COVID-19 containment measures and incidence of invasive bacterial disease
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Bibliographic record
Abstract
Interventions implemented amidst ongoing infectious disease outbreaks can act as natural experiments that help to disentangle how pathogens spread and diseases manifest. The most well known example is John Snow's seminal cholera study from mid-19th century London. Suspecting that recurring cholera outbreaks were resulting from drinking water contaminated with sewage, Snow recognised the relocation of water intake pipes to a source upstream from city effluent as an opportunity to test, and ultimately confirm, his hypothesis. In response to the COVID-19 pandemic declared in early 2020, governments worldwide enacted a range of COVID-19 containment measures to control the spread of SARS-CoV-2, including school and workplace closures, stay-at-home orders, and travel restrictions. These natural experiments have been evaluated for their effects on COVID-19 incidence, human contact behaviour, and other outcomes.1Islam N Sharp SJ Chowell G et al.Physical distancing interventions and incidence of coronavirus disease 2019: natural experiment in 149 countries.BMJ. 2020; 370m2743Crossref PubMed Scopus (368) Google Scholar, 2Jarvis CI Gimma A van Zandvoort K Wong KLM Edmunds WJ The impact of local and national restrictions in response to COVID-19 on social contacts in England: a longitudinal natural experiment.BMC Med. 2021; 19: 52Crossref PubMed Scopus (34) Google Scholar However, consequences for the spread of pathogens other than SARS-CoV-2 are only just beginning to be revealed. In this issue of The Lancet Digital Health, Angela B Brueggemann and colleagues3Brueggemann AB Jansen van Rensburg MJ Shaw D et al.Changes in the incidence of invasive disease due to Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis during the COVID-19 pandemic in 26 countries and territories in the Invasive Respiratory Infection Surveillance Initiative: a prospective analysis of surveillance data.Lancet Digit Health. 2021; 3: e360-e370Summary Full Text Full Text PDF PubMed Scopus (260) Google Scholar present results from an extensive international surveillance network uniting 26 countries and territories across six continents, including 24 national reference centres, and use interrupted time series analyses to study the effects of COVID-19 containment measures on invasive disease due to three common respiratory pathogens: Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis. Coincident with COVID-19 containment measures, they observed substantial and sustained reductions in the incidence of hospital-reported invasive disease for each pathogen compared with the years 2018 and 2019. For S pneumoniae in particular, which had the largest sample size by an order of magnitude, reductions in incidence were associated with the stringency of containment measures (measured using the Oxford COVID-19 Government Response Tracker) and with corresponding reductions in human mobility (measured using Google COVID-19 Community Mobility Reports). Importantly, in nine countries with available data, they found no change in the incidence of Streptococcus agalactiae, a non-respiratory control pathogen, suggesting that neither pandemic-associated breakdowns in surveillance nor changes in health-care seeking behaviours among individuals with invasive disease were responsible for the decreased incidence of S pneumoniae, H influenzae, and N meningitidis. Indirect efficacy of COVID-19 containment measures for control of respiratory pathogens other than SARS-CoV-2 seems intuitive. Brueggemann and colleagues state that the most plausible explanation for observed reductions in disease incidence is reduction in person-to-person transmission of the bacteria under study. This explanation is supported by an estimated 38% reduction in invasive S pneumoniae disease immediately following the implementation of containment measures. However, unlike respiratory viruses, which often spread quickly and infect briefly, these bacteria tend to colonise their hosts as harmless symbionts, only occasionally becoming pathogenic when natural immunological barriers are overcome, causing opportunistic infections such as pneumonia, septicaemia, and meningitis. Colonisation is a necessary precursor to invasive disease, but how the probability of illness varies with time since acquisition remains unclear. Immediate reductions in disease incidence seem to support the hypothesis that containment measures prevented bacterial disease by blocking bacterial acquisition. However, a competing hypothesis is that containment measures prevented asymptomatic carriers from progressing to disease by blocking transmission of respiratory viruses that trigger bacterial infection. Viral respiratory infection is a known risk factor for invasive bacterial disease, and recent work4Domenech de Cellès M Arduin H Lévy-Bruhl D et al.Unraveling the seasonal epidemiology of pneumococcus.Proc Natl Acad Sci USA. 2019; 116: 1802-1807Crossref PubMed Scopus (25) Google Scholar has identified influenza-like illnesses as important drivers of the seasonal dynamics of invasive pneumococcal disease. In addition to immediate reductions in incidence, the authors estimated a 13% weekly reduction in the incidence of invasive disease due to S pneumoniae following implementation of COVID-19 containment measures, for an overall 82% reduction at 8 weeks. It is difficult to interpret the extent to which persistent declines in incidence reflect continued reduction in new acquisitions versus prevention of disease progression. Future longitudinal studies investigating changes in bacterial carriage and viral infection in different age groups in response to containment measures are needed to help understand these results. Other factors might have further contributed to the observed trends, including altered transmission of other constituents of the nasopharyngeal microbiome, which can both compete and cooperate with the pathogens under study.5Weiser JN Ferreira DM Paton JC Streptococcus pneumoniae: transmission, colonization and invasion.Nat Rev Microbiol. 2018; 16: 355-367Crossref PubMed Scopus (545) Google Scholar Potential interactions between SARS-CoV-2 and respiratory bacteria could also have had a role.6Amin-Chowdhury Z Aiano F Mensah A et al.Impact of the Coronavirus Disease 2019 (COVID-19) pandemic on invasive pneumococcal disease and risk of pneumococcal coinfection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): prospective national cohort study, England.Clin Infect Dis. 2021; 72: e65-e75Crossref PubMed Scopus (97) Google Scholar More broadly, the pandemic has disrupted antibiotic prescribing and consumption both in hospitals and in the community in many regions.7Malcolm W Seaton RA Haddock G et al.Impact of the COVID-19 pandemic on community antibiotic prescribing in Scotland.JAC Antimicrob Resist. 2020; 2dlaa105Crossref PubMed Scopus (38) Google Scholar, 8Ryu S Hwang Y Ali ST et al.Decreased use of broad-spectrum antibiotics during COVID-19 epidemic in South Korea.J Infect Dis. 2021; (published online April 15.)https://doi.org/10.1093/infdis/jiab208Crossref PubMed Scopus (18) Google Scholar, 9Rodríguez-Baño J Rossolini GM Schultsz C et al.Key considerations on the potential impacts of the COVID-19 pandemic on antimicrobial resistance research and surveillance.Trans R Soc Trop Med Hyg. 2021; (published online March 27.)https://doi.org/10.1093/trstmh/trab048Crossref PubMed Scopus (66) Google Scholar These changes might have affected the prevalence of asymptomatic pathogen colonisation, selection for drug-resistant strains, and antibiotic impacts on the microbiome, with potential knock-on effects for susceptibility to colonisation and infection. To date, the impacts of the COVID-19 pandemic on antimicrobial resistance are under-investigated phenomena of potentially great global health significance, for these and other pathogens.10Knight GM Glover RE McQuaid CF et al.Antimicrobial resistance and COVID-19: intersections and implications.eLife. 2021; 10e64139Crossref PubMed Scopus (186) Google Scholar The work by Brueggemann and colleagues shows the importance of maintaining high-quality microbiological surveillance systems during crises, the value of internationally collaborative infectious disease research networks, and together what they can reveal about indirect effects of natural experiments targeting certain pathogens but ultimately affecting others. When John Snow showed that clean drinking water can prevent cholera, Vibrio cholerae was not yet discovered. Brueggemann and colleagues show that COVID-19 containment measures in early 2020 protected against invasive diseases caused by respiratory bacteria. However, in the absence of even more comprehensive surveillance data across age groups, including data on asymptomatic carriage of these bacteria and other microorganisms that could influence host susceptibility to disease, the exact reasons remain unclear. LO reports grants from Agence Nationale de la Recherche (France), Pfizer, and Fondation de France. DRMS reports funding from Agence Nationale de la Recherche (France) and the Canadian Institutes of Health Research. Changes in the incidence of invasive disease due to Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis during the COVID-19 pandemic in 26 countries and territories in the Invasive Respiratory Infection Surveillance Initiative: a prospective analysis of surveillance dataThe introduction of COVID-19 containment policies and public information campaigns likely reduced transmission of S pneumoniae, H influenzae, and N meningitidis, leading to a significant reduction in life-threatening invasive diseases in many countries worldwide. Full-Text PDF Open Access
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it