Diabetes and Virtual Care: How COVID-19 impacted on a digital transformation

Mobile phone applications and other virtual care interventions such as telehealth present both a big problem and a big opportunity for improving the health of people with chronic diseases, in particular type 2 diabetes. These diseases have become more common in recent years, and with this increasing prevalence despite prevention efforts one thing is clear: we must adapt our healthcare methods to meet this growing pressure. The advent of COVID-19 has only made this problem worse, as people’s care has been fragmented and fractured during the outbreak of a global pandemic. The downside to apps and other virtual care interventions is that people don’t use them for very long. There’s emerging research showing that people often stop using their mobile applications, even the health ones, very quickly. We aren’t sure exactly how quickly this happens, and it seems to vary a lot between apps and health conditions, but it might be as many as 98% of people dropping out of app-based interventions within days of signing up. While other interventions such as telehealth may have better retention, even these have had challenges in getting people to use them long-term. Needless to say, a health intervention that lasts less than a week is not going to be as effective as one that people stick to for months or years

A systematic review and meta-analysis of published research data on COVID-19 infection fatality rates

An important unknown during the coronavirus disease-2019 (COVID-19) pandemic has been the infection fatality rate (IFR). This differs from the case fatality rate (CFR) as an estimate of the number of deaths and as a proportion of the total number of cases, including those who are mild and asymptomatic. While the CFR is extremely valuable for experts, IFR is increasingly being called for by policy makers and the lay public as an estimate of the overall mortality from COVID-19. Methods: Pubmed, Medline, SSRN, and Medrxiv were searched using a set of terms and Boolean operators on 25/04/2020 and re-searched on 14/05/2020, 21/05/2020 and 16/06/2020. Articles were screened for inclusion by both authors. Meta-analysis was performed in Stata 15.1 by using the metan command, based on IFR and confidence intervals extracted from each study. Google/Google Scholar was used to assess the grey literature relating to government reports. Results: After exclusions, there were 24 estimates of IFR included in the final meta-analysis, from a wide range of countries, published between February and June 2020. The meta-analysis demonstrated a point estimate of IFR of 0.68% (0.53%–0.82%) with high heterogeneity (p < 0.001). Conclusion: Based on a systematic review and meta-analysis of published evidence on COVID-19 until July 2020, the IFR of the disease across populations is 0.68% (0.53%–0.82%). However, due to very high heterogeneity in the meta-analysis, it is difficult to know if this represents a completely unbiased point estimate. It is likely that, due to age and perhaps underlying comorbidities in the population, different places will experience different IFRs due to the disease. Given issues with mortality recording, it is also likely that this represents an underestimate of the true IFR figure. More research looking at age-stratified IFR is urgently needed to inform policymaking on this front

Assessing the Burden of COVID-19 in Developing Countries: Systematic Review, Meta-Analysis, and Public Policy Implications

Abstract Introduction The infection fatality rate (IFR) of COVID-19 has been carefully measured and analysed in high-income countries, whereas there has been no systematic analysis of age-specific seroprevalence or IFR for developing countries. Methods We systematically reviewed the literature to identify all COVID-19 serology studies in developing countries that were conducted using representative samples collected by February 2021. For each of the antibody assays used in these serology studies, we identified data on assay characteristics, including the extent of seroreversion over time. We analysed the serology data using a Bayesian model that incorporates conventional sampling uncertainty as well as uncertainties about assay sensitivity and specificity. We then calculated IFRs using individual case reports or aggregated public health updates, including age-specific estimates whenever feasible. Results In most locations in developing countries, seroprevalence among older adults was similar to that of younger age cohorts, underscoring the limited capacity that these nations have to protect older age groups. Age-specific IFRs were roughly 2 times higher than in high-income countries. The median value of the population IFR was about 0.5%, similar to that of high-income countries, because disparities in healthcare access were roughly offset by differences in population age structure. Conclusion The burden of COVID-19 is far higher in developing countries than in high-income countries, reflecting a combination of elevated transmission to middle-aged and older adults as well as limited access to adequate healthcare. These results underscore the critical need to ensure medical equity to populations in developing countries through provision of vaccine doses and effective medications

Efficacy of telephone health coaching integration with standard multidisciplinary care for adults with obesity attending a weight management service : a pilot study

Australia has one of the highest prevalences of obesity in the developed world with recognised gaps in patient access to obesity services. This non-randomised before and after study investigated the health benefits and patient acceptability of integrating the Get Healthy Service, a state-funded telephone-delivered coaching service in Australia, as an adjunct to multidisciplinary care for adults attending a public obesity service. Forty-one participants received multidisciplinary care alone while 39 participants were subsequently allocated to receive adjunctive treatment with the Get Healthy Service. Weight, body mass index, glycosylated haemoglobin, measurement of hepatic steatosis and liver enzymes were collected at baseline and 6 months. Participant evaluation was obtained post intervention. Statistically significant reductions from baseline were achieved for both control and intervention with respect to weight (−6.7 ± 2.2 kg, p = 0.01; −12.6 ± 3.2, p = 0.002), body mass index (−2.3 ± 0.8, p = 0.01; −4.8 ± 1.2 kg/m2 , p = 0.002) and glycosylated haemoglobin (−0.2 ± 0.2%, p = 0.2 (NS); −0.7 ± 0.2%, p = 0.02), respectively. There were no significant differences in steatosis or liver enzymes or in outcomes between control and intervention cohorts. A high level of patient acceptability was reported. Integrating telephone-delivered coaching provided non-inferior care and high levels of patient satisfaction. Telephone coaching aligned with the principles of an obesity service should be trialled to improve patient access to obesity interventions

A hierarchical Bayesian model for estimating age-specific COVID-19 infection fatality rates in developing countries

The COVID-19 infection fatality rate (IFR) is the proportion of individuals infected with SARS-CoV-2 who subsequently die. As COVID-19 disproportionately affects older individuals, age-specific IFR estimates are imperative to facilitate comparisons of the impact of COVID-19 between locations and prioritize distribution of scare resources. However, there lacks a coherent method to synthesize available data to create estimates of IFR and seroprevalence that vary continuously with age and adequately reflect uncertainties inherent in the underlying data. In this paper we introduce a novel Bayesian hierarchical model to estimate IFR as a continuous function of age that acknowledges heterogeneity in population age structure across locations and accounts for uncertainty in the estimates due to seroprevalence sampling variability and the imperfect serology test assays. Our approach simultaneously models test assay characteristic, serology, and death data, where the serology and death data are often available only for binned age groups. Information is shared across locations through hierarchical modeling to improve estimation of the parameters with limited data. Modeling data from 26 developing country locations during the first year of the COVID-19 pandemic, we found seroprevalence did not change dramatically with age, and the IFR at age 60 was above the high-income country benchmark for most locations

Protocol for the development of a tool (INSPECT-SR) to identify problematic randomised controlled trials in systematic reviews of health interventions

This research is funded by the NIHR Research for Patient Benefit programme (NIHR203568). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.Peer reviewe

Causal and associational language in observational health research: a systematic evaluation

We estimated the degree to which language used in the high profile medical/public health/epidemiology literature implied causality using language linking exposures to outcomes and action recommendations; examined disconnects between language and recommendations; identified the most common linking phrases; and estimated how strongly linking phrases imply causality. We searched and screened for 1,170 articles from 18 high-profile journals (65 per journal) published from 2010-2019. Based on written framing and systematic guidance, three reviewers rated the degree of causality implied in abstracts and full text for exposure/outcome linking language and action recommendations. Reviewers rated the causal implication of exposure/outcome linking language as None (no causal implication) in 13.8%, Weak 34.2%, Moderate 33.2%, and Strong 18.7% of abstracts. The implied causality of action recommendations was higher than the implied causality of linking sentences for 44.5% or commensurate for 40.3% of articles. The most common linking word in abstracts was “associate” (45.7%). Reviewer’s ratings of linking word roots were highly heterogeneous; over half of reviewers rated “association” as having at least some causal implication. This research undercuts the assumption that avoiding “causal” words leads to clarity of interpretation in medical research

A systematic review and meta-analysis of published research data on COVID-19 infection fatality rates

2020 An important unknown during the coronavirus disease-2019 (COVID-19) pandemic has been the infection fatality rate (IFR). This differs from the case fatality rate (CFR) as an estimate of the number of deaths and as a proportion of the total number of cases, including those who are mild and asymptomatic. While the CFR is extremely valuable for experts, IFR is increasingly being called for by policy makers and the lay public as an estimate of the overall mortality from COVID-19. Methods: Pubmed, Medline, SSRN, and Medrxiv were searched using a set of terms and Boolean operators on 25/04/2020 and re-searched on 14/05/2020, 21/05/2020 and 16/06/2020. Articles were screened for inclusion by both authors. Meta-analysis was performed in Stata 15.1 by using the metan command, based on IFR and confidence intervals extracted from each study. Google/Google Scholar was used to assess the grey literature relating to government reports. Results: After exclusions, there were 24 estimates of IFR included in the final meta-analysis, from a wide range of countries, published between February and June 2020. The meta-analysis demonstrated a point estimate of IFR of 0.68% (0.53%-0.82%) with high heterogeneity (p \u3c 0.001). Conclusion: Based on a systematic review and meta-analysis of published evidence on COVID-19 until July 2020, the IFR of the disease across populations is 0.68% (0.53%-0.82%). However, due to very high heterogeneity in the meta-analysis, it is difficult to know if this represents a completely unbiased point estimate. It is likely that, due to age and perhaps underlying comorbidities in the population, different places will experience different IFRs due to the disease. Given issues with mortality recording, it is also likely that this represents an underestimate of the true IFR figure. More research looking at age-stratified IFR is urgently needed to inform policymaking on this front