• Nov
    17
    2016
    To understand the magnitude of an epidemic we often need rapid and low cost-information. In some of the countries where Kimetrica works, security conditions, the capacities of local health authorities and the physical infrastructure, all contribute to making conventional serological and anthropometric surveys extremely costly and time-consuming. So it is natural to ask whether there are cheaper, faster alternatives. Of course the alternatives do exist, but are they reliable? How do we resolve the apparent trade off between cost and accuracy to identify appropriate and sustainable measurement solutions? Read more –>
  • Aug
    30
    2016
    In any sphere of human activity, success requires focused effort and specialization. Socrates makes the point in Plato’s Republic written around 360 BCE. People and organizations should do more of what they do best, yet nonprofit organizations working in international development are often unfocused and unspecialized. Nonprofits face formidable incentives to lose focus, especially if they are defined by what they want to achieve (like “poverty reduction) or by who they want to help (like “children” or “refugees”) rather than by what they do. This blog is a summary of a Kimetrica White Paper that argues if organizations are interested in achieving high and measurable performance, they need to resist the temptation to drift and take deliberate regular steps to focus and refocus. Read more –>
  • Jun
    27
    2016
    Given the lack of resources, assistance and interventions often need to be targeted to those most in need or at risk. Most examples of targeting focus on targeting in – identifying those that should be included in the assistance programme or intervention. This works well when there is a clear characteristic or set of characteristics that define this group. However, in some circumstances, it may be better to target out -- to look for ways of identifying individuals who should not be included in the programme. Read more –>
  • May
    19
    2016
    Recently our analysis team came across the interesting problem of aggregating ranking correlation coefficients to higher levels within a refugee camp. We had data in which community leaders ranked the vulnerability of a subset of households and actual rankings of these households based on consumption expenditure. This data was on the block level. Our goal was to determine how well community leaders were able to accurately rank the vulnerability of households on a block level. We also wanted to see how these community leader ranking correlations aggregated up on a zone and subcamp level. Read more –>