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BackgroundSerological surveys have been the gold standard to estimate the numbers of SARS-CoV-2 infections, epidemic dynamics, and disease severity throughout the pandemic. Serological assays are known to have decaying sensitivity with time that can strongly bias their results, but there is a lack of guidelines to account for this phenomenon. AimAssess the sensitivity decay of seroassays for detecting infections, its dependence on assay characteristics, and provide a simple tool to correct for this phenomenon. MethodsWe performed a systematic review and meta-analysis of SARS-CoV-2 serology studies. We included studies testing previously diagnosed individuals, without any SARS-CoV-2 vaccines, and excluded studies of cohorts highly unrepresentative of the general population (e.g. hospitalised patients). ResultsOf the 488 screened studies, 76 studies reporting on 50 different seroassays were included in the analysis. Sensitivity decay depends strongly on the antigen and the analytic technique used by the assay, with average sensitivities ranging between 26% and 98% at 6 months after infection, depending on assay characteristics. We find that a third of the included assays depart significantly from manufacturer specifications after 6 months. ConclusionsSeroassay sensitivity decay depends on assay characteristics, and for some types of assays it can make manufacturer specifications highly unreliable. We provide a tool to correct for this phenomenon, and to assess the risk of decay for a given assay. This can be used to design better serosurveys, and quantify systematic biases in the existing serology literature.
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BackgroundRetraction is the final safeguard against research error/misconduct. In principle, retraction exists to prevent serious issues identified in published research through post-publication review. Our study investigated the citing of clinical research papers retracted during the COVID-19 pandemic. MethodsWe used the Retraction Watch database extracted as of 27/01/2022 to identify retracted COVID-19 papers and the Google Scholar citation function to gather a dataset of citations of retracted clinical research. We reviewed key aspects of the citing research. ResultsIn total, the Retraction Watch database included 212 entries for retracted COVID-19 papers. Of these, 53 papers were clinical. There were a total of 1,141 citations of retracted papers, with 105 errors, leaving 1,036 citations to analyze. The majority (86%) of citations were not critical. The majority (80%) of papers citing retracted research were published after the retraction date. ConclusionsThe citation of retracted and withdrawn COVID-19 clinical studies is common, and rarely critical. Most researchers who cite retracted research do not identify that the paper is retracted, even when submitting long after the paper has been withdrawn. This has serious implications for the reliability of published research and the academic literature, which need to be addressed.
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IntroductionThe infection-fatality rate (IFR) of COVID-19 has been carefully measured and analyzed in high-income countries, whereas there has been no systematic analysis of age-specific seroprevalence or IFR for developing countries. MethodsWe systematically reviewed the literature to identify all COVID-19 serology studies in developing countries that were conducted using population representative samples collected by early 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 analyzed 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. ResultsSeroprevalence in many developing country locations was markedly higher than in high-income countries. In most locations, 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 2x 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. ConclusionThe 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 accelerate the provision of vaccine doses to populations in developing countries. Key Points- Age-stratified infection fatality rates (IFRs) of COVID-19 in developing countries are about twice those of high-income countries. - Seroprevalence (as measured by antibodies against SARS-CoV-2) is broadly similar across age cohorts, underscoring the challenges of protecting older age groups in developing countries. - Population IFR in developing countries is similar to that of high-income countries, because differences in population age structure are roughly offset by disparities in healthcare access as well as elevated infection rates among older age cohorts. - These results underscore the urgency of disseminating vaccines throughout the developing world.
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Objectives: To determine how participants perceived telehealth consults in comparison to traditional in-person visits, and to investigate whether people believe that telehealth services would be useful beyond the pandemic. Design: A national cross-sectional community survey. Participants: Australian adults aged 18 years and over (n=1369). Main outcome measures: Telehealth experiences. Results: Of the 596 telehealth users, the majority of respondents (62%) rated their telehealth experience as "just as good" or "better" than a traditional in-person medical appointment. On average, respondents perceived that telehealth would be moderately to very useful for medical appointments after the COVID-19 pandemic is over (M=3.67 out of 5, SD=1.1). Being male (p=0.007), having a history of both depression and anxiety (p=0.037), or lower patient activation (individuals' willingness to take on the role of managing their health/healthcare) (p=0.037) were associated with a poorer telehealth experience. Six overarching themes were identified from free-text responses of why telehealth experience was poorer than a traditional in-person medical appointment: communication is not as effective; limitations with technology; issues with obtaining prescriptions and pathology; reduced confidence in doctor; additional burden for complex care; and inability to be physically examined. Conclusions: Telehealth appointments were reported to be comparable to traditional in-person medical appointments by most of our sample. Telehealth should continue to be offered as a mode of healthcare delivery while the pandemic continues and may be worthwhile beyond the pandemic.
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Structured AbstractO_ST_ABSObjectiveC_ST_ABSDetermine age-specific infection fatality rates for COVID-19 to inform public health policies and communications that help protect vulnerable age groups. MethodsStudies of COVID-19 prevalence were collected by conducting an online search of published articles, preprints, and government reports. A total of 111 studies were reviewed in depth and screened. Studies of 33 locations satisfied the inclusion criteria and were included in the meta-analysis. Age-specific IFRs were computed using the prevalence data in conjunction with reported fatalities four weeks after the midpoint date of the study, reflecting typical lags in fatalities and reporting. Meta-regression procedures in Stata were used to analyze IFR by age. ResultsOur analysis finds a exponential relationship between age and IFR for COVID-19. The estimated age-specific IFRs are very low for children and younger adults but increase progressively to 0.4% at age 55, 1.3% at age 65, 4.2% at age 75, and 14% at age 85. We find that differences in the age structure of the population and the age-specific prevalence of COVID-19 explain nearly 90% of the geographical variation in population IFR. DiscussionThese results indicate that COVID-19 is hazardous not only for the elderly but also for middle-aged adults, for whom the infection fatality rate is two orders of magnitude greater than the annualized risk of a fatal automobile accident and far more dangerous than seasonal influenza. Moreover, the overall IFR for COVID-19 should not be viewed as a fixed parameter but as intrinsically linked to the age-specific pattern of infections. Consequently, public health measures to mitigate infections in older adults could substantially decrease total deaths.
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An important unknown during the 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 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. MethodsPubmed, Medline, SSRN, and Medrxiv were searched using a set of terms and Boolean operators on 25/04/2020 and re-searched 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 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. ResultsAfter 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). ConclusionBased on a systematic review and meta-analysis of published evidence on COVID-19 until May, 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 the true 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 policy-making on this front. Key messages- COVID-19 infection-fatality rate (IFR) is an important statistic for policy about the disease - Published estimates vary, with a true fatality rate hard to calculate - Systematically reviewing the literature and meta-analyzing the results shows an IFR of 0.68% (0.53-0.82%)
