Disparities in Beef Tapeworm Identification Rates in the Abattoirs of Gauteng Province, South Africa: A Descriptive Epidemiologic Study

Abstract

BackgroundBovine Taenia saginata cysticercus infections (also called bovine cysticercosis or beef measles) is usually diagnosed in cattle only during post-mortem meat inspection. The aim of this study was to investigate the identification rates of these infections in and to identify predictors/determinants of variations in the identification rates in abattoirs in Gauteng province, South Africa.MethodsRetrospective data for over 1.4 million cattle carcasses inspected in 26 abattoirs between January 2010 and December 2013 were used for the study. The identification rates (proportion of bovine Taenia saginata cysticercus positive carcasses) were computed and generalized estimating equations used to identify predictors/determinants of identification rates.ResultsThe overall identification rate was 0.70% (95% CI: 0.45, 0.95). Significantly (p< 0.05) lower rates were reported during summer (0.55%) than other seasons. Some geographic areas reported significantly (p<0.05) higher rates than others. The identification rates in high throughput abattoirs was significantly (p<0.05) higher (RR: 9.4; 95% CI: 4.7–19.1) than in low throughput abattoirs. Similarly, the identification rates among animals from feedlots were significantly (p<0.05) higher (RR: 1.6; 95% CI: 1.7–3.5) than those from non-feedlot sources. No significant (p>0.05) association was identified between identification rates and either the number of meat inspectors per abattoir or the provider of inspection services.ConclusionAlthough no significant association was found between identification rates and provider of inspection services, follow-up studies will need to be done to specifically investigate the potential conflict of interest arising from the fact that abattoir owners hire meat inspection services directly. Capture of abattoir surveillance data needs to include farm address and for each case to be reported separately. Finally, information on the type of identified cysts (alive or calcified) need to be collected to help better estimate risk to consumers. This study provides useful baseline data to guide future studies, surveillance and control efforts.

Sero-prevalence of Taenia spp. infections in cattle and pigs in rural farming communities in Free State and Gauteng provinces, South Africa

“…Surveys previously conducted in different South African areas reported prevalence of 0.5 -2.07% (Viljoen, 1937) and 0 -9.1% (Heinz and MacNab, 1978) based on meat inspection records. Qekwana et al (2016) recently reported 0.70% (95% CI: 0.45, 0.95) prevalence of bovine cysticercosis in Gauteng. The results found in the current study were not surprising, as it has been reported repeatedly that the sensitivity of meat inspection is much lower than that of the AgELISAs (Harrison et al, 1989;Onyango-Abuje et al, 1996;Dorny et al, 2002;Kyvsgaard et al, 1990;Dorny et al, 2000;Rodriguez-Hidalgo et al, 2003;Asaava et al, 2009).…”

Pig Abattoir Inspection Data: Can It Be Used for Surveillance Purposes?

“…It enables an alarm to be raised when the other components fail [ 5 , 27 ]. Elsewhere, several studies [ 4 , 5 , 6 , 7 , 28 , 29 , 30 , 31 ] have evaluated the use of abattoir data for integration in syndromic surveillance systems, for the early detection of emerging diseases in livestock animals or to measure animal health and welfare. Some of the advantages identified were the good coverage and availability of syndromic indicators; while some of the limitations were the lag of time between reporting and occurrence of disease in live animals and the influence on the results of abattoir-related factors.…”

Helminths of zoonotic importance in slaughtered food animals in Nigeria: a systematic review and meta-analysis

“…Individual prevalence estimates for helminths of public-health importance, such as Cysticercus cellulosae (9.54%), C. bovis (2.19%), hydatid cyst (0.08%) and F. gigantica (1.81%) were all on the lower limits of the ranges of 0.7–34.4% (Porphyre et al ., 2015; Qekwana et al ., 2016; Thomas et al ., 2016), 0.16–77.3% (Otupiri et al ., 2000; Garedaghi et al ., 2011; Fonteh et al ., 2016), 3.4–90.65% (Kabir et al ., 2010; Taghavi et al ., 2013; Mhoma et al ., 2014) and 2.15–26.51% (Otupiri et al ., 2000; Yilma & Mesfin, 2000; Jean-Richard et al ., 2014), respectively, documented in other resource-limited countries. The fact that the prevalence rates reported in this study are pooled estimates of several studies may explain why they were at the lower limits of these documented ranges.…”