Epidemiological Trends in Emerging Infectious Diseases

Abstract

Emerging infectious diseases (EIDs) -- novel pathogens or known pathogens appearing in new populations, geographies, or with altered virulence -- have increased in frequency by roughly threefold over the past four decades, driven by deforestation, urbanisation, intensified livestock farming, global travel, and climate change. The COVID-19 pandemic underscored just how devastating a single zoonotic spillover event can be, but it also exposed gaps in our ability to detect, characterise, and predict emerging disease threats systematically. In this study, we analysed epidemiological data on 1,842 EID events recorded between 1990 and 2021 across 194 countries, sourced from the WHO Disease Outbreak News, ProMED-mail, GIDEON, and peer-reviewed surveillance literature. We evaluated five analytical frameworks for characterising EID trends: temporal incidence modelling, spatial hotspot analysis, zoonotic spillover risk scoring, genomic surveillance integration, and pandemic preparedness indexing. Our Emerging Disease Trend Score (EDTS) integrates detection speed, geographic spread prediction, zoonotic risk accuracy, genomic characterisation coverage, and preparedness correlation. Genomic surveillance integration achieved the highest EDTS (0.922) through real-time phylogenetic tracking that identified variant emergence a median of 18 days before clinical case surges, while spatial hotspot analysis best predicted cross-border spread (accuracy 0.88). These findings support prioritising genomic surveillance infrastructure and spatial modelling capacity in national pandemic preparedness strategies.