Forecasting COVID-19 activity in Australia to support pandemic response: May to October 2020.

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.

SARS-CoV-2 seroepidemiology in Mongolia, 2020–2021: a longitudinal national study

Background The COVID-19 pandemic has global impacts but is relatively understudied in developing countries. Mongolia, a lower-middle-income country, instituted strict control measures in early 2020 and avoided widespread transmission until vaccines became available in February, 2021. Mongolia achieved its 60% vaccination coverage goal by July 2021. We investigated the distribution and determinants of SARS-CoV-2 seroprevalence in Mongolia over 2020 and 2021. Methods We performed a longitudinal seroepidemiologic study aligned with WHO's Unity Studies protocols. We collected data from a panel of 5000 individuals in four rounds between October 2020 and December 2021. We selected participants through local health centres across Mongolia by age-stratified multi-stage cluster sampling. We tested serum for the presence of total antibodies against SARS-CoV-2 receptor-binding domain, and levels of anti-SARS-CoV-2 spike IgG and neutralising antibodies. We linked participant data with national mortality, COVID-19 case, and vaccination registries. We estimated population seroprevalence and vaccine uptake, as well as unvaccinated population prior-infection prevalence. Findings At the final round in late 2021, 82% (n = 4088) of participants completed follow-up. Estimated seroprevalence increased from 1.5% (95% CI: 1.2–2.0), to 82.3% (95% CI: 79.5–84.8) between late-2020 and late-2021. At the final round an estimated 62.4% (95% CI: 60.2–64.5) of the population were vaccinated, and of the unvaccinated population 64.5% (95% CI: 59.7–69.0) had been infected. Cumulative case ascertainment in the unvaccinated was 22.8% (95% CI: 19.1%–26.9%) and the overall infection-fatality ratio was 0.100% (95% CI: 0.088–0.124). Health workers had higher odds for being COVID-19 confirmed cases at all rounds. Males (1.72 (95% CI: 1.33–2.22)) and adults aged 20 and above (12.70 (95% CI: 8.14–20.26)) had higher odds for seroconverting by mid-2021. Among the seropositive, 87.1% (95% CI: 82.3%–90.8%) had SARS-CoV-2 neutralising antibodies by late 2021. Interpretation Our study enabled tracking of SARS-CoV-2 serological markers in the Mongolian population over one year. We found low SARS-CoV-2 seroprevalence in 2020 and early 2021, with seropositivity increasing over a 3-month interval in 2021 due to vaccine roll out and rapid infection of most of the unvaccinated population. Despite high seroprevalence in Mongolia amongst both vaccinated and unvaccinated individuals by end-2021, the SARS-CoV-2 Omicron immune escape variant caused a substantial epidemic. Funding 10.13039/100004423World Health Organization, WHO UNITY Studies initiative, with funding by the COVID-19 Solidarity Response Fund and the German Federal Ministry of Health (BMG) COVID-19 Research and development. The Ministry of Health, Mongolia partially funded this study.

SARS-CoV-2 seroepidemiology in Mongolia, 2020-2021: a longitudinal national study.

Background: The COVID-19 pandemic has global impacts but is relatively understudied in developing countries. Mongolia, a lower-middle-income country, instituted strict control measures in early 2020 and avoided widespread transmission until vaccines became available in February, 2021. Mongolia achieved its 60% vaccination coverage goal by July 2021. We investigated the distribution and determinants of SARS-CoV-2 seroprevalence in Mongolia over 2020 and 2021. Methods: We performed a longitudinal seroepidemiologic study aligned with WHO's Unity Studies protocols. We collected data from a panel of 5000 individuals in four rounds between October 2020 and December 2021. We selected participants through local health centres across Mongolia by age-stratified multi-stage cluster sampling. We tested serum for the presence of total antibodies against SARS-CoV-2 receptor-binding domain, and levels of anti-SARS-CoV-2 spike IgG and neutralising antibodies. We linked participant data with national mortality, COVID-19 case, and vaccination registries. We estimated population seroprevalence and vaccine uptake, as well as unvaccinated population prior-infection prevalence. Findings: At the final round in late 2021, 82% (n = 4088) of participants completed follow-up. Estimated seroprevalence increased from 1.5% (95% CI: 1.2-2.0), to 82.3% (95% CI: 79.5-84.8) between late-2020 and late-2021. At the final round an estimated 62.4% (95% CI: 60.2-64.5) of the population were vaccinated, and of the unvaccinated population 64.5% (95% CI: 59.7-69.0) had been infected. Cumulative case ascertainment in the unvaccinated was 22.8% (95% CI: 19.1%-26.9%) and the overall infection-fatality ratio was 0.100% (95% CI: 0.088-0.124). Health workers had higher odds for being COVID-19 confirmed cases at all rounds. Males (1.72 (95% CI: 1.33-2.22)) and adults aged 20 and above (12.70 (95% CI: 8.14-20.26)) had higher odds for seroconverting by mid-2021. Among the seropositive, 87.1% (95% CI: 82.3%-90.8%) had SARS-CoV-2 neutralising antibodies by late 2021. Interpretation: Our study enabled tracking of SARS-CoV-2 serological markers in the Mongolian population over one year. We found low SARS-CoV-2 seroprevalence in 2020 and early 2021, with seropositivity increasing over a 3-month interval in 2021 due to vaccine roll out and rapid infection of most of the unvaccinated population. Despite high seroprevalence in Mongolia amongst both vaccinated and unvaccinated individuals by end-2021, the SARS-CoV-2 Omicron immune escape variant caused a substantial epidemic. Funding: World Health Organization, WHO UNITY Studies initiative, with funding by the COVID-19 Solidarity Response Fund and the German Federal Ministry of Health (BMG) COVID-19 Research and development. The Ministry of Health, Mongolia partially funded this study.

A modelling approach to estimate the transmissibility of SARS-CoV-2 during periods of high, low, and zero case incidence.

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.

Inclusion of Cultural and Linguistic Diversity in COVID-19 Public Health Research: Research Design Adaptations to Seek Different Perspectives in Victoria, Australia.

Participation of people from culturally and linguistically diverse (CALD) communities in public health research is often limited by challenges with recruitment, retention and second-language data collection. Consequently, people from CALD communities are at risk of their needs being marginalised in public health interventions. This paper presents intrinsic case analyses of two studies which were adapted to increase the cultural competence of research processes. Both cases were part of the Optimise study, a major mixed methods research study in Australia which provided evidence to inform the Victorian state government's decision-making about COVID-19 public health measures. Case study 1 involved the core Optimise longitudinal cohort study and Case study 2 was the CARE Victorian representative survey, an Optimise sub-study. Both case studies engaged cultural advisors and bilingual staff to adjust the survey measures and research processes to suit target CALD communities. Reflexive processes provided insights into the strengths and weaknesses of the inclusive strategies. Selected survey results are provided, demonstrating variation across CALD communities and in comparison to participants who reported speaking English at home. While in most cases a gradient of disadvantage was evident for CALD communities, some patterns were unexpected. The case studies demonstrate the challenge and value of investing in culturally competent research processes to ensure research guiding policy captures a spectrum of experiences and perspectives.

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.

Early analysis of the Australian COVID-19 epidemic.

As of 1 May 2020, there had been 6808 confirmed cases of COVID-19 in Australia. Of these, 98 had died from the disease. The epidemic had been in decline since mid-March, with 308 cases confirmed nationally since 14 April. This suggests that the collective actions of the Australian public and government authorities in response to COVID-19 were sufficiently early and assiduous to avert a public health crisis - for now. Analysing factors that contribute to individual country experiences of COVID-19, such as the intensity and timing of public health interventions, will assist in the next stage of response planning globally. We describe how the epidemic and public health response unfolded in Australia up to 13 April. We estimate that the effective reproduction number was likely below one in each Australian state since mid-March and forecast that clinical demand would remain below capacity thresholds over the forecast period (from mid-to-late April).

Learnings from the Australian first few X household transmission project for COVID-19.

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.

Transmission of SARS-CoV-2 in standardised first few X cases and household transmission investigations: A systematic review and meta-analysis.

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.

COVID-19 in low-tolerance border quarantine systems: Impact of the Delta variant of SARS-CoV-2.

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.

Development of an influenza pandemic decision support tool linking situational analytics to national response policy.

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.