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Using Bad Data to Obscure Deadly Errors


In an article published in early December 2012, Jacques Pepin and colleagues reported that less than 1 in 20 Africans received an unsafe injection in 2010.[1] According to them, this was a huge improvement from the situation in 2000, when more than 1 in 3 got an unsafe injection.

The story sounds good, but let’s put it into context.

First, these rosy estimates distract from facts that need answers. Why do 16%-31% of HIV-positive children in Mozambique, Swaziland, and Uganda, have HIV-negative mothers (among children with tested mothers; see: https://dontgetstuck.wordpress.com/cases-unexpected-hiv-infections/). Why do so many mutually monogamous couples find that one or both partners are HIV-positive?

Second, the authors accept a double standard. In countries that fund health aid programs in Africa, governments respond to recognized reuse of unsterile instruments in health care with investigations to see if patients have been harmed. For example, after authorities in New Zealand found that a clinic had reused unsterilized instruments, governments of New Zealand and Australia issued a public notice warning people who had attended the clinic during 2010-12 that they might have been exposed to hepatitis B, C, or HIV and inviting them to come for tests.[2] But if the clinic with recognized unsafe procedures is in Africa, the response is entirely different. In Africa, people who present themselves as concerned and knowledgeable about health care safety, such as Pepin and colleagues, estimate that percentages of procedures are unsafe without asking for investigations. Such bland acceptance of deadly errors endorses a double standard.

Third, what Pepin and others state as facts are weak estimates based on unreliable data. Most of their data for 2010 comes from national surveys that asked people – in the midst of several hours of questions[3] about diet, education, birth control, sexual behavior, and blah, blah, blah – how many injections they had in the last year and whether the syringe and needle for the last injection came from a sealed pack. In a long survey, people are not able to take time to think and remember. Even with time to think, it’s hard to remember numbers of injections over the past year. Consider: A survey in India asked people if they had received an injection in the last 2 weeks and if they had received an injection in the last 3 months. The estimated number of injections per person per year was 5.9 based on 2 week recall, but only 2.9 based on 3 month recall.[4]

A bad manager listens to sycophants who tell him soothing fantasies that encourage him to ignore uncomfortable facts. I expect there will be many bad managers in health aid organizations and in African ministries of health who will be only too ready to cite Pepin and colleagues’ soothing fantasies rather than to do the right thing – to trace and investigate sources of HIV infection. Pepin and colleagues are not alone. For decades, sycophants who can cobble together weak evidence and arguments to say Africans only rarely get HIV from health care have gotten more attention than so many HIV-positive children with HIV-negative mothers.


 

[1] Pepin J, Abou Chakra CN, Pepin E, Nault V (2013) Evolution of the Global Use of Unsafe Medical Injections, 2000–2010. PLoS ONE 8(12): e80948.

doi:10.1371/journal.pone.0080948. Available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3851995/pdf/pone.0080948.pdf (accessed 22 December 2013).

[2] NZers warned over HIV at Sydney clinic. New Zealand: NZCity, 16 December 2013. Available at: http://tinyurl.com/l34v4ab (accessed 22 December 2013).

[3] ICF International. Demographic and Health Surveys Methodology: Questionnaires: Household, Woman’s, and Man’s. Calverton, Maryland: ICF International, 2011. Available at: http://www.measuredhs.com/pubs/pdf/DHSQ6/DHS6_Questionnaires_5Nov2012_DHSQ6.pdf (accessed 23 December 2013).

[4] See Table II in: Arora N K, et al. Assessment of Injection Practices in India, Executive Summary. New Delhi: InClen Trust, 2005. Available at: http://www.inclentrust.org/uploadedbyfck/file/complete%20Project/Executive%20summaru/15_Main%20Report%20Book%20(29-6-06)%20only.pdf (accessed 22 December 2013).

One response to “Using Bad Data to Obscure Deadly Errors

  1. Pingback: Predicting the Millennium Development Goal Scapegoats | Don't Get Stuck With HIV

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