Transboundary and Emerging Diseases

ORIGINAL ARTICLE

Knowledge, Attitudes and Practices Related to African Swine Fever Within Smallholder Pig Production in Northern Uganda E. Chenais1,2, S. Boqvist2, S. Sternberg-Lewerin2, U. Emanuelson2, E. Ouma3, M. Dione3, T. Aliro4, F. Crafoord5, C. Masembe6 and K. St ahl1,2 1 2 3 4 5 6

National Veterinary Institute, Uppsala, Sweden Swedish University of Agricultural Sciences, Uppsala, Sweden International Livestock Research Institute, Kampala, Uganda Directorate of Production and Marketing, Gulu District Local Government, Gulu, Uganda Distriktsveterin€ arerna, Flen, Sweden Makerere University, Kampala, Uganda

Keywords: knowledge, attitudes and practice; family farm; participatory epidemiology; participatory rural appraisal; biosecurity Correspondence: E. Chenais. National Veterinary Institute, SVA, S-751 89 Uppsala, Sweden. Tel.: +4618674615; Fax: +4618674445; E-mail: [email protected] Work Carried out: National Veterinary Institute, S-751 89 Uppsala, Sweden and Swedish University of Agricultural Sciences, S-750 07 Uppsala. Received for publication November 14, 2014 doi:10.1111/tbed.12347

Summary Uganda is a low-income country with the largest pig population in East Africa. Pig keeping has a large potential, commercially and as a tool for poverty reduction, but African swine fever (ASF) is a major hurdle for development of the sector. The objective of this study was to evaluate knowledge, attitudes and practices related to ASF in the smallholder pig production value chain in northern Uganda. The study included three separate series of participatory rural appraisals (PRA), comprising purposively selected farmers and other actors in the pig production value chain. In the PRAs, various participatory epidemiology tools were used. A total of 49 PRAs and 574 participants, representing 64 different villages, were included. The results indicate that participants were well aware of the clinical signs of ASF, routes for disease spread and measures for disease control. However, awareness of the control measures did not guarantee their implementation. A majority of middlemen and butchers acknowledged having sold live pigs, carcasses or pork they believed infected with ASF. Outbreaks of ASF had a strong negative impact on participants’ socio-economic status with loss of revenue and reversal into more severe poverty. In conclusion, lack of knowledge is not what is driving the continuous circulation of ASF virus in this setting. To control ASF and reduce its impact, initiatives that stimulate changes in management are needed. Because the behaviour of all actors in the value chain is largely influenced by the deep rural poverty in the region, this needs to be combined with efforts to reduce rural poverty.

Introduction Uganda is a low-income country with 24.5% of the population living below the national poverty line, and poverty is particularly prevalent in the rural areas (World Bank, 2013). The country has the largest pig population in east Africa and the most rapidly growing pig population in subSaharan Africa, with production increasing by 10% each © 2015 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

year (Phiri et al., 2003). In the last 50 years, pig production has grown from only 16 000 animals in 1961 to more than three million in 2011 (UBOS, 2008; FAOSTAT, 2013). Most pigs are kept on smallholder family farms in the rural areas, with each family keeping only a few adult pigs (NEPAD and FAO, 2004; Dione et al., 2014). Pig keeping in Uganda has a large potential, both commercially and as a tool for poverty reduction (Doble, 2007). In contrast to 1

KAP ASF Uganda

cattle, buffalo and camels, pigs are found close to the bottom of the ‘livestock ladder’, meaning that they are predominantly kept by poor people. The poorer the household is, the more diverse roles the livestock represent in the daily livelihood (Perry et al., 2002). Pig keeping offers an attractive alternative to ruminants as they come with smaller investment costs, do not compete for pasture land, can be used for transforming kitchen waste into food and have a short reproduction cycle allowing for a quick financial turnover (Phiri et al., 2003). Further, the marketing of pigs and pig products offers a good opportunity for the predominantly rural population to raise money quickly. However, pig production in Uganda is hampered by several factors including poor husbandry skills, poverty preventing business-oriented interventions requiring even minor investment, and endemic as well as epidemic diseases (Phiri et al., 2003; Perry and Grace, 2009; Waiswa et al., 2009; Nissen et al., 2011). African swine fever (ASF) has been recognized as one of the biggest hurdles for development of the pig sector in Uganda (Ssewaya, 2003; Doble, 2007). The disease is endemic in the domestic pig population (Gallardo et al., 2011; Aliro et al., 2012; Muhangi et al., 2012; Muwonge et al., 2012; Atuhaire et al., 2013). Official reports of outbreaks are regular and almost yearly (OIE, 2013), but the true scale is unknown. The transmission cycle in domestic pigs has been identified as the dominating driver of ASF circulation in several areas with a high density of pigs, high occurrence of free-range management systems and a generally low level of farm biosecurity (Penrith et al., 2013). Recent research suggests that this is also the case for ASFendemic regions in Uganda (Aliro et al., 2012), despite the infectious agent being present in wild suids (Plowright et al., 1994; Jori and Bastos, 2009), soft ticks (Plowright et al., 1994), evidence pointing towards natural infection in bush pigs and possible overlap of wild and domestic suid habitats (St ahl et al., 2014). In Uganda and similar settings, outbreaks follow the legal and illegal trade routes of live pigs and pork along the value chain (Gulenkin et al., 2011; Aliro et al., 2012). The behaviour of humans is therefore central to the ASF transmission cycle in domestic pigs in Uganda. Surveys of knowledge, attitudes and practice (KAP) collect information and identify knowledge gaps, cultural beliefs and behavioural patterns that may influence disease control (WHO, 2008). The methodology is widely used for the study of infectious diseases in developing countries, specifically to assess poor people’s willingness to adopt prevention and control measures (Tiongco et al., 2012). The objective of this study was to capture the KAPs related to ASF in the smallholder pig production value chain in northern Uganda with the aim to better understand the drivers of the disease, compliance versus non-compliance 2

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with control measures and the feasibility of potential intervention strategies. Materials and Methods Study area This study was carried out in and around Gulu district in northern Uganda. Gulu district covers 3,449 km2 and is divided in two counties, 12 subcounties and 294 villages (Gulu district information portal, 2014). ‘Village’ is the smallest administrative unit. The area was severely affected by a civil war between the government and the Lord’s Resistance Army between 1986 and 2006 (Finnstr€ om, 2008; Branch, 2013) but is now slowly recovering from the political, social, economic and military unrest. Pig farming is among the fastest growing livestock activities as communities resettle back into their villages. The pig production is characterized by an uncontrolled influx of pigs into the district and a free-range husbandry system (Ikwap et al., 2014). Previous studies in the area (Aliro et al., 2012) detected more than 40 ASF outbreaks in 24 months, all of these were laboratory-confirmed. Study design and selection of participants The study included three separate series of participatory rural appraisals (PRA). Two series targeted farmers and one targeted other actors in the pig production value chain. Participants were selected on the basis of purposive sampling strategies (McCracken et al., 1988; Mariner and Paskin, 2000), and the selection criteria varied for each PRA series. In the first farmer PRA series (n = 36), participants from villages with recent experience of ASF outbreaks were selected. These outbreaks were all reported to the district veterinary office in Gulu and laboratory-confirmed within previous project activities (Aliro et al., 2012). In contrast, for the second farmer PRA series (n = 8), neither participants nor any other farmers in the same village had ever reported any ASF outbreaks to the district veterinary office in Gulu. This selection was done to compare the KAPs of farmers who had experienced ASF and previous project activities, to those who had not. The selection of participants for the value chain actor PRA series was based on convenience sampling of known actors in the pig production value chain. Participants from both rural and semi-urban areas, and representing different activities in the value chain such as middlemen (traders buying pigs from farmers to sell either immediately or later or for slaughter), butchers, retailers (pork retail points are in Uganda called pork kiosks) and restaurant owners (in Uganda called pork joints) were included. All participants were invited by the district veterinary office in Gulu. Participants in the two farmer PRA series were invited via key © 2015 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

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informants and participants in the value chain actor PRA series via a personal letter. Information was triangulated within each PRA by cross-checking answers from several questions, and, in addition, for both farmer PRA series via key-informant interviews performed at the same time as the PRAs. Data collection The PRAs were conducted between September and October 2013. The study objectives and methodology were explained to the participants before beginning each PRA, followed by agreement on rules of conduct, clarification about the integrity of participants’ identities, and authorization of footage, sound- and video-recording. The PRA protocols (Appendices S1a and b) were adopted from those of the International Livestock Research Institute (ILRI) Smallholder Pig production Value Chain Development (SPVCD) project in Uganda (ILRI, 2014). The PRAs started as soon as five participants were present. If more than five participants were present, they were divided into two separate groups, constituting separate PRAs. Whenever possible, participants were grouped according to gender, but if the gender balance did not allow for an all-female group, women were always grouped together to make them feel more at ease. Participants could join or leave at any time during the PRAs, but most continued during the entire PRA. Questions using hand count were executed after most participants had arrived and the number of participants contributing in those questions was kept constant during the entire PRA. Key informants verified that the persons present were those that had been invited. No time limit was set for the duration of the PRAs. The PRAs were conducted in the local language (Luo), by one facilitator and one note-taker, both native Luo-speakers proficient in English. Facilitators and note-takers were trained in participatory methods, research ethics and the protocol before implementation of the PRAs. They exchanged roles between the PRAs. Four facilitators/note-takers, constituting two teams, performed all the PRAs. To provide consistency between the two teams and minimize information bias, the first author of this study was present during all first farmer PRAs and all value chain actor PRAs, and the eighth author was present during most of the first farmer PRA series, all of the second farmer PRA series and all value chain actor PRAs. For the first farmer PRA series and the value chain actor PRA series, two PRAs were performed in parallel. This allowed for immediate feedback between the two teams further avoiding subject and observer errors. The training of the facilitators/note-takers was conducted by trainers from the ILRI SPVCD-project and the first author and was followed by two pre-test PRAs and subsequent adjustment of the PRA protocol. © 2015 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

KAP ASF Uganda

Tools Participatory epidemiology tools such as listing, efficiency scores, hand counts, proportional piling and seasonal calendars (see Table 1) were used (Kirsopp-Reed, 1994; Mariner and Paskin, 2000; Catley et al., 2004). Beans were chosen as markers for the questions answered using proportional piling. One hundred beans were used, and the size of the piles (=number of beans) could thus be easily converted into percentages. A seasonal calendar was formed using proportional piling on a matrix pre-drawn on flip charts. The participants were asked to consider the last 2 years when constructing the calendar. Each question was answered separately with 100 beans distributed over the calendar months. Answers were agreed upon via group consensus. An initial question about the distribution of annual rainfall allowed the participants to familiarize themselves with the seasonal calendar and thus assure more accurate answers to the following questions. A question on pig housing during different seasons was included only in the farmer PRAs. A question on ‘presence of vectors’ was only included only in 12 of the first farmer PRAs because of time limitations. Data management and analysis All data were entered into Microsoft Excel spreadsheets (Microsoft, Redmond, WA, USA) by the first author as soon as possible after each PRA. Data analysis with descriptive statistics was performed using the commands quarantile and wilcox.test in RStudio (version 0.98.495 – © 2009-2013; RStudio, Inc., Boson, MA, USA). Medians and 10th and 90th percentiles were calculated. Differences between PRA series and between PRAs of different gender composition were tested using the Wilcoxon rank sum test. For the seasonal calendar, averages of the resulting percentages were calculated separately for each PRA series. Graphs were created in Excelâ (Microsoft). Results Results did not differ between the two farmer PRA series for most questions, and these are therefore presented together. For those questions where differences were detected, the results are presented separately. Demographics The demographic results are described in Table 2. A total of 574 participants, representing 64 different villages, were included in 49 PRAs in 3 PRA series. The first farmer series included 419 participants in 36 PRAs, the second farmer series 105 participants in 8 PRAs, and the PRA series with 3

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Table 1. Questions and participatory methods for three series of participatory rural appraisals (PRA) in a Knowledge–Attitudes–Practices study on African swine fever (ASF) in smallholder pig production conducted in northern Uganda in 2013

Question Demographics Production system Housing system Activities in the pig value chain Outbreaks Number of outbreaks Affected farmers Affected pigs Knowledge Name of ASF in Luo Clinical signs of ASF Sure to recognize ASF Age/breed classes affected Have seen ASF signs in pigs/products Routes for ASF spread Business related routes for ASF spread Seasonality of ASF-outbreaks and related factors Attitudes Perceived public health risks with ASF Perceived public health risks with other pig diseases Aware of other control methods than those used Other control methods than those used Obstacles to prevent using control methods Incentives for using control methods Know a model farmer Reasons for success of model farmer Perceived challenges in pig production Who should address the challenge How can the challenge be addressed Perceived needed future pig projects Attitudes to disease control in relation to value chain activities Practices Trade in pigs/products with ASF signs Back in business after ASF outbreak Socio-economical impacts of ASF outbreak Control methods used

value chain actors other than farmers included 50 participants in 5 PRAs. Figure 1 shows the geographical distribution of the three PRA series. The gender distribution was unbalanced; there were both fewer female than male participants and fewer all-female than all-male PRAs. No differences were detected between the answers from the allfemale, all-male and mixed farmer PRAs. Most participants keeping pigs were both breeders and growers. Being a breeder, that is selling piglets at weaning, was mentioned to be more profitable than being a grower. Being both breeder and grower was mentioned as a good way of spreading risks such as fluctuating market prices and disease outbreaks. Pig husbandry varied markedly by the cropping seasons, even if free-range husbandry systems were the most commonly 4

Tool

Farmer PRAs

Hand count Hand count Hand count

X X

Listing Proportional piling Proportional piling

X X X

Listing Listing Hand count Hand count Hand count Listing Listing Seasonal calendar/proportional piling

X X X X

Hand count Hand count Hand count Listing Listing Listing Hand count Listing Listing Listing Listing Listing Hand count

X X X X X X X X X X X X

Value chain actor PRAs

X

Hand count Hand count Listing Listing, efficiency score

X X

X X X

X X X X X X X X X X X X X X X X X X X X X X X X

used. The participants in the value chain actor PRAs were middlemen, butchers, owners of pork kiosks, owners of pork joints and dealers in pig skins. Most participants in the value chain actor PRAs were engaged in several activities, and, in addition, more than half of the participants kept pigs. Three of the five value chain actor PRAs included participants from all categories of actors. One PRA did not have any participants keeping pigs, and one did not have any participants acting as middlemen. Participants’ description of ASF outbreaks Outbreak results are described in Table 3. A total of 94 outbreaks were described in the farmer PRAs. According to the © 2015 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

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KAP ASF Uganda

Table 2. Demographic data on participants in three series of participatory rural appraisals (PRA) in a Knowledge–Attitudes–Practices study on African swine fever (ASF) in smallholder pig production conducted in northern Uganda in 2013 First farmer PRAs No. of PRAs Total 36 All male 9 (25%) All female 5 (14%) Mix 22 61%) No. of participants Total 419 Male 280 (67%) Female 138 (33%) No. of villages 46 Production system (%)1 Only breeder 12 (0,75) Only grower 18 (0, 53) Breeder and grower 47 (10, 100) Housing system (%)1,2 Free range 91 (12, 100) Tethered 75 (0, 100) Confined 59 (0, 100) Activities in the pig value chain (%)2,3 Middleman N/A Butcher N/A Owner of pork kiosk N/A Owner of pork joint N/A Owner/breeder of pigs N/A Other N/A

Second farmer PRAs

Both farmer PRAs

Value chain actor PRAs

8 1 (13%) 0 7 (87%)

44 10 (23%) 5 29 (67%)

5 3 (60%) 0 2 (40%)

105 * * 10

524 * * 56

All PRAs

49 13 (27%) 5 (10%) 31 (63%)

50 45 (90%) 5 (10%) 9

574 * * 65

0 (0, 9) 14 (8, 23) 83 (70, 92)

7 (0,75) 14 (0, 49) 63 (10, 100)

N/A N/A N/A

N/A N/A N/A

100 (67, 100) 75 (38, 100) 83 (26, 96)

93 (18, 100) 75 (3, 100) 66 (0, 100)

N/A N/A N/A

N/A N/A N/A

48 58 54 52 54 13

N/A N/A N/A N/A N/A N/A

N/A N/A N/A N/A N/A N/A

N/A N/A N/A N/A N/A N/A

1

Median proportion (10th, 90th percentiles). Participants reported all housing systems they used and all activities they performed, giving a possible sum of more than 100%. 3 Pork kiosk = in Uganda pork retail point, pork joint = in Uganda restaurant specialized in pork. *Data not available. 2

first farmer PRA series, the median proportion of farmers in the villages represented that were affected by each outbreak was 79%. The corresponding median proportion for the second farmer PRAs was significantly (P < 0.01) lower, 66%. For both series of farmer PRAs, the median proportion of pigs that died during these outbreaks was 80% and very few of the pigs that fell ill survived. A small proportion of the pigs (16 and 22%, respectively) was never affected. This proportion was significantly (P < 0.05) larger in the second farmer PRA series compared with the first farmer PRA series. Participants’ knowledge on ASF The results relating to knowledge are shown in Table 4. Perceptions of the clinical presentation of ASF Thirteen different names for ASF in Luo were mentioned, most frequently mentioned was ‘orere’, which was mentioned in 37 of the 49 PRAs. The Luo words typically described the clinical signs seen in the pigs. Participants in © 2015 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

the farmer PRAs as well as participants in the value chain actor PRAs that traded in live pigs (middlemen) could accurately describe the clinical signs of ASF; each PRA listed at least three correctly. Almost all participants in the first farmer PRA series and all of the middlemen were confident that if a pig showed the clinical signs they had described, it would be suffering from ASF. A significantly (P < 0.05) smaller proportion (but still a majority) of the participants in the second farmer PRA series were confident they could recognize ASF on the basis of the clinical signs. Furthermore, almost all participants had the experience that pigs of all ages were affected. Farmer participants who had owned any other breeds than local ones experienced that both local and improved breeds could be affected. Participants in the value chain actor PRAs who traded in carcasses or meat (butchers) described nine different signs that they believed would be visible in the meat or on the carcass if the pig had been infected with ASF at the time of slaughter or death. Descriptors mostly referred to smell, texture and quality of the meat. Pathological signs such as enlarged spleen, and kidneys were mentioned 5

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in two PRAs. Almost all of the butchers were sure that the pig would have been suffering from ASF if they saw the signs they had listed. All middlemen and almost all of the butchers had seen the signs they described as ASF signs in pigs or products.

Routes for spread of ASF In total, 158 correct routes and 61 incorrect routes of ASF spread were mentioned. Infected pork or pork products were mentioned in all but one PRA, direct contact in 31 (63%) and different sorts of indirect contact in 20 (41%). Every PRA mentioned at least two correct routes of spread. The two incorrect routes of spread most frequently mentioned were airborne (39 PRAs, 80%) and human faeces (17 PRAs, 35%). The value chain actor PRAs included an additional question on business-related routes of spread. On average, there were four such routes of spread in each PRA, and trade of infected pork was mentioned as an example in all of them. Seasonality of ASF outbreaks and related factors There was a clear seasonality in the ASF outbreaks, coinciding with several potential risk factors. Pork slaughter and sales were irregular with peaks around festivities such as Easter, Independence Day in October and Christmas/New Year, as well as in August (pigs are sold in August to obtain money for school fees). Furthermore, pigs were kept free-range between October and April and tethered or fenced in during the cropping season (MaySeptember). The seasonality of pigs kept on free-range as well as pig slaughter and pork sale coincided with the seasonality of ASF occurrence. The seasonal distribution of rainfall, ASF outbreaks, pig and pork sales, the presence of wild pigs and pig housing deriving from the seasonal calendars for the three PRA series are illustrated in Figure 2a–c. Participants’ attitudes about ASF The results relating to attitudes are shown in Table 5.

Fig. 1. Geographical distribution of three participatory rural appraisal series (PRA) in a Knowledge–Attitudes–Practices study on African swine fever in smallholder pig production conducted in northern Uganda in 2013.

Perceived public health risks Most participants in the first farmer PRAs considered consuming pork from pigs that had died from ASF a public health risk, as did the participants in the value chain actor

Question

Farmer PRAs

Number of outbreaks

94 First farmer PRAs

Second farmer PRAs

Both farmer PRAs

79 (60, 97)a 21 (3, 41)a

66 (25, 79)a 35 (22, 75)a

78 (46, 97) 23 (3, 56)

80 (53, 96) 0 (0, 9) 16 (3, 40)b

77 (24, 92) 0 (0, 6) 22 (9, 83)b

80 (50, 96) 0 (0, 9) 16 (3, 46)

Affected farmers (%)1 Affected Not affected Affected pigs (%)1 Died Sick but recovered Healthy

Table 3. Results relating to ‘ASF outbreaks’ in three series of participatory rural appraisals (PRA) in a Knowledge–Attitudes–Practices study on African swine fever (ASF) in smallholder pig production conducted in northern Uganda in 2013

1

Median proportion (10th, 90th percentiles). Significantly different, P < 0.01. b Significantly different, P < 0.05. a

6

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Table 4. Results relating to ‘Knowledge’ in three series of participatory rural appraisals (PRA) in a Knowledge–Attitudes–Practices study on African swine fever (ASF) in smallholder pig production conducted in northern Uganda in 2013 Question,

Farmer PRAs

Value chain actor PRAs

Names for ASF in Luo 1,2

Both farmer PRAs Orere (75), Ebola (20), Aburu opego (5), Aewii (2), Alili (2)

Orere (80), Ebola (60), Malaria (20), Ocel-cel (20)

Clinical signs of ASF1

Loss of appetite (73), changes in skin colour (66), poor general condition (55), paralysis/affected movements (41), salivation (41)

Middlemen Loose body condition (80), changes in skin colour (80), ear and tail drop down (60), death (60), hair stand up (60)

Butchers Meat smells bad (100), pork change colour (100), meat quality deteriorates (60), smoking process negatively affected (40), bad taste (40)

First farmer PRAs 100 (85, 100)b 0 (0, 40)b

100 0

98 2

Sure to recognize ASF (%)3

Yes No Age/Breed classes affected (%)4 Adult Young Local (n = 41) Improved (n = 28) Both (n = 31) Have seen ASF signs in pigs/products (%) Yes No Routes for ASF spread1

Business related routes for ASF spread1

Second farmer PRAs 93 (82, 100)b 7 (0, 18)b

Both farmer PRAs 100 (84, 100) 0 (0,14)

Both farmer PRAs 100 (100, 100) 100 (100, 100) 100 (100, 100) 100 (91, 100) 100 (100, 100)

N/A N/A Infected pork/products (100), air borne (80), direct contact (64), indirect contact (41), free range pigs (25) N/A

N/A N/A N/A N/A N/A

100 (n = 38) 97 (n = 36) 0 (n = 38) 2.8 (n = 36) Infected pork (80), air borne (80), direct pig-pig contact (60), human faeces (40), indirect contact (40) Trade in infected pork (100), contamination at sale and slaughter (80), blood and fomite contaminated hands and equipment (60), trade in live pigs (40), contaminated clothing of middlemen and butchers (40)

1

In parenthesis: The percentage of PRAs in which the term was mentioned. Terms in order of frequency, similar terms grouped by authors. If more than five terms were mentioned, the five most frequently mentioned terms are included in the Table and additional terms in Appendix S2. 2 Most of the names describe clinical signs. Translation to English when appropriate: Orere = massive death in animals, Aburu opego = pig influenza, Aewii = always, Alili = mowing in circles, Ocel cel = sudden death. 3 Farmer PRAs: median proportion (10th, 90th percentiles), value chain actor PRAs: % of participants. 4 Median proportion (10th, 90th percentiles). b Significantly different, P < 0.05.

PRAs. In contrast, significantly (P < 0.001) fewer (less than 25%) of the participants in the second farmer PRAs perceived consumption of such pork to be a public health risk. More than a third of the participants in the second farmer PRAs could not provide a ‘yes’ or ‘no’ answer regarding whether consuming such pork constituted a public health risk. This was significantly (P < 0.001) lower compared with the first farmer PRAs. Regarding pork from pigs that had died from other diseases than ASF, the majority of the participants in the first farmer PRAs and the value chain actor PRAs considered such consumption a public health risk, compared with only © 2015 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

a third of the participants in the second farmer PRAs (difference significant, P < 0.01). Almost half of the participants in the second farmer PRAs could not provide a ‘yes’ or ‘no’ answer regarding whether such pork was a public health risk. This was significantly (P < 0.001) lower compared with the first farmer PRAs. Control methods other than those already used by participants Most participants in all the PRAs said they were aware of more control methods than what they used. The farmer PRAs mentioned 95 such methods, most frequently 7

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(a)

(b)

(c)

Fig. 2. Seasonality of rainfall, occurrence of African swine fever (ASF), pork sales and slaughter according to seasonal calendars from participatory rural appraisals (PRA) with two series of farmers (a) and value chain actors (b) and seasonality of pig housing from two farmer PRAs (c), in a Knowledge–Attitudes– Practices study on ASF in smallholder pig production conducted in northern Uganda in 2013.

vaccination (12 PRAs, 24%) and confinement of pigs (9 PRAs, 18%). Factors preventing adoption of these methods were as follows: lack of knowledge how to implement them, lack of capital for construction and investments, lack of income and a cultural taboo against throwing away food. Factors that could serve as incentives for adopting control methods were as follows: training in biosecurity, pig health and management; provision of new or improved pigs; mass vaccination; and farm visits by veterinarians. The participants in the value chain actor PRAs named 12 control meth8

ods, of which safe disposal of offal from ASF-infected pigs was the most mentioned. Factors preventing them from adopting the known control methods were as follows: the absence of slaughter slabs in the area, low veterinary presence at slaughter, the need for maximizing profits, ‘the love for pork’, lack of capital and the fact that some ‘do not take the pig business seriously’, i.e., they regarded it only as supplementary income. Improvement of the existing, or construction of new, slaughter slabs was indicated as a factor that could serve as an incentive for adopting the known but © 2015 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

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Table 5. Results relating to ‘Attitudes’ in three series of participatory rural appraisals (PRA) in a Knowledge–Attitudes–Practices study on African Swine fever (ASF) in smallholder pig production conducted in northern Uganda in 2013 Farmer PRAs Question

First farmer PRAs

Second farmer PRAs

Both farmer PRAs

Value chain actor PRAs

84 (36, 100)b 0 (0, 40)b 0 (0, 41)b

23 (10, 39)b 37 (21, 56)b 37 (20, 56)b

76 (21, 100) 13 (0, 47) 11 (0, 49)

52 25 23

88 (30, 100)a 0 (0, 42) 0 (0, 41)b

36 (24, 65)a 13 (0, 37) 45 (28, 62)b

68 (28, 100) 0 (0, 42) 0 (0, 53)

79 4.2 17

75 (5, 100) 25 (0, 100)

76 (26, 100) 25 (0, 74)

75 (3, 100) 25 (0, 100)

92 8.3

1

Public health risks ASF (%) Yes No Unable to answer yes/no Public health risks other pig diseases (%)1 Yes No Unable to answer yes/no Aware of other control methods than those used (%)1 Yes No

Other control methods than those used2 Obstacles to prevent using control methods2

Incentives for using control methods2

Know a model farmer (%)1 Yes No

Reason for success of model farmer2 How can the challenges be addressed2

Perceived needed future pig projects2

Responsibility for controlling ASF in relation to value chain activities (%) Yes No No opinion

Both farmer PRAs

Value chain PRA

Vaccination (73), prevent animal movements (57), confine pigs (45), treat for external parasites (36), bury/burn dead pigs (36) Lack of knowledge (68), lack of capital for construction and investments (41), lack of income (41), culture does not allow to throw away meat (36), lack of control of animal movements and regulations (14) Training on bio security, pig health and management (59), provision of pigs/improved pigs (16), mass vaccination (16), vet farm visits (14), enforcement of animal movement restrictions (14)

Burn offal and blood (60), bury dead pigs (40), safe disposal of blood and water (40), quarantine and movement restrictions (40) No slaughter slab in area (60), no vet meat inspection (20), need for profit (20), love for pork (20), pig business not taken seriously (20) Improve/construct slaughter slab (60), appoint vet (60), training (60), increase law enforcement (40), institutionalise local regulations (20)

First farmer PRAs

Second farmer PRAs

Both farmer PRAs

20 (0, 100) 8 (0, 100)

62 (0, 100) 38 (0, 100)

28 (0, 100) 0 (73, 100)

38 63

Both farmer PRAs

Value chain PRA

Confined pigs (39), enough/good feed and water (23), good pig housing (18), good hygiene (14), regular vet visits (9) Training and community mobilisation (75), farmer groups (50), enforce law implementation (39), cooperation between value chain actors (32), more vet presence (18) Training of farmers on pig husbandry, health and disease control (45), construction of pig houses (32), ASF vaccine (32), improved breeds (23), disease control and investigations (18)

Good husbandry practice (80), good pig housing (40), confined pigs (40), resources to buy feed (20), isolated farm (20) Enforce law implementation (80), farmers groups (60), radio messages/training (60), cooperation between value chain actors (40), sample and testing (40) Construction of slaughter slabs (60), training of butchers and traders on pig husbandry and health (60), soft loans (40), vaccines (40), construction of market slots for middlemen (20)

N/A N/A N/A

87.5 8.3 4.2

1

Farmer PRAs: median proportion (10th, 90th percentiles). Value chain actor PRAs: % of participants. In parenthesis: The percentage of PRAs in which the term was mentioned. Terms in order of frequency, similar terms grouped by authors. If more than five terms were mentioned the five most frequently mentioned terms are included in the Table and additional terms in Appendix 2. a Significantly different, P < 0.01. b Significantly different, P < 0.001. 2

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unimplemented control methods, as was appointment of veterinary inspectors, training in biosecurity, increased legal enforcement and institutionalization of local trade regulations. Most participants said they knew at least one ‘model farmer’. Frequently cited reasons for the success of these farmers included the following: good pig husbandry practices, well-constructed pigsties, regular veterinary visits and adoption of some basic biosecurity measures (e.g. confinement of pigs and prevention of human access to the pigs). Perceived challenges in pig production The farmer PRAs listed 136 different challenges and the value chain actor PRAs 13. The most frequently mentioned challenges were lack of an ASF vaccine, uncontrolled movement of pigs and the free-range management system. The two farmer PRAs also frequently mentioned lack of knowledge and the behaviour of butchers. Participants in all three PRA series declared that it was the veterinarian who should address most of the challenges, followed by local leaders or government, and finally, the participants themselves. Suggestions varied from training

and community mobilization, formation of farmer groups, stronger enforcement of laws and animal health regulations and increased cooperation between the value chain actors. Perceived needs for future pig projects In the farmer PRAs, the most wanted projects were training in pig husbandry and pig health, and disease control. The participants also expressed a need for support in the construction of pig sties and for vaccination. In the value chain PRAs construction of slaughter slabs, training in pig husbandry and pig health followed by provision of soft loans and vaccines were the most wanted projects. Attitudes to disease control in relation to value chain activities In total, 48 participants in the value chain actor PRAs responded to the question about ‘their role in control and spread of ASF’. Forty-two (87.5%) confirmed that they considered themselves to have some responsibilities, four (8.3%) denied any responsibilities and two participants (4.2%) had no opinion.

Table 6. Results relating to ‘Practices’ in three series of participatory rural appraisals (PRA) in a Knowledge–Attitudes–Practices study on African swine fever (ASF) in smallholder pig production conducted in northern Uganda in 2013 Vale chain actor PRAs Question Have sold pigs/products with ASF signs (%) Yes No

Back in business after ASF outbreak (%)1 Yes No Socioeconomical impacts of ASF outbreaks2 Control methods used3

Farmer PRAs

Middlemen

Butchers

N/A N/A First farmer PRAs

49 (n = 37) 51 (n = 37)

71 (n = 35) 29 (n = 35)

Second farmer PRAs

Both farmer PRAs

82 (47, 100) * * 18 (0, 49) * * Both farmer PRAs Loss of income (68), failure to pay school fees (75), failure to pay for agriculture labour (45), poorer diet (43), medical expenses not met (34 Confine pigs (84; 2.1), hide pigs away from house or other pigs (36; 2.4), give drugs (36; 1.8) stop buying pork (36; 2.1), tether (27; 2.2)

98 2 Loss of clients (100), bad for business (60), good for business (60), loss of income (40), scarcity of pigs (40) Avoid to purchase pigs from areas with outbreaks (40; 3), separate slaughter equipment from equipment used at home (40; 3), confine pigs (40; 3), isolate pigs awaiting slaughter in bush (40; 2.5), bury slaughter remains and offal (40; 2.5)

1

Farmer PRAs: median proportion (10th, 90th percentiles), value chain actor PRAs: % of participants. In parenthesis: The percentage of PRAs in which the term was mentioned. Terms in order of frequency, similar terms grouped by authors. If more than five terms were mentioned the five most frequently mentioned terms are included in the Table and additional terms in Appendix S2. 3 In parenthesis: The percentage of PRAs in which the term was mentioned; efficiency score. Terms in order of frequency, similar terms grouped by authors. Five most frequently mentioned terms included, others in Appendix S2. *Data unavailable. 2

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Participants’ practices relating to ASF The results relating to practices are shown in Table 6. Trade in pigs or products with signs of ASF All participating middlemen had sold pigs with signs they recognized as ASF. Most of the butchers had also sold carcasses or meat with signs they recognized as ASF. Impacts of recent outbreaks Approximately one-fifth of the participants in the first farmer PRAs had discontinued pig farming after an outbreak of ASF. Reasons given were as follows: lack of funds for acquiring new pigs, no pigs available on the market and fear of new ASF outbreaks. Consequences of the outbreaks included failure to pay school fees, failure to pay for farm labour leading to less cultivated land, decreased meat content in the family diet, feelings of discouragement, lost hope, fear, failure to pay medical expenses, loss of important pig breeds, increase in pig prices, direct human health problems, postponement of marriages, and disputes with neighbours. Of the 50 participants in the value chain actor PRAs, only one had ceased his business after an ASF outbreak, citing lack of money to buy new pigs. The value chain actor PRAs cited both negative and positive impacts of ASF outbreaks with negative impacts dominating. All these PRAs mentioned loss of clients as a negative effect. A positive impact of the outbreaks was that farmers were eager to sell both their healthy and diseased pigs, leading to lower farm gate prices and an opportunity for middlemen to make a profit. Control methods used More than 40 different control methods were mentioned in the farmer PRAs. The most frequent one was confinement of pigs, followed by transferal of the affected pig away from the house, village or other pigs, administration of drugs, and not buying pork. Four control methods were given the maximum efficiency score: ‘transferring pig far from affected village’, ‘only one person tending to the pigs’, ‘do not feed swill’ and ‘implement movement restrictions’. The control methods ranked with the highest efficiency scores were not the same as the ones most frequently used. The value chain actor PRAs mentioned 16 different control methods. Their methods differed depending on the type of activities in which they were engaged. Discussion In this study, two ASF outbreaks were described in each of the second farmer PRAs where none of the participants had reported any outbreaks to the local authorities. This probably reflects the difficulties in determining the distribution © 2015 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

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of ASF within Uganda, even within an area such as Gulu where ASF research has been ongoing for several years. This study consequently supports results from previous research demonstrating the suitability and efficiency of participatory methods for detecting and quantifying animal diseases in rural communities (Bett et al., 2009; Grace et al., 2009; Jost et al., 2010; Mariner et al., 2011; Robyn et al., 2012). It is worth mentioning that even if no case definition of ASF was given to participants in this study, in the setting where neither classical swine fever nor porcine reproductive and respiratory syndrome (PRRS) are present, the list of differential diagnoses for infectious pig diseases with very high mortality ends almost exclusively with ASF (Muhangi, D., et al. Submitted, BMC Vet Res, 2014). Our study may have some biases, some of them directly associated with the PRA methodology (Chambers, 1983; Mariner and Paskin, 2000; Bett et al., 2009). Recall and group bias are two of these (Bett et al., 2009). Participants are likely to agree with dominant group members and are unlikely to express opinions that oppose the majority or disclose that they break laws, rules or regulations. To control for this, group dynamics were included in the training of the facilitators and the purely scientific (as opposed to controlling) interest of the study was emphasized during all PRAs. The PRA method collects mostly qualitative data and some information is lost in transcribing this into data that can be described and analysed. To mitigate this loss of information, the original protocols were frequently consulted during the compilation of the results and this paper. Quantitative and semi-quantitative data collected by PRAs can be analysed using nonparametric tests (Bett et al., 2009; Okell et al., 2013), as was done in this study. Another bias may have been the unequal gender balance of the participants. Participants in the farmer PRAs were invited by key informants, most of whom were male. This may have exacerbated the skewed gender balance in these PRAs. Nevertheless, it is uncertain whether the underrepresentation of women biased the results. There were no differences detected when comparing the results from the few all-female farmer PRAs with the all-male or mixed ones. The gender balance in the value chain PRAs was probably a fair representation of the true gender balance among the actors. Cultural habits, taboos and poverty seemed to be strong factors in the consumption and trade of infected pigs as well as implementation of known control methods. Studies from Russia, Georgia and Sardinia report a similar importance of cultural and social factors in the understanding of ASF transmission and control failures (Zaberezhnyı˘ et al., 2012; Gogin et al., 2013; Mur et al., 2014). In our study, several participants mentioned the importance of pork in the often poor diets and the taboo of throwing away food. These factors in combination with 11

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economic drivers lead to consumption of, and trade in, pork from pigs that have died from ASF or been slaughtered upon showing clinical signs. Indeed, most participants in the value chain actor PRAs stated that they had sold live pigs, carcasses or pork from pigs they thought were infected with ASF. In conclusion, almost all participants consumed pork from ASF-infected pigs. Either they were unaware of the status of the pork, they did not consider it a risk, or they perceived this specific risk to be insignificant compared with all other risks in everyday life in rural Uganda, such as food insecurity. This phenomenon of differences between perceptions of risk and behavioural changes has been named the risk perception paradox (Wachinger et al., 2013). There was a temporal association between ASF outbreaks and slaughter/pork sales as well as free-roaming pig management systems. This association supports the theory that ASF transmission is driven by the practices of the actors in the value chain. However, the results do not indicate causality between the events and ASF outbreaks, that is one event could drive any of the other. For example, farmers reported sale or slaughter of pigs in October to be rid of them before the yearly, expected, ASF outbreak. Considering these associations and the frequent consumption of pork from ASF-infected pigs, one way of reducing the risk of ASF spread could be to promote safe slaughter and production of safe pork products, for example by heat treatment (Thomson et al., 2013). There is limited scientific information on the socio-economic impact of endemic ASF at the household, community and national levels in countries such as Uganda. Even if the objective of this study did not include a formal impact assessment, it is concluded that the outbreaks of ASF had a strong negative effect on the participants’ social and economic status. When outbreaks occurred in a community, most of the farmers were affected and a large proportion of the pigs died, leading to income loss and deeper poverty. This confirms results from previous studies where ASF is mentioned as one of the factors preventing pig production from becoming a realistic pathway out of poverty in rural Uganda (Doble, 2007). The results also demonstrate that not only farmers, but all the actors in the smallholder pig production value chain, are affected by the outbreaks. Such negative impacts on the entire pig value chain have been shown to occur in poor rural areas also for events other than infectious disease (Dewey et al., 2011). Although members of the value chain such as middlemen and butchers are often accused of spreading ASF to maximize profit, our results demonstrate that they too experienced mostly negative effects from outbreaks. They were as equally aware of signs of disease, routes of disease spread and control methods as the farmers. Most participants in 12

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the value chain actor PRAs acted at several levels of the value chain, including keeping and breeding of pigs. Thus, they would have a strong interest in disease control. This was confirmed as 87.5% of participants in the value chain actor PRAs agreed that they were responsible for conducting their business in a way to prevent spread of disease. Of course, it can be argued that participants answered according to what they thought the facilitators wanted to hear in this particularly sensitive question, but the fact that not all answered in the affirmative confers credibility to the response. All PRAs correctly described the clinical signs of ASF (Taylor, 2006), albeit with a difference between the second and first farmer PRA series regarding how many participants could confidently identify the disease. This difference probably reflects the positive impact of dissemination activities carried out in connection with previous research activities in the areas where farmers had reported ASF outbreaks. Remarkably ‘death’ was only mentioned as a clinical sign of ASF in eight of the farmer PRAs, despite a median mortality of 80% in the described outbreaks. This is probably because participants regarded death as an outcome of the disease rather than a clinical sign. Most participants were well aware of routes for disease spread and control measures. All PRAs correctly identified pork, pork products, offal and trade of live pigs as the main risk factors for spreading, or acquiring, ASF. For all PRAs, the level of knowledge was high in most aspects, but some knowledge gaps were, however, evident. As an example, many of the control methods in use and others with a high efficiency score assumed that participants would be made aware of outbreaks in their neighbouring areas and thus able to adopt behaviour and routines. In a situation where ASF is endemic and reporting scarce, this is not a safe way of operating. In addition, the incubation period and the potential excretion of ASF virus before the appearance of clinical signs seemed to be unknown or not taken into account. Further, many participants stated that their pigs had been vaccinated against ASF and/or thought that vaccination could be a future solution for ASF control. However, there is currently no ASF vaccine available, making the need for other control methods in endemic areas pressing. Despite the participants’ overall good knowledge of ASF, all PRAs mentioned ‘lack of knowledge’ as a factor preventing implementation of certain control measures. This farmer ‘denial’ of existing knowledge is not unique for ASF in smallholder pig production in Uganda. It has been reported from a situation as seemingly distant in geography, context and microbiology, as bovine tuberculosis in the United Kingdom (Enticott and Vanclay, 2011). Participants frequently requested training on biosecurity, pig diseases and pig management, both as an incentive to © 2015 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

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implement known but not used control methods, and in response to perceived needed future pig projects. Undoubtedly, targeted education initiatives on requested subjects, such as biosecurity, could serve to fill knowledge gaps and increase motivation for improving biosecurity to reduce circulation of ASF. Improved biosecurity has the benefit of preventing not only ASF but also other infectious pig diseases. The KAPs related to ASF in the smallholder pig production value chain described in this study are important factors in understanding how ASF control could be attempted. It is not primarily a lack of knowledge driving the continuous circulation of ASF virus in this setting. All participants were well aware of routes for disease spread and control measures. What seems to be needed is not training on ASF but initiatives to stimulate changes in management with the objective to ‘make people practice what they already know’. In addition, the study results propose that any suggested control methods must require little investment and offer immediate financial return. The behaviour of all actors in the value chain is largely influenced by the deep rural poverty in Uganda. Changed management therefore needs to be twinned with efforts to reduce rural poverty to maximize the possibilities for ASF control and reduce the impacts of outbreaks. The conclusions drawn from this study are not specific to ASF in northern Uganda, but can be extrapolated to a variety of smallholder systems trying to cope with infectious animal diseases. Conclusions This study confirmed that ASF is endemic in domestic pigs in the study area, with participants describing numerous outbreaks. The ASF outbreaks had a strongly negative social and economic impact on the participants. Regardless of their different roles in the pig production value chain, all participants were negatively affected. The outbreaks were temporally associated with events driven by human behaviour such as pig/pork sales and free-range management systems. Underreporting remains high and yet participants trusted that they would be given notice of any outbreaks to be able to adjust and change their practices accordingly. Because most participants in this study had good knowledge of most aspects of ASF, it can be concluded that it is not lack of knowledge that is the basis for the various practices driving the continuous ASF transmission in this setting. The numerous outbreaks described suggest that farm-level biosecurity is insufficient and, moreover, that the currently applied traditional control methods for ASF are ineffective. While considering other solutions for control, the widespread poverty and associated need to maximize any possible income, for example, © 2015 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

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using all available animal protein for human consumption, as expressed by the participants in this study, cannot, be ignored. Acknowledgements The authors acknowledge ILRI for providing the PRA tools, Mr Peter Lule and Mr Peter Ssentumbwe from the ILRI SPVCD-project for conducting the facilitator training, Ms Linda Svensson for constructing the map and Dr Solomon Alike, Mr Bruce Nokorach, Mr Wokorac Samuel Opiyo, Mr Simon Peter Otema and Mr Peter Ogweng from the Gulu district veterinary office for invaluable help in performing and planning the PRAs. We also deeply thank the farmers and value chain actors in Gulu district for participating in the PRAs. The study was financed by the Swedish research council/ U-forsk under contract no. 348-2013-146. No conflicts of interest are prevailing in connection with the study for any of the authors. References Aliro, T., E. Tejler, D. Muhangi, S. Ndyanabo, S. Boqvist, A. Ademun Okurut, C. Masembe, U. Emanuelson, and K. Stahl, 2012: Spatio-temporal dynamics of African Swine Fever in Gulu district, northern Uganda. EPIZONE 6th Annual Meeting “Viruses on the move”. Atuhaire, D. K., M. Afayoa, S. Ochwo, S. Mwesigwa, J. B. Okuni, W. Olaho-Mukani, and L. Ojok, 2013: Molecular characterization and phylogenetic study of African swine fever virus isolates from recent outbreaks in Uganda (2010–2013). Virol. J. 10, 247. Bett, B., C. Jost, R. Allport, and J. Mariner, 2009: Using participatory epidemiological techniques to estimate the relative incidence and impact on livelihoods of livestock diseases amongst nomadic pastoralists in Turkana South District, Kenya. Prev. Vet. Med. 90, 194–203. Branch, A., 2013: Gulu in War. . . and Peace? The Town as Camp in Northern Uganda. Urban Stud. 50, 3152–3167. Catley, A., R. T. Chibunda, E. Ranga, S. Makungu, F. T. Magayane, G. Magoma, M. J. Madege, and W. Vosloo, 2004: Participatory diagnosis of a heat-intolerance syndrome in cattle in Tanzania and association with foot-and-mouth disease. Prev. Vet. Med. 65, 17–30. Chambers, R., 1983: Rural poverty unobserved; the six biases. Rural Development Putting the Last First, pp. 13–23. Longman, Essex, UK. Dewey, C. E., J. M. Wohlgemuta, M. Levya, and F. K. Mutuaa, 2011: The impact of political crisis on smallholder pig farmers in western Kenya, 2006–2008. J. Mod. Afr. Stud. 49, 455–473. Dione, M., E. Oumaa, K. Roesel, J. Kungu, P. Lule, and D. Pezo, 2014: Participatory assessment of animal health and husbandry practices in smallholder pig production systems in

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three high poverty districts in Uganda. Prev. Vet. Med., 117, 565–576. Doble, L., 2007: Prioritisation of Production Constraints within the Kampala Urban and Peri-urban Pig Production System: A Baseline Study. Graduate Studies Program. St. George’s University, Grenada. Enticott, G., and F. Vanclay, 2011: Scripts, animal health and biosecurity: the moral accountability of farmers’ talk about animal health risks. Health Risk Soc. 13, 293–309. FAOSTAT, 2013. Available at: http://faostat3.fao.org/faostatgateway/go/to/home/E (accessed October 21, 2014). Finnstr€ om, S., 2008: Living with Bad Surroundings. War, History, and Everyday Moments in Northern Uganda. Duke University Press, Durham and London. Gallardo, C., A. Ademun, R. Nieto, N. Nantina, M. Arias, E. Martin, V. Pelayo, and P. R. Bishop, 2011: Genotyping of African swine fever virus (ASFV) isolates associated with disease outbreaks in Uganda in 2007. Afr. J. Biotechnol. 10, 3488–3497. Gogin, A., V. Gerasimov, A. Malogolovkin, and D. Kolbasov, 2013: African swine fever in the North Caucasus region and the Russian Federation in years 2007-2012. Virus Res. 173, 198–203. Grace, D., T. Randolph, H. Affognon, D. Dramane, O. Diall, and P. H. Clausen, 2009: Characterisation and validation of farmers’ knowledge and practice of cattle trypanosomosis management in the cotton zone of West Africa. Acta Trop. 111, 137–143. Gulenkin, V. M., F. I. Korennoy, A. K. Karaulov, and S. A. Dudnikov, 2011: Cartographical analysis of African swine fever outbreaks in the territory of the Russian Federation and computer modeling of the basic reproduction ratio. Prev. Vet. Med. 102, 167–174. Gulu district information portal, 2014. Available at: http:// www.gulu.go.ug/ (accessed June 17, 2014). Ikwap, K., M. Jacobson, N. Lundeheim, D. O. Owiny, G. W. Nasinyama, C. Fellstr€ om, and J. Erume, 2014: Characterization of pig production in Gulu and Soroti districts in northern and eastern Uganda. Livestock Res. Rural Dev. 26, Article ID 74. http://www.lrrd.org/lrrd26/4/ikwa26074.htm. ILRI, 2014: Pig Value Chain Development - Uganda. Available at: http://livestock-fish.wikispaces.com/VCD+Uganda#Pig Value Chain Development - Uganda-Tools (accessed June 10, 2014). Jori, F., and A. D. Bastos, 2009: Role of wild suids in the epidemiology of African swine fever. EcoHealth 6, 296–310. Jost, C. C., S. Nzietchueng, S. Kihu, B. Bett, G. Njogu, E. S. Swai, and J. C. Mariner, 2010: Epidemiological assessment of the Rift Valley fever outbreak in Kenya and Tanzania in 2006 and 2007. Am. J. Trop. Med. Hyg. 83, 65–72. Kirsopp-Reed, K., 1994: A review of PRA methods for livestock research and development. RRA Notes, IIED IIED, London. Mariner, J. C., and R. Paskin, 2000: Manual on participatory epidemiology. Methods for the collection of action-oreinted epidemioligical intelligence. FAO Animal Health Manual.

14

E. Chenais et al.

Food and Agriculture Organization of the United Nations, Rome. Mariner, J. C., S. Hendrickx, D. U. Pfeiffer, S. Costard, L. Knopf, S. Okuthe, D. Chibeu, J. Parmley, M. Musenero, C. Pisang, J. Zingeser, B. A. Jones, S. N. Ali, B. Bett, M. McLaws, F. Unger, A. Araba, P. Mehta, and C. C. Jost, 2011: Integration of participatory approaches into surveillance systems. Rev. Sci. Tech. 30, 653–659. McCracken, J., J. Pretty, and G. Conway, 1988: An Introduction to Rapid Rural Appraisal for Agricultural Development. IIED Sustainable Agriculture Programme, London, UK. Muhangi, D., M. Ocaido, C. Masembe, K. Stahl, and S. Ndyanabo, 2012: Surveillance for African swine fever in Masaka and Rakai, Uganda. EPIZONE 6th Annual Meeting “Viruses on the move”. Mur, L., M. Atzeni, B. Martinez-Lopez, F. Feliziani, S. Rolesu, and J. M. Sanchez-Vizcaino, 2014: Thirty-Five-Year presence of african swine fever in Sardinia: history, evolution and risk factors for disease maintenance. Transbound Emerg. Dis. doi: 10.1111/tbed.12264. [Epub ahead of print]. Muwonge, A., H. M. Munang’andu, C. Kankya, D. Biffa, C. Oura, E. Skjerve, and J. Oloya, 2012: African swine fever among slaughter pigs in Mubende district, Uganda. Trop. Anim. Health Prod. 44, 1593–1598. NEPAD and FAO, 2004: Livestock Development Project BANKABLE INVESTMENT PROJECT PROFILE. Available at: http://www.fao.org/docrep/007/ae562e/ae562e00.htm (accessed October 1, 2014). Nissen, S., I. H. Poulsen, P. Nejsum, A. Olsen, A. Roepstorff, C. Rubaire-Akiiki, and S. M. Thamsborg, 2011: Prevalence of gastrointestinal nematodes in growing pigs in Kabale District in Uganda. Trop. Anim. Health Prod. 43, 567–572. OIE, 2013: OIE Animal health data. Available at http:// www.oie.int/en/animal-health-in-the-world/the-world-ani mal-health-information-system/the-oie-data-system/ (accessed November 27, 2013). Okell, C. N., G. P. Pinchbeck, A. P. Stringer, G. Tefera, and R. M. Christley, 2013: A community-based participatory study investigating the epidemiology and effects of rabies to livestock owners in rural Ethiopia. Prev. Vet. Med. 108, 1–9. Penrith, M. L., W. Vosloo, F. Jori, and A. D. Bastos, 2013: African swine fever virus eradication in Africa. Virus Res. 173, 228–246. Perry, B., and D. Grace, 2009: The impacts of livestock diseases and their control on growth and development processes that are pro-poor. Philos. Trans. R. Soc. Lond. B Biol. Sci. 364, 2643–2655. Perry, B. D., T. F. Randolph, J. J. McDermott, K. R. Sones, and P. K. Thornton, 2002: Investing in Animal Health Research to Alleviate Poverty. International Livestock Research Institute, Nairobi, Kenya. Phiri, I. K., H. Ngowi, S. Afonso, E. Matenga, M. Boa, S. Mukaratirwa, S. Githigia, M. Saimo, C. Sikasunge, N. Maingi, G. W. Lubega, A. Kassuku, L. Michael, S. Siziya, R. C. Krecek, E. Noormahomed, M. Vilhena, P. Dorny, and A. L. 3rd Willing-

© 2015 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

E. Chenais et al.

ham, 2003: The emergence of Taenia solium cysticercosis in Eastern and Southern Africa as a serious agricultural problem and public health risk. Acta Trop. 87, 13–23. Plowright, W., G. R. Thomson, and J. A. Neser, 1994: African swine fever. In: Coetzer, J. A. W., G. R. Thomson, and Tustin, R.C. (eds), Infectious Diseases in Livestock with Special Reference to Southern Africa, pp. 567–592. Oxford University press, Cape Town. Robyn, M., W. B. Priyono, L. M. Kim, and E. Brum, 2012: Diagnostic sensitivity and specificity of a participatory disease surveillance method for highly pathogenic avian influenza in household chicken flocks in Indonesia. Avian Dis. 56, 377–380. Ssewaya, A., 2003: Dynamics of chronic poverty in remote rural Uganda. In proceedings of: Staying Poor: Chronic Poverty and Development Policy, Univ. of Manchester, UK. St ahl, K., P. Ogweng, E. Okoth, T. Aliro, D. Muhangi, N. LeBlanc, P. Atimnedi, M. Berg, R. P. Bishop, H. B. Rasmussen, and C. Masembe, 2014: Understanding the dynamics and spread of African swine fever virus at the wildlife-livestock interface: insights into the potential role of the bushpig, Potamochoerus larvatus. Suiform Soundings, 13, 24–28. Taylor, D. J., 2006: Pig Diseases. 8th edn. D.J. Taylor, Glasgow. Thomson, G. R., M. L. Penrith, M. W. Atkinson, S. Thalwitzer, A. Mancuso, S. J. Atkinson, and S. A. Osofsky, 2013: International trade standards for commodities and products derived from animals: the need for a system that integrates food safety and animal disease risk management. Transbound Emerg. Dis. 60, 507–515. Tiongco, M., C. Narrod, R. Scott, M. Kobayashi, and J. Omiti, 2012: Understanding Knowledge, Attitude, Perceptions, and Practices for HPAI Risks and Management Options Among Kenyan Poultry Producers. In: Zilberman, D., J. Otte, D. Roland-Holst and D. U. Pfeiffer (eds), Health and Animal

© 2015 Blackwell Verlag GmbH • Transboundary and Emerging Diseases.

KAP ASF Uganda

Agriculture in Developing Countries, pp. 281–304. Springer, New York, Dordrecht Heidelberg London. UBOS, 2008: The National Livestock Census Report 2008. Ministry of Agriculture, Animal Industry & Fisheries, Entebbe, Uganda and Uganda Bureau of Statistics, Kampala, Uganda. Wachinger, G., O. Renn, C. Begg, and C. Kuhlicke, 2013: The risk perception paradox–implications for governance and communication of natural hazards. Risk Anal. 33, 1049–1065. Waiswa, C., E. M. Fevre, Z. Nsadha, C. S. Sikasunge, and A. L. Willingham, 2009: Porcine cysticercosis in southeast Uganda: seroprevalence in kamuli and kaliro districts. J. Parasitol. Res. 5. doi:10.1155/2009/375493. WHO (2008) Advocacy, Communication and Social Mobilization for TB Control: a Guide to Developing Knowledge, Attitude and Practice Surveys. WHO/HTM/STB/2008.46. WHO, Geneva, Switzerland. World Bank (2013) Available at: http://databank.world bank.org/data/views/reports/tableview.aspx (accessed 29th November 2013). Zaberezhnyı˘, A., T. Aliper, T. Grebennikova, O. Verkhovskiı˘, J. Sanchez-Vizcaino, L. Mur, E. Nepoklonov, and D. L’vov, 2012: African swine fever in Russian Federation. Vopr. Virusol. 57, 4–10.

Supporting Information Additional Supporting Information may be found in the online version of this article: Appendix S1. (a) Questionnare farmer PRAs and (b) Questionaire value chain actor PRAs. Appendix S2. Extensive list of answers.

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Knowledge, Attitudes and Practices Related to African Swine Fever Within Smallholder Pig Production in Northern Uganda.

Uganda is a low-income country with the largest pig population in East Africa. Pig keeping has a large potential, commercially and as a tool for pover...
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