Evaluation of the National Electronic Disease Surveillance System Amid the COVID-19 Pandemic in Elsahel District, Cairo Governorate, Egypt, 2020
Notice bibliographique
Résumé
Background The Egypt National Disease Surveillance is a routine system established in 2002. The system electronically reports on 41 infectious diseases including COVID-19. Reporting sites include all Egyptian governorates, districts, governmental infectious disease hospitals, and primary health units. Surveillance is essential during the pandemic to detect cases early, describe the epidemiology of health problems, guide priority setting, and plan and evaluate public health policy and strategies. Objective This study aims to evaluate the surveillance system during the pandemic to assess its effectiveness in achieving its objectives and to find and fill the gaps. Methods The evaluation was performed using the Centers for Disease Control and Prevention guidelines. A structured questionnaire was used to evaluate the qualitative attributes including simplicity, flexibility, and acceptability through interviewing surveillance teams at the central level, health directorate, and Sahel district. Quantitative attributes, including completeness, timeliness, and predictive positive value, were performed using COVID-19 surveillance data of Sahel district in March-December 2020. Data were assessed for completeness and accuracy. The usefulness of surveillance was assessed in terms of achieving its objectives and use of data. Results Of 33 respondents, 90% thought that the system was simple, and 77% thought it was acceptable; work overload reduced the acceptability rate. The system is funded by the Ministry of Health and Population and was operational 53% of the time due to connectivity problems. The system was flexible when adapting to include COVID-19 in a short time with minimal cost. It is quite representative, as it covers 60% of the population. Completeness was 82%, positive value predictive was 58%, and data validity was 86%. The median duration between patient admissions and reporting was 2.7 days. Conclusions The evaluation of the Egypt COVID-19 surveillance system indicated that the system partly achieved its objectives in the area of simplicity and flexibility with adequate data quality. There is a need to improve acceptability and timeliness through increasing manpower and to enhance stability through effective connectivity. Expansion of the system to cover all of the Egyptian population is recommended to improve representativeness.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».