Epidemiological characteristics of co-infection between porcine epidemic diarrhea virus (PEDV) and other pathogens: a meta-analysis and systematic review.

backgroundCurrently, despite numerous local epidemiological investigations, knowledge of porcine epidemic diarrhea virus (PEDV) coinfections remains fragmented. Most existing studies are restricted to individual regions or specific farms with limited sample sizes, and a comprehensive synthesis of PEDV coinfection epidemiology at the global level remains lacking. Consequently, the overall prevalence of PEDV coinfections, predominant pathogen combinations, and their spatiotemporal dynamics remain poorly defined. Here, we systematically characterize PEDV coinfections with other pathogens and investigate their spatiotemporal distribution across China.

methodsThis study strictly followed the PRISMA guidelines. Four major databases (CNKI, PubMed, Web of Science, and Scopus) were systematically searched for cross-sectional epidemiological studies on PEDV coinfections published from database inception to February 1, 2026. In total, 60 eligible studies comprising 49,455 samples were included. Meta-analysis, subgroup analysis, meta-regression, and spatiotemporal stratification were conducted.

resultsThe pooled coinfection rate of PEDV with other pathogens was 12% (95% CI: 0.09–0.16). Funnel plots, together with Egger’s and Begg’s tests, indicated no significant publication bias, and sensitivity analyses confirmed the robustness of the findings. A total of 121 coinfection patterns were identified, with double infections predominating (83.47%), followed by triple (14.88%) and quadruple infections (1.65%). Among double infections, PEDV-PDCoV was the most common combination (23.1%), followed by PEDV-TGEV (13.2%) and PEDV-PoRV (10.7%). Subgroup analyses demonstrated that farm size and coinfection type were the primary sources of heterogeneity (both P < 0.001). Spatiotemporal analyses across five geographical regions of China revealed pronounced heterogeneity in PEDV coinfections. The eastern (ES = 12.40%, I² = 74.9%) and northwestern (ES = 12.90%, I² = 75.4%) regions exhibited the highest coinfection rates and the most complex pathogen profiles. In contrast, the central-southern region showed the lowest coinfection rate (ES = 2.50%, I² = 50.6%), suggesting effective PEDV control. The northern region displayed stable epidemic characteristics, with coinfections exclusively involving PDCoV (ES = 6.60%, I² = 0%), whereas the southwestern region showed a declining trend in single infections accompanied by an increase in coinfections (ES = 5.50%, I² = 68.2%).

conclusionThis study characterizes the epidemiological features, predominant pathogen combinations, and China’s regional spatiotemporal patterns of porcine epidemic diarrhea virus (PEDV) co-infections. However, these findings should be interpreted with caution, as potential detection bias exists; the reported co-infection rates and pathogen profiles were influenced by heterogeneity in the panels of target pathogens tested across the included studies. Despite this limitation, our results provide valuable data to support the development of region-specific, precision-based diagnostic and prevention strategies for PEDV-associated diseases. SYSTEMATIC REVIEW REGISTRATION: Open Science Framework ( https://doi.org/10.17605/OSF.IO/9UY8F ).