A case-case study on the effect of primary and booster immunization with China-produced COVID-19 vaccines on prevention of pneumonia and viral load among vaccinated persons infected by Delta and Omicron variants.

Using a three-prefecture, two-variant COVID-19 outbreak in Henan province in January 2022, we evaluated the associations of primary and booster immunization with China-produced COVID-19 vaccines and COVID-19 pneumonia and SARS-CoV-2 viral load among persons infected by Delta or Omicron variant. We obtained demographic, clinical, vaccination, and multiple Ct values of infections ≥3 years of age. Vaccination status was either primary series ≥180 days prior to infection; primary series <180 days prior to infection, or booster dose recipient. We used logistic regression to determine odds ratios (OR) of Delta and Omicron COVID-19 pneumonia by vaccination status. We analysed minimum Ct values by vaccination status, age, and variant. Of 826 eligible cases, 405 were Delta and 421 were Omicron cases; 48.9% of Delta and 19.0% of Omicron cases had COVID-19 pneumonia. Compared with full primary vaccination ≥180 days before infection, the aOR of pneumonia was 0.48 among those completing primary vaccination <180 days and 0.18 among booster recipients among these Delta infections. Among Omicron infections, the corresponding aOR was 0.34 among those completing primary vaccination <180 days. There were too few (ten) Omicron cases among booster dose recipients to calculate a reliable OR. There were no differences in minimum Ct values by vaccination status among the 356 Delta cases or 70 Omicron cases. COVID-19 pneumonia was less common among Omicron cases than Delta cases. Full primary vaccination reduced pneumonia effectively for 6 months; boosting six months after primary vaccination resulted in further reduction. We recommend accelerating the pace of booster dose administration.

Risk factors for developing severe COVID-19 in China: an analysis of disease surveillance data.

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.