Economic Consequences
Monetary losses due to paratuberculosis have been difficult to quantify. Due to the unknown magnitude of subclinical effects, as well as the inability to determine true prevalence, economic studies have been at best rough estimations and likely underestimate true costs.
Economic losses because of the disease are usually attributed to either milk loss, early culling, decreased carcass weight, increased susceptibility to other diseases or reduced fertility (Johnson et al., 2001; Mckenna et al., 2006; Raizman et al., 2009; Vazquez et al., 2012). For the US dairy industry, losses due to paratuberculosis have been estimated to be ~USS200± 160million per year (Losinger, 2005), whereas for the Canadian dairy industry, costs would be close to CAS15 million per year (Mckenna et al., 2006). Milk loss due to paratuberculosis are estimated to be ~2kg∕cow∕day for MAP-infected animals (Sorge et al., 2011; McAloon et al., 2016b). Faecal culture-positive cows are removed from the herd 124 days earlier and produce 11% less milk than faecal culture-negative herd mates (Raizman et al., 2007). Interestingly, there was increased milk production in cows prior to testing positive, suggesting a genetic susceptibility component to high producers (Sorge et al., 2011; Garcia and Shalloo, 2015; McAloon et al., 2016b).Cost estimates of paratuberculosis are mainly based on the reduced milk production, reduced carcass weights and increased disease susceptibility; there is, however, also a potential public health concern. There have been numerous studies on the viability of MAP in processed food. MAP has been detected in both milk and meat products and can survive both high temperature short time (HTST) pasteurization and desiccation (Savi et al., 2015; McAloon et al., 2019) as well as processing of some meat products and, although it has been demonstrated that cooking meat to well done will render it free of the bacterium (Mutharia et al., 2010), its presence in the raw product is a concern.
MAP has long been associated with Crohn's disease in humans, and there have also been studies that have demonstrated links to type 1 diabetes (Barkema et al., 2010). The current theory is that there is a genetic susceptibility to MAP and the development of autoimmune disorders (Sechi and Dow, 2015). If this theory is supported, this could harm future success and growth of the dairy industry. With a perceived public health risk, consumer confidence and demand for dairy will decline, resulting in potentially enormous economic losses (Groenendaal and Galligan, 2003). There are similar concerns in beef herds; however, the main economic consequence is reduced weaning weights, due to decreased milk production and direct effects of MAP infection (Roy et al., 2017). Estimated losses from these adjusted weaning weights amount to USS57∕calf from cows with elevated ELISA titres to USS157∕calf from cows that are heavy shedders (Bhattarai et al., 2013).Costs of implementing a paratuberculosis control programme must be balanced with disease cost (Pillars et al., 2009). The most effective control programmes at reducing disease prevalence are sometimes not the most economical (Webb Ware et al., 2012; Smith et al., 2017). Cost-benefit analysis often shows poor economic benefit to utilizing control programmes especially in low-prevalence herds (Collins and Morgan, 1991; Wolf et al., 2014; Kirkeby et al., 2016). Some economic models predicted only minor benefit in instituting control measures, even with subsidies (Groenendaal and Wolf, 2008; Wolf et al., 2014). Chiu et al. (2018) reported that utilizing a test and cull strategy to control paratuberculosis was less economically beneficial compared with culling based off low production in herds known to have MAP; however, these herds did not achieve eradication. Costs of culling cows as well as the low apparent prevalence of disease within the herd and the long lag until benefits of required management changes are evident are barriers to the adoption of paratuberculosis control programmes (Arrigoni et al., 2014; Cardwell et al., 2016; McAloon et al., 2017; Ritter et al., 2017).
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