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.

Background: Coronavirus disease 2019 (Covid-19) has resulted in a global outbreak. Few existing targeted medications are available. Lianhuaqingwen (LH) capsule, a repurposed marketed Chinese herb product, has been proven effective for influenza. Purpose: To determine the safety and efficacy of LH capsule in patients with Covid-19. Methods: We did a prospective multicenter open-label randomized controlled trial on LH capsule in confirmed cases with Covid-19. Patients were randomized to receive usual treatment alone or in combination with LH capsules (4 capsules, thrice daily) for 14 days. The primary endpoint was the rate of symptom (fever, fatigue, coughing) recovery. Results: We included 284 patients (142 each in treatment and control group) in the full-analysis set. The recovery rate was significantly higher in treatment group as compared with control group (91.5% vs. 82.4%, p = 0.022). The median time to symptom recovery was markedly shorter in treatment group (median: 7 vs. 10 days, p < 0.001). Time to recovery of fever (2 vs. 3 days), fatigue (3 vs. 6 days) and coughing (7 vs. 10 days) was also significantly shorter in treatment group (all p < 0.001). The rate of improvement in chest computed tomographic manifestations (83.8% vs. 64.1%, p < 0.001) and clinical cure (78.9% vs. 66.2%, p = 0.017) was also higher in treatment group. However, both groups did not differ in the rate of conversion to severe cases or viral assay findings (both p > 0.05). No serious adverse events were reported.

The ongoing COVID-19 pandemic has caused a serious health threat globally. Many countries have seen a two-wave pattern of reported cases, namely a second wave followed the first wave. To our knowledge, there are no studies to date to compare the case fatality rate between these two waves (Figure 1).

BackgroundHuman parainfluenza viruses (HPIVs) are important causes of upper respiratory tract illness (URTI) and lower respiratory tract illness (LRTI). To analyse epidemiologic and clinical characteristics of the four types of human parainfluenza viruses (HPIVs), patients with acute respiratory tract illness (ARTI) were studied in Guangzhou, southern China.MethodsThroat swabs (n=4755) were collected and tested from children and adults with ARTI over a 26-month period, and 4447 of 4755 (93.5%) patients’ clinical presentations were recorded for further analysis.ResultsOf 4755 patients tested, 178 (3.7%) were positive for HPIV. Ninety-nine (2.1%) samples were positive for HPIV-3, 58 (1.2%) for HPIV-1, 19 (0.4%) for HPIV-2 and 8 (0.2%) for HPIV-4. 160/178 (88.9%) HPIV-positive samples were from paediatric patients younger than 5 years old, but no infant under one month of age was HPIV positive. Seasonal peaks of HPIV-3 and HPIV-1 occurred as autumn turned to winter and summer turned to autumn. HPIV-2 and HPIV-4 were detected less frequently, and their frequency of isolation increased when the frequency of HPIV-3 and HPIV-1 declined. HPIV infection led to a wide spectrum of symptoms, and more “hoarseness” (p=0.015), “abnormal pulmonary breathing sound” (p<0.001), “dyspnoea” (p<0.001), “pneumonia” (p=0.01), and “diarrhoea” (p<0.001) presented in HPIV-positive patients than HPIV-negative patients. 10/10 (100%) HPIV-positive adult patients (≥14 years old) presented with systemic influenza-like symptoms, while 90/164 (54.9%) HPIV-positive paediatric patients (<14 years old) presented with these symptoms (p=0.005). The only significant difference in clinical presentation between HPIV types was “Expectoration” (p<0.001). Co-infections were common, with 33.3%–63.2% of samples positive for the four HPIV types also testing positive for other respiratory pathogens. However, no significant differences were seen in clinical presentation between patients solely infected with HPIV and patients co-infected with HPIV and other respiratory pathogens.ConclusionsHPIV infection led to a wide spectrum of symptoms, and similar clinical manifestations were found in the patients with four different types of HPIVs. The study suggested pathogenic activity of HPIV in gastrointestinal illness. The clinical presentation of HPIV infection may differ by patient age.