DIMAMO

What We Collect

The DIMAMO Population Health Research Centre collects data through regular, systematic tracking of health and population changes in a defined community. The process started with a full baseline census in 1995, where all households and individuals in the surveillance area are captured and assigned unique ID numbers. Basic demographic details such as age, gender, education, and household relationships are recorded. After this initial setup, data collection continued through a combination of field-based and telephonic methods. The two methods allow for collection of three data points in every year. 

Field-Based data collection

Field-based data collection is the primary method used to gather longitudinal health and demographic data. Trained fieldworkers visit households within the surveillance area at one every year to record events such as births, deaths, migrations, pregnancies, health episodes, verbal autopsies and socioeconomic conditions.

Key aspects:

• Enables direct interaction with household members
• Allows for verification of events through observation
• Essential for accurate tracking of demographic changes over time
• Suitable for capturing data in areas with limited resources

Key measures collected:

• Individual level data collection
  • vital events (births, deaths, migrations)
  • demographics (age, sex, marital status, relationship to household head, Religion)
  • migrations (internal and external in-and-out migrations, migration place type, reasons, destination/origin)
  • verbal autopsies (causes of death)
  • individual health (mental health, health utilisation, bio-measures, financial status, HIV services, HIV & TB statuses, hypertension status, HIV & glucose tests, viral load, vaccinations)
  • reproductive history (pregnancy history and outcomes, age at first birth, number of living children)
  • socioeconomics (educational & employment statuses, grants, marital status)
• Household data collection
  • Household Structure (household composition, head of household)
  • migrations (internal and external in-and-out migrations, migration place type)
  • socio-economic (assets status, financial status, food security, housing conditions, water and sanitation)

Telephonic Data Collection

Telephonic data collection is used to complement field visits. It involves calling respondents to update households’ data on vital events or follow up, helping to maintain data continuity between rounds and reach households that may be temporarily inaccessible. Two data points per year are collected though this method. 

Key aspects:

• Allows remote data collection without physical visits
• Useful and cost-effective for follow-up interviews
• Limited by mobile network coverage, access to phones, and respondent availability

Key measures collected:

• Household updates (residency status, migrations, household head change)
• Individual updates (residency status, educational and employment status, grants, marital status, pregnancy status, relationship status)

How we collect data

The data is collected electronically using Survey Solutions, a software developed by the World Bank, involves using tablets and computers to administer digital questionnaires in the field and call centre. The platform supports real-time data entry, automated skip patterns, validation rules, GPS tagging, and interviewer monitoring. These features significantly enhance data quality assurance by reducing manual entry errors, enabling immediate error detection, enforcing logical consistency checks, and facilitating real-time supervision and feedback from supervisors and central teams. Robust measures were put in place to improve the accuracy, completeness, and timeliness of data collection compared to traditional paper-based methods.

Why we collect data

Data is collected to generate reliable, up-to-date evidence on population dynamics, health outcomes, and social conditions. One crucial reason for collecting this data is to make it available for researchers, enabling them to uncover underlying issues affecting rural communities, such as health disparities, barriers to education, food insecurity, or access to essential services. This evidence supports the design and evaluation of policies and interventions, ensuring that programs are targeted, effective, and responsive to community needs. Additionally, data collection helps track trends over time, identify emerging public health threats, monitor the impact of development programs, and ensure accountability in resource allocation. Ultimately, robust data empowers both local and national stakeholders to make informed decisions that improve the well-being of vulnerable populations.