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This work addresses the impacts of endemic FMD on some of the poorest sections of society in a developing country. Until recently, this area has received scant coverage in the literature despite FMD affecting a large number of animals and the importance of livestock to rural livelihoods and food security in these countries (Knight-Jones & Rushton, 2013).

Key conclusions from this chapter are

a) Livestock play a vital role in the livelihoods of rural communities in northern Tanzania. In this study, livestock sales were the most important mechanism of cash release. The majority of households relied on milk from their livestock for daily consumption and as source of income. In addition, oxen were depended upon to pull ploughs and carts for crop production.

b) People in the study area were familiar with FMD in their livestock and their reports of frequent outbreaks were supported by findings from active surveillance and by FMD seroprevalence patterns.

c) Households in all three livestock practices in northern Tanzania reported a wide range of impacts on the productivity of their livestock due to FMD.

Brucellosis Tick borne (not ECF) Malignant catharral fever Trypanasomiasis Foot−and−mouth disease East Coast fever Anthrax/Blackleg

−0.2 0.0 0.2

Proportion of times ranked above other disease minus average

Rural smallholder N = 23

the most important livestock diseases in the region.

The serious impacts due to FMD on milk and crop production reported by the households in this study resonate with those of households in Ethiopia and South Sudan (Barasa et al., 2008; Bayissa et al., 2011; Jemberu et al., 2014). The significant effect of FMD outbreaks on milk production and drought capacity are consistently reported in these studies.

However, the seroprevalence of FMDV in cattle in the present study (69%) was three times higher than reported in an Ethiopian study (23%) (Bayissa et al., 2011).

FMD has impacts on the emerging economy of intra-regional livestock trade that has the potential to empower the rural poor (Little, 2009). For example, weight loss in livestock due to FMD influences decisions about when to sell. Pastoral and agropastoral households reported durable (1 -2 month) impacts on crops, milk, livestock weight and draught capacity and multiple FMD outbreaks per year. This would explain why FMD is ranked as the most important livestock disease by agropastoralists and second only to East Coast Fever by pastoralists. Several other studies have similarly reported high ranking of FMD amongst livestock diseases of importance in East Africa (Bedelian et al., 2007; Cleaveland et al., 2001; Jost et al., 2010; Ohaga et al., 2007). As well as impacts due to acute FMD, almost a quarter of households reported one or more animals with chronic heat intolerance syndrome. This chronic condition has been previously documented in Tanzania and elsewhere in East Africa (Barasa et al., 2008; Bayissa et al., 2011; Catley et al., 2004;

Rufael et al., 2008), and is reported to cause reduced milk yield and draught capacity and increased calving interval for the lifetime of affected livestock (Bayissa et al., 2011). On top of production lossess, and consistently with other studies (Subramaniam et al., 2013), the majority of livestock owners reported altered work patterns due to the care requirements of FMD infected livestock, contributing to FMD induced attrition of resources.

A strong similarity was evident between patterns suggested by household reports about FMD, and those detected by laboratory analyses and longitudinal studies. Seroprevalence patterns, observations of serial outbreaks in the same herds and clinical examinations by

frequency of outbreaks were supported by laboratory data. Given that livestock may remain NSP seropositive for three years or more after an FMD infection (Elnekave et al., 2015), it makes sense that FMD outbreaks ever or in the past year were better explanatory variables for seropositivity than FMD outbreaks in the past four months.

These consistencies between household reports and laboratory analyses increase confidence in conclusions based on household reports of FMD, including the very high variation in reported morbidity in this study. Furthermore, even when including only the herds that were clinically examined, the high variation in morbidity remained, and other studies in endemic countries have reported similarly high variability in morbidity (Gonzales et al., 2014)(Klein et al., 2008). Median herd level reported morbidity for cattle (42.9%) was lower than that reported for a European breed dairy herd in Kenya (62.1%) (Lyons et al., 2015) and for Ethiopian cattle (60.8-74.3%) (Jemberu et al., 2014).

The variation in reported FMD morbidity within and between studies may be partially explained by subclinical infections. Early experimental studies recognised that when cattle were serially infected with different serotypes of FMD (as is likely to happen to northern Tanzanian cattle), clinical signs were milder in latter infections (Cottral & Gailunas, 1971).

This may explain the lack of association between seropositivity and reported morbidity in this study. Subclinical FMD infections were also suggested in a study of FMD outbreaks in a partially immune population of Bolivian cattle where there were FMDV NSP positive results in cattle with no recorded clinical signs (Gonzales et al., 2014). A recent study in Uganda also reported SAT1 infection in cattle in absence of any observed clinical signs (Dhikusooka et al., 2016). Further studies are needed to investigate post-infection immunity to FMD and the proportion of infected animals that show clinical signs of FMD through serial outbreaks.

Similarly to this study’s finding of higher reported morbidity in pastoral settings, an Ethiopian study also demonstrated that pastoralists reported higher morbidity in their livestock compared to crop-livestock mixed systems (Jemberu et al., 2014). Pastoralists may have reported higher morbidity in their small ruminants because of their greater dependence on these species for milk, as evidenced by the livestock usage described in this study. Subsequently, they may have monitored the health of their sheep and goats more

to pastoral livestock being more vulnerable to FMD due to the more challenging conditions which they live in, which could influence susceptibility to disease.

The finding that the SAT1 serotype caused outbreaks with higher morbidity levels than serotype A warrants further investigation over a longer period of time. More serotype A outbreaks occurred in the dry season, but even when season was investigated with a univariable model, it did not explain morbidity. Further, SAT1 outbreaks occurred in both wet and dry seasons, but still had the greatest positive effect on reported morbidity. Given the frequency of FMD outbreaks in the study area, herd immunity to the different serotypes may also have played a role in the relative morbidity. It is also possible that the serotype A virus was a less virulent virus than the SAT viruses that caused the outbreaks during this study.

The negative effect of herd size on reported morbidity could be due to the increased difficulty for the owners of large herds to examine every animal in detail. This could potentially result in under-reporting of animals with clinical signs in large herds. Further, in low morbidity outbreaks, a single animal observed with clinical signs would make up a larger proportion of a small herd compared to a large herd.

As well as differences in morbidity, this study also suggested a difference in the seasonality of outbreaks reported by pastoral and agropastoral respondents. Pastoral households reported more FMD outbreaks in the wetter months, and agropastoralists reported more in the dry months. However, as inferences were dependent on recollected outbreak dates, further active surveillance is necessary to endorse this idea. Gaining insight into the timing of FMD outbreaks is important to better understand their impacts as well as their epidemiology. For example, outbreaks during the “hunger gap” at the end of the dry season in South Sudan have maximal negative impact on human nutrition (Barasa et al., 2008).

Like the agropastoral area in this study, a study in Ethiopia reported more outbreaks in the

Victoria indicated that more FMD outbreaks were reported between May and July (after the long rains) and in January and February (after the short rains) and attributed this to increased livestock movements (Genchwere et al., 2014). In the relatively more arid pastoral areas, FMDV may be more vulnerable to desiccation during the dry season, and subsequently reduced transmission. FMDV is known to be more stable and to retain its infectivity for longer at higher humidity (Donaldson, 1973). This has been suggested as an explanation for increased wet season FMD outbreaks in India and Pakistan (Subramaniam et al., 2013; Klein et al., 2008).

Differences in pastoral livestock management practices throughout the year could also explain why they may have more FMD outbreaks during the wetter months. Wildebeest calving occurs in the pastoral areas of the study area between February and June. To avoid MCF associated with calving wildebeest, pastoralists move their cattle (Bedelian et al., 2007; Cleaveland et al., 2001; Lankester et al., 2015b), and herds from multiple different areas congregate elsewhere. This movement and mixing of cattle during the wetter season could explain why pastoralists reported more FMD in the wetter season. In contrast, wildebeest do not go to the agropastoral area for calving, meaning that agropastoralists do not need to move their cattle during these months. Anecdotally, Simanjiro pastoralists report increased livestock diseases, including FMD, when cattle from different areas congregate on the hilly areas to avoid the wildebeest calving (Dr Ahmed Lugelo, personal communication). This raises the potential for an interplay between the impacts of FMD and MCF.

Unlike morbidity and seasonality, milk losses were similarly high in all three management systems in our study. Even in absence of FMD, the milk production reported compares poorly to what would be expected from native breed cattle (Kurwijila, 2001), especially in pastoral and agropastoral systems, and is on a different scale to what more intensively managed European breed cattle can produce in East Africa (Lyons et al., 2015b). Rural smallholder livestock produced more milk than those in the pastoral or agropastoral areas in this study and this resonated with better child health status and food security reported for smallholders versus pastoralists in another study in the same area (Lawson et al., 2014).

Whilst smallholders owned fewer animals, they had a greater proportion of exotic breeds, higher milk yield per animal and were likely to benefit from milk sales in the adjacent

seroprevalence (37.1%) of FMD in smallholder livestock was consistent with the lower rank (third in importance) that smallholders attributed to this disease. Never the less, smallholders reported similar milk losses to the other systems when outbreaks occurred.

Similarly to this study, a study in Ethiopia also reported higher FMD related impacts on pastoralists compared to smallholders (Jemberu et al., 2014).

Pastoral livestock have low milk outputs but this is the management system that can least afford reduced milk yield due to FMD. Whilst many pastoral households reported some degree of crop production, this is on a small scale compared to smallholder or agropastoral systems (Tanzania Natural Resource Forum, 2011). Pastoralists were the only management system where some households milked their sheep as well as goats and cattle, adding evidence to the degree to which they rely on milk as a food source. None of the pastoralists in the Loliondo area reported eating meat at regular intervals, highlighting the role of milk as a vital source of protein in their diet. A study of child health in northern Tanzania similarly highlighted that pastoralists were most dependent on milk for protein and most vulnerable to food insecurity (Lawson et al., 2014). This emphasises the severity of FMD’s impact on this management system, as has been reported in other parts of East Africa (Barasa et al., 2008; Bayissa et al., 2011; Jemberu et al., 2014; Rufael et al., 2008), with potential repercussions for human nutrition. For example, milk reductions due to severe drought on child mortality have been clearly documented (Seaman et al., 1978) and further studies are needed to investigate the association between FMD related milk decreases and human health. As well impacts on human nutrition, it is also likely that milk reduction may cause mortality in young animals during outbreaks, as has been reported in this study.

In addition to implications of FMD for human nutrition, pastoral households reported potential human infections due to FMD, and households in all three management systems were aware of this potential. It is known that humans can contract FMD from drinking the milk of infected animals (Bauer, 1997) and this is how the majority of respondents in this study believed that people contracted FMD. It is also possible that people succumb to respiratory infections secondary to nutritional stress during outbreaks or that they better

In conclusion, this study demonstrates significant impacts of FMD on traditional livestock keeping systems in northern Tanzania. People living in this region are already faced with high levels of poverty in a challenging environment of increasing human populations, decreased land availability and climate change (Upton, 2004). Their livelihood strategies show resilience, and optimal use of their livestock may represent a pathway out of poverty.

Control of FMD would allow them to invest extra resources on pursuing this path.

Livestock movement, whilst a risk factor for FMD, is integral to the pastoral way of life and allows maximum benefit to be derived from land as well as being the least harmful system to wildlife conservation (Castel, 2006; Nelson, 2012). Supporting FMD control in a way that supports traditional livestock keeping systems is therefore justified upon the grounds of conservation and sustainable land use as well as on a humanitarian basis.

Chapter 4: Risk factors for