The Post-COVID-19 Era: Interdisciplinary Demands of Contagion Surveillance Mass Spectrometry for Future Pandemics

Giri, Chaitanya; Cleaves, H. James; Meringer, Markus; Chandru, Kuhan

doi:10.3390/su13147614

Cited by 7 publications

(4 citation statements)

References 76 publications

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“…(As with climate change and transmissions, the relationship between containment policies and transmissions can be complex, and stricter containment may not always imply fewer transmissions [ 150 , 151 ].) Finally, new technologies will always renew the potential to improve early surveillance methods [ 152 - 154 ].…”

Section: Discussionmentioning

confidence: 99%

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Latin America and the Caribbean: Longitudinal Trend Analysis

Post,

Wu,

Soetikno

et al. 2024

JMIR Public Health Surveill

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Background In May 2020, the World Health Organization (WHO) declared Latin America and the Caribbean (LAC) the epicenter of the COVID-19 pandemic, with over 40% of worldwide COVID-19–related deaths at the time. This high disease burden was a result of the unique circumstances in LAC. Objective This study aimed to (1) measure whether the pandemic was expanding or contracting in LAC when the WHO declared the end of COVID-19 as a public health emergency of international concern on May 5, 2023; (2) use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history; and (3) provide, with a focus on prevention policies, a historical context for the course of the pandemic in the region. Methods In addition to updates of traditional surveillance data and dynamic panel estimates from the original study, we used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern (VOCs). We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Additionally, we conducted a 1-sided t test for whether the regional weekly speed (rate of novel COVID-19 transmission) was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the period from August 2020 to May 2023. Results The speed of pandemic spread for the region had remained below the outbreak threshold for 6 months by the time of the WHO declaration. Acceleration and jerk were also low and stable. Although the 1- and 7-day persistence coefficients remained statistically significant for the 120-day period ending on the week of May 5, 2023, the coefficients were relatively modest in magnitude (0.457 and 0.491, respectively). Furthermore, the shift parameters for either of the 2 most recent weeks around May 5, 2023, did not indicate any change in this clustering effect of cases on future cases. From December 2021 onward, Omicron was the predominant VOC in sequenced viral samples. The rolling t test of speed=10 became entirely insignificant from January 2023 onward. Conclusions Although COVID-19 continues to circulate in LAC, surveillance data suggest COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. However, the region experienced a high COVID-19 burden in the early stages of the pandemic, and prevention policies should be an immediate focus in future pandemics. Ahead of vaccination development, these policies can include widespread testing of individuals and an epidemiological task force with a contact-tracing system.

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Section: Discussionmentioning

confidence: 99%

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Latin America and the Caribbean: Longitudinal Trend Analysis

Post,

Wu,

Soetikno

et al. 2024

JMIR Public Health Surveill

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show abstract

“…So, it is not a matter of asking how exactly to get there, but to start walking. Even if favoriting MS-based quantitative strategies is a small step for overall sustainability, it is the start of a long journey toward a sustainable future, and it may turn out to be an unparalleled notch-up for some future pandemics [83,84]. At the moment, considerable efforts are invested in the development of sustainable nanosystems as front-end technology for MS [85].…”

Section: Sustainable Ms-based Quantitative Strategiesmentioning

confidence: 99%

Mass Spectrometry-Based Techniques Towards OMICS 2.0

Šoša¹

2023

Preprint

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The literature was scoped to help place mass spectrometric (MS) platforms in the spotlight of the life sciences, as a tool of OMICS and OMICS 2.0 technologies. Moreover, today’s appliances are so handy, that they literally place a whole lab on a single chip. Methods of OMICS (and the most recently developed term OMICS 2.0) are tackled, having in mind their aptness for educational purposes, as well as their feasibility. This same topic was highlighted in many reviews that have been periodically published. The author’s initial interest was the forensic application of MS, but since these interests changed, terms such as “biosensors” were also examined, so the review included means of discovery of efficient biomarkers and clinical therapeutic targets. Aside from simply reviewing the research status and the future perspectives, this article tackles terms such as Society 5.0 and OMICS 2.0. However, within the framework of this review, physical chemistry, bioinformatics, or specific software solutions were not specifically studied. Since the topic of generating permanent collections of digital content for retrospective analysis was also reviewed, the need for loads of data – cloud storage was discussed in the context of MS. These large quantities of data are easier to operate with if generated by MS, rather than by any other commercially available assay. In this manner, the review has strengthened an in-depth understanding of the applications of MS.

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“…In atmospheric mass spectrometry, machine learning is already applied to some, but not all, of the steps outlined in Figure 4. Machine learning models have been trained on different atmospheric mass spectrometry data (like AMS, PTRMS, ESI-mass spectrometry, single particle mass spectrometry, and inductively coupled plasma mass spectrometry) for aerosol classification and source apportionment and [82][83][84][85][86][87][88][89][90] prediction of composition [91][92][93][94] and properties. [95,96] Moreover, a recent review highlighted the role of machine learning in data pre-processing during measurements of volatile organic compounds.…”

Section: Compound Identification With Mass Spectrometrymentioning

confidence: 99%

Data‐Driven Compound Identification in Atmospheric Mass Spectrometry

Sandström,

Rissanen,

Rousu

et al. 2023

Advanced Science

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Aerosol particles found in the atmosphere affect the climate and worsen air quality. To mitigate these adverse impacts, aerosol particle formation and aerosol chemistry in the atmosphere need to be better mapped out and understood. Currently, mass spectrometry is the single most important analytical technique in atmospheric chemistry and is used to track and identify compounds and processes. Large amounts of data are collected in each measurement of current time‐of‐flight and orbitrap mass spectrometers using modern rapid data acquisition practices. However, compound identification remains a major bottleneck during data analysis due to lacking reference libraries and analysis tools. Data‐driven compound identification approaches could alleviate the problem, yet remain rare to non‐existent in atmospheric science. In this perspective, the authors review the current state of data‐driven compound identification with mass spectrometry in atmospheric science and discuss current challenges and possible future steps toward a digital era for atmospheric mass spectrometry.

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The Post-COVID-19 Era: Interdisciplinary Demands of Contagion Surveillance Mass Spectrometry for Future Pandemics

Cited by 7 publications

References 76 publications

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Latin America and the Caribbean: Longitudinal Trend Analysis

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Latin America and the Caribbean: Longitudinal Trend Analysis

Mass Spectrometry-Based Techniques Towards OMICS 2.0

Data‐Driven Compound Identification in Atmospheric Mass Spectrometry

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