Infection Risk Prediction in Healthcare Settings: Lessons from COVID-19 Contact Tracing.

Objective: Contact tracing aids epidemic control by enabling early detection and isolation without overburdening healthcare systems despite potential challenges. This study aimed to evaluate the practical application of contact and risk assessment-based models in predicting SARS-CoV-2 infection following exposure among healthcare workers in a large tertiary public university hospital in Türkiye. Materials and Methods: The study was designed as a retrospective cohort study, including contact tracing data from 3389 exposed healthcare workers from March 23, 2020, to October 22, 2021. Contact-based (mask use, contact duration and distance) and exposure risk-assessment-based (low, medium, high-risk) models with and without having symptoms were generated using logistic regression. SARS-CoV-2 infection was defined as having a positive SARS-CoV-2 RT-PCR test result. Adjustments were made to the models for demographic and occupational variables, previous infection, and vaccination. Model parameters were compared. Results: Of 3389 exposed healthcare workers, 2451 underwent RT-PCR testing. Among those tested, RT-PCR positivity was 5.9% (144/2451). Lack of personal protective equipment use (odds ratio [OR]=1.64, 95% confidence interval [CI]=1.03-2.66) and ≥15 minutes of contact duration (1.89, 1.21-3.09) were significantly associated with RT-PCR positivity. In the risk-assessment model, being a high-risk contact increased the odds of RT-PCR positivity (OR=2.76, 95% CI=1.61-5.03). Adding the presence of symptoms to contact-based and risk assessment models improved model parameters (Akaike information criterion [AIC]: from 1086.1 to 1083.1; Tjur's R2: from 0.016 to 0.019, respectively). Conclusion: The inclusion of being symptomatic improved the contact-based and risk assessment-based models. Institutions should be encouraged to incorporate symptom inquiries into risk assessment protocols in response to newly emerging respiratory virus epidemics. Institutions lacking the capacity for extensive contact tracing are recommended, at minimum, to track symptomatic exposed workers for epidemic control.

The presence of symptoms within 6 months after COVID-19: a single-center longitudinal study.

BACKGROUND: Characterizing the post-COVID health conditions is helpful to direct patients to appropriate healthcare. AIMS: To describe the presence of symptoms in COVID-19 patients within 6 months after diagnosis and to investigate the associated factors in terms of reporting symptoms. METHODS: Data of DEU-COVIMER (a telephone interview-based COVID-19 follow-up center established in a tertiary care hospital) was analyzed for SARS-CoV-2 RNA positive participants aged ≥ 18 years from November 1st, 2020, to May 31st, 2021. Symptom frequencies were stratified by demographic and clinical characteristics at one, three, and 6 months after diagnosis. With the patients who had symptoms at baseline, generalized estimating equations were applied to identify the factors associated with reporting of symptoms. RESULTS: A total of 5610 patients agreed to participate in the study. Symptom frequency was 37.2%, 21.8%, and 18.2% for the first, third, and sixth months. Tiredness/fatigue, muscle or body aches, and dyspnea/difficulty breathing were the most common symptoms in all time frames. In multivariate analysis, older age, female gender (odds ratio OR 1.74, 95% confidence interval 1.57-1.93), bad economic status (OR 1.37, 1.14-1.65), current smoking (OR 1.15, 1.02-1.29), being fully vaccinated before COVID-19 (OR 0.53, 0.40-0.72), having more health conditions (≥ 3 conditions, OR 1.78, 1.33-2.37), having more symptoms (> 5 symptoms, OR 2.47, 2.19-2.78), and hospitalization (intensive care unit, OR 2.18, 1.51-3.14) were associated with reporting of symptoms. CONCLUSIONS: This study identifies risk factors for patients who experience post-COVID-19 symptoms. Healthcare providers should appropriately allocate resources prioritizing the patients who would benefit from post-COVID rehabilitation.

Transmission dynamics and timing of key events for SARS-CoV-2 infection in healthcare workers.

BACKGROUND: Healthcare workers (HCWs) have increased risk for SARS-CoV-2 infection via contacts in hospitals, as well as via transmission in the community. Serial interval, which is defined as the time between symptom onsets in an infector-infectee pair, and the incubation period are key parameters in determining the control strategies for COVID-19. This study aimed to evaluate surveillance of HCWs and estimate the serial interval and incubation period of COVID-19. METHODS: A total of 149 HCWs and 36 certain infector-infectee pairs between 19th March 2020 and 1st November 2020 in a university hospital were included in the study. Epidemiological characteristics were recorded. Serial interval and incubation period were estimated using parametric accelerated failure time models. RESULTS: Forty HCWs (26.8%) were detected via contact-based surveillance. Of 100 HCWs epidemiologically linked with a confirmed COVID-19 case, 36 (36%) had contact with a colleague. The median serial interval was 3.93 days (95% CI: 3.17-4.83). Of symptomatic HCWs, 97.5% had developed symptoms 13.71 (95% CI: 9.39-18.73) days after symptom onset of the primary case. The median incubation period was 3.99 (95% CI: 3.25-4.84) days. Of symptomatic HCWs, 97.5% developed symptoms within 9.49 (95% CI: 6.75-12.20) days after infection. CONCLUSIONS: The serial interval and the incubation period of COVID-19 in HCWs were shorter than in the general population. Rigorous contact tracing and isolation of infected HCWs could have resulted in shorter serial intervals. Implementation of more stringent in-hospital control measures focussed on transmission between HCWs should be considered.