Survival analysis and mortality predictors of COVID-19 across the six-wave pattern of the pandemic in Monastir, Tunisia
BMC Infectious Diseases·
- DOI
- 10.1186/s12879-026-13659-y
- PMID
- 42271262
- PMCID
- —
- OpenAlex
- W7164183587
- Study type
- Cohort study
- Publisher
- Springer Science and Business Media LLC
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The findings highlight the need for early identification and targeted interventions for high-risk COVID-19 patients, particularly elderly individuals and those with cancer or neurological symptoms. The temporal analysis across six waves provides evidence to inform preparedness and response strategies in similar middle-income country settings.
Structured evidence summary
Research question
The study examined survival rates and mortality predictors across six successive COVID-19 pandemic waves in Monastir, Tunisia, between March 2020 and March 2022.
Study design
This was a prospective cohort study that enrolled all COVID-19 patients admitted to healthcare facilities in Monastir governorate across six full waves of infection. Data were collected by trained residents using a structured questionnaire, and survival analysis with Cox proportional hazards modeling was used to identify mortality risk factors.
Population and setting
The study included all hospitalized COVID-19 patients in Monastir governorate, Tunisia, totaling 5,176 hospitalizations from 58,861 infections recorded during the six-wave period.
Main findings
The 30-day survival rate declined progressively, reaching lowest levels during waves 4 and 5 at 30.6% and 29.5% respectively, with cumulative in-hospital mortality probability of 57.4%. Independent predictors of early hospital death included age over 75 years (HR 3.44), cancer (HR 1.90), and neurological symptoms (HR 1.30), while fever (HR 0.69) and digestive symptoms (HR 0.73) were associated with lower mortality.
Public-health relevance
The findings highlight the need for early identification and targeted interventions for high-risk COVID-19 patients, particularly elderly individuals and those with cancer or neurological symptoms. The temporal analysis across six waves provides evidence to inform preparedness and response strategies in similar middle-income country settings.
Important limitations
This summary relies on the supplied single-article abstract and metadata. A full assessment of study limitations, including potential selection bias from hospital-based sampling, generalizability beyond Monastir governorate, and confounding variables, requires access to the complete published article.
GIDS interpretation
This article would be discoverable through disease classifiers for SARS and COVID-19, geographic filters for Tunisia, and topic categories related to treatment and clinical outcomes. The study provides regional epidemiological context for understanding COVID-19 mortality patterns in North African healthcare settings during the pandemic's evolution through multiple variant waves.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 9 auditable classifier relationships to diseases, places, topics, and study design.