Background: The coronavirus disease 2019 (COVID-19) outbreak originating in Wuhan, Hubei province, China, coincided with chunyun, the period of mass migration for the annual Spring Festival. To contain its spread, China adopted unprecedented nationwide interventions on January 23 2020. These policies included large-scale quarantine, strict controls on travel and extensive monitoring of suspected cases. However, it is unknown whether these policies have had an impact on the epidemic. We sought to show how these control measures impacted the containment of the epidemic. Methods: We integrated population migration data before and after January 23 and most updated COVID-19 epidemiological data into the Susceptible-Exposed-Infectious-Removed (SEIR) model to derive the epidemic curve. We also used an artificial intelligence (AI) approach, trained on the 2003 SARS data, to predict the epidemic. Results: We found that the epidemic of China should peak by late February, showing gradual decline by end of April. A five-day delay in implementation would have increased epidemic size in mainland China three-fold. Lifting the Hubei quarantine would lead to a second epidemic peak in Hubei province in mid-March and extend the epidemic to late April, a result corroborated by the machine learning prediction. Conclusions: Our dynamic SEIR model was effective in predicting the COVID-19 epidemic peaks and sizes. The implementation of control measures on January 23 2020 was indispensable in reducing the eventual COVID-19 epidemic size.
Human coronaviruses (HCoV) OC43, 229E, NL63, and HKU1 are common respiratory viruses which cause various respiratory diseases, including pneumonia. There is a paucity of evidence on the epidemiology and clinical manifestations of these four HCoV strains worldwide. We collected 11,399 throat swabs from hospitalized children with acute respiratory tract infection from July 2009 to June 2016 in Guangzhou, China. These were tested for four strains of HCoV infection using real-time polymerase chain reaction (PCR). HCoV-positive patients were then tested for 11 other respiratory pathogens. 4.3% (489/11399) of patients were positive for HCoV, of which 3.0% were positive for OC43 (346/11399), 0.6% for 229E (65/11399), 0.5% for NL63 (60/11399), and 0.3% for HKU1 (38/11399). Patients aged 7–12 months had the highest prevalence of HCoV and OC43 when compared with other age groups (p < 0.001). The peak seasons of infection varied depending on the HCoV strain. Patients infected with a single strain of HCoV infection were less likely to present fever (≥ 38 °C) (p = 0.014) and more likely to present pulmonary rales (p = 0.043) than those co-infected with more than one HCoV strain or other respiratory pathogens. There were also significant differences in the prevalence of certain symptoms, including coughing (p = 0.032), pneumonia (p = 0.026), and abnormal pulmonary rales (p = 0.002) according to the strain of HCoV detected. This retrospective study of the prevalence of four HCoV strains and clinical signs among a large population of pediatric patients in a subtropical region of China provides further insight into the epidemiology and clinical features of HCoV.
Respiratory syncytial virus (RSV) is one of the most important pathogenic infections of children and requires in-depth research worldwide, and especially in developing countries. We used a novel multiplex real-time PCR to test 5483 patients (≤ 14 years old) hospitalized with respiratory illness in Guangzhou, China, over a 3-year period. Of these patients, 729 were positive for RSV-A (51.2%, 373/729) or RSV-B (48.8%, 356/729), but none was infected with both viruses. Two seasonal peaks in total RSV were detected at the changes from winter to spring and from summer to autumn. RSV-B was dominant in 2013 and RSV-A in 2015, whereas RSV-A and RSV-B cocirculated in 2014. The clinical presentations of 645 RSV-positive patients were analyzed. Bronchiolitis, dyspnea, coryza, vomiting, poor appetite, and diarrhea occurred more frequently in RSV-A-positive than RSV-B-positive patients, whereas chill, headache, myalgia, debility, and rash etc. were more frequent in RSV-B-positive than RSV-A-positive patients, suggesting specific clinical characteristics for RSV-A and RSV-B. Coinfectons with other pathogens were common and diverse. Bronchiolitis, fever (≥ 38°C), and poor appetite were more frequent in patients with single RSV infections than in coinfected patients, suggesting the key pathogenic activity of RSV. Analysis of the relationships between the comparative viral load and clinical presentations showed significant differences in bronchiolitis, fever (≥ 38°C), and rash etc. among patients with different viral loads. This study provides a novel rapid method for detecting RSV subgroups, and provides new insights into the epidemiology and clinical implications of RSV.
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