Research Assistant

Established in 2003, Malaria Consortium is one of the world’s leading non-profit organisations specialising in the prevention, control and treatment of malaria and other communicable diseases among vulnerable populations. Our mission is to save lives and improve health in Africa and Asia, through evidence-based programmes that combat targeted diseases and promote universal health coverage. We are recruiting to fill the position below:

Job Title: Research Assistant Locations: Kaduna, Oyo, and Sokoto

Employment Type: Contract Project Background Malaria remains one of the leading causes of morbidity and mortality among children in Nigeria, accounting for a significant proportion of global malaria cases and deaths. While national statistics provide aggregated estimates, there is limited disaggregated data describing how severe malaria burden, clinical manifestations, and outcomes vary across age groups. Recognizing this evidence gap, the DISBURMA Study (Disaggregating the Burden of Severe Malaria in Paediatric Populations in Nigeria) aims to provide comprehensive, age-specific insights into severe malaria morbidity and mortality patterns among children and adolescents up to 20 years of age. The findings will guide health system planning, case management protocols, and malaria control strategies. The study’s overarching aim is to quantify the burden, clinical characteristics, and outcomes of severe malaria among paediatric and adolescent populations (0–20 years). Purpose of the Assignment This is a multi-center retrospective cohort study using routine hospital records of paediatric and adolescent admissions with severe malaria from January 1, 2021, to December 31, 2025. Study sites will include the 18 health facilities selected to represent Nigeria's epidemiological zones, urban/rural mix, and population density. The specific objectives include to: Estimate age-specific incidence, clinical presentations, and case-fatality rates of severe malaria among children and adolescents aged 0–20 years across multiple facilities in Nigeria (2021–2025). Examine temporal trends in severe malaria admissions and deaths by age, sex, SMC and non-SMC zones. Identify key comorbidities and complications associated with severe malaria. Assess facility-level differences in severe malaria burden and management practices. Scope of work The DISBURMA Study will adopt a retrospective, multi-centre hospital-based cohort design, using data from 18 selected health facilities across Nigeria’s six geopolitical zones. These facilities represent diverse malaria epidemiological profiles, urban-rural contexts, and population densities. The retrospective analysis will cover hospital admission records from January 2021 to December 2025, focusing on children and adolescents diagnosed with severe malaria. All admissions of patients aged 0–20 years with clinically or laboratory-confirmed severe malaria will be eligible for inclusion. Data abstraction will use a standardized electronic data capture (EDC) system (SurveyCTO), guided by a detailed extraction form and variable dictionary. Key variables will include demographic information, clinical presentation, laboratory findings, treatment details, comorbidities, and patient outcomes. A minimum of 100 severe malaria cases among 0-20 years over 5 years (2021-2025) will be extracted from hospital records. Level of Effort (LOE): Data extraction of severe malaria cases from inpatient medical records (case notes), laboratory registers (malaria microscopy/RDT results), paediatric and emergency department logs, referral and discharge forms and national severe malaria register between 2021-2025. The research coordinator will provide technical oversight on the daily data extraction of severe malaria cases and the research assistants. Specific tasks for Research Assistant Receive briefing from Malaria and Public Health team on the assignment Identify from registers and case notes the severe malaria cases Work with the medical record officers to ensure that the records are retrieved, extracted and send to the electronic database using the data collection tool. Capture data elements available in all primary data sources, which could include: Unique record ID (study-specific) Facility identifier Patient demographics: age (in months/years), sex, residence (urban/rural) Date of admission, date of discharge/death Diagnosis of Severe malaria: Clinical Diagnosis or Laboratory diagnosis of Severe Malaria Pre referral Treatment (Tick as appropriate): Rectal Artesunate vs. other Antimalarial Parenteral Treatment (Tick as appropriate): Inj. Artesunate, Inj. Artemether, Inj. Quinine and other antimalarials (specify) Oral follow up to Parenteral treatment (Tick as appropriate): Oral ACTs, Oral Quinine and other forms of Oral Antimalarials Outcome of treatment (Tick as appropriate): Improved & Discharged, Death, Absconded / Discharged Against Medical Advice (DAMA) and Referred for further treatment Clinical presentation: signs/symptoms (coma, impaired consciousness, prostration, severe anemia, respiratory distress, hypoglycaemia, repeated convulsions, jaundice, renal impairment, shock), vital signs at admission Laboratory results: malaria test type and result, haemoglobin/PCV, blood glucose, parasite density (if available) Treatment variables: antimalarial therapy (parenteral artesunate, quinine), blood transfusion, antibiotics, anticonvulsants, supportive care (oxygen), time to first dose Co-morbidities and complications: HIV status (if documented), sickle cell disease, severe malnutrition, pneumonia, sepsis Referral source and time from symptom onset to admission Respond to related queries and data needs and requests from the project’s technical team and key national and sub-national partners, NMEP and SMEP. Deliverables for Res