Considerations for improving future pandemic responses DOI Open Access
Mikolaj Raszek, David E. Cowley,

Rubio-Casillas Alberto

et al.

Journal of Vaccines and Immunology, Journal Year: 2023, Volume and Issue: 10(1), P. 001 - 005

Published: Feb. 8, 2023

The COVID-19 pandemic of 2020 shook the world with its unprecedented scale, affecting over 700 million people and causing nearly 7 deaths globally. In response, rapid extraordinary measures were taken, including development distribution vaccines at an pace. However, speed magnitude response have raised questions about efficacy ethics certain measures. To address these concerns, we present a non-comprehensive list contentious issues that merit discussion investigation by scientific medical communities. These encompass public education, ethical considerations, legal implications, policy decisions, regulatory oversight, gaps in knowledge, concerns related to mass vaccination efforts. By examining topics, aim improve future crisis responses maintain trust participation programs. It is essential learn from successes shortcomings better prepare for health crises ensure safety well-being communities worldwide.

Language: Английский

The COVID-19 pandemic death toll in India: can we know better? DOI Creative Commons
Mamta Gupta, Chalapati Rao, Arun Kumar Yadav

et al.

BMJ Global Health, Journal Year: 2023, Volume and Issue: 8(8), P. e012818 - e012818

Published: Aug. 1, 2023

Language: Английский

Citations

2
Übersterblichkeit im Kontext der COVID-19-Pandemie in Deutschland DOI
Daniel Wollschläger,

Sebastian Fückel,

Maria Blettner

et al.

Deleted Journal, Journal Year: 2024, Volume and Issue: 18(2), P. 101 - 108

Published: Feb. 1, 2024

Internationale Vergleiche der Krankheitslast COVID-19-Pandemie verwenden oft die Übersterblichkeit als Maßstab – auch zur Bewertung Wirksamkeit von Interventionsmaßnahmen. Für Deutschland gab es dabei starke Diskrepanzen zwischen Übersterblichkeitsschätzungen verschiedener Studien. Da den Schätzungen unterschiedliche Modelle und Datenquellen zugrunde liegen, ist eine eingehende Analyse ihrer Methodik notwendig. Diese Studie schätzt mit verschiedenen Methoden in 01/2020 bis 10/2023. Ziel zum einen, zeitliche sowie räumliche Muster zu identifizieren, anderen, Auswirkungen unterschiedlicher methodischer Herangehensweisen ermitteln. Im Referenzzeitraum 2011 2019 wurde ein Regressionsmodell für Mortalitätsraten Bundesländer angepasst, auf seiner Basis wurden erwarteten monatlichen Sterbefälle im Indexzeitraum 2020 2023 berechnet. Das Modell berücksichtigt Bevölkerungsgröße -struktur, Temperatur, Influenzaaktivität sozioökonomische Deprivation. Die Differenz beobachteten Sterbefällen wird registrierten COVID-19-Sterbefällen verglichen. Als Alternativmodell nur geschlechts- altersspezifischen medianen je Kalendermonat geschätzt. COVID-19-attribuierte weisen klare auf. Ab Herbst 2021 Zahl COVID-19-attribuierten geringer Übersterblichkeit. höchste wiesen Sachsen, Sachsen-Anhalt Thüringen vereinfachte Übersterblichkeitsschätzung führt teils stark abweichenden Ergebnissen. Zeitliche darauf hin, dass einer Untererfassung COVID-19-Mortalität beruhen. Ohne Berücksichtigung starker Einflüsse das Sterbegeschehen kommt verzerrten

Citations

0
Responses to the letters on “Mortality in Norway and Sweden during the COVID-19 pandemic 2020 – 22: A comparative study.” DOI Creative Commons
Per‐Henrik Zahl, Rune Johansen,

Örjan Hemström

et al.

Journal of Infection and Public Health, Journal Year: 2024, Volume and Issue: 17(6), P. 1145 - 1146

Published: March 19, 2024

Language: Английский

Citations

0
Analyses of academician cohorts generate biased pandemic excess death estimates DOI Creative Commons
John P. A. Ioannidis

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: March 24, 2024

ABSTRACT Objective Death data from cohorts of academicians have been used to estimate pandemic excess deaths. We aimed evaluate the validity this approach. Study design and setting Data were analyzed living deceased member lists Mainland China, UK Greece academies; Nobel laureates (and US subset thereof). Samples early elected probed for unrecorded deaths; datasets overtly missing deaths excluded further analyses. Actuarial risks compared against general population in same country respective age strata. Relative incidence risk increases death active periods population-wide estimates country. Results Royal Society Academy Athens missed Pre-pandemic rates 4-12-fold lower Chinese Engineering (CAE) versus strata China population. A +158% relative increase was seen CAE during first 12-months wide viral spread. Both (+34% British Academy) decreases (-27% laureates) occurred (2020-22) pre-pandemic (2017-2019) years; point far known countries (+6% +14%, respectively). Published urban-dwelling selectively CAE, but not another academy (Chinese Sciences) with half rates. Conclusion Missingness, lack representativeness, large uncertainty, selective analysis reporting make rosters unreliable estimating

Language: Английский

Citations

0
Construction and validation of a covariate-based model for district-level estimation of excess deaths due to COVID-19 in India DOI Creative Commons
Anand Krishnan, Mahasweta Dubey, Rakesh Kumar

et al.

Journal of Global Health, Journal Year: 2024, Volume and Issue: 14

Published: May 30, 2024

Different statistical approaches for estimating excess deaths due to coronavirus disease 2019 (COVID-19) pandemic have led varying estimates. In this study, we developed and validated a covariate-based model (CBM) with imputation prediction of district-level in India.

Language: Английский

Citations

0
Differential risk of healthcare workers versus the general population during outbreak, war and pandemic crises DOI Creative Commons
John P. A. Ioannidis

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: May 31, 2024

ABSTRACT Healthcare workers may have different risk for severe outcomes compared with the general population during diverse crises. This paper introduces concept of healthcare worker versus hazard (HPH), an outcome interest in active they serve. HPH can be expressed relative (HPH(r)) and absolute difference (HPH(a)) metrics. Illustrative examples are drawn from infectious outbreaks, war, COVID-19 pandemic on death outcomes. extreme lethal outbreaks (HPH(r)=30 to 143, HPH(a)=8 91 per 1000 Ebola deaths 3 Western African countries 2013-5), modestly high terms very protracted, major armed conflicts (HPH(r)=1.38 HPH(a)=10.2 Syria 2011-2024). Conversely, had 8-12-fold lower than served excess (physicians USA) or Ontario, Finland), while Indonesia did not this advantage population. is susceptible data inaccuracies numbers at-risk populations interest. Importantly, inferences about misleading, if retired contaminate calculations – as case misleading early perceptions exaggerated professionals. offer useful insights assessment professionals, public, policy makers monitor planning interventions

Language: Английский

Citations

0
Analyses of academician cohorts generate biased pandemic excess death estimates DOI
John P. A. Ioannidis

Journal of Clinical Epidemiology, Journal Year: 2024, Volume and Issue: 173, P. 111437 - 111437

Published: June 24, 2024

Language: Английский

Citations

0
Understanding excess mortality in Europe during the COVID-19 pandemic DOI Creative Commons
Lasse S Vestergaard, Richard Pebody

The Lancet Regional Health - Europe, Journal Year: 2024, Volume and Issue: 45, P. 101053 - 101053

Published: Aug. 30, 2024

Language: Английский

Citations

0
Excess Deaths in South Korea During the COVID-19 Pandemic : 2020-2022 DOI Creative Commons

So-Jin Im,

Ji-Yeon Shin, Duk‐Hee Lee

et al.

Journal of Preventive Medicine and Public Health, Journal Year: 2024, Volume and Issue: 57(5), P. 480 - 489

Published: Sept. 21, 2024

Objectives: Excess deaths, an indicator that compares total mortality rates before and during a pandemic, offer comprehensive view of the pandemic’s impact. However, discrepancies may arise from variations in estimating expected deaths. This study aims to compare excess deaths Korea coronavirus disease 2019 pandemic using 3 methods analyze patterns most appropriate method.Methods: Expected 2020 2022 were estimated data 2015-2019 as reference years. estimation employed approaches: (1) simple average, (2) age-adjusted (3) linear regression. by age, gender, cause death also presented.Results: The number varied depending on method used, reaching its highest point with average lowest average. Age-adjusted regression, which accounts for both aging population declining rates, was considered appropriate. Using this model, at 0.3% 2020, 4.0% 2021, 20.7% 2022. surged among individuals their 20s throughout largely attributed rise self-harm suicide. Additionally, results indicated sharp increases associated “endocrine, nutritional, metabolic diseases” “symptoms, signs, abnormal clinical laboratory findings, not elsewhere classified.”Conclusions: Substantial evident based method, notable increase heightened young adults specific causes underscore key considerations future responses.

Language: Английский

Citations

0
Differential risk of healthcare workers versus the general population during outbreak, war and pandemic crises DOI
John P. A. Ioannidis

European Journal of Epidemiology, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 20, 2024

Language: Английский

Citations

0