These lessons would apply not only to PMCV, but also to infectious diseases whose spread is predominantly via fish movement . The decision to use a susceptible-infected over a susceptible-infected-susceptible model for within-farm spread was based on the fact that different experimental studies have found the viral genome present in tissues of challenged fish throughout the whole duration of the study, indicating that the salmon immune response may be unable to eliminate the virus . This, together with studies where PMCV has been consistently found in cohorts of fish sampled through long periods of time, indicating that PMCV can be present in fish for some months , provides further support for the modeling approach used here. Nevertheless, more research is required to further validate or refute this modeling choice, as it is possible that fish clear the infection beyond the time frames used in both experimental and observational studies. The model was sensitive to changes in the values of the indirect transmission rate, rate of decay in environmental infectious pressure, and the rate of viral shedding from infected individuals, but not to changes in the level of spatial coupling . Model outputs were also not substantially influenced by different parameter assumptions regarding either distance or seasonality , noting that information about distance thresholds was derived from other viral infections such as infectious salmon anemia , where estimates have varied from 5 to 20 km or more . Collectively, these results suggest that local spread may play a secondary role in the spread of PMCV across the Atlantic salmon farms in the country. When local spread was removed completely from the model , it was even clearer that this transmission pathway under current model assumptions was not the most important. On the basis of these results, greenhouse bench top we hypothesize that the widespread presence of PMCV in Ireland is most likely a product of the shipments of infected but subclinical fish through the network of live fish movements that occur in Ireland.
This is consistent with fish being infected but subclinical for months prior to manifesting signs of disease , and by the structure of the network of live fish movements in the country . There is limited knowledge of agent survival of PMCV in the aquatic environment. Infection risk is higher on farms with a history of CMS outbreaks , which could suggest survival of the causal agent in the local environment. Further, infection pressure from farms within 100 km of seaway distance was found to be one of the most important risk factors for clinical CMS diagnosis , although this study did not evaluate spread via fish movement. It is noted that the distance over which infection can be transmitted via water is determined by an interaction between hydrodynamics, viral shedding and decay rates . Further research on PMCV survival in the environment is needed to guide parameterization of future models. The most effective intervention strategies are based on outdegree and outcloseness , with the highest impact being observed when using these intervention strategies with a proactive approach . Note that all outgoing shipments from selected farms are assumed to include only susceptible fish , which can be equated with high levels of bio-security. The outdegree and outcloseness based strategies are comparable, most likely because both strategies refer to outgoing shipments from a farm , the former with the number of farms receiving fish from a given source, and the latter inversely related to the number of intermediaries between the source and the rest of the farms in the network. Both centrality measures were moderately correlated with each other, with a Pearson correlation of 0.53 for the proactive approach when including all farms for each time window used. Based on a closer examination of the top eight farms of each list, for every year , one list always included at least the top three elements of the other. In other words, each list contained the top three farms in terms of outdegree and the top three farms in terms of outcloseness. Further iterations of this model could exploit the similarity between ranks of farms based on these two centrality measures, for example evaluating the effect of targeting a lower number of farms based on a list created from the top elements of both rankings. For the case presented here , either centrality measure could be used.
Being this the case, we would advocate for the use of outdegree over outcloseness, given its simplicity of estimation and understanding. The proportion of farms connected via live fish movements varied in a cyclical manner, with spikes during the periods of January-April, July, and October-December, which is consistent with results from our previous descriptive study of the network of live fish movements in Ireland . Interventions could be considered that specifically apply at these times of higher connectivity between farms, to take account of this observed cyclicity. The remaining between-farm prevalence levels observed after the implementation of this targeted strategies is due to residual infectious pressure and local spread, where PMCV is not fully cleared from the environment between generations of fish, allowing its transmission to newly stocked fish and locally between neighboring farms. Similarly, the lower performance of the reactive approach, even if all transmission via fish movements is halted suggests that eradication of PMCV is virtually impossible in Ireland, as it seems that after elimination of transmission via fish movements, the agent is consistently sustained by local spread . The lack of complete production records for all Irish Atlantic salmon farms was the main reason for using movement records to recreate fish population dynamics. Nevertheless, we consider that the rules as applied in this study were realistic. For example, if a farm ships fish in excess of the total fish population at the time of the shipment, it is reasonable to assume that these fish must have originated at a previous time. The options for this origin are either non-recorded, incoming fish shipments or hatching of new fish. In the case of the latter, this is perfectly reasonable if the fish deficit at the farm is due to a shipment of eggs. However, if the deficit is due to a shipment of older fish , assigning an enter event for this age groups is not realistic. Nevertheless, in the absence of records accounting for the origin of fish sent in these age groups, this seemed like a better approach than arbitrarily imputing their origin to another farm, which in turn would have created fish deficits in other farms cascading to the rest of the network. Arguably, the availability of complete production records from all Irish salmon farms would minimize this issue, although making such records available for a 9-year time period would pose a hefty burden on fish farmers. Additionally, botanicare rolling benches we assert that the impact of our imputation is marginal, considering that only 90 enter events were imputed during the study period , mostly at the beginning of the simulation , and involving mainly fertilized eggs in freshwater farms. This is further evident when evaluating the generated population dynamics, like the number of fish in each age group and the timing of fish enter events , where the abundance of each age group and the enter events follow a seasonal pattern that would be expected given the life cycle of farmed Atlantic salmon. Assigning exit events the day before the last fish shipment of a fish cohort was a simplification necessary for allowing farms not to overpopulate as the simulation proceeded.
The impact of assuming all fish within a cohort were present until the day before shipping is hard to gauge, but we think it would be a small effect, especially considering the large fish populations involved in salmon farming. Future iterations of this model could include a mortality function fitted from the data, or even better, real mortality data from fish farm production records, if available. One of the assumptions of the intervention strategies used in this study is that they are 100% effective in eliminating transmission between farms via fish movements. In order to achieve a similar level of effectiveness in the field, it would require screening of all fish shipments with a highly sensitive test before they exit the origin farm, and elimination of all positive batches . The sensitivity of currently used diagnostic methods is not reported in the literature, but one could arguably assume that the RT-PCR method for detection of the virus has a high sensitivity given its capacity to measure viral RNA, which may or may not be present within a virion that is able to replicate. Currently there are no confirmatory tests for PMCV, and diagnosis of the clinical disease is based on clinical observations, necropsy, and histopathological findings . As for diagnosing latently or subclinically infected fish, this would pose a great challenge today, as there are no cell cultures or other methods that could assist in such a task, which is particularly important for the correct diagnosis of the agent on the early stages of fish life, namely eggs, juvenile fish, and smolts. Further, even if accurate diagnostic tests were available, the feasibility of discarding all infected fish consignments is doubtful, as it would impose a heavy burden on fish farmers, especially considering the modeled current levels of PMCV prevalence. Nonetheless, it does suggest a clear path to prevent the spread of exotic infectious agents in Ireland, such as ISA virus, piscine reovirus , and others. For these agents, targeted surveillance strategies could be implemented based on the top ranked farms in terms of outdegree as described above, which would allow for a timely detection and prevention of further spread across the country. In conclusion, in this study we highlight the importance of human-assisted live fish movement for the dissemination of PMCV across the country, and demonstrate a means, using centrality based targeted surveillance strategies, to prevent this type of spread in the future for other infectious disease agents. These strategies should be applied early on in the epidemic process, before country-wide dissemination of the agent has taken place. The Irish salmon farming industry would benefit from this approach, as it would help in the early detection and prevent the spread of exotic viral agents which have the potential to severely impact local farms and the livelihoods of people that depend on them. This in turn would make Irish salmon farming a more robust and sustainable industry, capable of dealing with infectious agents in a timely and effective way, minimizing socioeconomic and environmental losses, and maximizing fish health and welfare. The literature documents high incidence of low back disorders in the agricultural industry . A national survey in the U.S. shows that, for males, farming is the occupation with the fifth highest risk of inducing low back pain . It has been suggested that the preponderance of the morbidity is related to farm workers’ working conditions, such as stooped working postures and awkward postures during lifting, carrying, and moving loads . Such hazards, however, affect both adult and youth workers. Estimates show that each year in the United States, more than 2 million youths under the age of 20 are exposed to such agricultural hazards . These youths perform many farm-related activities involving significant manual handling of materials and are exposed to factors found to be related to the development of musculoskeletal disorders and LBDs . For instance, emptying a bag of swine feed into a feeder, spreading straw, and shoveling silage into a feed bunk are all reported as causes of serious back injuries . It might be useful to first define terms commonly used in reference to workers based on their age. The term “legal adult” or “age of majority” is the threshold of adulthood as declared by law . This age varies based on geographical regions and may have several age-based restrictions . In most circumstances, “adult” is usually in reference to the age of majority, or one of its exception, and not the biological adult age. According to the National Institutes of Health , the term “child” is an individual under the age of 21, where the definition spans the period from birth to the age where most children are dependent on their parents .