Establishing Webuye Health and Demographic Surveillance Site in Rural
Western Kenya: Challenges and Lessons Learned
Chrispinus J Simiyu, BSc1*, Violet Naanyu, PhD1, Andrew A Obala, PhD1, David O Odhiambo,
MPH1, Paul Ayuo, MMed1, Dinah Chelagat, MSc1, Raymond Downing, MD1, Diana Menya,
MSc2, Emily Mwaliko, MMed1, Wendy P. Omeara, PhD2,3, Edwin O Were, MMed1, Marc
Twagirumukiza PhD4, Davy Vanden Broeck PhD4, Stanley Shitote, PhD5, Jan De Maeseneer,
PhD4 , Barasa O Khwa-Otsyula, MMed1
1. Moi University School of Medicine, Eldoret, Kenya; 2. Moi University School of Public Health, Eldoret, Kenya;
3. Duke University, Durham, USA; 4. Ghent University, Ghent, Belgium; 5. Moi University School of Engineering,
*Corresponding Author: P.O. Box 4606, Eldoret – 30100, Kenya. E-mail: firstname.lastname@example.org.
Telephone: +254 722 140 641 Fax: +254 53 2033041
Keywords: Webuye, Kenya, Health Demographic Surveillance
This paper describes the methodologies, challenges and lessons learned in establishing Webuye
Health and Demographic Surveillance System (HDSS) in Webuye Division of Bungoma County.
The Webuye HDSS was established in 2007 through a collaborative programme between Moi
University, (Eldoret, Kenya) and Ghent University (Ghent, Belgium.) through the Flemish
Interuniversity Council (VLIR), university cooperation for development (UOS) in Flanders
framework. The goal for establishing the HDSS was to provide reliable and comprehensive
demographic, health and economic data to inform health policy and planning at local and
national levels. The data were collected by households visit within the community twice a year,
using field interviewers from the local community. The participatory data collection methods
used enhanced locals’ interests to take part in data collection processes.
Challenges encountered include insufficient funding, refusals to participate by some household
members, modalities for coping with future anticipated community fatigue, responsibility to
protect both the University and community, threat by other programmes operating in the area and
Despite these challenges, the Webuye HDSS has been successfully established and maintained
for the last 4 years. To overcome the challenges establishing and running Webuye HDSS,
thorough explanation of the concept to both stakeholders and the community was found to be of
Historically, the demographic surveillance system (DSS) is the process of monitoring births,
deaths, causes of deaths, and population dynamics data over time . This approach has been
considered as the cornerstones of public health research, particularly in investigating and
tackling health disparities[Ref: ibidem], and nowadays the process have an added value of
collecting data on other determinants of health. This inclusive approach is operationally defined
as Health and Demographic Surveillance Systems (HDSS) which is a set of field and computing
operations designed to prospectively collect and analyse demographic and health related data of
well-defined populations in clearly defined geographic areas . The HDSS sites play a critical
supplementary role of generating high-quality, longitudinal, population-based health and
demographic data and this fills the gap left by government registering systems. In many low and
middle income countries, such as those in sub-Saharan region, many people are born and die
before being formally registered in government systems [1-4]. Often demographic data that is
obtained comes from censuses or other transversal sample surveys in the community. However,
these surveys and censuses may be fraught with errors with some omissions of still births, peri-
natal deaths, and deaths from households that closed down. Moreover multiple reporting of
individuals and demographic events where the concepts of “household” and “family” are not
clearly differentiated; and the fact that these data quickly become out of date[1;2;4-6].
An international network of demographic surveillance systems (DSS) now operates mostly in
sub-Saharan Africa and Asia where thirty-eight DSS sites are coordinated by the International
Network for the Continuous Demographic Evaluation of Populations and Their Health in
developing countries (INDEPTH) [7-9;12]. Three of these sites are in Kenya .
Webuye Health and Demographic Surveillance System was established in 2007 by the
collaborative research programme between Moi University (Kenya) and Ghent University
(Belgium) through the Flemish Interuniversity Council (VLIR), university cooperation for
development (UOS) in Flanders framework. It is a component of the Health Science Project
within this programme, and is run by staff from the schools of Medicine (MUSOM) and Public
Health (MUSPH) of Moi University. The establishment of the site was a natural progression of
the Moi University’s Community Based Education and Service (COBES) programme, which
emphasizes teaching of students as well as provision of service in the community. The main
objective of the site is to provide reliable and comprehensive demographic, health and economic
data to inform health policy and planning at local and national levels as well as being a
community ‘classroom’ for teaching, medical practice and research. The expertise support to set
up the Webuye HDSS was received from CDC Kisumu-HDSS and from the INDEPTH-Network.
Webuye HDSS is located in Webuye Division of Bungoma County, approximately 380km west
of Nairobi. The County borders the Republic of Uganda to the West and lies between latitude 0
25.3’ and 0 53.2’ north and longitude 34 21.4’ and 35 04’ East. It covers a land area of 3032 km2
or a quarter of the former western province .
The County is mostly inhabited by people of the Luhya ethnic group. The population of the
county is estimated at 1.37 million according to the 2009 population and housing census report
. It is evenly distributed with an average population density of 453 persons per square km.
There are heavier population concentrations in the main urban centres and around major
factories. These include Pan African Paper Mills in Webuye, Nzoia Sugar Company, Bungoma
Town, Kimilili, Sirisia, Malakisi Tobacco Leaf Centre, Chwele and Tongaren. Urban population
is about 30 per cent of the total.
The main economic activity is small scale with maize, sunflower, sugarcane, coffee, tobacco,
potatoes, beans, sorghum and millet being some of the main crops as well as cattle and chicken
raring. Of the total labour force of about 565,000, 52 percent are engaged in agricultural
production which provides 60 percent all household incomes; 19 percent wage employment and
13 percent urban self employment .
Typical characteristics of the population include high unemployment, low participation of locals
in commercial enterprises, low agricultural productivity, child labour due to high school dropout
rate, high dependency ratio, high population growth and a high youth/adult ratio. Most
households are poor with 61% of the population living below poverty line and generally social
amenities like water and electricity are not readily available to the majority [14;15].
Webuye Division has 5 administrative locations with a total population of 230,252 persons living
in area of 269.1 km2 in 2009 . Webuye HDSS covers four administrative locations with total area
of 130km2[14;15]. Figure 1 is a map showing the six sub-locations within these four locations.
The Webuye HDSS is mainly funded by the collaborative programme between Moi University
and VLIR- UOS  The vision of the programme is to improve the socio-economic welfare of
western Kenya through human capacity building, development of innovative research and
extension strategies, review and development of curricula and working with stakeholders to
address and resolve problems identified in the community. Other sources of funding for
Webuye HDSS come from the nested research studies carried out at the site.
The site operates under the general direction of the Scientific Committee of Moi University-
VLIR-OUS Health Sciences Project which is a multi-disciplinary team. The team guides the
site’s research agenda and reviews new and on-going projects. It reports to University
Management through the Moi University_VLIR UOS Steering Committee and works closely
with the Community Advisory Board, which is the stakeholder taking care of the interests of the
There is a Site Manager who is responsible for the day to day running of the site with an office
located at the Webuye District Hospital. The team under him includes the Data Manager, Data
Quality Checkers (2), Data Entry Clerks (5), Field Supervisors (5), Community Interviewers
(32), and a Secretary. Studies conducted within the Webuye HDSS use the reference laboratory
at the Moi University School of Medicine in Eldoret.
This project received study approval no FAN:IREC000653 of the joint Institutional Review and
Ethical Committee (IREC) of Moi University and Moi Teaching and Referral Hospital (MTRH)
Community Sensitization and Mobilization
In the initial stages, meetings were held with the stakeholders, who included government
officials, church leaders, local leaders and Webuye District Hospital administration, to explain
the concept of the HDSS and how it will be conducted. Questions were raised on a variety of
issues including how the project would benefit the community and the possibility of securing
employment in the project. After these issues were addressed, the stakeholders and the
community accepted the project. Following community acceptance, additional educational and
sensitization activities commenced. Several barazas  (local community meetings), were
conducted in each sub-location within the 4 locations to allow community members to ask
questions about the proposed site. The barazas were usually attended by the Chiefs (Locational
administrator), Assistant Chiefs, bakasa (village elders) and the villagers.
Recruitment and Training
The site manager and the data manager were competitively recruited through an open, nation-
wide advertisement. The candidates for these positions were required to have a minimum
academic qualification of bachelors’ degree in a relevant field. The CI's were also competitively
recruited and employed on a 3-month contract twice a year. They were required to have
completed at least four years of high school and must be residents of the surveillance area. Field
supervisors were selected from among the team of community interviewers.
Before the commencement of the baseline survey, the field teams received classroom and field-
based training. This was to ensure proper understanding of the concept of HDSS and the accurate
completion of questionnaires and utilization of all the relevant tools used in the field in
accordance with INDEPTH recommendations . The training modules included an overview
on the HDSS operations, use of Personal Digital Assistants (PDAs), use of Geographical
Positioning Systems (GPSs) units, community entry techniques, questionnaire administration and
standardization. At the end of the training, each participant was required to take and pass a
Human Subjects Protection (HSP) test on social and behavioral research ethics as required by
IREC. A pilot study was carried out in an adjacent area before the baseline survey. Refresher
trainings are subsequently conducted prior to each update cycle. Additional trainings are
conducted for all the other additional studies.
Mapping the Webuye HDSS
The entire Webuye HDSS was mapped during the baseline census (Fig. 1). The mapping team
visited each homestead in the HDSS and took the geo-coordinates. Mapping was performed
using a differential Global Positioning System (GPS) . The digital coordinates of family
compounds and other sentinel sites such as markets, schools, health facilities, churches, and
water sources were taken using the GPS units (Trimble Navigation, Limited, Sunnyvale, CA).
The coordinates captured from each compound were used to create a digital map used to identify
these compounds. They then assigned each household a unique code and painted this code on the
Prior to data collection at baseline, verbal informed consent was sought from the head of the
household. The area and its sub-units and households mapping was carried out through a GIS-
based approach. The baseline census, which took 4 months, was carried out in November 2008
using paper questionnaires only. Subsequently data collection is carried out twice a year with
each cycle lasting 3 months.
A household is defined as a group of people who regularly eat from the same “pot” regardless of
whether they live or sleep in the same homestead. [Ref] A resident is defined as an individual
who has lived in the Webuye HDSS surveillance area continuously for a period of at least four
calendar months prior to the interview date .
Information collected includes an assigned household code; name and assigned code of
household head; number of inhabitable rooms; name and code of sub location and the GPS
coordinates for each homestead. Other information collected included: demographic information
for each household member; household drinking water type and source; household possessions
including domestic animals, land size and use; type of fuel used for cooking; lighting source;
land ownership; tenure status of the dwelling place; waste disposal methods and source of
finance for the household members.
A quality control system was put in place at every stage of data collection to ensure data quality.
In this system, completed data collection questionnaires are first checked in the field by the field
supervisors for completeness after which the questionnaires are sent to the field office where
they are reviewed by data quality checkers for completeness, logic and consistency. The
incorrectly filled questionnaires are returned to the respective CIs for correction. The correctly
filled questionnaires are then passed on for data entry into the database. After data entry,
questionnaires are checked again through automated internal consistency checks and those found
to be incomplete are again sent back to the CIs for verification and correction.
The data management system is modeled on the Household Registration System [20; 21]. This
model ensures accuracy and consistency of the database specifically for longitudinal follow-ups
of individuals over a long period of time. All data are stored in a Mysql structured database
(Mysqlab Inc, 2011).
Data collected are first analyzed and the results shared with stakeholders including Ministries of
Health and the community. It will be published for general consumption by researchers.
Webuye HDSS has been in operation for four years. It has carried out six update cycles since the
baseline census. It has registered a total population of 77,000 people in 13,333 households and
9,784 compounds within the area. Figure 2 is a map showing the distribution of the compounds
within the six administrative sub locations. The information collected include longitudinal
follow-up data on the births, deaths, morbidity, socio-economic status, pregnancies,
immunizations, parental survival, water, sanitation and health seeking.
In addition to the regular update of the demographic-events data, there have been nested studies
carried out within the Webuye HDSS. These include: Prevalence of Intestinal worms in children
under 5 years of age; Prevalence of malaria in children under 5 years of age; Type and level of
disabilities among the residents; Causes and treatment of jiggers from the infested households;
Assessment of cardiovascular risk factors among the residents; Assessment of the quality of
water; Survey on the availability, accessibility and affordability of antimalaria medicine in retail
outlets; and a survey of injuries in children below 18 years of age.
Challenges encountered up to this point have been few. These include inadequate funding,
refusal by some individuals to participate, loss of good workers to other employers who offer
better terms. One has to be aware all the time of the enormous responsibility to protect the
community and university image. The other major challenge likely to occur later is community
To address the challenge of protecting the image of the University and that of the community,
Webuye HDSS established a community advisory board with the responsibility of advising the
management on issues of community interest. Regular interactive meetings with the community
for feedback and sharing with them about their concerns. The HDSS has developed a strict field
standard operating procedures in line with the university’s policy and ethical standards in
research. This ensures that the field staff do not contravene both the University and community
norms that may raise conflict.
To address the challenge of community fatigue, Webuye HDSS intends to conduct studies to
understand the causes of fatigue and how to deal with it. The HDSS has also been providing
incentives to the community such as employing people from the community and conducting
annual free health days in partnership with the faculty, staff and students of Moi University. The
HDSS also engages the community to participate in the decision-making process within the
through the Community Advisory Board. Prior to the launch of each cycle, the HDSS conducts a
launch. During these launches, the HDSS keeps the community engaged by providing feedback
on the studies already conducted and respond to the questions that are raised by the community.
Inadequate funding is being addressed by continuously developing more nested research studies
to attract more funding to sustain the HDSS. Fund raising through the donor community and
local partners is also being exploited to find strategic partners in implementing some community
health intervention projects.
Risk of losing staff to other programmes working within the surveillance area has been addressed
through development of staff incentives that motivate the staff. Some of these incentives include
continuously providing in-house training that sharpens the skills of the staff. Where possible, the
HDSS collaborates with the other programmes to find areas of synergy between them to ensure
resource sharing and reduce competition.
The HDSS addresses the challenge of refusals by some villagers to participate in the project
through continued sensitization and education on the importance of participating the Webuye
HDSS activities, and how this contributes to the development of interventions that benefit the
nation as a whole. This has proven successful thus far as the coverage has increased since the
In the 4 years that the Webuye HDSS has been in operation, many lessons have been learned. and
can serve to when setting up an HDSS in other area in developing countries First, collaboration
with colleagues from complementary institutions, both public and private is crucial. Developing
strong institutional relationships provides a good opportunity for cordial relationships and
existence. Noteworthy, leadership in any of the collaborating institutions is transitory in nature.
However, this should not affect the fundamental relationship that exists. A strong institutional
partnership and a stable research team with strong interpersonal relationships remain crucial to
achieve the longitudinal studies goals. Running a HDSS requires a multidisciplinary approach,
and the scientific team should comprise experts in the field of data management, data analysis,
community outreach and Information and Communication Technology).
Second, HDSS in general plays a significant role in filling the gaps in the Health Management
Information Systems (HMIS) nationally . It is therefore imperative that the management of the
HDSS sites take up their role in the national health information system agenda. Fostering good
inter-site relationship, and between individual sites and government can greatly improve
information flow in the health sector, thereby enhancing speed and accuracy in decision-making
at the various levels. This relationship should be of symbiotic nature such that HDSS sites collect
accurate and timely information and share it with government. Government on the other hand
should support HDSS activities by providing the needed infrastructure upon which the HDSS
sites operate and lobby on behalf of the HDSS sites for funding to support the HDSS activities
Third, a cordial HDSS-community relationship is vital. Survival and success of the HDSS sites
largely depends on this. Employing community Interviewers from the community improves the
relationship with the community. This helps the HDSS to understand and respect the
communities’ cultures and related traditions. Designing interventions that contravene local
traditions or conducting studies in a manner that is offending to the local population can
antagonize the cordial relationship between the two sides. Indeed, HDSS sites have a duty to
maintain this relationship and to continually provide feedback to the community on the outcomes
of the interventions carried out. The feedback mechanisms need to be elaborate and exhaustive
and must include all the stakeholders, starting from the district to the household level. It is also
important to ensure that the stakeholders from the community are adequately informed prior to
conducting any field activity.
Fourth, an understanding of all the parties (stakeholders, funders and the community)
concerning the activities to be carried out and use as well as sharing of data is extremely
important as it avoids conflict that could arise at a future date .
Fifth, it is important to keep the staff well trained and motivated at all times. Field activities are
particularly exhaustive both physically and psychologically. The accuracy and reliability of the
data received from the field is, to a large extent, dependent on the interviewing skills and morale
of the field worker. Within a limited resource constraints context and insufficiency of funding,
like the situation faced, other kind of incentives can help to keep all staff motivated. This has to
be planned ahead of the HDSS establishment.
Finally, running a HDSS site is expensive and sensitive to time. Proper advance planning is
important to avoid staggering the planned activities and thereby ensuring accurate measurement
of the variables of interest.
Implementing a HDSS site provides several challenges, however there are enormous benefits of
a HDSS especially the generation of timely and representative data from the community that not
only supplements health facility generated data, but also facilitates formulation of local health
interventions, which are community friendly. Nonetheless, whatever the challenges and obstacles
encountered, we learned that these can be overcome if the concept of the HDSS was explained
and was acceptable to the stakeholders and the community. By sharing our challenges in setting
up the Webuye HDSS, we hope these experiences and the techniques used in solving them will
inform others who wish to start HDSS in other parts of the sub-Saharan Africa to address local
We thank the Moi University-VLIR UOS collaborative programme for providing funds to run
this project. The CDC Kisumu HDSS is acknowledged for assisting with the logistics to start the
Webuye HDSS. The Provincial Administration and other stakeholders are acknowledged for
allowing us to access the community, while the community is thanked for accepting to
participate in the project. We also wish to thank the Deans of Schools of Medicine and Public
Health for granting permission to setup the Webuye HDSS site and compile this report.
All the authors participated in the design of the project. CJS, VN, AAO, RD and BOK drafted the
manuscript. PA, JDM, WPO, MT, DVB, DM, EM, DC, DOO, EOW participated in the review of
1. Bangha M, Diagne A, Bawah A & Sankoh O.(2010) .Monitoring the millennium
development goals: the potential role of the INDEPTH Network. Global Health
Action,3( ),p. 5517.
2. Lopez AD, AbouZahr C, Shibuya K & Gollogly L.(2007) .Keeping count: births,
deaths, and causes of death. Lancet,370( 9601),pp. 1744-1746.
3. Mahapatra P, Shibuya K, Lopez AD, Coullare F, Notzon FC, Rao C, Szreter S.
(2007) .Civil registration systems and vital statistics: successes and missed
opportunities. Lancet,370( 9599),pp. 1653-1663.
4. Setel PW, Macfarlane SB, Szreter S, Mikkelsen L, Jha P, Stout S, AbouZahr C.(2007)
.A scandal of invisibility: making everyone count by counting everyone.
Lancet,370( 9598),pp. 1569-1577.
5. AbouZahr C, Cleland J, Coullare F, Macfarlane SB, Notzon FC, Setel P, Szreter Set
al.(2007) .The way forward. Lancet,370( 9601),pp. 1791-1799.
6. Nhacolo A, Nhalungo D, Sacoor C, Aponte J, Thompson R & Alonso P.(2006)
.Levels and trends of demographic indices in southern rural Mozambique: evidence
from demographic surveillance in Manhica District. BMC Public Health,6( 1),p. 291.
7. INDEPTH N. (2002).Population and health in developing countries. volume 1,
population, health and survival at indepth sites. Ottawa: International Development
8. Binka FN, Ngom P, Phillips JF, Adazu K & MacLEOD BB.(1999) .Assessing
population dynamics in a rural african society: the Navrongo demographic
surveillance system. Journal of Biosocial Science,31( 03),pp. 375-391.
9. Chandramohan D, Shibuya K, Setel P, Cairncross S, Lopez AD, Murray CJL, Zaba B
et al. (2008) .Should data from demographic surveillance systems be made more
widely available to researchers?.PLoS Medicine,5( 2),p. e57.
10. Adazu K, Lindblade KA, Rosen DH, Odhiambo F, Ofware P, Kwach J, Van Eijk
AMet al.(2005) .Health and demographic surveillance in rural western Kenya: a
platform for evaluating interventions to reduce morbidity and mortality from
infectious diseases. The American Journal of Tropical Medicine and
Hygiene,73( 6),pp. 1151-1158.
11. Binka FN, Nazzar A & Phillips JF.(1995) .The Navrongo community health and
family planning project. Studies in Family Planning,26( 3),pp. 121-139.
12. Kinyanjui S & TimÃ¦us IM. ().The international network for the demographic
evaluation of populations and their health (indepth), the importance of core support. :.
13. Moi University COBES website.(Accessed: 27th March, 2012). Available at:
14. Bungoma District Statistics Office.(2006). Bungoma District Profile.,( ),.
15. Kenya National Bureau of Staistics. (2010).Population distribution by administrative
units. Nairobi, Kenya:Government Printer.
16. Moi University MU-K_VLIR-UOS website.(Accessed: 30th August, 2010). Available
17. Naanyu V, Sidle JE, Frankel RM, Ayuku D, Nyandiko WM & Inui TS.(2011)
.Rooting inquiry in tradition: the health baraza as a tool for social research in Kenya.
Qualitative Health Research,21( 1),pp. 14-26.
18. The INDEPTH Network resource kit.(Accessed: 30th August, 2010). Available at:
19. Hightower AW, Ombok M, Otieno R, Odhiambo R, Oloo AJ, Lal AA & Nahlen BL.
(1998) .A geographic information system applied to a malaria field study in western
kenya. The American Journal of Tropical Medicine and Hygiene,58( 3),pp. 266-272.
20. MacLeod B, David L & Phillips JF.(1992) .“The Household Registration System : a
database program generator for longitudinal studies of households,” ..Social Science
Computer Review,Duke University Press..
21. Phillips JF, Macleod BB & Pence B.(2000) .The household registration system:
computer software for the rapid dissemination of demographic surveillance systems.
Demographic Research,2( ),p.  p..
22. Baiden F, Hodgson A & Binka FN.(2006) .Demographic surveillance sites and
emerging challenges in international health. Bulletin of the World Health
Organization,84( 3),p. 163.
FIGURE 1: MAP SHOWING THE WEBUYE HDSS ENUMERATION AREA
FIGURE 2. MAP SHOWING THE DISTRIBUTION OF HOUSEHOLDS IN WEBUYE HDSS