The impact of the Omicron epidemic on the health behavior in Cape Town, South Africa

Lin, Xiaoqing; Lv, Li; Chen, Yan; Chen, He-Dan; Zhang, Meixian; Tung, Tao‐Hsin; Zhu, Jiansheng

doi:10.1016/j.onehlt.2022.100395

Cited by 3 publications

(4 citation statements)

References 20 publications

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“…Most countries worldwide implemented comprehensive prevention and control measures in response to the pandemic, some countries followed dynamic zero-COVID strategy to eliminate the virus, while many countries adopted mitigation measures to reduce the number of infections [ 2 , 3 ]. However, SARS-CoV-2 has been evolving in an unanticipated way, which has made prevention and control extremely difficult [ 4 ]. Several waves of epidemic resurgences have been caused by the lifting of non-pharmaceutical interventions, the emergence of new variants, and the waning effectiveness of vaccination [ 5 , 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Retrospective Modeling of the Omicron Epidemic in Shanghai, China: Exploring the Timing and Performance of Control Measures

et al. 2023

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Background: In late February 2022, the Omicron epidemic swept through Shanghai, and the Shanghai government responded to it by adhering to a dynamic zero-COVID strategy. In this study, we conducted a retrospective analysis of the Omicron epidemic in Shanghai to explore the timing and performance of control measures based on the eventual size and duration of the outbreak. Methods: We constructed an age-structured and vaccination-stratified SEPASHRD model by considering populations that had been detected or controlled before symptom onset. In addition, we retrospectively modeled the epidemic in Shanghai from 26 February 2022 to 31 May 2022 across four periods defined by events and interventions, on the basis of officially reported confirmed (58,084) and asymptomatic (591,346) cases. Results: According to our model fitting, there were about 785,123 positive infections, of which about 57,585 positive infections were symptomatic infections. Our counterfactual assessment found that precise control by grid management was not so effective and that citywide static management was still needed. Universal and enforced control by citywide static management contained 87.65% and 96.29% of transmission opportunities, respectively. The number of daily new and cumulative infections could be significantly reduced if we implemented static management in advance. Moreover, if static management was implemented in the first 14 days of the epidemic, the number of daily new infections would be less than 10. Conclusions: The above research suggests that dynamic zeroing can only be achieved when strict prevention and control measures are implemented as early as possible. In addition, a lot of preparation is still needed if China wants to change its strategy in the future.

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Section: Introductionmentioning

confidence: 99%

Retrospective Modeling of the Omicron Epidemic in Shanghai, China: Exploring the Timing and Performance of Control Measures

et al. 2023

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“…This obvious emotional change which was demonstrated as Happy (p≤0.001), Sadness (p≤0.001), Anger (p≤0.001), Surprise (p≤0.001), and Fear (p≤0.001) emotional classes could also be attributed to a large media hype and awareness created by health authorities with the South Africa's National Coronavirus Command Council (NCCC), especially, when they announced that the country will retain its lockdown to the lowest five-tier system of restrictions 62 due to the increase in the number of COVID-19 cases at that time. This announcement was made in the couple two weeks of the Omicron outbreak, precisely, December 16, 2021, because of its high infectious rate as suggested by the health authorities 12,14,62 .…”

Section: Ethical Considerationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Omicron is said to be highly transmissible than Delta variant 14 . For example, from the earlier reports of the variant, within a period of two weeks the Omicron cases in South Africa rose from 300 a day to 3000 a day 14,15 . This may be attributed to be the reason the virus was said to be the most dominant variant in a short while in most countries 16,17 .…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Omicron Variant in Vaccine Uptake in South Africa

Ogbuokiri

Ahmadi

Tripathi

et al. 2023

Preprint

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The first report of the Omicron variant triggered a lot of emotions towards vaccination in South Africa. These emotions are mostly expressed on social media such as Twitter. The result could weaken the confidence level of users even before they are vaccinated. Identifying these emotions and how they change before and during the Omicron variant can help, in understanding the dynamics in citizens' behaviour, towards vaccination for health policy-making. In this study, 23,000 vaccine-related Twitter posts were collected in South Africa, from 1 October 2021 to 15 January 2022 using Natural Language Processing techniques. The emotional classification of Twitter posts and their associated intensities were achieved using the Text2emotion pre-trained model. The results were validated using Naive Bayes with an accuracy of 76%, Logistic Regression (91%), Support Vector Machines (84%), Decision Tree (82%), and K-Nearest Neighbours (72%). The number of tweets significantly positively correlated with the increase in vaccination across all South African provinces (Corr<=0.532, P<=0.003) except Northern Cape province. The emotional intensities for vaccine-related posts showed a strong association with the increase in vaccination during Omicron (P<0.04) in Eastern Cape, Gauteng, Limpopo, and North West provinces than other provinces. The comparison of the intensities of the emotional classes differed across provinces before and during Omicron. The result of this research showed that social media data can be used to complement existing data, in understanding and predicting the dynamics in citizens' emotional behaviour towards vaccination, during a new COVID-19 variant or future outbreaks. The result could also inform health policy in planning, control, and management of provinces identified with vaccine hesitancy. It can also serve as a template or reference for related future academic research.

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Analysis of Potential Risk Factors of COVID-19 Based on Variants: Omicron, Delta, and Alpha

Kannan,

Muppiri,

Reid

2023

Preprint

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The coronavirus disease 2019 (COVID-19) pandemic has changed which affects the risk of COVID-19 infection for specific subgroups. We focused on the subgroups based on the factors (sex, age, and vaccination) and COVID-19 strains (Alpha, Delta, and Omicron). Past studies focused on analyzing these factors based on one geographic region or one COVID-19 strain. Therefore, there is a need to understand these factors’ association with risk of COVID-19 infection through analyzing data from various geographic regions and strains. The association between COVID-19 strains and the factors was assessed through chi-square test and odds ratio tests. Sex, vaccination, age had a significant association with testing positive for the COVID-19 strains of interest in most geographies. The biggest difference was unvaccinated individuals have 3.14 higher odds of getting Alpha than vaccinated individuals in Canada. These findings provide insights into the groups that are more susceptible to contracting specific strains of COVID-19.SummaryThis manuscript offers a broad examination of key factors that may impact the risk of COVID-19 infection across various geographic regions. Results provide evidence about potential risk factors for COVID-19 infection around the world for certain sub-groups as COVID-19 mutates.

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The impact of the Omicron epidemic on the health behavior in Cape Town, South Africa

Cited by 3 publications

References 20 publications

Retrospective Modeling of the Omicron Epidemic in Shanghai, China: Exploring the Timing and Performance of Control Measures

Retrospective Modeling of the Omicron Epidemic in Shanghai, China: Exploring the Timing and Performance of Control Measures

The Impact of Omicron Variant in Vaccine Uptake in South Africa

Analysis of Potential Risk Factors of COVID-19 Based on Variants: Omicron, Delta, and Alpha

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