182 research outputs found
'I live in extremes': A qualitative investigation of Autistic adults' experiences of inertial rest and motion
'Autistic inertia' is a term used by Autistic people to refer to difficulties with starting and stopping tasks. However, there has not been much research on Autistic inertia. The research that is available on Autistic inertia has mostly focused on the negative aspects of inertia, rather than on the possible benefits of needing to continue tasks. In this research, we wanted to understand more about Autistic people's experiences of inertia and to work out what things might influence these experiences. Autistic and non-Autistic researchers spoke in-depth to 24 Autistic adults. We identified four key ideas from people's responses. Autistic people spoke about their inertial 'difficulties moving from one state to another' and described how these challenges affected them 'every single day'. While they experienced inertia as 'the single most disabling part of being Autistic', people also described the positive aspects of inertia, including the joy they felt when completely immersed in a task. Our Autistic participants emphasised that inertial difficulties are experienced by everyone, the intensity of these task-switching difficulties might be especially challenging for Autistic people. Our findings also reveal how Autistic inertia can be seen both as a disabling and as an enabling condition
Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission.
BACKGROUND: Several countries have controlled the spread of COVID-19 through varying combinations of border restrictions, case finding, contact tracing and careful calibration on the resumption of domestic activities. However, evaluating the effectiveness of these measures based on observed cases alone is challenging as it does not reflect the transmission dynamics of missed infections. METHODS: Combining data on notified local COVID-19 cases with known and unknown sources of infections (i.e. linked and unlinked cases) in Singapore in 2020 with a transmission model, we reconstructed the incidence of missed infections and estimated the relative effectiveness of different types of outbreak control. We also examined implications for estimation of key real-time metrics — the reproduction number and ratio of unlinked to linked cases, using observed data only as compared to accounting for missed infections. FINDINGS: Prior to the partial lockdown in Singapore, initiated in April 2020, we estimated 89% (95%CI 75–99%) of the infections caused by notified cases were contact traced, but only 12.5% (95%CI 2–69%) of the infections caused by missed infectors were identified. We estimated that the reproduction number was 1.23 (95%CI 0.98–1.54) after accounting for missed infections but was 0.90 (95%CI 0.79-1.1) based on notified cases alone. At the height of the outbreak, the ratio of missed to notified infections was 34.1 (95%CI 26.0–46.6) but the ratio of unlinked to linked infections was 0.81 (95%CI 0.59–1.36). Our results suggest that when case finding and contact tracing identifies at least 50% and 20% of the infections caused by missed and notified cases respectively, the reproduction number could be reduced by more than 14%, rising to 20% when contact tracing is 80% effective. INTERPRETATION: Depending on the relative effectiveness of border restrictions, case finding and contact tracing, unobserved outbreak dynamics can vary greatly. Commonly used metrics to evaluate outbreak control — typically based on notified data — could therefore misrepresent the true underlying outbreak. FUNDING: Ministry of Health, Singapore. EVIDENCE BEFORE THIS STUDY: We searched PubMed, BioRxiv and MedRxiv for articles published in English up to Mar 20, 2021 using the terms: (2019-nCoV OR “novel coronavirus” OR COVID-19 OR SARS-CoV-2) AND (border OR travel OR restrict* OR import*) AND (“case finding” OR surveillance OR test*) AND (contact trac*) AND (model*). The majority of modelling studies evaluated the effectiveness of various combinations of interventions in the absence of outbreak data. For studies that reconstructed the initial spread of COVID-19 with outbreak data, they further simulated counterfactual scenarios in the presence or absence of these interventions to quantify the impact to the outbreak trajectory. None of the studies disentangled the effects of case finding, contact tracing, introduction of imported cases and the reproduction number, in order to reproduce an observed SARS-CoV-2 outbreak trajectory. ADDED VALUE OF THIS STUDY: Notified COVID-19 cases with unknown and known sources of infection are identified through case finding and contact tracing respectively. Their respective daily incidence and the growth rate over time may differ. By capitalising on these differences in the outbreak data and the use of a mathematical model, we could identify the key drivers behind the growth and decline of both notified and missed COVID-19 infections in different time periods — e.g. domestic transmission vs external introductions, relative role of case finding and contact tracing in domestic transmission. Estimating the incidence of missed cases also allows us to evaluate the usefulness of common surveillance metrics that rely on observed cases. IMPLICATIONS OF ALL THE AVAILABLE EVIDENCE: Comprehensive outbreak investigation data integrated with mathematical modelling helps to quantify the strengths and weaknesses of each outbreak control intervention during different stages of the pandemic. This would allow countries to better allocate limited resources to strengthen outbreak control. Furthermore, the data and modelling approach allows us to estimate the extent of missed infections in the absence of population wide seroprevalence surveys. This allows us to compare the growth dynamics of notified and missed infections as reliance on the observed data alone may create the illusion of a controlled outbreak
Community health programs delivered through information and communications technology in high-income countries : Scoping review
Background:
The COVID-19 pandemic has required widespread and rapid adoption of information and communications technology (ICT) platforms by health professionals. Transitioning health programs from face-to-face to remote delivery using ICT platforms has introduced new challenges.
Objective:
The objective of this review is to scope for ICT-delivered health programs implemented within the community health setting in high-income countries and rapidly disseminate findings to health professionals.
Methods:
The Joanna Briggs Institute’s scoping review methodology guided the review of the literature.
Results:
The search retrieved 7110 unique citations. Each title and abstract was screened by at least two reviewers, resulting in 399 citations for full-text review. Of these 399 citations, 72 (18%) were included. An additional 27 citations were identified through reviewing the reference lists of the included studies, resulting in 99 citations. Citations examined 83 ICT-delivered programs from 19 high-income countries. Variations in program design, ICT platforms, research design, and outcomes were evident.
Conclusions:
Included programs and research were heterogeneous, addressing prevalent chronic diseases. Evidence was retrieved for the effectiveness of nurse and allied health ICT-delivered programs. Findings indicated that outcomes for participants receiving ICT-delivered programs, when compared with participants receiving in-person programs, were either equivalent or better. Gaps included a paucity of co-designed programs, qualitative research around group programs, programs for patients and carers, and evaluation of cost-effectiveness. During COVID-19 and beyond, health professionals in the community health setting are encouraged to build on existing knowledge and address evidence gaps by developing and evaluating innovative ICT-delivered programs in collaboration with consumers and carers
How to model the impact of vaccines for policymaking when the characteristics are uncertain: a case study in Thailand prior to the vaccine rollout during the COVID-19 pandemic
Thailand faced a dilemma of which groups to prioritise with a limited first tranche of COVID-19 vaccinations in early 2021, at a time when there was low incidence and low mortality in the country. A mathematical modelling analysis was performed to compare the potential short-term impact of allocating the available doses to either the high severity group (over 65-year-olds) or the high transmission group (aged 20-39). At the time of the analysis, there was uncertainty about the precise characteristics of the vaccines available, in terms of their potential impact on transmission and reductions to the severity of infection. As such, a range of vaccine characteristic scenarios, with differing levels of severity and transmission reductions were explored. Using the evidence available at the time regarding severity reduction of infection due to the vaccines, the model suggested that vaccinating high severity group should be the priority if reductions in deaths is the priority. Vaccinating this group was found to have a direct impact on reducing the number of deaths, while the incidence and hospitalisations remained unchanged. However, the model found that vaccinating the high transmission group with a vaccine with sufficiently high protection against infection (more than 70%) could provide enough herd effects to delay the expected epidemic peak, resulting in both case and death reductions in both target groups. The model explored a 12-month time horizon. These analyses helped to inform the vaccination strategy in Thailand throughout 2021 and can inform future modelling studies for policymaking when the characteristics of vaccines are uncertain
Dengue vector control in high-income, city settings: A scoping review of approaches and methods.
BACKGROUND: Dengue virus (DENV) is endemic to many parts of the world and has serious health and socioeconomic effects even in high-income countries, especially with rapid changes in the climate globally. We explored the literature on dengue vector control methods used in high-income, city settings and associations with dengue incidence, dengue prevalence, or mosquito vector densities. METHODS: Studies of any design or year were included if they reported effects on human DENV infection or Aedes vector indices of dengue-specific vector control interventions in high-income, city settings. RESULTS: Of 24 eligible sources, most reported research in the United States (n = 8) or Australia (n = 5). Biocontrol (n = 12) and chemical control (n = 13) were the most frequently discussed vector control methods. Only 6 sources reported data on the effectiveness of a given method in reducing human DENV incidence or prevalence, 2 described effects of larval and adult control on Aedes DENV positivity, 20 reported effectiveness in reducing vector density, using insecticide, larvicide, source reduction, auto-dissemination of pyriproxyfen and Wolbachia, and only 1 described effects on human-vector contact. CONCLUSIONS: As most studies reported reductions in vector densities, rather than any effects on human DENV incidence or prevalence, we can draw no clear conclusions on which interventions might be most effective in reducing dengue in high-income, city areas. More research is needed linking evidence on the effects of different DENV vector control methods with dengue incidence/prevalence or mosquito vector densities in high-income, city settings as this is likely to differ from low-income settings. This is a significant evidence gap as climate changes increase the global reach of DENV. The importance of community involvement was clear in several studies, although it is impossible to tease out the relative contributions of this from other control methods used
Epidemiology of Infant Dengue Cases Illuminates Serotype-Specificity in the Interaction between Immunity and Disease, and Changes in Transmission Dynamics
BACKGROUND: Infants born to dengue immune mothers acquire maternal antibodies to dengue. These antibodies, though initially protective, decline during the first year of life to levels thought to be disease enhancing, before reaching undetectable levels. Infants have long been studied to understand the interaction between infection and disease on an individual level. METHODS/FINDINGS: Considering infants (cases \u3c 1 year old) as a unique group, we analyzed serotype specific dengue case data from patients admitted to a pediatric hospital in Bangkok, Thailand. We show differences in the propensity of serotypes to cause disease in individuals with dengue antibodies (infants and post-primary cases) and in individuals without dengue antibodies (primary cases). The mean age of infant cases differed among serotypes, consistent with previously observed differential waning of maternal antibody titers by serotype. We show that trends over time in epidemiology of infant cases are consistent with those observed in the whole population, and therefore with trends in the force of infection.
CONCLUSIONS/SIGNIFICANCE: Infants with dengue are informative about the interaction between antibody and the dengue serotypes, confirming that in this population DENV-2 and DENV-4 almost exclusively cause disease in the presence of dengue antibody despite infections occurring in others. We also observe differences between the serotypes in the mean age in infant cases, informative about the interaction between waning immunity and disease for the different serotypes in infants. In addition, we show that the mean age of infant cases over time is informative about transmission in the whole population. Therefore, ongoing surveillance for dengue in infants could provide useful insights into dengue epidemiology, particularly after the introduction of a dengue vaccine targeting adults and older children
Making medicines baby size:the challenges in bridging the formulation gap in neonatal medicine
The development of age-Appropriate formulations should focus on dosage forms that can deliver variable yet accurate doses that are safe and acceptable to the child, are matched to his/her development and ability, and avoid medication errors. However, in the past decade, the medication needs of neonates have largely been neglected. The aim of this review is to expand on what differentiates the needs of preterm and term neonates from those of the older paediatric subsets, in terms of environment of care, ability to measure and administer the dose (from the perspective of the patient and carer, the routes of administration, the device and the product), neonatal bio-Pharmaceutics and regulatory challenges. This review offers insight into those challenges posed by the formulation of medicinal products for neonatal patients in order to support the development of clinically relevant products
Relative role of border restrictions, case finding and contact tracing in controlling SARS-CoV-2 in the presence of undetected transmission: a mathematical modelling study.
BACKGROUND: Understanding the overall effectiveness of non-pharmaceutical interventions to control the COVID-19 pandemic and reduce the burden of disease is crucial for future pandemic planning. However, quantifying the effectiveness of specific control measures and the extent of missed infections, in the absence of early large-scale serological surveys or random community testing, has remained challenging. METHODS: Combining data on notified local COVID-19 cases with known and unknown sources of infections in Singapore with a branching process model, we reconstructed the incidence of missed infections during the early phase of the wild-type SARS-CoV-2 and Delta variant transmission. We then estimated the relative effectiveness of border control measures, case finding and contact tracing when there was no or low vaccine coverage in the population. We compared the risk of ICU admission and death between the wild-type SARS-CoV-2 and the Delta variant in notified cases and all infections. RESULTS: We estimated strict border control measures were associated with 0.2 (95% credible intervals, CrI 0.04-0.8) missed imported infections per notified case between July and December 2020, a decline from around 1 missed imported infection per notified case in the early phases of the pandemic. Contact tracing was estimated to identify 78% (95% CrI 62-93%) of the secondary infections generated by notified cases before the partial lockdown in Apr 2020, but this declined to 63% (95% CrI 56-71%) during the lockdown and rebounded to 78% (95% CrI 58-94%) during reopening in Jul 2020. The contribution of contact tracing towards overall outbreak control also hinges on ability to find cases with unknown sources of infection: 42% (95% CrI 12-84%) of such cases were found prior to the lockdown; 10% (95% CrI 7-15%) during the lockdown; 47% (95% CrI 17-85%) during reopening, due to increased testing capacity and health-seeking behaviour. We estimated around 63% (95% CrI 49-78%) of the wild-type SARS-CoV-2 infections were undetected during 2020 and around 70% (95% CrI 49-91%) for the Delta variant in 2021. CONCLUSIONS: Combining models with case linkage data enables evaluation of the effectiveness of different components of outbreak control measures, and provides more reliable situational awareness when some cases are missed. Using such approaches for early identification of the weakest link in containment efforts could help policy makers to better redirect limited resources to strengthen outbreak control
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