Real-time analysis of hospital length of stay in a mixed SARS-CoV-2 Omicron and Delta epidemic in New South Wales, Australia.

BACKGROUND: The distribution of the duration that clinical cases of COVID-19 occupy hospital beds (the 'length of stay') is a key factor in determining how incident caseloads translate into health system burden. Robust estimation of length of stay in real-time requires the use of survival methods that can account for right-censoring induced by yet unobserved events in patient progression (e.g. discharge, death). In this study, we estimate in real-time the length of stay distributions of hospitalised COVID-19 cases in New South Wales, Australia, comparing estimates between a period where Delta was the dominant variant and a subsequent period where Omicron was dominant. METHODS: Using data on the hospital stays of 19,574 individuals who tested positive to COVID-19 prior to admission, we performed a competing-risk survival analysis of COVID-19 clinical progression. RESULTS: During the mixed Omicron-Delta epidemic, we found that the mean length of stay for individuals who were discharged directly from ward without an ICU stay was, for age groups 0-39, 40-69 and 70 +, respectively, 2.16 (95% CI: 2.12-2.21), 3.93 (95% CI: 3.78-4.07) and 7.61 days (95% CI: 7.31-8.01), compared to 3.60 (95% CI: 3.48-3.81), 5.78 (95% CI: 5.59-5.99) and 12.31 days (95% CI: 11.75-12.95) across the preceding Delta epidemic (1 July 2021-15 December 2021). We also considered data on the stays of individuals within the Hunter New England Local Health District, where it was reported that Omicron was the only circulating variant, and found mean ward-to-discharge length of stays of 2.05 (95% CI: 1.80-2.30), 2.92 (95% CI: 2.50-3.67) and 6.02 days (95% CI: 4.91-7.01) for the same age groups. CONCLUSIONS: Hospital length of stay was substantially reduced across all clinical pathways during a mixed Omicron-Delta epidemic compared to a prior Delta epidemic, contributing to a lessened health system burden despite a greatly increased infection burden. Our results demonstrate the utility of survival analysis in producing real-time estimates of hospital length of stay for assisting in situational assessment and planning of the COVID-19 response.

Estimating the excess burden of pertussis disease in Australia within the first year of life, that might have been prevented through timely vaccination.

BACKGROUND: Previous Australian studies have shown that delayed vaccination with each of the three primary doses of diphtheria-tetanus-pertussis-containing vaccines (DTP) is up to 50 % in certain subpopulations. We estimated the excess burden of pertussis that might have been prevented if (i) all primary doses and (ii) each dose was given on time. METHODS: Perinatal, immunization, pertussis notification and death data were probabilistically linked for 1 412 984 infants born in two Australian states in 2000-12. A DTP dose administered >15 days after the recommended age was considered delayed. We used Poisson regression models to compare pertussis notification rates to 1-year of age in infants with ≥1 dose delayed (Aim 1) or any individual dose delayed (Aim 2) versus a propensity weighted counterfactual on-time cohort. RESULTS: Of all infants, 42% had ≥1 delayed DTP dose. We estimated that between 39 to 365 days of age, 85 (95% CI: 61-109) cases per 100 000 infants, could have been prevented if all infants with ≥1 delayed dose had received their three doses within the on-time window. Risk of pertussis was higher in the delayed versus the on-time cohort, so crude rates overestimated the excess burden (110 cases per 100 000 infants (95% CI: 95-125)). The estimated dose-specific excess burden per 100 000 infants was 132 for DTP1, 50 for DTP2 and 19 for DTP3. CONCLUSIONS: We provide robust evidence that improved DTP vaccine timeliness, especially for the first dose, substantially reduces the burden of infant pertussis. Our methodology, using a potential outcomes framework, is applicable to other settings.

Whole of population-based cohort study of recovery time from COVID-19 in New South Wales Australia.

BACKGROUND: COVID-19 results in persisting symptoms but there is little systematically collected data estimating recovery time following infection. METHODS: We followed 94% of all COVID-19 cases diagnosed in the Australian state of New South Wales between January and May 2020 using 3-4 weekly telephone interviews and linkage to hospitalisation and death data to determine if they had recovered from COVID-19 based on symptom resolution. Proportional hazards models with competing risks were used to estimate time to recovery adjusted for age and gender. FINDINGS: In analyses 2904 cases were followed for recovery (median follow-up time 16 days, range 1-122, IQR 11-24).There were 2572 (88.6%) who reported resolution of symptoms (262/2572 were also hospitalised), 224 (7.8%) had not recovered at last contact (28/224 were also hospitalised), 51 (1.8%) died of COVID-19, and 57 (2.0%) were hospitalised without a documented recovery date. Of those followed, 20% recovered by 10 days, 60% at 20, 80% at 30, 91% at 60, 93% at 90 and 96% at 120 days. Compared to those aged 30-49 years, those 0-29 years were more likely to recover (aHR 1.22, 95%CI 1.10-1.34) while those aged 50-69 and 70+ years were less likely to recover (aHR respectively 0.74, 95%CI 0.67-0.81 and 0.63, 95%CI 0.56-0.71). Men were faster to recover than women (aHR 1.20, 95%CI 1.11-1.29) and those with pre-existing co-morbidities took longer to recover than those without (aHR 0.90, 95%CI 0.83-0.98). INTERPRETATION: In a setting where most cases of COVID-19 were ascertained and followed, 80% of those with COVID-19 recover within a month, but about 5% will continue to experience symptoms 3 months later. FUNDING: NSW Health Emergency Response Priority Research Projects.

Emergence of pertactin-deficient pertussis strains in Australia can be explained by models of vaccine escape.

A number of developed countries including Australia have experienced significant pertussis outbreaks in recent years despite consistent high levels of vaccine coverage. Evolutionary changes in Bordetella pertussis carrying variants of the gene encoding pertactin, and the emergence of pertactin-deficient strains (PRN-) in the recent epidemics suggest a possible role of vaccine-driven evolution. In this study, we considered a deterministic 2-strain compartmental model to characterize the relative fitness of PRN- strains and vaccine efficacy against PRN- infection in comparison to the wild-type pertactin-expressing (PRN+) strains. We first showed that the model's equilibrium behavior allows for replacement and co-existence, depending on key parameters related to transmission, vaccine efficacy and durations of immunity. We then fitted the model to epidemiological and pathogen PRN data from the state of New South Wales, Australia. Fitted model parameters showed that the changes in pertussis epidemiology have been governed by a vaccine-escape B. pertussis strain (PRN-) having a basic reproduction number ∼ 1/2 of the wild-type strain which was in circulation prior to April 2009, against which the vaccine was estimated to have substantially reduced efficacy. While not causal, our results suggest that selective pressure from acellular pertussis vaccination is consistent with the changing epidemiology observed in Australia over the analysis period.

Modelling the in-host dynamics of Neisseria gonorrhoeae infection.

The bacterial species Neisseria gonorrhoeae (NG) has evolved to replicate effectively and exclusively in human epithelia, with its survival dependent on complex interactions between bacteria, host cells and antimicrobial agents. A better understanding of these interactions is needed to inform development of new approaches to gonorrhoea treatment and prevention but empirical studies have proven difficult, suggesting a role for mathematical modelling. Here, we describe an in-host model of progression of untreated male symptomatic urethral infection, including NG growth and interactions with epithelial cells and neutrophils, informed by in vivo and in vitro studies. The model reproduces key observations on bacterial load and clearance and we use multivariate sensitivity analysis to refine plausible ranges for model parameters. Model variants are also shown to describe mouse infection dynamics with altered parameter ranges that correspond to observed differences between human and mouse infection. Our results highlight the importance of NG internalisation, particularly within neutrophils, in sustaining infection in the human model, with ∼80% of the total NG population internalised from day 25 on. This new mechanistic model of in-host NG infection dynamics should also provide a platform for future studies relating to antimicrobial treatment and resistance and infection at other anatomical sites.

ENVirT: inference of ecological characteristics of viruses from metagenomic data.

BACKGROUND: Estimating the parameters that describe the ecology of viruses,particularly those that are novel, can be made possible using metagenomic approaches. However, the best-performing existing methods require databases to first estimate an average genome length of a viral community before being able to estimate other parameters, such as viral richness. Although this approach has been widely used, it can adversely skew results since the majority of viruses are yet to be catalogued in databases. RESULTS: In this paper, we present ENVirT, a method for estimating the richness of novel viral mixtures, and for the first time we also show that it is possible to simultaneously estimate the average genome length without a priori information. This is shown to be a significant improvement over database-dependent methods, since we can now robustly analyze samples that may include novel viral types under-represented in current databases. We demonstrate that the viral richness estimates produced by ENVirT are several orders of magnitude higher in accuracy than the estimates produced by existing methods named PHACCS and CatchAll when benchmarked against simulated data. We repeated the analysis of 20 metavirome samples using ENVirT, which produced results in close agreement with complementary in virto analyses. CONCLUSIONS: These insights were previously not captured by existing computational methods. As such, ENVirT is shown to be an essential tool for enhancing our understanding of novel viral populations.

Modelling the decline and future of hepatitis A transmission in Australia.

Hepatitis A incidence has declined in most countries through a combination of prevention measures, augmented through the use of a highly effective vaccine. In Australia, the proportion of the population susceptible to hepatitis A infection has declined over time due to high rates of opportunistic vaccination as well as the sustained inflow of seropositive immigrants from high-endemicity countries. These factors have contributed to a rapid decline in incidence. An age-structured hepatitis A transmission model incorporating demographic changes was fitted to seroprevalence and disease notification data and used to project incidence trends and transmission potential for hepatitis A in the general population. Robustness of findings was assessed through worst-case scenarios regarding vaccine uptake, migration and the duration of immunity. The decline in age-specific seroprevalence until the introduction of hepatitis A vaccine in 1994 was well explained through a declining basic reproduction number (R0 ) that remained >1. Accounting for existing immunity, we estimated that the effective reproduction number (Reff ) <1 in the general population of Australia since the early 1990s, declining more rapidly after the introduction of the hepatitis A vaccine. Future projections under a variety of scenarios support Reff remaining <1 with continued low incidence in the general population. In conclusion, our results suggest that sustained endemic transmission in the general Australian population is no longer possible although risks of sporadic outbreaks remain. This suggests potential for local elimination of hepatitis A infection in Australia, provided that elimination criteria can be defined and satisfied in risk groups. The methodology used here to investigate elimination potential can easily be replicated in settings such as in the USA where sequential seroprevalence studies are supported by routine notification data.

Assessing Species Diversity Using Metavirome Data: Methods and Challenges.

Assessing biodiversity is an important step in the study of microbial ecology associated with a given environment. Multiple indices have been used to quantify species diversity, which is a key biodiversity measure. Measuring species diversity of viruses in different environments remains a challenge relative to measuring the diversity of other microbial communities. Metagenomics has played an important role in elucidating viral diversity by conducting metavirome studies; however, metavirome data are of high complexity requiring robust data preprocessing and analysis methods. In this review, existing bioinformatics methods for measuring species diversity using metavirome data are categorised broadly as either sequence similarity-dependent methods or sequence similarity-independent methods. The former includes a comparison of DNA fragments or assemblies generated in the experiment against reference databases for quantifying species diversity, whereas estimates from the latter are independent of the knowledge of existing sequence data. Current methods and tools are discussed in detail, including their applications and limitations. Drawbacks of the state-of-the-art method are demonstrated through results from a simulation. In addition, alternative approaches are proposed to overcome the challenges in estimating species diversity measures using metavirome data.

Quantifying the population effects of vaccination and migration on hepatitis A seroepidemiology in Australia.

Since licensure of hepatitis A vaccine in Australia in 1994, infection rates have declined to record lows. Cross-sectional serosurveys conducted over this period meanwhile have shown rising population immunity, particularly in young to middle-aged Australians. In this study, we performed a retrospective birth cohort analysis to estimate the contributions of infection, migration and vaccination towards increased levels of age specific hepatitis A seroprevalence in Australia. When aggregated across age, we find that two-thirds of the increase in population seropositivity (67.04%) between 1994 and 2008 was due to vaccination, just under one-third due to migration, with a negligible contribution from infection (<1%). Comparisons with other data sources reflecting vaccine uptake suggest the magnitude of this effect is realistic. We suggest that these results primarily relate to opportunistic vaccination and indicate the level of population immunity achievable through opportunistic programs providing further evidence for policy considerations around universal hepatitis A vaccine recommendations.

Accurate reconstruction of viral quasispecies spectra through improved estimation of strain richness.

BACKGROUND: Estimating the number of different species (richness) in a mixed microbial population has been a main focus in metagenomic research. Existing methods of species richness estimation ride on the assumption that the reads in each assembled contig correspond to only one of the microbial genomes in the population. This assumption and the underlying probabilistic formulations of existing methods are not useful for quasispecies populations where the strains are highly genetically related. RESULTS: On benchmark data sets, our estimation method provided accurate richness estimates (< 0.2 median estimation error) and improved the precision of ViQuaS by 2%-13% and F-score by 1%-9% without compromising the recall rates. We also demonstrate that our estimation method can be used to improve the precision and F-score of ShoRAH by 0%-7% and 0%-5% respectively. CONCLUSIONS: The proposed probabilistic estimation method can be used to estimate the richness of viral populations with a quasispecies behavior and to improve the accuracy of the quasispecies spectra reconstructed by the existing methods ViQuaS and ShoRAH in the presence of a moderate level of technical sequencing errors. AVAILABILITY: http://sourceforge.net/projects/viquas/.

ViQuaS: an improved reconstruction pipeline for viral quasispecies spectra generated by next-generation sequencing.

MOTIVATION: The combined effect of a high replication rate and the low fidelity of the viral polymerase in most RNA viruses and some DNA viruses results in the formation of a viral quasispecies. Uncovering information about quasispecies populations significantly benefits the study of disease progression, antiviral drug design, vaccine design and viral pathogenesis. We present a new analysis pipeline called ViQuaS for viral quasispecies spectrum reconstruction using short next-generation sequencing reads. ViQuaS is based on a novel reference-assisted de novo assembly algorithm for constructing local haplotypes. A significantly extended version of an existing global strain reconstruction algorithm is also used. RESULTS: Benchmarking results showed that ViQuaS outperformed three other previously published methods named ShoRAH, QuRe and PredictHaplo, with improvements of at least 3.1-53.9% in recall, 0-12.1% in precision and 0-38.2% in F-score in terms of strain sequence assembly and improvements of at least 0.006-0.143 in KL-divergence and 0.001-0.035 in root mean-squared error in terms of strain frequency estimation, over the next-best algorithm under various simulation settings. We also applied ViQuaS on a real read set derived from an in vitro human immunodeficiency virus (HIV)-1 population, two independent datasets of foot-and-mouth-disease virus derived from the same biological sample and a real HIV-1 dataset and demonstrated better results than other methods available.