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. 2022 Feb 16;7(2):28.
doi: 10.3390/tropicalmed7020028.

Exposure of South African Abattoir Workers to Coxiella burnetii

Liesl De Boni  1   2 , Sumaya Mall  2 , Veerle Msimang  3 , Alex de Voux  1 , Jennifer Rossouw  3 , John Frean  3   4
Affiliations

Exposure of South African Abattoir Workers to Coxiella burnetii

Liesl De Boni et al. Trop Med Infect Dis. .

Abstract

Abattoir workers may contract Q fever by inhalation of Coxiella burnetii bacteria in aerosols generated by slaughtering livestock, or in contaminated dust. We estimated the seroprevalence of C. burnetii and examined the associated factors in a survey of South African abattoir workers. Coxiella burnetii seropositivity was determined by detection of IgG antibodies against C. burnetii phase II antigen. Logistic regression, adjusted for clustering and sampling fraction, was employed to analyze risk factors associated with C. burnetii seropositivity. Among 382 workers from 16 facilities, the overall seroprevalence was 33% (95% confidence interval (CI): 28-38%) and ranged from 8% to 62% at the facility level. Prolonged contact with carcasses or meat products (odds ratio (OR): 4.6, 95% CI: 1.51-14.41) and prior abattoir or butchery work experience (OR: 1.9, 95% CI: 1.13-3.17) were associated with C. burnetii seropositivity. In contrast, increasing age and livestock ownership were inversely associated. Precautions to protect abattoir personnel from Q fever are discussed.

Keywords: Coxiella burnetii; Q fever; Q fever prevalence; abattoir workers; meat workers; seroprevalence; slaughterhouse workers.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of this study; in the collection, analyses, or interpretation of data; in the writing of this manuscript, or in the decision to publish these results.

Figures

Figure 1
Figure 1
Locations of abattoir facilities sampled in the abattoir survey, South Africa, 2018.
Figure 2
Figure 2
Factors significantly associated with Coxiella burnetii seropositivity in the multivariable logistic regression analysis of the abattoir survey, South Africa, 2018.
See this image and copyright information in PMC

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