Respiratory syndromic disease study in Shanghai community population

This prospective community-based cohort study (Acute Respiratory Infection Epidemiological Characteristics Assessment Study (ARI-ECAS)) aims to systematically monitor acute respiratory infection (ARI) incidence, characterise multiple pathogen coinfection patterns and explore microbial landscape dynamics in Shanghai's general population. By integrating syndromic surveillance, molecular diagnostics and metagenomic sequencing, the study seeks to enhance understanding of ARI epidemiology, seasonal variation and host-pathogen interactions to inform predictive modelling and optimise public health interventions in high-density urban environments.

The study enrolled 15 199 permanent residents from all 16 districts of Shanghai, with baseline oropharyngeal swab samples across five representative districts (Xuhui, Jing'an, Jiading, Songjiang and Fengxian). Inclusion criteria required residency ≥6 months and consent for weekly follow-ups. Exclusion criteria addressed mobility limitations (planned relocation >6 months) and recent ARI history. Participants provided demographic, behavioural and clinical data via the Shanghai Health Cloud platform, with baseline and symptomatic-phase biological samples collected for analysis.

During the initial 8-month surveillance period (May 2024-January 2025), the ARI-ECAS cohort demonstrated critical insights into the epidemiology of acute respiratory infections in Shanghai's urban communities. Among 15 199 participants, 10.96% reported symptomatic episodes, of whom 21.43% experienced recurrent infections. Pathogen detection using targeted next-generation sequencing (tNGS) identified microbial aetiologies in 53.52% of symptomatic cases, revealing a high prevalence of coinfections: 27.96% involved dual pathogens, while 33.01% showed polymicrobial interactions (≥3 pathogens). Notably, 85.09% of symptomatic episodes were self-managed, underscoring a low healthcare-seeking rate (14.91%) consistent with patterns observed in urban China during postpandemic transitions.

The current phase of data collection will conclude in June 2025; however, syndromic surveillance and tNGS protocols will be sustained to capture multiyear seasonal transmission patterns. To enhance comparative rigour, future protocols will aim to collect samples from participants during asymptomatic periods in the subsequent year to serve as seasonal baseline controls. Building on this foundation, the study will integrate contact behaviour and mobility surveys to quantify parameters critical for understanding pathogen transmission dynamics (eg, household contacts and public transportation usage). Furthermore, pathogen detection and metagenomic data will be combined with transcriptomic and metabolomic profiling in selected cases to model multipathogen interaction networks and delineate host immune response pathways, thereby advancing mechanistic insights into polymicrobial cocirculation.