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1.
BMC Infect Dis ; 22(1): 674, 2022 Aug 05.
Article in English | MEDLINE | ID: covidwho-2196078

ABSTRACT

BACKGROUND: To quantitatively assess the impact of the onset-to-diagnosis interval (ODI) on severity and death for coronavirus disease 2019 (COVID-19) patients. METHODS: This retrospective study was conducted based on the data on COVID-19 cases of China over the age of 40 years reported through China's National Notifiable Infectious Disease Surveillance System from February 5, 2020 to October 8, 2020. The impacts of ODI on severe rate (SR) and case fatality rate (CFR) were evaluated at individual and population levels, which was further disaggregated by sex, age and geographic origin. RESULTS: As the rapid decline of ODI from around 40 days in early January to < 3 days in early March, both CFR and SR of COVID-19 largely dropped below 5% in China. After adjusting for age, sex, and region, an effect of ODI on SR was observed with the highest OR of 2.95 (95% CI 2.37‒3.66) at Day 10-11 and attributable fraction (AF) of 29.1% (95% CI 22.2‒36.1%) at Day 8-9. However, little effect of ODI on CFR was observed. Moreover, discrepancy of effect magnitude was found, showing a greater effect from ODI on SR among patients of male sex, younger age, and those cases in Wuhan. CONCLUSION: The ODI was significantly associated with the severity of COVID-19, highlighting the importance of timely diagnosis, especially for patients who were confirmed to gain increased benefit from early diagnosis to some extent.


Subject(s)
COVID-19 , Adult , COVID-19/diagnosis , COVID-19 Testing , China/epidemiology , Humans , Male , Retrospective Studies , SARS-CoV-2
2.
Int J Infect Dis ; 122: 38-45, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-2036061

ABSTRACT

OBJECTIVES: Selenium deficiency can be associated with increased susceptibility to some viral infections and even more severe diseases. In this study, we aimed to examine whether this association applies to severe fever with thrombocytopenia syndrome (SFTS). METHOD: An observational study was conducted based on the data of 13,305 human SFTS cases reported in mainland China from 2010 to 2020. The associations among incidence, case fatality rate of SFTS, and crop selenium concentration at the county level were explored. The selenium level in a cohort of patients with SFTS was tested, and its relationship with clinical outcomes was evaluated. RESULTS: The association between selenium-deficient crops and the incidence rate of SFTS was confirmed by multivariate Poisson analysis, with an estimated incidence rate ratio (IRR, 95% confidence interval [CI]) of 4.549 (4.215-4.916) for moderate selenium-deficient counties and 16.002 (14.706-17.431) for severe selenium-deficient counties. In addition, a higher mortality rate was also observed in severe selenium-deficient counties with an IRR of 1.409 (95% CI: 1.061-1.909). A clinical study on 120 patients with SFTS showed an association between serum selenium deficiency and severe SFTS (odds ratio, OR: 2.94; 95% CI: 1.00-8.67) or fatal SFTS (OR: 7.55; 95% CI: 1.14-50.16). CONCLUSION: Selenium deficiency is associated with increased susceptibility to SFTS and poor clinical outcomes.


Subject(s)
Bunyaviridae Infections , Phlebovirus , Selenium , Severe Fever with Thrombocytopenia Syndrome , Thrombocytopenia , China/epidemiology , Fever/epidemiology , Humans , Thrombocytopenia/epidemiology
3.
Clin Infect Dis ; 75(1): e1054-e1062, 2022 Aug 24.
Article in English | MEDLINE | ID: covidwho-1758700

ABSTRACT

BACKGROUND: To combat the coronavirus disease 2019 (COVID-19) pandemic, nonpharmaceutical interventions (NPIs) were implemented worldwide, which impacted a broad spectrum of acute respiratory infections (ARIs). METHODS: Etiologically diagnostic data from 142 559 cases with ARIs, who were tested for 8 viral pathogens (influenza virus [IFV], respiratory syncytial virus [RSV], human parainfluenza virus [HPIV], human adenovirus [HAdV], human metapneumovirus [HMPV], human coronavirus [HCoV], human bocavirus [HBoV], and human rhinovirus [HRV]) between 2012 and 2021, were analyzed to assess the changes in respiratory infections in China during the first COVID-19 pandemic year compared with pre-pandemic years. RESULTS: Test-positive rates of all respiratory viruses decreased during 2020, compared to the average levels during 2012-2019, with changes ranging from -17.2% for RSV to -87.6% for IFV. Sharp decreases mostly occurred between February and August when massive NPIs remained active, although HRV rebounded to the historical level during the summer. While IFV and HMPV were consistently suppressed year-round, RSV, HPIV, HCoV, HRV, and HBoV resurged and went beyond historical levels during September 2020-January 2021, after NPIs were largely relaxed and schools reopened. Resurgence was more prominent among children <18 years and in northern China. These observations remain valid after accounting for seasonality and long-term trend of each virus. CONCLUSIONS: Activities of respiratory viral infections were reduced substantially in the early phases of the COVID-19 pandemic, and massive NPIs were likely the main driver. Lifting of NPIs can lead to resurgence of viral infections, particularly in children.


Subject(s)
COVID-19 , Human bocavirus , Metapneumovirus , Orthomyxoviridae , Respiratory Syncytial Virus, Human , Respiratory Tract Infections , Virus Diseases , Viruses , COVID-19/epidemiology , Child , Humans , Pandemics , Parainfluenza Virus 1, Human
4.
Nat Commun ; 12(1): 6923, 2021 11 26.
Article in English | MEDLINE | ID: covidwho-1537314

ABSTRACT

Nationwide nonpharmaceutical interventions (NPIs) have been effective at mitigating the spread of the novel coronavirus disease (COVID-19), but their broad impact on other diseases remains under-investigated. Here we report an ecological analysis comparing the incidence of 31 major notifiable infectious diseases in China in 2020 to the average level during 2014-2019, controlling for temporal phases defined by NPI intensity levels. Respiratory diseases and gastrointestinal or enteroviral diseases declined more than sexually transmitted or bloodborne diseases and vector-borne or zoonotic diseases. Early pandemic phases with more stringent NPIs were associated with greater reductions in disease incidence. Non-respiratory diseases, such as hand, foot and mouth disease, rebounded substantially towards the end of the year 2020 as the NPIs were relaxed. Statistical modeling analyses confirm that strong NPIs were associated with a broad mitigation effect on communicable diseases, but resurgence of non-respiratory diseases should be expected when the NPIs, especially restrictions of human movement and gathering, become less stringent.


Subject(s)
Communicable Diseases/epidemiology , Disease Notification/statistics & numerical data , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/transmission , China/epidemiology , Communicable Disease Control , Communicable Diseases/classification , Communicable Diseases/transmission , Humans , Incidence , Models, Statistical , SARS-CoV-2
5.
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
6.
Lancet Reg Health West Pac ; 16: 100268, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1415636

ABSTRACT

BACKGROUND: Non pharmaceutical interventions (NPI) including hand washing directives were implemented in China and worldwide to combat the COVID-19 pandemic, which are likely to have had impacted a broad spectrum of enteric pathogen infections. METHODS: Etiologically diagnostic data from 45 937 and 67 395 patients with acute diarrhea between 2012 and 2020, who were tested for seven viral pathogens and 13 bacteria respectively, were analyzed to assess the changes of enteric pathogen infections in China during the first COVID-19 pandemic year compared to pre-pandemic years. FINDINGS: Test positive rates of all enteric viruses decreased during 2020, compared to the average levels during 2012-2019, with a relative decrease of 71•75% for adenovirus, 58•76% for norovirus, 53•50% for rotavirus A, and 72•07% for the combination of other four uncommon viruses. In general, a larger reduction of positive rate in viruses was seen among adults than pediatric patients. A rebound of rotavirus A was seen after September 2020 in North China rather than South China. Test positive rates of bacteria decreased during 2020, compared to the average levels during 2012-2019, excepting for nontyphoidal Salmonella and Campylobacter coli with 66•53% and 90•48% increase respectively. This increase was larger for pediatric patients than for adult patients. INTERPRETATION: The activity of enteric pathogens changed profoundly alongside the NPIs implemented during the COVID-19 pandemic in China. Greater reductions of the test positive rates were found for almost all enteric viruses than for bacteria among acute diarrhea patients, with further large differences by age and geography. Lifting of NPIs will lead to resurgence of enteric pathogen infections, particularly in children whose immunity may not have been developed and/or waned. FUNDING: China Mega-Project on Infectious Disease Prevention; National Natural Science Funds.

8.
Infect Dis Poverty ; 10(1): 48, 2021 Apr 12.
Article in English | MEDLINE | ID: covidwho-1181127

ABSTRACT

BACKGROUND: COVID-19 has posed an enormous threat to public health around the world. Some severe and critical cases have bad prognoses and high case fatality rates, unraveling risk factors for severe COVID-19 are of significance for predicting and preventing illness progression, and reducing case fatality rates. Our study focused on analyzing characteristics of COVID-19 cases and exploring risk factors for developing severe COVID-19. METHODS: The data for this study was disease surveillance data on symptomatic cases of COVID-19 reported from 30 provinces in China between January 19 and March 9, 2020, which included demographics, dates of symptom onset, clinical manifestations at the time of diagnosis, laboratory findings, radiographic findings, underlying disease history, and exposure history. We grouped mild and moderate cases together as non-severe cases and categorized severe and critical cases together as severe cases. We compared characteristics of severe cases and non-severe cases of COVID-19 and explored risk factors for severity. RESULTS: The total number of cases were 12 647 with age from less than 1 year old to 99 years old. The severe cases were 1662 (13.1%), the median age of severe cases was 57 years [Inter-quartile range(IQR): 46-68] and the median age of non-severe cases was 43 years (IQR: 32-54). The risk factors for severe COVID-19 were being male [adjusted odds ratio (aOR) = 1.3, 95% CI: 1.2-1.5]; fever (aOR = 2.3, 95% CI: 2.0-2.7), cough (aOR = 1.4, 95% CI: 1.2-1.6), fatigue (aOR = 1.3, 95% CI: 1.2-1.5), and chronic kidney disease (aOR = 2.5, 95% CI: 1.4-4.6), hypertension (aOR = 1.5, 95% CI: 1.2-1.8) and diabetes (aOR = 1.96, 95% CI: 1.6-2.4). With the increase of age, risk for the severity was gradually higher [20-39 years (aOR = 3.9, 95% CI: 1.8-8.4), 40-59 years (aOR = 7.6, 95% CI: 3.6-16.3), ≥ 60 years (aOR = 20.4, 95% CI: 9.5-43.7)], and longer time from symtem onset to diagnosis [3-5 days (aOR = 1.4, 95% CI: 1.2-1.7), 6-8 days (aOR = 1.8, 95% CI: 1.5-2.1), ≥ 9 days(aOR = 1.9, 95% CI: 1.6-2.3)]. CONCLUSIONS: Our study showed the risk factors for developing severe COVID-19 with large sample size, which included being male, older age, fever, cough, fatigue, delayed diagnosis, hypertension, diabetes, chronic kidney diasease, early case identification and prompt medical care. Based on these factors, the severity of COVID-19 cases can be predicted. So cases with these risk factors should be paid more attention to prevent severity.


Subject(s)
Age Factors , COVID-19/epidemiology , Comorbidity , Severity of Illness Index , Sex Factors , Adolescent , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , China/epidemiology , Early Diagnosis , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Risk Factors , Young Adult
9.
Infect Dis Poverty ; 10(1): 21, 2021 Mar 01.
Article in English | MEDLINE | ID: covidwho-1112454

ABSTRACT

BACKGROUND: Considering the widespread of coronavirus disease 2019 (COVID-19) pandemic in the world, it is important to understand the spatiotemporal development of the pandemic. In this study, we aimed to visualize time-associated alterations of COVID-19 in the context of continents and countries. METHODS: Using COVID-19 case and death data from February to December 2020 offered by Johns Hopkins University, we generated time-associated balloon charts with multiple epidemiological indicators including crude case fatality rate (CFR), morbidity, mortality and the total number of cases, to compare the progression of the pandemic within a specific period across regions and countries, integrating seven related dimensions together. The area chart is used to supplement the display of the balloon chart in daily new COVID-19 case changes in UN geographic regions over time. Javascript and Vega-Lite were chosen for programming and mapping COVID-19 data in browsers for visualization. RESULTS: From February 1st to December 20th 2020, the COVID-19 pandemic spread across UN subregions in the chronological order. It was first reported in East Asia, and then became noticeable in Europe (South, West and North), North America, East Europe and West Asia, Central and South America, Southern Africa, Caribbean, South Asia, North Africa, Southeast Asia and Oceania, causing several waves of epidemics in different regions. Since October, the balloons of Europe, North America and West Asia have been rising rapidly, reaching a dramatically high morbidity level ranging from 200 to 500/10 000 by December, suggesting an emerging winter wave of COVID-19 which was much bigger than the previous ones. By late December 2020, some European and American countries displayed a leading mortality as high as or over 100/100 000, represented by Belgium, Czechia, Spain, France, Italy, UK, Hungary, Bulgaria, Peru, USA, Argentina, Brazil, Chile and Mexico. The mortality of Iran was the highest in Asia (over 60/100 000), and that of South Africa topped in Africa (40/100 000). In the last 15 days, the CFRs of most countries were at low levels of less than 5%, while Mexico had exceptional high CFR close to 10%. CONCLUSIONS: We creatively used visualization integrating 7-dimensional epidemiologic and spatiotemporal indicators to assess the progression of COVID-19 pandemic in terms of transmissibility and severity. Such methodology allows public health workers and policy makers to understand the epidemics comparatively and flexibly.


Subject(s)
COVID-19/epidemiology , Public Health Surveillance/methods , Computer Graphics , Global Health/statistics & numerical data , Humans , Pandemics/statistics & numerical data , Spatio-Temporal Analysis
10.
Biomed Environ Sci ; 33(8): 639-645, 2020 Aug 20.
Article in English | MEDLINE | ID: covidwho-771379

ABSTRACT

An online survey conducted March 18-19, 2020 on the official China CDC WeChat account platform was used to evaluate the effect of public education about masks usage during the new coronavirus disease 2019 (COVID-19) epidemic. Chinese nationals older than 18 were eligible for the survey. The survey collected 5,761 questionnaires from the 31 provinces, municipalities, and autonomous regions of mainland China. 99.7% and 97.2% of the respondents answered correctly that respiratory droplets and direct contact were the main transmission routes. 73.3% of the respondents considered COVID-19 to be 'serious' or 'very serious'. When going to the hospital, 96.9% (2,885/2,976 had gone to a hospital) used a mask during the COVID-19 epidemic, while 41.1% (2,367/5,761) did not use a mask before the epidemic. Among the respondents that used public transportation and went shopping, 99.6% and 99.4%, respectively, wore masks. Among respondents who returned to work, 75.5% wore a mask at the workplace, while 86.3% of those who have not returned to work will choose to use masks when they return to the workplace. The Chinese public is highly likely to use a mask during COVID-19 epidemic, and the mask usage changed greatly since the COVID-19 outbreak. Therefore, public education has played an important role during the COVID-19 epidemic.


Subject(s)
Betacoronavirus/physiology , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Disease Outbreaks , Masks , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Social Media , Surveys and Questionnaires , Adolescent , Adult , Age Distribution , COVID-19 , China/epidemiology , Health Behavior , Humans , Middle Aged , Pandemics , SARS-CoV-2 , Young Adult
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