Coupling of Indo-Pacific climate variability over the last millennium.

The Indian Ocean Dipole (IOD) affects climate and rainfall across the world, and most severely in nations surrounding the Indian Ocean1-4. The frequency and intensity of positive IOD events increased during the twentieth century5 and may continue to intensify in a warming world6. However, confidence in predictions of future IOD change is limited by known biases in IOD models7 and the lack of information on natural IOD variability before anthropogenic climate change. Here we use precisely dated and highly resolved coral records from the eastern equatorial Indian Ocean, where the signature of IOD variability is strong and unambiguous, to produce a semi-continuous reconstruction of IOD variability that covers five centuries of the last millennium. Our reconstruction demonstrates that extreme positive IOD events were rare before 1960. However, the most extreme event on record (1997) is not unprecedented, because at least one event that was approximately 27 to 42 per cent larger occurred naturally during the seventeenth century. We further show that a persistent, tight coupling existed between the variability of the IOD and the El Niño/Southern Oscillation during the last millennium. Indo-Pacific coupling was characterized by weak interannual variability before approximately 1590, which probably altered teleconnection patterns, and by anomalously strong variability during the seventeenth century, which was associated with societal upheaval in tropical Asia. A tendency towards clustering of positive IOD events is evident in our reconstruction, which-together with the identification of extreme IOD variability and persistent tropical Indo-Pacific climate coupling-may have implications for improving seasonal and decadal predictions and managing the climate risks of future IOD variability.

Voxelisation Algorithms and Data Structures: A Review.

Voxel-based data structures, algorithms, frameworks, and interfaces have been used in computer graphics and many other applications for decades. There is a general necessity to seek adequate digital representations, such as voxels, that would secure unified data structures, multi-resolution options, robust validation procedures and flexible algorithms for different 3D tasks. In this review, we evaluate the most common properties and algorithms for voxelisation of 2D and 3D objects. Thus, many voxelisation algorithms and their characteristics are presented targeting points, lines, triangles, surfaces and solids as geometric primitives. For lines, we identify three groups of algorithms, where the first two achieve different voxelisation connectivity, while the third one presents voxelisation of curves. We can say that surface voxelisation is a more desired voxelisation type compared to solid voxelisation, as it can be achieved faster and requires less memory if voxels are stored in a sparse way. At the same time, we evaluate in the paper the available voxel data structures. We split all data structures into static and dynamic grids considering the frequency to update a data structure. Static grids are dominated by SVO-based data structures focusing on memory footprint reduction and attributes preservation, where SVDAG and SSVDAG are the most advanced methods. The state-of-the-art dynamic voxel data structure is NanoVDB which is superior to the rest in terms of speed as well as support for out-of-core processing and data management, which is the key to handling large dynamically changing scenes. Overall, we can say that this is the first review evaluating the available voxelisation algorithms for different geometric primitives as well as voxel data structures.

The potential impact of a recent measles epidemic on COVID-19 in Samoa.

BACKGROUND: The pandemic of COVID-19 has occurred close on the heels of a global resurgence of measles. In 2019, an unprecedented epidemic of measles affected Samoa, requiring a state of emergency to be declared. Measles causes an immune amnesia which can persist for over 2 years after acute infection and increases the risk of a range of other infections. METHODS: We modelled the potential impact of measles-induced immune amnesia on a COVID-19 epidemic in Samoa using data on measles incidence in 2018-2019, population data and a hypothetical COVID-19 epidemic. RESULTS: The young population structure and contact matrix in Samoa results in the most transmission occurring in young people < 20 years old. The highest rate of death is the 60+ years old, but a smaller peak in death may occur in younger people, with more than 15% of total deaths in the age group under 20 years old. Measles induced immune amnesia could increase the total number of cases by 8% and deaths by more than 2%. CONCLUSIONS: Samoa, which had large measles epidemics in 2019-2020 should focus on rapidly achieving high rates of measles vaccination and enhanced surveillance for COVID-19, as the impact may be more severe due to measles-induced immune paresis. This applies to other severely measles-affected countries in the Pacific, Europe and elsewhere.

Seldom heard voices: a meta-narrative systematic review of Aboriginal and Torres Strait Islander peoples healthcare experiences.

BACKGROUND: It is well established that Aboriginal and Torres Strait Islander populations face considerable health inequities, exacerbated by poorer healthcare quality. Patient experience is recognised as a major contributing factor to healthcare quality and outcomes, therefore, enriched knowledge of the patient experiences of Aboriginal and Torres Strait Islander populations is critical to redress health inequities. This review synthesises evidence of the healthcare experiences amongst Aboriginal and Torres Strait Islander patients through a metanarrative synthesis of qualitative literature. METHODS: A systematic search strategy was developed and applied to six electronic databases between January 2000 and July 2019. Titles and abstracts were screened before applying the inclusion criteria to full text articles. A meta-narrative synthesis was undertaken. RESULTS: Fifty-four publications were identified from four research traditions; each with a unique conceptualisation of patient experience. Three themes emerged that demonstrate Aboriginal and Torres Strait Islander patient experiences are informed by 1) beliefs about wellbeing and healthcare provision, 2) their level of trust in the healthcare system, and 3) individual and community health system interactions. The findings highlight a range of aspects of patient experience that were important to participating Aboriginal and Torres Strait Islanders in the included studies but not captured currently in health system surveys. CONCLUSION: This review highlights the influence of beliefs about health and wellbeing on the patient experience amongst Aboriginal and Torres Strait Islander populations in the Australian health system. Patient experiences were informed by past experience and their trust in the health system. The different factors influencing patient experience and the gravity of their influence must be considered in current approaches to capturing patient experience data collection methods. TRIAL REGISTRATION: PROSPERO (ID: CRD42019134765 ).

Can feedback approaches reduce unwarranted clinical variation? A systematic rapid evidence synthesis.

BACKGROUND: Assessment of clinical variation has attracted increasing interest in health systems internationally due to growing awareness about better value and appropriate health care as a mechanism for enhancing efficient, effective and timely care. Feedback using administrative databases to provide benchmarking data has been utilised in several countries to explore clinical care variation and to enhance guideline adherent care. Whilst methods for detecting variation are well-established, methods for determining variation that is unwarranted and addressing this are strongly debated. This study aimed to synthesize published evidence of the use of feedback approaches to address unwarranted clinical variation (UCV). METHODS: A rapid review and narrative evidence synthesis was undertaken as a policy-focused review to understand how feedback approaches have been applied to address UCV specifically. Key words, synonyms and subject headings were used to search the major electronic databases Medline and PubMed between 2000 and 2018. Titles and abstracts of publications were screened by two reviewers and independently checked by a third reviewer. Full text articles were screened against the eligibility criteria. Key findings were extracted and integrated in a narrative synthesis. RESULTS: Feedback approaches that occurred over a duration of 1 month to 9 years to address clinical variation emerged from 27 publications with quantitative (20), theoretical/conceptual/descriptive work (4) and mixed or multi-method studies (3). Approaches ranged from presenting evidence to individuals, teams and organisations, to providing facilitated tailored feedback supported by a process of ongoing dialogue to enable change. Feedback approaches identified primarily focused on changing clinician decision-making and behaviour. Providing feedback to clinicians was identified, in a range of a settings, as associated with changes in variation such as reducing overuse of tests and treatments, reducing variations in optimal patient clinical outcomes and increasing guideline or protocol adherence. CONCLUSIONS: The review findings suggest value in the use of feedback approaches to respond to clinical variation and understand when action is warranted. Evaluation of the effectiveness of particular feedback approaches is now required to determine if there is an optimal approach to create change where needed.

Translation of Real-Time Infectious Disease Modeling into Routine Public Health Practice.

Infectious disease dynamic modeling can support outbreak emergency responses. We conducted a workshop to canvas the needs of stakeholders in Australia for practical, real-time modeling tools for infectious disease emergencies. The workshop was attended by 29 participants who represented government, defense, general practice, and academia stakeholders. We found that modeling is underused in Australia and its potential is poorly understood by practitioners involved in epidemic responses. The development of better modeling tools is desired. Ideal modeling tools for operational use would be easy to use, clearly indicate underlying parameterization and assumptions, and assist with policy and decision making.

Increase in African dust flux at the onset of commercial agriculture in the Sahel region.

The Sahara Desert is the largest source of mineral dust in the world. Emissions of African dust increased sharply in the early 1970s (ref. 2), a change that has been attributed mainly to drought in the Sahara/Sahel region caused by changes in the global distribution of sea surface temperature. The human contribution to land degradation and dust mobilization in this region remains poorly understood, owing to the paucity of data that would allow the identification of long-term trends in desertification. Direct measurements of airborne African dust concentrations only became available in the mid-1960s from a station on Barbados and subsequently from satellite imagery since the late 1970s: they do not cover the onset of commercial agriculture in the Sahel region approximately 170 years ago. Here we construct a 3,200-year record of dust deposition off northwest Africa by investigating the chemistry and grain-size distribution of terrigenous sediments deposited at a marine site located directly under the West African dust plume. With the help of our dust record and a proxy record for West African precipitation we find that, on the century scale, dust deposition is related to precipitation in tropical West Africa until the seventeenth century. At the beginning of the nineteenth century, a sharp increase in dust deposition parallels the advent of commercial agriculture in the Sahel region. Our findings suggest that human-induced dust emissions from the Sahel region have contributed to the atmospheric dust load for about 200 years.

Early detection of emerging infectious diseases - implications for vaccine development.

Vast quantities of open-source data from news reports, social media and other sources can be harnessed using artificial intelligence and machine learning, and utilised to generate valid early warning signals of emerging epidemics. Early warning signals from open-source data are not a replacement for traditional, validated disease surveillance, but provide a trigger for earlier investigation and diagnostics. This may yield earlier pathogen characterisation and genomic data, which can enable earlier vaccine development or deployment of vaccines. Early warning also provides a more feasible prospect of stamping out epidemics before they spread. There are several of such systems currently, but they are not used widely in public health practice, and only some are publicly available. Routine and widespread use of open-source intelligence, as well as training and capacity building in digital surveillance, will improve pandemic preparedness and early response capability.

Estimated Mask Use and Temporal Relationship to COVID-19 Epidemiology of Black Lives Matter Protests in 12 Cities.

BACKGROUND: There is an increased risk of SARS-CoV-2 transmission during mass gatherings and a risk of asymptomatic infection. We aimed to estimate the use of masks during Black Lives Matter (BLM) protests and whether these protests increased the risk of COVID-19. Two reviewers screened 496 protest images for mask use, with high inter-rater reliability. Protest intensity, use of tear gas, government control measures, and testing rates were estimated in 12 cities. A correlation analysis was conducted to assess the potential effect of mask use and other measures, adjusting for testing rates, on COVID-19 epidemiology 4 weeks (two incubation periods) post-protests. Mask use ranged from 69 to 96% across protests. There was no increase in the incidence of COVID-19 post-protest in 11 cities. After adjusting for testing rates, only Miami, which involved use of tear gas and had high protest intensity, showed a clear increase in COVID-19 after one incubation period post-protest. No significant correlation was found between incidence and protest factors. Our study showed that protests in most cities studied did not increase COVID-19 incidence in 2020, and a high level of mask use was seen. The absence of an epidemic surge within two incubation periods of a protest is indicative that the protests did not have a major influence on epidemic activity, except in Miami. With the globally circulating highly transmissible Alpha, Delta, and Omicron variants, layered interventions such as mandated mask use, physical distancing, testing, and vaccination should be applied for mass gatherings in the future.

Open-Source Intelligence for Detection of Radiological Events and Syndromes Following the Invasion of Ukraine in 2022: Observational Study.

BACKGROUND: On February 25, 2022, Russian forces took control of the Chernobyl power plant after continuous fighting within the Chernobyl exclusion zone. Continual events occurred in the month of March, which raised the risk of potential contamination of previously uncontaminated areas and the potential for impacts on human and environmental health. The disruption of war has caused interruptions to normal preventive activities, and radiation monitoring sensors have been nonfunctional. Open-source intelligence can be informative when formal reporting and data are unavailable. OBJECTIVE: This paper aimed to demonstrate the value of open-source intelligence in Ukraine to identify signals of potential radiological events of health significance during the Ukrainian conflict. METHODS: Data were collected from search terminology for radiobiological events and acute radiation syndrome detection between February 1 and March 20, 2022, using 2 open-source intelligence (OSINT) systems, EPIWATCH and Epitweetr. RESULTS: Both EPIWATCH and Epitweetr identified signals of potential radiobiological events throughout Ukraine, particularly on March 4 in Kyiv, Bucha, and Chernobyl. CONCLUSIONS: Open-source data can provide valuable intelligence and early warning about potential radiation hazards in conditions of war, where formal reporting and mitigation may be lacking, to enable timely emergency and public health responses.

Early pandemic use of face masks in Papua New Guinea under a mask mandate.

Objective: During the coronavirus disease (COVID-19) pandemic, face mask wearing was mandated in Port Moresby, Papua New Guinea in July 2020, but compliance was observed to be low. We aimed to determine the frequency of face mask wearing by the general public in Papua New Guinea under the mask mandate. Methods: To estimate compliance with the mandate, we analysed photographs of people gathering in Port Moresby published between 29 September and 29 October 2020. Photo-epidemiology was performed on the 40 photographs that met pre-defined selection criteria for inclusion in our study. Results: Among the total of 445 fully visible photographed faces, 53 (11.9%) were observed wearing a face mask over mouth and nose. Complete non-compliance (no faces wearing masks) was observed in 19 (4.3%) photographs. Physical distancing was observed in 10% of the 40 photographs. Mask compliance in indoor settings (16.4%) was higher than that observed in outdoor settings (9.8%), and this difference was statistically significant (P < 0.05). Mask compliance was observed in 8.9% of large-sized gatherings (> 30 people), 12.7% of medium-sized gatherings (11-30 people) and 25.0% of small-sized gatherings (4-10 people; photographs with < 4 people were excluded from analysis). Discussion: We found very low population compliance with face mask mandates in Papua New Guinea during the pre-vaccine pandemic period. Individuals without face coverings and non-compliant with physical distancing guidelines are considered to be in a high-risk category for COVID-19 transmission particularly in medium- and large-sized gatherings. A new strategy to enforce public health mandates is required and should be clearly promoted to the public.

Modeling on the Effects of Deliberate Release of Aerosolized Inhalational Bacillus anthracis (Anthrax) on an Australian Population.

This study aimed to determine optimal mitigation strategies in the event of an aerosolized attack with Bacillus anthracis, a category A bioterrorism agent with a case fatality rate of nearly 100% if inhaled and untreated. To simulate the effect of an anthrax attack, we used a plume dispersion model for Sydney, Australia, accounting for weather conditions. We determined the radius of exposure in different sizes of attack scenarios by spore quantity released per second. Estimations of different spore concentrations were then used to calculate the exposed population to inform a Susceptible-Exposed-Infected-Recovered (SEIR) deterministic mathematical model. Results are shown as estimates of the total number of exposed and infected people, along with the burden of disease, to quantify the amount of vaccination and antibiotics doses needed for stockpiles. For the worst-case scenario, over 500,000 people could be exposed and over 300,000 infected. The number of deaths depends closely on timing to start postexposure prophylaxis. Vaccination used as a postexposure prophylaxis in conjunction with antibiotics is the most effective mitigation strategy to reduce deaths after an aerosolized attack and is more effective when the response starts early (2 days after release) and has high adherence, while it makes only a small difference when started late (after 10 days).

Artificial intelligence in public health: the potential of epidemic early warning systems.

The use of artificial intelligence (AI) to generate automated early warnings in epidemic surveillance by harnessing vast open-source data with minimal human intervention has the potential to be both revolutionary and highly sustainable. AI can overcome the challenges faced by weak health systems by detecting epidemic signals much earlier than traditional surveillance. AI-based digital surveillance is an adjunct to-not a replacement of-traditional surveillance and can trigger early investigation, diagnostics and responses at the regional level. This narrative review focuses on the role of AI in epidemic surveillance and summarises several current epidemic intelligence systems including ProMED-mail, HealthMap, Epidemic Intelligence from Open Sources, BlueDot, Metabiota, the Global Biosurveillance Portal, Epitweetr and EPIWATCH. Not all of these systems are AI-based, and some are only accessible to paid users. Most systems have large volumes of unfiltered data; only a few can sort and filter data to provide users with curated intelligence. However, uptake of these systems by public health authorities, who have been slower to embrace AI than their clinical counterparts, is low. The widespread adoption of digital open-source surveillance and AI technology is needed for the prevention of serious epidemics.

Indian Ocean glacial deoxygenation and respired carbon accumulation during mid-late Quaternary ice ages.

Reconstructions of ocean oxygenation are critical for understanding the role of respired carbon storage in regulating atmospheric CO2. Independent sediment redox proxies are essential to assess such reconstructions. Here, we present a long magnetofossil record from the eastern Indian Ocean in which we observe coeval magnetic hardening and enrichment of larger, more elongated, and less oxidized magnetofossils during glacials compared to interglacials over the last ~900 ka. Our multi-proxy records of redox-sensitive magnetofossils, trace element concentrations, and benthic foraminiferal Δδ13C consistently suggest a recurrence of lower O2 in the glacial Indian Ocean over the last 21 marine isotope stages, as has been reported for the Atlantic and Pacific across the last glaciation. Consistent multi-proxy documentation of this repeated oxygen decline strongly supports the hypothesis that increased Indian Ocean glacial carbon storage played a significant role in atmospheric CO2 cycling and climate change over recent glacial/interglacial timescales.

Pacific Eclipse - A tabletop exercise on smallpox pandemic response.

BACKGROUND: In December 2019, we ran Pacific Eclipse, a pandemic tabletop exercise using smallpox originating in Fiji as a case study. Pacific Eclipse brought together international stakeholders from health, defence, law enforcement, emergency management and a range of other organisations. AIM: To review potential gaps in preparedness and identify modifiable factors which could prevent a pandemic or mitigate the impact of a pandemic. METHODS: Pacific Eclipse was held on December 9-10 in Washington DC, Phoenix and Honolulu simultaneously. The scenario began in Fiji and becomes a pandemic. Mathematical modelling of smallpox transmission was used to simulate the epidemic under different conditions and to test the effect of interventions. Live polling, using Poll Everywhere software that participants downloaded onto their smart phones, was used to gather participant decisions as the scenario unfolded. Stakeholders from state and federal government and non-government organisations from The United States, The United Kingdom, Australia, New Zealand, Canada, as well as industry and non-government organisations attended. RESULTS: The scenario progressed in three phases and participants were able to make decisions during each phase using live polling. The polling showed very diverse and sometimes conflicting decision making. Factors influential to pandemic severity were identified and categorised as modifiable or unmodifiable. A series of recommendations were made on the modifiable determinants of pandemic severity and how these can be incorporated into pandemic planning. These included preventing an attack through intelligence, law enforcement and legislation, improved speed of diagnosis, speed and completeness of case finding and case isolation, speed and security of vaccination response (including stockpiling), speed and completeness of contact tracing, protecting critical infrastructure and business continuity, non-pharmaceutical interventions (social distancing, PPE, border control) and protecting first responders. DISCUSSION: Pacific Eclipse illustrated the impact of a pandemic of smallpox under different response scenarios, which were validated to some extent by the COVID-19 pandemic. The framework developed from the scenario draws out modifiable determinants of pandemic severity which can inform pandemic planning for the ongoing COVID-19 pandemic and for future pandemics.

Factors associated with repeated influenza vaccine uptake among aged care staff in an Australian sample from 2017 to 2019.

BACKGROUND/AIM: Influenza vaccination is strongly recommended every year for aged care staff to protect themselves and minimise risk of transmission to residents. This study aimed to determine the factors associated with repeated annual influenza vaccine uptake among Australian aged care staff from 2017 to 2019. METHODS: Demographic, medical and vaccination data collected from the staff, who participated in an observational study from nine aged care facilities under a single provider in Sydney Australia, were analysed retrospectively. Based on the pattern of repeated influenza vaccination from 2017 to 2019, three groups were identified: (1) unvaccinated all three years; (2) vaccinated occasionally(once or twice) over three years; and (3)vaccinated all threeyears. Multinomial logistic regression analysis was performed to better understand the factors associated with the pattern of repeated influenza vaccination. RESULTS: From a total of 138 staff, between 2017 and 2019, 28.9 % (n = 40) never had a vaccination, while 44.2 % (n = 61) had vaccination occasionally and 26.8 % (n = 37) had vaccination all three years. In the multinomial logistic regression model, those who were<40 years old (OR = 0.57, 95 % CI: 0.19-0.90, p < 0.05) and those who were current smokers (OR = 0.20; 95 % CI: 0.03-0.76, p < 0.05) were less likely to have repeated vaccination for all three years compared to the unvaccinated group. Those who were<40 years old (OR = 0.61; 95 % CI: 0.22-0.68, p < 0.05) and those who were born overseas (OR = 0.50; 95 % CI:0.27-0.69, p < 0.05) were more likely to be vaccinated occasionally compared to the unvaccinated group. CONCLUSION: The significant predictors of repeated vaccine uptake across the three-year study period among aged care staff were age, smoking status and country of birth (Other vs Australia). Targeted interventions towards the younger age group (<40 years old), smokers and those who were born overseas could improve repeated influenza vaccination uptake in the aged care workforce.

Influenza cases in nine aged care facilities in Sydney, Australia over a three-year surveillance period, 2018-2020.

BACKGROUND: Influenza outbreaks in aged care facilities are a major public health concern. In response to the severe 2017 influenza season in Australia, enhanced influenza vaccines were introduced from 2018 onwards for those over 65 and more emphasis was placed on improving vaccination rates among aged care staff. During the COVID-19 pandemic, these efforts were then further escalated to reduce the additional burden that influenza could pose to facilities. METHODS: An observational epidemiological study was conducted from 2018 to 2020 in nine Sydney (Australia) aged care facilities of the same provider. De-identified vaccination data and physical layout data were collected from participating facility managers from 2018 to 2020. Active surveillance of influenza-like illness was carried out from 2018 to 2020 influenza seasons. Correlation and Poisson regression analyses were carried out to explore the relationship between physical layout variables to occurrence of influenza cases. RESULTS: Influenza cases were low in 2018 and 2019, and there were no confirmed influenza cases identified in 2020. Vaccination rates increased among staff by 50.5% and residents by 16.8% over the three-year period of surveillance from 2018 to 2020. For each unit increase in total number of beds, common areas, single rooms, all types of rooms (including double occupancy rooms), the influenza cases increased by 1.02 (95% confidence interval:1.018-1.025), 1.04 (95% confidence interval: 1.019-1.073), 1.03 (95% confidence interval: 1.016-1 0.038) and 1.02 (95% confidence interval:1.005-1.026) times which were found to be statistically significant. For each unit increase in the proportion of shared rooms, influenza cases increased by 1.004 (95% confidence interval:1.0001-1.207) which was found to be statistically significant. CONCLUSIONS: There is a relationship between influenza case counts and aspects of the physical layout such as facility size, and this should be considered in assessing risk of outbreaks in aged care facilities. Increased vaccination rates in staff and COVID-19 prevention and control measures may have eliminated influenza in the studied facilities in 2020.

Effectiveness estimates for enhanced trivalent influenza vaccines in an aged care summer outbreak.

An influenza outbreak occurred during summer (February 2019) in an aged-care facility in Sydney, Australia. Residents had not received the annual 2019 influenza vaccine while 76.7% had received 2018 influenza vaccines about 9 months prior. Overall, 2018 influenza vaccine effectiveness during this outbreak was high (93.6%). The effectiveness of the high-dose trivalent vaccine (HD-TIV) and adjuvanted trivalent (a-TIV) vaccine were 89.8% (95% confidence interval: 18.8%-98.7%) and 72.5% (95% confidence interval: -106.7%-96.3%) respectively. The differences in effectiveness between HD-TIV, a-TIV and SD-QIV, during the summer outbreak were not significant.