ArticleInfluenza and other respiratory viruses2022
Investigating the effects of population density of residence and rural/urban classification on rate of influenza-like illness symptoms in England and Wales.
Article in Influenza and other respiratory viruses, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Monitoring influenza-like symptoms in the UK through participatory surveillance: Insights from FluSurvey over two winter seasons (2023-24 and 2024-25).PLOS digital health · 2026Article
- Temporal patterns and risk factors of recurrent influenza infection: a population-based epidemiological study.BMC public health · 2026Article
- A spatio-temporal causal network for multi-scale analysis of infectious respiratory diseases transmission.Infectious Disease Modelling · 2026Article
- Epidemiological trends of laboratory-confirmed influenza cases driven by meteorological factors in Anhui Province, China: a multi-city time-series analysis.BMC public health · 2025Article
- Impact of multiple environmental factors on influenza-like illness in Fujian Province, China, 2015-2023: a multicity study.Frontiers in public health · 2025Article
- Associations between Short-Term Exposure to Ambient Air Pollution and Influenza: An Individual-Level Case-Crossover Study in Guangzhou, China.Environmental health perspectives · 2023Article
- Investigating the effects of population density of residence and rural/urban classification on rate of influenza-like illness symptoms in England and Wales.Influenza and other respiratory viruses · 2022Article
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Abstract
backgroundBetter understanding of risk factors for influenza could help improve seasonal and pandemic planning. There is a dearth of literature on area-level risk factors such as population density and rural/urban living.
methodsWe used data from Flusurvey, an online community-based cohort that records influenza events. The study outcome was symptoms of influenza-like illness (ILI). Multivariable Poisson regression analysis was used to explore associations of both population density and rural/urban status with rate of ILI symptoms and whether these effects differed by vaccination status.
resultsOf the 6177 study participants, the median age was 45 (IQR 32-57), 65.73% were female, and 66% reported at least one episode of ILI symptoms between 2011 and 2016. We found no evidence to suggest that the rate of ILI symptoms was higher in the medium [RR 1.02 (95% CI 0.95-1.09)] or high [RR 1.02 (95% CI 0.96-1.09)] population density group versus the low population density group. This was the same for the effect of urban living [RR 0.96 (95% CI 0.90-1.03)] versus rural living on symptom rate. There was weak evidence to suggest that the ILI symptom rate was lower in urban areas compared with rural areas among unvaccinated individuals only [RR 0.90 (95% CI 0.83-0.99)], whereas no difference was seen among vaccinated individuals [1.04 (95% CI 0.94-1.16)].
conclusionsAlthough neither population density nor rural/urban status was associated with ILI symptom rate in this community cohort, future research that incorporates activity and contact patterns will help to elucidate this relationship further.
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