Drivers of Ebola Virus Disease Resurgence in DRC: A Root Cause Analysis of the 16th Outbreak in Mweka, Kasai Province (2025)

Simple Summary

In 2025, an outbreak of Ebola occurred in Mweka and was found to be a new spillover of the virus from animals to humans, closely related to an earlier outbreak identified in 1976. Changes in the environment, such as deforestation, the consumption of wild animals, and climate-related movement of animal hosts, increased the risk of this type of outbreak, especially in communities living near forests. Delays in identifying the outbreak led to several deaths, including among healthcare workers, and highlighted weaknesses in disease monitoring and early warning systems. Limited laboratory capacity and reliance on centralized testing slowed confirmation of the outbreak. At the same time, other diseases such as mpox, cholera, and malaria were affecting the region, placing additional pressure on the health system. These challenges show the need for faster local testing, stronger community involvement, and better coordination between human, animal, and environmental health efforts to prevent and control future outbreaks.

Abstract

In 2025, the Democratic Republic of the Congo (DRC) experienced its 16th Ebola Virus Disease (EVD) outbreak, centered in the Bulape Health Zone of Kasai Province, amid multiple concurrent epidemics and limited health infrastructure. Genomic sequencing revealed a novel zoonotic spillover genetically related to the 1976 Yambuku strain. A Root Cause Analysis (RCA) using the “5 Whys” framework, integrating epidemiological data, genomic analysis, and surveillance reports, identified key contributors to delayed detection and response, with comparative insights drawn from the 2018–2020 North Kivu outbreak. The Mweka outbreak resulted in 28 confirmed, probable, or suspected cases and 15 deaths, including four healthcare workers. Root causes included inadequate ecological surveillance, weak community alert systems, diagnostic delays due to reliance on centralized laboratories, health system overload from concurrent outbreaks, and structural underfunding of preparedness and coordination. Unlike North Kivu, where security issues drove response delays, systemic and ecological vulnerabilities predominated in Mweka. These findings highlight how ecological and structural weaknesses facilitate novel Ebola spillovers and their escalation, emphasizing the need for sustained investment in One Health surveillance, decentralized diagnostics, and resilient public health governance to strengthen outbreak response capacity.

1. Introduction

Ebola Virus Disease (EVD) continues to pose a serious threat to global public health. While most outbreaks have been concentrated in Africa, the 2014–2016 West African Ebola epidemic demonstrated how quickly the disease can escalate into an international crisis. Its high fatality rate, potential for cross-border spread, and need for strict containment measures have led the World Health Organization to classify it as a priority disease for research and emergency response [1].

In North America, substantial investments have been directed toward EVD prevention and control. This includes the development and deployment of vaccines such as the rVSV-ZEBOV vaccine, which has played a key role in outbreak containment [1]. Organizations like the Centers for Disease Control and Prevention and the Public Health Agency of Canada have also contributed expertise, personnel, and logistical support during major outbreaks in Africa [1].

Australia’s involvement has largely focused on financial contributions and international health deployments. The country has supported emergency response missions coordinated by the World Health Organization while also contributing to vaccine research and broader global health initiatives [2,3].

In Asia, countries such as China and India have provided both logistical and technical assistance. Their efforts include participation in collaborative research, as well as the construction and strengthening of healthcare infrastructure in regions affected by EVD [3].

European contributions have been equally significant, combining field operations with advanced scientific research. Organizations like Médecins Sans Frontières have deployed frontline medical teams, while the European Centre for Disease Prevention and Control has supported genomic surveillance efforts. Research institutions such as the Institute of Tropical Medicine have also made important contributions in sequencing and bioinformatics [4,5].

Despite global support, Africa remains the epicenter of EVD outbreaks. The Democratic Republic of the Congo has reported 16 outbreaks since the virus was first identified in 1976. Ongoing challenges in surveillance, diagnostics, and overall health system resilience continue to hinder effective response efforts [4].

The 16th outbreak, which occurred in Mweka in 2025, unfolded alongside other public health emergencies, including mpox, cholera, and malaria. This convergence of crises underscored critical gaps in the country’s capacity to manage multiple outbreaks simultaneously and highlighted the need for more integrated health system responses [4].

This report was conducted to systematically identify and understand the upstream factors and operational failures that led to the resurgence of EVD in Mweka, Kasai Province (2025). The findings are intended to inform sustainable health systems strengthening, outbreak preparedness, and response strategies in the DRC and comparable settings.

2. Methods and Materials

2.1. Cases

Case identification relied on a combination of active and passive surveillance strategies designed to maximize the sensitivity and timeliness of detection during the outbreak period. Active surveillance included field-based epidemiological activities such as systematic contact tracing, daily follow-up of identified contacts, community event-based surveillance, and rapid investigation of alerts generated by community informants. Field investigation teams conducted door-to-door case searches in affected and surrounding areas to identify individuals meeting the suspected case definition, particularly in locations with limited healthcare access or delayed reporting.

Passive surveillance was conducted through routine reporting systems embedded within health facilities, where clinicians and surveillance officers reported suspected cases using standardized case definitions. Weekly and, when required, daily reporting channels were used to ensure the rapid escalation of alerts. Laboratory request forms and admission registers were cross-checked to identify missed or inconsistently reported cases.

To strengthen case detection and validation, field teams conducted retrospective reviews of outpatient and inpatient registers, triaged emergency room logs, and mortality records to identify unreported suspected cases and deaths potentially related to the outbreak. Epidemiological investigations were carried out for each confirmed or probable case to reconstruct exposure histories, identify transmission chains, and map geographic clustering.

These efforts were supported by the triangulation of multiple data sources, including situation reports from the Ministry of Health, real-time updates from the World Health Organization, and data from established national and subnational surveillance platforms. Integration of these datasets improved completeness, reduced reporting delays, and enhanced the overall sensitivity and specificity of case detection [4,5,6,7].

2.2. Analytical Study and Rationale

A Root Cause Analysis (RCA) was conducted to systematically identify the underlying drivers of the outbreak, using the 5 Whys framework as the primary analytical tool, complemented by systems thinking. The 5 Whys technique was applied iteratively to each major epidemiological finding (e.g., delayed detection, amplification of transmission, and health system response gaps) to trace observed events back to their fundamental causes rather than stopping at proximate explanations.

Systems thinking was incorporated to examine the outbreak as an interconnected set of components within the broader health system. This included an assessment of surveillance infrastructure, laboratory capacity, workforce availability, community engagement mechanisms, and logistical response systems. The approach allowed for the identification of reinforcing feedback loops, bottlenecks, and points of system failure that contributed to sustained transmission and delayed containment.

The analysis further explored structural determinants such as healthcare access barriers, ecological conditions influencing zoonotic spillover risk, and operational constraints affecting response speed and coordination. Attention was given to interactions between these domains, such as how weak surveillance systems compounded delays in laboratory confirmation and how limited community trust affected case reporting and contact-tracing effectiveness.

To contextualize the findings, a comparative analysis was undertaken with previous Ebola virus disease outbreaks, particularly the 2018–2020 North Kivu outbreak in the Democratic Republic of the Congo. This comparative approach enabled the identification of recurring systemic weaknesses, including delayed alert verification, fragmented coordination structures, and resource constraints during surge periods. Lessons learned were synthesized to inform targeted recommendations for strengthening preparedness, early detection, and rapid response capacity [4,6,7].

2.3. Laboratory Methods

Laboratory confirmation of suspected cases was performed using molecular diagnostic techniques in accordance with national and international outbreak protocols. Initial screening utilized GeneXpert platforms for the rapid detection of viral RNA, followed by confirmatory testing using the BioFire Global Fever Panel (BioFire Defense LLC, Salt Lake City, UT, USA) and the Altona RealStar Filovirus RT-PCR Kit (altona Diagnostics GmbH, Mörkenstr, Germany). All assays were conducted in certified biosafety level-appropriate laboratories under strict quality assurance procedures to ensure accuracy and prevent contamination [4].

Positive samples were subjected to genomic sequencing using the Oxford Nanopore GridION platform equipped with R10.4.1 flow cells. Library preparation followed standardized filovirus sequencing protocols, and sequencing runs were monitored in real time to ensure adequate coverage depth. The resulting sequence data achieved approximately 99.97% genome completeness and demonstrated 99.52% similarity to the historical 1976 Yambuku-Mayinga reference strain, enabling high-resolution genetic characterization of the outbreak virus [4].

Bioinformatics processing included basecalling, read filtering, and consensus genome generation using iVar (v1.3.1). Multiple sequence alignment was performed using MAFFT (v7.520) to compare outbreak sequences with reference datasets and contemporaneous strains. Phylogenetic relationships were inferred using IQ-TREE (v2.2.6) under appropriate substitution models, with branch support assessed through bootstrap replication to evaluate evolutionary confidence and transmission clustering patterns [6,7].

2.4. Environmental Study Methods

Environmental investigations were conducted to identify potential zoonotic spillover sources and assess ecological conditions that may have facilitated viral transmission. Field teams collected environmental specimens from high-risk interfaces, including forest-edge communities, animal handling sites, and areas with reported unusual wildlife mortality. Sample types included surface swabs, water samples, and biological material from potential reservoir species where ethically and logistically feasible.

Ecological surveillance data were integrated with field observations to evaluate spatial and temporal patterns of human–animal interaction. Focus was placed on identifying environmental disruptions such as land-use changes, deforestation, and wildlife displacement that may have increased human exposure to potential reservoir hosts. Geographic mapping tools were used to correlate environmental sampling locations with case clusters and suspected transmission zones.

Findings from environmental sampling were analyzed alongside epidemiological and laboratory data to explore plausible transmission pathways and assess consistency with known zoonotic spillover mechanisms. This integrated approach enabled triangulation of ecological and epidemiological evidence to better understand the role of environmental factors in outbreak emergence and propagation [4,6,7].

2.5. Ethics Statement

This Root Cause Analysis was conducted using data derived from routine public health surveillance activities during an officially declared outbreak response. All clinical, epidemiological, and genomic datasets were anonymized before analysis in accordance with national data protection and public health confidentiality requirements.

Ethical oversight was provided through review and authorization by the Institut National de Recherche Biomédicale (INRB) and the Ministry of Public Health. The study adhered to the ethical principles and guidelines established by the DRC National Health Ethics Committee, including provisions for data minimization, confidentiality, and the responsible use of outbreak-related information [4]. No personally identifiable information was accessed or included in the analysis. Genomic data sharing was conducted under pre-publication agreements to ensure responsible dissemination while maintaining scientific collaboration and outbreak transparency. All procedures were aligned with ethical standards for outbreak investigations and public health emergency research [4].

This RCA was conducted using data collected through routine public health surveillance during an officially declared outbreak. All genomic sequencing and clinical data were anonymized according to DRC national health policies and reviewed by the Institut National de Recherche Biomédicale (INRB) and the Ministry of Public Health [4]. The analysis adhered to ethical guidelines from the DRC National Health Ethics Committee. No personally identifiable information was used, and genomic data were shared under pre-publication agreements [4].

2.6. Finding Methods

Case identification relied on a combination of active and passive surveillance strategies. Active surveillance involved field-based activities such as contact tracing, community alert monitoring, and targeted investigations. Passive surveillance was conducted through routine reporting systems within healthcare facilities, allowing for continuous detection of suspected cases [4].

To enhance detection, field teams also reviewed health facility records and conducted epidemiological investigations. These efforts were supported by multiple data sources, including reports from the Ministry of Health, situation updates from the World Health Organization, and established outbreak surveillance systems. This integrated approach improved the timeliness and accuracy of case identification [4,5,6,7].

3. Results

3.1. Descriptive Findings

A detailed root cause analysis (

Table 1. Root Cause Summary Table.

Root Cause	Evidence	Key Weakness Identified
Zoonotic Spillover	99.52% similarity to 1976 strain; no linkage to recent cases	Wildlife–human interface unmanaged
Surveillance Failure	Detected only after deaths, including healthcare workers	No community-based surveillance system
Diagnostic Delay	Samples shipped to Kinshasa for confirmation	No regional lab capacity or cold chain logistics
Health System Overload	Ongoing mpox, cholera, and malaria outbreaks	Competing resource demands, weak IPC systems
Structural Gaps	Recurrent outbreaks in the same zones	Fragmented preparedness and poor coordination

) identified several critical weaknesses that contributed to the 16th Ebola Virus Disease (EVD) outbreak in the Democratic Republic of Congo (DRC). The outbreak likely originated from a zoonotic spillover event, evidenced by a 99.52% genetic similarity to the 1976 Yambuku strain and no linkage to recent human cases, highlighting an unmanaged wildlife–human interface [4]. Surveillance systems failed to detect the outbreak early, with cases identified only after deaths had occurred—including among healthcare workers—reflecting a lack of community-based surveillance [4]. Diagnostic confirmation was delayed due to reliance on centralized laboratories in Kinshasa and the absence of regional lab capacity and cold chain logistics [4]. Concurrent epidemics of mpox, cholera, and malaria further strained health system resources and weakened infection prevention and control practices [1,8,9]. Structural gaps such as fragmented preparedness and poor multisectoral coordination, perpetuated the vulnerability of affected zones to repeated outbreaks [4].

The outbreak was officially declared on 4 September 2025 and was centered in Bulape Health Zone, Kasai Province, with a single suspected spillover case in the neighboring Mweka Health Zone (

Table 2. Summary of Mweka (Kasai, 2025) Ebola Outbreak.

Metric	Value
Outbreak Declaration Date	4 September 2025
Virus Strain	Zaire ebolavirus
Total Cases	28 (confirmed, probable, suspected)
Total Deaths	15
Case Fatality Rate (CFR)	53.6%
Geographic Spread	Bulape (14 deaths), Mweka (1)
Healthcare Worker Deaths	4
Index Case	Pregnant woman, 34 yrs, died 25 Aug
Genomic Similarity	99.52% to 1976 Yambuku-Mayinga
Diagnostic Timeline	Samples shipped to Kinshasa for PCR and WGS

). The causative virus was confirmed as Zaire ebolavirus, genetically like the 1976 strain, supporting the zoonotic spillover hypothesis. A total of 28 suspected, probable, or confirmed cases were reported, with 15 deaths, resulting in a provincial case fatality rate of 53.6%. The index case, a 34-year-old pregnant woman presenting with hemorrhagic symptoms, died rapidly on 25 August, triggering further transmission, including nosocomial infections. Bulape experienced a high case fatality rate of 62%, while Mweka reported one fatal suspected case, raising concerns about surveillance and containment capabilities in this isolated zone. Four healthcare workers died during the outbreak [4].

Table 3. Comparison: Mweka vs. North Kivu EVD Outbreaks.

Dimension	Mweka (Kasai, 2025)	North Kivu (2018–2020)
Total Cases	28	3470 confirmed and probable
Total Deaths (CFR)	15 (53.6%)	2287 (65.9%)
Outbreak Origin	New zoonotic spillover	Linked to the 2014–2016 West Africa strain
Security Context	Stable, remote	Armed conflict, high community mistrust
Surveillance Capacity	Weak, passive case finding	Contact tracing and digital tools are used
Diagnostic Access	Centralized (Kinshasa)	Decentralized labs (e.g., Goma, Beni)
Concurrent Outbreaks	Yes—mpox, cholera, malaria	Minimal during the EVD peak period
Health Worker Infections	4 fatalities	>170 infected
Community Trust	Low literacy, moderate engagement	Resistance, attacks on health workers

provides a comparison between the Mweka and North Kivu EVD Outbreaks.

3.2. Laboratory Findings

Genomic analysis confirmed Zaire ebolavirus with 99.52% similarity to the 1976 Yambuku-Mayinga strain, supporting a new zoonotic spillover hypothesis and indicating no linkage to recent human cases [4]. Diagnostic confirmation was delayed due to reliance on centralized laboratories in Kinshasa, highlighting the absence of regional lab capacity and cold chain logistics [4].

3.3. Environmental Study Findings

The outbreak likely originated from an unmanaged wildlife–human interface, and environmental investigations highlighted structural gaps in ecological surveillance and early warning systems, contributing to delayed detection [4].

3.4. Analytical Results

A Root Cause Analysis (Table 1) identified critical upstream drivers: inadequate ecological surveillance, weak community alert systems, delayed diagnostics, health system overload from concurrent epidemics, and fragmented preparedness with poor multisectoral coordination [4]. Compared to the 2018–2020 North Kivu outbreak, the Kasai outbreak was smaller but similarly exposed systemic vulnerabilities. While North Kivu faced armed conflict and community mistrust, Kasai’s delays were primarily due to geographic isolation, logistical constraints, and ecological risk. North Kivu benefited from decentralized laboratory networks and digital surveillance, enabling faster detection and contact tracing, whereas Kasai relied on centralized confirmation and passive case finding.

3.5. Further Study and Implications

The Mweka outbreak emphasizes the need to strengthen multi-sectoral preparedness in geographically isolated zones, including community-based surveillance, decentralized diagnostics, rapid response logistics, and cross-zone coordination to mitigate future Ebola emergence in known hotspots [4,6,7]. Comparison with North Kivu underscores the differential impact of structural, ecological, and social factors on outbreak dynamics and highlights the value of One Health approaches in risk-prone areas.

4. Discussion

The 2025 Ebola Virus Disease (EVD) outbreak in Mweka was genetically distinct from recent transmission chains and was most closely related to the 1976 Yambuku-Mayinga strain [4]. This supports the conclusion that the outbreak resulted from a novel zoonotic spillover event. Environmental factors such as deforestation, bushmeat consumption, and climate-driven displacement of reservoir species, particularly bats, have increased spillover risks in forest-edge communities [8,9,10]. These findings highlight the importance of a One Health approach that integrates human, animal, and environmental health to reduce future outbreaks.

The outbreak was identified only after multiple fatalities, including among healthcare workers, underscoring critical delays in local surveillance systems [4]. Traditional top-down alert mechanisms proved ineffective in remote zones such as Bulape, where community mistrust and limited health literacy impeded early detection. Strengthening community engagement, implementing mobile reporting tools, and deploying trained community health workers could improve early case identification and reduce mortality [11].

Globally, the outbreak highlights persistent challenges in outbreak preparedness and rapid response. While genomic sequencing was conducted efficiently once samples reached centralized laboratories, the centralization of diagnostics caused substantial delays [4]. Geographic remoteness, limited regional PCR capacity, and weak cold chain logistics hindered timely confirmation. In contrast, decentralized mobile labs in regions like North Kivu previously enabled faster outbreak detection. Expanding GeneXpert systems and biosafety-level diagnostic capabilities in provincial hubs is critical to reducing delays and allowing earlier clinical interventions [12].

Concurrent epidemics of mpox, cholera, and malaria placed additional strain on personnel, laboratories, and financial resources [1,8,9]. This multi-outbreak context weakened the Ebola response, demonstrating the need for integrated emergency management systems, flexible staffing strategies, and consistent funding to sustain effective clinical and public health interventions [13].

Across Africa, repeated EVD outbreaks highlight the interplay of ecological and systemic vulnerabilities. Habitat disruption, human encroachment into wildlife areas, and inadequate surveillance infrastructure increase spillover risks [10]. The 2025 outbreak reinforces lessons from prior African outbreaks: early detection, community engagement, and decentralized laboratory capacity are essential to minimize both clinical morbidity and mortality.

In the DRC, persistent structural weaknesses have limited effective outbreak control. Despite repeated EVD events over the past two decades, health system resilience remains fragile. The recurrence of outbreaks in similar zones reflects insufficient investment in preparedness, poor inter-sectoral coordination, and limited local ownership [14]. Emergency interventions alone are insufficient; long-term solutions must include institutionalized public health training, regional genomic laboratories, and governance reforms to support decentralized outbreak response and strengthen clinical care.

Clinically, delayed detection and confirmation contributed to higher case fatality rates, an increased risk of nosocomial transmission, and limited early therapeutic interventions [4]. Strengthening surveillance and local diagnostic capacity is therefore crucial not only for outbreak control but also for improving patient outcomes. Additional challenges remain in implementing decentralized outbreak response systems across the DRC and other Ebola-endemic regions. Although decentralized laboratory networks can significantly shorten diagnostic turnaround times, their establishment and maintenance require substantial financial investment, a stable electricity supply, biosafety infrastructure, trained personnel, and reliable transport systems for specimens and reagents. Many provincial health facilities continue to face shortages of molecular diagnostic equipment, maintenance support, and skilled laboratory technologists, limiting the sustainability of decentralized surveillance programs [15,16,17]. Furthermore, weak coordination among national authorities, international agencies, and local partners often delays procurement, data sharing, and operational decision-making during emergencies. Strengthening regional collaboration through cross-border surveillance frameworks, laboratory exchange programs, and long-term technical partnerships is therefore essential to improve preparedness and rapid response capacity. Sustained funding mechanisms are equally critical to support genomic sequencing platforms, veterinary surveillance laboratories, workforce retention, and continuous professional development for clinicians, laboratorians, epidemiologists, and field technicians. Recurring Ebola outbreaks also raise important concerns regarding vaccine deployment strategies, outbreak fatigue, and policy implementation. Although vaccines such as rVSV-ZEBOV have improved outbreak containment in previous epidemics, challenges persist in ensuring equitable access, cold-chain maintenance, community acceptance, and rapid deployment in remote settings. Repeated outbreaks in vulnerable regions may contribute to declining public trust, misinformation, and reduced adherence to public health interventions. In addition, inconsistent national and regional policies regarding emergency preparedness, vaccination prioritization, and outbreak financing continue to hinder coordinated responses. Policymakers must therefore prioritize harmonized preparedness frameworks that integrate vaccination campaigns, emergency stockpiles, rapid response teams, and community-based risk communication strategies. Greater political commitment is needed to transition from reactive emergency responses to proactive preparedness models that strengthen long-term health system resilience and reduce the recurrence of future epidemics [16]. The 2023 study by Kabego L. and colleagues demonstrated that a multimodal intervention strategy, including healthcare worker training, IPC supply donation, supportive supervision, and a Pay for Performance Strategy (PPS), significantly improved Infection Prevention and Control (IPC) practices in healthcare facilities during the 2018–2019 Ebola outbreak in Nord Kivu, Democratic Republic of Congo, with IPC scores increasing from 44% at baseline to 79% after eight weeks [15]. The 2025 commentary by Milambo JPM and Businge CB highlighted important clinical and occupational predictors associated with mortality in Ebola Virus Disease, emphasizing the vulnerability of frontline healthcare workers and the need for strengthened occupational protection measures. The 2026 study by Milambo JPM and Benjamin LM evaluated the Democratic Republic of Congo’s progress in implementing International Health Regulations (IHR) capacities using the 2022 e-SPAR and NAPHS assessments, identifying improvements in preparedness alongside persistent gaps in surveillance, workforce capacity, and sustainable outbreak response systems. Together, these studies underscore the importance of integrated IPC strengthening, workforce training, and long-term public health preparedness in improving outbreak response and reducing Ebola-related mortality in the DRC [15,16,17].

From a clinical and public health perspective, the expansion of genomic and veterinary surveillance systems represents a major opportunity to improve outbreak prediction and patient outcomes. Integrating genomic surveillance with veterinary monitoring of wildlife reservoirs, particularly bats and non-human primates, could enhance the early identification of zoonotic spillover risks before widespread human transmission occurs. A strengthened One Health framework involving ministries of health, agriculture, wildlife, and environmental sectors would facilitate coordinated surveillance, shared data platforms, and joint outbreak investigations [17]. However, implementation remains constrained by limited research funding, inadequate laboratory infrastructure, shortages of trained genomic scientists, and insufficient investment in regional biosafety-level laboratories. Expanding international research collaborations, academic exchange programs, and specialized technical training initiatives would support capacity building in endemic countries while promoting sustainable local expertise. Such investments are essential not only for Ebola preparedness but also for strengthening Africa’s broader capacity to respond to emerging infectious diseases and future pandemics.

5. Conclusions

The 2025 Mweka EVD outbreak demonstrates that zoonotic spillovers remain a significant threat, particularly in ecologically fragile regions with weak public health systems. While the DRC has made advances in genomic surveillance and rapid outbreak declaration, the centralization of diagnostics, delayed detection, and limited system resilience continue to hinder effective response. Sustainable outbreak management requires localized detection, decentralized laboratory capacity, improved clinical readiness, and a coordinated One Health approach that addresses ecological, animal, and human health risks. Implementing these measures will reduce outbreak severity, improve patient outcomes, and strengthen resilience against future EVD events.