Global Estimate of Human Brucellosis Incidence

Abstract

Brucellosis is a major public health concern worldwide, especially for persons living in resource-limited settings. Historically, an evidence-based estimate of the global annual incidence of human cases has been elusive. We used international public health data to fill this information gap through application of risk metrics to worldwide and regional at-risk populations. We performed estimations using 3 statistical models (weighted average interpolation, bootstrap resampling, and Bayesian inference) and considered missing information. An evidence-based conservative estimate of the annual global incidence is 2.1 million, significantly higher than was previously assumed. Our models indicate Africa and Asia sustain most of the global risk and cases, although areas within the Americas and Europe remain of concern. This study reveals that disease risk and incidence are higher than previously suggested and lie mainly within resource-limited settings. Clarification of both misdiagnosis and underdiagnosis is required because those factors will amplify case estimates.

Keywords: Brucella; bacteria; brucellosis; brucellosis epidemiology; brucellosis incidence; human brucellosis.

Figure 1

Percentage completeness of World Organization of Animal Health annual reports that provide information on each of the zoonotic Brucella species, by worldwide region, 2014–2018. Each point on the plot denotes the 5-year average percentage completeness of reports from an individual country. Reporting the presence or absence of all Brucella species (B. abortus, B. melitensis, and B. suis) equates to 100%. Bar tops indicate mean % completeness for each region and error bars indicate SDs from each mean.

Figure 2

Heat map of global annual incidence of human brucellosis estimated per 1 million population at risk. Overall global risk is defined by the weighted average interpolation data (total number of new cases/total population at risk × 1 million). The global average is ≈500 new cases per 1 million persons at risk. The heat scale shows high risk to low risk; yellow (>4,000 cases) to blue (<1 case). This heatmap is intended to represent transnational zones that require priority control or surveillance initiative, not to represent the risk for individual countries.

Figure 3

Estimated distribution of annual human brucellosis incidence as determined by bootstrap resampling model for Africa (A), Asia (B), Americas (C), and Europe (D) and globally (E). Histograms generated via 1 million sample iterations based on observed reported case count values.

Figure 4

Estimated distribution of annual human brucellosis incidence as determined by Bayesian hierarchical model for Africa (A), Asia (B), Americas (C), and Europe (D) and globally (E). Histograms generated via 1 million sample iterations. Posterior distributions were estimated using a Markov chain Monte Carlo (MCMC) algorithm based on observed reported case count values. For the MCMC algorithm, 50,000 burn-in iterations were performed before the samples were retained.

Figure 5

Heatmaps of regional annual incidence of human brucellosis estimated per 1 million population at risk. Each region has a different scale for incidence per 1 million population at risk. Heatmaps are intended to represent transnational zones that require priority control or surveillance initiative, not to represent the risk of individual countries. The heat scale shows high risk to low risk; yellow to blue. A) Africa: average risk is ≈750 new cases per million; high is >3,000. B) Asia: average risk is ≈500 new cases per million; high is >4,000. C) Americas: average risk is ≈20 new cases per million; high is >75. D) Europe: average risk is ≈10 new cases per million; high >100.