How immunity shapes the long-term dynamics of seasonal influenza DOI Creative Commons
Oliver Eales, Freya M. Shearer, James M. McCaw

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Sept. 8, 2023

Abstract Since its emergence in 1968, influenza A H3N2 has caused yearly epidemics temperate regions. While infection confers immunity against antigenically similar strains, new distinct strains that evade existing regularly emerge (‘antigenic drift’). Immunity at the individual level is complex, depending on an individual’s lifetime history. An first with typically elicits greatest response subsequent infections eliciting progressively reduced responses seniority’). The combined effect of individual-level immune and antigenic drift epidemiological dynamics are not well understood. Here we develop integrated modelling framework transmission, immunity, to show how exposure, build-up population shape long-term H3N2. Including seniority model, observe following initial decline after pandemic year, average annual attack rate increases over next 80 years, before reaching equilibrium, greater older age-groups. Our analyses suggest still a growth phase. Further increases, particularly elderly, may be expected coming decades, driving increase healthcare demand due infections. We anticipate our findings methodological developments will applicable other variable pathogens. This includes recent pathogens H1N1pdm09, circulating since 2009, SARS-CoV-2, 2019. highlight short-term reduction rates pandemic, if there any degree then resurgence should longer-term. Designing implementing studies assess for help rises health burden.

Language: Английский

Burden of respiratory syncytial virus in older adults in Taiwan: An expert perspective on knowledge gaps DOI Creative Commons
Yu-Lin Lee, Szu‐Min Hsieh, Yi‐Tsung Lin

et al.

Journal of Microbiology Immunology and Infection, Journal Year: 2024, Volume and Issue: 57(4), P. 523 - 532

Published: May 30, 2024

The burden of respiratory syncytial virus (RSV) infection among older adults in Taiwan is not well understood due to a scarcity published epidemiological data. Nonetheless, the increasing proportion anticipated translate increased RSV infection, presenting challenge healthcare system. Thus, an expert meeting was convened panel infectious disease specialists from evaluate existing local evidence and data gaps related (aged ≥50 years), propose steps generating on this population. Overall, there are few studies clinical economic Taiwan, limited by small sample sizes highly selected populations. Inconsistent testing practices contribute under-diagnosis under-reporting, driven limitations reimbursement policies that discourage proactive adults, lack appropriate, targeted treatment. Crucially, paucity may perpetuate awareness clinicians public, hinder investments into at policymaker level, thereby impede implementation consistent diagnostic practices, precluding deeper understanding RSV. To overcome these challenges, it imperative prioritize generation establish Taiwan. Such would also support multi-stakeholder group assessing impact future RSV-related interventions, such as educational initiatives preventative strategies including vaccines.

Language: Английский

Citations

1
Biases in routine influenza surveillance indicators used to monitor infection incidence and recommendations for improvement DOI Creative Commons
Oliver Eales, James M. McCaw, Freya M. Shearer

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 6, 2024

Abstract Background Monitoring how the incidence of influenza infections changes over time is important for quantifying transmission dynamics and clinical severity influenza. Infection difficult to measure directly, hence other quantities which are more amenable surveillance used monitor trends in infection levels, with implicit assumption that they correlate incidence. Method Here we demonstrate, through mathematical reasoning, relationship between three commonly reported indicators: 1) rate per unit influenza-like illness sentinel healthcare sites, 2) laboratory-confirmed infections, 3) proportion laboratory tests positive (‘test-positive proportion’). Results Our analysis suggests none these ubiquitously indicators a reliable tool monitoring In particular, highlight can be heavily biased by: circulating pathogens (other than influenza) similar symptom profiles; testing rates; differences rates, healthcare-seeking behaviour age-groups time. We make six practical recommendations improve The implementation our would enable construction interpretable indicator(s) from underlying patterns could readily monitored. Conclusion all (or subset) greatly understanding dynamics, burden, influenza, improving ability respond effectively seasonal epidemics future pandemics.

Language: Английский

Citations

1
Temporal trends in test-seeking behaviour during the COVID-19 pandemic DOI Creative Commons
Oliver Eales,

Mingmei Teo,

David J. Price

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 7, 2024

Abstract Background During the COVID-19 pandemic, many countries implemented mass community testing programs, where individuals would seek tests due to (primarily) onset of symptoms. The cases recorded by programs represent only a fraction infected individuals, and depend on how people testing. If test-seeking behaviour exhibits heterogeneities or changes over time, this is not accounted for when analysing case data, then inferred epidemic dynamics used inform public health decision-making can be biased. Methods Here we describe temporal trends in Australia symptoms, age group, test type, jurisdiction from November 2021–September 2023. We use data two surveillance systems: weekly nationwide behavioural survey (NBS), established Australian Government monitor range responses COVID-19; Australia’s FluTracking system, ‘participatory system’ designed monitoring influenza-like illness health-care seeking behaviour, which was adapted early 2020 include questions relevant COVID-19. Results found that peaks generally aligned with rate reported cases. Test-seeking rapidly increased early-2022 coinciding greater availability rapid antigen tests. There were age-group, dynamic through time. lowest older (60+ years) until July 2022, after there homogeneity across age-groups. highest Capital Territory Tasmania consistently Queensland. Over course study who symptoms more predictive infection. probability compared NBS, suggesting participatory systems such as may health-conscious subset population. Conclusions Our findings demonstrate dynamism highlighting importance continued collection dedicated systems.

Language: Английский

Citations

1
Biases in Routine Influenza Surveillance Indicators Used to Monitor Infection Incidence and Recommendations for Improvement DOI
Oliver Eales, James M. McCaw, Freya M. Shearer

et al.

Influenza and Other Respiratory Viruses, Journal Year: 2024, Volume and Issue: 18(12)

Published: Dec. 1, 2024

ABSTRACT Background Monitoring how the incidence of influenza infections changes over time is important for quantifying transmission dynamics and clinical severity influenza. Infection difficult to measure directly, hence, other quantities which are more amenable surveillance used monitor trends in infection levels, with implicit assumption that they correlate incidence. Methods Here, we demonstrate, through mathematical reasoning using fundamental principles, relationship between three commonly reported indicators: (1) rate per unit influenza‐like illness sentinel healthcare sites, (2) laboratory‐confirmed (3) proportion laboratory tests positive (‘test‐positive proportion’). Results Our analysis suggests none these ubiquitously indicators a reliable tool monitoring In particular, highlight can be heavily biassed by following: circulating pathogens (other than influenza) similar symptom profiles, testing rates differences rates, healthcare‐seeking behaviour age‐groups time. We make six practical recommendations improve The implementation our would enable construction interpretable indicator(s) from underlying patterns could readily monitored. Conclusions all (or subset) greatly understanding dynamics, burden influenza, improving ability respond effectively seasonal epidemics future pandemics.

Language: Английский

Citations

1
Improving estimates of epidemiological quantities by combining reported cases with wastewater data: a statistical framework with applications to COVID-19 in Aotearoa New Zealand DOI Creative Commons
Leighton M. Watson, Michael J. Plank, Bridget Armstrong

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Aug. 16, 2023

Abstract Background Timely and informed public health responses to infectious diseases such as COVID-19 necessitate reliable information about infection dynamics. The case ascertainment rate (CAR), the proportion of infections that are reported cases, is typically much less than one varies with testing practices behaviours, making cases unreliable sole source data. concentration viral RNA in wastewater samples provides an alternate measure prevalence not affected by clinical testing, healthcare-seeking behaviour or access care. Methods We constructed a state-space model observed data levels SARS-CoV-2 incidence estimated hidden states R CAR using sequential Monte Carlo methods. Results Here, we analysed from 1 January 2022 31 March 2023 Aotearoa New Zealand. Our estimates peaked at 2.76 (95% CrI 2.20, 3.83) around 18 February 12 2022. calculate Zealand’s second Omicron wave July was similar size first, despite fewer cases. estimate BA.5 approximately 50% lower BA.1/BA.2 Conclusions Estimating , CAR, cumulative number useful for planning understanding state immunity population. This disease surveillance tool, improving situational awareness dynamics real-time. Plain Language Summary To make decisions diseases, it important understand community. Reported however, underestimate degree underestimation likely changes time. Wastewater alternative does depend on practices. combined observations reproduction (how quickly increasing decreasing) (the fraction cases). apply Zealand demonstrate had same first being lower.

Language: Английский

Citations

2
Challenges in the case-based surveillance of infectious diseases DOI Creative Commons
Oliver Eales, James M. McCaw, Freya M. Shearer

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Dec. 19, 2023

Abstract To effectively inform infectious disease control strategies, accurate knowledge of the pathogen’s transmission dynamics is required. The infection incidence, which describes number new infections in a given time interval (e.g., per day or week), fundamental to understanding dynamics, and can be used estimate time-varying reproduction severity fatality ratio) disease. timings are rarely known so estimates incidence often rely on measurements other quantities amenable surveillance. Case-based surveillance, infected individuals identified by positive test, pre-dominant form surveillance for many pathogens, was extensively during COVID-19 pandemic. However, there biases present case-based indicators due to, example, test sensitivity specificity, changing testing behaviours, co-circulation pathogens with similar symptom profiles. Without full process systems generate data, robust number, based these data cannot made. Here we develop mathematical description diseases. By considering realistic epidemiological parameters situations, demonstrate potential common data. highly general could applied diverse set situations. inference using existing where bias uncertainty will any such analysis. Future strategies designed minimise sources uncertainty, providing more and, ultimately, targeted application public health measures.

Language: Английский

Citations

2
Severe Acute Respiratory Infection (SARI) due to Influenza in Post‐COVID Resurgence: Disproportionate Impact on Older Māori and Pacific Peoples DOI Creative Commons

Isabella M. Y. Cheung,

Janine Paynter, David Broderick

et al.

Influenza and Other Respiratory Viruses, Journal Year: 2024, Volume and Issue: 18(11)

Published: Oct. 30, 2024

Influenza reemerged after a 2020-2021 hiatus in 2022, but understanding the resurgence needs pre-COVID era surveillance. We compared age- and ethnicity-specific incidence of severe acute respiratory infection (SARI) from hospital network Auckland, New Zealand, 2022 against baseline, 2012-2019.

Language: Английский

Citations

0
Inferring temporal trends of multiple pathogens, variants, subtypes or serotypes from routine surveillance data DOI Creative Commons
Oliver Eales, Saras M. Windecker, James M. McCaw

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 4, 2024

Abstract Estimating the temporal trends in infectious disease activity is crucial for monitoring spread and impact of interventions. Surveillance indicators routinely collected to monitor these are often a composite multiple pathogens. For example, ‘influenza-like illness’ — monitored as proxy influenza infections symptom definition that could be caused by wide range pathogens, including subtypes influenza, SARS-CoV-2, RSV. Inferred from such time series may not reflect any one component each which can exhibit distinct dynamics. Although many surveillance systems test subset individuals contributing indicator providing information on relative contribution pathogens obscured time-varying testing rates or substantial noise observation process. Here we develop general statistical framework inferring data. We demonstrate its application three different covering (influenza, dengue), locations (Australia, Singapore, USA, Taiwan, UK), scenarios (seasonal epidemics, non-seasonal pandemic emergence), reporting resolutions (weekly, daily). This methodology applicable systems.

Language: Английский

Citations

0
How immunity shapes the long-term dynamics of seasonal influenza DOI Creative Commons
Oliver Eales, Freya M. Shearer, James M. McCaw

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Sept. 8, 2023

Abstract Since its emergence in 1968, influenza A H3N2 has caused yearly epidemics temperate regions. While infection confers immunity against antigenically similar strains, new distinct strains that evade existing regularly emerge (‘antigenic drift’). Immunity at the individual level is complex, depending on an individual’s lifetime history. An first with typically elicits greatest response subsequent infections eliciting progressively reduced responses seniority’). The combined effect of individual-level immune and antigenic drift epidemiological dynamics are not well understood. Here we develop integrated modelling framework transmission, immunity, to show how exposure, build-up population shape long-term H3N2. Including seniority model, observe following initial decline after pandemic year, average annual attack rate increases over next 80 years, before reaching equilibrium, greater older age-groups. Our analyses suggest still a growth phase. Further increases, particularly elderly, may be expected coming decades, driving increase healthcare demand due infections. We anticipate our findings methodological developments will applicable other variable pathogens. This includes recent pathogens H1N1pdm09, circulating since 2009, SARS-CoV-2, 2019. highlight short-term reduction rates pandemic, if there any degree then resurgence should longer-term. Designing implementing studies assess for help rises health burden.

Language: Английский

Citations

1