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Summary: Background: The Invasive Respiratory Infection Surveillance (IRIS) Consortium was established to assess the impact of the COVID-19 pandemic on invasive diseases caused by Streptococcus pneumoniae, Haemophilus influenzae, Neisseria meningitidis, and Streptococcus agalactiae. We aimed to analyse the incidence and distribution of these diseases during the first 2 years of the COVID-19 pandemic compared to the 2 years preceding the pandemic. Methods: For this prospective analysis, laboratories in 30 countries and territories representing five continents submitted surveillance data from Jan 1, 2018, to Jan 2, 2022, to private projects within databases in PubMLST. The impact of COVID-19 containment measures on the overall number of cases was analysed, and changes in disease distributions by patient age and serotype or group were examined. Interrupted time-series analyses were done to quantify the impact of pandemic response measures and their relaxation on disease rates, and autoregressive integrated moving average models were used to estimate effect sizes and forecast counterfactual trends by hemisphere. Findings: Overall, 116 841 cases were analysed: 76 481 in 2018–19, before the pandemic, and 40 360 in 2020–21, during the pandemic. During the pandemic there was a significant reduction in the risk of disease caused by S pneumoniae (risk ratio 0·47; 95% CI 0·40–0·55), H influenzae (0·51; 0·40–0·66) and N meningitidis (0·26; 0·21–0·31), while no significant changes were observed for S agalactiae (1·02; 0·75–1·40), which is not transmitted via the respiratory route. No major changes in the distribution of cases were observed when stratified by patient age or serotype or group. An estimated 36 289 (95% prediction interval 17 145–55 434) cases of invasive bacterial disease were averted during the first 2 years of the pandemic among IRIS-participating countries and territories. Interpretation: COVID-19 containment measures were associated with a sustained decrease in the incidence of invasive disease caused by S pneumoniae, H influenzae, and N meningitidis during the first 2 years of the pandemic, but cases began to increase in some countries towards the end of 2021 as pandemic restrictions were lifted. These IRIS data provide a better understanding of microbial transmission, will inform vaccine development and implementation, and can contribute to health-care service planning and provision of policies. Funding: Wellcome Trust, NIHR Oxford Biomedical Research Centre, Spanish Ministry of Science and Innovation, Korea Disease Control and Prevention Agency, Torsten Söderberg Foundation, Stockholm County Council, Swedish Research Council, German Federal Ministry of Health, Robert Koch Institute, Pfizer, Merck, and the Greek National Public Health Organization.

Abstract Methicillin-resistant Staphylococcus aureus (MRSA) rates have remained relatively low in Finland. In Southwest Finland, however, annual MRSA incidence increased from 12 to 25/100,000 between 2007 and 2016 with spa t172 strain causing one fourth (237/983) of all cases. This provoked us to study the molecular epidemiology of t172-MRSA, aiming to better understand the transmission of this strain type. We combined epidemiological data and whole genome sequencing (WGS) of a set of 64 (27%, 64/237) t172-MRSA isolates covering 10 years. Isolates represented sporadic and index cases of all identified healthcare-associated outbreaks (HAOs) and family clusters (FCs). Among the included 62 isolates, core-genome MLST analysis revealed eight genomic clusters comprising 24 (38.7%) isolates and 38 (61.3%) non-clustered isolates. Cluster 1 comprised ten and the remaining seven clusters two isolates each, respectively. Two epidemiologically distinct HAOs were linked in cluster 1. FCs were involved in all clusters. All strains were associated with epidemic clonal complex CC59. We were able to confirm the spread of several successful t172-MRSA subclones in regional healthcare and the community. WGS complemented routine surveillance by revealing undetected links between t172-MRSA cases. Targeted, WGS-based typing could enhance MRSA surveillance without the need for routine WGS diagnostics.