Smart City Projects Against COVID-19: Quantitative Evidence from China
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ABSTRACT:
SUBMITTER: Yang S
PROVIDER: S-EPMC8015371 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Innovation is an important driving force for high-quality regional economic development. In recent years, the Chinese government has actively explored new ways to improve regional innovation level, and the construction of smart cities is regarded as an important measure to implement the innovation-driven development strategy. Based on the panel data of 287 prefecture-level cities in China from 2001 to 2019, this paper examined the impact of smart city construction on regional innovation. The research shows that: (i) The construction of smart city has significantly improved the level of regional innovation; (ii) Investment in science and technology and human capital level are important transmission paths for smart city construction to affect regional innovation; (iii) Compared with the central and western regions, the impact of smart city construction on regional innovation is more obvious in the eastern region. This study deepens the understanding of smart city construction, which has important policy significance for China to accelerate the construction of an innovative country and the healthy development of smart cities, and provides reference for other developing countries to promote smart city construction.
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Project description:In the year 2020, the word “pandemic” has become quite popular. A pandemic is a disease that spreads over a wide geographical region. The massive outbreak of coronavirus popularly known as COVID-19 has halted normal life worldwide. On 11th March 2020, the World Health Organization (WHO) quoted the COVID-19 outbreak as a “Pandemic”. The outbreak pattern differs widely across the globe based on the findings discovered so far; however, fever is a common and easily detectable symptom of COVID-19 and the new COVID strain. After the virus outbreak, thermal scanning is done using infrared thermometers in most public places to detect infected persons. It is time-consuming to track the body temperature of each person. Besides, close contact with infected persons can spread the virus from the infected persons to the individual performing the screening or vice-versa. In this research, we propose a device architecture capable of automatically detecting the coronavirus or new COVID strain from thermal images; the proposed architecture comprises a smart mask equipped with a thermal imaging system, which reduces human interactions. The thermal camera technology is integrated with the smart mask powered by the Internet of Things (IoT) to proactively monitor the screening procedure and obtain data based on real-time findings. Besides, the proposed system is fitted with facial recognition technology; therefore, it can also display personal information. It will automatically measure the temperature of each person who came into close contact with the infected humans or humans in public spaces, such as markets or offices. The new design is very useful in healthcare and could offer a solution to preventing the growth of the coronavirus. The presented work hasa key focus on the integration of advanced algorithms for the predictive analytics of parameters required for in-depth evaluations. The proposed work and the results are pretty effectual and performance cognizant for predictive analytics. The manuscript and associated research work integrate the IoT and Internet of Everything (IoE) based analytics with sensor technologies with real-time data so that the overall predictions will be more accurate and integrated with the health sector. Supplementary Information The online version contains supplementary material available at 10.1007/s12652-022-04395-7.
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Project description:What is known about this topic?Coronavirus disease 2019 (COVID-19) is widespread globally. In China, COVID-19 has been well controlled and has appeared only in importation-related cases. Local epidemics occur sporadically in China and have been contained relatively quickly.What is added by this report?Epidemiological investigation with genome sequence traceability analysis showed that the first case of COVID-19 in Nangong City acquired infection from a confirmed case from Shijiazhuang City; infection subsequently led to 76 local cases. All cases were associated with the index case, and most were located in Fenggong Street and did not spread outside of Nangong City. The main routes of transmission were family clusters, intra-unit transmission, and nosocomial transmission.What are the implications for public health practice?This study highlights new techniques for rapidly tracing cases and identifying COVID-19 transmission chains. The different epidemiological characteristics in Nangong City, from the earliest stages of the outbreak, suggest that allocation of health sources for prevention and treatment were reasonable. Preventing transmission within medical institutions and isolation facilities and strengthening management in the community should be priorities for COVID-19 control during a city lockdown.
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Project description:Phase 3 clinical trials and real-world effectiveness studies showed that China's two main inactivated COVID-19 vaccines are very effective against serious illness. In November 2021, an outbreak occurred in the Inner Mongolia Autonomous Region that provided an opportunity to assess the vaccine effectiveness (VE) of these inactivated vaccines against COVID-19 caused by the delta variant. We evaluated VE with a retrospective cohort study of close contacts of infected individuals, using a generalized linear model with binomial distribution and log-link function to estimate risk ratios (RR) and VE. A total of 8842 close contacts were studied. Compared with no vaccination and adjusted for age, presence of comorbidity, and time since last vaccination, full vaccination reduced symptomatic infection by 62%, pneumonia by 64% and severe COVID-19 by 90%; reductions associated with homologous booster doses were 83% for symptomatic infection, 92% for pneumonia and 100% for severe COVID-19. There was no significant decline in two-dose VE for any outcome for up to 325 days following the last dose. There were no differences by vaccine brand. Inactivated vaccines were effective against delta-variant illness, and were highly effective against pneumonia and severe COVID-19; VE was increased by booster doses.
| S-EPMC9961555 | biostudies-literature
Project description:Accumulating studies have suggested an important role of environmental factors (e.g. air pollutants) on the occurrence and development of coronavirus disease 2019 (COVID-19). Evidence concerning the relationship of greenness on COVID-19 is still limited. This study aimed to assess the association between greenness and COVID-19 incidence in 266 Chinese cities. A total of 12,377 confirmed COVID-19 cases were identified through February 29th, 2020. We used the average normalized difference vegetation index (NDVI) during January and February 2020 from MOD13A2 product, to represent the city-level greenness exposure. A generalized linear mixed-effects model was used to estimate the association between NDVI exposure and COVID-19 incidence using COVID-19 cases as the outcome. We evaluated whether the association was modified by population density, GDP per capita, and urbanization rate, and was mediated by air pollutants. We also performed a series of sensitivity analyses to discuss the robustness of our results. Per 0.1 unit increment in NDVI was negatively associated with COVID-19 incidence (IRR: 0.921, 95% CI: 0.898, 0.944) after adjustment for confounders. Associations with COVID-19 incidence were stronger in cities with lower population density, lower GDP per capita, and lower urbanization rate. We failed to detect any mediation effect of air pollutants on the association between NDVI and COVID-19 incidence. Sensitivity analyses also indicated consistent estimates. In conclusion, our study suggested a beneficial association between city-level greenness and COVID-19 incidence. We could not establish which mechanisms may explain this relationship.
| S-EPMC8812109 | biostudies-literature
Project description:This paper examines the impact of Covid-19 lockdowns on exports by Chinese cities. We use city-level export data at a monthly frequency from January 2018 through April 2020. Differences-in-differences estimates suggest cities in lockdown experienced a ceteris paribus 34 percentage points reduction in the year-on-year growth rate of exports. The lockdown impacted the intensive and extensive margin, with higher exit and lower new entry into foreign markets. The drop in exports was smaller in (i) coastal cities; (ii) cities with better-developed ICT infrastructure; and (iii) cities with a larger share of potential teleworkers. Time-sensitive and differentiated goods experienced a more pronounced decline in export growth. Global supply chain characteristics matter, with more upstream products and industries that had accumulated larger inventories experiencing a smaller decline in export growth. Also, products that relied more on imported (domestic) intermediates experienced a sharper (flatter) slowdown in export growth. The rapid recovery in cities' exports after lockdowns were lifted suggests the policy was cost-effective in terms of its effects on trade.
| S-EPMC8447424 | biostudies-literature
Project description:BackgroundInformation disclosure is a top priority for official responses to the COVID-19 pandemic. The timely and standardized information published by authorities as a response to the crisis can better inform the public and enable better preparations for the pandemic; however, there is limited evidence of any systematic analyses of the disclosed epidemic information. This in turn has important implications for risk communication.ObjectiveThis study aimed to describe and compare the officially released content regarding local epidemic situations as well as analyze the characteristics of information disclosure through local communication in major cities in China.MethodsThe 31 capital cities in mainland China were included in this city-level observational study. Data were retrieved from local municipalities and health commission websites as of March 18, 2020. A checklist was employed as a rapid qualitative assessment tool to analyze the information disclosure performance of each city. Descriptive analyses and data visualizations were produced to present and compare the comparative performances of the cities.ResultsIn total, 29 of 31 cities (93.5%) established specific COVID-19 webpages to disclose information. Among them, 12 of the city webpages were added to their corresponding municipal websites. A majority of the cities (21/31, 67.7%) published their first cases of infection in a timely manner on the actual day of confirmation. Regarding the information disclosures highlighted on the websites, news updates from local media or press briefings were the most prevalent (28/29, 96.6%), followed by epidemic surveillance (25/29, 86.2%), and advice for the public (25/29, 86.2%). Clarifications of misinformation and frequently asked questions were largely overlooked as only 2 cities provided this valuable information. The median daily update frequency of epidemic surveillance summaries was 1.2 times per day (IQR 1.0-1.3 times), and the majority of these summaries (18/25, 72.0%) also provided detailed information regarding confirmed cases. The reporting of key indicators in the epidemic surveillance summaries, as well as critical facts included in the confirmed case reports, varied substantially between cities. In general, the best performance in terms of timely reporting and the transparency of information disclosures were observed in the municipalities directly administered by the central government compared to the other cities.ConclusionsTimely and effective efforts to disclose information related to the COVID-19 epidemic have been made in major cities in China. Continued improvements to local authority reporting will contribute to more effective public communication and efficient public health research responses. The development of protocols and the standardization of epidemic message templates-as well as the use of uniform operating procedures to provide regular information updates-should be prioritized to ensure a coordinated national response.
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Project description:BackgroundCoronavirus disease 2019 (COVID-19) is an emerging infectious disease, which has caused numerous deaths and health problems worldwide. This study aims to examine the effects of airborne particulate matter (PM) pollution and population mobility on COVID-19 across China.MethodsWe obtained daily confirmed cases of COVID-19, air particulate matter (PM2.5, PM10), weather parameters such as ambient temperature (AT) and absolute humidity (AH), and population mobility scale index (MSI) in 63 cities of China on a daily basis (excluding Wuhan) from January 01 to March 02, 2020. Then, the Generalized additive models (GAM) with a quasi-Poisson distribution were fitted to estimate the effects of PM10, PM2.5 and MSI on daily confirmed COVID-19 cases.ResultsWe found each 1 unit increase in daily MSI was significantly positively associated with daily confirmed cases of COVID-19 in all lag days and the strongest estimated RR (1.21, 95% CIs:1.14 ~ 1.28) was observed at lag 014. In PM analysis, we found each 10 μg/m3 increase in the concentration of PM10 and PM2.5 was positively associated with the confirmed cases of COVID-19, and the estimated strongest RRs (both at lag 7) were 1.05 (95% CIs: 1.04, 1.07) and 1.06 (95% CIs: 1.04, 1.07), respectively. A similar trend was also found in all cumulative lag periods (from lag 01 to lag 014). The strongest effects for both PM10 and PM2.5 were at lag 014, and the RRs of each 10 μg/m3 increase were 1.18 (95% CIs:1.14, 1.22) and 1.23 (95% CIs:1.18, 1.29), respectively.ConclusionsPopulation mobility and airborne particulate matter may be associated with an increased risk of COVID-19 transmission.
| S-EPMC7576551 | biostudies-literature
Project description: Not available
| S-EPMC8393057 | biostudies-literature