Indicator Development Surveillance for Urban Emergencies
The indicator Development for Surveillance of Urban Emergencies (IDSUE) was a five year project funded by the USAID (Office of U.S Foreign Disaster Assistance-OFDA) and implemented by Concern Worldwide in partnership with African Population and Health Research Center (APHRC). The project's aim was to develop and empirically test a set of emergency indicators for an urban slum environment. The project was to empirically define indicators of urban emergencies suitable for triggering a humanitarian response. This work was to feed into a larger movement in Kenya to identify such indicators as well as fill a critical knowledge and information gap that currently prevents humanitarian actors from effectively and equitably responding to the emergency needs of Kenya's urban poor.
Version 1.2, 2014: Rounds 1 to 4 documented, Anonymized, DOI and Recommended Citation added.
The study was conducted in Nairobi county (Korogocho, Viwandani, Dandora, Jericho, Mukuru) and Kisumu (Obunga, Nyalenda). The study sites were visited differently over the entire 7 rounds: Korogocho and Viwandani for all 7 rounds, Mukuru for round 4 to 7, Obunga and Nyalenda for rounds 5 to 7, Dandora for rounds 4 and 5, and Jericho for round 5
Unit of Analysis
Basic unit of analysis or observation that the study describes is a household.
The target study population was residents of the seven communities (Korogocho, Viwandani, Mukuru, Dandora, Nyalenda, Obungo and Jericho) and the sampling unit was a household.
Producers and sponsors
Authoring entity/Primary investigators
African Population and Health Research Center
USAID Office of U.S Foreign Disaster Assistance
Efforts were made by the study team to ensure that all populations in the selected settings were well represented in the study through the sampling methodology used. Selections of households in the seven communities followed the following procedure.
1. The sample size of 400 households was targeted for each slum to be selected across all the villages included in the survey.
2. The selection of households involved use of a modified cluster sampling using segmentation of villages due to the absence of household or enumeration area listings.
3. Each slum was divided into villages for which approximate boundaries have been mapped. Each village was subdivided into sampling segments for the purpose of household selection and to ensure spatial representativeness in the selection.
4. The number of segments in each village was based on the estimated number of households in the village. On average about 10 households were selected from each segment.
5. The segments were treated as geographic strata to ensure that sample is taken from the whole slum area. Within each segment, smaller sub-segments were delineated by teams on the ground. These sub-segments were approximately 150-200 households in size.
6. After sub-segments are defined they will be assigned a number and a random sample of sub-segments was taken from each segment (most segments had 4 sub-segments being selected).
7. In each selected sub-segment the field worker created a full household listing by moving systematically through the sub-segment and listing the households in each dwelling structure.
8. The fieldworker then randomly selected 3 households from the sub-segment household list for interview.
Deviations from the Sample Design
A total of 13,048 household visits were made over the 7 rounds of data collection in all the study sites (Viwandani-3673, Korogocho-3691, Dandora-828, Mukuru-2076, Jericho-313, Obunga-1096 and Nyalenda-1372).
Dates of Data Collection (YYYY/MM/DD)
Mode of data collection
There were approximately 70 field workers selected in the rounds of data collection for the seven data collection sites. Each site had two team leader and approximately 8-12 field workers. The fieldworkers collected and recorded the survey information on their netbooks or the mobile data collection systems while the team leaders planned the survey collection logistics, managed the data collection, organized the selection of the households, observed interviews, and checked the data for quality.
Completed quantitative interviews were reviewed by the field worker and sent electronically to the supervisor each day for quality checks. The data was then synchronized to the main database on a daily basis for back up. Overall data collation was done by the project Data analyst.
Type of Research Instrument
The household questionnaire was administered in Kiswahili for each selected household to credible respondent (mainly household head). Data were collected using electronically programmed questionnaires in netbooks and android phones. The questionnaire included sections on Household living arrangements, Source of drinking water, Hygiene & sanitation domain, Food security domain, Food consumption and expenditure, Health and health seeking behavior, Interpersonal relationships, Personal and property security domain, Non-food consumption & expenditure, Household livelihoods and coping strategies.
Data analyst was in charge of harmonizing data structure from both Netbooks and mobile phone system. The processing included harmonizing variables name, labels and codes. The editing also included generating common indicators.
Data were collected electronically using netbooks and android phones during the interviews.
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African Population and Health Research Center, Indicator Development Surveillance for Urban Emergencies, December 2013. APHRC, Nairobi. doi:11239/176-2011-023-1.2
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