Key lessons from the COVID-19 public health response in Australia

Basseal, JM; Bennett, C. R.; Collignon, P; Currie, BJ; Dn, Dürrheim; Leask, Julie; Es, McBryde; McIntyre, Peter; Russell, Fiona; Smith, David M.; Sorrell, Tania C.; Marais, Ben J

doi:10.1016/j.lanwpc.2022.100616

Cited by 41 publications

(32 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Evidence suggests that New Zealand was able to mount a success response because of strong leadership coordinating with many institutions to implement response measures in real-time, prioritisation of vulnerable populations in responses, effective communication strategies that induced population-wide support of responses and swift institutional approval of pandemic tools 80 81. Responses in Australia82 and Iceland83 also benefited from similarly strong, rapid and coordinated responses. While the USA has a multitude of pandemic capacities, the US response was fragmented due to states implementing different control strategies,84 early institutional rules preventing rapid mobilisation of diagnostic equipment85 and mixed communication that potentially harmed compliance in response measures 86…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the Global Health Security Index as a predictor of COVID-19 excess mortality standardised for under-reporting and age structure

Ledesma¹,

Isaac²,

Dowell³

et al. 2023

BMJ Glob Health

View full text Add to dashboard Cite

BackgroundPrevious studies have observed that countries with the strongest levels of pandemic preparedness capacities experience the greatest levels of COVID-19 burden. However, these analyses have been limited by cross-country differentials in surveillance system quality and demographics. Here, we address limitations of previous comparisons by exploring country-level relationships between pandemic preparedness measures and comparative mortality ratios (CMRs), a form of indirect age standardisation, of excess COVID-19 mortality.MethodsWe indirectly age standardised excess COVID-19 mortality, from the Institute for Health Metrics and Evaluation modelling database, by comparing observed total excess mortality to an expected age-specific COVID-19 mortality rate from a reference country to derive CMRs. We then linked CMRs with data on country-level measures of pandemic preparedness from the Global Health Security (GHS) Index. These data were used as input into multivariable linear regression analyses that included income as a covariate and adjusted for multiple comparisons. We conducted a sensitivity analysis using excess mortality estimates from WHO and The Economist.ResultsThe GHS Index was negatively associated with excess COVID-19 CMRs (table 2; β= −0.21, 95% CI= −0.35 to −0.08). Greater capacities related to prevention (β= −0.11, 95% CI= −0.22 to −0.00), detection (β= −0.09, 95% CI= −0.19 to −0.00), response (β = −0.19, 95% CI= −0.36 to −0.01), international commitments (β= −0.17, 95% CI= −0.33 to −0.01) and risk environments (β= −0.30, 95% CI= −0.46 to −0.15) were each associated with lower CMRs. Results were not replicated using excess mortality models that rely more heavily on reported COVID-19 deaths (eg, WHO and The Economist).ConclusionThe first direct comparison of COVID-19 excess mortality rates across countries accounting for under-reporting and age structure confirms that greater levels of preparedness were associated with lower excess COVID-19 mortality. Additional research is needed to confirm these relationships as more robust national-level data on COVID-19 impact become available.

show abstract

Section: Discussionmentioning

confidence: 99%

Evaluation of the Global Health Security Index as a predictor of COVID-19 excess mortality standardised for under-reporting and age structure

Ledesma¹,

Isaac²,

Dowell³

et al. 2023

BMJ Glob Health

View full text Add to dashboard Cite

show abstract

“…In reflecting on what needs to be learnt from the pandemic response in Australia, colleagues and I nominated comprehensive and transparent data collection, reporting, and communication as our top recommendations 5. We are not there yet and will struggle as long as essential public health data aren’t routinely collected and released.…”

Section: An Uphill Battlementioning

confidence: 99%

Covid-19 in Australia: How did a country that fought so hard for extra time end up so ill prepared?

Bennett

2023

BMJ

View full text Add to dashboard Cite

“…Disease surveillance, including AMR, is mostly based on reports submitted by clinical or laboratory outlets (Gibbons et al, 2014). Covid-19 pandemic has highlighted the importance of a broad but accurate surveillance of communicable diseases (Assefa et al, 2022; Basseal et al, 2022). Detection and monitoring of virulence factors can be particularly useful in understanding public health risks of potential infections as virulence factors are often associated with the ability of bacteria or virus to adhere, colonize, invade and sequester nutrients from hosts (Sharma et al, 2017) and increase their pathogenicity (Miller et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

One Health Assessment of an Urban Temporary Settlement Reveals Gut Microbiome Serving as Antimicrobial Resistance Gene Reservoir

Napit

Gurung

Poudel

et al. 2023

Preprint

View full text Add to dashboard Cite

Antimicrobial resistance (AMR) is an emerging and growing global health challenge that could result in 10.2 million deaths annually by 2050. The unrestricted and haphazard use of antibiotics is contributing to the rapid emergence and spread of AMR, and the problem is exacerbated by release of untreated waste water from high-risk sources like hospitals into rivers. Bacteria often develop resistance through horizontal gene transfer mechanism and gut flora can act as a source for new Antimicrobial Resistance Genes (ARG). Upcoming methods like metagenomics can identify the resistance profile (AMR) of gut microbiome, and detect bacterial infections that otherwise go unnoticed. Our study focused on understanding the presence of AMR mutations and gene transfer dynamics in human, animal and environmental samples collected in one of the temporary settlements of Kathmandu (Nepal) using One Health approach. Current AMR reporting based on clinical cases is limited and does not provide information on specific pathogen and associated AMR genes- our study is an effort to contribute information to fulfill this gap. Twenty-one samples were collected from a temporary settlement in Thapathali (Kathmandu), which included fecal samples from birds (n=3) and humans (n=14), and environmental samples (n=4). Microbiological assessment was carried out based on 16S sequence metagenomic analysis using MiSeq (Illumina, USA). Taxonomic classification on obtained 16S sequences were determined by using Metaphlan 2 and Qiime 2 bioinformatics tools. ShortBRED was used to classify ARG and virulence factors, and WAFFLE was used for horizontal gene transfer event prediction. The network analysis was carried out using Gephi v0.9 and the ResistoXplorer web tool to identify ARG in the collected samples. Prevotella spp. was the dominant gut microbiome in humans. We detected diverse phages and viruses, including Stx-2 converting phages. 72 virulence factors and 53 ARG subtypes were detected, with poultry samples having the highest number of subtypes. The cluster and network analysis showed a strong association between gut microbiome and ARG, which was also supported by Horizontal Gene Transfer (HGT) analysis. One-Health interface showed ARG dynamics and revealed gut microbiomes of humans and animals serving as a reservoir for the circulating ARG.

show abstract

Key lessons from the COVID-19 public health response in Australia

Cited by 41 publications

References 37 publications

Evaluation of the Global Health Security Index as a predictor of COVID-19 excess mortality standardised for under-reporting and age structure

Evaluation of the Global Health Security Index as a predictor of COVID-19 excess mortality standardised for under-reporting and age structure

Covid-19 in Australia: How did a country that fought so hard for extra time end up so ill prepared?

One Health Assessment of an Urban Temporary Settlement Reveals Gut Microbiome Serving as Antimicrobial Resistance Gene Reservoir

Contact Info

Product

Resources

About