مجله اپیدمیولوژی ایران
سال نوزدهم شماره 1 (پیاپی 69، بهار 1402)

Human resources play a crucial role in delivering optimal healthcare services to the population. Expanding primary healthcare coverage requires a heightened focus on the healthcare workforce due to their pivotal role in service delivery. This study aims to evaluate the current workload and staffing requirements for primary health workers and midwives in Kerman, Iran, employing the Workload Indicators of Staffing Need (WISN) methodology.

A descriptive cross-sectional study was conducted in four selected health centers in Kerman, Iran, to estimate staffing requirements across two categories. A total of 118 activities for primary health workers and 89 activities for midwives were identified through the collaboration of expert panels and a comprehensive review of the Iran’s integrated health system. Subsequently, all activities were meticulously timed in each of the four health centers using stopwatches, and WISN ratios and proportions were calculated using Microsoft Excel 2010.

The WISN calculations revealed a surplus in the number of primary health workers in three of the centers: B, C, and D. However, in center A, the workforce in this category is deemed sufficient. Conversely, a deficiency of midwives was noted in two centers, A and B, with WISN ratios of 0.67 and 0.50, respectively, while center C demonstrated an excess of the workforce with a WISN ratio of 2.00. Notably, an average of 50% of the staff workload in both categories comprises supportive and additional activities.

Interestingly, despite 75% of the cases indicating an excess or sufficiency of employees, staff members continue to grapple with high work pressures. This anomaly appears to be linked to the substantial volume of support and additional activities. Furthermore, the intense workload during specific days and hours translates into a pervasive sense of pressure throughout the week. As a potential remedy, introducing a queuing system into the primary healthcare sector could alleviate this issue.

This research aims to investigate the components of Rowe and Kahn's successful aging model, encompassing the absence of disease and disability, high cognitive and physical performance, and active participation in life among the elderly population in Tehran in 2020, considering both genders.

This study utilized a survey approach, involving a sample of 637 individuals aged 60 years and above in Tehran. The sample was selected using a multi-stage cluster sampling method from 22 districts of Tehran, considering the elderly population in each district. Confirmatory structural equation modeling (SEM) was employed to assess whether Rowe and Kahn's model aligns with the collected data.

The study's findings demonstrated that Rowe and Kahn's model exhibited a strong statistical fit (p<0.01). Factor loadings in the overall population model and among the two genders were statistically significant and varied. Across the three dimensions of successful aging (avoiding disease and disability, maintaining physical and cognitive functioning, and continuing engagement with life), avoiding disease and disability was the most strongly associated with successful aging, regardless of gender. However, in the other two dimensions, the significance and strength of participation in life and physical and cognitive function varied based on gender.

Programs to support the physical health of the elderly, especially in chronic diseases resulting from lifestyle choice should be developed, and increasing active participation should be a priority, which requires interventions in youth and middle age.

The publication of outbreak investigation reports is critical for disseminating lessons learned from outbreaks. While there are existing reporting guidelines for outbreak investigations, there is a gap in specific guidelines for reporting food-borne and water-borne outbreaks. This study aims to introduce a specific framework and reporting guideline for food and waterborne outbreak investigations in Iran.

The initial draft of the framework for reporting food and waterborne outbreaks was derived from existing general reporting guidelines for outbreak investigations. Additionally, a systematic review of studies reporting outbreaks of waterborne and foodborne diseases from 2010 to 2022 was conducted without language restrictions to extract relevant information. Expert opinions were then sought to finalize and adapt the reporting guideline.

The reporting guideline framework for outbreaks of waterborne and foodborne diseases consists of eight parts: title, abstract (background, methods, results, conclusion), introduction, methods (study characteristics, study type, variables under investigation), results (participant information, statistical results, laboratory results, environmental investigation results), discussion, conclusion, and conflict of interest.

This specific reporting guideline for food and waterborne outbreak investigations can be utilized by outbreak investigation teams, rapid response teams, and researchers to effectively report the results of outbreak investigations in this domain.

Antibiotics are extensively utilized and constitute a significant portion of hospital drug expenses, posing challenges due to their overuse. Among hospital wards, the intensive care unit (ICU) is a major consumer of antibiotics. This study aimed to assess the antibiotic prescription rates within the ICU wards of Namazi Hospital in Shiraz. 

We retrieved and analyzed electronic prescriptions from all 16 ICU wards at Namazi Hospital in 2020. The data were collected using a checklist that included patient demographics, prescription date, and the number of prescribed antibiotics. The relationship between antibiotic groups and patient demographics was assessed using Chi-square test.

Out of 381,003 electronic prescriptions, 67,002 (17.6%) included at least one antibiotic. Additionally, 5,056 patients (98.9%) received antibiotics. Analysis of the prescriptions revealed that most antibiotics were prescribed for male patients and those under 15 years old (P<0.05). Patients admitted during the winter also received the highest rate of antibiotics (P<0.05). The most commonly prescribed antibiotic groups were beta-lactam and chloramphenicols (32.89%), cephalosporins (19.28%), and glycopeptides (18%).

While less than one-fifth of prescriptions included antibiotics, nearly all patients received them. It is advisable for future studies to evaluate antibiotic prescribing based on prescriptions to provide hospital managers with more precise statistics, enabling appropriate actions for antibiotic stewardship.

Mucormycosis is a severe fungal infection with high mortality, particularly affecting immunocompromised patients. COVID-19 patients, due to their compromised immunity, are also susceptible to mucormycosis. Given the rising prevalence of mucormycosis, this research aims to analyze highly cited articles focused on mucormycosis in COVID-19 patients.

This research employed a citation analysis approach using bibliometric analysis. The study's statistical population comprised articles related to mucormycosis and COVID-19 indexed in the Web of Science database between 1945 and 2023 that received a high number of citations. Histcite and VOS Viewer software were utilized to draw scientific and co-occurrence clusters of words.

Analysis of highly cited articles revealed that among the 1,082 documents published, the top 100 works primarily focused on mucormycosis and COVID-19, histopathological findings, and fungal co-infections, garnering the highest citations. An article by Singh received the highest number of citations. The journal "Mycoses" was identified as an influential journal in the COVID-19 and mucormycosis domain, publishing 10 highly cited articles. Co-occurrence analysis of words highlighted four key thematic clusters related to COVID-19 and mucormycosis, as well as other types of fungal infections. Analysis of the top 100 articles indicated that mucormycosis and COVID-19 clusters had the highest frequency, focusing on histopathological areas and fungal coinfections.

The co-occurrence map of words and emerging topics in mucormycosis, COVID-19, and fungal infections can guide researchers in laboratory research, enhancing their understanding of the disease, related current issues and potential treatment methods. Moreover, it offers valuable insights for authors, journals, and researchers in selecting future research priorities.

Vaccination stands as a paramount achievement in global public health and a key strategy to control COVID-19. Vaccine acceptance is a pivotal determinant of the success or failure of vaccination programs. Leveraging health education models and theories to predict behavioral intention, this study aimed to investigate the determinants of the intention to receive the COVID-19 vaccine among the general population of Urmia using the Health Belief Model (HBM).

This descriptive-analytical study employed a cross-sectional approach among 575 individuals aged over 18 residing in Urmia. Sampling was conducted through the snowball and convenience sampling methods. Data was collected using a valid and reliable electronic researcher-made questionnaire comprising four sections: demographic characteristics, knowledge, HBM constructs, and intention to receive the COVID-19 vaccine. Data were analyzed using descriptive and inferential statistics in SPSS version 16.

The HBM effectively explained 67% of the variance in the intention to vaccinate against COVID-19. Within the model's constructs, individuals' perceived self-efficacy (β = 0.505, P = 0.001) emerged as the strongest predictor of the intention to receive the COVID-19 vaccination. Other influencing factors included perceived susceptibility (β = 0.158, P = 0.001) and perceived barriers (β = -0.109, P = 0.001).

Given the robust predictive ability of the HBM for the intention to vaccinate against COVID-19, this model can be utilized in educational and behavioral programs and interventions. Special emphasis should be placed on effective constructs, particularly self-efficacy, to enhance citizens' willingness to receive the COVID-19 vaccine.

Identification of rotavirus genotypes in children is clinically important. This study aimed to determine the spectrum of rotavirus genotypes and assess their correlation with demographic variables and clinical manifestations in hospitalized children.

To determine rotavirus genotypes, rotavirus positive stool samples of symptomatic children were included in the study between December 2019 and March 2020. RNA extraction and cDNA synthesis for VP7 and VP4 genes were performed following standard protocols. Genotypes were determined using specific primers. Validation of results was done through sequencing and bioinformatic analysis. Data were statistically analyzed using SPSS version 20 and GraphPad version 9.5.0.

Among the infected patients, three genotypes emerged as dominant in the studied population. The study demonstrated a significant correlation between genotype frequency and seasonal variations (p-value=0.0077), as well as between genotypes, hospitalization, and severity of diarrhea. While significantly more types of rotavirus group A were identified with increasing age, no correlation was observed between the genotypes and gender (p-value=0.473). Furthermore, there was no significant association between genotype, dehydration rates, and the presence or absence of fever.

This study revealed a relatively high diversity of rotavirus genotypes in children. The findings suggest the need for further research to validate the identified correlations between certain genotypes and age groups, seasonal variations, clinical symptoms, and the efficacy of available vaccines.