Estimated global public health and economic impact of COVID-19 vaccines in the pre-omicron era using real-world empirical data

Yang, Jingyan; Vaghela, Shailja; Yarnoff, Benjamin; Boisvilliers, Solène de; Fusco, Manuela Di; Wiemken, Timothy; Kyaw, Moe H.; Nguyen, Jennifer

doi:10.1080/14760584.2023.2157817

Cited by 15 publications

(7 citation statements)

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“…An image resizing process was performed to reduce the image size to 100 by 100 pixels. • Convolution layers: All convolution layers were employed with a kernel size of (3,3). In our study, the input shape of the CXR image was (100, 100, 3), where 100 denotes the width and height, while 3 indicates the input image's three color channels (RGB).…”

Section: The Structure Of the Covid-convnet Modelmentioning

confidence: 99%

“…Because the outbreak surged across the globe and infected millions of individuals, the WHO declared it a worldwide pandemic, and the number of affected people continues to rise daily. As of 22 September 2022, over 610 million coronavirus cases worldwide, as well as 6.5 million deaths, had been reported [3]. The COVID-19 virus primarily spreads through respiratory droplets when an infected person coughs, sneezes, talks, or breathes [4].…”

Section: Introductionmentioning

confidence: 99%

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COVID-ConvNet: A Convolutional Neural Network Classifier for Diagnosing COVID-19 Infection

Alablani

Alenazi

2023

Diagnostics

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The novel coronavirus (COVID-19) pandemic still has a significant impact on the worldwide population’s health and well-being. Effective patient screening, including radiological examination employing chest radiography as one of the main screening modalities, is an important step in the battle against the disease. Indeed, the earliest studies on COVID-19 found that patients infected with COVID-19 present with characteristic anomalies in chest radiography. In this paper, we introduce COVID-ConvNet, a deep convolutional neural network (DCNN) design suitable for detecting COVID-19 symptoms from chest X-ray (CXR) scans. The proposed deep learning (DL) model was trained and evaluated using 21,165 CXR images from the COVID-19 Database, a publicly available dataset. The experimental results demonstrate that our COVID-ConvNet model has a high prediction accuracy at 97.43% and outperforms recent related works by up to 5.9% in terms of prediction accuracy.

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Section: The Structure Of the Covid-convnet Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

COVID-ConvNet: A Convolutional Neural Network Classifier for Diagnosing COVID-19 Infection

Alablani

Alenazi

2023

Diagnostics

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“…Parents in rural areas believe vaccine-preventable diseases (VPD) are not severe enough to justify vaccination [ 14 ]. The emergence of the COVID-19 pandemic has placed an extraordinary burden on global healthcare infrastructures, potentially impacting the continuity of standard immunization efforts [ 15 , 16 , 17 , 18 , 19 , 20 ]. Disruptions in the supply chain of vaccines, the redirection of healthcare resources and personnel to COVID-19 management [ 21 ], the logistic challenges of COVID-19 immunization [ 22 ], and heightened public reluctance to visit medical facilities due to infection risk have all been implicated in the observed decrease in vaccination rates [ 23 , 24 , 25 , 26 , 27 , 28 ].…”

Section: Introductionmentioning

confidence: 99%

Has COVID-19 Affected DTP3 Vaccination in the Americas?

Aguinaga-Ontoso,

Guillén-Aguinaga,

Guillén-Aguinaga

et al. 2024

Vaccines

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Background: In the Americas, deaths by diseases avoidable with vaccines are a significant contributor to child mortality. An essential means of reducing this is through broad vaccine coverage. The COVID-19 pandemic has posed a potential disruption to vaccine coverage due to its effects on the healthcare system. Objectives: this study aims to evaluate the impact of the COVID-19 pandemic on DTP3 vaccination coverage in the Americas, investigating trends from 2012 to 2022 to identify significant changes, regional disparities, and the overall effect of the pandemic on progress towards global immunization targets. Methods: This study used the coverage data for the third dose of the diphtheria, tetanus, and pertussis vaccine (DTP3) pulled from UNICEF databases spanning 2012 to 2022. We conducted a Joinpoint regression to identify points of significant trend changes. The annual percentage change (APC) and 95% confidence intervals (95% CIs) were calculated for America and its regions. We also used segmented regression analysis. Using the Chi-square test, we compared DTP3 vaccination coverage for each country between 2019 and 2022. Results: Overall, America saw a decrease in vaccine coverage during this period, with an APC of −1.4 (95% CI −1.8; −1.0). This trend varied across regions. In North America, the decrease was negligible (−0.1% APC). South America showed the steepest decrease, with an APC of −2.5%. Central America also declined, with an APC of −1.3%. Our findings suggest a concerning trend of declining DTP-vaccination rates in the Americas, exacerbated in certain regions, in the wake of the COVID-19 pandemic. The absolute decrease in vaccine coverage in the Americas was −4% between 2019 and 2022, with the most important drop being in Central America (−7%). However, six countries reported increased vaccination rates post-COVID-19, led by Brazil, with a 7% increase. Conversely, twenty-two countries registered a decline in DTP3 vaccine coverage, with the average decrease being −7.37%. This decline poses an important challenge to achieving the WHO’s target of 90% coverage for the third dose of DTP by 2030, as evidenced by the reduction in the number of countries meeting this target from 2019 to 2022. Conclusions: The COVID-19 pandemic has impacted vaccine coverage in America, leading to a decrease, especially across Central America.

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“…Developing many COVID-19 vaccines across multiple technology platforms in under a year and manufacturing and distributing billions of doses of them while leaving swathes of the world’s population without access in the face of a pandemic is both an incredible achievement [ 1 , 2 , 3 ] and a terrible indictment of our current health innovation model and of global collaboration and solidarity. An estimated 31% of the world’s population is yet to receive even one dose of a coronavirus vaccine and there are wide disparities [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

The Future of Epidemic and Pandemic Vaccines to Serve Global Public Health Needs

et al. 2023

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This Review initiates a wide-ranging discussion over 2023 by selecting and exploring core themes to be investigated more deeply in papers submitted to the Vaccines Special Issue on the “Future of Epidemic and Pandemic Vaccines to Serve Global Public Health Needs”. To tackle the SARS-CoV-2 pandemic, an acceleration of vaccine development across different technology platforms resulted in the emergency use authorization of multiple vaccines in less than a year. Despite this record speed, many limitations surfaced including unequal access to products and technologies, regulatory hurdles, restrictions on the flow of intellectual property needed to develop and manufacture vaccines, clinical trials challenges, development of vaccines that did not curtail or prevent transmission, unsustainable strategies for dealing with variants, and the distorted allocation of funding to favour dominant companies in affluent countries. Key to future epidemic and pandemic responses will be sustainable, global-public-health-driven vaccine development and manufacturing based on equitable access to platform technologies, decentralised and localised innovation, and multiple developers and manufacturers, especially in low- and middle-income countries (LMICs). There is talk of flexible, modular pandemic preparedness, of technology access pools based on non-exclusive global licensing agreements in exchange for fair compensation, of WHO-supported vaccine technology transfer hubs and spokes, and of the creation of vaccine prototypes ready for phase I/II trials, etc. However, all these concepts face extraordinary challenges shaped by current commercial incentives, the unwillingness of pharmaceutical companies and governments to share intellectual property and know-how, the precariousness of building capacity based solely on COVID-19 vaccines, the focus on large-scale manufacturing capacity rather than small-scale rapid-response innovation to stop outbreaks when and where they occur, and the inability of many resource-limited countries to afford next-generation vaccines for their national vaccine programmes. Once the current high subsidies are gone and interest has waned, sustaining vaccine innovation and manufacturing capability in interpandemic periods will require equitable access to vaccine innovation and manufacturing capabilities in all regions of the world based on many vaccines, not just “pandemic vaccines”. Public and philanthropic investments will need to leverage enforceable commitments to share vaccines and critical technology so that countries everywhere can establish and scale up vaccine development and manufacturing capability. This will only happen if we question all prior assumptions and learn the lessons offered by the current pandemic. We invite submissions to the special issue, which we hope will help guide the world towards a global vaccine research, development, and manufacturing ecosystem that better balances and integrates scientific, clinical trial, regulatory, and commercial interests and puts global public health needs first.

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Estimated global public health and economic impact of COVID-19 vaccines in the pre-omicron era using real-world empirical data

Cited by 15 publications

References 50 publications

COVID-ConvNet: A Convolutional Neural Network Classifier for Diagnosing COVID-19 Infection

COVID-ConvNet: A Convolutional Neural Network Classifier for Diagnosing COVID-19 Infection

Has COVID-19 Affected DTP3 Vaccination in the Americas?

The Future of Epidemic and Pandemic Vaccines to Serve Global Public Health Needs

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