Effectiveness of nirmatrelvir/ritonavir and molnupiravir in non-hospitalized adults with COVID-19: systematic review and meta-analysis of observational studies.

OBJECTIVE: To determine the effectiveness of nirmatrelvir/ritonavir and molnupiravir among vaccinated and unvaccinated non-hospitalized adults with COVID-19. METHODS: Observational studies of nirmatrelvir/ritonavir or molnupiravir compared to no antiviral drug treatment for COVID-19 in non-hospitalized adults with data on vaccination status were included. We searched MEDLINE, EMBASE, Scopus, Web of Science, WHO COVID-19 Research Database and medRxiv for reports published between 1 January 2022 and 8 November 2023. The primary outcome was a composite of hospitalization or mortality up to 35 days after COVID-19 diagnosis. Risk of bias was assessed with ROBINS-I. Risk ratios (RR), hazard ratios (HR) and risk differences (RD) were separately estimated using random-effects models. RESULTS: We included 30 cohort studies on adults treated with nirmatrelvir/ritonavir (n = 462 279) and molnupiravir (n = 48 008). Nirmatrelvir/ritonavir probably reduced the composite outcome (RR 0.62, 95%CI 0.55-0.70; I2 = 0%; moderate certainty) with no evidence of effect modification by vaccination status (RR Psubgroup = 0.47). In five studies, RD estimates against the composite outcome for nirmatrelvir/ritonavir were 1.21% (95%CI 0.57% to 1.84%) in vaccinated and 1.72% (95%CI 0.59% to 2.85%) in unvaccinated subgroups.Molnupiravir may slightly reduce the composite outcome (RR 0.75, 95%CI 0.67-0.85; I2 = 32%; low certainty). Evidence of effect modification by vaccination status was inconsistent among studies reporting different effect measures (RR Psubgroup = 0.78; HR Psubgroup = 0.08). In two studies, RD against the composite outcome for molnupiravir were -0.01% (95%CI -1.13% to 1.10%) in vaccinated and 1.73% (95%CI -2.08% to 5.53%) in unvaccinated subgroups. CONCLUSIONS: Among cohort studies of non-hospitalized adults with COVID-19, nirmatrelvir/ritonavir is effective against the composite outcome of severe COVID-19 independent of vaccination status. Further research and a reassessment of molnupiravir use among vaccinated adults are warranted. REGISTRATION: PROSPERO CRD42023429232.

Use of telephone helpline data for syndromic surveillance of adverse events following immunization in Australia: A retrospective study, 2009 to 2017.

BACKGROUND: The increasing availability of electronic healthcare data offers an opportunity to enhance adverse events following immunisation (AEFI) signal monitoring in near real-time. AIM: To evaluate the potential use of telephone helpline data to augment the existing AEFI surveillance system in Victoria, Australia. METHODS: Anonymised telephone helpline call data were extracted between 2009 and 2017. For comparison, we included AEFI reports to the Victorian enhanced passive surveillance system, SAEFVIC-"Surveillance of Adverse Events Following Vaccination In the Community". The temporal pattern cross-correlation coefficient at different time lags was estimated as a measure of timeliness evaluation. Historically known AEFI signals in 2010 and 2015 were examined using the Farrington statistical signal detection algorithm. RESULT: During the study period, overall, the telephone helpline centre received 2,005,226 calls. Of these, 0.68% (13,719) were AEFI-related. In the same period, SAEFVIC received 10,367 AEFI related reports. Cross-correlation analysis, generally, showed that the two datasets were moderately correlated (r = 0.4) at a negative lag of 1 week. For individual years, the cross-correlation coefficient was highest (r = 0.66) in 2010 with the telephone helpline data leading by 2 weeks. Our analysis indicated the 2010 reported incidence of febrile convulsions and the 2015 reported increased allergic-related reactions following seasonal influenza vaccination three weeks and one week earlier respectively. CONCLUSION: Telephone helpline data was able to detect an increased rate of AEFI earlier than the enhanced passive AEFI surveillance system. This dataset offers a valuable and near real-time component of an integrated AEFI early signal detection system in Australia.