PubMed دسترسی آزاد

Preparedness of the Ghana Health Service for field epidemiology and applied biostatistics: a systematic review protocol of infectious disease surveillance, outbreak investigation methodologies, and statistical modeling capacities in resource-limited settings.

استودیوی صوتی مقاله

پخش حرفه‌ای فارسی و انگلیسی

در حال بررسی نسخه‌های صوتی ذخیره‌شده…

صوت تولیدشده با هوش مصنوعی است. برای کاربرد علمی یا درمانی، متن و منبع اصلی را بررسی کنید.
خواندن هوشمند فارسی و انگلیسی در حال آماده‌سازی صداهای مرورگر…
تنظیم صدای طبیعی و سرعت

صداهایی که در نامشان «Natural»، «Neural» یا «Online» دیده می‌شود معمولاً طبیعی‌ترند. انتخاب صدا به صداهای نصب‌شده در ویندوز و مرورگر شما بستگی دارد.

چکیده اصلی

BACKGROUND: Infectious disease outbreaks pose significant threats to global health security, with resource-limited settings in West Africa bearing a disproportionate burden. Despite sustained investments in field epidemiology training and surveillance system strengthening, no comprehensive systematic synthesis exists of Ghana Health Service preparedness for field epidemiology and applied biostatistics. This protocol addresses the primary research question: What is the current level of preparedness of the Ghana Health Service for field epidemiology and applied biostatistics, as assessed across World Health Organization International Health Regulations core capacity domains? Preparedness is operationally defined as the measurable capacity of the Ghana Health Service to detect, investigate, confirm, and respond to infectious disease events across the eight WHO IHR core capacity domains, including surveillance, human resources, laboratory systems, and response mechanisms. METHODS AND ANALYSIS: This systematic review follows PRISMA 2020 guidelines and is registered with PROSPERO (CRD420261299788). Searches will be conducted in PubMed/MEDLINE, African Index Medicus, African Journals Online, and grey literature sources for studies published from January 2010 to present. Eligible studies include those describing field epidemiology capacity, surveillance system performance, outbreak investigation preparedness, biostatistical capacity, training program outcomes, infrastructure, or health workforce within the Ghana Health Service. Two independent reviewers will screen citations, extract data, and assess quality using study-design-appropriate tools including the JBI Critical Appraisal Checklist, CASP Qualitative Checklist, and Mixed Methods Appraisal Tool. Primary outcomes are overall field epidemiology preparedness level measured using Joint External Evaluation and State Party Annual Reporting scores, and surveillance system performance with outbreak response capacity. Secondary outcomes include field epidemiology workforce capacity, statistical modeling and biostatistical capacity, and infrastructure and governance systems. Narrative synthesis is the primary analytic approach. Meta-analysis will be conducted where sufficient comparable studies with acceptable methodological homogeneity are identified. DISCUSSION: This review will provide the first comprehensive assessment of Ghana Health Service field epidemiology preparedness mapped against WHO IHR core capacities, generating actionable evidence-based recommendations applicable to similar resource-limited settings across Africa. ETHICS AND DISSEMINATION: No ethical approval is required. Results will be disseminated through peer-reviewed publication, conference presentations, and policy briefs for the Ghana Health Service, Ministry of Health, and international stakeholders. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/PROSPERO/view/CRD420261299788, identifier CRD420261299788.

متن کامل اصلی

نسخه دارای مجوز در منبع علمی در دسترس است.

لینک مستقیم از metadata منبع گرفته شده و در تب جدید باز می‌شود.

باز کردن متن کامل

کلیدواژه‌ها

Ghana Health Servicebiostatisticsdisease surveillanceepidemic preparednessfield epidemiologyhealth systems strengtheningoutbreak investigationpublic health capacity
در همین زیرشاخه

مقاله‌های مرتبط

PubMed2026

A divide and conquer strategy for recapitulating whole genome 3D structure using Hi-C data.

The three dimensional (3D) spatial organization of the genome is closely linked to biological functions and can be captured by Hi-C assays through interrogating genome-wide chromatin interactions. Methodologies for inferring 3D structures from Hi-C data summarized as a two-dimensional (2D) contact matrix can be broadly placed within the paradigms of optimization-based and sampling-based. Many optimization-based methods are capable of c…

PubMed2026

Data-adaptive identification of effect modifiers through stochastic shift interventions and cross-validated targeted learning.

In epidemiology, identifying subpopulations that are particularly vulnerable to exposures and those who may benefit differently from exposure-reducing interventions is essential. Factors such as age, gender-specific vulnerabilities, and physiological states such as pregnancy are critical for policymakers when setting regulatory guidelines. However, current semiparametric methods for estimating heterogeneous treatment effects are often …

PubMed2026

Risk estimation and dynamic prediction using discrete-time joint models for longitudinal and multistate data with interval and state censoring.

This paper presents a joint model of multivariate longitudinal data and multistate data with application to modeling and predicting autoantibody development in The Environmental Determinants of Diabetes in the Young (TEDDY) study. The model quantifies the risks of state transitions based on observed time-varying and non-time-varying risk factors. Based on the estimated model, a dynamic prediction approach is suggested to predict future…