Perceptions of communicable disease surveillance system attributes among key informants at primary healthcare centers in Jeddah, Saudi Arabia

Introduction

Communicable diseases, both emerging and re-emerging, continue to pose substantial global public health challenges. Over the past two decades, experts have emphasized the critical need for establishing robust communicable disease surveillance systems (CDSSs) at national, regional, and global levels to ensure early detection and maintain health security.^1,2 The main goal of surveillance is to provide vital information that guides the development and implementation of effective interventions.³

Communicable diseases such as dengue fever have a relatively higher incidence in Saudi Arabia, particularly in Jeddah, and represent an alarming global concern.⁴ As one of Saudi Arabia’s most active and culturally diverse cities, Jeddah has a population of approximately four million individuals, nearly half of whom are foreigners.⁵ In 2017, the number of international travelers at King Abdulaziz International Airport exceeded 21 million.⁶ This high population mobility, especially during the Umrah and Hajj seasons, substantially increases the risk of importing emerging communicable diseases.⁷ Consequently, implementing an efficient and effective CDSS is crucial as a first line of defense for early disease identification.^8,9

The key components of surveillance evaluation include the system’s priority diseases, structure, core functions, support functions, and quality.¹⁰ While developed countries primarily focus on quality metrics, including timeliness, completeness, and usefulness,¹¹ CDSS evaluation in Saudi Arabia emphasizes service quality and healthcare sector improvement.^7,12,13

Primary healthcare (PHC) providers are critical stakeholders in the CDSS, playing a vital role in policy assessment, development, and the establishment of effective communication channels to deliver appropriate actions.¹⁴ Their involvement in CDSS assessment is essential for fostering mutual understanding and improving system effectiveness.¹⁵ The capacity of primary healthcare centers (PHCCs) to respond rapidly to outbreaks depends on a high-quality CDSS with well-functioning attributes, including timeliness, usefulness, simplicity, acceptability, and flexibility.

Periodic evaluations of the CDSS at PHCCs are necessary to ensure optimal system performance and stakeholder engagement.^15–17 This study aimed to examine CDSS key informants’ perceptions of system attributes at PHCCs, focusing on timeliness, usefulness, simplicity, acceptability, and flexibility.

Methods

This cross-sectional study was conducted at all 45 PHCCs located in Jeddah City between November 2017 and March 2018, excluding those in the peripheral and rural districts of the Jeddah governorate. From each PHCC, one physician was selected as a key informant who was designated to oversee the CDSS at the respective PHCC.

The study employed an electronic questionnaire adapted from Benson et al.,¹⁸ available under a Creative Commons Attribution 4.0 International License. The questionnaire evaluated five key attributes of public health surveillance systems based on the Centers for Disease Control and Prevention guidelines¹⁹: timeliness, usefulness, simplicity, acceptability, and flexibility. The adapted questionnaire²⁰ consisted of three sections: (1) demographic characteristics of key informants, (2) perception assessment of these five CDSS attributes, and (3) potential areas for CDSS improvement. Each attribute was assessed through one to four questions, with alternating positive and negative phrasing to minimize response bias. Responses were recorded using a seven-point Likert-type scale (1=strongly disagree to 7=strongly agree). The adaptation involved terminology modifications to reflect local CDSS processes, while maintaining the original question structure and measurement approach.

A pilot study was conducted at three randomly selected PHCCs to evaluate the adapted questionnaire’s feasibility and reliability. The questionnaire showed acceptable reliability (Cronbach’s alpha = 0.76). The pilot findings supported proceeding with the adapted questionnaire without further modifications. The main study included 42 key informants from the remaining PHCCs.

Data analysis was conducted using Stata Statistical Software (StataCorp. 2015. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP). For each attribute, average points were calculated from the seven-point Likert-type scale responses after reversing scores for negative questions, and frequency distributions were described. Responses were categorized as “agree” (points 5-7) or “disagree” (points 1-3), with the midpoint response (point 4, “neither agree nor disagree”) excluded to minimize central tendency bias. The proportion of participants agreeing with each attribute was then computed. A sensitivity analysis was conducted using three methods to account for midpoint responses: (1) excluding neutral responses, (2) combining neutral responses with “agree,” and (3) combining neutral responses with “disagree.” Statistical significance was set at p ≤ 0.05. Categorical data were analyzed using Pearson’s Chi-squared tests when all expected cell counts were ≥ 5 and Fisher’s exact test otherwise.

Results

A total of 42 key informants of the CDSS at their respective PHCCs were enrolled in the study. After excluding non-respondents (n=2), the final sample comprised 40 participants, yielding a response rate of 95%. Approximately two-thirds of the key informants were male, with a median age of 36.5 years (range: 30–52 years). The median experience in PHC was eight years (interquartile range: 5–11 years).

Family medicine specialists constituted the majority of participants (n=24, 60%), while 16 (40%) had no specialty beyond their medical college education. About half of the key informants (55%) had received CDSS training, with 27% completing their training within the previous two years. Table 1 provides a detailed overview of these characteristics.

Perceptions of CDSS attributes

Key informants’ perceptions of CDSS attributes revealed that 17% of participants selected neutral responses (“neither agree nor disagree”) for all attributes except timeliness, where neutral responses were higher (28%). A greater proportion of participants slightly disagreed with all attributes except timeliness, with about half the level of disagreement observed in other attributes. Acceptability and flexibility had the highest proportions of disagreement. Strong disagreement was rare across all attributes, with acceptability showing the highest level of strong disagreement (7.5%). These findings are detailed in Table 2.

Table 2. Key informants’ perceptions of CDSS attributes.

Level of agreement	Timeliness (N=40)	Usefulness (N=40)	Simplicity (N=40)	Acceptability (N=40)	Flexibility (N=40)
Strongly agree	3 (7.5%)	2 (5.0%)	2 (5.0%)	1 (2.5%)	1 (2.5%)
Agree	9 (22.5%)	1 (2.5%)	6 (15.0%)	3 (7.5%)	4 (10.0%)
Slightly agree	8 (20.0%)	11 (27.5%)	4 (10.0%)	4 (10.0%)	4 (10.0%)
Neither agree nor disagree	11 (27.5)	7 (17.5%)	7 (17.5%)	6 (15.0%)	7 (17.5%)
Slightly disagree	5 (12.5)	12 (30.0%)	13 (32.5%)	10 (25.0%)	10 (25.0%)
Disagree	3 (7.5%)	6 (15.0%)	7 (17.5%)	13 (32.5%)	12 (30.0%)
Strongly disagree	1 (2.5%)	1 (2.5%)	1 (2.5%)	3 (7.5%)	2 (5.0%)

After excluding neutral responses (Method 1), 69% of key informants perceived the CDSS as timely, 42% as useful, 36% as simple, 24% as acceptable, and 27% as flexible ( Figure 1).

Figure 1. Key informants’ perceptions of CDSS attributes using Method 1 (N=40).

The sensitivity analysis evaluated the impact of neutral responses by alternatively including them as agreements (Method 2) or disagreements (Method 3). Method 2 resulted in slightly higher overall attribute scores, whereas Method 3 yielded slightly lower scores. Neither approach revealed significant associations between key informants’ characteristics and their attribute perceptions, confirming minimal central tendency bias ( Table 3).

Table 3. Sensitivity analysis of key informants’ perceptions of CDSS attributes.

Method	Timeliness (N=40)	Usefulness (N=40)	Simplicity (N=40)	Acceptability (N=40)	Flexibility (N=40)
Method 1: “Neither agree nor disagree” excluded	69.0%	42.4%	36.4%	23.5%	27.3%
Method 2: “Neither agree nor disagree” included as part of “agree”	77.5%	52.5%	47.5%	35.0%	40.0%
Method 3: “Neither agree nor disagree” included as part of “disagree”	50.0%	35.0%	30.0%	20.0%	22.5%

Analyzing factors associated with perceptions revealed that key informants with eight or more years of PHC experience reported slightly higher perceptions of the system’s simplicity, acceptability, and flexibility. Those with a family medicine specialty rated the CDSS as simpler, more acceptable, and more flexible but perceived it as less timely and useful. Conversely, key informants who had received CDSS training reported lower perceptions across all attributes. However, statistical analyses showed no significant differences in attribute perceptions based on years of experience, specialty, or training status ( Table 4).

Table 4. Factors associated with CDSS attributes among key informants using Method 1.

Attribute	Overall (N=40)	≥ 8 Years of experience (n=22)	Family medicine specialty (n=24)	Training on CDSS (n=22)
Timeliness	69.0%	62.5% (p=.454)*	66.7% (p=1.000)*	63.1% (p=.431)*
Usefulness	42.4%	37.5% (p=.575)	40.9% (p=.803)	35.0% (p=.284)
Simplicity	36.4%	38.9% (p=.741)	36.8% (p=.947)	35.0% (p=1.000)*
Acceptability	23.5%	25.0% (p=1.000)*	25.0% (p=1.000)*	20.0% (p=.689)*
Flexibility	27.3%	35.0% (p=.263)*	31.6% (p=.698)*	22.2% (p=.697)*

* Fisher’s exact test was used.

Perceived issues and interventions

While 20% of key informants reported good PHC organizational capacity for CDSS, 90% highlighted reduced and challenging staff availability at the PHC level. Regarding possible interventions to improve the CDSS, key informants strongly endorsed addressing staffing gaps (85%) and implementing electronic systems (95%). Using mobile technology and increasing financial resources received moderate support (43% and 58%, respectively) ( Figure 2).

Figure 2. Key informants’ perceived intervention that would benefit the CDSS (N=40).

Discussion

Jeddah’s unique role as the principal gateway for pilgrims from approximately 184 countries makes it one of the largest gatherings of diverse cultures globally.²¹ While the Saudi Ministry of Health has extensive experience managing potential health risks associated with such gatherings, the risk of communicable disease importation and spread remains a substantial concern.²²

Our study revealed varying perceptions of CDSS attributes among key informants at PHCCs. The timeliness attribute received the highest score (69%), surpassing other attributes and findings from comparable studies.^15,21 This relatively high score might be attributed to the implementation of the Health Electronic Surveillance Network at the administrative level, electronic disease reporting at PHCCs, and heightened awareness of emerging diseases.

In contrast, other attributes showed concerning results. The usefulness score (42%) was lower than in similar studies, where most participants actively used generated data and published reports,²³ suggesting potential gaps in CDSS data utilization for disease prevention and control. Similarly, the simplicity score (36%) was notably lower than the 77% reported in a 2016 South African study,¹⁵ possibly due to the absence of a user-friendly electronic system at PHCCs. This finding aligns with an Armenian study²⁴ that identified system complexity as a substantial challenge.

The low acceptability score (24%) suggests reluctance among key informants to engage with the system, potentially due to reported staffing shortages at PHCCs. While concerning, this score is consistent with findings from South Africa’s 2016 CDSS evaluation.¹⁵ Similarly, the flexibility score (27%) highlights challenges in adapting to changing circumstances, echoing findings from an Australian study²³ that identified flexibility as a primary weakness of its system.

Interestingly, years of experience, family medicine specialization, and CDSS training showed no significant association with attribute perceptions. This may indicate ineffective training programs or a lack of prioritization of the system among physicians. The finding that two-thirds of key informants expressed dissatisfaction with the current CDSS is concerning. However, the identified causes, including oversight issues, staffing shortages, and electronic system limitations, provide clear opportunities for improvement.

Conclusion

While the CDSS demonstrates strength in timeliness, substantial improvements are needed in its usefulness, simplicity, acceptability, and flexibility. The absence of associations between CDSS perceptions and key informants’ characteristics highlights the need to reevaluate existing training programs. Critical priorities include addressing staffing gaps, implementing user-friendly electronic systems, and enhancing data utilization mechanisms. Additional quantitative assessments of CDSS attributes, including input from other healthcare sectors, are necessary to validate these findings and improve system quality locally and nationally.