Background

Public health surveillance is vital for collecting, analyzing, and interpreting health data to inform decision-making and interventions [1,2]. It monitors population health, detects outbreaks, and optimizes resource allocation [3–5]. A robust surveillance system ensures timely and accurate data to address emerging health concerns [4–6]. Regular assessments are essential for the Integrated Disease Surveillance and Response (IDSR) system, as mandated by world health organization (WHO) [7]. Periodic evaluations of threat detection and tracking systems are essential for adapting to evolving needs and responding effectively to health challenges [6,8–10]. These evaluations assess the functionality of the surveillance system, address the needs of stakeholders, and measure progress toward achieving objectives [8,10–12]. A major challenge facing public health surveillance systems in low- and middle-income countries is the lack of periodic IDSR evaluations [13]. Without conducting regular assessments, public health systems cannot make well-informed decisions or mount agile responses to emerging health risks [10–12,14,15]. Insufficient surveillance systems also impede their ability to optimize processes and strengthen capabilities in line with changing public health priorities and advancements [12,14,15].

A previous study has shown that sub-Saharan Africa’s surveillance shortcomings, which prevented timely identification and containment of emerging outbreaks, contributed to increased spread of illnesses in approximately 30% of previous disease outbreaks investigated, underscoring the importance of building robust monitoring systems [16]. The COVID-19 pandemic highlighted the consequences of insufficient surveillance, as initial detection rates in African countries were less than 20%, hampering efforts to mount effective crisis responses [15]. Evaluative studies conducted between 2015 and 2020 in Zimbabwe, Tanzania, Ghana, Kenya, India, and Iraq [17–21] revealed common mmon deficiencies in surveillance systems across different healthcare settings. A review in Zimbabwe found issues with case detection in 31% of programs [18]; a similar study in Tanzania uncovered inaccurate case definitions being applied in 49% of emerging disease monitoring [22]. Multi-site evaluations in Ghana and Kenya revealed that health facilities correctly diagnosed the causative pathogen in only 56% of enrolled fever cases [17,19], and a retrospective analysis of India’s malaria surveillance data from 2006 to 2010 indicated under-reporting rates exceeded 40% in many districts [21]. A facility-based study in Iraq detected that over 25% of outbreaks in 2019 were not notified to authorities within the mandated 48-hour period [23].

While previous evaluations of disease surveillance in sub-Saharan Africa and the Middle East revealed critical gaps, more thoroughly assessing regional and local surveillance systems is needed to contextualize deficiencies. Most past studies examined national surveillance programs or broad healthcare settings, but few evaluated public health surveillance from frontline health workers’ perspectives. This study addresses that gap by conducting an in-depth assessment of Ethiopia’s Sidama Region’s public health surveillance system at facility and community levels through surveys, interviews, and record reviews. The Sidama Region was purposively selected due to its recent establishment as a standalone region, regular occurrence of epidemics [24], diverse disease patterns within a relatively small geographic area, suitable field visit conditions, and the need for a comprehensive regional surveillance evaluation. The study aimed to identify surveillance practices, challenges, and information sharing between local clinics and regional officials to inform targeted improvements to frontline surveillance skills and outbreak detection capacity.

Materials and methods

Results

A total of 13 districts, 27 public health facilities, 15 private health facilities, 36 health posts, and 48 Health Development Army (HDA) members were included in the evaluation. Standardized checklists, adapted from WHO and CDC guidelines, were used to assess core surveillance functions, supportive functions, and system attributes. Using the a priori performance thresholds defined in the Methods (≥90% for formal facilities, ≥ 80% for community actors), we evaluated adherence across all levels.

Core surveillance functions

Availability of standard case definitions varied across levels: 96% in public facilities, 67% in private facilities, 50% in health posts, and 4% among HDA members. Correct diagnosis of at least one priority disease was observed in 89% of public facilities, 73% of private facilities, 44% of health posts, and 4% of HDA members. Case registers were available in 81% of public facilities, 73% of private facilities, and 86% of health posts. All districts (100%) and public facilities (100%) reported capacity for specimen handling and transport. Written feedback from higher levels was received by 73% of districts.

Regarding epidemic preparedness, 69% of districts had preparedness plans, 61% maintained emergency stocks, and all districts (100%) had a rapid response team. However, only 54% of districts had a dedicated budget line for epidemic response. Adequate surveillance forms in the preceding six months were available in 23% of districts, 15% of public facilities, and 53% of health posts. Data analysis by person, place, and time was performed by 85% of districts, 52–59% of public facilities, 53% of private facilities, and 64–69% of health posts. Trend analysis was performed by 52% of public facilities, 27% of private facilities, and 61% of health posts (Table 1).

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Table 1. Public health surveillance system core activities at regional, district, health facilities, and community levels; by direct observation at facilities.

https://doi.org/10.1371/journal.pone.0349856.t001

Supportive surveillance functions

Availability of national surveillance guidelines was highest in districts (92%) and lowest in public facilities (44%). Supervision in the preceding six months ranged from 92% of districts to 60% of HDA members. Training coverage varied considerably across levels: district-level training reached 69% of staff, compared to only 11% at health posts and 12% among HDA members. A designated surveillance focal person was present in all districts and public facilities (100%), but only 60% of private facilities and health posts had one (Table 2).

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Table 2. Public health surveillance system supportive activities.

https://doi.org/10.1371/journal.pone.0349856.t002

Resource availability for surveillance system

All districts (100%) had a designated data manager. Computer availability was limited: only 8% of districts and 7% of public facilities had computers. Stationery was available in 85% of districts, 92% of public facilities, and 60% of private facilities. Telephone service was available in 54% of districts, 74% of public facilities, 87% of private facilities, and 58% of health posts. Computers with internet access were available in only 18% of public facilities and 7% of private facilities.

Regarding IEC materials, posters were widely available: 77% of districts, 96% of public facilities, 93% of private facilities, and 66% of health posts. Flip charts were present in 62% of districts but only 4% of public facilities. Electricity access varied considerably: 80% of private facilities had electricity, compared to 54% of districts, 52% of public facilities, and only 11% of health posts. Motorcycles were available in 23% of districts, 37% of public facilities, and 13% of private facilities (Table 3).

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Table 3. Available resources at district, health facilities, and community levels of Sidama regional state, Ethiopia, 2023.

https://doi.org/10.1371/journal.pone.0349856.t003

Attributes of surveillance system

Case definitions were easiest to apply in private and public facilities (over 85%), followed by health posts (72%), districts (61%), and HDA members (37%). Time-consuming data collection was most frequently reported by health posts (61%) and public facilities (52%). Reporting formats were highly usable for private facilities (100%) but least usable for HDA members (22%). Difficulty implementing changes was most common at district level (69%) and health posts (47%), while public facilities reported the least difficulty (18%). Data collection formats were clearest in private facilities (93%) and least clear in districts (23%) and HDA members (22%). Complete reports were submitted by all private facilities (100%), but only half of health posts (55%) (Table 4).

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Table 4. Attributes of surveillance system at district, health facilities, and community levels of Sidama regional state, Ethiopia, 2023.

https://doi.org/10.1371/journal.pone.0349856.t004

The system was considered highly useful for detecting outbreaks and estimating disease burden across all facility types (over 90% in most cases), though district-level respondents reported much lower usefulness (15%). Acceptability of surveillance activities was higher in public facilities (70%) than districts (30%). Resource shortages disrupting surveillance were a major concern for public facilities (78%) but less so for districts (30%). Population health-seeking behavior was rated as good by 85% of both districts and public facilities.

Discussion

This study comprehensively evaluated Ethiopia’s IDSR in Sidama Region, revealing substantial disparities in implementation across healthcare tiers. Core capabilities varied markedly between district-level offices and lower-level facilities, including private clinics, health posts, and community actors. Deficiencies in epidemiological data attributes and inconsistent emergency preparedness were also observed. Approximately half of districts maintained complete preparedness plans, budgets, and supplies, while supportive functions such as feedback and data review showed considerable variability, with regular implementation in over half to three-quarters of facilities.

Using the predefined performance benchmarks (≥90% adherence for formal facilities, ≥ 80% for community actors), most sites fell below the adequacy threshold for core surveillance tasks, including case finding and diagnostic capabilities. Specifically, rural health posts and Health Development Army (HDA) workers performed case detection, diagnosis, and record-keeping less frequently than public health facilities, aligning with findings from Tanzania and Kenya [19,20]. Lower-level facilities in Sidama lacked standardized case definitions and encountered difficulties accurately diagnosing priority diseases. Reliance on clinical diagnosis alone in under-resourced areas risks underestimating disease burden, reducing correct treatment, missing atypical cases, and diminishing epidemiological understanding compared to laboratory confirmation. These gaps in case detection and diagnosis can lead to reduced accuracy in disease identification and reporting [19].

The observed disparities likely reflect underlying structural and managerial factors rather than isolated individual performance gaps. District-level offices receive direct budget allocations for training and supervision from the regional health bureau, whereas health posts and HDA members rely on intermittent, often unfunded support from health centers. This cascaded model of capacity building, while efficient for centralized resource allocation, results in a gradual dilution of training quality and reduced frequency of supervision at lower tiers. The 89 percentage-point gap in case definition adherence between public facilities (96%) and HDA members (4.2%) illustrates this cascade effect. Similar patterns have been documented in Tanzania and India [20,21], suggesting that decentralized surveillance systems require explicit bottom-up reinforcement mechanisms. Furthermore, the absence of dedicated budget lines for outbreak response at the district level (54%) indicates that even where structural capacity exists, such as the presence of rapid response teams in all districts, operational readiness remains constrained by financial limitations.

Preparedness resources, including response plans and medical supplies, showed marked lack of uniformity between better-resourced hospitals and less equipped clinics in Sidama, mirroring disparities documented between urban and rural sites in Iraq that jeopardize outbreak response coverage [21]. Most facilities in the region lacked updated outbreak plans and rapid response teams. This can seriously undermine timely and coordinated initial control efforts, surveillance capabilities, and may allow illnesses to spread more widely before detection. The absence of readiness in these facilities indicates an urgent need for comprehensive and up-to-date preparedness plans to ensure coordinated and efficient responses to public health emergencies [23].

The evaluation found inconsistencies in supportive oversight activities, including staff training, guideline distribution, and facility monitoring, between well-supported hospitals and more peripherally located clinics in Sidama. This matches uneven reinforcement documented between urban and rural sites in Maharashtra and Tanzania that fails to strengthen early detection abilities uniformly [20,21]. Variations in surveillance training coverage and supervision frequencies were evident, with lower rates observed at facilities and within communities compared to districts, which demonstrated substantially greater capacity for workforce development and oversight. Inconsistent workforce support, competency gaps, and threats to early detection capabilities stemming from these variabilities can negatively impact the effectiveness of the surveillance system [19–21,29]. Harmonizing training programs and increasing supervision frequencies, particularly at peripheral levels, would promote a standardized approach and improve overall system performance.

Key attributes such as flexibility were positively regarded across most levels, but gaps persisted in data quality and monitoring sensitivity. Similar issues with data quality, analysis, and presentation have been identified in studies conducted in Tanzania and Iraq [20,23]. Poor data recording and reporting from clinics carrying out early detection threatens accurate regional surveillance and delays evidence-based outbreak responses. The very low adherence to case definitions among HDA members (4.2%) reflects not only training gaps but also the fundamental mismatch between clinically oriented case definitions and the practical, symptom-based surveillance feasible at the community level. Addressing these gaps and improving data quality and monitoring sensitivity are essential for enhancing the effectiveness of the surveillance system.

This study revealed substantial disparities in IDSR implementation across healthcare tiers in Sidama Region. Training coverage declined sharply from district to peripheral levels, with only 11% of health posts and 12% of HDA members receiving relevant training, reflecting a clear cascade gap consistent with patterns reported elsewhere in East Africa. In Tanzania, Saleh et al. [20]documented a similar gradient, with training coverage declining from 78% at district level to 34% at dispensary level. Likewise, supervisory visits reached only 61% of health posts in Sidama, comparable to findings from Kenya, where Ng’etich et al. [19]reported that only 41% of health posts had received supervisory visits. Within Ethiopia, our findings align with Tefera A et al. [29], who evaluated the Dangila district surveillance system and similarly identified training gaps (only 45% of health workers trained) and inconsistent supervision as major barriers. However, the present study extends these findings by quantifying the cascade gap specifically at the HDA level (4.2% case definition adherence), a community-tier actor not included in previous Ethiopian evaluations. In Iraq, Hamalaw et al. [23] found that more than 25% of outbreaks were not notified within mandated timeframes, consistent with the preparedness and reporting delays observed in Sidama. Taken together, these cross-country patterns suggest that the challenges identified are not unique to Ethiopia but reflect broader systemic weaknesses in decentralized surveillance systems across comparable low- and middle-income settings.

Limitations and strength

This study has several limitations. First, reliance on self-reported data may introduce social desirability bias, though the substantial disparities observed suggest gaps are real and likely understated. Second, the evaluation focused on structural processes rather than outbreak response or data quality outcomes. Third, purposive sampling of health posts and HDA members limits generalizability to non-participating units; results represent surveillance-active facilities and community actors only. Fourth, inferential statistics were not employed a deliberate choice given the descriptive, evaluative design, non-probability sampling, and hierarchical clustering of observations. Instead, we provide descriptive estimates with confidence intervals and benchmarked interpretations, which are appropriate for systems evaluations.

Despite these limitations, the study has important strengths. It included community-level surveillance actors (health posts and HDA members), a gap often missing in similar evaluations. The design aligned with WHO IDSR frameworks and Ethiopian PHEM standards. The sample (n = 140 across 13 districts, 27 public facilities, 15 private facilities, 36 health posts, and 48 HDA members) provided broad geographic and facility-type coverage. Transparent reporting of performance benchmarks and confidence intervals allows readers to interpret gaps without overreliance on statistical significance.

The use of purposive sampling at lower levels limits generalizability beyond the selected facilities and community actors, and because we selected only facilities with documented surveillance activity, our findings likely overestimate true population-level performance.

Implications and recommendations

The following actionable recommendations emerge from the findings:

1. Establish dedicated outbreak response budgets at district level and ensure regular supply of surveillance forms at health posts.
2. Redesign training programs to reach peripheral levels, supported by simplified case definition job aids and quarterly supervisory visits.
3. Institutionalize routine data quality audits with feedback loops from regional to community levels, using predefined benchmarks as monitoring targets.

Strengthening IDSR requires tier-specific interventions that address cascaded weaknesses at peripheral levels rather than one-size-fits-all approaches.

Conclusions

This study revealed substantial disparities in IDSR implementation across healthcare tiers in Sidama Region. Using predefined performance benchmarks, public facilities met the standard for case definition adherence, while private facilities, health posts, and community-level HDA members fell substantially below the threshold. Training coverage was inadequate at peripheral levels, and dedicated outbreak response budgets were missing in nearly half of districts.

While district-level structures exist, uneven implementation across lower tiers threatens early detection and response capabilities. Strategic prioritization of capacity strengthening at health post and community levels is urgently needed. Targeted interventions including simplified case definition job aids, quarterly supervisory visits, dedicated budget lines, and routine data quality audits would help address the cascaded weaknesses identified in this study. Regular assessments using predefined benchmarks should guide ongoing optimization to ensure reliable outbreak detection and improved public health protection.

Supporting information