Transparency in infectious disease research: meta-research survey of specialty journals.

BACKGROUND: Infectious diseases carry large global burdens and have implications for society at large. Therefore, reproducible, transparent research is extremely important. METHODS: We evaluated transparency indicators (code and data sharing, registration, conflict and funding disclosures) in the 5340 PubMed Central Open Access articles published in 2019 or 2021 in the 9 most-cited specialty journals in infectious disease using the text-mining R package, rtransparent. RESULTS: 5340 articles were evaluated (1860 published in 2019 and 3480 in 2021 (of which 1828 on COVID-19)). Text-mining identified code sharing in 98 (2%) articles, data sharing in 498 (9%), registration in 446 (8%), conflict of interest disclosures in 4209 (79%) and funding disclosures in 4866 (91%). There were substantial differences across the 9 journals: 1-9% for code sharing, 5-25% for data sharing, 1-31% for registration, 7-100% for conflicts of interest, and 65-100% for funding disclosures. Validation-corrected imputed estimates were 3%, 11%, 8%, 79% and 92%, respectively. There were no major differences between articles published in 2019 and non-COVID-19 articles in 2021. In 2021, non-COVID-19 articles had more data sharing (12%) than COVID-19 articles (4%). CONCLUSIONS: Data sharing, code sharing, and registration are very uncommon in infectious disease specialty journals. Increased transparency is required.

What Really Happened During the Massive SARS-CoV-2 Omicron Wave in China?

This Viewpoint discusses reports from China after its zero COVID-19 policy ended in December 2022.

Excess death estimates from multiverse analysis in 2009-2021.

Excess death estimates have great value in public health, but they can be sensitive to analytical choices. Here we propose a multiverse analysis approach that considers all possible different time periods for defining the reference baseline and a range of 1 to 4 years for the projected time period for which excess deaths are calculated. We used data from the Human Mortality Database on 33 countries with detailed age-stratified death information on an annual basis during the period 2009-2021. The use of different time periods for reference baseline led to large variability in the absolute magnitude of the exact excess death estimates. However, the relative ranking of different countries compared to others for specific years remained largely unaltered. The relative ranking of different years for the specific country was also largely independent of baseline. Averaging across all possible analyses, distinct time patterns were discerned across different countries. Countries had declines between 2009 and 2019, but the steepness of the decline varied markedly. There were also large differences across countries on whether the COVID-19 pandemic years 2020-2021 resulted in an increase of excess deaths and by how much. Consideration of longer projected time windows resulted in substantial shrinking of the excess deaths in many, but not all countries. Multiverse analysis of excess deaths over long periods of interest can offer an approach that better accounts for the uncertainty in estimating expected mortality patterns, comparative mortality trends across different countries, and the nature of observed mortality peaks.

Flaws and uncertainties in pandemic global excess death calculations.

Several teams have been publishing global estimates of excess deaths during the COVID-19 pandemic. Here, we examine potential flaws and underappreciated sources of uncertainty in global excess death calculations. Adjusting for changing population age structure is essential. Otherwise, excess deaths are markedly overestimated in countries with increasingly aging populations. Adjusting for changes in other high-risk indicators, such as residence in long-term facilities, may also make a difference. Death registration is highly incomplete in most countries; completeness corrections should allow for substantial uncertainty and consider that completeness may have changed during pandemic years. Excess death estimates have high sensitivity to modelling choice. Therefore different options should be considered and the full range of results should be shown for different choices of pre-pandemic reference periods and imposed models. Any post-modelling corrections in specific countries should be guided by pre-specified rules. Modelling of all-cause mortality (ACM) in countries that have ACM data and extrapolating these models to other countries is precarious; models may lack transportability. Existing global excess death estimates underestimate the overall uncertainty that is multiplicative across diverse sources of uncertainty. Informative excess death estimates require risk stratification, including age groups and ethnic/racial strata. Data to-date suggest a death deficit among children during the pandemic and marked socioeconomic differences in deaths, widening inequalities. Finally, causal explanations require great caution in disentangling SARS-CoV-2 deaths, indirect pandemic effects and effects from measures taken. We conclude that excess deaths have many uncertainties, but globally deaths from SARS-CoV-2 may be the minority of calculated excess deaths.

Prolific non-research authors in high impact scientific journals: meta-research study.

Journalistic papers published in high impact scientific journals can be very influential, especially in hot fields. This meta-research analysis aimed to evaluate the publication profiles, impact, and disclosures of conflicts of interest of non-research authors who had published > 200 Scopus-indexed papers in Nature, Science, PNAS, Cell, BMJ, Lancet, JAMA or New England Journal of Medicine. 154 prolific authors were identified, 148 of whom had published 67,825 papers in their main affiliated journal in a non-researcher capacity. Nature, Science, and BMJ have the lion's share of such authors. Scopus characterized 35% of the journalistic publications as full articles and another 11% as short surveys. 264 papers had received more than 100 citations. 40/41 most-cited papers in 2020-2022 were on hot COVID-19 topics. Of 25 massively prolific authors with > 700 publications in one of these journals, many were highly-cited (median citations 2273), almost all had published little or nothing in the Scopus-indexed literature other than in their main affiliated journal, and their influential writing covered diverse hot topics over the years. Of the 25, only 3 had a PhD degree in any subject matter, and 7 had a Master's degree in journalism. Only the BMJ offered conflicts of interest disclosures for prolific science writers in its website, but even then only 2 of the 25 massively prolific authors disclosed potential conflicts with some specificity. The practice of assigning so much power to non-researchers in shaping scientific discourse should be further debated and disclosures of potential conflicts of interest should be emphasized.

Analysis of fatality impact and seroprevalence surveys in a community sustaining a SARS-CoV-2 superspreading event.

There is an ongoing debate on the COVID-19 infection fatality rate (IFR) and the impact of COVID-19 on overall population mortality. Here, we addressed these issues in a community in Germany with a major superspreader event analyzing deaths over time and auditing death certificates in the community.18 deaths that occurred within the first six months of the pandemic had a positive test for SARS-CoV-2. Six out of 18 deaths had non-COVID-19 related causes of death (COD). Individuals with COVID-19 COD typically died of respiratory failure (75%) and tended to have fewer reported comorbidities (p = 0.029). Duration between first confirmed infection and death was negatively associated with COVID-19 being COD (p = 0.04). Repeated seroprevalence essays in a cross-sectional epidemiological study showed modest increases in seroprevalence over time, and substantial seroreversion (30%). IFR estimates accordingly varied depending on COVID-19 death attribution. Careful ascertainment of COVID-19 deaths is important in understanding the impact of the pandemic.

An umbrella review of systematic reviews on the impact of the COVID-19 pandemic on cancer prevention and management, and patient needs.

The relocation and reconstruction of health care resources and systems during the coronavirus disease 2019 (COVID-19) pandemic may have affected cancer care. An umbrella review was undertaken to summarize the findings from systematic reviews on impact of the COVID-19 pandemic on cancer treatment modification, delays, and cancellations; delays or cancellations in screening and diagnosis; psychosocial well-being, financial distress, and use of telemedicine as well as on other aspects of cancer care. Bibliographic databases were searched for relevant systematic reviews with or without meta-analysis published before November 29th, 2022. Abstract, full- text screening, and data extraction were performed by two independent reviewers. AMSTAR-2 was used for critical appraisal of included systematic reviews. Fifty-one systematic reviews were included in our analysis. Most reviews were based on observational studies judged to be at medium and high risk of bias. Only two reviews had high or moderate scores based on AMSTAR-2. Findings suggest treatment modifications in cancer care during the pandemic versus the pre-pandemic period were based on low level of evidence. Different degrees of delays and cancellations in cancer treatment, screening, and diagnosis were observed, with low- and- middle- income countries and countries that implemented lockdowns being disproportionally affected. A shift from in-person appointments to telemedicine use was observed, but utility of telemedicine, challenges in implementation and cost-effectiveness in cancer care were little explored. Evidence was consistent in suggesting psychosocial well-being of patients with cancer deteriorated, and cancer patients experienced financial distress, albeit results were in general not compared to pre-pandemic levels. Impact of cancer care disruption during the pandemic on cancer prognosis was little explored. In conclusion, substantial but heterogenous impact of COVID-19 pandemic on cancer care has been observed.

The onset of the COVID-19 pandemic disrupted many aspects of human life, not least healthcare. As resources were redistributed towards the crisis, social isolation rules also limited access to medical professionals. In particular, these measures may have affected many aspects of cancer care, such as early detection or treatment. Many studies have aimed to capture the impact of these changes, but most have been observational, with researchers recording events without trying to impose a controlled design. These investigations also often faced limitations such as small sample sizes, or only focusing on one aspect of cancer care. Systemic reviews, which synthetize and assess existing research on a topic, have helped to bypass these constraints. However, they are themselves not devoid of biases. Overall, a clear, unified picture of the impact of COVID-19 on cancer care is yet to emerge. In response, Muka et al. carried an umbrella analysis of 51 systematic reviews on this topic. They used a well-known critical appraisal tool to assess the methodological rigor of each of these studies, while also summarising their findings. This work aimed to capture many aspects of the patients' experience, from diagnosis to treatment and the financial, psychological, physical and social impact of the disease. The results confirmed that the pandemic had a substantial impact on cancer care, including delays in screening, diagnosis and treatment. Throughout this period cancer patients experienced increased rates of depression, post-traumatic stress and fear of their cancer progressing. The long-term consequences of these disruptions remain to be uncovered. However, Muka et al. also showed that, overall, these conclusions rely on low-quality studies which may have introduced unaccountable biases. In addition, their review highlights that most of the data currently available has been collected in high- and middle-income countries, with evidence lacking from regions of the world with more limited resources. In the short-term, these results indicate that interventions may be needed to mitigate the negative impact of the pandemic on cancer care; in the long-term, they also demonstrate the importance of rigorous systematic reviews in guiding decision making. By shining a light on the ripple effects of certain decisions about healthcare resources, this work could also help to shape the response to future pandemics.

Incidence, Risk, and Severity of SARS-CoV-2 Reinfections in Children and Adolescents Between March 2020 and July 2022 in Serbia.

Importance: During the COVID-19 pandemic, children and adolescents were massively infected worldwide. In 2022, reinfections became a main feature of the endemic phase of SARS-CoV-2, so it is important to understand the epidemiology and clinical impact of reinfections. Objective: To assess the incidence, risk, and severity of pediatric SARS-CoV-2 reinfection. Design, Setting, and Participants: This retrospective cohort study used epidemiologic data of documented SARS-CoV-2 infections from the surveillance database of the Institute for Public Health of Vojvodina. A total of 32 524 children and adolescents from Vojvodina, Serbia, with laboratory-confirmed SARS-CoV-2 infection between March 6, 2020, and April 30, 2022, were followed up for reinfection until July 31, 2022. Main Outcomes and Measures: Incidence rates of documented SARS-CoV-2 reinfection per 1000 person-months, estimated risk of documented reinfection 90 days or more after laboratory confirmation of primary infection, reinfection severity, hospitalizations, and deaths. Results: The study cohort included 32 524 children and adolescents with COVID-19 (mean [SD] age, 11.2 [4.9] years; 15 953 [49.1%] male), including 964 children (3.0%) who experienced documented reinfection. The incidence rate of documented reinfections was 3.2 (95% CI, 3.0-3.4) cases per 1000 person-months and was highest in adolescents aged 12 to 17 years (3.4; 95% CI, 3.2-3.7). Most reinfections (905 [93.9%]) were recorded in 2022. The cumulative reinfection risk was 1.3% at 6 months, 1.9% at 9 months, 4.0% at 12 months, 6.7% at 15 months, 7.2% at 18 months, and 7.9% after 21 months. Pediatric COVID-19 cases were generally mild. The proportion of severe clinical forms decreased from 14 (1.4%) in initial episodes to 3 (0.3%) in reinfections. Reinfected children were approximately 5 times less likely to have severe disease during reinfection compared with initial infection (McNemar odds ratio, 0.2; 95% CI, 0.0-0.8). Pediatric reinfections rarely led to hospitalization (0.5% vs 1.3% during primary infections), and none resulted in death. Conclusions and Relevance: This cohort study found that the SARS-CoV-2 reinfection risk remained substantially lower for children and adolescents compared with adults as of July 2022. Pediatric infections were mild, and reinfections were even milder than primary infections.

Estimates of COVID-19 deaths in Mainland China after abandoning zero COVID policy.

BACKGROUND: China witnessed a surge of Omicron infections after abandoning 'zero COVID' strategies on 7 December 2022. The authorities report very sparse deaths based on very restricted criteria, but massive deaths are speculated. METHODS: We aimed to estimate the COVID-19 fatalities in Mainland China until summer 2023 using the experiences of Hong Kong and of South Korea in 2022 as prototypes. Both these locations experienced massive Omicron waves after having had very few SARS-CoV-2 infections during 2020-2021. We estimated age-stratified infection fatality rates (IFRs) in Hong Kong and South Korea during 2022 and extrapolated to the population age structure of Mainland China. We also accounted separately for deaths of residents in long-term care facilities in both Hong Kong and South Korea. RESULTS: Infection fatality rate estimates in non-elderly strata were modestly higher in Hong Kong than South Korea and projected 987,455 and 619,549 maximal COVID-19 deaths respectively, if the entire China population were infected. Expected COVID-19 deaths in Mainland China until summer 2023 ranged from 49,962 to 691,219 assuming 25-70% of the non-elderly population being infected and variable protection of elderly (from none to three-quarter reduction in fatalities). The main analysis (45% of non-elderly population infected and fatality impact among elderly reduced by half) estimated 152,886-249,094 COVID-19 deaths until summer 2023. Large uncertainties exist regarding potential changes in dominant variant, health system strain and impact on non-COVID-19 deaths. CONCLUSIONS: The most critical factor that can affect total COVID-19 fatalities in China is the extent to which the elderly can be protected.

Aggressive measures, rising inequalities, and mass formation during the COVID-19 crisis: An overview and proposed way forward.

A series of aggressive restrictive measures were adopted around the world in 2020-2022 to attempt to prevent SARS-CoV-2 from spreading. However, it has become increasingly clear the most aggressive (lockdown) response strategies may involve negative side-effects such as a steep increase in poverty, hunger, and inequalities. Several economic, educational, and health repercussions have fallen disproportionately on children, students, young workers, and especially on groups with pre-existing inequalities such as low-income families, ethnic minorities, and women. This has led to a vicious cycle of rising inequalities and health issues. For example, educational and financial security decreased along with rising unemployment and loss of life purpose. Domestic violence surged due to dysfunctional families being forced to spend more time with each other. In the current narrative and scoping review, we describe macro-dynamics that are taking place because of aggressive public health policies and psychological tactics to influence public behavior, such as mass formation and crowd behavior. Coupled with the effect of inequalities, we describe how these factors can interact toward aggravating ripple effects. In light of evidence regarding the health, economic and social costs, that likely far outweigh potential benefits, the authors suggest that, first, where applicable, aggressive lockdown policies should be reversed and their re-adoption in the future should be avoided. If measures are needed, these should be non-disruptive. Second, it is important to assess dispassionately the damage done by aggressive measures and offer ways to alleviate the burden and long-term effects. Third, the structures in place that have led to counterproductive policies should be assessed and ways should be sought to optimize decision-making, such as counteracting groupthink and increasing the level of reflexivity. Finally, a package of scalable positive psychology interventions is suggested to counteract the damage done and improve humanity's prospects.

Does natural and hybrid immunity obviate the need for frequent vaccine boosters against SARS-CoV-2 in the endemic phase?

The coronavirus disease 2019 (COVID-19) pandemic has entered its endemic phase and we observe significantly declining infection fatality rates due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). On this background, it is crucial but challenging to define current and future vaccine policy in a population with a high immunity against SARS-CoV-2 conferred by previous infections and/or vaccinations. Vaccine policy must consider the magnitude of the risks conferred by new infection(s) with current and evolving SARS-CoV-2 variants, how these risks vary in different groups of individuals, how to balance these risks against the apparently small, but existent, risks of harms of vaccination, and the cost-benefit of different options. More evidence from randomized controlled trials and continuously accumulating national health data is required to inform shared decision-making with people who consider vaccination options. Vaccine policy makers should cautiously weight what vaccination schedules are needed, and refrain from urging frequent vaccine boosters unless supported by sufficient evidence.

Age-stratified infection fatality rate of COVID-19 in the non-elderly population.

The largest burden of COVID-19 is carried by the elderly, and persons living in nursing homes are particularly vulnerable. However, 94% of the global population is younger than 70 years and 86% is younger than 60 years. The objective of this study was to accurately estimate the infection fatality rate (IFR) of COVID-19 among non-elderly people in the absence of vaccination or prior infection. In systematic searches in SeroTracker and PubMed (protocol: https://osf.io/xvupr), we identified 40 eligible national seroprevalence studies covering 38 countries with pre-vaccination seroprevalence data. For 29 countries (24 high-income, 5 others), publicly available age-stratified COVID-19 death data and age-stratified seroprevalence information were available and were included in the primary analysis. The IFRs had a median of 0.034% (interquartile range (IQR) 0.013-0.056%) for the 0-59 years old population, and 0.095% (IQR 0.036-0.119%) for the 0-69 years old. The median IFR was 0.0003% at 0-19 years, 0.002% at 20-29 years, 0.011% at 30-39 years, 0.035% at 40-49 years, 0.123% at 50-59 years, and 0.506% at 60-69 years. IFR increases approximately 4 times every 10 years. Including data from another 9 countries with imputed age distribution of COVID-19 deaths yielded median IFR of 0.025-0.032% for 0-59 years and 0.063-0.082% for 0-69 years. Meta-regression analyses also suggested global IFR of 0.03% and 0.07%, respectively in these age groups. The current analysis suggests a much lower pre-vaccination IFR in non-elderly populations than previously suggested. Large differences did exist between countries and may reflect differences in comorbidities and other factors. These estimates provide a baseline from which to fathom further IFR declines with the widespread use of vaccination, prior infections, and evolution of new variants.

A meta-epidemiological assessment of transparency indicators of infectious disease models.

Mathematical models have become very influential, especially during the COVID-19 pandemic. Data and code sharing are indispensable for reproducing them, protocol registration may be useful sometimes, and declarations of conflicts of interest (COIs) and of funding are quintessential for transparency. Here, we evaluated these features in publications of infectious disease-related models and assessed whether there were differences before and during the COVID-19 pandemic and for COVID-19 models versus models for other diseases. We analysed all PubMed Central open access publications of infectious disease models published in 2019 and 2021 using previously validated text mining algorithms of transparency indicators. We evaluated 1338 articles: 216 from 2019 and 1122 from 2021 (of which 818 were on COVID-19); almost a six-fold increase in publications within the field. 511 (39.2%) were compartmental models, 337 (25.2%) were time series, 279 (20.9%) were spatiotemporal, 186 (13.9%) were agent-based and 25 (1.9%) contained multiple model types. 288 (21.5%) articles shared code, 332 (24.8%) shared data, 6 (0.4%) were registered, and 1197 (89.5%) and 1109 (82.9%) contained COI and funding statements, respectively. There was no major changes in transparency indicators between 2019 and 2021. COVID-19 articles were less likely to have funding statements and more likely to share code. Further validation was performed by manual assessment of 10% of the articles identified by text mining as fulfilling transparency indicators and of 10% of the articles lacking them. Correcting estimates for validation performance, 26.0% of papers shared code and 41.1% shared data. On manual assessment, 5/6 articles identified as registered had indeed been registered. Of articles containing COI and funding statements, 95.8% disclosed no conflict and 11.7% reported no funding. Transparency in infectious disease modelling is relatively low, especially for data and code sharing. This is concerning, considering the nature of this research and the heightened influence it has acquired.

Aggressive measures, rising inequalities, and mass formation during the COVID-19 crisis: An overview and proposed way forward

A series of aggressive restrictive measures were adopted around the world in 2020–2022 to attempt to prevent SARS-CoV-2 from spreading. However, it has become increasingly clear the most aggressive (lockdown) response strategies may involve negative side-effects such as a steep increase in poverty, hunger, and inequalities. Several economic, educational, and health repercussions have fallen disproportionately on children, students, young workers, and especially on groups with pre-existing inequalities such as low-income families, ethnic minorities, and women. This has led to a vicious cycle of rising inequalities and health issues. For example, educational and financial security decreased along with rising unemployment and loss of life purpose. Domestic violence surged due to dysfunctional families being forced to spend more time with each other. In the current narrative and scoping review, we describe macro-dynamics that are taking place because of aggressive public health policies and psychological tactics to influence public behavior, such as mass formation and crowd behavior. Coupled with the effect of inequalities, we describe how these factors can interact toward aggravating ripple effects. In light of evidence regarding the health, economic and social costs, that likely far outweigh potential benefits, the authors suggest that, first, where applicable, aggressive lockdown policies should be reversed and their re-adoption in the future should be avoided. If measures are needed, these should be non-disruptive. Second, it is important to assess dispassionately the damage done by aggressive measures and offer ways to alleviate the burden and long-term effects. Third, the structures in place that have led to counterproductive policies should be assessed and ways should be sought to optimize decision-making, such as counteracting groupthink and increasing the level of reflexivity. Finally, a package of scalable positive psychology interventions is suggested to counteract the damage done and improve humanity's prospects.

Estimating conditional vaccine effectiveness.

Vaccine effectiveness for COVID-19 is typically estimated for different outcomes that often are hierarchical in severity (e.g. any documented infection, symptomatic infection, hospitalization, death) and subsets of each other. Conditional effectiveness for a more severe outcome conditional on a less severe outcome is the protection offered against the severe outcome (e.g. death) among those who already sustained the less severe outcome (e.g. documented infection). The concept applies also to the protection offered by previous infection rather than vaccination. Formulas and a nomogram are provided here for calculating conditional effectiveness. Illustrative examples are presented from recent vaccine effectiveness studies, including situations where effectiveness for different outcomes changed at different pace over time. E(death | documented infection) is the percent decrease in the case fatality rate and E(death | infection) is the percent decrease in the infection fatality rate (IFR). Conditional effectiveness depends on many factors and should not be misinterpreted as a causal effect estimate. However, it may be used for better personalized communication of the benefits of vaccination, considering also IFR and epidemic activity in public health decision-making and communication.

The end of the COVID-19 pandemic.

There are no widely accepted, quantitative definitions for the end of a pandemic such as COVID-19. The end of the pandemic due to a new virus and the transition to endemicity may be defined based on a high proportion of the global population having some immunity from natural infection or vaccination. Other considerations include diminished death toll, diminished pressure on health systems, reduced actual and perceived personal risk, removal of restrictive measures and diminished public attention. A threshold of 70% of the global population having being vaccinated or infected was probably already reached in the second half of 2021. Endemicity may still show major spikes of infections and seasonality, but typically less clinical burden, although some locations are still hit more than others. Death toll and ICU occupancy figures are also consistent with a transition to endemicity by end 2021/early 2022. Personal risk of the vast majority of the global population was already very small by end 2021, but perceived risk may still be grossly overestimated. Restrictive measures of high stringency have persisted in many countries by early 2022. The gargantuan attention in news media, social media and even scientific circles should be tempered. Public health officials need to declare the end of the pandemic. Mid- and long-term consequences of epidemic waves and of adopted measures on health, society, economy, civilization and democracy may perpetuate a pandemic legacy long after the pandemic itself has ended.