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The availability of COVID-19 vaccines promised a reduction in the severity of disease and relief from the strict public health and social measures (PHSMs) imposed in many countries to limit spread and burden of COVID-19. We were asked to define vaccine coverage thresholds for Australia’s transition to easing restrictions and reopening international borders. Using evidence of vaccine effectiveness against the then-circulating Delta variant, we used a mathematical model to determine coverage targets. The absence of any COVID-19 infections in many sub-national jurisdictions in Australia posed particular methodological challenges. We used a novel metric called Transmission Potential (TP) as a proxy measure of the population-level effective reproduction number. We estimated TP of the Delta variant under a range of PHSMs, test-trace-isolate-quarantine (TTIQ) efficiencies, vaccination coverage thresholds, and age-based vaccine allocation strategies. We found that high coverage across all ages (>_70%) combined with ongoing TTIQ and minimal PHSMs was sufficient to avoid lockdowns. At lesser coverage (<_60%) rapid case escalation risked overwhelming of the health sector or the need to reimpose stricter restrictions. Maintaining low case numbers was most beneficial for health and the economy, and at higher coverage levels (>_80%) further easing of restrictions was deemed possible. These results directly informed easing of COVID-19 restrictions in Australia.

BACKGROUND: Since the emergence of SARS-CoV-2 (COVID-19), there have been multiple waves of infection and multiple rounds of vaccination rollouts. Both prior infection and vaccination can prevent future infection and reduce severity of outcomes, combining to form hybrid immunity against COVID-19 at the individual and population level. Here, we explore how different combinations of hybrid immunity affect the size and severity of near-future Omicron waves. METHODS: To investigate the role of hybrid immunity, we use an agent-based model of COVID-19 transmission with waning immunity to simulate outbreaks in populations with varied past attack rates and past vaccine coverages, basing the demographics and past histories on the World Health Organization Western Pacific Region. RESULTS: We find that if the past infection immunity is high but vaccination levels are low, then the secondary outbreak with the same variant can occur within a few months after the first outbreak; meanwhile, high vaccination levels can suppress near-term outbreaks and delay the second wave. Additionally, hybrid immunity has limited impact on future COVID-19 waves with immune-escape variants. CONCLUSIONS: Enhanced understanding of the interplay between infection and vaccine exposure can aid anticipation of future epidemic activity due to current and emergent variants, including the likely impact of responsive vaccine interventions.

BACKGROUND: Australian states and territories used test-trace-isolate-quarantine (TTIQ) systems extensively in their response to the COVID-19 pandemic in 2020-2021. We report on an analysis of Australian case data to estimate the impact of test-trace-isolate-quarantine systems on SARS-CoV-2 transmission. METHODS: Our analysis uses a novel mathematical modelling framework and detailed surveillance data on COVID-19 cases including dates of infection and dates of isolation. First, we directly translate an empirical distribution of times from infection to isolation into reductions in potential for onward transmission during periods of relatively low caseloads (tens to hundreds of reported cases per day). We then apply a simulation approach, validated against case data, to assess the impact of case-initiated contact tracing on transmission during a period of relatively higher caseloads and system stress (up to thousands of cases per day). RESULTS: We estimate that under relatively low caseloads in the state of New South Wales (tens of cases per day), TTIQ contributed to a 54% reduction in transmission. Under higher caseloads in the state of Victoria (hundreds of cases per day), TTIQ contributed to a 42% reduction in transmission. Our results also suggest that case-initiated contact tracing can support timely quarantine in times of system stress (thousands of cases per day). CONCLUSION: Contact tracing systems for COVID-19 in Australia were highly effective and adaptable in supporting the national suppression strategy from 2020-21, prior to the emergence of the Omicron variant in November 2021. TTIQ systems were critical to the maintenance of the strong suppression strategy and were more effective when caseloads were (relatively) low.

Scabies is a parasitic infestation with high global burden. Mass drug administrations (MDAs) are recommended for communities with a scabies prevalence of >10%. Quantitative analyses are needed to demonstrate the likely effectiveness of MDA recommendations. In this study, we developed an agent-based model of scabies transmission calibrated to demographic and epidemiological data from Monrovia. We used this model to compare the effectiveness of MDA scenarios for achieving scabies elimination and reducing scabies burden, as measured by time until recrudescence following delivery of an MDA and disability-adjusted-life-years (DALYs) averted. Our model showed that three rounds of MDA delivered at six-month intervals and reaching 80% of the population could reduce prevalence below 2% for three years following the final round, before recrudescence. When MDAs were followed by increased treatment uptake, prevalence was maintained below 2% indefinitely. Increasing the number of and coverage of MDA rounds increased the probability of achieving elimination and the number of DALYs averted. Our results suggest that acute reduction of scabies prevalence by MDA can support a transition to improved treatment access. This study demonstrates how modelling can be used to estimate the expected impact of MDAs by projecting future epidemiological dynamics and health gains under alternative scenarios.

Since the emergence of SARS-CoV-2 in 2019 through to mid-2021, much of the Australian population lived in a COVID-19-free environment. This followed the broadly successful implementation of a strong suppression strategy, including international border closures. With the availability of COVID-19 vaccines in early 2021, the national government sought to transition from a state of minimal incidence and strong suppression activities to one of high vaccine coverage and reduced restrictions but with still-manageable transmission. This transition is articulated in the national 're-opening' plan released in July 2021. Here, we report on the dynamic modelling study that directly informed policies within the national re-opening plan including the identification of priority age groups for vaccination, target vaccine coverage thresholds and the anticipated requirements for continued public health measures-assuming circulation of the Delta SARS-CoV-2 variant. Our findings demonstrated that adult vaccine coverage needed to be at least 60% to minimize public health and clinical impacts following the establishment of community transmission. They also supported the need for continued application of test-trace-isolate-quarantine and social measures during the vaccine roll-out phase and beyond.

As of January 2021, Australia had effectively controlled local transmission of COVID-19 despite a steady influx of imported cases and several local, but contained, outbreaks in 2020. Throughout 2020, state and territory public health responses were informed by weekly situational reports that included an ensemble forecast of daily COVID-19 cases for each jurisdiction. We present here an analysis of one forecasting model included in this ensemble across the variety of scenarios experienced by each jurisdiction from May to October 2020. We examine how successfully the forecasts characterised future case incidence, subject to variations in data timeliness and completeness, showcase how we adapted these forecasts to support decisions of public health priority in rapidly-evolving situations, evaluate the impact of key model features on forecast skill, and demonstrate how to assess forecast skill in real-time before the ground truth is known. Conditioning the model on the most recent, but incomplete, data improved the forecast skill, emphasising the importance of developing strong quantitative models of surveillance system characteristics, such as ascertainment delay distributions. Forecast skill was highest when there were at least 10 reported cases per day, the circumstances in which authorities were most in need of forecasts to aid in planning and response.

BACKGROUND: Streptococcus pyogenes, or group A Streptococcus (GAS), infections contribute to a high burden of disease in Aboriginal Australians, causing skin infections and immune sequelae such as rheumatic heart disease. Controlling skin infections in these populations has proven difficult, with transmission dynamics being poorly understood. We aimed to identify the relative contributions of impetigo and asymptomatic throat carriage to GAS transmission. METHODS: In this genomic analysis, we retrospectively applied whole genome sequencing to GAS isolates that were collected as part of an impetigo surveillance longitudinal household survey conducted in three remote Aboriginal communities in the Northern Territory of Australia between Aug 6, 2003, and June 22, 2005. We included GAS isolates from all throats and impetigo lesions of people living in two of the previously studied communities. We classified isolates into genomic lineages based on pairwise shared core genomes of more than 99% with five or fewer single nucleotide polymorphisms. We used a household network analysis of epidemiologically and genomically linked lineages to quantify the transmission of GAS within and between households. FINDINGS: We included 320 GAS isolates in our analysis: 203 (63%) from asymptomatic throat swabs and 117 (37%) from impetigo lesions. Among 64 genomic lineages (encompassing 39 emm types) we identified 264 transmission links (involving 93% of isolates), for which the probable source was asymptomatic throat carriage in 166 (63%) and impetigo lesions in 98 (37%). Links originating from impetigo cases were more frequent between households than within households. Households were infected with GAS for a mean of 57 days (SD 39 days), and once cleared, reinfected 62 days (SD 40 days) later. Increased household size and community presence of GAS and scabies were associated with slower clearance of GAS. INTERPRETATION: In communities with high prevalence of endemic GAS-associated skin inf

BACKGROUND: In 2021, the Australian Government Department of Health commissioned a consortium of modelling groups to generate evidence assisting the transition from a goal of no community COVID-19 transmission to 'living with COVID-19', with adverse health and social consequences limited by vaccination and other measures. Due to the extended school closures over 2020-21, maximizing face-to-face teaching was a major objective during this transition. The consortium was tasked with informing school surveillance and contact management strategies to minimize infections and support this goal. METHODS: Outcomes considered were infections and days of face-to-face teaching lost in the 45 days following an outbreak within an otherwise COVID-naïve school setting. A stochastic agent-based model of COVID-19 transmission was used to evaluate a 'test-to-stay' strategy using daily rapid antigen tests (RATs) for close contacts of a case for 7 days compared with home quarantine; and an asymptomatic surveillance strategy involving twice-weekly screening of all students and/or teachers using RATs. FINDINGS: Test-to-stay had similar effectiveness for reducing school infections as extended home quarantine, without the associated days of face-to-face teaching lost. Asymptomatic screening was beneficial in reducing both infections and days of face-to-face teaching lost and was most beneficial when community prevalence was high. INTERPRETATION: Use of RATs in school settings for surveillance and contact management can help to maximize face-to-face teaching and minimize outbreaks. This evidence supported the implementation of surveillance testing in schools in several Australian jurisdictions from January 2022.

Against a backdrop of widespread global transmission, a number of countries have successfully brought large outbreaks of COVID-19 under control and maintained near-elimination status. A key element of epidemic response is the tracking of disease transmissibility in near real-time. During major outbreaks, the effective reproduction number can be estimated from a time-series of case, hospitalisation or death counts. In low or zero incidence settings, knowing the potential for the virus to spread is a response priority. Absence of case data means that this potential cannot be estimated directly. We present a semi-mechanistic modelling framework that draws on time-series of both behavioural data and case data (when disease activity is present) to estimate the transmissibility of SARS-CoV-2 from periods of high to low - or zero - case incidence, with a coherent transition in interpretation across the changing epidemiological situations. Of note, during periods of epidemic activity, our analysis recovers the effective reproduction number, while during periods of low - or zero - case incidence, it provides an estimate of transmission risk. This enables tracking and planning of progress towards the control of large outbreaks, maintenance of virus suppression, and monitoring the risk posed by re-introduction of the virus. We demonstrate the value of our methods by reporting on their use throughout 2020 in Australia, where they have become a central component of the national COVID-19 response.

Against a backdrop of widespread global transmission, a number of countries have successfully brought large outbreaks of COVID-19 under control and maintained near-elimination status. A key element of epidemic response is the tracking of disease transmissibility in near real-time. During major outbreaks, the effective reproduction number can be estimated from a time-series of case, hospitalisation or death counts. In low or zero incidence settings, knowing the potential for the virus to spread is a response priority. Absence of case data means that this potential cannot be estimated directly. We present a semi-mechanistic modelling framework that draws on time-series of both behavioural data and case data (when disease activity is present) to estimate the transmissibility of SARS-CoV-2 from periods of high to low – or zero – case incidence, with a coherent transition in interpretation across the changing epidemiological situations. Of note, during periods of epidemic activity, our analysis recovers the effective reproduction number, while during periods of low – or zero – case incidence, it provides an estimate of transmission risk. This enables tracking and planning of progress towards the control of large outbreaks, maintenance of virus suppression, and monitoring the risk posed by re-introduction of the virus. We demonstrate the value of our methods by reporting on their use throughout 2020 in Australia, where they have become a central component of the national COVID-19 response.

First few ‘X’ (FFX) studies for COVID-19 involve data collection from confirmed cases and their close contacts. They remain relevant especially as many remain susceptible to infection, and as they can provide detailed insight into vaccine effectiveness and the epidemiology of variants of concern, helping to inform a proportionate health response.

Scientific knowledge and advances are a cornerstone of modern society. They improve our understanding of the world we live in and help us navigate global challenges including emerging infectious diseases, climate change and the biodiversity crisis. However, there is a perpetual challenge in translating scientific insight into policy. Many articles explain how to better bridge the gap through improved communication and engagement, but we believe that communication and engagement are only one part of the puzzle. There is a fundamental tension between science and policy because scientific endeavors are rightfully grounded in discovery, but policymakers formulate problems in terms of objectives, actions and outcomes. Decision science provides a solution by framing scientific questions in a way that is beneficial to policy development, facilitating scientists’ contribution to public discussion and policy. At its core, decision science is a field that aims to pinpoint evidence-based management strategies by focussing on those objectives, actions, and outcomes defined through the policy process. The importance of scientific discovery here is in linking actions to outcomes, helping decision-makers determine which actions best meet their objectives. In this paper we explain how problems can be formulated through the structured decision-making process. We give our vision for what decision science may grow to be, describing current gaps in methodology and application. By better understanding and engaging with the decision-making processes, scientists can have greater impact and make stronger contributions to important societal problems.

In controlling transmission of coronavirus disease 2019 (COVID-19), the effectiveness of border quarantine strategies is a key concern for jurisdictions in which the local prevalence of disease and immunity is low. In settings like this such as China, Australia, and New Zealand, rare outbreak events can lead to escalating epidemics and trigger the imposition of large-scale lockdown policies. Here, we develop and apply an individual-based model of COVID-19 to simulate case importation from managed quarantine under various vaccination scenarios. We then use the output of the individual-based model as input to a branching process model to assess community transmission risk. For parameters corresponding to the Delta variant, our results demonstrate that vaccination effectively counteracts the pathogen's increased infectiousness. To prevent outbreaks, heightened vaccination in border quarantine systems must be combined with mass vaccination. The ultimate success of these programs will depend sensitively on the efficacy of vaccines against viral transmission.

During the early stages of an emerging disease outbreak, governments are required to make critical decisions on how to respond, despite limited data being available to inform these decisions. Analytical risk assessment is a valuable approach to guide decision-making on travel restrictions and border measures during the early phase of an outbreak. Here we describe a rapid risk assessment framework that was developed in February 2020 to support time-critical decisions on the risk of SARS-CoV-2 importation into Australia. We briefly describe the context in which our framework was developed, the framework itself, and provide an example of the type of decision support provided to the Australian government. We then report a critical evaluation of the modelling choices made in February 2020, assessing the impact of our assumptions on estimated rates of importation, and provide a summary of "lessons learned". The framework presented and evaluated here provides a flexible approach to rapid assessment of importation risk, of relevance to current and future pandemic scenarios.

Outbreaks of influenza in swine can result in potential threats to human public health. A notable occurrence was the emergence of swine-origin H1N1 influenza viruses in 2009. Since then, there have been several documented outbreaks of swine-origin influenza infecting humans in several countries. Sustained events have occurred when H1N1v, H1N2v, and H3N2v swine-origin viruses have infected humans visiting agricultural shows in the US. The predominant H3N2v viruses gained the matrix protein from the A(H1N1)pdm09 viruses, with reported human-to-human transmission raising fears of another pandemic. Current vaccines do not induce secondary cell-mediated immune responses, which may provide cross-protection against novel influenza A subtypes, however, population susceptibility to infection with seasonal influenza is likely to be influenced by cross-reactive CD8+ T-cells directed towards immunogenic peptides derived from viral proteins. This study involved a retrospective review of historical influenza viruses circulating in human populations from 1918 to 2020 to identify evidence of prior circulation of H3N3v immunogenic CD8+ T-cells peptides found in the NP and M1 proteins. We found evidence of prior circulation of H3N2v NP and M1 immunogenic peptides in historical influenza viruses. This provides insight into the population context in which influenza viruses emerge and may help inform immunogenic peptide selection for cytotoxic T-cell lymphocytes (CTL)-inducing influenza vaccines. Next-generation vaccines capable of eliciting CD8+ T-cell-mediated cross-protective immunity may offer a long-term alternative strategy for influenza vaccines.

BACKGROUND: Estimating community level scabies prevalence is crucial for targeting interventions to areas of greatest need. The World Health Organisation recommends sampling at the unit of households or schools, but there is presently no standardised approach to scabies prevalence assessment. Consequently, a wide range of sampling sizes and methods have been used. As both prevalence and drivers of transmission vary across populations, there is a need to understand how sampling strategies for estimating scabies prevalence interact with local epidemiology to affect the accuracy of prevalence estimates. METHODS: We used a simulation-based approach to compare the efficacy of different scabies sampling strategies. First, we generated synthetic populations broadly representative of remote Australian Indigenous communities and assigned a scabies status to individuals to achieve a specified prevalence using different assumptions about scabies epidemiology. Second, we calculated an observed prevalence for different sampling methods and sizes. RESULTS: The distribution of prevalence in subpopulation groups can vary substantially when the underlying scabies assignment method changes. Across all of the scabies assignment methods combined, the simple random sampling method produces the narrowest 95% confidence interval for all sample sizes. The household sampling method introduces higher variance compared to simple random sampling when the assignment of scabies includes a household-specific component. The school sampling method overestimates community prevalence when the assignment of scabies includes an age-specific component. DISCUSSION: Our results indicate that there are interactions between transmission assumptions and surveillance strategies, emphasizing the need for understanding scabies transmission dynamics. We suggest using the simple random sampling method for estimating scabies prevalence. Our approach can be adapted to various populations and diseases.

UNLABELLED: Cultural practices and development level can influence a population's household structures and mixing patterns. Within some populations, households can be organized across multiple dwellings. This likely affects the spread of infectious disease through these communities; however, current demographic data collection tools do not record these data. METHODS: Between June and October 2018, the Contact And Mobility Patterns in remote Aboriginal Australian communities (CAMP-remote) pilot study recruited Aboriginal mothers with infants in a remote northern Australian community to complete a monthly iPad-based contact survey. RESULTS: Thirteen mother-infant pairs (participants) completed 69 study visits between recruitment and the end of May 2019. Participants reported they and their other children slept in 28 dwellings during the study. The median dwelling occupancy, defined as people sleeping in the same dwelling on the previous night, was ten (range: 3.5-25). Participants who completed at least three responses (n = 8) slept in a median of three dwellings (range: 2-9). Each month, a median of 28% (range: 0-63%) of the participants travelled out of the community. Including these data in disease transmission models amplified estimates of infectious disease spread in the study community, compared to models parameterized using census data. CONCLUSIONS: The lack of data on mixing patterns in populations where households can be organized across dwellings may impact the accuracy of infectious disease models for these communities and the efficacy of public health actions they inform.

BACKGROUND: Household studies are crucial for understanding the transmission of SARS-CoV-2 infection, which may be underestimated from PCR testing of respiratory samples alone. We aim to combine the assessment of household mitigation measures; nasopharyngeal, saliva, and stool PCR testing; along with mucosal and systemic SARS-CoV-2-specific antibodies, to comprehensively characterize SARS-CoV-2 infection and transmission in households. METHODS: Between March and September 2020, we obtained samples from 92 participants in 26 households in Melbourne, Australia, in a 4-week period following the onset of infection with ancestral SARS-CoV-2 variants. RESULTS: The secondary attack rate was 36% (24/66) when using nasopharyngeal swab (NPS) PCR positivity alone. However, when respiratory and nonrespiratory samples were combined with antibody responses in blood and saliva, the secondary attack rate was 76% (50/66). SARS-CoV-2 viral load of the index case and household isolation measures were key factors that determine secondary transmission. In 27% (7/26) of households, all family members tested positive by NPS for SARS-CoV-2 and were characterized by lower respiratory Ct values than low transmission families (Median 22.62 vs. 32.91; IQR 17.06-28.67 vs. 30.37-34.24). High transmission families were associated with enhanced plasma antibody responses to multiple SARS-CoV-2 antigens and the presence of neutralizing antibodies. Three distinguishing saliva SARS-CoV-2 antibody features were identified according to age (IgA1 to Spike 1, IgA1 to nucleocapsid protein (NP)), suggesting that adults and children generate distinct mucosal antibody responses during the acute phase of infection. CONCLUSION: Utilizing respiratory and nonrespiratory PCR testing, along with the measurement of SARS-CoV-2-specific local and systemic antibodies, provides a more accurate assessment of infection within households and highlights some of the immunological differences in response between children and

BACKGROUND: First Few "X" (FFX) studies provide a platform to collect the required epidemiological, clinical and virological data to help address emerging information needs about the COVID-19 pandemic. METHODS: We adapted the WHO FFX protocol for COVID-19 to understand severity and household transmission dynamics in the early stages of the pandemic in Australia. Implementation strategies were developed for participating sites; all household members were followed for 14 days from case identification. Household contacts completed symptom diaries and had multiple respiratory swabs taken irrespective of symptoms. We modelled the spread of COVID-19 within households using a susceptible-exposed-infectious-recovered-type model, and calculated the household secondary attack rate and key epidemiological parameters. FINDINGS: 96 households with 101 cases and 286 household contacts were recruited into the study between April-October 2020. Forty household contacts tested positive for SARS-CoV-2 in the study follow-up period. Our model estimated the household secondary attack rate to be 15% (95% CI 8-25%), which scaled up with increasing household size. Our findings suggest children were less infectious than their adult counterparts but were also more susceptible to infection. INTERPRETATION: Our study provides important baseline data characterising the transmission of early SARS-CoV-2 strains from children and adults in Australia, against which properties of variants of concern can be benchmarked. We encountered many challenges with respect to logistics, ethics, governance and data management. Continued efforts to invest in preparedness research will help to test, refine and further develop Australian FFX study protocols in advance of future outbreaks. FUNDING: Australian Government Department of Health.

Rotavirus infection is a common cause of severe diarrheal disease and a major cause of deaths and hospitalizations among young children. Incidence of rotavirus has declined globally with increasing vaccine coverage. However, it remains a significant cause of morbidity and mortality in low-income countries where vaccine access is limited and efficacy is lower. The oral human neonatal vaccine RV3-BB can be safely administered earlier than other vaccines, and recent trials in Indonesia have demonstrated high efficacy. In this study, we use a stochastic individual-based model of rotavirus transmission and disease to estimate the anticipated population-level impact of RV3-BB following delivery according to either an infant (2, 4, 6 months) and neonatal (0, 2, 4 months) schedule. Using our model, which incorporated an age- and household-structured population and estimates of vaccine efficacy derived from trial data, we found both delivery schedules to be effective at reducing infection and disease. We estimated 95-96% reductions in infection and disease in children under 12 months of age when vaccine coverage is 85%. We also estimate high levels of indirect protection from vaccination, including 78% reductions in infection in adults over 17 years of age. Even for lower vaccine coverage of 55%, we estimate reductions of 84% in infection and disease in children under 12 months of age. While open questions remain about the drivers of observed lower efficacy in low-income settings, our model suggests RV3-BB could be effective at reducing infection and preventing disease in young infants at the population level.

BACKGROUND: Scabies was added to the WHO NTD portfolio in 2017 and targets for the control of scabies were included in the 2021-2030 WHO NTD roadmap. A major component of scabies control efforts a strategy based on mass drug administration (MDA) with ivermectin. Currently diagnosis of scabies relies on clinical examination with a limited role for diagnostic testing. Under the recommendation of the WHO Diagnostic Technical Advisory Group (DTAG) for Neglected Tropical Diseases, a working group was assembled and tasked with agreeing on priority use cases for and developing target product profiles (TPPs) for new diagnostics tools for scabies. METHODOLOGY AND PRINCIPAL FINDINGS: The working group convened three times and established two use cases: establishing if the 10% threshold for mass drug administration had been reached and if the 2% threshold for stopping mass drug administration has been achieved. One subgroup assessed the current diagnostic landscape for scabies and a second subgroup determined the test requirements for both use cases. Draft TPPs were sent out for input from stakeholders and experts. Both TPPs considered the following parameters: product use, design, performance, configuration, cost, access and equity. The group considered the use of the tests as a single step process or as part of a two step process following initial clinical examination. When used a single step test (the ideal scenario) for starting MDA a new diagnostic required a sensitivity of ≥92% and a specificity of ≥98%. When used a single step test (the ideal scenario) for stopping MDA a new diagnostic required a sensitivity of ≥80% and a specificity of ≥99%. CONCLUSIONS: The TPPs developed will provide test developers with guidance to ensure that novel diagnostic tests meet identified public health needs.

We aimed to estimate the household secondary infection attack rate (hSAR) of SARS-CoV-2 in investigations aligned with the WHO Unity Studies Household Transmission Investigations (HHTI) protocol. We conducted a systematic review and meta-analysis according to PRISMA 2020 guidelines. We searched Medline, Embase, Web of Science, Scopus and medRxiv/bioRxiv for "Unity-aligned" First Few X cases (FFX) and HHTIs published 1 December 2019 to 26 July 2021. Standardised early results were shared by WHO Unity Studies collaborators (to 1 October 2021). We used a bespoke tool to assess investigation methodological quality. Values for hSAR and 95% confidence intervals (CIs) were extracted or calculated from crude data. Heterogeneity was assessed by visually inspecting overlap of CIs on forest plots and quantified in meta-analyses. Of 9988 records retrieved, 80 articles (64 from databases; 16 provided by Unity Studies collaborators) were retained in the systematic review; 62 were included in the primary meta-analysis. hSAR point estimates ranged from 2% to 90% (95% prediction interval: 3%-71%; I 2 = 99.7%); I 2 values remained >99% in subgroup analyses, indicating high, unexplained heterogeneity and leading to a decision not to report pooled hSAR estimates. FFX and HHTI remain critical epidemiological tools for early and ongoing characterisation of novel infectious pathogens. The large, unexplained variance in hSAR estimates emphasises the need to further support standardisation in planning, conduct and analysis, and for clear and comprehensive reporting of FFX and HHTIs in time and place, to guide evidence-based pandemic preparedness and response efforts for SARS-CoV-2, influenza and future novel respiratory viruses.

Vaccination plays an important role in pandemic planning and response. The possibility of developing an effective vaccine for a novel pandemic virus is not assured. However, as we have seen with SARS-CoV-2 vaccine development, with sufficient resources and global focus, successful outcomes can be achieved in a relatively short period. However even when vaccine is available it will initially be scarce. When one becomes available, how should it be distributed? In this paper we explicate how ethical thinking that is carefully attuned to context is essential to decisions about how we should conduct vaccination in a pandemic where demand exceeds supply. We focus on two key issues. First, setting the aims for a pandemic vaccination programme. Second, thinking about the means of delivering a chosen aim. We outline how pandemic vaccine distribution strategies can be implemented with distinct aims, e.g. protecting groups at greater risk of harm, saving the most lives, or ensuring societal benefit. Each aim will result in a focus on a different priority population and each strategy will have a different benefit-harm profile. Once we have decided our aim, we still have choices to make about delivery. We may achieve at least some ends via direct or indirect strategies. Such policy decisions are not merely technical, but necessarily involve ethics. One important general issue is that such planning decisions about distribution will always be made under conditions of uncertainty about vaccine safety and effectiveness. However, planning how to distribute vaccine for SARS-CoV-2 is even harder because we understand relatively little about the virus, transmission, and its immunological impact in the short and long term.

Background: Mathematical models have been used throughout the COVID-19 pandemic to inform policymaking decisions. The COVID-19 Multi-Model Comparison Collaboration (CMCC) was established to provide country governments, particularly low- and middle-income countries (LMICs), and other model users with an overview of the aims, capabilities and limits of the main multi-country COVID-19 models to optimise their usefulness in the COVID-19 response. Methods: Seven models were identified that satisfied the inclusion criteria for the model comparison and had creators that were willing to participate in this analysis. A questionnaire, extraction tables and interview structure were developed to be used for each model, these tools had the aim of capturing the model characteristics deemed of greatest importance based on discussions with the Policy Group. The questionnaires were first completed by the CMCC Technical group using publicly available information, before further clarification and verification was obtained during interviews with the model developers. The fitness-for-purpose flow chart for assessing the appropriateness for use of different COVID-19 models was developed jointly by the CMCC Technical Group and Policy Group. Results: A flow chart of key questions to assess the fitness-for-purpose of commonly used COVID-19 epidemiological models was developed, with focus placed on their use in LMICs. Furthermore, each model was summarised with a description of the main characteristics, as well as the level of engagement and expertise required to use or adapt these models to LMIC settings. Conclusions: This work formalises a process for engagement with models, which is often done on an ad-hoc basis, with recommendations for both policymakers and model developers and should improve modelling use in policy decision making.

PCR testing is a crucial capability for managing disease outbreaks, but it is also a limited resource and must be used carefully to ensure the information gain from testing is valuable. Testing has two broad uses for informing public health policy, namely to track epidemic dynamics and to reduce transmission by identifying and managing cases. In this work we develop a modelling framework to examine the effects of test allocation in an epidemic, with a focus on using testing to minimise transmission. Using the COVID-19 pandemic as an example, we examine how the number of tests conducted per day relates to reduction in disease transmission, in the context of logistical constraints on the testing system. We show that if daily testing is above the routine capacity of a testing system, which can cause delays, then those delays can undermine efforts to reduce transmission through contact tracing and quarantine. This work highlights that the two goals of aiming to reduce transmission and aiming to identify all cases are different, and it is possible that focusing on one may undermine achieving the other. To develop an effective strategy, the goals must be clear and performance metrics must match the goals of the testing strategy. If metrics do not match the objectives of the strategy, then those metrics may incentivise actions that undermine achieving the objectives.

BACKGROUND: Pandemic planning has historically been oriented to respond to an influenza virus, with vaccination strategy being a key focus. As the current COVID-19 pandemic plays out, the Australian government is closely monitoring progress towards development of SARS-CoV2 vaccines as a definitive intervention. However, as in any pandemic, initial supply will likely be exceeded by demand due to limited manufacturing output. METHODS: We convened community juries in three Australian locations in 2019 to assess public acceptability and perceived legitimacy of influenza pandemic vaccination distribution strategies. Preparatory work included literature reviews on pandemic vaccine allocation strategies and on vaccine allocation ethics, and simulation modelling studies. We assumed vaccine would be provided to predefined priority groups. Jurors were then asked to recommend one of two strategies for distributing remaining early doses of vaccine: directly vaccinate people at higher risk of adverse outcomes from influenza; or indirectly protect the general population by vaccinating primary school students, who are most likely to spread infection. RESULTS: Thirty-four participants of diverse backgrounds and ages were recruited through random digit dialling and topic-blinded social media advertising. Juries heard evidence and arguments supporting different vaccine distribution strategies, and questioned expert presenters. All three community juries supported prioritising school children for influenza vaccination (aiming for indirect protection), one by 10-2 majority and two by consensus. Justifications included that indirect protection benefits more people and is likely to be more publicly acceptable. CONCLUSIONS: In the context of an influenza pandemic, informed citizens were not opposed to prioritising groups at higher risks of adverse outcomes, but if resources and epidemiological conditions allow, achieving population benefits should be a strategic priority. These insights m

National influenza pandemic plans have evolved substantially over recent decades, as has the scientific research that underpins the advice contained within them. While the knowledge generated by many research activities has been directly incorporated into the current generation of pandemic plans, scientists and policymakers are yet to capitalise fully on the potential for near real-time analytics to formally contribute to epidemic decision-making. Theoretical studies demonstrate that it is now possible to make robust estimates of pandemic impact in the earliest stages of a pandemic using first few hundred household cohort (FFX) studies and algorithms designed specifically for analysing FFX data. Pandemic plans already recognise the importance of both situational awareness i.e., knowing pandemic impact and its key drivers, and the need for pandemic special studies and related analytic methods for estimating these drivers. An important next step is considering how information from these situational assessment activities can be integrated into the decision-making processes articulated in pandemic planning documents. Here we introduce a decision support tool that directly uses outputs from FFX algorithms to present recommendations on response options, including a quantification of uncertainty, to decision makers. We illustrate this approach using response information from within the Australian influenza pandemic plan.

Understanding human movement patterns at local, national and international scales is critical in a range of fields, including transportation, logistics and epidemiology. Data on human movement is increasingly available, and when combined with statistical models, enables predictions of movement patterns across broad regions. Movement characteristics, however, strongly depend on the scale and type of movement captured for a given study. The models that have so far been proposed for human movement are best suited to specific spatial scales and types of movement. Selecting both the scale of data collection, and the appropriate model for the data remains a key challenge in predicting human movements. We used two different data sources on human movement in Australia, at different spatial scales, to train a range of statistical movement models and evaluate their ability to predict movement patterns for each data type and scale. Whilst the five commonly-used movement models we evaluated varied markedly between datasets in their predictive ability, we show that an ensemble modelling approach that combines the predictions of these models consistently outperformed all individual models against hold-out data.

Scabies is a neglected tropical disease (NTD) that causes a significant health burden, particularly in disadvantaged communities and where there is overcrowding. There is emerging evidence that ivermectin-based mass drug administration (MDA) can reduce the prevalence of scabies in some settings, but evidence remains limited, and there are no formal guidelines to inform control efforts. An informal World Health Organization (WHO) consultation was organized to find agreement on strategies for global control. The consultation resulted in a framework for scabies control and recommendations for mapping of disease burden, delivery of interventions, and establishing monitoring and evaluation. Key operational research priorities were identified. This framework will allow countries to set control targets for scabies as part of national NTD strategic plans and develop control strategies using MDA for high-prevalence regions and outbreak situations. As further evidence and experience are collected and strategies are refined over time, formal guidelines can be developed. The control of scabies and the reduction of the health burden of scabies and associated conditions will be vital to achieving the targets set in WHO Roadmap for NTDs for 2021 to 2030 and the Sustainable Development Goals.

BACKGROUND: Remote Australian Aboriginal and Torres Strait Islander communities have potential to be severely impacted by COVID-19, with multiple factors predisposing to increased transmission and disease severity. Our modelling aims to inform optimal public health responses. METHODS: An individual-based simulation model represented SARS-CoV2 transmission in communities ranging from 100 to 3500 people, comprised of large, interconnected households. A range of strategies for case finding, quarantining of contacts, testing, and lockdown were examined, following the silent introduction of a case. RESULTS: Multiple secondary infections are likely present by the time the first case is identified. Quarantine of close contacts, defined by extended household membership, can reduce peak infection prevalence from 60 to 70% to around 10%, but subsequent waves may occur when community mixing resumes. Exit testing significantly reduces ongoing transmission. Concurrent lockdown of non-quarantined households for 14 days is highly effective for epidemic control and reduces overall testing requirements; peak prevalence of the initial outbreak can be constrained to less than 5%, and the final community attack rate to less than 10% in modelled scenarios. Lockdown also mitigates the effect of a delay in the initial response. Compliance with lockdown must be at least 80-90%, however, or epidemic control will be lost. CONCLUSIONS: A SARS-CoV-2 outbreak will spread rapidly in remote communities. Prompt case detection with quarantining of extended-household contacts and a 14 day lockdown for all other residents, combined with exit testing for all, is the most effective strategy for rapid containment. Compliance is crucial, underscoring the need for community supported, culturally sensitive responses.

The veterinary prescription of antibiotics in low- and middle-income countries (LMIC) remains largely undocumented. In Bhutan, however, the national veterinary service keeps records of their activities and prescriptions, which offer an opportunity to establish a benchmark to assess the use of these agents in this and other LMIC. A cross-sectional retrospective study was designed and 2,266 handwritten veterinary records from 2017 were sampled from 23 animal health premises (AHPs) to estimate individual and an overall proportion of consultations that resulted in an antibiotic prescription. The frequency of antibiotic prescription per species, type of AHP, and according to WHO's AWaRe index and OIE list of priority antimicrobials were also explored. It was estimated that 31% (95% confidence interval: 29-33%; intracluster correlation: 0.03) of the veterinary consultations resulted in an antibiotic prescription. The incidence of antibiotic prescription was highest in consultations of poultry across AHP. Across species, diarrhea and wounds were frequently treated with broad-spectrum antibiotics including sulfonamides, tetracyclines, trimethoprim + sulfa, and penicillin. Between 45% and 70% antibiotics prescribed correspond to AWaRe's access group and up to 25% to AWaRe's watch group. Over 70% of antibiotics dispensed in veterinary consultations for any species correspond to the OIE's veterinary critically important antimicrobial agents. Overall, the study demonstrated positive features of veterinary antimicrobial stewardship in Bhutan, given the conservative proportion of consultation that results in this type of prescription and the type of antibiotic prescribed. Although the veterinary service closely follows the Bhutanese Standard Treatment Guidelines, the prescription of antibiotics to key species should be closely monitored. Our study suggests that further improvements of antibiotic stewardship can be achieved through standardisation of antibiotic prescription to som

The ability of health systems to cope with coronavirus disease (COVID-19) cases is of major concern. In preparation, we used clinical pathway models to estimate healthcare requirements for COVID-19 patients in the context of broader public health measures in Australia. An age- and risk-stratified transmission model of COVID-19 demonstrated that an unmitigated epidemic would dramatically exceed the capacity of the health system of Australia over a prolonged period. Case isolation and contact quarantine alone are insufficient to constrain healthcare needs within feasible levels of expansion of health sector capacity. Overlaid social restrictions must be applied over the course of the epidemic to ensure systems do not become overwhelmed and essential health sector functions, including care of COVID-19 patients, can be maintained. Attention to the full pathway of clinical care is needed, along with ongoing strengthening of capacity.

BACKGROUND: The high burden of infectious disease and associated antimicrobial use likely contribute to the emergence of antimicrobial resistance in remote Australian Aboriginal communities. We aimed to develop and apply context-specific tools to audit antimicrobial use in the remote primary healthcare setting. METHODS: We adapted the General Practice version of the National Antimicrobial Prescribing Survey (GP NAPS) tool to audit antimicrobial use over 2-3 weeks in 15 remote primary healthcare clinics across the Kimberley region of Western Australia (03/2018-06/2018), Top End of the Northern Territory (08/2017-09/2017) and far north Queensland (05/2018-06/2018). At each clinic we reviewed consecutive clinic presentations until 30 presentations where antimicrobials had been used were included in the audit. Data recorded included the antimicrobials used, indications and treating health professional. We assessed the appropriateness of antimicrobial use and functionality of the tool. RESULTS: We audited the use of 668 antimicrobials. Skin and soft tissue infections were the dominant treatment indications (WA: 35%; NT: 29%; QLD: 40%). Compared with other settings in Australia, narrow spectrum antimicrobials like benzathine benzylpenicillin were commonly given and the appropriateness of use was high (WA: 91%; NT: 82%; QLD: 65%). While the audit was informative, non-integration with practice software made the process manually intensive. CONCLUSIONS: Patterns of antimicrobial use in remote primary care are different from other settings in Australia. The adapted GP NAPS tool functioned well in this pilot study and has the potential for integration into clinical care. Regular stewardship audits would be facilitated by improved data extraction systems.

Freya Shearer and co-authors discuss the use of decision analysis in planning for infectious disease pandemics.

Prevalence of impetigo (skin sores) remains high in remote Australian Aboriginal communities, Fiji, and other areas of socio-economic disadvantage. Skin sore infections, driven primarily in these settings by Group A Streptococcus (GAS) contribute substantially to the disease burden in these areas. Despite this, estimates for the force of infection, infectious period and basic reproductive ratio—all necessary for the construction of dynamic transmission models—have not been obtained. By utilising three datasets each containing longitudinal infection information on individuals, we estimate each of these epidemiologically important parameters. With an eye to future study design, we also quantify the optimal sampling intervals for obtaining information about these parameters. We verify the estimation method through a simulation estimation study, and test each dataset to ensure suitability to the estimation method. We find that the force of infection differs by population prevalence, and the infectious period is estimated to be between 12 and 20 days. We also find that optimal sampling interval depends on setting, with an optimal sampling interval between 9 and 11 days in a high prevalence setting, and 21 and 27 days for a lower prevalence setting. These estimates unlock future model-based investigations on the transmission dynamics of skin sores.

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Households are known to be high-risk locations for the transmission of communicable diseases. Numerous modelling studies have demonstrated the important role of households in sustaining both communicable diseases outbreaks and endemic transmission, and as the focus for control efforts. However, these studies typically assume that households are associated with a single dwelling and have static membership. This assumption does not appropriately reflect households in some populations, such as those in remote Australian Aboriginal and Torres Strait Islander communities, which can be distributed across more than one physical dwelling, leading to the occupancy of individual dwellings changing rapidly over time. In this study, we developed an individual-based model of an infectious disease outbreak in communities with demographic and household structure reflective of a remote Australian Aboriginal community. We used the model to compare the dynamics of unmitigated outbreaks, and outbreaks constrained by a household-focused prophylaxis intervention, in communities exhibiting fluid vs. stable dwelling occupancy. We found that fluid dwelling occupancy can lead to larger and faster outbreaks in modelled scenarios, and may interfere with the effectiveness of household-focused interventions. Our findings suggest that while short-term restrictions on movement between dwellings may be beneficial during outbreaks, in the longer-term, strategies focused on reducing household crowding may be a more effective way to reduce the risk of severe outbreaks occurring in populations with fluid dwelling occupancy.