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1.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315884

ABSTRACT

Background: The Coronavirus Disease 2019 (COVID-19) epidemic has been largely controlled in China, to the point where case fatality rate (CFR) data can be comprehensively evaluated. Methods: Data on confirmed patients, with a final outcome reported as of 29 March 2020, were obtained from official websites and other internet sources. The hospitalized CFR (HCFR) was estimated, epidemiological features described, and risk factors for a fatal outcome identified. Findings: The overall CFR in China was estimated to be 4.6% (95% CI 4.5%-4.8%). It increased with age and was higher in males than females. The highest CFR observed was in male patients ≥70 years old. Although the outcome of infection is generally worse for males, this adverse effect from male sex decreased as people get old. Differential age/sex CFR patterns across geographical regions were found: the age effect on CFR was greater in other provinces outside Hubei than in Wuhan. An effect of longer interval from symptom onset to admission was only observed outside Hubei, not in Wuhan. By performing multivariate analysis and survival analysis, the higher CFR was associated with older age, and male sex. Only in regions outside Hubei, longer interval from symptom onset to admission, were associated with higher CFR. Interpretation: This up-to-date and comprehensive picture of COVID-19 CFR and its drivers will help healthcare givers target limited medical resources to patients with high risk of fatality.

2.
BMC Public Health ; 21(1): 2239, 2021 12 09.
Article in English | MEDLINE | ID: covidwho-1566517

ABSTRACT

BACKGROUND: COVID-19 patients with long incubation period were reported in clinical practice and tracing of close contacts, but their epidemiological or clinical features remained vague. METHODS: We analyzed 11,425 COVID-19 cases reported between January-August, 2020 in China. The accelerated failure time model, Logistic and modified Poisson regression models were used to investigate the determinants of prolonged incubation period, as well as their association with clinical severity and transmissibility, respectively. RESULT: Among local cases, 268 (10.2%) had a prolonged incubation period of > 14 days, which was more frequently seen among elderly patients, those residing in South China, with disease onset after Level I response measures administration, or being exposed in public places. Patients with prolonged incubation period had lower risk of severe illness (ORadjusted = 0.386, 95% CI: 0.203-0.677). A reduced transmissibility was observed for the primary patients with prolonged incubation period (50.4, 95% CI: 32.3-78.6%) than those with an incubation period of ≤14 days. CONCLUSIONS: The study provides evidence supporting a prolonged incubation period that exceeded 2 weeks in over 10% for COVID-19. Longer monitoring periods than 14 days for quarantine or persons potentially exposed to SARS-CoV-2 should be justified in extreme cases, especially for those elderly.


Subject(s)
COVID-19 , Epidemics , Infectious Disease Incubation Period , COVID-19/epidemiology , China/epidemiology , Humans , Quarantine , SARS-CoV-2
3.
Nat Commun ; 12(1): 5026, 2021 08 18.
Article in English | MEDLINE | ID: covidwho-1363491

ABSTRACT

Nationwide prospective surveillance of all-age patients with acute respiratory infections was conducted in China between 2009‒2019. Here we report the etiological and epidemiological features of the 231,107 eligible patients enrolled in this analysis. Children <5 years old and school-age children have the highest viral positivity rate (46.9%) and bacterial positivity rate (30.9%). Influenza virus, respiratory syncytial virus and human rhinovirus are the three leading viral pathogens with proportions of 28.5%, 16.8% and 16.7%, and Streptococcus pneumoniae, Mycoplasma pneumoniae and Klebsiella pneumoniae are the three leading bacterial pathogens (29.9%, 18.6% and 15.8%). Negative interactions between viruses and positive interactions between viral and bacterial pathogens are common. A Join-Point analysis reveals the age-specific positivity rate and how this varied for individual pathogens. These data indicate that differential priorities for diagnosis, prevention and control should be highlighted in terms of acute respiratory tract infection patients' demography, geographic locations and season of illness in China.


Subject(s)
Bacteria/isolation & purification , Bacterial Infections/microbiology , Respiratory Tract Infections/microbiology , Respiratory Tract Infections/virology , Virus Diseases/virology , Viruses/isolation & purification , Adolescent , Adult , Bacteria/classification , Bacteria/genetics , Bacterial Infections/epidemiology , Child , Child, Preschool , China/epidemiology , Female , Humans , Infant , Male , Prospective Studies , Respiratory Tract Infections/epidemiology , Seasons , Virus Diseases/epidemiology , Viruses/classification , Viruses/genetics , Young Adult
4.
BMC Infect Dis ; 21(1): 481, 2021 May 26.
Article in English | MEDLINE | ID: covidwho-1244909

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) epidemic has been largely controlled in China, to the point where case fatality rate (CFR) data can be comprehensively evaluated. METHODS: Data on confirmed patients, with a final outcome reported as of 29 March 2020, were obtained from official websites and other internet sources. The hospitalized CFR (HCFR) was estimated, epidemiological features described, and risk factors for a fatal outcome identified. RESULTS: The overall HCFR in China was estimated to be 4.6% (95% CI 4.5-4.8%, P < 0.001). It increased with age and was higher in males than females. Although the highest HCFR observed was in male patients ≥70 years old, the relative risks for death outcome by sex varied across age groups, and the greatest HCFR risk ratio for males vs. females was shown in the age group of 50-60 years, higher than age groups of 60-70 and ≥ 70 years. Differential age/sex HCFR patterns across geographical regions were found: the age effect on HCFR was greater in other provinces outside Hubei than in Wuhan. An effect of longer interval from symptom onset to admission was only observed outside Hubei, not in Wuhan. By performing multivariate analysis and survival analysis, the higher HCFR was associated with older age (both P < 0.001), and male sex (both P < 0.001). Only in regions outside Hubei, longer interval from symptom onset to admission, were associated with higher HCFR. CONCLUSIONS: This up-to-date and comprehensive picture of COVID-19 HCFR and its drivers will help healthcare givers target limited medical resources to patients with high risk of fatality.


Subject(s)
COVID-19/epidemiology , COVID-19/mortality , Hospital Mortality , Hospitalization , SARS-CoV-2 , Adult , Age Factors , Aged , China/epidemiology , Female , Humans , Male , Middle Aged , Risk Factors , Sex Factors , Time-to-Treatment
5.
BMC Infect Dis ; 21(1): 452, 2021 May 19.
Article in English | MEDLINE | ID: covidwho-1236546

ABSTRACT

BACKGROUND: COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. METHODS: An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. RESULTS: Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019-13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21-12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14-4.98) for moderate-selenium-deficient cities and 3.06 (1.49-6.27) for severe-selenium-deficient cities. CONCLUSIONS: Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.


Subject(s)
COVID-19/diagnosis , Selenium/analysis , COVID-19/mortality , COVID-19/virology , China/epidemiology , Crops, Agricultural/chemistry , Humans , Micronutrients/analysis , SARS-CoV-2/isolation & purification , Selenium/deficiency , Soil/chemistry , Survival Analysis
6.
Travel Med Infect Dis ; 35: 101654, 2020.
Article in English | MEDLINE | ID: covidwho-31614

ABSTRACT

BACKGROUND: A novel coronavirus emerged in China in December 2019, and human-to-human transmission was previously identified. This study aimed to compare the epidemiological characteristics in Jiangsu Province and assess whether so-called wartime control measures changed the trend of coronavirus disease 2019 (COVID-19) in the province. METHODS: Epidemiological data were obtained from the websites of China's Bureau of Health and the People's Government of Jiangsu Province and informal online sources from January 22 to February 20, 2020. RESULTS: The cumulative number of patients in Jiangsu Province (over 79 million people) was 613. The number of daily confirmed new cases reached the inflection point on January 31 with the maximum of 39 cases. The temporal number of patients peaked from January 29 to February 9. The proportion of confirmed cases who were residents or travelers to Hubei Province was 100.0%-58.8% before January 31 and then gradually declined. The proportion of close contacts increased gradually from January 27 to February 17. The geographical distribution of COVID-2019 cases showed that all 13 cites reported confirmed new cases after only five days of the first confirmed new case in Suzhou. The cases were concentrated in Nanjing, Suzhou, and Xuzhou with a high population density (over eight million people). The epidemiological features of COVID-2019 cases in Wuxi, Jiangsu showed that seven confirmed cases were tourists from others areas beyond Hubei Province. The longest incubation period of COVID-2019 was 19 days based on the onset of laboratory-confirmed cases. CONCLUSION: The number of daily confirmed new cases in Jiangsu Province peaked around January 31 and then declined. This result emphasized that wartime control measures, such as putting cities on lockdown to limit population mobility in Jiangsu Province, resulted in dramatic reductions in COVID-19 cases.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Pneumonia, Viral/epidemiology , Pneumonia, Viral/transmission , Quarantine/methods , COVID-19 , China/epidemiology , Cities/epidemiology , Coronavirus Infections/virology , Female , Humans , Male , Pandemics , Pneumonia, Viral/virology , Retrospective Studies , SARS-CoV-2 , Transients and Migrants , Travel
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