Influenza and other respiratory viruses · 2022
Investigating the effects of population density of residence and rural/urban classification on rate of influenza-like illness symptoms in England and Wales.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Tunnicliffe Louis, Warren-Gash Charlotte
Аннотация
BACKGROUND: Better 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.
METHODS: We 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.
RESULTS: Of 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)].
CONCLUSIONS: Although 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.
METHODS: We 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.
RESULTS: Of 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)].
CONCLUSIONS: Although 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.