Acute hepatopancreatic necrosis disease (AHPND) is an emerging bacterial infection in shrimp that has been widespread across the major world shrimp producing countries since 2009. AHPND epizootics have resulted in a huge loss of global shrimp production, similar to that caused by white spot disease in the 1990’s. The epizootiological understanding of the spread of AHPND is still in its early stages, however, and most of the currently published research findings are based on experimental studies that may struggle to capture the potential for disease transmission at the country scale. The main aim of this research, therefore, is to develop epizootiological tools to study AHPND transmission between shrimp farming sites. Some tools used in this research have already been applied to shrimp epizoology, but others are used here for the first time to evaluate the spread of shrimp diseases. According to an epizootiological survey of AHPND in Thailand (Chapter 3), the first case of AHPND in the country was in eastern shrimp farms in January 2012. The disease was then transmitted to the south in December 2012. The results obtained from interviews, undertaken with 143 sample farms were stratified by three farm-scales (large, medium and small) and two locations (east and south). Both the southern location and large-scale farming were associated with a delay in AHPND onset compared with the eastern location and small- and medium-scale farming. The 24 risk factors (mostly related to farming management practices) for AHPND were investigated in a cross-sectional study (Chapter 3). This allowed the development of an AHPND decision tree for defining cases (diseased farms) and controls (non-diseased farms) because at the time of the study AHPND was a disease of unknown etiology. Results of univariate and unconditional logistic regression models indicated that two farming management practices related to the onset of AHPND. First, the absence of pond harrowing before shrimp stocking increased the risk of AHPND occurrence with an odds ratio () of 3.9 (95 % CI 1.3–12.6; P‑value = 0.01), whereas earthen ponds decreased the risk of AHPND with an of 0.25 (95 % CI 0.06–0.8; P‑value = 0.02). These findings imply that good farming management practices, such as pond-bottom harrowing, which are a common practice of shrimp farming in earthen ponds, may contribute to overcoming AHPND infection at farm level. For the purposes of disease surveillance and control, the structure of the live shrimp movement network within Thailand (LSMN) was modelled, which demonstrated the high potential for site-to-site disease spread (Chapter 4). Real network data was recorded over a 13-month period from March 2013 to March 2014 by the Thailand Department of Fisheries. After data validation, c. 74 400 repeated connections between 13 801 shrimp farming sites were retained. 77 % of the total connections were inter-province movements; the remaining connections were intra-province movements (23 %). The results demonstrated that the LSMN had properties that both aided and hindered disease spread (Chapter 4). For hindering transmission, the correlation between and degrees was weakly positive, i.e. it suggests that sites with a high risk of catching disease posed a low risk for transmitting the disease (assuming solely network spread), and the LSMN showed disassortative mixing, i.e. a low preference for connections joining sites with high degree linked to connections with high degree. However, there were low values for mean shortest path length and clustering. The latter characteristics tend to be associated with the potential for disease epidemics. Moreover, the LSMN displayed the power-law in both and degree distributions with the exponents 2.87 and 2.17, respectively. The presence of power-law distributions indicates that most sites in the LSMN have a small number of connections, while a few sites have large numbers of connections. These findings not only contribute to a better understanding of disease spread between sites, therefore, but also reveal the importance of targeted disease surveillance and control, due to the detection of scale-free properties in the LSMN. Chapter 5, therefore, examined the effectiveness of targeted disease surveillance and control in respect to reducing the potential size of epizootics in the LSMN. The study untilised network approaches to identify high-risk connections, whose removal from the network could reduce epizootics. Five disease-control algorithms were developed for the comparison: four of these algorithms were based on centrality measures to represent targeted approaches, with a non-targeted approach as a control. With the targeted approaches, technically admissible centrality measures were considered: the betweenness (the number of shortest paths that go through connections in a network), connection weight (the frequency of repeated connections between a site pair), eigenvector (considering the degree centralities of all neighbouring sites connected to a specified site), and subnet-crossing (prioritising connections that links two different subnetworks). The results showed that the estimated epizootic sizes were smaller when an optimal targeted approach was applied, compared with the random targeting of high-risk connections. This optimal targeted approach can be used to prioritise targets in the context of establishing disease surveillance and control programmes. With complex modes of disease transmission (i.e. long-distance transmission like via live shrimp movement, and local transmission), an compartmental, individual-based epizootic model was constructed for AHPND (Chapter 6). The modelling uncovered the seasonality of AHPND epizootics in Thailand, which were found likely to occur between April and August (during the hot and rainy seasons of Thailand). Based on two movement types, intra-province movements were a small proportion of connections, and they alone could cause a small AHPND epizootic. The main pathway for AHPND spread is therefore long-distance transmission and regulators need to increase the efficacy of testing for diseases in farmed shrimp before movements and improve the conduct of routine monitoring for diseases. The implementation of these biosecurity practices was modelled by changing the values of the long-distance transmission rate. The model demonstrated that high levels of biosecurity on live shrimp movements (1) led to a decrease in the potential size of epizootics in Thai shrimp farming. Moreover, the potential size of epizootics was also decreased when AHPND spread was modelled with a decreased value for the local transmission rate. Hence, not only did the model predict AHPND epizootic dynamics stochastically, but it also assessed biosecurity enhancement, allowing the design of effective prevention programmes. In brief, this thesis develops tools for the systematic epizootiological study of AHPND transmission in Thai shrimp farming and demonstrates that: (1) at farm level, current Thai shrimp farming should enhance biosecurity systems even in larger businesses, (2) at country level, targeted disease control strategies are required to establish disease surveillance and control measures. Although the epizootiological tools used here mainly evaluate the spread of AHPND in shrimp farming sites, they could be adapted to other infectious diseases or other farming sectors, such as the current spread of tilapia lake virus in Nile tilapia farms.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:736845 |
| Date | January 2017 |
| Creators | Saleetid, Nattakan |
| Contributors | Green, Darren ; Murray, Francis |
| Publisher | University of Stirling |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1893/26828 |
Page generated in 0.002 seconds