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Enregistrement W3153680332 · doi:10.1101/2021.04.08.21255096

Impact of the COVID-19 pandemic and response on the utilisation of health services during the first wave in Kinshasa, the Democratic Republic of the Congo

2021· preprint· en· W3153680332 sur OpenAlexafffund
Celestin Hategeka, Simone Carter, Faustin Chenge, Eric Nyambu Katanga, Grégoire Lurton, Serge Mayaka, Dieudonné Kazadi Mwamba, Esther van Kleef, Veerle Vanlerberghe, Karen A. Grépin

Notice bibliographique

RevuemedRxiv · 2021
Typepreprint
Langueen
DomaineMedicine
ThématiqueGlobal Maternal and Child Health
Établissements canadiensUnited Nations Children's Fund Canada
Organismes subventionnairesInternational Development Research Centre
Mots-clésPandemicPublic healthMedicineEnvironmental healthCommunicable diseaseOutbreakDemographyCoronavirus disease 2019 (COVID-19)DiseaseInfectious disease (medical specialty)Nursing

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction Health service use among the general public can decline during infectious disease outbreaks and has been predicted among low and middle-income countries during the COVID-19 pandemic. In March 2020, the government of the Democratic Republic of the Congo (DRC) implemented public health measures across Kinshasa, including strict lockdown measures in the Gombe health zone, to mitigate impact of the pandemic. Methods Using data from the Health Management Information System (January 2018 - December 2020), we evaluated the impact of the pandemic on the use of essential health services (total visits, maternal health, vaccinations, visits for common infectious diseases, and diagnosis of non-communicable diseases) using interrupted time series with mixed effects segmented Poisson regression models during the first wave of the pandemic. Analyses were stratified by age, sex, health facility, and neighbourhood. Results Health service use dropped rapidly following the start of the pandemic and ranged from 16% for hypertension diagnoses to 39% for diabetes diagnoses. However, reductions were highly concentrated in Gombe (81% decline in total visits) relative to health zones without lockdown. When the lockdown was lifted, total visits, visits for infectious diseases, and diagnoses for non-communicable diseases increased approximately two-fold. Hospitals were more affected than health centres. Overall, the use of maternal health services and vaccinations was not significantly affected. Conclusion The COVID-19 pandemic resulted in important reductions in health service utilisation in Kinshasa, particularly Gombe. Lifting of lockdown led to a rebound in the level of health service use but it remained lower than pre-pandemic levels. Summary Box What is already known about this subject Substantial declines in the use of health services among the general public have been well-documented during previous outbreaks of infectious diseases. Modelled studies predicted substantial increases in morbidity and mortality in many low- and middle-income countries (LMICs) mainly due to expected declines in the use of health services among the general public. Only a small number of studies have so far evaluated the impact of the COVID-19 pandemic on the use of health services in LMICs and none have also evaluated both the implementation and lifting of lockdown measures. What are the new findings This study found that overall use of health services declined in Kinshasa but was most pronounced in the Gombe health zone which was subject to strict lockdown measures. Some health services were more affected than others, most notably visits and tests for malaria and visits for new diagnoses of non-communicable diseases. Maternal and child health services were relatively unaffected. When the lockdown measures were lifted, health service utilization rebounded but remained at levels lower than those observed pre-pandemic. What do the new findings imply The COVID-19 pandemic has likely had important effects on the use of health services among the general public throughout LMICs. However, evidence from Kinshasa suggests the effects may not be as widespread as previously assumed. The impact of strict social distancing measures needs on COVID-19 outcomes needs to be weighed off against the potential population-level health effects of these policies in various international contexts.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,226
Score d'incertitude au seuil0,450

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,051
Tête enseignante GPT0,330
Écart entre enseignants0,279 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations7
Publié2021
Routes d'admission2
Résumé présentoui

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