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Abstract Background Evidence on the relationship between air pollution and allergic sensitisation in childhood is inconsistent, and this relationship has not been investigated in the context of smoke events that are predicted to increase with climate change. Thus, we aimed to evaluate associations between exposure in two early life periods to severe levels of particulate matter with an aerodynamic diameter

Autoantibodies to multiple targets are found during acute COVID-19. Whether all, or some, persist after 6 months, and their correlation with sustained anti-SARS-CoV-2 immunity, is still controversial. Herein, we measured antibodies to multiple SARS-CoV-2 antigens (Wuhan-Hu-1 nucleoprotein (NP), whole spike (S), spike subunits (S1, S2 and receptor binding domain (RBD)) and Omicron spike) and 102 human proteins with known autoimmune associations, in plasma from healthcare workers 8 months post-exposure to SARS-CoV-2 (n=31 with confirmed COVID-19 disease and n=21 uninfected controls (PCR and anti-SARS-CoV-2 negative) at baseline). IgG antibody responses to SARS-CoV-2 antigens were significantly higher in the convalescent cohort than the healthy cohort, highlighting lasting antibody responses up to 8 months post-infection. These were also shown to be cross-reactive to the Omicron variant spike protein at a similar level to lasting anti-RBD antibodies (correlation r=0.89). Individuals post COVID-19 infection recognised a common set of autoantigens, specific to this group in comparison to the healthy controls. Moreover, the long-term level of anti-Spike IgG was associated with the breadth of autoreactivity post-COVID-19. There were further moderate positive correlations between anti-SARS-CoV-2 responses and 11 specific autoantigens. The most commonly recognised autoantigens were found in the COVID-19 convalescent cohort. Although there was no overall correlation in self-reported symptom severity and anti-SARS-CoV-2 antibody levels, anti-calprotectin antibodies were associated with return to healthy normal life 8 months post infection. Calprotectin was also the most common target for autoantibodies, recognized by 22.6% of the overall convalescent cohort. Future studies may address whether, counter-intuitively, such autoantibodies may play a protective role in the pathology of long-COVID-19.

The Inter-Agency Standing Committee (IASC), created by the United Nations (UN) General Assembly in 1991, serves as the global humanitarian coordination forum of the UN s system. The IASC brings 18 agencies together, including the World Health Organization (WHO), for humanitarian preparedness and response policies and action. Early in the COVID-19 pandemic, the IASC recognized the importance of providing intensified support to countries with conflict, humanitarian, or complex emergencies due to their weak health systems and fragile contexts. A Global Humanitarian Response Plan (GHRP) was rapidly developed in March 2020, which reflected the international support needed for 63 target countries deemed to have humanitarian vulnerability. This paper assessed whether WHO provided intensified technical, financial, and commodity inputs to GHRP countries (n = 63) compared to non-GHRP countries (n = 131) in the first year of the COVID-19 pandemic. The analysis showed that WHO supported all 194 countries regardless of humanitarian vulnerability. Health commodities were supplied to most countries globally (86%), and WHO implemented most (67%) of the $1.268 billion spent in 2020 at country level. However, proportionally more GHRP countries received health commodities and nearly four times as much was spent in GHRP countries per capita compared to non-GHRP countries ($232 vs. $60 per 1,000 capita). In countries with WHO country offices (n = 149), proportionally more GHRP countries received WHO support for developing national response plans and monitoring frameworks, training of technical staff, facilitating logistics, publication of situation updates, and participation in research activities prior to the characterization of the pandemic or first in-country COVID-19 case. This affirms WHO's capacity to scale country support according to its humanitarian mandate. Further work is needed to assess the impact of WHO's inputs on health outcomes during the COVID-19 pandemic, which will strengthen WHO's scaled support to countries during future health emergencies.

Abstract Objective: To assess the impact of an enhanced viral hepatitis surveillance program on data completeness and on epidemiological assessment of affected populations. Methods: Notified cases of non‐acute hepatitis B and C were analysed to determine demographic characteristics and risk factors during the period prior to July 2015–June 2016, and during enhanced surveillance of the period July 2016–June 2017, during which time doctors were contacted for information about new diagnoses. Results: During the enhanced period, completeness for country of birth and Indigenous status doubled for both hepatitis B and hepatitis C, from 18–37% to 48–65%. The incidence ratio of hepatitis C among Aboriginal and Torres Strait Islander people increased from eight‐fold to 11.4‐fold, and the proportion of hepatitis B cases reported as born in China and Vietnam relative to other countries increased. New data fields identified that 12% of hepatitis C diagnoses occurred in a correctional facility, and 2% of hepatitis B cases were healthcare workers. Conclusions: Improved data completeness highlighted the underlying epidemiology of chronic viral hepatitis, demonstrating the increased burden of infection among specific priority populations. Implications for public health: Enhanced surveillance provides greater insight into the epidemiology of chronic viral hepatitis, identifying groups at risk and opportunities for public health action.

Summary: Background: A cornerstone of Australia's ability to control COVID-19 has been effective border control with an extensive supervised quarantine programme. However, a rapid recrudescence of COVID-19 was observed in the state of Victoria in June, 2020. We aim to describe the genomic findings that located the source of this second wave and show the role of genomic epidemiology in the successful elimination of COVID-19 for a second time in Australia. Methods: In this observational, genomic epidemiological study, we did genomic sequencing of all laboratory-confirmed cases of COVID-19 diagnosed in Victoria, Australia between Jan 25, 2020, and Jan 31, 2021. We did phylogenetic analyses, genomic cluster discovery, and integrated results with epidemiological data (detailed information on demographics, risk factors, and exposure) collected via interview by the Victorian Government Department of Health. Genomic transmission networks were used to group multiple genomic clusters when epidemiological and genomic data suggested they arose from a single importation event and diversified within Victoria. To identify transmission of emergent lineages between Victoria and other states or territories in Australia, all publicly available SARS-CoV-2 sequences uploaded before Feb 11, 2021, were obtained from the national sequence sharing programme AusTrakka, and epidemiological data were obtained from the submitting laboratories. We did phylodynamic analyses to estimate the growth rate, doubling time, and number of days from the first local infection to the collection of the first sequenced genome for the dominant local cluster, and compared our growth estimates to previously published estimates from a similar growth phase of lineage B.1.1.7 (also known as the Alpha variant) in the UK. Findings: Between Jan 25, 2020, and Jan 31, 2021, there were 20 451 laboratory-confirmed cases of COVID-19 in Victoria, Australia, of which 15 431 were submitted for sequencing, and 11 711 met all quality control metrics and were included in our analysis. We identified 595 genomic clusters, with a median of five cases per cluster (IQR 2–11). Overall, samples from 11 503 (98·2%) of 11 711 cases clustered with another sample in Victoria, either within a genomic cluster or transmission network. Genomic analysis revealed that 10 426 cases, including 10 416 (98·4%) of 10 584 locally acquired cases, diagnosed during the second wave (between June and October, 2020) were derived from a single incursion from hotel quarantine, with the outbreak lineage (transmission network G, lineage D.2) rapidly detected in other Australian states and territories. Phylodynamic analyses indicated that the epidemic growth rate of the outbreak lineage in Victoria during the initial growth phase (samples collected between June 4 and July 9, 2020; 47·4 putative transmission events, per branch, per year [1/years; 95% credible interval 26·0–85·0]), was similar to that of other reported variants, such as B.1.1.7 in the UK (mean approximately 71·5 1/years). Strict interventions were implemented, and the outbreak lineage has not been detected in Australia since Oct 29, 2020. Subsequent cases represented independent international or interstate introductions, with limited local spread. Interpretation: Our study highlights how rapid escalation of clonal outbreaks can occur from a single incursion. However, strict quarantine measures and decisive public health responses to emergent cases are effective, even with high epidemic growth rates. Real-time genomic surveillance can alter the way in which public health agencies view and respond to COVID-19 outbreaks. Funding: The Victorian Government, the National Health and Medical Research Council Australia, and the Medical Research Future Fund.

Abstract Objective: Recent studies have used Bayesian methods to predict timing of influenza epidemics many weeks in advance, but there is no documented evaluation of how such forecasts might support the day‐to‐day operations of public health staff. Methods: During the 2015 influenza season in Melbourne, Australia, weekly forecasts were presented at Health Department surveillance unit meetings, where they were evaluated and updated in light of expert opinion to improve their accuracy and usefulness. Results: Predictive capacity of the model was substantially limited by delays in reporting and processing arising from an unprecedented number of notifications, disproportionate to seasonal intensity. Adjustment of the predictive algorithm to account for these delays and increased reporting propensity improved both current situational awareness and forecasting accuracy. Conclusions: Collaborative engagement with public health practitioners in model development improved understanding of the context and limitations of emerging surveillance data. Incorporation of these insights in a quantitative model resulted in more robust estimates of disease activity for public health use. Implications for public health: In addition to predicting future disease trends, forecasting methods can quantify the impact of delays in data availability and variable reporting practice on the accuracy of current epidemic assessment. Such evidence supports investment in systems capacity.

Abstract Objective: The proportion of positive chlamydia tests in young people in Tasmania increased significantly between 2001 and 2010. While female positivity rates increased steadily, male positivity rose steeply to 2005 then stabilised. Crude positivity rates can be influenced by a variety of factors making interpretation difficult. Unique Tasmanian datasets were used to explore whether symptom status, reason for testing or sexual exposure could explain the observed positivity trends. Methods: Population‐level chlamydia positivity rates in Tasmania over a 10‐year period were compared with surveillance data collected on people aged 15 to 29 years notified with chlamydia. Results: The proportion of asymptomatic chlamydia cases increased, with the largest increase in males aged 15 to 19 years (28%). Opportunistic testing of cases increased (greatest in males, range 17–32%). Sexual exposure remained consistent. Conclusions: After allowing for any changes in sexual exposure, symptom status and reason for testing, an increase in chlamydia positivity occurred over the 10 years. Healthcare providers have increased chlamydia testing in high‐risk groups. Implications: Monitoring chlamydia testing patterns and positivity rates at a population level is a step forward in surveillance practices. Targeted surveys provide valuable information to supplement routine surveillance data.