Realising rural economic transformation: Pathways to inclusive and sustainable prosperity in post-COVID-19 Asia

Mallawaarachchi, Thilak; Rahut, Dil Bahadur

doi:10.1016/j.eap.2023.01.009

Cited by 10 publications

(6 citation statements)

References 20 publications

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“…The slow recovery from the pandemic is attributed to the lack of reliable public health infrastructure, war, widespread poverty, and export-focused economies in the region [72,[100][101][102]. As of May 2023, long-term financial and economic repercussions are still evident [103].…”

Section: Resultsmentioning

confidence: 99%

Surveillance Metrics and History of the COVID-19 Pandemic in Central Asia: Updated Epidemiological Assessment

Lundberg,

Ozer,

et al. 2024

JMIR Public Health Surveill

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Background: This study updates the COVID-19 pandemic surveillance in Central Asia we first conducted in 2020 by providing two additional years of data for the region.Objective: First, we aim to measure whether there was an expansion or contraction in the pandemic in Central Asia when the World Health Organization (WHO) declared the end of the public health emergency for the COVID-19 pandemic on May 5, 2023. Second, we 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. Third, we aim to provide historical context for the course of the pandemic in Central Asia.Methods: Traditional static surveillance, including absolute numbers and rates of COVID-19 transmissions and deaths, and enhanced dynamic surveillance indicators, including speed, acceleration, jerk, and persistence, were used to measure shifts in the pandemic. To identify the appearance and duration of variants of concern, we used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID). We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a onesided t-test for whether regional weekly speed was greater than an outbreak threshold of ten. We ran the test iteratively with six months of data across the sample period.Results: Speed for the region had remained below the outbreak threshold for seven months by the time of the WHO declaration. Acceleration and jerk were also low and stable. While the 1-and 7-day persistence coefficients remained statistically significant, the coefficients were relatively small in magnitude (0.125 and 0.347, respectively). Furthermore, the shift parameters for either of the two most recent weeks around May 5, 2023, were both significant and negative, meaning the clustering effect of new COVID-19 cases became even smaller in the two weeks around the WHO declaration. From December of 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t-test of speed equal to ten became entirely insignificant for the first time in March of 2023. Conclusions:While COVID-19 continues to circulate in Central Asia, the rate of transmission had remained well below the threshold of an outbreak for seven months ahead of the WHO declaration. COVID-19 is endemic in the region and no longer

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Section: Resultsmentioning

confidence: 99%

Surveillance Metrics and History of the COVID-19 Pandemic in Central Asia: Updated Epidemiological Assessment

Lundberg,

Ozer,

et al. 2024

JMIR Public Health Surveill

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“…A 2019 World Economic Forum research found that investing in digital technology may start a positive feedback loop that boosts creativity, economic development, and technical preparedness. However, as long-term impacts on economic development may not be captured by short-term changes, it is crucial to assess the effectiveness of digital investment over time [23]- [25].…”

Section: The Value Of Investing In Digitalmentioning

confidence: 99%

Quantifying the Impact of Digital Transformation on Economic Growth: A Longitudinal Analysis

Lukmanova,

Saini,

Parkash Singh

et al. 2024

BIO Web Conf.

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This study examined how digital transformation and economic development interact in a longitudinal analysis that went from 2016 to 2020. A persistent commitment to digitalization was shown by the statistics, which showed a constant growth in digital transformation measures including investment, adoption rates, talent development, and preparedness. Indicators of economic development, including GDP growth, employment, productivity, and corporate investments, all showed positive trends at the same time. The percentages of the calculated digital transformation impact indicated an increasing effect over time. An examination conducted over a period of five years highlighted the overall effect of digital transformation and emphasized its ongoing contribution to economic development. Policymakers, companies, and academics should take note of this research's important implications, which underscore the pivotal role that digital transformation plays in determining economic advancement in the digital era.

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“…Following the COVID-19 outbreak, numerous studies have been conducted to investigate the impact of the pandemic on households (see Padhan and Prabheesh 2021 ; Rathnayaka et al 2023 , for a review). These studies have examined safety, health (Kansiime et al, 2021 ; Lecoutere et al, 2023 ) and the economic effects on family businesses (Baker et al, 2020 ) or start-up creation (Albert et al, 2023 ) in both advanced (Jung et al, 2023 ) and emerging economies (Mallawaarachchi and Rahut, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

Statistical learning models to measure the impact of COVID-19 on financial fragility

Agosto,

Giudici,

Tanda

2024

Front. Artif. Intell.

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This paper investigates the effects of the economic shock produced by the COVID-19 outbreak and diffusion on households'. Through a survey administered to Italian households, without loss of generality, we investigate changes in financial and economic decisions and the households' ability to cope with daily purchases, repay their debt obligations and face unexpected expenses. The paper also applies a statistical learning model through a synthetic indicator for the financial vulnerability of households, integrating the relevant information on the financial literacy and education of the surveyed individuals.

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Realising rural economic transformation: Pathways to inclusive and sustainable prosperity in post-COVID-19 Asia

Cited by 10 publications

References 20 publications

Surveillance Metrics and History of the COVID-19 Pandemic in Central Asia: Updated Epidemiological Assessment

Surveillance Metrics and History of the COVID-19 Pandemic in Central Asia: Updated Epidemiological Assessment

Quantifying the Impact of Digital Transformation on Economic Growth: A Longitudinal Analysis

Statistical learning models to measure the impact of COVID-19 on financial fragility

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