 7. ProMed, 2014a. Archive Number: 20141222.3049031 (accessed 1.14.15). 8. ProMed, 2014b. Archive Number: 20141218.3040607 (accessed 1.14.15). 9. Wu H, 2014. Novel reassortant influenza A(H5N8) viruses in domestic ducks, eastern China. Emerg. Infect. Dis. 20, 1315â&#x20AC;&#x201C;8. doi:10.3201/eid2008.140339 -Edited by: Centro di Referenza Nazionale per Influenza Aviaria e Malattia di New Castle, Istituto Zooprofilattico Sperimentale delle Venezie, Legnaro (Padova) - Italy

33 Around us

BENV National Veterinary Epidemiological Bulletin

Lumpy skin disease: still a neglected disease?

For many years Lumpy skin disease (LSD) has been considered a “neglected disease” because present in developing countries alone and not of major interest for the international trade. Historically, in fact, LSD of cattle has been confined to the African continent, with sporadic outbreaks occurring in the Middle East. More recently, LSD has attracted the interest of the European Union and Mediterranean countries after its spread throughout the Near East, Turkey and Cyprus at a scale that has never been seen before (Tuppurainen E. et al., 2014). It is important, therefore, to review and make the point about the current knowledge on LSD. This short review mainly results from a very recent 2015 EFSA report (EFSA, 2015).

What is LSD ? LSD is a viral disease of cattle characterised by severe losses, especially in naive animals. LSD virus (LSDV) belongs to the family Poxviridae which is divided into two subfamilies—poxviruses affecting insects (Entomopoxvirinae) and vertebrates (Chordopoxvirinae)—and several genera. The genus Capripoxvirus (CaPV) comprises LSDV, sheep pox virus (SPPV) and goat pox virus (GTPV). The prototype of LSDV, Neethling strain, was isolated in South Africa (Alexander et al., 1957). The replication of LSDV occurs in the cytoplasm of the host cell, in intracytoplasmic eosinophilic inclusion bodies (Weiss, 1968; Prozesky and Barnard, 1982).

Which is the host range ? In addition to cattle, natural infections have been reported in Asian water buffalo (Bubalus bubalis) in Egypt, but with significantly lower prevalence rate (1.6 %) than in cattle (30.8 %) (Ali et al., 1990; El-Nahas et al., 2011). LSDV replicates in cell cultures of sheep and goat origin and experimentally infected sheep and goats show a local reaction at the inoculation site but no reports exist on clinical disease in small ruminants caused by LSDV. Thin-skinned, high-producing dairy Bos taurus breeds are highly susceptible against LSDV, whereas indigenous (Bos indicus) breeds such as zebu and zebu hybrids are likely to have some natural resistance against the virus (Davies, 1991; Gari et al., 2011). It is not known which genetic factors influence the disease severity (Babiuk et al. 2008). High air temperatures, coupled with farming practices to produce high milk yields, could be deemed to stress the animals and contribute to the severity of the disease in Holstein–Friesian cattle (Tageldin et al., 2014). Wildlife Clinical signs of LSD have been observed in impala (Aepyceros melampus) and giraffe (Giraffa camelopardalis) after experimental inoculation with LSDV (Young et al., 1970). LSD was reported in an Arabian oryx (Oryx leucoryx) in Saudi Arabia (Greth et al., 1992). Antibodies against SPPV and GTPV and LSDV cannot be differentiated from each other by serological tests, and this is an important limitation. The presence of antibodies in an animal species indicates its susceptibility to the virus and its potential involvement in the epidemiology of the disease (Barnard, 1997). There is evidence that African wild ruminant species may have a role in the epidemiology of LSD. Although certain wildlife species can be experimentally infected by LSDV, information on the susceptibility of wildlife to LSD is scarce and further limited by the inability to distinguish antibodies evoked by LSDV from those evoked by sheep and goat pox.

34 Around us

January 2015 Number 19

Which clinical signs ? The course of the disease may be acute, subacute or chronic. Only 40 to 50 % of experimentally infected animals develops generalised skin lesions; many cases are subclinical but can be viraemic and can transmit the virus (Weiss, 1968). The incubation period of LSD is two to four weeks in field conditions (Haig, 1957). In animals that develop clinical disease, there is a biphasic febrile reaction that may exceed 41Â°C. They remain febrile for 4 up to 14 days. This is accompanied by depression, disinclination to move, inappetence, salivation, lachrymation and a nasal discharge, which may be mucoid or mucopurulent. Lachrymation may be followed by conjunctivitis and, in some cases, by corneal opacity and blindness. The superficial lymph nodes, especially prescapular, precrural and subparotid, are usually markedly enlarged (Thomas and MarĂ¨, 1945; Haig, 1957; Weiss, 1968; Prozesky and Barnard, 1982; Barnard et al., 1994; Carn and Kitching, 1995a). The eruption of nodular skin lesions usually occurs within 48 hours of onset of the febrile reaction.

Where is LSD present ? LSD is endemic in most African countries, and outbreaks outside the African continent occurred in the Middle East in 2006 and 2007 and in Mauritius in 2008 (OIE, 2014). The American continent and Australia are free of CaPV infections. LSD was first reported in Zambia in 1929, then 15 years later was observed in Botswana and in South Africa, where eight million cattle were affected. Until the 1970s, LSD had spread northwards to Kenya and Sudan, westwards to Nigeria and then reported in Mauritania, Mali, Ghana and Liberia (OIE, 2014). The global occurrence of LSD from 2005 to 2013 is reported in figure 1.

35 Around us

BENV National Veterinary Epidemiological Bulletin

Figure 1. Global occurrence of LSD from 2005 to 2013 (Source: EFSA AHAW Panel, 2015. Scientific Opinion on lumpy skin disease. EFSA Journal 2015;13(1):3986, 73 pp. doi:10.2903/j. efsa.2015.3986)

Until 1989, LSD occurrence was restricted to sub-Saharan Africa, but Egypt reported its first LSD outbreak in 1988 (House et al., 1990) and Israel in 1989 (Yeruham et al., 1995). In subsequent years, Bahrain, Kuwait, Oman, Yemen, Israel and the West Bank also reported LSD incursions. From July 2012 to August 2013, 293 outbreaks were reported in Israel; in 2012, 34 outbreaks were reported to OIE in Lebanon; in May 2013, two outbreaks were reported in Jordan; in September 2013, 28 outbreaks were reported in Iraq (still on-going); since August 2013, 236 outbreaks have been reported in Turkey; in May 2014, four outbreaks were reported in Iran; and, in July 2014, two outbreaks were reported in Azerbaijan. LSD may have now become endemic in Turkey. Although LSD has not been reported in the Syrian Arab Republic—most likely owing to the current armed conflict—the disease is present (FAO, 2013b). LSD probably spread from Syria and Iraq to Turkey, as most outbreaks in Turkey occurred along the eastern part of the southern border with Syria and Iraq.

36 Around us

January 2015 Number 19

How can be diagnosed ? Clinical diagnosis A presumptive diagnosis of the disease can be made based on highly characteristic clinical signs of LSD. However, mild and asymptomatic disease may be difficult to diagnose and rapid laboratory methods are needed to confirm the diagnosis. The skin lesions of pseudo LSD (bovine herpesvirus-2, BHV-2), insect bites, Demodex infection, onchocerciasis, besnoitiosis and dermatophilosis can be confused with LSD (Barnard et al., 1994). Generally, BHV-2 infection causes more superficial skin lesions, has a shorter course and is a milder disease than LSD. In addition, the presence of histopathologically demonstrable intranuclear inclusion bodies in BHV-2 infection, as opposed to intracytoplasmic inclusions in LSD, is characteristic. In contrast to the rapid molecular diagnostic tools available for LSD, the detection of BHV-2 in negatively stained biopsy specimens by electron microscopy or the isolation of the virus is only possible approximately one week after the development of skin lesions. In some cases, diseases causing mucosal lesions, can be confused with LSD, such as bovine viral diarrhoea/mucosal disease and bovine malignant catarrhal fever (Barnard et al., 1994). Laboratory techniques The antigen detection through a general CaPV real-time PCR method is more sensitive than other diagnostic assays for the detection of the virus; the test detects CaPV viral DNA, but does not differentiate between the different members of the genus, which may be required if characteristic clinical signs for LSD are not clear. Species-specific real-time PCR methods for differentiation between SPPV, GTPV and LSDV have been published. The general CaPV gel-based PCR method has been validated and published in the OIE Manual of Diagnostic Tests and Vaccines for Terrestrial Animals for LSD but this method is not as fast or as sensitive as real-time PCR. Portable pen-side PCR was recently developed, and it has promising preliminary results: it is easy to use in field conditions and results are obtained within one hour (EFSA, 2015). Electron microscopy: CaPV is morphologically indistinguishable from Orthopoxvirus, but, apart from vaccinia virus, no Orthopoxvirus causes lesions in sheep and goats. Virus isolation is not suitable for primary diagnostics but is needed to confirm the infectivity of the virus. If tissue culture systems are available, then the virus can be isolated on a variety of cells, such as primary lamb kidney or testis cell cultures. The detection of antibodies against LSDV through Serum/virus neutralisation tests are gold standard tests for serology. They are very specific but not sufficiently sensitive for the detection of low antibody titres in animals with mild clinical disease and vaccinated animals. The capacity of Indirect fluorescent antibody test (IFAT) allows testing of larger numbers of samples than with the neutralisation test. Tests may cross-react with other poxviruses. The agar gel immune diffusion test is a very simple test requiring the bare minimum laboratory facilities. However, it lacks sensitivity (EFSA, 2015) and can cross-react with Parapoxvirus (Mangana-Vougiouka et al., 2000), which is one of the differential diagnoses. Positive test results must be confirmed with another test. The performance of enzyme-linked immunosorbent assays (ELISA) for sheep pox/goat pox screened from the literature ranges from 70 to 100 % for sensitivity and from 84 to 100 % for specificity. Western blotting is difficult to perform and requires purified antigens, and it cannot be used as a primary assay but can be used if inconclusive or positive SNT/ELISA results need to be confirmed.

Which is/are the route/s of transmission? Transmission of LSDV is mainly through blood-feeding insects and ticks although indirect or direct contact and seminal transmission of the virus can also occur. Transmission of LSDV by Aedes aegypti mosquitos (Chihota and others 2001) and transmission of the closely related sheep pox (SPP) virus by stable flies (Stomoxys calcitrans) (Kitching and Mellor 1986) have been demonstrated, although it is not known if insects can be also biological vectors for the virus. In recent years, the ability of ixodid ticks to transmit LSDV has been investigated in some detail. It has been shown that LSDV can be transmitted by ticks mechanically (Tuppurainen and others 2013a) and the virus can survive from one tick life cycle stage to the next.

37 Around us

BENV National Veterinary Epidemiological Bulletin

The virus has also been detected in tick eggs, indicating transovarial transmission (Tuppurainen and others 2013b), and in different tick life cycle stages (Lubinga and others 2013, 2014) that are developing off the host in soil or vegetation. This results in the environment being contaminated with LSDV-infected ticks, thus hampering the eradication of the virus without the use of vaccination.

Are vaccines available ? Only live attenuated vaccines against LSD are currently commercially available. The attenuated Neethling strain (LSDV) vaccine is used to vaccinate cattle in Africa. It is possible to use the sheep pox/goat pox vaccine for cattle (Capstick and Coackley, 1961) but the cross-protection is not satisfactory and the use of this vaccine has been restricted to those countries where sheep and goat pox are endemic. Neutralising antibodies to LSDV persist for at least two to three years after vaccination. In some animals, the antibody levels are too low to demonstrate, but they are, nevertheless, still resistant to challenge (Weiss, 1968). Antibodies appear 10 days after vaccination and reach the highest level 30 days post inoculation. Calves born to immunised cows will have passive immunity that persists for about six months (Weiss, 1968). The following excerpts may be of interest to readers : 1. The eradication of LSDV is notoriously difficult, if not impossible, without the use of vaccination. Early detection of the index cases is required in order to stand any chance of controlling the disease through the stamping out of infected and in-contact animals. 2. The field diagnosis of LSD, particularly in the early stages, is not easy. The disease can be confused with many other diseases and conditions, including pseudo-LSD and insect bites. In addition, beef cattle may not be monitored daily, and mild cases of LSD are easily missed. The situation is further complicated by the fact that only about half of infected viraemic animals show clinical signs of the disease, and those apparently healthy animals are able to transmit the virus mechanically to blood-feeding vectors. The likely delay in diagnosing the disease in the field and in the lab may allow sufficient time to pass for the virus to contaminate vector populations, making the control of the disease through the culling of infected and in-contact animals ineffective. 3. According to the current OIE Terrestrial Code (OIE 2014), 3 disease-free years are required for a country to regain the official disease-free status following an LSD outbreak. If vaccination of cattle against LSD is implemented, international trade restrictions or a total ban of live cattle and their products will automatically follow. 4. Currently, only attenuated live vaccines are commercially available for use against LSD. Live vaccines are thought to provide good protection; however, the use of live vaccines in countries that are free of disease is considered risky because of potential safety issues, and also costly because of the associated trade restrictions that would ensue. Recently, novel inactivated LSDV and SPP virus vaccines have been developed. A safety and efficacy study in which sheep and goats were vaccinated with an inactivated SPP vaccine and then challenged with a virulent field strain has been conducted with promising results (EFSA, 2015). Similar experiments are currently in progress in which cattle are being vaccinated with an inactivated LSDV vaccine and then challenged with virulent (Tuppurainen E. and Oura C., 2014). 5. The spread of LSD is likely to have been a result of multiple factors; however, between 2012 and 2014, LSDV outbreaks are likely to have been associated with the severe political unrest and conflicts in Syria and Iraq, which have resulted in the collapse of veterinary services, the associated lack of effective vaccinaton actons in these countries, and the movement of hundreds of thousands of refugees and unvaccinated domestic ruminants from infected areas to neighbouring territories. 6. Disease outbreaks have recently been reported in countries neighbouring Syria including Israel, Lebanon, Jordan, Turkey and Iraq, and for the first time in Iran in July 2014. In addition, LSD is capable of spreading over long distances, as demonstrated by the latest LSD outbreak in Azerbaijan in July 2014. The longdistance spread of the disease from Iraq, Iran and/or Turkey to Azerbaijan is more likely to have occurred via legal or illegal animal movements rather than through arthropod vectors (Tuppurainen E. and Oura C., 2014).

38 Around us

January 2015 Number 19

7. As stamping out of infected and in-contact animals is not feasible in developing countries and the implementation of total restrictions of cattle movements is next to impossible because of transhumance and nomadic cattle farming practices, the control of the disease relies heavily on the immunisation of sufficient numbers of cattle. By using enforced compulsory vaccination campaigns, the spread of the disease has so far been curbed in Israel, Lebanon, and partially in Jordan. 8. LSD is a high impact but largely neglected cattle disease that is on the move and is posing a real and present threat to the cattle populations in European countries.

Bibliografia 1. Ali AA, Esmat M, Attia H, Selim A and Abdel-Hamid YM, 1990. Clinical and pathological studies on lumpy skin disease in Egypt. Veterinary Record, 127, 549550. 2. Alexander RA, Plowright W and Haig DA, 1957. Cytopathic agents associated with LSD of cattle. Bulletin of epizootic diseases of Africa, 5, 489â&#x20AC;&#x201C;492 3. Barnard B, Munz E, Dumbell K and Prozesky L, 1994. Lumpy skin disease. Infectious diseases of livestock with special reference to Southern Africa, 1, 604612 4. Barnard BJ, 1997. Antibodies against some viruses of domestic animals in southern African wild animals. Onderstepoort Journal of Veterinary Research, 64, 95-110. 5. Capstick P and Coackley W, 1961. Protection of cattle against lumpy skin disease. Research in Veterinary Science, 2, 362-375 6. Carn VM and Kitching RP, 1995. The clinical response of cattle experimentally infected with lumpy skin disease (Neethling) virus. Archives of virology, 140, 503513 OIE (Office International des Epizooties), 2014. Lumpy skin disease - Technical disease card. Available online 7. Davies FG, 1991. Lumpy skin disease, an African capripox virus disease of cattle. The British veterinary journal, 147, 489-503. 8. El-Nahas E, El-Habbaa A, El-bagoury G and Radwan ME, 2011. Isolation and Identification of Lumpy Skin Disease Virus from Naturally Infected Buffaloes at Kaluobia, Egypt. Global Veterinaria 7, 234-237. 9. European Food Safety Authority (EFSA). 2015. Scientific Opinion on lumpy skin disease. EFSA Journal 2015;13(1):3986 10. Gari G, Bonnet P, Roger F and Waret-Szkuta A, 2011. Epidemiological aspects and financial impact of lumpy skin disease in Ethiopia. Preventive Veterinary Medicine, 102, 274-283. 11. Greth A, Gourreau JM, Vassart M, Nguyen Ba V, Wyers M and Lefevre PC, 1992. Capripoxvirus disease in an Arabian oryx (Oryx leucoryx) from Saudi Arabia. Journal of Wildlife Diseases, 28, 295-300. 12. Haig DA, 1957. Lumpy skin disease. Bulletin of epizootic diseases of Africa, 5, 421430 13. House JA, Wilson TM, el Nakashly S, Karim IA, Ismail I, el Danaf N, Moussa AM and Ayoub NN, 1990. The isolation of lumpy skin disease virus and bovine herpesvirus-4 from cattle in Egypt. Journal of Veterinary Diagnostic Investigation, 2, 111-115. 14. Lubinga JC, Clift SJ, Tuppurainen ES, Stoltsz WH, Babiuk S, Coetzer JA and Venter EH, 2014a. Demonstration of lumpy skin disease virus infection in Amblyomma hebraeum and Rhipicephalus appendiculatus ticks using immunohistochemistry. Ticks and tick borne diseases, 5, 113-120. 15. Lubinga JC, Tuppurainen ES, Coetzer JA, Stoltsz WH and Venter EH, 2014b. Transovarial passage and transmission of LSDV by Amblyomma hebraeum, Rhipicephalus appendiculatus and Rhipicephalus decoloratus. Experimental & applied acarology, 62, 67-75. 16. Lubinga JC, Tuppurainen ES, Mahlare R, Coetzer JA, Stoltsz WH and Venter EH, 2013a. Evidence of transstadial and mechanical transmission of Lumpy Skin Disease Virus by Amblyomma hebraeum ticks. Transboundary and Emerging Diseases. 17. Lubinga JC, Tuppurainen ES, Stoltsz WH, Ebersohn K, Coetzer JA and Venter EH, 2013b. Detection of lumpy skin disease virus in saliva of ticks fed on lumpy skin disease virus-infected cattle. Experimental & applied acarology, 61, 129-138. 18. Lubinga JC, Tuppurainen ESM, Coetzer JAW, Stoltsz WH and Venter EH, 2014c. Transovarial passage and transmission of LSDV by Amblyomma hebraeum, Rhipicephalus appendiculatus Tuppurainen ESM, Lubinga JC, Stoltsz WH, Troskie

39 Around us

BENV National Veterinary Epidemiological Bulletin

M, Carpenter ST, Coetzer JAW, Venter EH and Oura CAL, 2013b. Evidence of vertical transmission of lumpy skin disease virus in Rhipicephalus decoloratus ticks. Ticks and tick borne diseases, 4, 329-333. 19. Prozesky L and Barnard BJ, 1982. A study of the pathology of lumpy skin disease in cattle. Onderstepoort Journal of Veterinary Research, 49, 167-175. 20. Tageldin MH, Wallace DB, Gerdes GH, Putterill JF, Greyling RR, Phosiwa MN, Al Busaidy RM and Al Ismaaily SI, 2014. Lumpy skin disease of cattle: an emerging problem in the Sultanate of Oman. Tropical Animal Health and Production, 46, 241-246. 21. Thomas A and Marè C, 1945. Knopvelsiekte. Journal of the South African Veterinary Association, 16, 36–43. 22. Tuppurainen ES, Lubinga JC, Stoltsz WH, Troskie M, Carpenter ST, Coetzer JA, Venter EH and Oura CA, 2013a. Mechanical transmission of lumpy skin disease virus by Rhipicephalus appendiculatus male ticks. Epidemiology and infection, 141, 425-430 23. Tuppurainen E., Oura C., 2014 Lumpy skin disease: an African cattle disease getting closer to the EU. Veterinary Record. September 27, 2014 pp. 300-301 24. Weiss KE, 1968. Lumpy skin disease. In: Virology Monographs. Vienna-New York, Springer Verlag, 111-131. 25. Yeruham I, Nir O, Braverman Y, Davidson M, Grinstein H, Haymovitch M and Zamir O, 1995. Spread of lumpy skin disease in Israeli dairy herds. Veterinary Record, 137, 91-93. 26. Young E, Basson PA and Weiss KE, 1970. Experimental infection of game animals with lumpy skin disease virus (prototype strain Neethling). Onderstepoort Journal of Veterinary Research, 37, 79-87. --

Edited by: Maria Luisa Danzetta COVEPI Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “G. Caporale”

40 Around us

January 2015 Number 19

Mathematical models for the study of microbial growth, survival and inactivation: predictive microbiology between past and future

Ensuring healthy foods is a priority for food industries and competent authorities in charge of control activities. In a world experiencing an unprecedented rate of change and globalisation, it is often necessary to apply proactive strategies in order to rapidly react to the threats against consumer’s safety. Preventing instead of correcting is the preferable approach. Nowadays food microbiology needs new tools able to address critical knowledge gaps and trigger quick responses for food risk management, also in the absence of comprehensive laboratory data, in the past considered crucial to apply efficacy control measures. Moreover, laboratory activities can be expensive, and costs cannot always be covered by food industries. Important elements of a proactive approach are the accumulation of quantitative information on microbial behaviour in foods and an increased understanding of microbial physiology (McMeekin et al. 2002). In fact, these are the elements on which predictive microbiology is based. It is an interdisciplinary research area that has become more and more used to evaluate, through suitable mathematical models, the responses of pathogenic or spoilage microorganisms to different environmental conditions that could be find in foods during processing and storing. A great boost to predictive microbiology has been given by EC regulation 2073/2005 on microbiological criteria, currently in force, that has clearly given to food business operators the possibility of using “predictive mathematical modelling established for the food in question, using critical growth or survival factors for the micro-organisms of concern in the product”. Moreover, Codex Alimentarius recommended to move food control activities from a hazard- based and final testing approach to a more risk-based management approach (Codex Alimentarius 1999, Tenenhaus-Aziza & Ellouze 2015). This has made more and more necessary statistic and mathematical tools specifically designed to predict microbial behaviour in food processing. Predictive models cannot completely replace lab testing nor the judgement of an expert food microbiologist. However, they can yield information very useful to take food safety decisions (Whiting & Buchanan, 2002). What is the exact definition of “predictive microbiology”? McMeekin et al. (1993) described it as a quantitative science that enables users to evaluate objectively the effect of processing, distribution and storage operations on the microbiological safety and quality of foods. The same authors also used the expression “Quantitative Microbial Ecology of Food”, while more recently the need to describe the microbial responses to the food environments by mathematical models was also highlighted (McKellar & Xu, 2003, Ceron-Carrillo et al. 2014). Baranyi and Roberts, who designed the most popular primary predictive model, see in this progression a sign of the evolution of predictive microbiology into a more and more exact science (Baranyi & Roberts 2004). Predictive microbiology history begin in 1922 thanks to Esty and Meyer, who described how the thermal inactivation of Clostridium botulinum spores happens according to a log-linear model, still used to estimate heat processing of canned foods: at a given temperature, the specific death rate of a microorganism is constant with time. Another step was made in 1936 by Scott, who studied the direct relation between bacterial growth and available water, that today is called water-activity (aw ) and measured from 0 (no water) to 1 (water). Moreover, Scott established that the specific growth rate of microorganisms in fresh meat was influenced by temperature and that the knowledge of growth kinetic of spoilage bacteria could be useful to define shelf-life of foodstuffs at different storing conditions. The basis of mathematical predictive models had been laid down, in particular for primary models (describe changes in bacterial concentrations in foods in function of time – figure 1) and secondary models (describe parameters of the primary models as a function of environmental conditions as temperature, pH and aw – figure 2).

41 Around us

BENV National Veterinary Epidemiological Bulletin

Figure 1. Primary predictive model. After the lag phase, the logarithm of the population size increases linearly with time (exponential phase), until the stationary phase

Figure 2. Secondary predictive model. The specific rate (sqr: square root) increases linearly with temperature

After these “pioneers”, there was a long time of silence in scientific literature about predictive microbiology until 1960’s and 1970’s, when predictive models were used to manage botulism problems (Spencer and Baines, 1967; Roberts et al. 1981). It was during the 1980’s that the interest toward predictive microbiology noticeably increased, after many foodborne outbreaks from Listeria monocytogenes and Salmonella in USA, UK, Australia and New Zealand and the consequent need of new tools to guarantee food safety (Ceron-Carrillo et al. 2014). A number of different approaches to predictive microbiology were experimented during that period. However, particularly in the 1990’s, the use of mechanistic models according to a two-step approach was preferred and currently it is the most used one (“classical” approach): the first step is to establish the growth/death primary model in constant environment, the second step is to produce a secondary model to establish how the parameters of the primary model are affected by environmental factors. But as bacteria are living organisms, they do not always follow simple mathematical rules. Therefore, different factors that could influence bacterial growth had to be considered in order to develop these mechanistic models. Even if it is recognized that in normal conditions bacterial populations grow or die at constant specific rate, complicating factor could arise and modify the most probable standard model.

42 Around us

January 2015 Number 19

Particularly for growth, the prior history of the cells is important, because it could affect their capability of coping with the new environment and therefore the duration of the transitional period (lag phase), during which bacteria arrive at the exponential phase. Another stage difficult to be predicted is the post-exponential (stationary phase), when bacteria get to the maximum carrying capacity of their environment. Next, when the nutrients have been consumed, cells die (death phase). The four stages of bacterial growth in function of time are reported in figure 3. In the case of primary death models there is a shoulder instead of a lag phase, and a tail in the place of the stationary phase. Figure 3. The four stages of microbic growth: lag phase (lag), exponential phase (log), stationary phase and death phase

Mathematical foundations necessary to design predictive models were defined by Gibson et al. (1988), who proposed the use of the sigmoid function of Gompertz for the primary models and a quadratic polynomial for the secondary models. As it was not originally developed for modelling bacterial growth, the Gompertz model had important limitations although it had been modified so that parameters had biological interpretation (Zwietering et al 1990, Grijspeerdt & Vanrolleghem 1999). Therefore, a truly dynamic model able to deal with time varying environmental conditions that can occur during food shelf-life was specifically developed by Baranyi and Roberts (1993, 1994, 1995): it is still the most used primary model. As concerns secondary models, despite of some efforts for alternative methods made in 1990â&#x20AC;&#x2122;s (Rosso et al. 1995), the use of simple empirical multivariate polynomials is still the most popular approach. Other than classic predictive microbiology models, during the 2000â&#x20AC;&#x2122;s tertiary models became more and more important. They are the integration of primary and secondary models into databases and software tools. These programs collect lab data and yield predictions of bacterial behaviour at different environmental conditions. Some examples are the ComBase, managed by an international consortium funded also by European Union, the Pathogen Modeling Program (PMP), that is a tool from the USA Government, the Danish Food Spoilage and Safety Predictor (FSSP). Recently, predictive microbiology software have been also integrated in programs for risk analysis, just as Dairy Product Safety Predictor, FDA-iRISK, MicroHibro (TenenhausAziza & Ellouze 2015). Other than tertiary models, researches during the last decade have been aimed to introduce variability in predictive models. In particular a mathematical theory was prosed and then validated in order to conclude the behaviour of the population from observing many individual cells and design statistical distributions including the natural variability of the whole population (Baranyi & Pin 2001, Elfwing et al. 2004). The introduction of variability is crucial for the use of predictive microbiology in the framework of quantitative microbial risk assessment (QMRA) models, and it needs further research. In fact, predictive microbiology is a science in constant evolution, aiming to predict with more and more precision bacterial behaviour, taking into considerations factors that could influence microbial growth or death. Among future

43 Around us

BENV National Veterinary Epidemiological Bulletin

developments could be the study of bacterial behaviour at the growth-no growth boundary region, which is difficult to be predicted and should be included in new types of models. New models should also consider “persister” cells, which have been reported in bacterial populations during recent year and that could survive after inactivation treatments (Balaban 2011). Finally, it could be useful to relate predictive microbiology and molecular microbiology, considering data on how genes are switched on as function of changing environmental conditions. However, it is clear that the use of predictive microbiology will increase during next years. Currently, it is more and more applied in order to estimate the risk associated to the consumption of different foodstuffs, particularly when laboratory data are scarce. An example of this tendency is given by two recent EFSA opinions, which based proposals of important changes to CE regulations mostly on results from predictive mathematical models (EFSA 2014a, 2014b). This is the most evident demonstration of the overwhelming evolution of this research area, that only a few decades ago was still considered by food microbiologists not reliable enough to be used in food industry.

References 1. Balaban N.Q. 2011. Persistence: mechanisms for triggering and enhancing phenotypic variability. Curr Opin Genet Dev 21: 768–775. 2. Baranyi J. and Pin C. 2001. A parallel study on modelling bacterial growth and survival curves. J Theor Biol 210: 327-336. 3. Baranyi J. and Roberts T.A. 1994. A dynamic approach to predicting bacterial growth in food. Int J Food Microbiol 23: 277-294. 4. Baranyi J. and Roberts T.A. 1995. Mathematics of predictive food microbiology. Int J Food Microbiol 26: 199-218. 5. Baranyi J. and Roberts T.A. 2004. Predictive Microbiology – Quantitative Microbial Ecology. Culture – March 2004. http://www.ifr.ac.uk/safety/comicro/ Culture_25.pdf accessed on 07/01/2015 accessed on 12/01/2015. 6. Baranyi J., Roberts T.A., McClure P.J. 1993. A non-autonomous differential equation to model bacterial growth. Food Microbiol 10: 43-59. 7. Ceron-Carrillo T.G., Luna-Villa M., Munguia- Perez R., Santiesteban- Lopez N.A. 2014. Description and importance of some predictive models that are used as tools in food conservation. Ann Biol Res 5: 18-25. 8. Codex Alimentarius 1999. Principles and Guidelines for the Conduct of Microbiological Risk Assessment. CAC/GL-30, p. 6. 9. Commissione Europea 2005. Regolamento 2073/2005 della Commissione del 15 novembre 2005 sui criteri microbiologici applicabili ai prodotti alimentari. Gazzetta Ufficiale dell’Unione Europea L 338 del 22.12.2005, pag. 1. 10. Elfwing, A., Le Marc, Y., Baranyi, J., Ballagi A. 2004. Observing the growth and division of large number of individual bacteria using image analysis. Appl Environ Microbiol 70: 675-678. 11. Esty J.R. and Meyer K.F. 1922. The heat resistance of the spore of Bacillus botulinus and allied anaerobes, J Infect Dis 31: 650-663. 12. European Food Safety Authority (EFSA) 2014a. Scientific Opinion on the public health risks related to the maintenance of the cold chain during storage and transport of meat. Part 1 (meat of domestic ungulates). EFSA Journal 12: 3601. 13. European Food Safety Authority (EFSA) 2014b. Scientific Opinion on the public health risks related to the maintenance of the cold chain during storage and transport of meat. Part 2 (minced meat from all species). EFSA Journal 12: 3783. 14. Gibson A.M., Bratchell N, Roberts T.A. 1988. Predicting microbial growth: growth responses of salmonellae in a laboratory medium as affected by pH, sodium chloride and storage temperature. Int J Food Microbiol 6: 155-178. 15. Grijspeerdt K. and Vanrolleghem P. 1999. Estimating the parameters of the Baranyi model for bacterial growth. Food Microbiol 16: 593-605. 16. McKellar R.C., and Lu X. 2003. Modelling Microbial Responses in Food. CRC Press, Boca Raton, FL. 17. McMeekin T.A., Olley J.N., Ross. T, Ratkowsky D.A. 1993. Predictive Microbiology. John Wiley & Sons Ltd. Chichester UK. 18. McMeekin T.A., Olley J., Ratkowsky D.A., Ross T. 2002. Predictive microbiology: towards the interface and beyond. Int J Food Microbiol 73: 395-605.

44 Around us

January 2015 Number 19

19. Roberts T.A., Gibson A. M., Robinson A. 1981. Prediction of toxin production by Clostridium botulinum in pasteurized pork slurry. J Food Technol 16: 337-355. 20. Rosso L., Lobry J.R., Bajard S., Flandrois J.P. 1995. A convenient model to describe the combined effects of temperature and pH on microbial growth. Appl Env Microbiol 61: 610-616. 21. Scott W.J. (1928). The growth of microorganisms on ox muscle. I. The influence of water content of substrate on rate of growth at -1°C. J Counc Sci Ind Res 9: 177-182. 22. Spencer R. and Baines C.R. 1964. The effect of temperature on the spoilage of wet fish: I. Storage at constant temperature between -1 °C and 25 °C. Food Technol Champaign 18: 769-772. 23. Tenenhaus-Aziza F., Ellouze M. 2015. Software for predictive microbiology and risk assessment: A description and comparison of tools presented at the ICPMF8 Software Fair. Food Microbiol 45: 290-299. 24. Whiting R.C. and Buchanan R.L. 2001. Predictive microbiology and risk assessment. In Food Microbiology. Fundamentals and Frontiers. American Society for Microbiology Press, Washington DC. 25. Zwietering M.H., Jongenburger I., Rombouts F.M., van’t Riet K. 1990. Modeling of the bacterial growth curve. Appl Environ Microbiol 56: 1875-1881. -Edited by: Luigi Iannetti1 & Romolo Salini2 Istituto Zooprofilattico Sperimentale dell’Abruzzo e del Molise “G. Caporale” 1 National Reference Laboratory for Listeria monocytogenes 2 COVEPI - Statistica e GIS

45 Around us

BENV National Veterinary Epidemiological Bulletin

OFFICIALLY FREE TERRITORIES Bovine tuberculosis: provinces and regions officially free according to the community legislation up to 14/02/2014 Decision

Province

Region

Bergamo Lecco 2003/467/CE

Ascoli Piceno Bolzano Trento

2004/230/CE 2005/28/CE 2006/169/CE

Marche Trentino Alto Adige

Grosseto

Toscana

Como

Lombardia

Prato

Toscana

Pescara

Abruzzo

All the region

Friuli Venezia Giulia

All the region

Emilia Romagna

Novara Verbania 2007/174/CE

Lombardia

Sondrio

Piemonte

Livorno Lucca

Toscana

Siena Belluno Padova Vercelli 2008/97/CE

Pisa Pistoia

2008/404/CE 2009/342/CE

2010/391/CE

All the region

Veneto Piemonte Toscana Veneto

Oristano

Sardegna

All the region

Lombardia

All the region

Toscana

Cagliari Medio-Campidano Ogliastra

Bovine tuberculosis Sardegna

Olbia-Tempio 2011/277/CE

Rieti Viterbo Asti

2012/204/UE

Biella Fermo

46 Officially free territories

Lazio Piemonte Marche

January 2015 Number 19

Bovine leukosis: Provinces and Regions Officially Free according to the EU legislation up to 14/02/2014 Decision

Province

Region

Bergamo

Pescara

Abruzzo

Brescia

Tutta la regione

Friuli Venezia Giulia

Como

Frosinone

Province

Lecco

Region

Lombardia

Mantova

Decision

2006/169/CE

Sondrio Ascoli Piceno

Marche

Bolzano

Trentino Alto Adige

Bologna

Macerata 2006/290/CE 2007/174/CE

ForlĂŹ Cesena Parma

Emilia Romagna

2009/342/CE

Piacenza Ravenna

2010/391/CE

Reggio Emilia Rimini Aosta

Lombardia

2011/277/CE

2004/63/CE

Liguria

Oristano in Sardegna;

Sardegna

Tutta la regione

Veneto

Tutta la regione

Sardegna

Napoli

Campania

Brindisi

Puglia

Agrigento

Sicilia

Caltanissetta

Viterbo

Lazio

Enna Palermo

Sicilia

Ragusa

Grosseto

2013/177/UE

Livorno Lucca

Molise

Savona

Catania 2012/204/UE

Firenze

Tutta la regione

Trapani

Milano Arezzo

Marche

Siracusa

Valle D'Aosta

Cremona Lodi

Liguria

Pesaro

Ferrara

Modena

Imperia

Lazio

Ancona

Varese

2003/467/CE

Rieti

Toscana

2014/91/UE

Pisa Pistoia

Benevento

Campania

Latina

Lazio

Tutta la regione

Liguria

Avellino

Campania

Prato Siena

2005/28/CE

Pavia

Lombardia

Massa-Carrara

Toscana

Perugia Terni

Bovine leukosis

Umbria

Alessandria Asti Biella 2005/604/CE

Cuneo Novara

Piemonte

Torino

Verbania Vercelli

Officially free territories 47

BENV National Veterinary Epidemiological Bulletin

Bovine brucellosis: Provinces and Regions Officially Free according to the EU legislation up to 14/02/2014 Decision

Province

Region

Decision

Bergamo Como Lecco Mantova

2007/174/CE Lombardia 2008/97/CE

Sondrio Varese Ascoli Piceno Bolzano Trento

Marche

2009/342/CE

Trentino Alto Adige 2010/391/CE

Ferrara 2011/277/CE

Cesena Parma

Piemonte

Firenze

Toscana

Tutta la regione

Veneto

Brindisi

Puglia

Tutta la regione

Toscana

Macerata Cuneo

Piemonte

Campobasso

Molise

Latina

Emilia Romagna

2012/204/UE

Tutta la regione

Valle dâ&#x20AC;&#x2122;Aosta

2014/91/UE

Tutta la regione

Liguria

Ravenna Reggio Emilia Rimini Cagliari Oristano

Sardegna

Sassari Cremona 2004/63/CE

Lodi

Lombardia

Pavia

2005/28/CE

Pavia

Lombardia

Massa-Carrara

Toscana

Perugia Terni

Umbria

Alessandria Asti 2005/604/CE

Biella Novara

Piemonte

Verbania Vercelli

2006/169/CE

Pescara

Abruzzo

Tutta la regione

Friuli Venezia Giulia

Rieti

Lazio

Imperia Savona Milano Pistoia Siena

48 Officially free territories

Lazio

Viterbo

Piacenza

Nuoro

Marche

Pesaro

Frosinone

ForlĂŹ Modena

Region

Torino

Ancona

Bologna 2003/467/CE

Province

Liguria Lombardia Toscana

Bovine brucellosis

January July 2014 2015 Number 17 19

Ovine and caprine brucellosis: Provinces and Regions Officially Free according to the EU legislation up to 14/02/2014 Decision

Province

Region

2002/482/CE

Bolzano

Trentino Alto Adige

Arezzo

Toscana

Decision

Roma 2008/97/CE

Cagliari 2003/237/CE

Nuoro Sassari

Sardegna

2010/391/CE 2011/277/CE

Oristano Bergamo

2014/91/UE

Brescia

Province Latina

Region Lazio

Tutta la regione

Veneto

Tutta la regione

Molise

Tutta la regione

Emilia Romagna

Tutta la regione

Valle dâ&#x20AC;&#x2122;Aosta

Tutta la regione

Lazio

Tutta la regione

Liguria

Como Cremona Lecco 2003/732/CE

Lodi

Lombardia

Mantova Milano Pavia Sondrio Varese Trento

2004/199/CE

Rieti Viterbo

Trentino Alto Adige Lazio

Firenze Livorno Lucca Massa-Carrara 2005/28/CE

Pisa

Toscana

Pistoia Prato Siena Perugia

2005/764/CE

Terni

Umbria

Grosseto

Toscana

Ancona

Ovine and caprine brucellosis

Ascoli Piceno Macerata

Marche

Pesaro Urbino Alessandria 2005/604/CE

Asti Biella Cuneo Novara

Piemonte

Torino Verbania Vercelli

2006/169/CE

Pescara

Abruzzo

Tutta la regione

Friuli Venezia Giulia

Savona

Liguria

Isernia

Molise

Officially free territories 49

BENV National Veterinary Epidemiological Bulletin

CONTACTS & EDITORIAL STAFF

National Reference Centre for Veterinary Epidemiology, Planning, Information and Risk Analysis (COVEPI)

National Reference Centre for the study and verification of Foreign Animal Diseases (CESME)

Epidemiology Dr. Paolo Calistri ph +39 0861 332241

Diagnostics and Monitoring of Exotic Viral Diseases Dr. Federica Monaco ph +39 0861 332446

Statistics and GIS Dr. Annamaria Conte ph +39 0861 332246

Diagnostic and surveillance of exotic diseases, Virology laboratory. Windhoek, Namibia Dr. Massimo Scacchia ph +39 0861 332405

Coordinator Simona Iannetti (COVEPI) Editorial board Barbara Alessandrini Paolo Calistri Fabrizio De Massis Gianfranco Diletti Nicola Ferri Armando Giovannini Federica Monaco Daniela Morelli Francesco Pomilio Giovanni Savini Istructional designer Alessandro De Luca Web master and desktop publishing Sandro Santarelli mail benv@izs.it fax +39 0861 332251 www.izs.it

50 Contacts & Editorial staff