Communicable diseases intelligence (2018)最新文献

{"title":"Australian Gonococcal Surveillance Program, 1 January to 31 March 2026.","authors":"Monica Lahra, Tiffany Hogan","doi":"10.33321/cdi.2026.50.060","DOIUrl":"https://doi.org/10.33321/cdi.2026.50.060","url":null,"abstract":"<p><p>The Australian National Neisseria Network (NNN) comprises reference laboratories in each state and territory that report data on antimicrobial susceptibility testing to an agreed group of antimicrobial agents for the Australian Gonococcal Surveillance Programme (AGSP). The AGSP data are presented quarterly in tabulated form, as well as in the AGSP annual report. This report presents national gonococcal antimicrobial resistance surveillance data from 1 January to 31 March 2026.</p>","PeriodicalId":36867,"journal":{"name":"Communicable diseases intelligence (2018)","volume":"50 ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149224982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epidemiology of malaria in the Torres Strait Islands, Australia, 2000-2025 and the public health response to three recent outbreaks.","authors":"C Bowers, D Pourmarzi, J Hanson, A Hempenstall, P Dugdale, C Cashman, A Fauid, G Ehlers, J Davis, D Peniyamina, L Stephens, C Taunton","doi":"10.33321/cdi.2026.50.065","DOIUrl":"https://doi.org/10.33321/cdi.2026.50.065","url":null,"abstract":"<p><strong>Background: </strong>Australia was declared malaria free in 1981. However, the proximity of Australia's Torres Strait region to malaria-endemic Papua New Guinea (PNG), and the presence of the <i>Anopheles</i> mosquito across Northern Australia, means there is an ongoing risk of malaria for many Australian residents. This paper describes the epidemiology of malaria in the Torres Strait region between 2000 and 2025 and reports the public health response to three malaria outbreaks between 2023 and 2025.</p><p><strong>Methods: </strong>Case data from 1 January 2000 to 31 December 2025 were extracted from the Queensland Notifiable Conditions System to describe the epidemiology of malaria in the Torres Strait. The public health responses to each of the three recent outbreaks were reported against the Queensland Health Public Health Unit Guidelines for Malaria.</p><p><strong>Results: </strong>During the period 2000-2013, there were 171 cases of malaria reported in the Torres Strait region. Of these, 89 (52%) were positive for <i>Plasmodium falciparum</i> and 82 (48%) for <i>P. vivax</i>. Of cases during this period, 130 (76%) were imported from PNG; 13 (8%) were acquired in Australia; and 28 (16%) had an unknown place of acquisition. After a nine-year period without any confirmed malaria cases in the region, eight cases were reported across three outbreaks between 2023 and 2025. In all six of the outbreak cases in which a species could be confirmed, <i>P. vivax</i> was identified. The three outbreaks were managed effectively in partnership with local leaders, and included active case finding and vector control activities.</p><p><strong>Discussion and conclusion: </strong>The public health response successfully halted transmission of malaria during three separate outbreaks in the Torres Strait Islands. However, there is an ongoing local risk due to the high incidence of malaria in PNG and cross-border movement under the Torres Strait Treaty. Ongoing collaboration with PNG stakeholders and enhanced local surveillance are essential to minimise the future importation of malaria, and other potentially life-threatening pathogens, into mainland Australia.</p>","PeriodicalId":36867,"journal":{"name":"Communicable diseases intelligence (2018)","volume":"50 ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149224956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nationwide survey of testing practices for respiratory viruses in Australia in the post COVID-19 pandemic era.","authors":"Jane Tuckerman, Andrew Daley, Danielle Wurzel, Ian Barr","doi":"10.33321/cdi.2026.50.008","DOIUrl":"https://doi.org/10.33321/cdi.2026.50.008","url":null,"abstract":"<p><strong>Background: </strong>In the wake of the coronavirus disease 2019 (COVID-19) pandemic, there have been dramatic changes in the testing protocols for respiratory illness. Laboratory identification of respiratory pathogens causing clinical symptoms has become more important in the post-COVID-19 era, both for epidemiological and clinical reasons. This is particularly the case for respiratory syncytial virus (RSV) where a number of preventatives are at the point of clinical translation. The laboratory diagnosis is one of the critical elements in understanding the disease burden of respiratory pathogens and the effectiveness of preventatives. The aims of this study were to understand current laboratory testing and reporting practices across Australia.</p><p><strong>Methods: </strong>We undertook a cross-sectional survey of Australian NATA (National Association of Testing Authorities) accredited laboratories to collect data on patterns of laboratory testing, the methods used and their reporting processes. The survey asked participants to report on testing of respiratory samples for 2022 as well as current respiratory multiplex testing in 2023.</p><p><strong>Outcomes: </strong>In total, 45 out of 193 eligible laboratories (23%) completed the online survey. The majority of laboratories were from Victoria and New South Wales (31% and 27%, respectively) and most were hospital-based clinical diagnostic laboratories. Overall, 40% of responding laboratories (18/44) reported that > 80% of all tests in the molecular laboratory in 2023 were respiratory multiplex. Influenza viruses, RSV and SARS-CoV-2 were tested most frequently on respiratory multiplex PCR panels. RSV typing (RSV A or RSV B) was included in under a quarter of panels (9/43; 21%), compared to almost two-thirds for influenza typing (influenza A or influenza B: 29/44; 66%). There was considerable variability in testing platforms used, with thirty-seven laboratories using 87 different platforms (18 unique platforms). GeneXpert® (Cepheid) was the most commonly used platform; with a higher concentration of this instrument in laboratories from the eastern states (New South Wales, Queensland, Victoria). Forty percent of laboratories reported changes to respiratory testing procedures/panels in 2023 compared to the previous year. Laboratories were most likely to report results directly to the referring doctor (96-100%) followed by notifying their jurisdictional Department of Health.</p>","PeriodicalId":36867,"journal":{"name":"Communicable diseases intelligence (2018)","volume":"50 ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149225001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Australian Rotavirus Surveillance Program: Annual Report, 2025.","authors":"Sarah Thomas, Ruth Phang, Nada Bogdanovic-Sakran, Turgut Atkepe, Julie Bines, Celeste Donato","doi":"10.33321/cdi.2026.50.061","DOIUrl":"https://doi.org/10.33321/cdi.2026.50.061","url":null,"abstract":"<p><p>This report from the Australian Rotavirus Surveillance Program (ARSP) describes the circulating rotavirus genotypes identified in children and adults during the period 1 January to 31 December 2025. In 2025, the ARSP saw a continuation of a high burden of rotavirus disease in the Australian population. During this period, 2,419 faecal specimens were referred to the National Rotavirus Reference Centre (NRRC) for rotavirus G- and P-genotype analysis; of these samples, 2,288 were confirmed as rotavirus positive. This represents the highest number of referred samples and the highest number of positive samples recorded in a single surveillance year in the NRRC's more than 20-year history. Of the 2,288 samples confirmed rotavirus positive, 2,071 (90.5%) were identified as wildtype rotavirus; 215 (9.4%) were identified as the Rotarix vaccine-like strain; and two G1P[8] samples could not be confirmed as wildtype or vaccine-like due to inadequate sequence quality. The equine-like G3P[8] variant was the dominant genotype nationally (87.7%; n = 1,816/2,071). Other genotypes were identified at low frequencies, including wildtype G1P[8] (0.3%; n = 6/2,071), G2P[4] (2.0%; n = 42/2,071), G3P[8] (2.4%; n = 50/2,071), G8P[8] (0.5%; n = 10/2,071), G9P[4] (0.3%; n = 6/2,071), G9P[8] (2.2%; n = 46/2,071) and G12P[8] (0.3%; n = 6/2,071). Genotype distribution was consistent nationally, with equine-like G3P[8] the dominant genotype in all jurisdictions. Consistent with observations in recent years, a small number of samples with unusual genotypes were identified (3.7%; n = 77/2,071). Of these unusual genotypes, the most frequently detected was equine-like G3P[6] which accounted for 26.0% of unusual samples (n = 20/74) and 1.0% of all positive wildtype samples (n = 20/2,071). The high number of rotavirus positive samples received by the program reflected the notifications for rotavirus disease reported to the National Notifiable Diseases Surveillance Service (NNDSS). Across Australia, 9,520 notifications were recorded, which is the second highest annual total reported since rotavirus became nationally notifiable in 2018. Outbreaks were reported in the Northern Territory, Western Australia and Queensland. The ability to monitor the genotypes of rotavirus strains causing disease across ages and jurisdictions provides important data to aid in assessing the performance of the national rotavirus vaccination program and to inform public health interventions during outbreaks. The ARSP also provides important data to monitor annual variations in genotypes circulating in the population. Understanding the diversity of genotypes in circulation and the emergence of variants provides important context for any changes observed in disease epidemiology in the community. The ARSP provides diagnostic laboratories with valuable feedback on laboratory data quality by reporting incidences of wildtype, vaccine-like, and/or false positive rotavirus results.</p>","PeriodicalId":36867,"journal":{"name":"Communicable diseases intelligence (2018)","volume":"50 ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149225039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Australian Gonococcal Surveillance Programme Annual Report, 2025.","authors":"Tiffany Hogan, Monica Lahra","doi":"10.33321/cdi.2026.50.057","DOIUrl":"https://doi.org/10.33321/cdi.2026.50.057","url":null,"abstract":"&lt;p&gt;&lt;p&gt;The Australian Gonococcal Surveillance Programme (AGSP) has continuously monitored antimicrobial resistance in &lt;i&gt;Neisseria gonorrhoeae&lt;/i&gt; (NG) for more than 45 years through the system of jurisdictional &lt;i&gt;Neisseria&lt;/i&gt; reference laboratories, the National Neisseria Network (NNN). In 2025, a total of 10,204 isolates across Australia, from public and private sectors, were tested for in vitro antimicrobial susceptibility by standardised methods. In 2025, the AGSP captured antimicrobial susceptibility data for 23.9% of all gonococcal infection notifications nationally. The current treatment recommendation for gonorrhoea, for the majority of Australia, continues to be dual therapy with ceftriaxone and azithromycin. In 2025, of NG isolates tested, 0.73% (74/10,204) met the World Health Organization (WHO) criterion for decreased susceptibility (DS) to ceftriaxone, defined as a minimum inhibitory concentration (MIC) ≥ 0.125 mg/L. This proportion of isolates meeting the ceftriaxone DS criterion was greater than that reported in 2024 (0.51%), with the majority from New South Wales and Victoria. Genomic analysis indicated that 64.9% of these isolates (48/74) possessed the mosaic penA 60.001 allele, the key target associated with ceftriaxone resistance. Resistance to azithromycin was reported in 7.1% of NG isolates nationally, increasing from being proportionally stable (3.9% to 4.7%) since 2019. Of NG isolates tested, 0.20% (20/10,204) exhibited high-level resistance to azithromycin (MIC value ≥ 256 mg/L), with cases reported across Australia, predominantly in New South Wales, Victoria and non-remote Western Australia. There were ten isolates detected in 2025 that had an extensively drug-resistant (XDR) phenotype: i.e., displaying both high-level resistance to azithromycin and decreased susceptibility to ceftriaxone (MIC ≥ 0.125 mg/L). When added to the 14 XDR isolates reported during 2022-2024, this brings the total to 24 XDR NG isolates reported in Australia since 2022. Genomic analyses of the ten XDR isolates reported in 2025 indicated all harboured the mosaic penA 60.001 allele, with several differing sequence types (ST) identified. By contrast, during 2022 and 2024, XDR NG sequence types were limited to ST-16406, consistent with reports from Europe and England. Travel information, where available, indicates infections in 2025 were associated with travel to Southeast Asia but also arose where no travel was involved. In 2025, penicillin resistance was found in 23.4% of gonococcal isolates, and ciprofloxacin resistance in 59.3% of isolates where tested, although there was variation by jurisdiction particularly in remote settings, where acquisition of cultures for antimicrobial susceptibility testing is low. Tetracycline resistance has been included in surveillance in the AGSP in recent years, coincident with increasing use of doxycycline post-exposure prophylaxis for syphilis and chlamydia. Nationally 36.2% of NG isolates in 2025 were tetracyclin","PeriodicalId":36867,"journal":{"name":"Communicable diseases intelligence (2018)","volume":"50 ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149225016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nirsevimab provides age-specific protection against RSV hospitalisation in the first year of life: a population-level study in Queensland, Australia.","authors":"Asmaa El-Heneidy, Keith Grimwood, Mohana Rajmokan, Ashish Shrestha, Stephen Lambert, Robert Ware","doi":"10.33321/cdi.2026.50.066","DOIUrl":"https://doi.org/10.33321/cdi.2026.50.066","url":null,"abstract":"<p><p>Nirsevimab, a long-acting monoclonal antibody with activity against respiratory syncytial virus (RSV), was introduced into the Queensland paediatric RSV prevention program in 2024. Using Queensland Notifiable Conditions Register (NoCS) data, we found that the infant cohort eligible for the nirsevimab program had lower RSV hospitalisation rates than comparable pre-program cohorts. The population-level impact of nirsevimab was greatest during the first month of life (incidence rate ratio [IRR]: 0.22; 95% confidence interval [95% CI]: 0.16-0.31; representing a 78% reduction in hospitalisation rate), with its magnitude gradually declining thereafter until nine months of age (IRR: 0.77; 95% CI: 0.62-0.96; a 23% reduction), following which the impact of nirsevimab on hospitalisation rate, with increasing age of the infant or child, was no longer statistically significant. An interrupted time-series analysis demonstrated an immediate 63% reduction in RSV hospitalisations following nirsevimab's introduction (IRR: 0.37; 95% CI: 0.23-0.60), showing a substantial population-level impact of the program in Queensland, Australia.</p>","PeriodicalId":36867,"journal":{"name":"Communicable diseases intelligence (2018)","volume":"50 ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149224954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Surveillance for severe influenza, COVID-19, and RSV in patients admitted to sentinel Australian hospitals in 2025: the Influenza Complications Alert Network (FluCAN) and the Paediatric Active Enhanced Disease Surveillance (PAEDS) system.","authors":"Hannah Morgan, Dominic Dwyer, Mark Holmes, Louis Irving, Megan Rees, Stephen Vincent, Fabian Chiong, Ian Marr, Tony Korman, Caroline Bartolo, Louise Cooley, Simon Bowler, Jen Kok, Naomi Runnegar, Daniel Fatovich, Grant Waterer, Kristine Macartney, Nigel Crawford, Karen Bellamy, Jeremy Carr, Helen Marshall, Julia Clark, Joshua Francis, Brendan McMullan, Philip Britton, Nicholas Wood, Tom Kotsimbos, Paul Kelly, Christopher Blyth, Allen Cheng","doi":"10.33321/cdi.2026.50.058","DOIUrl":"https://doi.org/10.33321/cdi.2026.50.058","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Introduction: &lt;/strong&gt;Influenza, coronavirus disease 2019 (COVID-19) and respiratory syncytial virus (RSV) are common acute respiratory infections and are a cause of significant morbidity and mortality. This report summarises the epidemiology of hospitalisations with laboratory-confirmed influenza, COVID-19 and RSV in 2025 in an Australian sentinel surveillance system.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The Influenza Complications Alert Network (FluCAN) and the Paediatric Active Enhanced Disease Surveillance (PAEDS) are collaborative sentinel hospital-based surveillance programs that operate at 23 sites across all jurisdictions in Australia. Influenza, COVID-19 and RSV patients were defined as those hospitalised due to an acute respiratory infection at the sentinel hospitals with virus confirmation by nucleic acid detection.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In 2025, there were 8,749 hospitalisations of patients with influenza; 3,501 with COVID-19; and 5,105 with RSV reported at the 23 sentinel hospitals. Of patients hospitalised with influenza, 4,397 (50.3%) were children (&lt; 16 years of age); 697 (8.0%) were Aboriginal and/or Torres Strait Islander people; and 5,020 (57.4%) had chronic comorbidities. The mean length of hospital stay for patients with influenza was 4.4 days (median: 2 days). Influenza hospital admissions peaked nationally in epidemiological week 28. Influenza vaccine effectiveness against hospitalisation with any influenza type/subtype was estimated at 43% (95% confidence interval [95% CI]: 39-48%) and was highest for influenza B (75% [95% CI: 69-80%]), and lowest for influenza A H3N2 including subclade K (30.5% [95% CI: 15.0-43.2%]). Of patients hospitalised with COVID-19, 1,057 (30.2%) were children (&lt; 16 years of age); 230 (6.6%) were Aboriginal and/or Torres Strait Islander people; and 2,544 (72.7%) had chronic comorbidities. The mean length of hospital stay for patients with COVID-19 was 7 days (median: 3 days). COVID-19 hospital admissions peaked nationally in week 26. In adults ≥ 75 years of age, the relative risk of hospitalisation was 40% (95% CI: 25-52%) lower in those who had received a COVID-19 vaccine within 180 days, compared to those vaccinated &gt; 1 year prior to admission. Of patients hospitalised with RSV, 1,551 (30.4%) were infants (&lt; 1 year of age) and 3,723 (72.9%) were young children (&lt; 5 years of age); 348 (6.8%) were Aboriginal and/or Torres Strait Islander people; and 2,110 (41.3%) had chronic comorbidities. The mean length of hospital stay for patients with RSV was 3.5 days (median: 2 days). There was a peak in activity in week 28.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Discussion: &lt;/strong&gt;Since 2022, influenza, RSV and COVID-19 have co-circulated. In 2025, disease severity-as indicated by average length of stay and proportions admitted to intensive care-was similar in patients hospitalised with any of the three pathogens. Assessment of vaccine effectiveness demonstrated protection against influenza hospitalisation and sho","PeriodicalId":36867,"journal":{"name":"Communicable diseases intelligence (2018)","volume":"50 ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149076110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Report of the National Influenza Surveillance Scheme, 2022-2023.","authors":"Jenna Hassall, Tracy Tsang, Lauren Kutzner, Lauren Welsh, Suzie Whitehead","doi":"10.33321/cdi.2026.50.022","DOIUrl":"https://doi.org/10.33321/cdi.2026.50.022","url":null,"abstract":"<p><p>This report describes influenza surveillance activities in Australia in 2022 to 2023. Data were extracted from several sources constituting the National Influenza Surveillance Scheme. Following the relaxation of public health and social measures which had been applied in Australia in response to the coronavirus disease 2019 (COVID-19) pandemic in 2020 and 2021, the influenza seasons in 2022 and 2023 were characterised by high activity overall, with 1.4 and 1.8 times the number of laboratory-confirmed influenza notifications than those of the 2015-2019 pre-pandemic five-year mean, respectively. There were differences in the timing of the 2022 and 2023 influenza seasons compared to most pre-pandemic years, with earlier season starts and earlier peaks (approximately six to eight weeks earlier than in pre-pandemic years). There was also considerable variation in the timing of peak influenza activity between the states and territories, particularly in 2023. Notification rates were highest in the 5-9 years age group, with rates in this age group about two and a half times as high in 2022 and three times as high in 2023 as the overall notification rate in the corresponding years. Influenza A(unsubtyped) comprised most notifications in 2022 and 2023. Of the remaining samples, influenza A(H3N2) was dominant in 2022; however, in 2023, there was substantial circulation of influenza B, which predominantly affected children and younger adults, and of A(H1N1). Sentinel surveillance supports the assessment that both the 2022 and 2023 influenza seasons were characterised by early, high activity. High notification rates were also reflected in increased sentinel hospital admissions with confirmed influenza in 2023, particularly among children. The burden placed on sentinel hospitals due to people admitted with influenza was moderate in 2022 but high in 2023. Severity, measured through the proportion of patients admitted to sentinel hospital intensive care units, was moderate in both years and consistent with historical estimates. Influenza was recorded as the underlying cause of death in 0.16% of all deaths that occurred in 2022, and 0.24% of all deaths in 2023. Overall, the 2022 influenza season had high activity with low-to-moderate severity, while 2023 had high activity with moderate severity.</p>","PeriodicalId":36867,"journal":{"name":"Communicable diseases intelligence (2018)","volume":"50 ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149076148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing influenza surveillance in Australia using Google search data combined with machine learning.","authors":"Aminath Shausan, Adam Dunn, Fiona May, Satyamurthy Anuradha, Teresa Wozniak, Amalie Dyda","doi":"10.33321/cdi.2026.50.051","DOIUrl":"https://doi.org/10.33321/cdi.2026.50.051","url":null,"abstract":"<p><strong>Background: </strong>To effectively respond to acute respiratory infections such as influenza, timely information about the spread of disease is required. Surveillance methods that train machine learning models on Google Trends data have been developed to forecast outbreaks. Our aim was to examine the feasibility of forecasting influenza rates for states and territories in Australia using Google Trends data.</p><p><strong>Methods: </strong>Weekly search volume data across 2018 and 2019 from Google Trends, for each state and territory in Australia excepting the Australian Capital Territory, were compared to weekly influenza notifications from the National Notifiable Disease Surveillance System (NNDSS). Four supervised machine learning regression models were developed: elastic net; support vector regression; random forest; and feedforward neural network. Models were fitted independently to data from each state and territory, considering nowcast (current week) and forecast (one and two weeks ahead) predictions.</p><p><strong>Results: </strong>The results show that Google search volumes are correlated with reported influenza rates over time. Random forest and elastic net models generally showed better predictive performance compared to other models. Each modelled state and territory, except the Northern Territory and Tasmania, showed at least two search queries with moderate to strong Pearson correlation with the influenza notifications. The forecast accuracy (measured by the Pearson correlation coefficient) for the best-performing model varied by state or territory (from -0.353 to 0.977) and accuracy was lower for forecasts for one week and two weeks ahead.</p><p><strong>Conclusion: </strong>Combinations of Google search data and machine learning showed predictive utility for forecasting weekly influenza rates in Australian jurisdictions, with lower accuracy in jurisdictions with smaller populations. Future work should investigate specific keywords by location exploring disease prediction at a more geographically specific level, with considerations for smaller populations and robustness over time.</p>","PeriodicalId":36867,"journal":{"name":"Communicable diseases intelligence (2018)","volume":"50 ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149076082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Summary of National Surveillance Data on Vaccine Preventable Diseases in Australia, 2019-2022.","authors":"Joanne Jackson, Nicole Sonneveld, Han Wang, Fariha Hossain, Aditi Dey, Stephen Lambert, Frank Beard","doi":"10.33321/cdi.2026.50.040","DOIUrl":"https://doi.org/10.33321/cdi.2026.50.040","url":null,"abstract":"<p><p>This summary report on vaccine preventable diseases in Australia is the latest in a series of multi-year surveillance reports that bring together the three most important national sources of routinely-collected data on VPDs (notifications, hospitalisations and deaths) and serve as a resource to support surveillance and control of VPDs in Australia. This report focuses on the four-year period 1 January 2019 to 31 December 2022 with longer term trends also presented. Two VPDs are included for the first time: coronavirus disease 2019 (COVID-19) and Japanese encephalitis virus (JEV) infection.</p>","PeriodicalId":36867,"journal":{"name":"Communicable diseases intelligence (2018)","volume":"50 ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149076091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}