The COVID-19 pandemic has created an urgent need for timely data and evidence to help monitor and mitigate the social and economic effects of the crisis. Once the recovery from the pandemic had started new shocks hit Kenya, including drought and inflation, resulting in a continued need for timely monitoring. In response, a high-frequency phone survey with households was designed and implemented to measure the socio-economic impacts of these shocks in Kenya and monitor the recovery.
The high-frequency phone survey on the socio-economic impacts of shocks, includingCOVID-19, droughts, and inflation, in Kenya is implemented by the World Bank, in collaboration with the Kenyan National Bureau of Statistics (KNBS) and the United Nations High Commissioner for Refugees (UNHCR) as well as the University of California, Berkeley.
The data is collected by phone interviews [i] with households from three different groups. The first group of households is drawn randomly from a subset of the Kenya Integrated Household Budget Survey in 2015/16. The second group is reached by Random Digit Dialing, whereby phone numbers potentially existing in Kenya are randomly generated. These first two groups cover urban and rural areas and are designed to be representative of the population of Kenya using cell phones. The third group consists of refugees registered with UNHCR and living in refugee camps as well as urban areas.
The questionnaire covers a range of topics including experiences of shocks, knowledge of COVID-19 and mitigation measures, changes in behavior in response to the COVID-19 pandemic, employment, income, food security, access to educational activities and health services, subjective well-being, perceptions of the government¡¯s response, and coping strategies.
Data collection started in May 2020 and households were called repeatedly since then, to track the impact of shocks over time. Households were called every two to four months. For waves 1 to 7, the subgroup of households interviewed in each week is representative of the surveyed population, allowing the analysis of trends as in the above dashboard.
Phone-based surveys avoided face-to-face interviews and the associated health risks during the COVID-19 epidemic. However, they can only reach respondents who use a phone with an active subscription in an area with network coverage and ¨C of course ¨C who agree to be interviewed. Therefore, statistics from such a survey are only representative for this part of the population ¨C potentially excluding to some extent the poorest households living in hard-to-reach areas or who don¡¯t own phones. The Kenya rapid response phone survey uses re-weighting techniques to mitigate these issues and to ensure that statistics are as representative of the full population of Kenya as possible.