COVID-19 training gaps exposed among Iran’s frontline health workers, study finds

Guilan Province, including Rasht, was among the areas affected early in Iran's COVID-19 outbreak. A seroprevalence study conducted in April 2020 estimated that approximately 22 percent of the province's population had been infected, underscoring the substantial burden placed on the local health system, including primary health care services.

The study, published in Discover Public Health, surveyed 297 primary health care workers and 12 managers in Rasht County between May 19 and September 19, 2023. Of 342 worker questionnaires distributed, 297 were completed, yielding a response rate of 86.8 percent. The instruments were developed by the research team from the World Health Organization’s 2020 guidance document on health workforce policy and management in the context of the COVID-19 pandemic response, which identified four key domains for action. The researchers focused on two of them: capacity-building, meaning the training of health workers in contact with patients on COVID-19 tailored to their roles, and role optimization, meaning the reallocation or expansion of tasks to meet service demands amid workforce shortages.

The training results show large differences in coverage across WHO priority training topics. Among the workers surveyed, 90.2 percent reported receiving training in prevention and 80.8 percent in infection prevention and control, while 74.4 percent reported training in contact tracing. But only 30.3 percent reported training in medication safety, 30.6 percent in triage, and 37.7 percent in patient identification. The authors suggest this imbalance may reflect the emphasis on COVID-19-specific infection-control skills during the initial response, while broader clinical-safety competencies received less targeted reinforcement. They note that these gaps are relevant to patient safety and may be associated with preventable errors, that effective triage has been linked to fewer unnecessary visits and more timely referrals, and that accurate patient identification is fundamental to reducing treatment errors.

The gaps extended beyond training content. A majority of workers, 82.5 percent, reported being usually or always required to deliver COVID-19-related care beyond their existing competencies and skills. Meanwhile, 46.8 percent of workers reported not receiving training on teamwork and 42.1 percent reported no training on effective communication, skills that become critical when roles shift rapidly during a health emergency.

The findings also indicate substantial gaps in supervisory support within the primary health care settings studied. Only 17.2 percent of workers described their supervisory visits as supportive, and 35.7 percent reported fewer than three supervisory visits during the previous year. More than half, 55.2 percent, said there was no appropriate supportive supervision structure for health workers assigned to COVID-19 tasks. From the managers’ side, 41.7 percent reported inadequate mentoring and supervision for students, recent graduates, non-specialists, and personnel reassigned to COVID-19-related services. The authors draw parallels with studies in Ethiopia and Rwanda, where supervisory practices were described as unsupportive, checklist-oriented, and fault-finding, and cite international evidence associating supportive supervision with higher provider motivation and quality of care.

Role clarity also suffered. Among workers, 33.0 percent reported that guidelines specifying roles and tasks were unclear, and 45.0 percent reported that the guidelines were not adapted to the local context. On the managerial side, the picture was more mixed: 66.7 percent of managers indicated that in settings with specific skills shortages, health workers’ roles were usually or always optimized to cover both essential and COVID-19-related care, and the same proportion reported that students and recent graduates were assigned to roles appropriate to their knowledge and skills. But all 12 managers reported that telemedicine was not employed to reduce direct patient-provider contact for vulnerable health workers, such as those of advanced age or with comorbidities, despite WHO guidance describing telemedicine as a potential tool for self-screening, triage, and follow-up during the pandemic.

To understand what drove variation in how workers experienced these interventions, the researchers fitted stepwise multiple linear regression models. The final capacity-building model explained 20.1 percent of the variance in capacity-building scores. Supportive supervisory visits were associated with higher capacity-building scores, with a coefficient of 0.353 for workers who said visits were fully supportive compared with those who said they were not, and 0.197 for partially supportive visits. Higher perceived usefulness of training courses was also associated with higher scores, with a coefficient of 0.269. Two workplace categories were associated with lower scores relative to health houses: health posts, with a coefficient of -0.207, and urban-rural health centers, with a coefficient of -0.317.

The role optimization model explained 10.6 percent of the variance. Supportiveness of supervisory visits was again the strongest predictor, with a coefficient of 0.451 for fully supportive visits and 0.220 for partially supportive ones. A higher volume of data collected and reported was associated with higher role optimization scores, with a coefficient of 0.188, and Moraghebe-salamat workers, the urban community health workers, reported lower scores than Behvarzes, their rural counterparts, with a coefficient of -0.142. The authors caution that these mechanisms were not directly measured and that the interpretation should be considered hypothesis-generating rather than causal. They note that Behvarzes complete a structured two-year pre-service education program followed by ongoing in-service training, whereas Moraghebe-salamat are recruited from university graduates and then receive supplementary training, so differences in training pathways may be relevant.

The study has limitations the authors are careful to enumerate. Data were collected roughly three years after the onset of the response, introducing potential recall bias. Managers were interviewed about programs they had helped administer, which may have introduced social desirability bias despite the use of supporting documents. The single-county design limits generalizability, and the cross-sectional design does not permit causal inference. The authors also flag a potential conceptual overlap: one capacity-building item addressed supportive supervision while supportive supervisory visits were also included as an organizational predictor, which may have inflated the observed association. The framework used was workforce-focused and did not directly assess financing, governance, or other system-level dimensions.

The authors suggest that these findings identify several areas for consideration in strengthening primary health care preparedness for future public health emergencies. The authors suggest that strengthening preparedness for future health emergencies may require institutionalizing competency-based training that covers both clinical skills such as triage, medication safety, and case identification and soft skills including communication and teamwork; shifting inspection-focused supervision toward supportive, mentoring-based models; ensuring context-specific role guidelines that are regularly reviewed; expanding digital health infrastructure including telemedicine; and streamlining data-reporting requirements to reduce workforce burden. On that last point, the data tell a nuanced story: 71.4 percent of workers reported that the volume of data collection and reporting interfered with performing core tasks and delivering quality care, yet greater reporting responsibility was associated with higher role optimization scores, a contrast the authors attribute to the dual nature of reporting work, where burdensome data duties may accompany a broader or more visible scope of practice. They recommend a minimal dataset to improve data quality while reducing unnecessary collection. Taken together, the study offers a detailed account of capacity-building and role optimization during the COVID-19 response in one county's primary health care network, with findings that should be interpreted in light of its single-county, cross-sectional design and retrospective self-report data.

Subject of Research: Capacity-building and role optimization interventions for primary health care workers during the COVID-19 pandemic in Rasht, Iran

Article Title: Capacity building and role optimization among primary health care workers in Rasht, Iran, during the COVID-19 pandemic

Article References: Mehdizad, M., Ashktorab, T., Zayeri, F., Mehrabian, F., Zarei, E., Alimoradi, M., & Daneshkohan, A. (2026). Capacity building and role optimization among primary health care workers in Rasht, Iran, during the COVID-19 pandemic. Discover Public Health, 23(1), Article 1719. https://doi.org/10.1186/s12982-026-03224-y

Image Credits: AI Generated

DOI: 10.1186/s12982-026-03224-y

Keywords: primary health care, COVID-19, community health workers, capacity building, role optimization, supportive supervision, Iran, WHO guidance, training gaps, cross-sectional study, health workforce, telemedicine