Critical unemployment or shortage of the health workforce in West Africa? Unravelling the health labour market puzzle in Guinea, 2024

Abstract

Introduction

The 2016 global strategy on health human resources highlights the health workforce as a cornerstone of sustainable and resilient health systems. Over the last decade, Guinea has launched great reforms to tackle critical health workforce challenges, including shortages and geographical imbalances. We undertook this study to understand the implications of these reforms on the availability, distribution, gender composition, and employment of the workforce in rural areas.

Methods

We conducted a health labour market analysis focusing on HRH data in two regions—N’zérékoré and Kindia—using mixed-methods approach. Data were collected from private and public health facilities and training institutions, complemented by policy documents and literature published between 2018 and 2024. The analysis focused on key indicators of workforce production, availability, distribution, employment and gender equity.

Results

In 2024, the two study regions reported 9,545 skilled health workers across ten health professions, predominantly state-registered nurses (36.7%), auxiliary nurses (29.7%), and midwives (17.8%), with medical doctors constituting only 4.4%. This reflects a density of 2.0 skilled health workers per 1,000 population in the regional health system—triple the official statistics of 2022. However, 61.2% of this workforce was concentrated in urban and peri-urban areas, serving 28% of the population. Health workforce density varied widely across districts, from 3.9 per 1,000 in N’zérékoré to 0.9 in Beyla. Despite increased production, local absorption and employment outcomes remain poor. Of the 21,208 health workers trained locally since 2016, only 23.7% were absorbed by the regional health system, and 64.1% remain unemployed. The overall health worker unemployment rate reached 74.8%, with nurses, midwives, and nurse-aides most affected. Gender disparities were also notable, as women make up 64.4% of the workforce, yet men disproportionately occupy higher-paying roles such as medical doctors, pharmacists, and managers, and represent 77.4% of specialists.

Conclusion

Guinea has made significant progress in skilled health workforce production and availability in rural regions. However, high unemployment and persistent gender inequities threaten the long-term sustainability of these gains. Addressing these challenges will require strengthening the health workforce reporting and financing systems.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12960-026-01087-7.

Introduction

In 2006, the World Health Organization (WHO) identified 36 countries in sub-Saharan Africa (SSA) as experiencing severe shortages of the Health Workforce (HWF) [1]. The West African region was particularly impacted with all 16 countries reporting fewer than 1 health care worker (medical doctors, nurses and midwives) per 1,000 inhabitants—a figure significantly below the WHO minimum threshold of 2.3 per 1,000 [1]. Thereafter, several efforts to develop the HWF were accelerated, employing various strategies to enhance their production, employment, motivation and retention across SSA (see Fig. 1) [2–4]. These efforts have been instrumental in tripling the size of the HWF in SSA over the past decade [5].

Fig. 1.

Historical chronology of health workforce development reforms in Guinea, including the influence of international, regional and national events, policies and programmes, 2000–2024

However, 13 countries in West Africa continue to face critical shortages of the HWF, a situation which hampers their progress towards achieving universal health coverage [6]. The persistent lag of West African countries in addressing the HWF crisis is driven by several factors, including insufficient investment in HWF education, and widespread international recruitment from the region [7]. Rapid population growth, which outpaces HWF development, further complicates efforts to address the crisis [6]. Additionally, a growing body of literature links this HWF crisis in Africa to governance challenges, particularly the substandard quality and incompleteness of HWF data [8, 9].

Like many other West African countries, Guinea has long been facing critical challenges related to the HWF, including shortages, unequal distribution, and performance issues [10]. Almost 20 years ago, the HWF crisis in Guinea was identified as stemming from production and management deficiencies [11]. In response, the government implemented a range of policy efforts and interventions to address the crisis, particularly among the rural population (see Fig. 1). A key intervention was the expansion of health training institutions with support from the private sector, aiming at boosting the HWF production capacity nationwide. Another significant measure involved engaging local municipalities and international organizations in the recruitment of the HWF for service delivery within the public healthcare system [12]. This effort leveraged local taxes, formal revenues of local health facilities, and development aid to remunerate the HWF and to increase their motivation to work and stay in rural areas [12].

Nevertheless, the shortage of HWF continues to be a major bottleneck for the national health system's performance, including its preparedness and response to epidemics [10]. In 2022, the overall stock of the skilled HWF was estimated at 7,198—this corresponds to a density of 0.5 skilled HWF per 1,000 inhabitants in 2022 [13]. One fundamental issue posed by the HWF statistics in Guinea is that they only include employees of the government and formal private sector [14]. In other terms, official data exclude a significant proportion of the HWF, including those contracted by communities and international organizations in the public healthcare system, and self-employed workers in the non-formal private sector [14].

Nevertheless, in recent years, a notable expansion of profit-oriented private health schools has occurred in the Guinean health system, driven in part by efforts to boost the production of the HWF [14]. For instance, the number of private training schools more than tripled in Guinea between 2010 and 2018, producing an average of 3,000 health workers annually [14, 15]. However, only about 8,000 health workers were recruited into the public sector over the past decade [16, 17]. This implies that at least 20,000 newly trained health workers between 2010 and 2020 remained without formal employment in the public sector, and the capacity of the formal private sector to absorb this workforce remains uncertain. For example, in 2024, the national network of private, associative, and faith-based health organizations in Guinea estimated the number of its member health facilities at 1,477, while at the same time the public sector had 2,542 facilities of all types combined, including national referral hospitals, regional and district hospitals, and health centres [18]. This situation raises the question of whether a chronic unemployment problem among the HWF is being overlooked, particularly given that official statistics fail to account for the total stock of health workers, including those not employed by the central government.

Yet, research on the HWF that incorporates data beyond official statistics remains limited. This research gap contributes to the persistent narrative of critical HWF shortages in Guinea, despite the increasingly significant production of the HWF entering the labour market. Such an oversight may result in a misalignment of HWF development priorities, such as an undue emphasis on expanding production capacity. Addressing this issue would require strengthening HWF data systems to effectively analyse and monitor progress towards the milestones of the 2030 Global Strategy on Human Resources for Health (GSHRH 2030) [19]. As a central component of this strategy, the WHO has recently published a Health Labour Market Analysis (HLMA) guidebook to help countries conduct comprehensive analyses of their HWF landscape, thereby facilitating more evidence-informed and context-specific policy development [16].

Some studies have applied HLMA methodologies in Guinea in recent years [14, 16, 20]. However, these studies have had limitations. They either focused solely on maternal healthcare providers [16], explored attributes of rural medical practices [20], or relied on official HWF data that are often incomplete [14, 16]. Moreover, these studies may not accurately reflect the dynamics of the labour market due to recent health system changes. For instance, as part of the post-Ebola health system reforms, more than 6,000 HWF were recruited between 2016 and 2017, primarily for deployment in rural areas [14, 21]. This recruitment included 1,500 medical doctors and 2,000 nurses and midwives [14, 21]. However, following the political instability of 2021, thousands of HWF exited the government payroll through retirement. Official statistics show an overall stock of 11,820 skilled HWF in 2021 compared to 7,198 in 2022, indicating that nearly 5,000 HWF left the public sector payroll during this period in Guinea [13]. The current state of the HWF availability and distribution in the health care sector is therefore not up to date nor precise enough.

Hence, conducting an updated HLMA was essential to provide insights into the current levels of the HWF and the extent of unemployment within it, particularly following the post-Ebola reforms and political change. Such study could generate evidence to support policy decisions aimed at improving the availability, distribution, and efficient use of the HWF, thereby supporting Guinea to achieve GSHRH 2030 and broader health-related development targets. This HLMA aimed to analyse the HWF education, the labour market dynamics including their supply and demand, and formulate policy options for addressing imbalances in the HLMA in Guinea.

Methods

Study design

This study employed a convergent mixed-methods research design, integrating document review, semi-structured survey questionnaires, and secondary data analysis from health training institutions spanning 2016–2024.

Analytical framework

This study applied the HLMA framework to examine the complex interactions among HWF supply, demand, and governance, including sectoral inefficiencies and dysfunctions [22]. HLMA identifies quantitative mismatches (HWF shortages or surpluses) and skills mismatches (misalignment between training and job requirements), facilitating context-specific policy analysis and enabling cross-national comparisons of HWF dynamics (see Fig. 2) [22]. The framework comprises three principal components:

1. Training or education sector:

Fig. 2.

Health labour market framework for universal health coverage [22]

This component assesses HWF production through public and private medical, nursing, and allied health training institutions [22]. Institutional capacity is influenced by admission policies, curriculum quality, accreditation, and financial support [22–25]. For example, rapid private-sector expansion may augment supply but raises concerns regarding quality assurance, regulatory oversight, and alignment with health system needs. Additionally, graduate–employment mismatches may induce underemployment, unemployment, or workforce migration, affecting health system performance [23, 26].

This study evaluated:

• The number of accredited institutions

• Graduate output and alignment with health system needs requirements.

• 2.Labour market dynamics (HWF supply and demand):

This component examines the interaction between health workers and job market, focusing on HWF availability, employment conditions, and distribution.

The labour market dynamic was assessed through:

• Workforce stock and distribution (public vs private, formal vs informal)

• Demographic characteristics (age, sex, years of experience)

• Geographical distribution by district and region, highlighting disparities

• Income levels and income relativities, comparing wages across professions

• Labour flows or attrition, including retirement, and occupational hazards.

• 3.Policies and regulatory framework:

This component covers policy levers that influence workforce production, employment, distribution, and retention. Governments can implement a set of policy measures to regulate the labour market, including:

• Policies on production: strengthen infrastructure, manage student enrolment, and ensuring adequate teaching staff to optimize workforce training.

• Policies to regulate the private sector: address dual practice, improve training quality, and align private sector contributions with public health objectives.

• Policies to address inflows and outflows: manage migration, attract unemployed HWF, and reintegrate professionals into the healthcare sector.

• Policies to address maldistribution and inefficiencies: enhance HWF productivity, optimize skill mix composition, and implement retention strategies for underserved areas.

However, this component was not included in our study due to feasibility and scope constraints, though policy influences are indirectly considered in workforce distribution and training analyses and are discussed in the discussion section. The fiscal space supporting the HWF development in Guinea was neither assess in this study.

Study setting

Guinea, located in West Africa, had an estimated population of 13 million in 2023, with 71% residing in rural areas and 55% living below the poverty line [27]. The health system is pyramidal, comprising central administrative services (such as national directorates) and, in theory, deconcentrated services (including eight health regions and 38 health districts) [28].

The study focused on Kindia and N’zérékoré regions, (covering 11 districts: 4 urban and 7 rural), capturing variability in HWF supply and demand (see Fig. 3). Kindia is more accessible from the capital, while N’zérékoré faces recurrent outbreaks (Ebola, Marburg, Lassa fever). Both regions have around 2 million inhabitants, though populations are concentrated in the urban districts. Together, these regions represent nearly 30% of Guinea’s health districts, enhancing generalizability of study findings.

Fig. 3.

Study sites

The regional healthcare system is tiered into two distinct levels of care, namely, primary and secondary healthcare:

• Primary healthcare comprises health posts, health centres and private clinics and cabinets. In the region of Kindia, the primary healthcare system is composed of 286 health posts and 57 health centres and 77 private clinics and cabinets. In the N’zérékoré region, this includes 234 health posts; 78 health centres and 28 private clinics and cabinets.

• Secondary healthcare level is composed of improved health centres and district or regional hospitals. In the region of Kindia, this includes 2 improved health centres, and one regional and five district hospitals. In the region of N'zérékoré, this comprises 4 improved health centres, and one regional and five district hospitals.

• The regional and district health directorates are responsible for coordinating and supervising health interventions across the local health system.

In the health education sub-sector, there are eight schools in the region of Kindia and five in the region N’zérékoré [14]. Most of these schools are located in the provincial capitals of Kindia and N’zérékoré [14]. These schools primarily focus on training auxiliary nurses, state-registered nurses, midwives, and laboratory and public health technicians [14]. In 2015, each schools trained on average 1,156 workers; representing 17% of the total HWF trained in Guinea that year [29]. The majority of these trained HWF (54%) were allocated to the region of N’zérékoré, compared to 46% in the region of Kindia [29].

Data collection

Data collection covered two distinct populations: (i) all active health workers in the study sites, and (ii) training institutions. For training institutions, secondary data on the annual number of graduates by profession and sex (from 2016 to 2023) were obtained from the 23 training institutions available in the study sites. The year 2016 was selected as it marks the start of post-Ebola reforms aimed at aligning training supply with national HWF needs. Standardized Excel templates facilitated trend analysis and data verification.

For the health workers, a comprehensive survey was conducted. Snowball sampling identified informal private facilities. In total, 9,545 health workers were surveyed between January and March 2024 using French-language questionnaire administered through Kobo Toolbox—implemented as part of the ArcGIS platform. The survey questionnaire covered sociodemographic characteristics, employment conditions, regulatory mechanisms, and training pathways.

Data analysis

Quantitative data were summarized using descriptive statistics in R v4.0. A geographical equity index (GEI) quantified workforce distribution relative to population, with a composite GEI capturing disparities across health districts. In fact, using the districts’ percentage share of national population as a denominator and their respective percentage share of the public-sector HWF as the numerator, an ‘HRH GEI’ was derived for each of the districts and regions. Thus, the GEI measured the district’s or region’s share of the HWF in relation to its share of the population. With this approach, a perfectly distributed HWF is ideally yield GEI of one. Thus, higher GEI above 1 in a particular region or district reflected health workers distribution skewed in favour of that region or district and vice versa. A composite GEI was also determined as the ratio of the region/district with the highest GEI to the region/district with the lowest GEI which explained the magnitude of inequality between the best staffed region/district and the worst staffed ones.

Qualitative data underwent thematic content analysis; responses were coded, refined, and categorized to elucidate patterns and interrelationships. Findings were integrated, with illustrative quotations complementing quantitative results.

Ethics considerations

This study was approved by the Institutional Review Board at the Institute of Tropical Medicine in Antwerp, Belgium (approval number 1713/23), and by the National Ethics Review Committee in Guinea (approval number 215/CNERS/23). Respondents provided informed consent online by checking a box indicating their voluntary agreement to participate in the survey. All data were collected anonymously.

Results

The findings of this study are presented with the two of the three analytical dimensions of the HLMA framework: the health training sector and labour market dynamics.

Health training sector

Findings reveal notable developments in the health training sector, especially regarding the availability and distribution of training institutions as well as trends in the HWF production across the Kindia and N’zérékoré regions.

Availability and distribution of health training institutions

A total of 23 health training institutions were identified across Kindia and N’zérékoré regions (supplementary file 1). The education sector was overwhelmingly dominated by the private, with 91.3% of institutions under private ownership and 65.2% geographically concentrated in Kindia. Private institutions constituted the primary locus for the training of lower- and mid-level cadres, including auxiliary nurses, state-registered nurses, midwives, laboratory technicians, pharmacy technicians, and public health technicians (supplementary file 1).

By contrast, the training of higher-level professionals—namely medical doctors, dentists, and pharmacists—remains largely centralized outside these regions, predominantly in Conakry. This spatial concentration of advanced training institutions contributes to the maldistribution of the HWF and constraints equitable access to specialized health services within Kindia and N’zérékoré regions.

Trends in health workforce production

Between 2016 and 2023, 21,208 health workers were trained in the two regions, reflecting an estimated average annual training capacity of 2,651. Of this total, 59.7% were produced in Kindia. State-registered nurses constituted the largest share (58.2%) followed by midwives (18.8%) and auxiliary nurses (16.1%) (supplementary file 1).

Longitudinal trends indicated a sustained increase in the output of state-registered nurses and midwives over the eight-year period (see Fig. 4). Specifically, the number of state-registered nurses rose by 166% between 2016 and 2023, while the number of midwives increased by 182%. Conversely, the production of auxiliary nurses experienced a marked contraction, declining by 91% since 2018 (see Fig. 4). This reduction coincided with the implementation of the community health workers (CHWs) policy, which sought to transition auxiliary nurses into CHW cadre. In addition, findings highlight emerging efforts towards diversification of the HWF, most notably with the introduction of new occupational categories. For example, training programmes for pharmacy technicians commenced in 2019 and rapidly expanded, producing 53 graduates by 2023—an increase of 279% over this period.

Fig. 4.

Eight-year trends of health workforce production on the labour market in the regions of Kindia and N’zérékoré in Guinea, June 2024 (N = 21,176)

Labour market dynamics

Current stock, composition, and densities of the HWF

Current stock

Tables 1 and 2 present the composition and densities of the HWF in Kindia and N’zérékoré. As of 2024, the total HWF practising in the two regions was estimated at 9,545 individuals, distributed across 10 professional categories. The largest professional groups were state-registered nurses (36.7%), auxiliary nurses (29.7%), and midwives (17.8%), followed by biologists (7.3%) and medical doctors (4.4%) (Table 1). Among the 420 medical doctors, approximately 9% were specialists in medical or public health, while the remaining 91% were general practitioners.

Table 1.

Characteristics of the practising health workforce in the regions of N’zérékoré and Kindia in 2024 in Guinea, June 2024 (N = 9,545)

Characteristics	Frequency (%)
Professional categories (or composition of HWF)
State-registered nurses	3,502 (36.7)
Auxiliary nurses	2,835 (29.7)
Midwives	1,697 (17.8)
Biologists	695 (7.3)
Medical doctors	421 (4.4)
Lab technicians	166 (1.7)
Public health technicians	151 (1.6)
Allied health professionals (hygienists, psychosocial counsellors, etc.)	44 (0.5)
Pharmacists	24 (0.3)
Pharmaceutical technicians	8 (0.1)
Dentists	2 (0.0)
Health occupational groupsa
Medical doctors	421 (4.4)
Nursing and midwifery professionals	5,199 (54.5)
Nursing/midwifery associate professionals	2,835 (29.7)
Other health professionals	1,090 (11.4)
Age in years
< 25	676 (7.1)
25–34	5,604 (58.7)
35–44	2,468 (25.9)
45–54	578 (6.1)
> 54	219 (2.3)
Average age	33 years
Sex
Female	6,150 (64.4)
Male	3,395 (35.6)
Zone of residence
Urban	5,840 (61.2)
Rural	3,705 (38.8)
Type of health facility
Public	8,953 (93.8)
Private (health clinics or cabinets)b	592 (6.2)
Level of public health facilities (n = 8,953)
Health management office	145 (1.6)
Hospitals	2,354 (26.3)
Improved health centres	312 (3.5)
Health centres	5,074 (56.7)
Health posts	1,027 (11.5)
Others (specialized disease treatment facility, research centre, etc.)	41 (0.4)
Employment status
Permanent salaried	1,706 (17.9)
Temporary salaried	694 (7.3)
Unsalariedc	7,145 (74.8)
Years of experience
< 5	3,528 (37.0)
5–9	3,002 (31.4)
10–14	1,681 (17.6)
> 14	1,334 (14.0)
Year at current position
< 5	6,577 (68.9)
5–9	2,196 (23.0)
10–14	565 (5.9)
> 14	207 (2.2)
Amount of bonus received in the past month (in US Dollar)
0	7,211 (75.5)
1–5	473 (5.0)
6–10	408 (4.3)
> 10	1,453 (15.2)
Administrative promotion in the past 5 years
Yes	1,294 (13.6)
No	8,251 (86.4)
Obtained annual leave last year
Yes	1,955 (20.5)
No	7,590 (79.5)
Current job suffices to cover personal or family needs?
Yes	1,061 (11.1)
No	8,484 (88.9)
Intention to leave
Yes	2,155 (22.6)
No	7,390 (77.4)
Type of health training schools attended
Public	5,090 (53.3)
Private	4,455 (46.7)
Were health training schools located in the study sites
Yes	6,870 (72.0)
No, in other regions of Guinea	2,640 (27.7)
No, abroad	35 (0.4)

^aThis classification follows the health workforce accounts of the World Health Organization

^bThis workforce was distributed across 562 clinics and cabinets, with 64% of these being unlicensed

^cThis staff apparently relies on informal payments from patients, bonuses from vaccination campaigns, and other temporary activities

Table 2.

Geographical distribution of the qualified health workforce in the regions of N’zérékoré and Kindia in Guinea, June 2024

Region / District	Population	District Share of population (%)	Distribution of Health Workers				HWF Density Per 1,000 Population	Geographical Equity Index
			Medical doctors	Nurses	Midwives	Nurse Aides		Medical doctors	Nurses	Midwives	Nurse Aides
N’zérékoré region	2100764	50%	165	1694	855	2129	2,3	0,8	1,0	1,0	1,5
N’zérékoré District	527995	13%	65	770	501	749	3,9	1,2	1,7	2,3	2,0
Macenta District	370859	9%	34	323	98	326	2,1	0,9	1,0	0,6	1,3
Beyla District	434333	10%	13	132	50	186	0,9	0,3	0,4	0,3	0,7
Guéckédou District	386829	9%	23	212	98	454	2,0	0,6	0,7	0,6	1,8
Yomou District	152236	4%	11	115	51	189	2,4	0,7	0,8	0,8	1,7
Lola District	228513	5%	19	142	57	225	1,9	0,9	0,8	0,7	1,6
Kindia region	2073143	50%	258	1808	842	706	1,7	1,2	1,0	1,0	0,5
Kindia District	584655	14%	53	610	287	105	1,8	0,9	1,2	1,2	0,3
Forécariah District	323275	8%	32	183	64	164	1,4	0,9	0,7	0,5	0,7
Coyah District	350904	8%	80	430	179	185	2,5	2,4	1,5	1,3	0,8
Dubreka District	439456	11%	76	329	234	169	1,8	1,6	0,9	1,3	0,5
Télimélé District	374851	9%	17	256	78	83	1,2	0,4	0,8	0,5	0,3
Total N’zérékoré and Kindia	4173907	100%	423	3502	1697	2835	2,0	1,0	1,0	1,0	1,0
Crude geographical Equity between districts							4,5	7,7	4,5	7,7	6,2
Crude geographical Equity between regions							1,3	1,6	1,1	1,0	3,0

Composition and occupational groups

In alignment with the WHO national health accounts, the HWF can be grouped into four broad occupational categories: (i) medical doctors; (ii) nursing and midwifery professionals (state-registered nurses and midwives); (iii) nursing and midwifery associate professionals (auxiliary nurses); and other health professionals including dentists, pharmacists, biologists, and laboratory, public health, and pharmaceutical technicians) (Table 1). According to this typology, nursing and midwifery professionals constituted the majority of the HWF (54.5%) followed by nursing and midwifery associate professionals (29.7%) and other health professionals (11.4%) (Table 1).

HWF density and geographic distribution

In 2024, the overall HWF density was 2.3 per 1,000 inhabitants across the study regions. When restricted to healthcare providers—medical doctors, state-registered, midwives, and auxiliary nurses—the density declined to 2.0 per 1,000 inhabitants (Table 2). Considerable spatial heterogeneity was observed. N’zérékoré exhibited a higher skilled HWF density (2.3 per 1,000) compared to Kindia (1.7 per 1,000), rendering N’zérékoré 1.4 times better staffed. Intra-regional inequalities were more striking: the district of N’zérékoré reported 3.9 skilled HWF per 1,000, while Beyla reported just 0.9 per 1,000, indicating that N’zérékoré was staffed at more than four times the level of Beyla (Table 2).

Professional distribution across districts

Marked disparities were evident across professional groups. The GEI for medical doctors was 7.7, reflecting that Coyah health district (in Kindia) had nearly eight times more physicians than Beyla health district (in N’zérékoré). Midwives exhibited a similar degree of maldistribution, with N’zérékoré reporting nearly eight times the number of midwives compared to Beyla. Significant disparities were also observed for auxiliary nurses (GEI = 6.2) and state-registered (GEI = 4.5), underscoring uneven staffing patterns across health districts (Table 2).

Geographical compensation with lower-skilled HWF

Health districts with fewer medical doctors appeared to compensate by employing more auxiliary nurses (Table 2). For instance, N’zérékoré reliance on auxiliary nurses (GEI = 1.5) contributed to its higher overall HWF density relative to Kindia. Conversely, Kindia, with a relatively higher physician density (GEI = 1.2), exhibited a lower density of auxiliary nurses (GEI = 0.5). This substitution pattern helped sustain HWF availability but simultaneously highlighted systemic reliance on lower-skilled cadres in the absence of adequately distributed skilled professionals (Table 2).

Demographic characteristics

Age distribution

The HWF displayed a markedly young age profile. Overall, nearly two-thirds of the HWF (58.7%; n = 5,604) were aged 25–34 years, while only 2.3% (n = 219) were aged 55 years or older, indicating limited but forthcoming retirements over the next decade (Table 3). Workers aged 45–54 represented 6.1% (n = 578), suggesting that short-term attrition due to retirement will remain modest. This youthful structure was consistent across both regions, with similar age distributions observed in N’Zérékoré (n = 5,360) and Kindia (n = 4,185).

Table 3.

Demographic characteristics of the health workforce by employment status, Guinea, June 2024 (N = 9,545)

Characteristics	Permanent salaried HWF (%) n1 = 1,706	Temporary salaried HWF (%) n2 = 694	Unsalaried HWF (%) n3 = 7,145	Total (%) N = 9,545
Age (in years)
< 25	4 (0.2)	15 (2.2)	657 (9.2)	676 (7.1)
25–34	215 (12.6)	340 (49.0)	5,049 (70.7)	5,604 (58.7)
35–44	858 (50.3)	284 (41.0)	1,326 (18.6)	2,468 (25.9)
45–54	433 (25.4)	44 (6.3)	101 (1.4)	578 (6.1)
> 54	196 (11.5)	11 (1.5)	12 (0.1)	219 (2.3)
Average age	43 years	35 years	31 years
Sex
Male	773 (45.3)	404 (58.2)	2,218 (31.0)	3,395 (35.6)
Female	933 (54.7)	290 (41.8)	4,927 (69.0)	6,150 (64.4)

Age structures varied substantially by professional category. Medical doctors showed the oldest profile, with 13.3% aged 55 years or older (n = 56) and a further 15.5% aged 45–54 (n = 65). In contrast, advanced age groups were far less represented among other cadres: only 1.3% of state-registered nurses (n = 46), 0.9% of midwives (n = 16), and 2.6% of auxiliary nurses (n = 74) were aged 55 years or above (Fig. 5). Midwives and state-registered nurses were particularly young, with around 70% and 65%, respectively, concentrated in the 25–34 age group.

Fig. 5.

Age profile of selected health workers in the regions of N’zérékoré and Kindia in Guinea, June 2024

Overall, the HWF is heavily skewed towards younger age groups, a pattern that contrasts with the older age structures often reported in national HWF statistics. This discrepancy likely reflects the historical focus of national policies on permanent salaried health workers, who tend to be older and more stable in their positions. Indeed, contract type was strongly associated with age: permanent salaried workers had a mean age of 43 years, compared to 35 years among temporary salaried workers and 31 years among unsalaried workers (Table 3). The systematically higher age of permanent staff suggests infrequent recruitment into civil service positions or limited access for younger graduates.

Retirement projections further highlight these disparities. An estimated 11.5% of permanent salaried workers (n = 196) are expected to exit the workforce within the next decade, compared with only 1.5% of temporary salaried workers (n = 10) and 0.1% of unsalaried workers (n = 7). While the overall risk of imminent retirement remained low due to the youthfulness of the workforce, targeted succession planning will be required for older cadres—particularly medical doctors and permanent salaried staff—to ensure continuity of service delivery (see supplementary file 2).

Gender distribution

Women comprised 64.4% of the HWF, particularly concentrated in nursing and midwifery professionals (73.2%) and associate professionals (63.2%) (Table 4). By contrast, men predominated among medical doctors (77/4%) and specialists. Men were also disproportionately represented in health system management roles (2.8% vs 0.8% for women) (see supplementary file 3).

Table 4.

Distribution of health occupational groups by sex among the health workforce in Guinea, June 2024

Characteristics	Female HWF (%) n = 6,150	Male HWF (%) N = 3,395	Total HWF (%)
Health occupational groups
Medical doctors	95 (1.5)	326 (9.6)	421 (4.4)
Nursing and midwifery professionals	3,806 (61.9)	1,393 (41.0)	5,199 (54.5)
Nursing/midwifery associate professionals	1,801 (29.3)	1,034 (30.5)	2,835 (29.7)
Other health professionals	448 (7.3)	642 (18.9)	1,090 (11.4)

Employment status and income relativities

In 2024, approximately three-quarters (75%) of the HWF were unsalaried (Table 1). Gender disaggregation revealed that unsalaried status disproportionately affected women (80.1%) compared to men (65.3) (Table 3). Unemployment rates were highest among nursing and midwifery professionals (57.8%) and associate professionals (30.0%), with women comprising the majority in both categories (see supplementary file 3). By contrast, medical doctors were much less affected by unsalaried status, highlighting a clear professional divide. These patterns point to the intersectionality of multiple vulnerabilities—particularly sex, profession, and contract type—compounding to create greater insecurity for women-dominated cadres such as nurses and midwives.

Qualitative data underscored widespread dissatisfaction with remuneration, primarily linked to insufficient salaries relative to family obligations and the rising cost of living. Below are some quotes illustrating the reason for this dissatisfaction:

“I came from a poor family, and not only did I have to look after my own family, but also my father’s, as I am the only civil servant in the family” Female nurse, 33 years, Kindia.

“My family and children lived in Conakry, where life is extremely expensive. I am the sole provider of financial resources” Male medical doctor, 41 years, Kindia.

My husband doesn’t work, and the conditions under which maternity care is free mean that you can’t earn anything apart from your salary” Midwife, 35 years, Kindia.

To compensate for chronic inadequacies in their salaries, many HWF reported adopting a range of coping mechanisms. These strategies included contracting loans to finance their children’s education, relying on financial support from spouses or extended family members, and accepting in-kind or monetary gifts from patients. Some respondents also reported supplementing their earnings through monthly “motivation bonuses”, typically representing 10–15% of the revenue generated by health facilities. These revenues were primarily derived from the sale of pharmaceuticals and user fees paid by patients.

Additional income sources were frequently cited, including per diems received during training workshops or vaccination campaigns, which were often instrumental in meeting immediate household needs. Others engaged in secondary income-generating activities such as farming, livestock rearing, petty trade, evening provision of home-based care, or the sale of medicines from public facilities, particularly during night shifts. For volunteer staff (also named unsalaried workers), motivational bonuses constituted a key income stream, reportedly representing 10–15% of facility revenues. Interestingly, some volunteers indicated a preference for deployment in remote and hard-to-reach health posts, where the limited number of personnel allowed bonuses to be shared among fewer workers, in contrast to more densely staffed urban facilities.

Labour market flows

The structure of the Guinean health labour market is characterized by significant imbalances between the production of health workers (supply) and their integration (absorption) into the health system (see Fig. 6).

Fig. 6.

Flows of the health workforce in the labour market in Guinea in 2024 (adapted from Kober et al. [30])

Between 2016 and 2023, only 24% of graduates from health training institutions were integrated into the health system, while the trajectories of the remaining 76% remain undocumented. This suggested that the majority either migrated outside the health sector, relocated to other regions, or remained unemployed. The number of university-trained health professionals entering the system is unknown, as the study regions do not host universities offering medical training. However, previous research estimate that approximately 1,000 higher-level health professionals—including medical doctors, pharmacists, and dentists—enter the national labour market annually, predominantly trained in Conakry.

Civil service employment remains the preferred career pathway for most health professionals, offering stability despite the potential for higher remuneration in the private sector. Yet, the absorption of civil servant HWF is constrained and uneven, with marked urban concentration at the expense of rural deployment. Gender disparities are also evident, with men more likely to occupy managerial and specialized positions, while women are concentrated in caregiving roles. To address rural workforce shortages, the state relies heavily on temporary or contractual staff, as well as unpaid volunteers, often with the promise of priority consideration in future recruitment exercises. Employment conditions within the health labour market are thus highly stratified, ranging from permanent civil service contracts to temporary arrangements with international organizations, alongside widespread reliance on unpaid labour, which generates significant job insecurity.

Civil service recruitment via competitive national vacancy announcements has occurred only sporadically—in 2005, 2011, 2016, and most recently in 2024. The infrequency of such recruitment exercises forces many graduates to wait months or years before securing a public-sector position. In the interim, they often work under precarious conditions as volunteers, contractors, or, in some cases, exit the sector entirely. While the scale of international migration of Guinean health workers remains unknown, survey data revealed that 6 out of 10 respondents expressed an intention to migrate abroad, most frequently citing Senegal, Canada, and France as preferred destinations.

The for-profit and non-profit private sectors offer alternative employment opportunities, but their absorptive capacity is limited. Despite high levels of training output, the misalignment between supply and demand remains stark. In health labour market terms, demand is constrained not by a lack of need for health workers, but by the limited fiscal space of governments and their partners to finance and retain them in the public sector. Indeed, only 18% of practising health workers hold permanent government contracts, reflecting persistently low public-sector absorption. Consequently, the majority of the HWF (80%) comprises volunteers or contract staff, many of whom had spent at least 5 years in such arrangements.

This imbalance is further aggravated by the lack of systematic replacement of retirees. Although retirements occur annually, many vacancies remain unfilled for extended periods—sometimes up to 5 years—because recruitment processes are slow, budget allocations are limited, and approval procedures are bureaucratically cumbersome. For example, the large-scale retirement of approximately 5,000 personnel following the recent political change in 2021 further depleted the workforce, exacerbating staffing gaps and disrupting continuity in key services. Although 2,000 new health workers were recruited in 2024, they have not yet been deployed within the health system, leaving the losses from the mass retirement unaddressed and the workforce contraction uncompensated (as for February 2026).

As a coping mechanism, the health system has had to retain several senior officials beyond the statutory retirement age, often due to administrative discretion, the need to preserve institutional knowledge, or gaps in succession planning. Additional bottlenecks—including economic crises, political instability, and periodic workforce audits aimed at eliminating “ghost workers”—further delay new appointments. At the same time, recurrent health crises such as Ebola, Lassa fever, and COVID-19 alongside endemic diseases including malaria, tuberculosis, and HIV have accelerated workforce attrition, particularly among civil servants.

Discussion

From a labour market perspective, supply refers to the willingness of health workers to enter, remain in, and be deployed across the health system, while demand reflects the ability of government and development partners to finance and sustain HWF positions. Taken together, our findings show that Guinea’s health labour market is complex and shaped by a structural mismatch between the supply of and demand for the HWF. On the supply side, the HWF crisis in Guinea has little to do with limited training capacity or low production of graduates. Instead, the main challenges are the unequal distribution of the existing workforce—particularly the persistent shortage of highly skilled cadres, such as medical doctors, at local levels of the health system—and the misalignment between the mix of health cadres and competencies produced by training institutions and the actual needs of the health system. On the demand side, government demand for health workers is very low, accounting for less than a quarter of the available workforce supply. Rather than creating outright workforce shortages, this demand failure has led to increasingly stratified and insecure employment arrangements, ranging from permanent salaried positions funded by the central government to temporary contracts supported by donor-funded projects or local municipalities, and unpaid positions. At the same time, weak HWF data systems and fragmented governance fail to capture the full size and structures of the HWF. This contributes to a persistent narrative of HWF shortages, which promotes policies focused on expanding supply while diverting attention from deeper structural and organizational constraints, including fiscal limitations, fragmented governance, and the low political priority given to health employment.

Uncontrolled growth in the workforce supply

Trend analysis of HWF production showed a sustained increase in the supply of the HWF, largely driven by the rapid expansion of training programmes and significant private-sector investment in health education. However, several indicators suggest that this growth reflects a “flooding strategy” in the HWF supply, in which increased production is not well aligned with other essential components of HWF development [31]. These include training quality, absorption capacity, employment opportunities, equitable distribution, and retention in underserved areas.

First, training institutions were mainly concentrated in urban areas, with some cities hosting more than five schools offering similar programmes. This concentration raises concerns that competition among institutions may prioritize tuition fees and student enrolment over educational quality. In addition, the expansion of training capacity was not matched by growth in health infrastructure. Between 2000 and 2024, the number of district hospitals remained constant at 26, while the number of health centres increased only marginally, from 410 to 432 [11, 18]. This limited expansion may have constrained the capacity of health facilities—particularly in urban areas—to accommodate the growing number of trainees. Consequently, clinical training sites have likely being under increased pressure, with insufficient staff and resources to ensure adequate supervision. This situation may have reduced opportunities for hands-on clinical training and contributed to the graduation of health workers who are inadequately prepared for service delivery.

The urban concentration of training institutions has likely further intensified these challenges by limiting students’ exposure to rural health settings. Combined with limited formal government employment opportunities, this pattern may have reduced graduates’ readiness and willingness to accept postings in underserved areas. This helps explain why the rapid expansion of training has not led to a more equitable geographic distribution of health workers.

Second, available data indicate that the growth in the HWF production was only weakly informed by systematic assessments of health system needs. Policies tended to focus on numerical expansion rather than alignment between workforce skills, numbers, deployment, and actual service demand. For instance, public health technicians trained for managerial and programme-related roles were often redeployed into clinical positions at primary care facilities. This practice reflects pressures associated with workforce oversupply rather than deliberate workforce planning.

Finally, limited absorption of graduates into the health system represents a major constraint. Fewer than a quarter of health graduates were absorbed into the formal public sector, while the professional trajectories of the remaining graduates remain unclear. These individuals may have moved into other sectors, relocated within or outside the country, or remained unemployed [32]. Although this situation has not yet reduced enrolment in health training programmes, it may undermine the long-term attractiveness of health professions in Guinea and contribute to the expansion of the informal healthcare sector, with risks of unsafe and poor-quality care [33]. During the Ebola epidemic, patients’ reliance on informal providers—driven by lower costs, geographic proximity, and social ties—complicated efforts to control transmission, as these facilities were not integrated into formal disease surveillance systems [34]. Moreover, the low rate of absorption of graduates found in our study represents a loss for graduates and their families, who invest substantial resources in education, as well as for the regional health system, which fails to retain a large proportion of the trained workforce [33].

Public-sector demand failure for the workforce

Our findings indicate that overall demand for health workers in Guinea remains high, demonstrating that, notwithstanding the historical reliance on traditional medicine [35–37], the health system continues to require modern health facilities and a skilled HWF. However, government recruitment has not kept pace with this demand. Rather than resulting in an outright shortage of HWF, the labour market in Guinea’s health sector has adapted through self-regulation, absorbing a rapidly expanding supply of trained personnel outside formal public-sector employment. This adjustment has generated a proliferation of employment arrangements and widened inequalities within the health system, while more critically producing unprecedented employment precarity. Such conditions have significant implications for the effective implementation of public policies and for the overall performance of the health system.

A central driver of this demand-side failure is the limited fiscal space available for public-sector employment. Despite substantial HWF needs—particularly in rural and underserved areas—the Ministry of Health faces persistent constraints in integrating experienced, fit-for-purpose but unpaid HWF into the public system. Public service recruitment through competitive national examinations has been sporadic, with major nationwide recruitment exercises occurring only in 2005, 2011, 2014, 2016, and most recently in 2024 [16]. This irregularity has resulted in prolonged delays in the employment of graduates, leaving many health workers in extended periods of uncertainty, sometimes for months or years, before having the opportunity to apply for a formal public-sector position [14].

These fiscal constraints, combined with the health system’s limited capacity to remunerate highly qualified professionals and the lack of adequate financial and non-financial incentives to attract and retain medical graduates in underserved areas [20, 21], have compelled the system to rely disproportionately on auxiliary nurses. This reliance functions primarily as a coping mechanism rather than as part of a deliberate and structured policy reform. While such task-shifting arrangements may offer short-term relief, they raise concerns regarding quality of care, particularly in contexts characterized by limited clinical supervision, inconsistent training standards, and poorly defined scopes of practice. The uneven distribution of medical doctors not only undermines equity in access to quality healthcare but also places a substantial burden on lower-level cadres, who are frequently required to operate beyond their training and competencies.

At the macroeconomic level, HWF unemployment in Guinea is shaped by broader structural constraints common to many low-income countries. Stringent fiscal targets under International Monetary Fund programmes often limit the expansion of public-sector wage bills, thereby restricting governments’ capacity to recruit and deploy additional HWF in a sustainable manner [22, 38]. In Guinea, public health expenditure has consistently remained below standards of government spending, including during the post-Ebola period that prioritized health system strengthening [17].

Youth underemployment is particularly pronounced in Guinea, estimated at approximately 65% across all sectors [39]. Within the health sector, however, underemployment undermines both the implementation of public health policies and the system’s capacity to respond to current and emerging health challenges. Another key implication of insufficient public-sector demand is the fragmentation of human resource governance. Civil servants—recruited and deployed centrally—are managed directly by the central administration of Ministries of Health and Public services, while local health managers are left to oversee volunteers and contractual staff who lack employment protections and formal career pathways.

To retain these non-civil servant health workers, local managers rely on ad hoc incentive mechanisms, such as preferential access to per diems associated with vaccination campaigns and shares of facility-generated revenues (typically 10–15%) [14]. Although these arrangements provide short-term coping mechanisms, they entrench inequities in working conditions, job security, and career development. They also increase patients’ exposure to informal out-of-pocket payments and catastrophic health expenditure. In practice, such bonuses do little to improve workers’ living standards [16], often pushing them to seek alternative livelihoods outside the health sector—such as farming, fishing, or small-scale trading– or to solicit informal payments or gifts from patients.

By contrast, civil servants continue to enjoy privileged access to leadership positions, formal appointments, and in-service training opportunities, further marginalizing non-civil servant personnel despite their essential role in service delivery. Many health workers therefore remain in public facilities under informal arrangements as contractors or unpaid workers, a situation that undermines the effective implementation of key public health policies, including free maternal and malaria care, due to the heightened risk of informal fees and under-the-table payments.

Employment instability also contributes to inefficiencies in service delivery and fuels the rapid expansion of informal and unregulated health facilities, particularly in urban areas such as Conakry and its surrounding districts. In 2023, an estimated 2,000 unregulated clinics were operating in the capital alone. Such developments pose significant risks to patient safety and raise serious concerns for national health security, especially in a context marked by recurrent epidemic-prone diseases. In parallel, a growing number of health workers are exiting the sector entirely or migrating in search of better employment opportunities, resulting in a substantial loss of human capital and further exacerbating inefficiencies in the health labour market.

Policy implications

Our finding calls for actions to regulate the health labour market in Guinea, and a paradigm shift from production-driven strategies towards health labour market-informed workforce governance, in which quality training, employment, and retention are addressed as interdependent components of a single system.

First, HWF policy must move beyond numerical targets towards labour market-aligned workforce planning. Continued expansion of training outputs—particularly through largely unregulated private institutions—without parallel investments in employment creation, regulation, and service delivery risks exacerbating unemployment, informalization, and inefficiencies. Strengthening the regulation of health training institutions through accreditation, licensing, and periodic quality audits is essential to ensure that training outputs meet competency standards and correspond to health system needs. Workforce planning should be grounded in comprehensive health labour market analysis that incorporates skills mix and health system needs rather than relying solely on normative shortage thresholds.

Likewise, strengthening HWF data systems is a foundational requirement for effective workforce governance. The systematic exclusion of non-civil servant health workers from official statistics has distorted perceptions of shortages and weakened planning and regulation. Developing an inclusive HWF information system that captures all practising health workers, regardless of contractual status, is essential for accurate forecasting, transparent decision-making, and coherent coordination across public and private sectors.

Second, strengthening demand for health workers requires addressing the structural constraints limiting workforce absorption, particularly within the public sector. Chronic underinvestment in health and rigid public financial management arrangements have constrained recruitment despite persistent HWF gaps. Elevating HWF investment as a strategic priority within national development agendas is therefore critical. This requires sustained engagement with ministries responsible for health, public service, finance, and education to secure predictable and long-term commitments to health sector employment. Establishing an interministerial mechanism on health employment could enhance coordination across sectors and align training, budgeting, and recruitment decisions. Given fiscal constraints, leveraging public–private partnerships can help strengthen labour market absorption. Incentivizing private clinics, non-governmental organizations, and faith-based providers through service contracts, subsidies, or tax exemptions can create regulated employment opportunities while expanding service delivery in underserved areas. Complementary financing instruments, including debt-to-health swaps and social impact bonds, may further support strategic HWF investments.

Reforming recruitment and deployment systems is essential to correcting geographic and professional imbalances. Highly centralized recruitment processes, combined with fragmented and informal local hiring practices for mid-level professionals, have undermined equity, transparency, and responsiveness to local needs. Decentralizing recruitment authority to regional or prefectural levels under clear national guidelines could improve hiring timeliness and better match workforce deployment to district-level service demands. In parallel, tailored incentive packages for rural service, together with sustained investments in rural infrastructure (including but not limited to health), supervision, and professional support systems, are necessary to address chronic maldistribution of nurses, midwives, and medical doctors.

Third, gender equity must be embedded as a core principle of HWF reform. Despite women constituting the majority of Guinea’s HWF, they remain underrepresented in senior, specialist, and leadership roles. Gender-sensitive recruitment and promotion criteria, transparent decision-making processes, and targeted leadership development and mentorship programmes—particularly in nursing and midwifery—are necessary to address these inequities. Equally important are maternity protection measures and flexible work arrangements that support work–life balance and reduce attrition, especially in rural and underserved settings.

Without such integrated reforms, Guinea risks perpetuating a health labour market characterized by surplus production, persistent unemployment, inequitable distribution, and unmet population health needs. A strategic shift towards demand-responsive, equity-oriented, and data-driven workforce governance is essential to fully leverage the country’s growing health workforce and advance progress towards universal health coverage.

Study limitations

This study has several limitations that warrant consideration. First, the data collection represents a cross-sectional snapshot conducted between January and March 2024. Given the dynamic and policy-sensitive nature of the health labour market—particularly in politically unstable contexts such as Guinea—temporal fluctuations in the supply and demand of the health workforce may not be fully captured. Second, the study was limited to 11 health districts across only two of the country’s eights health regions, representing approximately 30% of the national territory. This geographical limitation may affect the generalizability of the findings to the broader national context. Third, the study did not assess the quality of training or the accreditation status of health training institutions, which are critical dimensions of health workforce development and regulation.

Despite these limitations, the study makes a significant contribution by providing empirical evidence on the health labour market in Guinea—an area where official statistics are often incomplete or outdated. It sheds light on underexplored challenges related to health workforce employment, gender and professional inequalities, and underscores the critical value of using primary data to inform health labour market analyses in low-resource and data-constrained settings.

Conclusion

This health labour market analysis highlights that Guinea has made tangible progress in addressing workforce shortages by increasing the production and availability of skilled health workers, especially in rural regions. Nevertheless, the persistently high unemployment—most notably among nurses and midwives, who are predominantly female—and the continued urban concentration of the workforce point to a deeper structural imbalance between the supply and demand of health workers within the public sector. This misalignment reflects the limited capacity of the public health system to expand demand-side opportunities, ensure decent working conditions, and offer incentives that make rural medical practice attractive and sustainable.

Equally concerning is the critical shortage of medical doctors across all levels of the regional health system, which undermines the capacity to deliver essential and specialized services in remote districts. To address this, the government should consider introducing mechanisms such as return-of-service scholarships or preferential recruitment for rural postings to help improve the availability and stability of medical doctors in underserved areas.

Moving forward, policy attention must shift from focusing solely on workforce production to reinforcing the demand side of the health labour market—through increased public financing, improved rural working conditions, and gender-sensitive career pathways. Better alignment between training institutions and the health system’s public sector needs, supported by dynamic workforce information systems and more effective governance, will be essential for building a responsive, inclusive, and resilient health workforce in Guinea.

Abbreviations

HLMA

Health Labour Market Analysis

HWF

Health workforce

WHO

World Health Organization

SSA

Sub-Saharan Africa

GEI

Geographical equity index

CNERS

National Ethics Review Committee in Guinea

CHW

Community Health Workers

Author contributions

DK, RvDP, and WVD conceptualized the study. DK developed the survey questionnaire, which was critically reviewed by RvDP and AD. Data curation and formal analysis were conducted by DK, RvDP, JVO, and WVD. DK and RvDP led the data analysis with critical inputs from KK, JVO, WVD, and AD. DK drafted the original manuscript, and all authors critically reviewed, commented on, and edited subsequent versions. RvDP and WVD provided overall guidance, supervision, and strategic direction for the project.

Funding

The first author (DK) was supported by a PhD scholarship from the Institute of Tropical Medicine, Antwerp, funded by the Belgian Directorate General for Development (DGD). The funding body had no involvement in the study’s conceptualization, design, data collection, analysis, interpretation, or manuscript preparation.

Data availability

The dataset underlying the results and conclusions of this article is available as part of the article and supplementary file. If additional information is required, the raw data supporting the results of this study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study was approved by the Institutional Review Board at the Institute of Tropical Medicine in Antwerp, Belgium (approval number 1713/23), and by the National Ethics Review Committee in Guinea (approval number 215/CNERS/23). Respondents provided informed consent online by checking a box indicating their voluntary agreement to participate in the survey. All data were collected anonymously.

Consent for publication

All participants have provided consent for the results to be published. Findings were disseminated to local stakeholders across the study sites in October and November 2020 in Guinea.

Competing interests

The authors declare no competing interests.