Routine Health Information System (RHIS) Assessment for Artemisinin-based combination Treatment outcomes for Malaria in Kisantu Health Zone, DRC

Routine Health Information System (RHIS) Assessment for Artemisinin-based combination Treatment outcomes for Malaria in Kisantu Health Zone, DRC | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Case Report Routine Health Information System (RHIS) Assessment for Artemisinin-based combination Treatment outcomes for Malaria in Kisantu Health Zone, DRC Antoine Mafwila Lusala, Hiwot Moge, Morenike Oluwatoyin Ukpong, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8957178/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background : Malaria treatment failure remains a significant challenge in the Democratic Republic of Congo (DRC) despite the adoption of Artemisinin-based Combination Therapies (ACTs) since 2005. While the World Health Organization (WHO) recommends periodic Therapeutic Efficacy Studies (TES) for high-transmission countries like the DRC, the practical effectiveness of using the existing Routine Health Information System (RHIS) to capture basic data on potential treatment failures remains unexamined. This study aimed to bridge this gap by evaluating the RHIS in the Kisantu Health Zone, assessing its structural capacity to capture treatment outcomes data, and identifying the challenges faced by health practitioners. The findings are intended to provide evidence-based recommendations to strengthen the RHIS for more timely surveillance of antimalarial treatment outcomes. Method : This qualitative study used a purposeful sampling approach to select seven primary health facilities and key health zone staff. Data was collected through semi-structured interviews on the documentation of therapeutic failures following ACT treatment and a structured document review to assess the system's capacity, existing processes, and associated challenges. Result: Interviews with health facility practitioners and health zone staff revealed a significant gap in the Routine Health Information System’s (RHIS) capacity for malaria surveillance. While facilities handle a high volume of malaria cases using standard RHIS tools, practitioners feel they lack the ability to formally document cases of treatment failure, despite observing them. This is largely due to a lack of a clear mandate from the national malaria control program, which has resulted in an absence of specific indicators and formal training on this issue. The findings indicate that RHIS is currently a passive system for general patient data rather than an active tool for surveillance drug outcomes. Both health facility and health zone staff have proposed feasible, low-cost solutions, including targeted training sessions, dedicated registers, and specific reporting forms, to improve the system's capacity to monitor treatment efficacy. These suggestions highlight that the primary barrier is not technical but a procedural and policy issue that can be addressed with targeted interventions. Conclusion. While the RHIS in the Kisantu Health Zone has the structural capacity to record basic patient data, it is still not an effective tool for the surveillance of anti-malarial drug effectiveness. The primary barriers are procedural and policy-based, stemming from a lack of clear mandate, specific indicators, and formal training for health workers. Implementing the proposed, low-cost interventions—such as targeted training and dedicated reporting tools—could significantly strengthen RHIS, transforming it into a more proactive surveillance tool to support timely and evidence-based public health decisions. Malaria health Information systems treatment failure developing countries Patient Generated Health Data Public Reporting of Health Care Data (MeSH) Introduction Malaria remains a major public health concern in the Democratic Republic of Congo (DRC) 1 , where treatment failure is a significant challenge exacerbated by a complex interplay of factors, including drug resistance, adherence issues 2 , 3 and other 4 – 6 . In response to rising resistance to older antimalarial drugs, the national malaria control program (NMCP) in the DRC adopted Artemisinin-based Combination Therapies (ACTs) in 2005 7 . While these therapies have demonstrated high efficacy transmission 8 , 9 and contributed to a substantial decrease in disease continuous surveillances of their effectiveness is critical to combat the growing threat of drug resistance. Recent therapeutic efficacy studies conducted in the country reported cure rates of approximately 94.7% for ASAQ 10 , and routine health data also show improvements in the country’s malaria control interventions. 11 The World Health Organization (WHO) recommends regular monitoring of antimalarial drug efficacy to inform national treatment policies 12 . In countries with high malaria transmission like the DRC, this is conducted through rigorous Therapeutic Efficacy Studies (TES) at NMCP’s sentinel sites, as these are capable of recruiting sufficient patients for robust analysis. In contrast, countries with low malaria transmission are advised to integrate this monitoring into their routine surveillance systems. Despite the established sentinel site approach in the DRC, it is also possible for RHIS to capture basic data on potential treatment failure, such as patients with persistent fever or persistent parasitaemia 13 after a correct ACT treatment 11 . However, the practical effectiveness of clinical practitioners in identifying, recording, and processing such data through the RHIS remains unexamined. This study evaluates the effectiveness of the national Health Management Information System (HMIS) in the Democratic Republic of the Congo (DRC) in capturing and reporting possible Artemisinin-based Combination Therapy (ACT) treatment failure at both facility and health zone levels. It specifically examines the structural capacity of health facilities and the Kisantu health zone office to identify and document possible treatment failures, the processes through which malaria case data are managed and reported, and the challenges that limit the effective monitoring of drug efficacy. By identifying these gaps, the study aims to generate evidence-based recommendations for strengthening the HMIS to support timely surveillance of antimalarial drug resistance and inform public health decision-making. Methods Study design This study employed a qualitative case study design. This approach is optimal for providing a detailed, in-depth assessment of the current capacity and functionality of the RHIS within a specific real-world context. We assess the structural capacity of health facilities and the health zone office to capture and report possible ACT treatment failures, analyze existing data management processes, and identify challenges that impede effective drug efficacy monitoring. The qualitative method (key informant interviews, structured document review) was used to understand processes, perceptions, challenges and functionality of data capture systems. Study setting The study was conducted in the Kisantu Health Zone, located within the Kongo Central Province of the Democratic Republic of the Congo (DRC). This zone is characterized by a high malaria burden, particularly in the Inkisi Valley area 14 . The selection of this zone is purposive, as it represents a typical high transmission setting where monitoring ACT efficacy is critical. The study focused on two levels of the health system. First is the Health Zone Office: The central administrative unit responsible for data aggregation, analysis, and reporting. The second level is the Primary Health Facilities: the frontline units where patient data is originally captured. Study population At the health zone level, the key respondents were the Head of the Health Zone (Médecin Chef de Zone) and the Nurse Supervisor responsible for malaria programs. At the health facility level, data were obtained from the head nurse or officer-in-charge and the head of the laboratory or the designated laboratory technician in each selected facility. Sample size The study sites have been chosen according to the location in the health zone of Kisantu and the Inkisi valley where malaria is more prevalent in the health zone. Sampling procedure Given the high malaria prevalence in the study area, a purposive sampling technique was used to ensure the selection of information-rich participants who are directly involved in malaria case management and health data reporting. At the health zone level, all key officials (head and malaria supervisor) were invited to participate. At the facility level: Seven facilities were selected based on the following criteria: (i) Geographical location: prioritization of facilities within the high-transmission Inkisi valley. (ii) Facility type: A mix of health centers and general referral hospitals to capture potential variations in capacity. (iii) Patient volume: Selection of facilities with a high volume of malaria cases to ensure adequate data for review. Study procedures Data was collected through two primary methods: Semi-Structured Interviews and a Structured Document Review. Data collection was performed by trained research assistants using pre-tested tools. a) Key Informant Interviews: Semi-structured interview guides with open and closed-ended questions were administered to the identified participants. The guides were tailored to the respondent's level (zone vs. facility). Health Zone Level Questionnaire (10 questions) covered the following: Existence and knowledge of a national protocol for identifying and defining ACT treatment failure. Availability of trained staff on ACT failure follow-up. RHIS tools used for tracking malaria patients and their specific features. Existence of specific indicators for tracing ACT treatment failure within the RHIS. Frequency of data analysis for monitoring treatment efficacy. Procedures for managing and reporting data on suspected treatment failures. Perceived challenges (e.g., logistical, technical, human resources) in reporting ACT failure. Recommendations for resources needed to improve monitoring. Health Facility Level Questionnaire (7 questions) covering: Respondent's role and responsibilities in malaria case management. Data collection tools in use (e.g., curative consultation register, lab register, patient files). The ability of these tools to specifically capture data elements related to treatment failure (e.g., follow-up visits, treatment repetition). Type of data system (paper-based or electronic). Data management and reporting process to the health zone. Awareness of indicators for ACT failure. Facility-level challenges and needed resources. b) Structured Document Review : A checklist was used to perform an objective audit of the existing systems and tools. This review verified the information obtained from the interviews. At the Health Zone Office: The review will focus on the national RHIS reporting canvas (Système National information Sanitaire - SNIS) to check for (i) the presence of fields or modules dedicated to reporting treatment outcomes. (2) the existence of a specific indicator for "suspected or confirmed ACT treatment failure." (3) the completeness and consistency of aggregated data received from facilities. At the Health Facilities: The review examined (i) curative consultation registers: to see if there are columns to record follow-up status or repeated treatments for the same episode. (2) laboratory registers: to assess the linkage between diagnosis (e.g., RDT, microscopy) and patient treatment and outcome. (3) individual patient consultation sheets: to determine if they allow for the documentation of treatment response, including failure symptoms and any change in medication. (4) data reporting forms: to check that facilities are required to report any data on treatment failure to the zone. Results In line with the objective of this study, which was to evaluate the effectiveness of the National Health Management Information System (HMIS) in the Democratic Republic of the Congo (DRC) in capturing and reporting possible Artemisinin-based Combination Therapy (ACT) treatment failure, this section presents the findings of this assessment at both the health facility and the Kisantu health zone office levels. The data presented below are structured to illuminate three key dimensions. Firstly, we present the main result on the existence of tools and the capacity of the health facilities and the health zone office to adequately identify and document probable treatment failures. Secondly, we explore the level of support provided by the health zone office to the facilities regarding the processes governing the management, flow, and reporting of malaria case data, especially the probable treatment failure. These results form the basis of the evidence-based recommendations aimed at strengthening the HMIS for improved public health decision-making. Table 1 Summary of themes identified in participant interviews Themes Description Representatives’ quotes Volume of Malaria Case Management This theme highlights the frequency and volume of malaria cases managed routinely by practitioners in health facilities. We often receive patients who come for outpatient consultations. We receive ≈ 200 suspected cases of malaria per month, ≈ 150 of which are confirmed by RDT. Use of RHIS tools for malaria data collection This theme describes the specific existing tools and registers used by practitioners to record and track data related to malaria cases as part of their routine practice. We use the consultation sheet, laboratory voucher, curative care register and laboratory register to record and track malaria patients’ data Ability to document treatment failure This theme captures the practitioners' perception of the capacity of the current system to properly document and monitor instances of malaria treatment failure. We are unable to document cases of treatment failure, even though we observed cases with persistent fever after treatment. We only have the mention of therapeutic failure as hypothetical diagnosis in the reference ticket as a reason for referral. Possibility of retrospective identification of potential treatment failures This theme looks for a method by which practitioners can retrospectively analyze existing data to identify cases of potential treatment failure. We can count referral tickets that mention that patients were referred for treatment failure. Barriers to recording treatment failure This theme highlights the key reasons for not recording treatment failure data. In the curative care register, we could have registered them as old cases, but we don't do it because we are not asked to We do not pay attention to cases of therapeutic failure. We were never asked to record data on treatment failures. Practitioner-suggested improvements This theme summarizes the direct recommendations from practitioners on how to improve data collection to better capture information on treatment failure. We need a briefing session on identifying and documenting treatment failure cases. We suggest that old cases of therapeutic failure be recorded in the curative care register with the note "therapeutic failure with ACT" in the observation section. The qualitative findings reveal a system with both strengths and significant gaps. Practitioners manage a high volume of malaria cases, utilizing a set of existing RHIS tools that, while foundational, are not designed to capture the nuances of treatment outcomes. These results in a perceived inability to document treatment failure, despite clinical observations of persistent fever in patients. While practitioners have found a workaround for the retrospective identification of treatment failure through referral tickets, this method is not a systematic or proactive solution. The root cause of this data gap lies in systemic barriers to recording treatment failure, including a lack of explicit instructions and formal training. To overcome these challenges, practitioners themselves have proposed tangible solutions, including dedicated briefing sessions and a modification of existing registers, demonstrating both an awareness of the problem and a proactive approach to improving the RHIS's capacity. This suggests that with targeted interventions, the system could be enhanced to support more effective real-time surveillance. Table 2 Outcomes from the head office staffs interview on the capacity of their office to collect and report on ACT treatment failure. Questions Answers Comments Do you have a standardized protocol for identifying treatment failures for malaria? (Yes/No) Yes We have guidelines on malaria case management we call “flowchart for malaria case management” in which instructions are given how to identify and manage ACT malaria treatment failure What tools do you use to track malaria cases? National RHIS canvas DHIS2 Do you have staff trained in methods for monitoring treatment failures? Yes Staff are trained in the use of the flowchart in general, but we do not insist on the identification of the ACT treatment failure detection Do you have access to rapid diagnostic kits (RDTs) and/or microscopy to confirm cases? (Yes/No) Yes All health centers, considered as the entry point of the health care system at least rapid diagnosis test is available, in the referral hospital and all secondary structures, microscopy is available How often do you analyze data to monitor ACT treatment failures? (daily, weekly, monthly, other — specify) Never We do data analysis but not specifically on the ACT treatment failure Do you have key indicators to measure treatment failures? No These cases are included in the persons referred indicator How do you manage data from patients identified as having failed treatment? (archiving, active monitoring, other - specify) We are not able to collect these data The only possibility that the system gives us is to record the number of people referred to the general hospital by giving the reason of reference that should be in that case “ACT treatment failure”. But we do not do that Do you have a mechanism for reporting cases of treatment failure to higher health authorities? No We are not asked to report on any outcomes for treatment, we only report on the people treated. If not, is it possible to report that to higher health authorities? Yes We have to report rare events to the higher health authorities, that is a way we can also use for the ACT treatment failure What are the main challenges encountered in identifying and monitoring treatment failures for malaria? (specify) That is not applicable in the current context The identification of malaria therapeutic failures is not required by the National Malaria Control Program, which results in a lack of specific indicators on that. What additional resources would you need to improve the monitoring of malaria treatment failures? (funding, training, equipment, other - specify) We suggest having: ● A briefing session to draw providers' attention to the identification and monitoring of malaria therapeutic failures ● A specific form completed by the provider when fever or parasitaemia persist after ACT treatment. ● A register where all patients suspected of therapeutic failure will be recorded and the reference to the general hospital mentioned as well as the final result of the microscopy ● An inclusion in the facility reports template of an indicator reporting the number of people referred to the hospital cause of persistence of fever after ACT treatment The table indicates that the supportive staff at the health facilities are aware of the existing RHIS tools and protocols, such as the "flowchart for malaria case management," but they feel there is a disconnect between these general guidelines and the specific task of monitoring for ACT treatment failure. They acknowledge having staff trained in the use of the flowchart, but not with specific emphasis on identifying treatment failure. A key finding is that the head office lacks a dedicated mechanism for tracking or reporting ACT treatment failures. The staff confirms that they do not analyze data for this specific purpose and lack key indicators to measure it, instead lumping these cases into a broader "persons referred" category. While they can and do report "rare events" to higher authorities, this is not a standardized procedure for treatment failure. The primary challenge they cite is the absence of a mandate from the NMCP to identify and monitor these cases, which leads to a lack of specific indicators and a lack of institutional attention. To address these issues, the staff suggests several improvements, including a "briefing session" to raise awareness, a specific form for providers to fill out, a dedicated register to record suspected cases, and the inclusion of a specific indicator in facility reports. These suggestions point to a clear desire for more explicit guidance, dedicated tools, and a formal process for identifying and documenting potential treatment failure cases. Discussion The results reveal a critical disjuncture between existing RHIS protocols and their application for monitoring ACT treatment failure. While health facilities manage a high volume of malaria cases using standard tools, practitioners report a perceived inability to formally document cases of treatment failure. The head office staff confirms this, noting that the system lacks specific indicators and a formal reporting mechanism for such cases. The qualitative data clearly demonstrates that while the RHIS has the structural capacity to record basic patient data, it is not optimized for surveillance of drug efficacy. The fact that practitioners can only retrospectively identify potential failures via referral tickets, and that there is no dedicated analysis of this data, directly relates to the study's objective of evaluating the system's effectiveness. The findings suggest that in its current form, the RHIS is a passive repository of general patient information rather than an active surveillance tool for drug effectiveness. This lack of interest from health care providers and supporting staff, also mentioned in the literature 15 , could take its origin in many considerations leading to the underutilization of the RHIS in surveillance, research or evaluation. Existing literature highlights that routine RHIS data are often underutilized for public health surveillance due to concerns over internal validity, completeness, and potential bias 16 . Some authors while recognizing that the use of facility-based data to estimate the impact of malaria control program could be helpful, they recommended however that they should be collected, analyzed, and interpreted with care, transparency and full recognition of their limitation 17 . That comes up to the option chosen by the NCMP to assess the artemisin-based combination therapy outcomes through separate, more rigorous studies like TES as recommended by WHO 18 . That has been also noticed by other authors that highlighted that challenges often render RHIS data unreliable or irrelevant impeding their usefulness in practice contributing to the continued preference for intermittent cross-sectional population-based survey as the primary source of data for tracking population health, risk factors and health service coverage 19 .But definitely, there is a recognition of data collected and reported routinely through RHIS as a potentially rich source of data for impact evaluation (which includes assessing treatment success/failure) 20 , it can complement and even offer an alternative to assess intervention effectiveness, and ultimately impact on health outcomes. RHIS Data can be used to regularly assess the effectiveness of various malaria interventions, which includes treatment regimens 11 . Even the WHO states that Efficacy Studies (TES) are the gold standard, routine HMIS data provides the essential context and flags areas where more intensive studies (TES) are required. 8 The study's findings have important practical implications. The most significant barrier is not a lack of tools or data, but a lack of a clear mandate from the national malaria control program, which has led to a lack of institutional attention and specific training. This is a common major, non-technical barriers cited for health information systems in resource-limited settings, where RHIS functionality is often limited by a lack of policy support, awareness and formal training for health workers on data collection protocols 21 but above all their analysis 22 . Existence of the tools alone cannot fix systemic issues. While patients with potential treatment failure are seen and their basic data are captured, practitioners do not record these specific outcomes within the current data collection system. This issue is pervasive across, especially in resource-limited settings where the elementary treatment outcome data (like "patient symptoms subsided" or "patient returned with relapse") during patient encounters, but fail to accurately and completely record this information in official registers, patient files, or standardized reporting forms. 23 Inadequately trained health worker has been identified as a factor leading to that 24 .The solutions proposed by both groups of staff, including training sessions, dedicated forms, and new indicators are feasible, low-cost interventions that can be directly implemented to strengthen the system. This is also proposed in the literature, especially where the data quality issues should be addressed by regular workshop focused not just on how to fill out a form, but on data quality dimensions (completeness, accuracy) and the impact of poor data on patient outcomes 25 . There is strong recognition for such training to contribute to increasing analysis competencies and decision taken at the local level 26 . This highlights that improving RHIS’s capacity to monitor treatment failure and its usability for research and surveillance is not a technical challenge, but a procedural and policy one 27 and solutions should be to establish clear Data governance Policies for ACT treatment outcomes. For ACT treatment outcomes as for major health issues in the country, clear rules, roles, responsibilities, standards, and processes for data collection, storage, and sharing. This provides the mandate for data capture and improve awareness at the local level 28 . Also, the ideal would be to have a digitalized information system for the easy implementation of such improvements and easy regular data analysis at the point of care and higher level of the system. The District Health Information Software (DHIS2) is implemented at the health zone level but, digitalization of the information system at the high level alone makes challenging the implementation of changes and improvements. Digitalizing health Information at the facility level ensures the data is digitized at the source, eliminating transcription errors, and allowing for immediate validation checks before data is transmitted 29 . Our qualitative study was conducted in seven health facilities selected within the health zone. However, we deliberately employed oversampling from the high-transmission Inkisi Valley to ensure data relevance and maximize insight into high-burden areas. Consequently, the results and conclusions of this study are heavily weighted toward the realities and challenges of high malaria burden settings and should be generalized with caution to lower transmission areas within the health zone. Conclusion This paper examines the current capabilities of the National Health Information system to capture data on the ACT treatment failure in the Kisantu Health Zone, in DR Congo, exploring the existence of tools, indicators that allow health facilities to collect and report to the head of the health Zone office data related to that topic. While the system in place is reliable and staff devoted to managing malaria cases, uncomplicated or not, receive and manage an important number of cases among which some are uncomplicated malaria with persistence of fever after getting appropriate treatment, data on treatment failure or that should lead to the diagnosis of ACT treatment failure are not captured and managed. To address the challenges highlighted by the field staff and noticed during the study, two key actions must be undertaken. First, targeted interventions within the health zone and facilities are needed to raise health practitioners' awareness regarding the critical importance of strictly adhering to the National Control Malaria Program (NCMP) case management algorithm. Crucially, practitioners must be trained to consistently record information concerning the persistence of fever or parasitemia in the appropriate existing data columns. Secondly, action at the higher level—the health zone and the NCMP—is essential. We recommend they establish a specific indicator for ACT treatment failure and implement mechanisms to ensure that all facilities collect the necessary data for their reliability and routine calculation. Declarations Ethics Approval and Consent to Participate This study was approved by the Kinshasa School of Public Health Ethics Committee of Ministry of the Superior Education of the Democratic Republic of Congo. Informed consent was obtained from all individual participants included in the study. Funding The authors declare that no funds, grants, or other financial support were received during the preparation of this manuscript. Competing Interests The authors have no relevant financial or non-financial interests to disclose Author Contribution All authors contributed to the study conception and design. Antoine Mafwila Lusala performed data collection and analysis, and all authors read and approved the final manuscript. References Venkatesan P. WHO world malaria report 2024. Lancet Microbe. 2025;6(4). Sowunmi A, Adewoye EO, Gbotsho GO, et al. Factors contributing to delay in parasite clearance in uncomplicated falciparum malaria in children. Malar J. 2010;9(1):53. Ding J, Hoglund RM, Tarning J. Medication adherence framework: A population-based pharmacokinetic approach and its application in antimalarial treatment assessments. CPT Pharmacometrics Syst Pharmacol. 2024;13(5):795–811. Oyebola KM, Ligali FC, Owoloye AJ et al. 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Waiganjo S, Muliaro JW, Karanja S, Reengineered. DHIS 2 to Capture Maternal and Child Data at Point of Service for Prompt Intelligent Decision Making and Data Visualisation: A Case of Kiambu County. Medicor: J Health Inf Health Policy. Published online 2025. https://api.semanticscholar.org/CorpusID:283022724 Additional Declarations No competing interests reported. Supplementary Files Annex.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 23 Apr, 2026 Reviewers agreed at journal 14 Apr, 2026 Reviewers invited by journal 13 Apr, 2026 Editor assigned by journal 28 Feb, 2026 Submission checks completed at journal 28 Feb, 2026 First submitted to journal 24 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Lusala","email":"data:image/png;base64,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","orcid":"","institution":"University of Kinshasa","correspondingAuthor":true,"prefix":"","firstName":"Antoine","middleName":"Mafwila","lastName":"Lusala","suffix":""},{"id":599023540,"identity":"577264f3-a3c4-4a2a-a3b7-b435d8386846","order_by":1,"name":"Hiwot Moge","email":"","orcid":"","institution":"Africa Centres for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Hiwot","middleName":"","lastName":"Moge","suffix":""},{"id":599023542,"identity":"71d174fb-68b7-4435-afde-c1d176a1a74c","order_by":2,"name":"Morenike Oluwatoyin Ukpong","email":"","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Morenike","middleName":"Oluwatoyin","lastName":"Ukpong","suffix":""},{"id":599023545,"identity":"2bfe27f9-6b56-44ec-bdc6-1e4aae3f5335","order_by":3,"name":"Henri Kimina","email":"","orcid":"","institution":"University of Kinshasa","correspondingAuthor":false,"prefix":"","firstName":"Henri","middleName":"","lastName":"Kimina","suffix":""},{"id":599023549,"identity":"37d402b7-6375-475d-b767-670ee06f25d4","order_by":4,"name":"Ruth Yanga Nsuka","email":"","orcid":"","institution":"University of Kinshasa","correspondingAuthor":false,"prefix":"","firstName":"Ruth","middleName":"Yanga","lastName":"Nsuka","suffix":""},{"id":599023556,"identity":"b850b24b-f4d4-43ef-a2ec-42e062b86b88","order_by":5,"name":"José Mavuna Nketo","email":"","orcid":"","institution":"Ministry of Public Health, Kisantu’s Health Zone Central Office","correspondingAuthor":false,"prefix":"","firstName":"José","middleName":"Mavuna","lastName":"Nketo","suffix":""},{"id":599023563,"identity":"c530e08f-c8ca-42c5-b1c6-f717f6484753","order_by":6,"name":"Gertrude Lay","email":"","orcid":"","institution":"Ministry of Public Health, National Malaria Control Program","correspondingAuthor":false,"prefix":"","firstName":"Gertrude","middleName":"","lastName":"Lay","suffix":""},{"id":599023564,"identity":"0bd3e796-1b70-4f0f-b324-7481fb5a1934","order_by":7,"name":"Baudouin Matela Baangi","email":"","orcid":"","institution":"Ministry of Public Health, National Malaria Control Program","correspondingAuthor":false,"prefix":"","firstName":"Baudouin","middleName":"Matela","lastName":"Baangi","suffix":""},{"id":599023566,"identity":"407296e0-185f-401f-89cc-28b98c6bd82f","order_by":8,"name":"Doudou Yobi Malekita","email":"","orcid":"","institution":"University of Kinshasa","correspondingAuthor":false,"prefix":"","firstName":"Doudou","middleName":"Yobi","lastName":"Malekita","suffix":""},{"id":599023568,"identity":"948687cd-7535-4d19-97c6-add15818f7bf","order_by":9,"name":"Dieudonné Mvumbi Makaba","email":"","orcid":"","institution":"University of Kinshasa","correspondingAuthor":false,"prefix":"","firstName":"Dieudonné","middleName":"Mvumbi","lastName":"Makaba","suffix":""},{"id":599023571,"identity":"d9f53f8d-1e7f-41db-8066-c213a66d18eb","order_by":10,"name":"Nebiyu Adebe Dereya","email":"","orcid":"","institution":"Africa Centres for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Nebiyu","middleName":"Adebe","lastName":"Dereya","suffix":""},{"id":599023579,"identity":"04c28a4c-31db-418a-9a68-180ec9b233bc","order_by":11,"name":"Georges Mvumbi Lelo","email":"","orcid":"","institution":"University of Kinshasa","correspondingAuthor":false,"prefix":"","firstName":"Georges","middleName":"Mvumbi","lastName":"Lelo","suffix":""},{"id":599023580,"identity":"e6305fab-c72d-4407-8216-bf7392a855aa","order_by":12,"name":"Marie Pierre Hayette","email":"","orcid":"","institution":"University of Liège, University Hospital Centre of Liège","correspondingAuthor":false,"prefix":"","firstName":"Marie","middleName":"Pierre","lastName":"Hayette","suffix":""}],"badges":[],"createdAt":"2026-02-24 12:08:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8957178/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8957178/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104401402,"identity":"dcce0c7e-bd96-42a0-96f8-33741701fd30","added_by":"auto","created_at":"2026-03-11 12:12:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":625520,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8957178/v1/ef33d7ca-e861-4dd8-b869-12041966067d.pdf"},{"id":103852040,"identity":"0f99d34d-fb35-417b-bafe-bc76cb361a5d","added_by":"auto","created_at":"2026-03-03 17:00:58","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22161,"visible":true,"origin":"","legend":"","description":"","filename":"Annex.docx","url":"https://assets-eu.researchsquare.com/files/rs-8957178/v1/626b0cc5fdf89d9adc9e5562.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Routine Health Information System (RHIS) Assessment for Artemisinin-based combination Treatment outcomes for Malaria in Kisantu Health Zone, DRC","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMalaria remains a major public health concern in the Democratic Republic of Congo (DRC)\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, where treatment failure is a significant challenge exacerbated by a complex interplay of factors, including drug resistance, adherence issues\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e and other\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. In response to rising resistance to older antimalarial drugs, the national malaria control program (NMCP) in the DRC adopted Artemisinin-based Combination Therapies (ACTs) in 2005\u003csup\u003e7\u003c/sup\u003e. While these therapies have demonstrated high efficacy transmission\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e and contributed to a substantial decrease in disease continuous surveillances of their effectiveness is critical to combat the growing threat of drug resistance. Recent therapeutic efficacy studies conducted in the country reported cure rates of approximately 94.7% for ASAQ \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, and routine health data also show improvements in the country\u0026rsquo;s malaria control interventions.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe World Health Organization (WHO) recommends regular monitoring of antimalarial drug efficacy to inform national treatment policies\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. In countries with high malaria transmission like the DRC, this is conducted through rigorous Therapeutic Efficacy Studies (TES) at NMCP\u0026rsquo;s sentinel sites, as these are capable of recruiting sufficient patients for robust analysis. In contrast, countries with low malaria transmission are advised to integrate this monitoring into their routine surveillance systems. Despite the established sentinel site approach in the DRC, it is also possible for RHIS to capture basic data on potential treatment failure, such as patients with persistent fever or persistent parasitaemia\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e after a correct ACT treatment\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. However, the practical effectiveness of clinical practitioners in identifying, recording, and processing such data through the RHIS remains unexamined.\u003c/p\u003e \u003cp\u003eThis study evaluates the effectiveness of the national Health Management Information System (HMIS) in the Democratic Republic of the Congo (DRC) in capturing and reporting possible Artemisinin-based Combination Therapy (ACT) treatment failure at both facility and health zone levels. It specifically examines the structural capacity of health facilities and the Kisantu health zone office to identify and document possible treatment failures, the processes through which malaria case data are managed and reported, and the challenges that limit the effective monitoring of drug efficacy. By identifying these gaps, the study aims to generate evidence-based recommendations for strengthening the HMIS to support timely surveillance of antimalarial drug resistance and inform public health decision-making.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis study employed a qualitative case study design. This approach is optimal for providing a detailed, in-depth assessment of the current capacity and functionality of the RHIS within a specific real-world context. We assess the structural capacity of health facilities and the health zone office to capture and report possible ACT treatment failures, analyze existing data management processes, and identify challenges that impede effective drug efficacy monitoring. The qualitative method (key informant interviews, structured document review) was used to understand processes, perceptions, challenges and functionality of data capture systems.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy setting\u003c/h3\u003e\n\u003cp\u003eThe study was conducted in the Kisantu Health Zone, located within the Kongo Central Province of the Democratic Republic of the Congo (DRC). This zone is characterized by a high malaria burden, particularly in the Inkisi Valley area\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The selection of this zone is purposive, as it represents a typical high transmission setting where monitoring ACT efficacy is critical. The study focused on two levels of the health system. First is the Health Zone Office: The central administrative unit responsible for data aggregation, analysis, and reporting. The second level is the Primary Health Facilities: the frontline units where patient data is originally captured.\u003c/p\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eAt the health zone level, the key respondents were the Head of the Health Zone (M\u0026eacute;decin Chef de Zone) and the Nurse Supervisor responsible for malaria programs. At the health facility level, data were obtained from the head nurse or officer-in-charge and the head of the laboratory or the designated laboratory technician in each selected facility.\u003c/p\u003e\n\u003ch3\u003eSample size\u003c/h3\u003e\n\u003cp\u003eThe study sites have been chosen according to the location in the health zone of Kisantu and the Inkisi valley where malaria is more prevalent in the health zone.\u003c/p\u003e\n\u003ch3\u003eSampling procedure\u003c/h3\u003e\n\u003cp\u003eGiven the high malaria prevalence in the study area, a purposive sampling technique was used to ensure the selection of information-rich participants who are directly involved in malaria case management and health data reporting. At the health zone level, all key officials (head and malaria supervisor) were invited to participate.\u003c/p\u003e \u003cp\u003eAt the facility level: Seven facilities were selected based on the following criteria: (i) Geographical location: prioritization of facilities within the high-transmission Inkisi valley. (ii) Facility type: A mix of health centers and general referral hospitals to capture potential variations in capacity. (iii) Patient volume: Selection of facilities with a high volume of malaria cases to ensure adequate data for review.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStudy procedures\u003c/h2\u003e \u003cp\u003eData was collected through two primary methods: Semi-Structured Interviews and a Structured Document Review. Data collection was performed by trained research assistants using pre-tested tools.\u003c/p\u003e \u003cp\u003e a) Key Informant Interviews: Semi-structured interview guides with open and closed-ended questions were administered to the identified participants. The guides were tailored to the respondent's level (zone vs. facility).\u003c/p\u003e \u003cp\u003eHealth Zone Level Questionnaire (10 questions) covered the following:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eExistence and knowledge of a national protocol for identifying and defining ACT treatment failure.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAvailability of trained staff on ACT failure follow-up.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eRHIS tools used for tracking malaria patients and their specific features.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eExistence of specific indicators for tracing ACT treatment failure within the RHIS.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFrequency of data analysis for monitoring treatment efficacy.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eProcedures for managing and reporting data on suspected treatment failures.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePerceived challenges (e.g., logistical, technical, human resources) in reporting ACT failure.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eRecommendations for resources needed to improve monitoring.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eHealth Facility Level Questionnaire (7 questions) covering:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eRespondent's role and responsibilities in malaria case management.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eData collection tools in use (e.g., curative consultation register, lab register, patient files).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe ability of these tools to specifically capture data elements related to treatment failure (e.g., follow-up visits, treatment repetition).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eType of data system (paper-based or electronic).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eData management and reporting process to the health zone.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAwareness of indicators for ACT failure.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFacility-level challenges and needed resources.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eb) Structured Document Review\u003c/b\u003e: A checklist was used to perform an objective audit of the existing systems and tools. This review verified the information obtained from the interviews. At the Health Zone Office: The review will focus on the national RHIS reporting canvas (Syst\u0026egrave;me National information Sanitaire - SNIS) to check for (i) the presence of fields or modules dedicated to reporting treatment outcomes. (2) the existence of a specific indicator for \"suspected or confirmed ACT treatment failure.\" (3) the completeness and consistency of aggregated data received from facilities.\u003c/p\u003e \u003cp\u003eAt the Health Facilities: The review examined (i) curative consultation registers: to see if there are columns to record follow-up status or repeated treatments for the same episode. (2) laboratory registers: to assess the linkage between diagnosis (e.g., RDT, microscopy) and patient treatment and outcome. (3) individual patient consultation sheets: to determine if they allow for the documentation of treatment response, including failure symptoms and any change in medication. (4) data reporting forms: to check that facilities are required to report any data on treatment failure to the zone.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eIn line with the objective of this study, which was to evaluate the effectiveness of the National Health Management Information System (HMIS) in the Democratic Republic of the Congo (DRC) in capturing and reporting possible Artemisinin-based Combination Therapy (ACT) treatment failure, this section presents the findings of this assessment at both the health facility and the Kisantu health zone office levels. The data presented below are structured to illuminate three key dimensions. Firstly, we present the main result on the existence of tools and the capacity of the health facilities and the health zone office to adequately identify and document probable treatment failures. Secondly, we explore the level of support provided by the health zone office to the facilities regarding the processes governing the management, flow, and reporting of malaria case data, especially the probable treatment failure. These results form the basis of the evidence-based recommendations aimed at strengthening the HMIS for improved public health decision-making.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of themes identified in participant interviews\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThemes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRepresentatives\u0026rsquo; quotes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolume of Malaria Case Management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThis theme highlights the frequency and volume of malaria cases managed routinely by practitioners in health facilities.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWe often receive patients who come for outpatient consultations.\u003c/p\u003e \u003cp\u003eWe receive\u0026thinsp;\u0026asymp;\u0026thinsp;200 suspected cases of malaria per month, \u0026asymp;\u0026thinsp;150 of which are confirmed by RDT.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of RHIS tools for malaria data collection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThis theme describes the specific existing tools and registers used by practitioners to record and track data related to malaria cases as part of their routine practice.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWe use the consultation sheet, laboratory voucher, curative care register and laboratory register to record and track malaria patients\u0026rsquo; data\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbility to document treatment failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThis theme captures the practitioners' perception of the capacity of the current system to properly document and monitor instances of malaria treatment failure.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWe are unable to document cases of treatment failure, even though we observed cases with persistent fever after treatment.\u003c/p\u003e \u003cp\u003eWe only have the mention of therapeutic failure as hypothetical diagnosis in the reference ticket as a reason for referral.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePossibility of retrospective identification of potential treatment failures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThis theme looks for a method by which practitioners can retrospectively analyze existing data to identify cases of potential treatment failure.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWe can count referral tickets that mention that patients were referred for treatment failure.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBarriers to recording treatment failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThis theme highlights the key reasons for not recording treatment failure data.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIn the curative care register, we could have registered them as old cases, but we don't do it because we are not asked to\u003c/p\u003e \u003cp\u003eWe do not pay attention to cases of therapeutic failure.\u003c/p\u003e \u003cp\u003eWe were never asked to record data on treatment failures.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePractitioner-suggested improvements\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThis theme summarizes the direct recommendations from practitioners on how to improve data collection to better capture information on treatment failure.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWe need a briefing session on identifying and documenting treatment failure cases.\u003c/p\u003e \u003cp\u003eWe suggest that old cases of therapeutic failure be recorded in the curative care register with the note \"therapeutic failure with ACT\" in the observation section.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe qualitative findings reveal a system with both strengths and significant gaps. Practitioners manage a high volume of malaria cases, utilizing a set of existing RHIS tools that, while foundational, are not designed to capture the nuances of treatment outcomes. These results in a perceived inability to document treatment failure, despite clinical observations of persistent fever in patients. While practitioners have found a workaround for the retrospective identification of treatment failure through referral tickets, this method is not a systematic or proactive solution. The root cause of this data gap lies in systemic barriers to recording treatment failure, including a lack of explicit instructions and formal training. To overcome these challenges, practitioners themselves have proposed tangible solutions, including dedicated briefing sessions and a modification of existing registers, demonstrating both an awareness of the problem and a proactive approach to improving the RHIS's capacity. This suggests that with targeted interventions, the system could be enhanced to support more effective real-time surveillance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOutcomes from the head office staffs interview on the capacity of their office to collect and report on ACT treatment failure.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuestions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnswers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eComments\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo you have a standardized protocol for identifying treatment failures for malaria? (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWe have guidelines on malaria case management we call \u0026ldquo;flowchart for malaria case management\u0026rdquo; in which instructions are given how to identify and manage ACT malaria treatment failure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhat tools do you use to track malaria cases?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNational RHIS canvas\u003c/p\u003e \u003cp\u003eDHIS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo you have staff trained in methods for monitoring treatment failures?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStaff are trained in the use of the flowchart in general, but we do not insist on the identification of the ACT treatment failure detection\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo you have access to rapid diagnostic kits (RDTs) and/or microscopy to confirm cases? (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAll health centers, considered as the entry point of the health care system at least rapid diagnosis test is available, in the referral hospital and all secondary structures, microscopy is available\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHow often do you analyze data to monitor ACT treatment failures? (daily, weekly, monthly, other \u0026mdash; specify)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWe do data analysis but not specifically on the ACT treatment failure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo you have key indicators to measure treatment failures?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThese cases are included in the persons referred indicator\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHow do you manage data from patients identified as having failed treatment? (archiving, active monitoring, other - specify)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWe are not able to collect these data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe only possibility that the system gives us is to record the number of people referred to the general hospital by giving the reason of reference that should be in that case \u0026ldquo;ACT treatment failure\u0026rdquo;. But we do not do that\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo you have a mechanism for reporting cases of treatment failure to higher health authorities?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWe are not asked to report on any outcomes for treatment, we only report on the people treated.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIf not, is it possible to report that to higher health authorities?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWe have to report rare events to the higher health authorities, that is a way we can also use for the ACT treatment failure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhat are the main challenges encountered in identifying and monitoring treatment failures for malaria? (specify)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThat is not applicable in the current context\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe identification of malaria therapeutic failures is not required by the National Malaria Control Program, which results in a lack of specific indicators on that.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhat additional resources would you need to improve the monitoring of malaria treatment failures? (funding, training, equipment, other - specify)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWe suggest having:\u003c/p\u003e \u003cp\u003e● A briefing session to draw providers' attention to the identification and monitoring of malaria therapeutic failures\u003c/p\u003e \u003cp\u003e● A specific form completed by the provider when fever or parasitaemia persist after ACT treatment.\u003c/p\u003e \u003cp\u003e● A register where all patients suspected of therapeutic failure will be recorded and the reference to the general hospital mentioned as well as the final result of the microscopy\u003c/p\u003e \u003cp\u003e● An inclusion in the facility reports template of an indicator reporting the number of people referred to the hospital cause of persistence of fever after ACT treatment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e The table indicates that the supportive staff at the health facilities are aware of the existing RHIS tools and protocols, such as the \"flowchart for malaria case management,\" but they feel there is a disconnect between these general guidelines and the specific task of monitoring for ACT treatment failure. They acknowledge having staff trained in the use of the flowchart, but not with specific emphasis on identifying treatment failure.\u003c/p\u003e \u003cp\u003eA key finding is that the head office lacks a dedicated mechanism for tracking or reporting ACT treatment failures. The staff confirms that they do not analyze data for this specific purpose and lack key indicators to measure it, instead lumping these cases into a broader \"persons referred\" category. While they can and do report \"rare events\" to higher authorities, this is not a standardized procedure for treatment failure. The primary challenge they cite is the absence of a mandate from the NMCP to identify and monitor these cases, which leads to a lack of specific indicators and a lack of institutional attention.\u003c/p\u003e \u003cp\u003eTo address these issues, the staff suggests several improvements, including a \"briefing session\" to raise awareness, a specific form for providers to fill out, a dedicated register to record suspected cases, and the inclusion of a specific indicator in facility reports. These suggestions point to a clear desire for more explicit guidance, dedicated tools, and a formal process for identifying and documenting potential treatment failure cases.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results reveal a critical disjuncture between existing RHIS protocols and their application for monitoring ACT treatment failure. While health facilities manage a high volume of malaria cases using standard tools, practitioners report a perceived inability to formally document cases of treatment failure. The head office staff confirms this, noting that the system lacks specific indicators and a formal reporting mechanism for such cases.\u003c/p\u003e \u003cp\u003eThe qualitative data clearly demonstrates that while the RHIS has the structural capacity to record basic patient data, it is not optimized for surveillance of drug efficacy. The fact that practitioners can only retrospectively identify potential failures via referral tickets, and that there is no dedicated analysis of this data, directly relates to the study's objective of evaluating the system's effectiveness. The findings suggest that in its current form, the RHIS is a passive repository of general patient information rather than an active surveillance tool for drug effectiveness. This lack of interest from health care providers and supporting staff, also mentioned in the literature\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, could take its origin in many considerations leading to the underutilization of the RHIS in surveillance, research or evaluation. Existing literature highlights that routine RHIS data are often underutilized for public health surveillance due to concerns over internal validity, completeness, and potential bias\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Some authors while recognizing that the use of facility-based data to estimate the impact of malaria control program could be helpful, they recommended however that they should be collected, analyzed, and interpreted with care, transparency and full recognition of their limitation\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. That comes up to the option chosen by the NCMP to assess the artemisin-based combination therapy outcomes through separate, more rigorous studies like TES as recommended by WHO\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. That has been also noticed by other authors that highlighted that challenges often render RHIS data unreliable or irrelevant impeding their usefulness in practice contributing to the continued preference for intermittent cross-sectional population-based survey as the primary source of data for tracking population health, risk factors and health service coverage\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.But definitely, there is a recognition of data collected and reported routinely through RHIS as a potentially rich source of data for impact evaluation (which includes assessing treatment success/failure)\u003csup\u003e20\u003c/sup\u003e, it can complement and even offer an alternative to assess intervention effectiveness, and ultimately impact on health outcomes. RHIS Data can be used to regularly assess the effectiveness of various malaria interventions, which includes treatment regimens\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Even the WHO states that Efficacy Studies (TES) are the gold standard, routine HMIS data provides the essential context and flags areas where more intensive studies (TES) are required.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe study's findings have important practical implications. The most significant barrier is not a lack of tools or data, but a lack of a clear mandate from the national malaria control program, which has led to a lack of institutional attention and specific training. This is a common major, non-technical barriers cited for health information systems in resource-limited settings, where RHIS functionality is often limited by a lack of policy support, awareness and formal training for health workers on data collection protocols\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003ebut above all their analysis\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Existence of the tools alone cannot fix systemic issues. While patients with potential treatment failure are seen and their basic data are captured, practitioners do not record these specific outcomes within the current data collection system. This issue is pervasive across, especially in resource-limited settings where the elementary treatment outcome data (like \"patient symptoms subsided\" or \"patient returned with relapse\") during patient encounters, but fail to accurately and completely record this information in official registers, patient files, or standardized reporting forms.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e Inadequately trained health worker has been identified as a factor leading to that\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.The solutions proposed by both groups of staff, including training sessions, dedicated forms, and new indicators are feasible, low-cost interventions that can be directly implemented to strengthen the system. This is also proposed in the literature, especially where the data quality issues should be addressed by regular workshop focused not just on how to fill out a form, but on data quality dimensions (completeness, accuracy) and the impact of poor data on patient outcomes\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. There is strong recognition for such training to contribute to increasing analysis competencies and decision taken at the local level\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. This highlights that improving RHIS\u0026rsquo;s capacity to monitor treatment failure and its usability for research and surveillance is not a technical challenge, but a procedural and policy one\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e and solutions should be to establish clear Data governance Policies for ACT treatment outcomes. For ACT treatment outcomes as for major health issues in the country, clear rules, roles, responsibilities, standards, and processes for data collection, storage, and sharing. This provides the mandate for data capture and improve awareness at the local level\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlso, the ideal would be to have a digitalized information system for the easy implementation of such improvements and easy regular data analysis at the point of care and higher level of the system. The District Health Information Software (DHIS2) is implemented at the health zone level but, digitalization of the information system at the high level alone makes challenging the implementation of changes and improvements. Digitalizing health Information at the facility level ensures the data is digitized at the source, eliminating transcription errors, and allowing for immediate validation checks before data is transmitted\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur qualitative study was conducted in seven health facilities selected within the health zone. However, we deliberately employed oversampling from the high-transmission Inkisi Valley to ensure data relevance and maximize insight into high-burden areas. Consequently, the results and conclusions of this study are heavily weighted toward the realities and challenges of high malaria burden settings and should be generalized with caution to lower transmission areas within the health zone.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis paper examines the current capabilities of the National Health Information system to capture data on the ACT treatment failure in the Kisantu Health Zone, in DR Congo, exploring the existence of tools, indicators that allow health facilities to collect and report to the head of the health Zone office data related to that topic. While the system in place is reliable and staff devoted to managing malaria cases, uncomplicated or not, receive and manage an important number of cases among which some are uncomplicated malaria with persistence of fever after getting appropriate treatment, data on treatment failure or that should lead to the diagnosis of ACT treatment failure are not captured and managed. To address the challenges highlighted by the field staff and noticed during the study, two key actions must be undertaken. First, targeted interventions within the health zone and facilities are needed to raise health practitioners' awareness regarding the critical importance of strictly adhering to the National Control Malaria Program (NCMP) case management algorithm. Crucially, practitioners must be trained to consistently record information concerning the persistence of fever or parasitemia in the appropriate existing data columns. Secondly, action at the higher level\u0026mdash;the health zone and the NCMP\u0026mdash;is essential. We recommend they establish a specific indicator for ACT treatment failure and implement mechanisms to ensure that all facilities collect the necessary data for their reliability and routine calculation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics Approval and Consent to Participate\u003c/h2\u003e\n\u003cp\u003eThis study was approved by the Kinshasa School of Public Health Ethics Committee of Ministry of the Superior Education of the Democratic Republic of Congo. Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other financial support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Antoine Mafwila Lusala performed data collection and analysis, and all authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eVenkatesan P. WHO world malaria report 2024. Lancet Microbe. 2025;6(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSowunmi A, Adewoye EO, Gbotsho GO, et al. 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Published online 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://api.semanticscholar.org/CorpusID:283022724\u003c/span\u003e\u003cspan address=\"https://api.semanticscholar.org/CorpusID:283022724\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Malaria, health Information systems, treatment failure, developing countries, Patient Generated Health Data, Public Reporting of Health Care Data (MeSH)","lastPublishedDoi":"10.21203/rs.3.rs-8957178/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8957178/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Malaria treatment failure remains a significant challenge in the Democratic Republic of Congo (DRC) despite the adoption of Artemisinin-based Combination Therapies (ACTs) since 2005. While the World Health Organization (WHO) recommends periodic Therapeutic Efficacy Studies (TES) for high-transmission countries like the DRC, the practical effectiveness of using the existing Routine Health Information System (RHIS) to capture basic data on potential treatment failures remains unexamined. This study aimed to bridge this gap by evaluating the RHIS in the Kisantu Health Zone, assessing its structural capacity to capture treatment outcomes data, and identifying the challenges faced by health practitioners. The findings are intended to provide evidence-based recommendations to strengthen the RHIS for more timely surveillance of antimalarial treatment outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e: This qualitative study used a purposeful sampling approach to select seven primary health facilities and key health zone staff. Data was collected through semi-structured interviews on the documentation of therapeutic failures following ACT treatment and a structured document review to assess the system's capacity, existing processes, and associated challenges.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResult: \u003c/strong\u003eInterviews with health facility practitioners and health zone staff revealed a significant gap in the Routine Health Information System’s (RHIS) capacity for malaria surveillance. While facilities handle a high volume of malaria cases using standard RHIS tools, practitioners feel they lack the ability to formally document cases of treatment failure, despite observing them. This is largely due to a lack of a clear mandate from the national malaria control program, which has resulted in an absence of specific indicators and formal training on this issue. The findings indicate that RHIS is currently a passive system for general patient data rather than an active tool for surveillance drug outcomes. Both health facility and health zone staff have proposed feasible, low-cost solutions, including targeted training sessions, dedicated registers, and specific reporting forms, to improve the system's capacity to monitor treatment efficacy. These suggestions highlight that the primary barrier is not technical but a procedural and policy issue that can be addressed with targeted interventions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion. \u003c/strong\u003eWhile the RHIS in the Kisantu Health Zone has the structural capacity to record basic patient data, it is still not an effective tool for the surveillance of anti-malarial drug effectiveness. The primary barriers are procedural and policy-based, stemming from a lack of clear mandate, specific indicators, and formal training for health workers. Implementing the proposed, low-cost interventions—such as targeted training and dedicated reporting tools—could significantly strengthen RHIS, transforming it into a more proactive surveillance tool to support timely and evidence-based public health decisions.\u003c/p\u003e","manuscriptTitle":"Routine Health Information System (RHIS) Assessment for Artemisinin-based combination Treatment outcomes for Malaria in Kisantu Health Zone, DRC","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-03 17:00:53","doi":"10.21203/rs.3.rs-8957178/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-23T16:05:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"134144665176811872054634531772333414688","date":"2026-04-15T03:01:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-13T05:12:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-28T08:22:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-28T08:17:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Malaria Journal","date":"2026-02-24T11:56:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"200da3d1-64a4-440a-8971-c3473884914f","owner":[],"postedDate":"March 3rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T05:23:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-03 17:00:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8957178","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8957178","identity":"rs-8957178","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}