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Enregistrement W3165370163 · doi:10.1016/s2589-7500(21)00085-6

COVID-19 containment measures and incidence of invasive bacterial disease

2021· letter· en· W3165370163 sur OpenAlexfundaboutno aff
David R. Smith, Lulla Opatowski

Notice bibliographique

RevueThe Lancet Digital Health · 2021
Typeletter
Langueen
DomaineMathematics
ThématiqueCOVID-19 epidemiological studies
Établissements canadiensnon disponible
Organismes subventionnairesCanadian Institutes of Health ResearchFondation de FranceAgence Nationale de la RecherchePfizer
Mots-clésOutbreakRelocationEnvironmental healthCholeraContainment (computer programming)SewageInfectious disease (medical specialty)Environmental scienceCoronavirus disease 2019 (COVID-19)GeographyDiseaseEnvironmental engineeringBiologyVirologyMedicine

Résumé

récupéré en direct d'OpenAlex

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

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,036
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,251
Score d'incertitude au seuil0,972

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,036
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,312
Tête enseignante GPT0,429
Écart entre enseignants0,117 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations11
Publié2021
Routes d'admission2
Résumé présentoui

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