The characteristics of and responses to the two COVID-19 outbreak waves in Hebei Province of China, January 2020 to February 2021

Cheng, Xiaomin; Li, Yifan; Zhang, Yali; Lu, Jiahai

doi:10.1017/s0950268821002089

Cited by 3 publications

(4 citation statements)

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“…Several studies have compared the characteristics of hospitalized patients during different waves of COVID-19 [ 15 , 24 , 25 , 26 , 27 ]. However, these studies were early in the pandemic and reported the first two waves using different variables and parameters.…”

Section: Discussionmentioning

confidence: 99%

“…In this cohort, about 98% of the infected hospitalized patients during the Omicron wave were nationals, compared to 77% during the first wave caused by the novel COVID-19 virus. Ethnicity has not been confirmed as a risk factor for negative outcomes in COVID-19 patients [ 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. The potential factors behind the differences in the first wave are the dense living conditions of the non-nationals and their lack to prompt access to medical care.…”

Section: Discussionmentioning

confidence: 99%

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The Impact of Demographic, Clinical Characteristics and the Various COVID-19 Variant Types on All-Cause Mortality: A Case-Series Retrospective Study

et al. 2022

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(1) Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly evolved into a pandemic affecting virtually every country in the world. We evaluated the demographic, clinical, laboratory, and all-cause mortality of moderate and severe COVID-19 patients admitted to a tertiary care hospital in Oman during the different COVID-19 waves and variant types. (2) Methods: A case-series retrospective study was carried out between 12 March 2020 and 30 June 2022. All adults over the age of 18 with laboratory-confirmed COVID-19 were enrolled. Analyses were performed using univariate and multivariate statistics. (3) Results: A total of 1462 confirmed cases enrolled with the mean age of the cohort was 55 ± 17 years with significant differences among the groups (p = 0.006). A total of 63% and 80% of the patients were males and citizens of Oman, respectively. Patients infected with the Alpha COVID-19 variant type were more likely to have acute respiratory distress syndrome (ARDS) (p < 0.001), stay longer in the hospital (p < 0.001), and get admitted to the intensive care unit (ICU) (p < 0.001). At the same time, those who had the Omicron COVID-19 type were more likely to have renal impairment (p < 0.001) and less likely to be associated with non-invasive ventilation (NIV) (p = 0.001) compared with other COVID-19 variant types. The Delta (adjusted odds ratio (aOR), 1.8; 95% confidence interval (CI): 1.22–2.66; p = 0.003) and Omicron (aOR, 1.88; 95% CI: 1.09–3.22; p = 0.022) COVID-19 variant types were associated with higher all-cause mortality when compared to the initial COVID-19 variant. Old age (aOR, 1.05; 95% CI: 1.04–1.06; p < 0.001), the presence of respiratory disease (aOR, 1.58; 95% CI: 1.02–2.44; p = 0.04), ICU admission (aOR, 3.41; 95% CI: 2.16–5.39; p < 0.001), lower eGFR (aOR, 1.61; 95% CI: 1.17–2.23; p = 0.004), and ARDS (aOR, 5.75; 95% CI: 3.69–8.98; p < 0.001) were also associated with higher mortality while NIV requirements were associated with lower odds of dying (aOR, 0.65; 95% CI: 0.46–0.91; p = 0.012). (4) Conclusions: Alpha and Delta variants were associated with a longer hospital stay, need for intensive care, mechanical ventilation, and increased mortality. Old age, cardiac renal dysfunction were commonly associated with Omicron variants. Large-scale national studies to further assess the risk factors for mortality related to COVID-19 waves are warranted.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The Impact of Demographic, Clinical Characteristics and the Various COVID-19 Variant Types on All-Cause Mortality: A Case-Series Retrospective Study

et al. 2022

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“…Although this was a small contagion chain, it illustrated the advantages of this kind of analysis. Cheng covered information on contagion chains in an analysis of the two COVID-19 outbreak waves in Hebei Province, China [10]. Likewise, Hu et al analyzed a chain of transmission involving 52 linked patients with COVID-19 in three separate hospitals in Wuhan [11].…”

Section: Related Workmentioning

confidence: 99%

Exploiting an Ontological Model to Study COVID-19 Contagion Chains in Sustainable Smart Cities

Martínez

Varén

et al. 2022

Information

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The COVID-19 pandemic has caused the deaths of millions of people around the world. The scientific community faces a tough struggle to reduce the effects of this pandemic. Several investigations dealing with different perspectives have been carried out. However, it is not easy to find studies focused on COVID-19 contagion chains. A deep analysis of contagion chains may contribute new findings that can be used to reduce the effects of COVID-19. For example, some interesting chains with specific behaviors could be identified and more in-depth analyses could be performed to investigate the reasons for such behaviors. To represent, validate and analyze the information of contagion chains, we adopted an ontological approach. Ontologies are artificial intelligence techniques that have become widely accepted solutions for the representation of knowledge and corresponding analyses. The semantic representation of information by means of ontologies enables the consistency of the information to be checked, as well as automatic reasoning to infer new knowledge. The ontology was implemented in Ontology Web Language (OWL), which is a formal language based on description logics. This approach could have a special impact on smart cities, which are characterized as using information to enhance the quality of basic services for citizens. In particular, health services could take advantage of this approach to reduce the effects of COVID-19.

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“…In late January 2021, there was a localized pandemic in Hebei Province, with more than 85% of infected patients coming from rural areas ( 8 ). Different from the early 2020 this time the pandemic broke out and spread widely in rural areas.…”

Section: Introductionmentioning

confidence: 99%

Roles and Challenges for Village Doctors in COVID-19 Pandemic Prevention and Control in Rural Beijing, China: A Qualitative Study

Zhao

Zhang

et al. 2022

Front. Public Health

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ObjectivesRural areas in China are more vulnerable to COVID-19 pandemic than urban areas, due to their far fewer health care resources. Village doctors, as rural grassroots health workers in China, have been actively engaged in the pandemic prevention and control. This study aims to describe the roles of village doctors in rural China, and the challenges they have faced during the prevention and control of the COVID-19 pandemic.SettingThis study was conducted in three towns in Huairou District, Beijing, China.DesignWe carried out semi-structured interviews with 75 key informants. All the interviews were audio-recorded and transcribed verbatim. We employed thematic analysis to define themes and sub-themes from the qualitative data.ResultsWe reported four themes. First, the village doctor guided the village committee to carry out decontamination, monitored home-isolated residents, and disseminated knowledge on prevention of the COVID-19 pandemic during the rural pandemic prevention and control. Second, they took pandemic prevention measures in village clinics, distributed pandemic prevention materials, and undertook pre-screening triage. Third, village doctors provided basic medical care, including treatment of common diseases as well as the purchase and delivery of medicines to villagers. Fourth, village doctors faced difficulties and challenges, such as inadequate medical skills, aging staff structure, and lack of pandemic prevention materials.ConclusionsDespite many difficulties and challenges, village doctors have actively participated in rural pandemic prevention and control, and made outstanding contributions to curbing spread of COVID-19 pandemic in rural areas. Village doctors provide basic health care while participating in various non-medical tasks.

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The characteristics of and responses to the two COVID-19 outbreak waves in Hebei Province of China, January 2020 to February 2021

Cited by 3 publications

References 21 publications

The Impact of Demographic, Clinical Characteristics and the Various COVID-19 Variant Types on All-Cause Mortality: A Case-Series Retrospective Study

The Impact of Demographic, Clinical Characteristics and the Various COVID-19 Variant Types on All-Cause Mortality: A Case-Series Retrospective Study

Exploiting an Ontological Model to Study COVID-19 Contagion Chains in Sustainable Smart Cities

Roles and Challenges for Village Doctors in COVID-19 Pandemic Prevention and Control in Rural Beijing, China: A Qualitative Study

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