Begin with the decision the NGO must make
A baseline study in Eritrea becomes valuable when it changes an implementation decision. Before interviewing households in Asmara or Keren, a programme team should decide what it needs to learn about access, quality, affordability, knowledge or behaviour. A pair of urban sites can illuminate how an intervention might work in different settings; it cannot establish results for every district, rural settlement or hard-to-reach population.
An effective baseline begins with the programme theory of change. Map the intended activities, outputs, outcomes and assumptions, then ask which assumptions are most uncertain. For an education intervention, access to classes and learning outcomes are different constructs; for a livelihood project, training participation is not the same as improved earnings. Define the measurement questions before selecting a questionnaire platform. The final study plan should say who will review the data and what programme choices each indicator is expected to support.
Understand how research geography works in Eritrea
Fieldwork should follow the administrative vocabulary used in Eritrea: regions (zobas) and sub-regions. These structures help researchers identify the correct boundaries, local gatekeepers and likely sources of population lists, but they do not automatically supply a complete probability sampling frame. First establish which boundaries apply to the actual programme area, then verify maps and household or facility counts. Administrative labels should be used only after checking their exact local meaning and relationship to the study population.
Define the target population and sampling frame
Sampling quality depends on how people can enter the study, not simply how many questionnaires are completed. Construct a frame with clearly defined geographic and eligibility boundaries. If households are selected through multiple stages, track selected clusters and household selection rules; if facilities are sampled, separate a facility census from interviews with its users. Anticipate nonresponse and predefine replacement procedures. A two-city study can estimate outcomes for well-defined urban populations when designed for that purpose, but it cannot automatically claim to represent every region.
Baseline research in Asmara: designing the first city sample
In Asmara, where the city functions as a capital-centred urban service environment, a baseline might start with an inventory of programme catchments and service points. If the intervention concerns livelihoods and local employment, the field team should test measures of income sources, employment quality, seasonality and access to productive assets. Interviewer routes should deliberately cover selected neighbourhoods rather than concentrating around accessible offices and major roads. Compare the register of intended participants with people who actually use services; discrepancies may expose targeting or access problems. Whether the unit is a household, young person, facility or beneficiary must remain consistent through analysis.
Baseline research in Keren: testing a contrasting city context
Keren deserves an independent field plan because it is a major town outside the capital. Before importing the Asmara questionnaire unchanged, conduct a short cognitive pilot and verify where the target population resides, travels and receives services. The sample allocation should reflect the stated comparison question, not an arbitrary equal split made for convenience. If the NGO needs a comparison between the two cities, agree the minimum precision and subgroup coverage needed. Findings should describe the observed difference without attributing it automatically to geography or programme performance.
Build indicators that can be measured again
Programme dashboards often group together activity counts, outputs and outcomes, but a baseline primarily needs interpretable starting values for the intended results. Define what counts as a person reached, a household with access, a user satisfied or a facility functioning. For sensitive measures, confirm privacy before selecting a mode. Set out missing-value rules and calculation conventions in advance. This protects the study from retrospective threshold-setting once the team has seen the data.
Choose appropriate survey and qualitative methods
Build a mixed-method design around the research questions. Structured interviews may estimate the prevalence of a condition in a defined population; in-depth discussions can uncover how respondents interpret the issue. Site observation can test whether reported services exist and are usable. A phone-only design may miss participants with limited ownership or connectivity, so consider whether targeted in-person coverage is essential. Before fieldwork, reconcile questionnaires, consent language, qualitative guides and indicator definitions so the evidence fits together.
Translate and pilot instruments for local respondents
Tools and consent scripts should be tested in Tigrinya, Tigre, Arabic and other relevant languages. A language that works for a formal meeting may not be the clearest language for a household interview, and bilingual respondents may switch vocabulary when describing sensitive experiences. Prepare a glossary for core constructs, reconcile translations with the source questionnaire and role-play difficult questions. Recruit interviewers for language competence and cultural familiarity, not only device skills. Translation changes need recorded approval so that future midline and endline rounds can preserve conceptual equivalence.
Design field operations around actual access conditions
Operationally, permissions and enumerator mobility should be confirmed before promising coverage. Plan interviewer assignments, transport, safe operating hours, supervision and escalation around this reality. An initial reconnaissance visit can check listing feasibility, accessibility, the actual duration of an interview and any mismatch between administrative maps and lived settlement boundaries. A rigorous pilot should include sample-selection rehearsal, consent practice, skip-logic tests and mock data submission. Budget for replacements that comply with the original selection procedure rather than allowing opportunistic substitution when a respondent is absent.
Protect consent, privacy and vulnerable participants
Plan for ethical interviewing as carefully as for sample selection. Recruitment scripts should not pressure participants through local authorities or service providers. Interviewers need a safe way to handle distress, complaints, safeguarding concerns and requests to withdraw. Consent for recordings must be explicit, and remote client observation must be disclosed when used. The research team should maintain a data-management plan describing storage, restricted access, de-identification and retention, with site-specific requirements verified.
Check quality while fieldwork is still active
Digital collection can enforce range checks, but the research still needs people and procedures. Supervisors should observe interviews, audit respondent selection, review suspicious patterns and ensure that genuine refusals are recorded. Training must address leading probes, substitution of selected households and pressure to meet numerical targets. A short feedback cycle allows correction before weaknesses contaminate the full sample. At closure, reconcile accepted interviews, exclusions, weights, field incidents and outstanding quality flags.
Analyse change without overstating causal claims
Analysis should move from data validation to clearly labelled findings. Report weighted estimates only when design and weights justify them. Examine subgroup differences with attention to sample sizes and uncertainty, and separate observed conditions from assumptions about programme causality. Triangulate conflicting findings: a facility may report stock availability while households describe barriers to access. The final product should include baseline values, limitations, an indicator annex or calculation dictionary, and a short decision brief for programme managers.
Turn baseline evidence into action in Eritrea
For a hypothetical NGO programme focused on livelihoods and local employment, the useful deliverable is not simply a table showing income sources, employment quality, seasonality and access to productive assets. It is an explanation of which barriers can be addressed through the intervention and which reflect factors outside programme control. If participants know a service exists but rarely use it, explore cost, location, opening time, quality, trust and social norms. Recommend a response only when the evidence distinguishes among those explanations. The baseline should also register external shocks and programme exposure dates to protect later interpretation.
At the end of the exercise, the NGO should be able to say what the baseline means for Eritrea, what it means specifically for Asmara and Keren, and what it does not mean. Set a schedule for repeating core indicators, preferably at comparable seasonal periods. Keep the sample frame, contact protocol, questionnaire versions, interview-date records and calculation syntax. Use a short management session to decide whether targeting, staffing, communication or referral practices should change. Record those decisions so the endline can examine both outcomes and the adaptation process.
What a useful baseline report should deliver
A strong Eritrea baseline report should provide a clearly defined study population, an honest sampling account, accepted-interview totals, response outcomes, reproducible indicators and accessible recommendations. City comparisons should carry their own denominators and limitations. The report can be supported by a clean dataset, fieldwork memo, codebook and monitoring matrix, for internal analysis and subsequent measurement rounds. Any gaps in coverage should be visible so implementers can decide whether further listing or targeted qualitative inquiry is needed before expanding activities.
How Surveysphere Africa can support
Surveysphere Africa helps NGOs and development organisations design baseline studies, define indicators, plan samples, manage fieldwork, verify data quality and turn findings into actionable programme decisions. For work involving Asmara, Keren or wider coverage in Eritrea, the research design should begin with the intended decision and the population it needs to represent, then adapt responsibly to the local context.
Related guidance
For the continent-wide view, read our guide to baseline, midline and endline studies.
Our services for research in Eritrea
We run research across African markets. Start with these services for work in Eritrea:
- Monitoring, evaluation and learning in Eritrea: Baseline, midline, endline and programme evaluation.
- Social and development research in Eritrea: Qualitative and quantitative studies for social and development programmes.
We also offer: Outsourced fieldwork, Market and consumer research, Public health research, Policy, economic and institutional research, Data analytics and insights visualisation.
