From 2007, when ASF entered Georgia, until the first case was detected in EU in 2014, the disease was mainly seen in domestic pig farms with low levels of biosecurity13. Since 2014, Chenais et al.13 describe direct transmission between wild boar as well as indirect transmission between wild boar via the habitat, suggesting that the wild boar-habitat cycle has dominated ASF spread in eastern EU, with occasional spillover to domestic farms. This contrasts with the experience in Romania since summer 2018, where many outbreaks in domestic farms, primarily with low levels of biosecurity, have been diagnosed, while relatively few cases in wild boar were notified14. Therefore, this study included covariates targeted to estimate and statistically evaluate the exposure from wild boar sources and from outbreaks in other domestic farms on study farms.
According to Romanian legislation, farms are classified as backyard, type A or commercial farms with different biosecurity requirements. Therefore, for practical and logistical reasons, two analyses were performed, one for backyard farms and one for type A and commercial farms. Furthermore, different types of questions were used in accordance with the type of farm, e.g. questions on biosecurity would most often not be relevant for backyard farms. However, as herd types can be difficult to compare between countries, with each country defining herd types differently, in order to extrapolate and to compare between countries or areas, classification of herd types based on numbers of pigs would often be of more use.
In the study period, too few commercial farms became infected to reach the estimated sample size, and therefore, even with the extra control farms included, the power of the study was only strong enough to determine a single statistically significant risk factor.
In backyard farms, nine explanatory variables remained in the final multivariable model. Of these, five factors were related to the numbers of and distances to potential sources of ASF virus in the area, i.e. number of outbreaks in domestic pig farms within 2 km, the distance to the nearest outbreak in a domestic pig farm, the distance to the nearest case of ASF in wild boar, wild boar abundance in the area surrounding the farm, and the growing of crops near the backyard which are attractive to wild boar. Three factors were related to farm management, i.e. the number of professional visitors in the high-risk period, the use of straw as bedding and the use of forage from ASF + areas. And finally, the larger size of the backyard farm itself was a risk factor. In commercial farms, only one factor remained in the final model, i.e. the distance to the nearest outbreak in another pig farm.
Factors related to exposure from other outbreak farms and cases in wild boar
The proximity of both outbreaks in domestic farms and/or wild boar cases were shown to be significant risk factors for ASF incursion in both Romanian backyard and commercial farms. The influence of outbreaks in domestic pigs in the model reflected the larger number of outbreaks in Romania compared to other European countries. However, the proximity of outbreaks in domestic farms and wild boar cases should be considered a proxy for the presence of ASF virus in the area. In other countries, with more wild boar cases and fewer outbreaks in domestic farms, the relative contribution of wild boar cases and wild boar abundance compared to outbreaks in domestic farms would most likely be more important. However, both covariates together are considered a proxy of the presence of ASF virus in the areas, and therefore we expect the results to be of value also for these countries.
In this study, ASF virus circulation in domestic farms in the proximity to the study farm was presumed to be correlated with the number of outbreaks in domestic pig farms within 2 km, the distance to the nearest outbreak in a domestic pig farm, and the density of pigs and farms. Similarly, the risk of ASF virus from wild boar surrounding the farm was presumed to be correlated with the distance to the nearest case of ASF in wild boar, wild boar abundance in the area surrounding the farm, wild boar seen in the surroundings of the farm, and the growing of crops attractive to wild boar near the backyard. In the final multivariate model, ASF virus in domestic farms were described by the number of outbreaks in domestic pig farms within 2 km, the distance to the nearest outbreak in a domestic pig farm. The risk of ASFV from wild boar surrounding the farm was described by the distance to the nearest case of ASF in wild boar, wild boar abundance in the area surrounding the farm, and the growing of crops attractive to wild boar near the backyard. The sensitivity of the surveillance system in domestic pig farms is expected to be high, as clinical surveillance must be performed in all pig farms in the zones around outbreak farms on a regular basis, while the sensitivity of the surveillance in wild boar is expected to be lower. It has been stated that “nothing is easier than to ignore a rotten, smelly wild boar carcass in a forest”15, and that the goal in passive surveillance of wild boar should be to find and investigate 10% of the carcasses15. This difference in surveillance sensitivity between domestic farms and wild boars contributed to decision-making during model building. Because the sensitivity of wild boar surveillance is lower, we sought to include several indirect measures of wild boar presence in the model, rather than focusing solely on direct measures, such as detected wild boar cases. Martinez-Lopez et al.16 found that communes with a number of closed herds above the median on Sardinia to have increased risk of ASF. However, their analysis was performed on commune level and therefore distance to other outbreaks was not included in the model.
For the calculation of the nearest distance to outbreaks in domestic pigs and wild boar cases, only outbreaks and cases diagnosed in the high-risk period were included. This was based on the assumption that outbreaks and cases diagnosed after the farm was infected could not have influenced the risk of ASF incursion. The high-risk period of six weeks in commercial farms was based on mortality data from one large commercial farm (unpublished data). However, the time from infection to detection in Estonian outbreak farms was estimated to be short, i.e. <7 days4, while Guinat et al. described by simulation studies that ASF virus could be circulating for nearly a month before mortality increased markedly17, and Halasa et al. similarly simulated the time between infection and detection to a median of 24 days18. Furthermore, in the analyses of Estonian data, all wild boar cases within a year before a farm was diagnosed with ASF were included in the analysis. The exact duration of the high-risk period can be difficult to determine, due to the short clinical phase and high mortality of ASF19, which especially in large farms can lead to an increase in herd mortality which is not immediately recognized as a consequence of ASF. If the length of the high-risk period is overestimated, this can lead to inclusion of risk factors, which in reality could not have influenced disease incursion. In contrast, an underestimation of the length of the high-risk period could potentially result in important risk factors being missed. Still, even with this uncertainty, the distance to the nearest domestic outbreaks and wild boar cases as well as the number of outbreaks in the area around the farm can be interpreted as a proxy for the amount of ASF virus circulating in the area.
Factors related to human activity and management
In this study, the number of professional visitors during the high-risk period was identified as a risk factor for ASF occurrence in backyard farms (Table 1). Similar results were found in a matched case-control study from Nigeria20. And experimental studies have indicated that indirect transmission of ASF virus to pigs introduced to a contaminated pen can only happen shortly after the pen has become contaminated (after 1 days)21. This suggests that swine professionals visiting several backyard farms on the same day may have contributed to the incursion of ASF.
The feeding of fresh forage (e.g. hay or grass) to pigs in backyard farms that had been harvested in areas affected by ASF was found to be a significant risk factor (Table 1). This is an important outcome and similar observations have been reported from Latvia and Lithuania2. In combination with growing attractive crops around the farm, this could explain the seasonal character of the disease. Seasonality of ASF in domestic pigs has been a clear observation of the ASF epidemic in the EU14.
In contrast, the use of straw was negatively correlated with the incursion of ASF in backyard farms in the model. The reason for this is unclear. It could be hypothesized that this was a confounding factor related to other husbandry factors, which could have protected the farms for ASF incursion but were not included in the interview. In addition, it could be hypothesized that the probability that straw contains infectious ASF virus is very low, due to the longer harvesting period, in generally warm weather conditions, which could inactivate the virus, as compared to freshly cut grass. ASF virus has previously been shown to be transmitted to pigs eating stable flies (Stomoxys calcitrans) spiked with ASF virus8. It could be hypothesized that use of straw as bedding would attract fewer flies than concrete floors with manure, or that straw could lead to activation of the pigs, and following that the probability of the pigs catching and eating flies or finding dead flies on the ground would decrease. However, this is very speculative and needs more investigation.
ASF virus can survive for long periods in meat from infected pigs7, and swill feeding has frequently been implicated in the spread of ASF7,22, especially as the source of initial introduction into new countries23. Furthermore, a study on the relation between hypothesized risk factors and ASF on commune level in Sardinia showed that a high number of closed farms per commune was related to higher risk of ASF, and the authors suggested that swill feeding might be more common in closed small-scale farms16. Although swill-feeding was statistically significant in the univariate analyses, it did not remain in the final multivariate model. This contradiction could be based on the feeding of swill that did not contain pork or at least did not contain ASF virus. However, there has been a total ban on swill-feeding in EU since 200224; no animal protein can be fed to the same species (Article 22 of Regulation 1774/2002/EC), e.g. no pig protein or catering waste (i.e. waste food originating in restaurants, catering facilities and kitchens, including central kitchens and household kitchens) can be fed to pigs. Still, in this study we found that 71 Romanian farms fed swill to pigs, especially backyard farms. Therefore, further initiatives to explaining the regulation and the risk related to swill feeding is needed.
Herd size as a risk factor
Among Romanian backyard farms, outbreak farms were significantly larger than control farms. A survival analysis from Estonia also showed that large farms were at higher ASF risk4. However, the Estonian farms categorized as large were 101–1000 pigs or >1000 pigs, while in our study, herd size was included as continuous variable and backyard and commercial farms were analyzed separately. In our study, herd size in outbreak farms originated from ADNS data, while herd size in control farms originated from the questionnaires. These different sources are not expected to cause differences, as the numbers in ADNS from outbreak farms were reported shortly before or at the same time as the questionnaires were filled for control farms. Furthermore, the relation between ASF occurrence and herd size was in accordance with the experience from the Romanian official veterinarians carrying out the epidemiological outbreak investigations in outbreak farms.
Herd sizes overlapped between backyard farms and commercial farms, with up to 454 pigs in the largest backyard farm and no more than 24 pigs in the smallest commercial farm. Furthermore, type A farms, which in the analyses were categorized as commercial farms, were somewhat in between in size, ranging from 1 to 106 pigs. Our differentiation between backyards and commercial was based on current herd types in the Romanian herd register and on which level of biosecurity could be expected in each type of farm. Furthermore, we took into account the relevance of different types of questions for each type of farm, e.g. questions on biosecurity would most often not be relevant for backyard farms. However, in order to extrapolate and to compare to other countries or areas, classification of herd types based on numbers of pigs would often be clearer. On the contrary, small-scale farming varies in different areas of Europe, from the free-ranging extensive production system of Sardinia25 to pot-bellied pigs kept as pets in Northern Europe. Additionally, the numbers of commercial outbreak farms were limited, leading us to increase the numbers of controls per outbreak to have some statistical power in the analyses of the questionnaires completed on commercial farms. Still, it was only possible to show statistical significance of one variable, i.e. the logarithm of the distance to the nearest outbreak in domestic pigs. This finding might be caused by the limited numbers of commercial outbreak farms included, i.e. the statistical power of the analyses is too small to reveal other risk factors.
Possible transmission routes involved in ASF incursions in romania
Although the final model included several risk factors describing the virus load in the surroundings, we still lack knowledge on how the virus is transmitted from the surroundings into the farm. Many of the transmission routes, which could bring the virus from the surroundings into the farm, were already included in the study, but were not statistically significant (Supplementary Table S1). However, other transmission routes, such as the farmer carrying the virus in boots or equipment, were not included for backyard farms. Furthermore, aerosol transmission from pen to pen has been demonstrated in experimental studies10, and the common stable fly (Stomoxis calcitrans) has been shown to transmit ASF virus mechanically by biting susceptible pigs or by being eaten by pigs8,9.
It was not possible to perform an entomological survey on the outbreak and control farms. Therefore, during each interview, estimates were made of the number of ticks in cracks on the wall and in the ground of the pig sheds as well as on the pigs, and the numbers of biting midges and mosquitoes observed on the farm, as a proxy of the number of vectors on the farm.
Neither biting midges nor mosquitoes were significant in the analyses. However, flying insects have previously been shown able to act as mechanical vectors over short distances8,9, DNA from ASF virus have been found in insects at ASF infected farms26, and the seasonality in domestic farms might indicate importance of insects14. Therefore, further field studies on the role of insects in ASF spread are needed.
Although the number of ticks (both on the animals and in the environment) was relatively higher in the outbreak farms (Tables 1 and 2) and borderline significant in the univariate analyses, this was not a significant risk factor in the multivariate analyses. Soft ticks are most often nest parasites, meaning that they reside in sheltered environments such as burrows, caves or cracks. Therefore, soft ticks are not expected to influence the risk of ASF introduction into pig farms. As hard ticks do not replicate ASF virus27, ticks of this type can theoretically be expected only to be able to act as mechanical vectors27,28.
Source: Ecology - nature.com
