Kefyalew Addis Alene , Hannah C. Moore , Archie C.A. Clements , Beth Gilmour , Dylan D. Barth , Rebecca Pavlos , Ben Scalley , Christopher C. Blyth
{"title":"Spatiotemporal patterns of influenza in Western Australia","authors":"Kefyalew Addis Alene , Hannah C. Moore , Archie C.A. Clements , Beth Gilmour , Dylan D. Barth , Rebecca Pavlos , Ben Scalley , Christopher C. Blyth","doi":"10.1016/j.puhip.2025.100602","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Understanding the geospatial distribution of influenza infection and the risk factors associated with infection clustering can inform targeted preventive interventions. We conducted a geospatial analysis to investigate the spatial patterns and identify drivers of medically attended influenza infection across all age groups in Western Australia (WA).</div></div><div><h3>Methods</h3><div>Data for confirmed influenza cases were obtained from the WA Notifiable Infectious Diseases Database for the period 2017–2020. Data were also obtained for vaccination coverage, meteorological parameters, socioeconomic indicators, and healthcare access. Spatial clustering of influenza incidence was identified using Global Moran's I and Getis-Ord statistic. Bayesian spatial models were used to identify factors associated with spatial clustering of infection.</div></div><div><h3>Results</h3><div>Of the 36,228 influenza cases reported, over half (18,773, 51·8 %) were in individuals aged between 15 and 64 years and more than three quarters (28,545, 78·9 %) in the Perth metropolitan region. The annual incidence rate ranged from 2·7 per 1000 population in individuals aged between 15 and 64 years to 5·2 per 1000 population in children <5 years of age. For all age groups, the lowest incidence (0·4 per 1000 population) and the highest incidence rate (8·8 per 1000 population) were reported during and pre-the COVID-19 pandemic respectively. The influenza incidence rate shows both seasonal and spatial variation. Spatial clustering was significantly associated with distance to the nearest health facility in minutes (<em>B</em> = −0·181; 95 %CrI: 0·279, −0·088) and annual mean temperature in degrees Celsius (<em>B</em> = 0·171; 95 %CrI: 0·015, 0·319).</div></div><div><h3>Conclusions</h3><div>Spatial clustering of influenza incidence was significantly associated with climatic conditions and healthcare access.</div></div>","PeriodicalId":34141,"journal":{"name":"Public Health in Practice","volume":"9 ","pages":"Article 100602"},"PeriodicalIF":1.9000,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Public Health in Practice","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666535225000217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Understanding the geospatial distribution of influenza infection and the risk factors associated with infection clustering can inform targeted preventive interventions. We conducted a geospatial analysis to investigate the spatial patterns and identify drivers of medically attended influenza infection across all age groups in Western Australia (WA).
Methods
Data for confirmed influenza cases were obtained from the WA Notifiable Infectious Diseases Database for the period 2017–2020. Data were also obtained for vaccination coverage, meteorological parameters, socioeconomic indicators, and healthcare access. Spatial clustering of influenza incidence was identified using Global Moran's I and Getis-Ord statistic. Bayesian spatial models were used to identify factors associated with spatial clustering of infection.
Results
Of the 36,228 influenza cases reported, over half (18,773, 51·8 %) were in individuals aged between 15 and 64 years and more than three quarters (28,545, 78·9 %) in the Perth metropolitan region. The annual incidence rate ranged from 2·7 per 1000 population in individuals aged between 15 and 64 years to 5·2 per 1000 population in children <5 years of age. For all age groups, the lowest incidence (0·4 per 1000 population) and the highest incidence rate (8·8 per 1000 population) were reported during and pre-the COVID-19 pandemic respectively. The influenza incidence rate shows both seasonal and spatial variation. Spatial clustering was significantly associated with distance to the nearest health facility in minutes (B = −0·181; 95 %CrI: 0·279, −0·088) and annual mean temperature in degrees Celsius (B = 0·171; 95 %CrI: 0·015, 0·319).
Conclusions
Spatial clustering of influenza incidence was significantly associated with climatic conditions and healthcare access.