Mapping factors associated with health system resilience against large-scale infectious disease outbreaks

A qualitative study in China

Datos Bibliográficos

ID15368488
AutoresShiyao Xu (Peking University), Hongyuan Wang (0009-0000-3110-568X), Li Z (0000-0002-6141-5184, Peking University), Fei Li (0009-0006-1479-2821, Peking University), Jincheng Li (0000-0002-0558-774X, Peking University Shenzhen Hospital), Bin He (0000-0001-7402-7183, Beijing Center for Disease Prevention and Control), Zhifeng Wang (0000-0003-0654-9953, Peking University, autor de correspondencia)
Año2026
Volumen26
Número1
Fecha de publicación2026-02-20
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaBMC Public Health (JOURNAL)
Identificadores de la revistaISSN: 1471-2458 • E-ISSN: 1471-2458
EditorialBioMed Central (PUBLISHER • GB)
DOI10.1186/s12889-026-26718-5
PMID41715036
OpenAlexW7130594873
IdiomaEN
Referencias citadas46

Resilient health systems have been demonstrated to be important in safeguarding global health security against crises. However, health system resilience against infectious disease outbreaks is not well understood because of the ambiguity in the details of the conceptualization, and lack of evidence on the specific capacities that health systems need to be resilient to infectious disease outbreaks. We aimed to provide a detailed understanding of health system resilience against large-scale outbreaks by exploring the relevant factors and clarifying the correlations among them based on empirical evidence. We conducted a qualitative study comprising interviews with key informants in fields related to infectious disease prevention and control from different levels of the health system in China (n = 31). We formed an initial theoretical model for interviews and analysis based on classic models of resilience and theories of infectious disease prevention and control. The experiences of key informants during COVID-19 were explored to collect empirical evidence. The interview data was analyzed to extract resilience-related factors using a hybrid approach of thematic analyses. The complex adaptive system was used to explain the complex correlations of factors during large-scale outbreaks. Five dimensions representing the antecedent condition, capacity, and improvement that impact health system resilience against COVID-19 pandemic were extracted: socio-demographic, systems and contingency plans, inputs and reserves, decision-making and community engagement, and recovery and feedback. These dimensions were categorized into 19 resilience-related factors in detail. These factors play different roles during infectious disease prevention and control, leading to outcomes and impact of large-scale outbreaks. A theoretical model was also developed to provide insight into the relationship of these factors and their roles in health system resilience against large-scale infectious disease outbreaks. Factors of antecedent condition, capacity, and improvement have an impact on health system resilience against large-scale outbreaks. More actions are needed for pandemic preparedness, outbreak control, reflection and feedback to enhance health system resilience. The resilience threshold concept should be calculated by quantitative research in the future

Ambiguity · Biostatistics · Disease · Infectious disease (medical specialty · Outbreak · Public health · Qualitative research · Safeguarding · Thematic analysis · COVID-19 epidemiological studies · Disaster Response and Management · Viral Infections and Outbreaks Research