Publications by authors named "Ashley Quigley"

Aims: Community-level childhood experiences make up important aspects of early life that are associated with long-term health outcomes. However, to date, there have been no validated measures that assess community-level experiences during childhood. Thus, we aimed to develop and validate a measure that would assess community-level experiences associated with both risk and resilience.

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  • Formal infectious disease surveillance in Ukraine has been severely affected by Russia's invasion in 2022, hindering the ability to track epidemics effectively.
  • An analysis using data from EPIWATCH showed significant increases in infections such as cholera, botulism, tuberculosis, and more during the conflict compared to before the invasion.
  • Open-source data emerged as a valuable tool for tracking infectious diseases in the absence of formal surveillance, although there were still limitations in data availability and accuracy during the war.
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Introduction: Admission of a newborn to a neonatal intensive care unit (NICU) can be a highly stressful event that affects maternal psychological well-being and disrupts the early maternal-infant bonding relationship. Determining factors that promote maternal-infant bonding among those with a NICU admission is essential for the development of effective interventions.

Methods: Using a longitudinal clinic-based sample of diverse and low-income pregnant women, we examined whether maternal-fetal bonding measured during the second trimester moderated the association between NICU admission and postpartum bonding measured at six months post birth, controlling for demographic characteristics.

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Background: Healthcare workers (HCWs) are at risk of SARS-CoV-2 infections due to occupational exposure. The use of airborne personal protective equipment (PPE) significantly reduces this risk. In June 2021, an epidemic of the Delta variant began in New South Wales (NSW), Australia.

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Background: Residential aged-care facilities in Australia emerged as the high-risk setting the COVID-19 outbreaks due to community transmission. The vulnerable aged-care residents of these facilities suffered due to low hospital transfers and high mortality and morbidity rates. This study aimed to monitor and report the burden of COVID-19 in residential aged-care facilities across Australia and the impact of hospital transfer policies on resident hospitalisation during the first year of the pandemic.

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  • - This study investigates how personality traits influence the connection between adverse childhood experiences (ACEs) and perceived stress in pregnant women, highlighting that ACEs are linked to higher stress levels during pregnancy.
  • - It focuses on the Big Five personality dimensions, especially neuroticism and conscientiousness, finding that mothers with high ACEs tend to be more neurotic and less conscientious, leading to increased stress.
  • - The research suggests that identifying mothers with high ACEs could facilitate early support for managing stress and improving mental health during pregnancy.
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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.

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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.

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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.

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Introduction: Prior research has identified associations between pregnancy intendedness and maternal-foetal bonding, but no studies have examined the potential mediation of pregnancy happiness on the development of the maternal-infant relationship.

Methods: In 2017-2018, a clinic-based pregnancy cohort of 177 low-income and racially diverse women in a South-Central U.S.

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Emerging infections are a continual threat to public health security, which can be improved by use of rapid epidemic intelligence and open-source data. Artificial intelligence systems to enable earlier detection and rapid response by governments and health can feasibly mitigate health and economic impacts of serious epidemics and pandemics. EPIWATCH is an artificial intelligence-driven outbreak early-detection and monitoring system, proven to provide early signals of epidemics before official detection by health authorities.

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Objectives: Since mask uptake and the timing of mask use has the potential to influence the control of the COVID-19 pandemic, this study aimed to assess the changes in knowledge toward mask use in Sydney and Melbourne, Australia, during the 2020 COVID-19 pandemic.

Design: An observational study, using a cross-sectional survey, was distributed to adults in Sydney and Melbourne, Australia, during July-August 2020 (survey 1) and September 2020 (survey 2), during the COVID-19 pandemic in Australia.

Setting And Participants: Participants aged 18 years or older and living in either Sydney or Melbourne.

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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.

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Background: The coronavirus disease 2019 (COVID-19) pandemic has resulted in significant morbidity and mortality in aged-care facilities worldwide. The attention of infection control in aged care needs to shift towards the built environment, especially in relation to using the existing space to allow social distancing and isolation. Physical infrastructure of aged care facilities has been shown to present challenges to the implementation of isolation procedures.

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Sleep during infancy contributes to the development and maintenance of infant regulatory functioning and may be an early risk marker for more difficult temperamental traits like negative reactivity. Further, maternal adverse childhood experiences (ACEs) may predispose individuals to greater sleep disturbances in adulthood and have been linked with sleep disturbances in both mothers and infants. Thus, examining maternal history of ACEs and maternal sleep difficulties during pregnancy and postpartum may provide insight into underlying risk factors affecting infant sleep difficulties and early temperament development.

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Background: Aged-care facilities (ACF's) provide unique challenges when implementing infection control methods for respiratory outbreaks such as COVID-19. Research on this highly vulnerable setting is lacking and there was no national reporting data of COVID-19 cases in ACFs in Australia early in the pandemic. We aimed to estimate the burden of aged-care worker (ACW) infections and outbreaks of COVID-19 in Australian aged-care.

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call for continued use of non-pharmaceutical interventions to control covid-19 during and after vaccine roll outs

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Introduction: There are no publicly available national data on healthcare worker infections in Australia. It has been documented in many countries that healthcare workers (HCW) are at increased occupational risk of COVID-19. We aimed to estimate the burden of COVID-19 on Australia HCW and the health system by obtaining and organizing data on HCW infections, analyzing national HCW cases in regards to occupational risk and analyzing healthcare outbreak.

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