Spatiotemporal analysis of influenza, pneumonia, and respiratory syncytial virus in association with environmental factors: A systematic review.

OBJECTIVES

Influenza, pneumonia, and respiratory syncytial virus are the leading causes of respiratory morbidity and mortality globally. Environmental factors influence the spread of these diseases, yet considerable variation remains in how these relationships are modelled across different climates and geographic scales. This systematic review evaluates the use of spatiotemporal frameworks to investigate the relationship between environmental factors and these diseases.

STUDY

DESIGN

Systematic review.

METHODS

A systematic search of PubMed, Embase, and Scopus identified peer-reviewed studies investigating the relationship between environmental factors and influenza, pneumonia, and respiratory syncytial virus using spatiotemporal modelling approaches. Methodological quality was assessed using the Spatial Methodology Appraisal of Research Tool. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines and was registered with PROSPERO.

RESULTS

Twelve studies met the inclusion criteria. Temperature and humidity were the most identified environmental determinants. Bayesian hierarchical models were the leading analytical framework for handling spatial and temporal dependencies. The interaction between environmental factors and area-level socioeconomic conditions significantly influenced local infection risk. Overall, the findings indicate that these relationships are often nonlinear and vary across locations, with threshold effects and geographical heterogeneity frequently reported.

CONCLUSIONS

Spatiotemporal modelling is a valuable tool for investigating the associations between environmental factors and respiratory infection risk. The reviewed evidence suggests that these relationships are often complex, delayed, and, in some cases, nonlinear. This study highlights temperature and humidity as the main environmental factors influencing respiratory infections, noting that local socioeconomic conditions strongly shape their impact. Effective public health surveillance should incorporate localised environmental characteristics and socioeconomic vulnerabilities to better address disease risk across diverse areas.