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1.
PLoS One ; 16(7): e0255229, 2021.
Article in English | MEDLINE | ID: covidwho-1327982

ABSTRACT

This study is to assess the influences of climate, socio-economic determinants, and spatial distance on the confirmed cases and deaths in the raise phase of COVID-19 in China. The positive confirmed cases and deaths of COVID-19 over the population size of 100,000 over every 5 consecutive days (the CCOPSPTT and DOPSPTT for short, respectively) covered from 25th January to 29th February, 2020 in five city types (i.e., small-, medium-, large-, very large- and super large-sized cities), along with the data of climate, socio-economic determinants, spatial distance of the target city to Wuhan city (DW, for short), and spatial distance between the target city and their local province capital city (DLPC, for short) were collected from the official websites of China. Then the above-mentioned influencing factors on CCOPSPTT and DOPSPTT were analyzed separately in Hubei and other provinces. The results showed that CCOPSPTT and DOPSPTT were significantly different among five city types outside Hubei province (p < 0.05), but not obviously different in Hubei province (p > 0.05). The CCOPSPTT had significant correlation with socio-economic determinants (GDP and population), DW, climate and time after the outbreak of COVID-19 outside Hubei province (p < 0.05), while was only significantly related with GDP in Hubei province (p < 0.05). The DOPSPTT showed significant correlation with socio-economic determinants, DW, time and CCOPSPTT outside Hubei province (p < 0.05), while was significantly correlated with GDP and CCOPSPTT in Hubei province (p < 0.05). Compared with other factors, socio-economic determinants have the largest relative contribution to variance of CCOPSPTT in all studied cities (> 78%). The difference of DOPSPTT among cities was mainly affected by CCOPSPTT. Our results showed that influences of city types on the confirmed cases and death differed between Hubei and other provinces. Socio-economic determinants, especially GDP, have higher impact on the change of COVID-19 transmission compared with other factors.


Subject(s)
COVID-19/epidemiology , Climate , Socioeconomic Factors , COVID-19/mortality , China/epidemiology , Cities/epidemiology , Disease Outbreaks , Humans , Spatial Analysis
2.
Front Pharmacol ; 11: 560209, 2020.
Article in English | MEDLINE | ID: covidwho-843841

ABSTRACT

OBJECTIVE: Since the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan City, China, coronavirus disease 2019 (COVID-19) has become a global pandemic. However, no special therapeutic drugs have been identified for COVID-19. The aim of this study was to search for drugs to effectively treat COVID-19. MATERIALS AND METHODS: We conducted a retrospective cohort study with a total of 162 adult inpatients (≥18 years old) from Ruijin Hospital (Shanghai, China) and Tongji Hospital (Wuhan, China) between January 27, 2020, and March 10, 2020. The enrolled COVID-19 patients were first divided into the Lianhuaqingwen (LHQW) monotherapy group and the LHQW + Arbidol combination therapy group. Then, these two groups were further classified into moderate and severe groups according to the clinical classification of COVID-19. RESULTS: The early combined usage of LHQW and Arbidol can significantly accelerate the recovery of patients with moderate COVID-19 by reducing the time to conversion to nucleic acid negativity, the time to chest CT improvement, and the length of hospital stay. However, no benefit was observed in severe COVID-19 patients treated with the combination of LHQW + Arbidol. In this study, both Arbidol and LHQW were well tolerated without serious drug-associated adverse events. CONCLUSION: The early combined usage of LHQW and Arbidol may accelerate recovery and improve the prognosis of patients with moderate COVID-19.

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