Our pilot study results captured various demographic and herder activity data that might shed light upon how zoonotic disease transmission was occurring. All but one household reported a male as the head of the household. It was observed that this household appeared to have no adult male. Age of the head of the household was on average 41 years old. A similar study in Tov aimag found an older mean at 47 years old for heads of the household (Zhen et al. 2010). It is unknown if this observed difference was due to our focus upon sampling horse and camel herders, the aimags, or the 10-year sampling date difference, as the study in Tov took place in 2006.
Income was only reported by 14 households. All but two households in Umnugobi reported deriving all their income from livestock. Many reported not knowing their monthly income or that it varied depending on how many animals or animal products they sold. Other indications of wealth such as cell phones or a source of power, primarily solar panels (93.1%), were owned by all households (Table 2). Furthermore, cell phones have been used effectively worldwide to educate and improve health outcomes on other populations (Krishna et al. 2009), making this a potential platform for future public health outreach.
Education among nomadic families is known to be difficult due to the families’ frequent household movements and the labour requirements of herding (Steiner-khamsi and Gerelmaa 2008). Boys from herding families make up an educationally disadvantaged group in Mongolia, as in one report 60% of school dropouts under the age of 15 were boys from herding families (Steiner-khamsi and Gerelmaa 2008). A study conducted in Tov found that 32.4% of participants had at least a 10th grade education (Zhen et al. 2010), which was higher than our study of 26.7%. However, as Tov is more densely settled than most other aimags (Zhen et al. 2010), access to education may be more consistent. Education is an important factor for health. A study in Europe found that increased education correlated with improved health in men and women over 50 years old. Furthermore, only up to a third of the health effect was derived from differences in tobacco use, drinking, exercise, and body mass index (Brunello et al. 2016).
Increased movement for households has been linked to decreased health in Mongolian nomads, (Mocellin and Foggin 2008) and this may be more extreme in our sample for households who moved further as in their study, a smaller average of 9 km. Extreme weather events, such as drought and dzuds, are known to further increase movement as herders seek grazing and water for livestock (Miao et al. 2016). More than 90% of the households in this study moved at least once during the year. Umnugobi aimag had both the highest percent (13.3%) who did not move and two families who moved an estimated ten times in a year. Households moved on average ~ 4 times a year, traveling 16–34 km each move (Table 2). Umnugobi households moved the farthest, moving an average of 150 km each year.
In summary, our study population was comprised primarily of households headed by men with often only an eighth-grade education and access to solar-generated electricity and a mobile phone. More than 90% of these households moved throughout the year, and all but two derived all their household income from herding. By knowing the characteristics of the households, higher risk individuals in households can be defined by movement and poor education.
Zoonotic risks
Of all the household livestock, we only examined the number of horses and camels (Table 2). Not all households owned the animals for which they cared. The previously mentioned study in Tov (Zhen et al. 2010) reported fewer horses on average per household at 27 horses compared to the median of 40 in our study. The median number of camels owned per household at 70 was higher than horses. The 3–4 h that households spent with their horses or camels each day included milking and preparation for horse races. Observationally, this number was given for when they were working with the horses or camels and not assumed to be consistent year-round. While making airag (fermented mare’s milk), mares are milked five to seven times a day from late June until late summer/fall, depending on geographic region (Bat-Oyun et al. 2015). Bactrian camels were milked on average for 12 months between parturition in one study with a range between 9 and 18 months (Brezovečki et al. 2015). The Umnugobi households in this study reported milking their camels twice a day. Milking requires seasonal, daily interaction with adults and young of both species. Both species are known to be reservoirs for zoonotic diseases, so herders and especially those that milk or drink milk from these animals are at increased risk of zoonoses. In other livestock species, Brucella sp., Mycobacterium sp., Salmonella sp., Listeria monocytogenes, Campylobacter sp., Coxiella burnetii, and Escherichia coli have all been transmitted in unpasteurized milk (John 2006). Little to no research has been focused specifically up mare and camel milk handling in Mongolia, as observationally noted, milk is often drunk unpasteurized, such as with milk tea.
The presence of dogs in more than 90% of the study households carries transmission risks for zoonoses, including rabies, anthrax, and echinococcosis (Odontsetseg et al. 2009, Odontsetseg et al. 2007, Ito and Budke 2015). From 2003 to 2005, the most recent years reported by the study of rabies in Mongolia, cases in dogs surpassed cases in livestock (Odontsetseg et al. 2009). Dogs also shed hydatid Echinococcus. Sheep are the primary intermediate host for echinococcosis, but other livestock and humans can also serve as an intermediate host (Jacob and Lorber 2015). This lifecycle makes herder families at high risk for echinococcosis. A review of echinococcosis in Mongolia primarily looked at human caseloads. From 1997 to 2006, community serology studies have found between 2 and 12% of people positive for Echinococcus granulosus. Studies in domestic dogs have found Echinococcus spp.-positive dogs by both serology (25%) and necropsy (35%). Humans are primarily infected by accidental ingestion of food or water contaminated with dog feces (Ito and Budke 2015).
Zoonotic risks: Tobacco use
Tobacco use is prevalent in Mongolia. Our study found that 42.7% of heads of the household smoked, which is similar to the 48% of men nationally surveyed in 2014 (Demaio et al. 2014). In that survey, more urban men smoked, which may account for the lower level seen here. Smoking has been linked with an increase in being serologically positive for zoonotic strains of influenza, both swine and equine (Larson et al. 2015, Coman et al. 2014). This has been explained by increased likelihood of contracting the virus from touching an animal or surface and then one’s mouth as well as potentially from a lowered immune system from smoking. In our study, 69.1% of people used loose tobacco, which may increase the chance of fecal-oral contamination since the tobacco is handled by either rolling it in paper or placing it in a pipe. The 2014 national study found no effect of education on tobacco use, which was also seen in our study (Demaio et al. 2014).
Zoonotic risks: Fuel and water sources
Fuel source was most commonly wood followed by dried manure. Handling manure for burning as well as using it around cooking areas may increase the risk of enteric pathogen contamination of hands and food. A review of zoonotic pathogens associated with cattle manure found that Salmonella spp., Campylobacter spp., Listeria monocytogenes, Yersinia enterocolitica, Escherichia coli, Cryptosporidium parvum, and Giardia lamblia were all spread in manure. These are known as manure-borne pathogens (Pachepsky et al. 2006, Manyi-Loh et al. 2016). A minimum of three months is needed when the air is more than 0 °C to properly kill microbes in untreated, dry manure (Manyi-Loh et al. 2016). This is problematic in Mongolia where during much of the year the ambient temperature is below 0 °C.
Our findings in Uvurkhangai were similar to those found in Tov (Zhen et al. 2010) where ~ 40% used wood and ~ 60–70% used dried manure. Arkhangai used more wood (98.1%), and Umnugobi households reported burning dried manure for heat 24.3 times more often than the other two aimags. However, Umnugobi is hotter and drier than the other study sites, which may lower the risk of transmission of disease even when more households use dried manure for fuel.
Drinking water was most commonly from a river (60–70%) in Arkhangai and Uvurkhangai and from an electric well in Umnugobi (70%). Households in Arkhangai were 4.2 times more likely to use a river as their primary water sources than the other two aimags. Umnugobi was similar to Tov (Zhen et al. 2010) aimag, where water was most commonly from a well (72.8%) and then the river (51.5%). Livestock also used similar water sources as the people. Of the manure-borne pathogens, C. parvum is considered very infectious (Pachepsky et al. 2006) and is relevant to the Mongolian setting. A major source of C. parvum from livestock, primarily cattle, is infected drinking water (Hunter and Thompson 2005). Horses are also known to carry C. parvum (Galuppi et al. 2016), and camels have been found to carry other species of Cryptosporidium (Liu et al. 2014). Cryptosporidium sp. was found in rivers in Japan and China (Xiao et al. 2012, Ono et al. 2001), but no test results have been published for Mongolia. Because of their increased use of river water, Arkhangai may be at greater risk for waterborne pathogens than the other two aimags.
In 2015, the United Nations reported that 59.2% of Mongolian rural populations used improved drinking water sources; this included covered wells (United Nations Data 2017). This was not true in our study as more than 50% used the river as a water source. However, our study participants were not randomly chosen and were limited by type of livestock owned. In our study, 48.8% had access to wells, but it is unknown how many of these wells would be considered improved. Thus, focus should be upon lowering risks for transmission of manure-borne pathogens in all rural water sources.
Limitations
All responses were self-reported leading to possible misclassification. Specifically, some participants appeared to be hesitant or unable to give an exact number of the livestock or other domestic animals associated with the household. Some people counted those only belonging to the one household, and others claimed an amount for the extended family. This discrepancy was especially true when counting the number of dogs owned by the household compared to the number observed at the household residence. In future studies, it would be suggested to ask both numbers owned and numbers on premises. Also, as all households were not chosen randomly, external validity is a concern. Since our households were chosen by the local veterinarian, it would be expected that households that were missed were more isolated and zoonotic risks for these families could potentially be higher due to a lack of sanitation and water or more livestock diseases from reduced access to veterinary care.