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It was originally published on the REAL Australian Sceptics blog and bears repeating. This information and the graphs included are excerpted from Mr Beattie. It demonstrates very clearly that a true sceptic will not necessarily believe in headlines such as . Others will have undoubtedly seen a stream of. However, the bodies of the stories leave us in no doubt as to the reason for their headlines. Here are some direct quotes: In a rare public health success story on the world. There is something deeply disturbing about the stories, and it is not immediately apparent. The fact is: no- one knows how many people died of measles in Africa. Not last year and not ten years ago. I will repeat that. So, where did these figures come from? I will explain that in this blog. In a nutshell, they were calculated on a spreadsheet, using a formula. You may be surprised when you see how simple the method was. We all believe these stories, because we have no reason to doubt them. The only people who would have questioned them were those who were aware that the deaths had not been counted. One of these was World Health Organisation (WHO) head of Health Evidence and Statistics, who reprimanded the authors of the original report (on which the stories were based) in an editorial published in the Bulletin of the WHO, as I will discuss shortly. Unfortunately, by then the train was already runaway. The stories had taken off virally through the worldwide media. Overview. First, an overview of the formula. The authors looked at it this way: for every million vaccines given out, we hope to save . From that premise, we simply count how many million vaccines we gave out, and multiply that by . That is how the figures were arrived at. The stories and the formula are both products of a deep belief in the power of vaccines. We think the stories report facts, but instead they report. That was possibly understandable. Why would we need to check them? After all, they were produced by experts: respected researchers, and reputable organisations such as UNICEF, American Red Cross, United Nations Foundation, and the World Health Organisation. However, I did check them. I checked because I knew the developing world wasn. In fact, it is currently estimated that only 2. Sub- Saharan Africa, where a large proportion of measles deaths are thought to occur, still had an estimated death registration of only around 1. Even sample demographic surveys, although considered accurate, were not collecting cause- of- death data that allowed for these figures to be reported. Simply put, this was not real data: the figures. After reading the article, I realised the reports were not measles deaths at all. In other words, they represented outcomes that the Measles Initiative had. We all know that planning and predicting are very useful, even necessary activities, but it is obvious they are not the same as? A natural history modelling study. I will simplify it in about ten lines. I realise that in doing so, some may accuse me of editorial vandalism, however I assure you what follows captures the essence of the method. If you are interested in confirming this, I urge you to read the original article for that detail. As you can see, this is a typical approach if we are. Using a spreadsheet to predict outcomes of various plans helps us set targets, and develop strategies. When it comes to evaluating the result of our plan however we need to go out into the field, and measure what happened. We must never simply return to the same spreadsheet. But this is precisely what the Measles Initiative team did. And the publishing world swallowed it. Writing editorially in the Bulletin of the WHO, under the title . However, that is no reason for us to avoid measuring it when we can also measure the quantity of interest directly; otherwise the global health community would continue to monitor progress on a spreadsheet with limited empirical basis. Users must be realistic, as annual data on representative cause- specific mortality are difficult to obtain without complete civil registration or sample registration systems. If such data are needed, the global health community must seek indicators that are valid, reliable and comparable, and must invest in data collection (e. Only by doing so will the global health community be able to show what works and what fails. In simple terms, Shibuya was saying: We know it is difficult to estimate measles deaths, but. You should have tried, because you attracted a lot of interest. Instead, you simply went back to the same spreadsheet you used to make the plan. So, without scientific scrutiny, the stories were unleashed into a world hungry for good news, especially concerning the developing world. Was it the architects of the original report? Or was it the robotic section of our media (that part that exists because of a lack of funds for employing real journalists) who spread the message virally to every corner of the globe, without checking it? One quote which really stands out in the stories is from former director of the United States Centers for Disease Control (CDC). Julie Gerberding. What strategy works? Is she talking about modelling on a spreadsheet? Or, using the predictions in place of? More recent reports from the Measles Initiative indicate the team are continuing with this deceptive approach. In their latest report. All were calculated on their spreadsheet, and all were attributed to vaccination, for the simple reason that it was the only variable on the spreadsheet that was under their control. And still there is no scrutiny of the claims. Furthermore, the authors make no effort to clarify in the public mind that the figures are nothing but planning estimates. No proof. Supporters of vaccination might argue that this does not prove vaccines are of no use. In fact,let me say it first. That is the crux of the matter. The media stories have trumpeted the success of the plan, and given us all a pat on the back for making it happen. But the stories are fabrications. The only aspect of them which is factual is that which tells us vaccination rates have increased. Some . That means deaths from. Because an inter- agency group, led by UNICEF and WHO, has been evaluating demographic survey data in countries that do not have adequate death registration data. These surveys have been going on for more than 5. One of the reasons they do this is to monitor trends in mortality; particularly infant, and under- five mortality. Although the health burden in developing countries is inequitably high, there is reason to be positive when we view these trends. Deaths are declining and, according to the best available estimates, have been steadily doing so for a considerable time; well over 5. One of the most useful indicators of a country. The best estimates available for Africa show a steady decline in under- 5 mortality rate, of around 1. Figure 1 shows this decline from 1. Both are plotted as averages of all countries in the WHO region of Africa. Figure 1. Child mortality, Africa. This graph may appear complex, but it is not difficult to read. The two thick lines running horizontally through the graph are the. The handful of finer lines which commence in 1. The vertical scale on the right side of the graph shows the rate at which children were vaccinated with each of these shots. The primary purpose of this graph (as well as that in Figure 2) is to deliver the real. We see a slowly, but steadily improving situation. Death rates for infants and young children are declining. I decided to add the extra lines (for vaccines) to illustrate that they appear to have had no impact on the declining childhood mortality rates; at least, not a positive impact. If they were as useful as we have been led to believe, these vaccines (covering seven illnesses) would surely have resulted in a sharp downward deviation from the established trend. As we can see, this did not occur. In Africa, the vaccines were introduced at the start of the 1. The only effect observable in the mortality rates, is a slowing of the downward trend. In other words, if anything were to be drawn from this, it would be that the introduction of the vaccines was counter- productive. One could argue that the later increase in vaccine coverage (after the year 2. However, that does not line up. The return to the prior decline predates it, by around five years. With both interpretations we are splitting hairs. Since we are discussing an intervention that has been marketed as a modern miracle, we should see a marked effect on the trend. The country that is believed to share the majority of worldwide child mortality burden with sub- Saharan Africa is India, in the WHO south- east Asia region. Together, the African and South- east Asian regions were thought in 1. Again, the introduction of various vaccines is also shown. Figure 2. Child mortality, India. And again, vaccines do not appear to have contributed. Mortality rates simply continued their steady decline. We commenced mass vaccination (for seven illnesses) from the late 1. In a nutshell, what happened in the developed world is still happening in the. The processes of providing clean water, good nourishment, adequate housing, education and employment, freedom from poverty, as well as proper care of the sick, have been on- going in poor countries. I would have loved to go back further in time with these graphs but unfortunately I was not able to locate the data. I did uncover one graph in an issue of the Bulletin of the WHO, showing the under- 5 mortality rate in sub- Saharan Africa to be an estimated 3. It subsequently dropped to around 1. It continued dropping, though slower, to 1. When cause- of- death data improves, or at least some genuine effort is made to establish credible estimates of measles deaths, it will undoubtedly be found they are dropping as well. This is good news, and all praise needs to be directed at the architects and supporters of the international activities that are helping to achieve improvements in the real determinants of health.
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