Economic losses due to foot-and-mouth disease (FMD) in Ethiopian cattle.

Ethiopia's cattle population is among the largest in Africa and is burdened by frequent foot-and-mouth disease (FMD) outbreaks. FMD is caused by several distinct and highly contagious viral strains that can result in acute disease in cattle, causing losses in productivity and impeding international trade. This economic simulation study considered four main sources of losses due to FMD in cattle: reduced milk yield, draft power yield, fertility, and increased mortality. Economic losses were estimated per case across age-sex strata in 89 Ethiopian administrative zones for the years 2010-2021 using a wide range of data to estimate distributions for 30 input variables in a series of Monte Carlo simulations. It was estimated that an average case of FMD in Ethiopian cattle results in losses (mean values reported followed 95 % confidence intervals in brackets) of US dollars (USD) 11 (USD 7-USD 16) per case. Losses resulting from an average outbreak were estimated to be USD 2300 (USD 1400-USD 3300), while national annual losses were estimated to be USD 0.9 Mil. (USD 0.2 Mil.-USD 2.3 Mil.). Per cow-year, based on a national cow population of approximately 39 Mil. head, these estimated annual losses are equivalent to losses of only USD 0.02 (USD 0.01-USD 0.06). Nationally, these losses were significantly less than previously estimated in the literature, with currently estimated losses more accurately reflecting the economic burden of FMD in Ethiopian cattle over the past decade. The relatively small estimated losses suggest that control efforts based on widespread vaccination in countries with primarily extensive cattle production systems, such as Ethiopia, are unlikely to be economically sound. Sensitivity analyses suggested losses would be far greater in intensive systems, and that certainty surrounding incidence rates is paramount to the formulation of economically sound animal healthpolicy in regions with endemic FMD.

Social network analysis reveals the failure of between-farm movement restrictions to reduce Salmonella transmission.

An increasing number of countries are investigating options to stop the spread of the emerging zoonotic infection Salmonella Dublin (S. Dublin), which mainly spreads among bovines and with cattle manure. Detailed surveillance and cattle movement data from an 11-yr period in Denmark provided an opportunity to gain new knowledge for mitigation options through a combined social network and simulation modeling approach. The analysis revealed similar network trends for noninfected and infected cattle farms despite stringent cattle movement restrictions imposed on infected farms in the national control program. The strongest predictive factor for farms becoming infected was their cattle movement activities in the previous month, with twice the effect of local transmission. The simulation model indicated an endemic S. Dublin occurrence, with peaks in outbreak probabilities and sizes around observed cattle movement activities. Therefore, pre- and postmovement measures within a 1-mo time window may help reduce S. Dublin spread.