Suwicha Kasemsuwan

Social Network Analysis for Assessment of Avian Influenza Spread and Trading Patterns of Backyard Chickens in Nakhon Pathom, Suphan Buri and Ratchaburi, Thailand

The aim of this study is to explain the social networks of the backyard chicken in Ratchaburi, Suphan Buri and Nakhon Pathom Provinces. In this study, we designed the nodes as groups of persons or places involved in activities relating to backyard chickens. The ties are all activities related to the nodes. The study applied a partial network approach to assess the spreading pattern of avian influenza. From 557 questionnaires collected from the nodes, the researchers found that the degree (the numbers of ties that a node has) and closeness (the distance from one node to the others) centralities of Nakhon Pathom were significantly higher than those of the others (P < 0.001). The results show that compared with the remaining areas, this area is more quickly connected to many links. If the avian influenza virus subtype H5N1 was released into the network, the disease would spread throughout this province more rapidly than in Ratchaburi and Suphan Buri. The betweenness centrality in each of these provinces showed no differences (P > 0.05). In this study, the nodes that play an important role in all networks are farmers who raise consumable chicken, farmers who raise both consumable chicken and fighting cocks, farmers’ households that connect with dominant nodes, and the owners and observers of fighting cocks at arenas and training fields. In this study, we did not find cut points or blocks in the network. Moreover, we detected a random network in all provinces. Thus, connectivity between the nodes covers long or short distances, with less predictable behaviour. Finally, this study suggests that activities between the important nodes must receive special attention for disease control during future disease outbreaks.

Comparative study of heavy metal and pathogenic bacterial contamination in sludge and manure in biogas and non-biogas swine farms

The objective of this study is to determine and compare the heavy metal (Zn, Cu, Cd, Pb) and bacterial (E. coli, coliform and Salmonella spp.) contamination between swine farms utilizing biogas and non-biogas systems in the central part of Thailand. Results showed that average levels of E. coli, coliform, BOD, COD, Zn, Cu and Pb in sludge from the post-biogas pond were higher than the standard limits. Moreover, the levels of E. coli, coliform, Cd and Pb were also higher than the standard limits for dry manure. The levels of E. coli, coliform and BOD on biogas farms were lower than on non-biogas farms. Following isolation of Salmonella spp., it was found that Salmonella serovars Rissen was the most abundant at 18.46% (12/65), followed by Anatum 12.31% (8/65), and Kedougou 9.23% (6/65). The pathogenic strains of Salmonella serovars Paratyphi B var. java and Typhimurium were present in equal amounts at 4.62% (3/65) in samples from all swine farms. This study revealed that significant reduction in E. coli and coliform levels in sludge from covered lagoon biogas systems on swine farms. The presence of Salmonella as well as Cd and Pb, in significant amount in dry manure, suggests that there is a high probability of environmental contamination if it is used for agricultural purposes. Thus, careful waste and manure disposal from swine farms and the regular monitoring of wastewater is strongly recommended to ensure the safety of humans, other animals and the environment.

Zero-inflated models for identifying disease risk factors when case detection is imperfect: application to highly pathogenic avian influenza H5N1 in Thailand.

Logistic regression models integrating disease presence/absence data are widely used to identify risk factors for a given disease. However, when data arise from imperfect surveillance systems, the interpretation of results is confusing since explanatory variables can be related either to the occurrence of the disease or to the efficiency of the surveillance system. As an alternative, we present spatial and non-spatial zero-inflated Poisson (ZIP) regressions for modelling the number of highly pathogenic avian influenza (HPAI) H5N1 outbreaks that were reported at subdistrict level in Thailand during the second epidemic wave (July 3rd 2004 to May 5th 2005). The spatial ZIP model fitted the data more effectively than its non-spatial version. This model clarified the role of the different variables: for example, results suggested that human population density was not associated with the disease occurrence but was rather associated with the number of reported outbreaks given disease occurrence. In addition, these models allowed estimating that 902 (95% CI 881-922) subdistricts suffered at least one HPAI H5N1 outbreak in Thailand although only 779 were reported to veterinary authorities, leading to a general surveillance sensitivity of 86.4% (95% CI 84.5-88.4). Finally, the outputs of the spatial ZIP model revealed the spatial distribution of the probability that a subdistrict could have been a false negative. The methodology presented here can easily be adapted to other animal health contexts.

Spatial analysis and characteristics of pig farming in Thailand

BackgroundIn Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Strategies toward more sustainable future developments are currently investigated, and these could be informed by a detailed assessment of the main trends in the pig sector, and on how different production systems are geographically distributed. This study had two main objectives. First, we aimed to describe the main trends and geographic patterns of pig production systems in Thailand in terms of pig type (native, breeding, and fattening pigs), farm scales (smallholder and large-scale farming systems) and type of farming systems (farrow-to-finish, nursery, and finishing systems) based on a very detailed 2010 census. Second, we aimed to study the statistical spatial association between these different types of pig farming distribution and a set of spatial variables describing access to feed and markets.ResultsOver the last decades, pig population gradually increased, with a continuously increasing number of pigs per holder, suggesting a continuing intensification of the sector. The different pig-production systems showed very contrasted geographical distributions. The spatial distribution of large-scale pig farms corresponds with that of commercial pig breeds, and spatial analysis conducted using Random Forest distribution models indicated that these were concentrated in lowland urban or peri-urban areas, close to means of transportation, facilitating supply to major markets such as provincial capitals and the Bangkok Metropolitan region. Conversely the smallholders were distributed throughout the country, with higher densities located in highland, remote, and rural areas, where they supply local rural markets. A limitation of the study was that pig farming systems were defined from the number of animals per farm, resulting in their possible misclassification, but this should have a limited impact on the main patterns revealed by the analysis.ConclusionsThe very contrasted distribution of different pig production systems present opportunities for future regionalization of pig production. More specifically, the detailed geographical analysis of the different production systems will be used to spatially-inform planning decisions for pig farming accounting for the specific health, environment and economical implications of the different pig production systems.

Social network analysis of food sharing among households in opisthorchiasis endemic villages of Lawa Lake, Thailand

Consumption of raw fish is a well-documented risk factor for Opisthorchis viverrini infection. Sharing of food, especially raw fish recipes may influence the spread of disease through a community. Using social network analysis of an ego network, we investigated food sharing among households in an Opisthorchis-endemic area. Network centrality properties were used to explain the differences in O. viverrini transmission and control between villages with a low and high prevalence of infection. Information on demography and O. viverrini infection in 2008 from villagers in the Lawa Lake area was extracted from the Tropical Disease Research Center database. The two villages that had the lowest and the highest O. viverrini infection at the household level were recruited. Ten percent of households of each village were randomly sampled. Participatory epidemiology and face-to-face structured interviews guided by a social network questionnaire were used to collect data on livelihood, agricultural patterns, food sources, raw fish eating habits, and other food sharing during daily life and social gatherings. The number of contacts including in-degree and out-degree varied from 0 to 7 in the low-infection village and 0 to 4 in the high-infection village. The mean number of contacts for the food-sharing network among the low- and high-infection villages was 1.64 and 0.73 contacts per household, respectively. Between these villages, the mean number of out-degree (p=0.0125), but not in-degree (p=0.065), was significantly different. Food-sharing differed in numbers of sharing-in and sharing-out between the two villages. Network analysis of food sharing may be of value in designing strategies for opisthorchiasis control at the community level.

Social network analysis of cattle movement in Kampong Cham, Kampong Speu and Takeo, Cambodia.

The aim of this study is to provide insight the network of cattle movement in Kampong Cham, Kampong Speu and Takeo, Cambodia. A cross-sectional study was carried out from July 2014 to August 2014, using questionnaires. It was implemented with 435 interviewees (24.4%, 24.6% and 51.0% from Kampong Cham, Kampong Speu and Takeo, respectively) using one-step snowball sampling. The findings suggest that the key players in all three provinces are producers who raise their cattle as backyard animals. In all three provinces the key players in spreading disease are probably the middlemen, collectors, brokers or traders. The network of cattle movement is presented as a strong component of varying size in each location. In this network we found three cut-points in both Kampong Cham and Kampong Speu. The network in each province indicates a random pattern of node distribution. The results of our study are useful to relevant authorities and researchers to understand the spread of infectious diseases into different areas. The middlemen, collectors, brokers and traders need to be controlled as first priority in order to reduce the magnitude of the spread of disease.

Social Influence in Liver Fluke Transmission: Application of Social Network Analysis of Food Sharing in Thai Isaan Culture

In northeastern Thai (Isaan) culture traditional raw fish dishes and raw fish-eating habits are common. Eating and sharing meals together among the communitys members, especially relatives and neighbours, are a common practice in both daily life and social gathering events. Fish are a significant protein source and are associated with variety of traditional recipes. Cyprinid fish are one of the most preferred fish by Isaan villagers for daily consumption because they are accessible and affordable. Consumption of these fish probably causes the persistence of high endemicity of human liver fluke infection, particularly with Opisthorchis viverrini, in northeast Thailand. Because the consumption of raw cyprinid fish is a well-documented risk factor for liver fluke infection, sharing of risky raw fish dishes may influence disease transmission through a community. Social network analysis was used to investigate fish and fish-based meal sharing among household members in Isaan villages in liver fluke endemic areas. The findings from three studies confirmed the persistence of traditional Isaan raw fish consumption and food-sharing practice. Social connections via food sharing among villagers played an important role in liver fluke infection and transmission dynamics as a risk factor. Thus these sociocultural factors should be taken into account in designing strategies for control of opisthorchiasis and other food-borne illnesses at the community level. Abstract In northeastern Thai (Isaan) culture traditional raw fish dishes and raw fish-eating habits are common. Eating and sharing meals together among the communitys members, especially relatives and neighbours, are a common practice in both daily life and social gathering events. Fish are a significant protein source and are associated with variety of traditional recipes. Cyprinid fish are one of the most preferred fish by Isaan villagers for daily consumption because they are accessible and affordable. Consumption of these fish probably causes the persistence of high endemicity of human liver fluke infection, particularly with Opisthorchis viverrini, in northeast Thailand. Because the consumption of raw cyprinid fish is a well-documented risk factor for liver fluke infection, sharing of risky raw fish dishes may influence disease transmission through a community. Social network analysis was used to investigate fish and fish-based meal sharing among household members in Isaan villages in liver fluke endemic areas. The findings from three studies confirmed the persistence of traditional Isaan raw fish consumption and food-sharing practice. Social connections via food sharing among villagers played an important role in liver fluke infection and transmission dynamics as a risk factor. Thus these sociocultural factors should be taken into account in designing strategies for control of opisthorchiasis and other food-borne illnesses at the community level.

Cultural Practices Shaping Zoonotic Diseases Surveillance: The Case of Highly Pathogenic Avian Influenza and Thailand Native Chicken Farmers.

Effectiveness of current passive zoonotic disease surveillance systems is limited by the under-reporting of disease outbreaks in the domestic animal population. Evaluating the acceptability of passive surveillance and its economic, social and cultural determinants appears a critical step for improving it. A participatory rural appraisal was implemented in a rural subdistrict of Thailand. Focus group interviews were used to identify sanitary risks perceived by native chicken farmers and describe the structure of their value chain. Qualitative individual interviews with a large diversity of actors enabled to identify perceived costs and benefits associated with the reporting of HPAI suspicions to sanitary authorities. Besides, flows of information on HPAI suspected cases were assessed using network analysis, based on data collected through individual questionnaires. Results show that the presence of cockfighting activities in the area negatively affected the willingness of all chicken farmers and other actors to report suspected HPAI cases. The high financial and affective value of fighting cocks contradicted the HPAI control policy based on mass culling. However, the importance of product quality in the native chicken meat value chain and the free veterinary services and products delivered by veterinary officers had a positive impact on suspected case reporting. Besides, cockfighting practitioners had a significantly higher centrality than other actors in the information network and they facilitated the spatial diffusion of information. Social ties built in cockfighting activities and the shared purpose of protecting valuable cocks were at the basis of the diffusion of information and the informal collective management of diseases. Building bridges with this informal network would greatly improve the effectiveness of passive surveillance.

Methods for Prioritisation of Diseases: Case Study of Zoonoses in Southeast Asia

Prioritisation of diseases is an essential tool for policy-makers in charge of allocating resources for surveillance and control programmes or for research projects, to target diseases that need to be addressed ahead of others. Nevertheless, methods for prioritisation need to be transparent, standardised and repeatable to be effective and objective in setting priorities. To date, various models have been developed, experimenting different approaches, but it remains some room for improvement in the design of such tools. The definition of the criteria – indicators used to assess diseases regarding the objective of the prioritisation exercise – is one of the cornerstones of the efficiency of the methodology. In previous developed methods, this step was usually poorly addressed and up to now, no standardised method has been developed and described to select relevant and accurate criteria. Through the use of an electronic-based questionnaire to collect data about criteria from a large population of respondents, this study, based on the analysis of zoonoses and their impact in Southeast Asia, aimed at investigating an innovative approach to identify criteria that ensure a good differentiation between the diseases. The findings of this study highlighted that refining an initial list of criteria using multivariate analysis was a reliable approach to select clear, accurate and relevant criteria that allow a differentiation between diseases for a further prioritisation exercise. Furthermore, this study indicated that using an electronic-based questionnaire, carefully designed, might be an interesting alternative of expert opinion elicitation, for the collection of data. Finally, the results of this study opened to other new perspectives to develop and improve methods for the prioritisation of infectious diseases.