COMMUNITY ENGAGEMENT
DIMAMO Population Health Research Center (PHRC)
DIMAMO Population Health Research Center (PHRC) operates as a rural Node. It a Health and Demographic Surveillance System (HDSS). DIMAMO PHRC employs a systematic method for collecting, analyzing and interpreting demographic and health-related data. This involves ongoing, long term and collation to monitor changes over time. DIMAMO PHRC focuses on population health research in a rural and socioeconomically disadvantaged area. The center started as the Dikgale HDSS (9) with a population of 8 000 which eventually expanded to 42 000 population covering all villages under the custodianship of Chief Dikgale. In 2018, the center expanded to cover approximately 100 000. The expansion prompted a name change of the center as it no longer serviced only villages within Ga- Dikgale, rather, various villages falling within traditional leadership of Tribal authorities and the center was therefore named DIMAMO Population Health Research Center.
As it stands, the Center cover a population of approximately 116000 individuals and was officially launched by Mrs. Mmamoloko Kubayi Ngubane Minister of Science and Technology on the 10th of December 2018.
Since its establishment in 1995.Dimamo, PHRC has conducted triannual surveillance, now using telephone-based data collection methods. With the assistance of household proxies, this surveillance captures vital information such as birth, deaths, migrations and household socio-demographics. Additionally, an annual individual bio-behavioral survey is conducted with over 65000 consenting individuals aged 15 and above residing in the surveillance area. This comprehensive data collection approach ensures the collection of intensive longitudinal data and a comprehensive understanding of participants’ health and sociodemographic profiles.
Situated in the Region of Capricorn District in Limpopo Province South Africa. DIMAMO surveillance area is situated between Polokwane and Tzaneen with an area coverage of approximately 545.175 km.2
Two major roads (R71 and R81) linking Polokwane to Tzaneen and Phalaborwa cut across the study area on the North Province and 57 villages with over 60 schools across the surveillance area. The predominant language in the study area is Sepedi with lesser percentages of Xitsonga and Venda speaking people.
VISION, MISSION AND OBJECTIVES
VISION
Building towards better health and well-being of under-resourced population through longitudinal scientific based research, innovation and transformation.
MISSION
To advance public health priorities through the assessment of public health status, evaluation of programs, conduct of scientific research. To provide a better understanding of health and social issues, and to encourage applying this understanding to alleviate major health and social problems in a geographically defined population.
OBJECTIVES
- To ensure that the research is ethically sound and sensitive to local circumstances.
- To ensure the center’s research capabilities through capacity building
- To attract, recruit, and retain research collaborators.
- To improve the quality of data collection
- To increase scientific articles and reports
- To increase conference attendance
- To strengthen postgraduate students’ recruitment.
- To share research findings through media and exhibition
- To strengthen the role of community engagement as a core function of DIMAMO PHRC.
Community Enagagement
The office is responsible for planning, developing, organising and implementing strategies that engage and mobilise communities across DIMAMO PHRC study area to ensure that they understand HDSS goals and take part in the research willingly. They engage with Traditional Leaders through Community Advisory Team (CAT) Members who are elected by those Traditional Councils.
They engage and build relationships with various stakeholders such as NGOs, Forums, Government Departments, Ward Councillors, Local Municipality, Religious Leaders, Traditional Health Practitioners, Local Radio Stations and UL Marketing and Communication Section. The community engagement office ensures that stakeholders are kept informed, involved, and have opportunities for meaningful participation in decision-making.
They collaborate with these stakeholders to understand their perspectives, needs, and concerns regarding DIMAMO’s activities. They actively reach out to community members by attending community events, meetings, and gatherings to introduce the organization or project, establish trust, and initiate dialogue. Furthermore, the office plays a crucial role in facilitating effective communication between DIMAMO and the community.
They develop communication strategies, materials, and channels to ensure that relevant information about DIMAMO’s initiatives, projects, or programs is disseminated to the community in a clear, accessible, and timely manner. This includes utilizing various mediums such as social media, newsletters, community forums, radio slots and public meetings.
DIMAMO Surveillance Area
DIMAMO Population Health Research Center (PHRC) is a Health and Demographic Surveillance System (HDSS) that was established in 1966, and it was formerly known as Dikgale HDSS.
Overview
The PHRC collects information on vital events routinely within villages, which falls within the leadership of Dikgale, Mamabolo, and Mothiba. Tribal Authorities to inform population and health policies. The PHRC monitors population dynamics and population health, including demographic events, such as births, deaths, causes of death, migration, and other health and socio-economic indicators over time, including health-seeking behaviors, and provides a foundation for characterizing and defining priorities and strategies for improving population health.
The PHRC provides demographically characterized sampling frames from which representative samples can be selected: this is a platform for conducting surveys, demonstration projects, and effectiveness studies, implementing and evaluating interventions, and carrying out investigational trials for new products with potential public health value. This PHRC has been part of the international Neatwork for the Continuous Demographic Evaluation of population and their Health (INDEPTH), which brought together 38-member research center, which run 44 HDSS, sites from 20 countries in Africa, Asia and Oceana.
- Health and Demographic Surveillance Systems (HDSS) are research platforms that systematically collect, update, and analyse longitudinal data on population dynamics, health, and socio-economic status within a specific geographic area. These systems play a crucial role in understanding and addressing public health challenges in various regions around the world. Here is an overview of the data collection process in an HDSS:
- Baseline Census: The surveillance begins with a comprehensive census of the study population. This involves collecting detailed information about individuals and households living in the selected area. This baseline data provides a starting point for future comparisons.
- Regular Updates: After the baseline census, the HDSS collects data through regular updates or rounds. These updates can be annual or more frequent, depending on the research design. During each update, enumerators revisit households to collect updated information.
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Data Collection Components: HDSS data collection typically includes various components:
- Demographic Data: Information about individuals, including age, sex, marital status, birth, death, and migration events.
- Health Data: Data on health status, illnesses, healthcare utilization, and access to healthcare services.
- Socio-economic Data: Economic indicators, education level, occupation, and household income.
- Geographic Information: Location data using GPS coordinates to accurately map households and health facilities.
- Event Surveillance: HDSS systems monitor key demographic events, such as births, deaths, and migrations, in real-time. This helps capture changes in population dynamics and health outcomes over time.
- Verbal Autopsy: In cases of deaths, a verbal autopsy is often conducted. This involves interviewing family members or caregivers to ascertain the probable cause of death, especially in areas with limited medical facilities.
- Data Quality Control: Rigorous quality control measures are implemented to ensure accurate and reliable data collection. Training of enumerators, data validation checks, and periodic data audits are common practices.
- Ethical Considerations: HDSS research involves human subjects, so ethical considerations are paramount. Informed consent is obtained from participants, and measures are taken to protect their privacy and confidentiality.
- Data Analysis and Utilization: Collected data are analyzed to provide insights into various health and demographic trends. Researchers, policymakers, and public health practitioners use these insights to make informed decisions and implement interventions to improve public health.
- Longitudinal Studies: One of the key strengths of HDSS data is its longitudinal nature. Researchers can track changes and trends over time, which is especially valuable for studying the impact of interventions and policies.
- HDSS systems have been instrumental in advancing our understanding of population health dynamics and have played a vital role in shaping public health policies and interventions. They are particularly useful in resource-constrained settings where traditional health information systems may be limited.
Data Collection
- Data collection involved various methods, and one of these methods is the use of data collection questionnaires. These questionnaires are structured surveys designed to collect specific information from individuals or households within the DIMAMO HDSS area. The questionnaires are administered periodically at regular intervals to the same set of individuals or households. This longitudinal approach allows researchers to track changes and trends over time, providing valuable insights into the dynamics of the population.
- Questionnaires were designed for both household-level and individual-level information. Household questionnaires capture information about the entire household’s demographics, living conditions, and socio-economic status. Individual questionnaires gather data about specific individuals’ health, education, and other characteristics.
- Here is the list of questionnaires used for data collection.
Data Dictionary
METADATA
Data Description as Data Dictionary Entry: In the context of a data dictionary, a data description would be the detailed information provided about a specific data element or attribute. The data described here includes:
- Database: The name of the database
- Table Name: The name of the table holding the data.
- Variable Name: The name of the data element or attribute.
- Data Type: The type of data the attribute holds (e.g., text, number, date).
- Short Description: An explanation of what the data represents and its purpose.
- Missing Value (%): The percentage of missing data values in the database
- Non-Missing Value (%): The percentage of available data values in the database
Surveillance metadata: Download here
DIMAMO Clinic Linkage
Record linkage also known as data matching, data linkage, entity resolution is the task of finding records in a data set that refer to the same entity across different data sources.
About Clinic Linkage to Care
Record linkage also known as data matching, data linkage, entity resolution is the task of finding records in a data set that refer to the same entity across different data sources.
Record linkage is necessary when joining different data sets based on entities that may or may not share a common identifier (e.g. database key, national identification number)
Combining information from a variety of data sources for the same individual.
Merge information from a record in one data source (File 1) with information from another data source (File2)
Example: Merging HIV information from HIV registry file with death information from HDSS database.
Purpose of Clinic Linkage
Link datasets within the context of health research including datasets collected for the purposes of research and those collected for other purposes for example information from patient records, HIV or TB registries, etc.
Benefits: HDSS and Clinic data linkage
Bringing together different pieces of information, research can identify factors and association that would otherwise be difficult or impossible to determine.
E.g., linking health or disease outbreak data to historical information collected for other purposes such as vital events or civil registration data- can reveal contributory factors for disease going back years into the past.
Similarly, linking health data to socioeconomic, geospatial datasets may provide vital insights into disease epidemiology.
Link data may also vastly increase the potential value that can be derived from individual dataset.
Reduce unnecessary or duplicative data collection efforts.
Data Privacy
Data privacy generally means the ability of a person to determine for themselves how and to what extent personal information about them is shared with or communicated to others.
Privacy Principles
Collection limitation principle- there should be limits to the collection of personal information, and it should be obtained by lawful and fair means with the knowledge or consent of the data subject.
The purpose specification principle for which personal information is collected should be specified not later than at the time of data collection.
Use limitation principle personal identifiers are not disclosed information to be used by purpose specific principle.
Security safeguards principle protected by reasonable security safeguards against loss or unauthorized access and destruction, use, modification or disclosure of data.
Individual participation principle to have the data erased, rectified, completed, or amended.
Accountability principle: Accountable for complying with measure confidentiality clause to sign.
Application clinic linkage installed on laptops for identified clinics.
Data is encrypted and password protected (e.g. Joseph =>aeb1w2rf)
Date matching and liking (HDSS and Clinched (datasets)
Permanent storage into the operational database.
Linkage System: Potential benefits near real-time reporting.
Increased research output (ready for analysis)
Planning interventions and high-quality decision making
Improved data quality and security
Future Plans
Designing and implementation of a hybrid clinic linkage system.
DIMAMO Publications
DIMAMO Upcoming Events
Roadshows
Details coming soon.
Dialogue/Feedback
Details coming soon
Annual general
Details coming soon
Training
Details coming soon.
Dr. Joseph Tlouyamma
Ms Katlego Mothapo
MS Diketso Mpyana
Ms Machipa Dikgale
Mr Moses Malatji
Mr Mccauley Mabedhle
Mr Jack Mashele
Ms Maite Mamabolo
Ms Evelyn Mamabolo
Ms Onica Chaba
Ms Rebecca Motokolo
Mr Given Mashaba
Kagiso Peace Seakamela
PhD candidate at DIMAMO PHRC is conducting research titled “The development of an evidence-based model for the management and prevention of multimorbidity in the DIMAMO Health and Demographic Surveillance Systems.” Socioeconomic factors, demographic characteristics, and population aging influence multimorbidity, a significant public health concern associated with increased mortality. South Africa’s high burden of communicable and non-communicable diseases may contribute to the rising prevalence of multimorbidity, particularly among young populations affected by HIV and TB. Despite this, there is limited research on the factors contributing to multimorbidity in rural black populations.
Seakamela’s study aims to investigate the prevalence, socio-demographic determinants, common disease combinations, and health impact of multimorbidity among young and adult populations in rural areas. Additionally, it seeks to develop an evidence-based model for preventing and managing multimorbidity in the DIMAMO HDSS in Limpopo province. The study will employ a sequential mixed methods approach, utilizing both quantitative (phase 1) and qualitative (phase 2) data collection methods from the DIMAMO HDSS. Statistical analyses including exploratory data analysis, regression models, and thematic data analysis will be conducted to achieve the study objectives.
Ethical approval has been obtained, and permissions to conduct the study within health facilities will be sought from Departments of Health in Limpopo and the Capricorn District. The study aims to contribute to understanding the relationship between multimorbidity, socio-determinants, and mortality in rural black populations. By exploring, the barriers faced by patients, clinic managers, nurses, and community health workers in managing and preventing chronic multimorbidity, the study aims to enhance knowledge and inform interventions addressing this growing epidemic. Notably, the involvement of patients in developing the prevention and management model adds a novel dimension to the study, particularly in a rural context.
Cairo Bruce Ntimana
PhD candidate at DIMAMO PHRC is conducting research titled: “Development of a framework to manage mental health disorders associated with chronic conditions among adults rural setting of Dikgale, Mamabolo, Mothiba (DIMAMO) Health and Demographic Surveillance Site (HDSS), Limpopo Province, South Africa.”
In the DIMAMO Population Health Research Centre (PHRC) and Limpopo Province, little is known about the burden of mental health disorders in elderly people with chronic conditions. Despite the substantial literature showing that those with high HIV prevalence also have higher rates of risk factors for non-communicable diseases in South African communities, there is limited evidence on the most effective techniques to safeguard mental health from declining in these susceptible groups.
Mr Ntimana aims to explore the relationship between mental health disorders and chronic conditions among adults rural setting of DIMAMO PHRC, Limpopo Province, South Africa. Mental health disorders and chronic conditions are managed separately in health care facilities, resulting in disjointed care that can negatively impact patient outcomes. An integrated framework is essential to provide comprehensive, coordinated care that addresses the complexities of comorbid mental and chronic conditions; hence the present study aims to develop a framework that will integrate the management of mental health disorders and chronic conditions.
Sylvia Matladi
Mr Kingsley Hlungwani
Mr Mahlodi Mahowa
Mr Precious Makoti
Mr Samson Rathobottha
Ms Mmapula Raphokoana
CONTACT DETAILS
DIMAMO PHRC Office Reception
Diketso Mpyana
Tel: 015 268 4229
Email: diketso.mpyana@ul.ac.za
Data Management Office & Director Office
Joseph Tlouyamma
Tel: 015 268 2836/4650
Email: joseph.tlouyamma@ul.ac.za
Research Operations Office
Katlego Mothapo
Tel: 015 268 4722
Email: katlego.mothapo@ul.ac.za
Community Engagement Office
Mrs. Machipa Dikgale
Tel: 015 268 4847
Email: machipa.dikgale@ul.ac.za