Prevalence, Associated Factors, and Temporal Trends of Brucella Detection Across Human and Animal Hosts in Bangladesh: A 25-Year Meta-Analysis.

BACKGROUND

Brucellosis remains an important zoonotic disease in Bangladesh, yet evidence on its prevalence across human and animal hosts is fragmented and heterogeneous.

OBJECTIVES

This study aims to synthesize evidence on Brucella detection across human and animal hosts in Bangladesh and to evaluate associated study-level factors and temporal patterns.

METHODS

The data were extracted from eligible studies published between 2000 and 2024 following a systematic review framework. Pooled prevalence was estimated using a random-effects meta-analysis. Heterogeneity was assessed using Cochran's Q and I2 statistics. Subgroup meta-analyses and univariable meta-regression were conducted to examine variation by host species, diagnostic method, and study-level factors. Forecasting was performed using ARIMA models on annual study-reported Brucella detection, with model performance evaluated using AIC, MAE, and RMSE.

RESULTS

The pooled Brucella detection across hosts was 3.75% (95% CI: 3.07-4.56), with substantial heterogeneity (I2 = 89.5%). Detection was the highest in dogs (7.49%) and the lowest in horses (1.78%)). Among evaluated variables, abortion history was the only study-level factorsignificantly associated with higher Brucella positivity, with aborted animals showing approximately 10 times higher odds of detection compared to non-aborted animals (OR = 10.09, 95% CI: 4.64-21.93, p <0.001). Temporal patterns suggested a decreasing trend in goats and an increasing trend in cattle; however, these likely reflect variation in study design, diagnostics, and coverage rather than true epidemiological change.

CONCLUSION

Brucella exposure and detection persist across multiple host species in Bangladesh, with variation largely driven by methodological and host-related differences. These findings underscore the need for standardized diagnostic and reporting approaches and support integrated One Health surveillance to improve interpretation and control strategies in Bangladesh.