 My name is Professor Bob Snow, I work for the Kenya Medical Research Institute Welcome Trust programme in Kenya and the University of Oxford in the UK. I'm here today to talk about the paper that was published this week in Nature. The work represents 21 years of research effort which began in 1996 and focuses on the malaria parasite prevalence rate and that's a measure of the quantity of malaria often done through surveys of communities to work out how many people have the parasite in their blood. Now this is a good indicator of the amount of malaria in any given area because it's really really hard to measure how many people die of malaria and how many people get sick of malaria in Africa largely because they share symptoms of science with many other causes but actually knowing whether or not you have the parasite in your blood is pretty unambiguous. So we've focused on trying to find survey data that's spanned over 100 years in Africa bearing in mind that these surveys were first done in the early 1900s by researchers working in Sierra Leone, working in Ghana, working in Nigeria and working in other areas of Africa. And it's been a huge effort. I mean largely we've had to go to archives across the continent some of them incredibly dusty and dirty. We've had to dig down into sort of the Ministry of Health's basements, pull out boxes covered in wood lice and rat droppings to salvage some of these really old survey data. And it's been a fantastic experience to be honest. It's been a bit like the Indiana Jones side of my job trying to track down these survey data. We've had some fantastic experiences finding people who've retired from the area working in Southern Africa, identified where they live, go to their houses, spend a couple of days with them in their garage finding all the survey records from Botswana and Namibia in the 1950s and 1960s. We've been to libraries and archives of the old eradication programmes in Senegal, Ghana, Nigeria, Uganda, Tanzania, Sudan. Some of these have been great successes and we've been in little joys finding treasures of original survey data. For example, in Uganda, we found the original survey records, cards with everybody's name, village and so on, how many, when they had their blood sample taken, the results of microscopy in Entebbe. We were told that the eradication programme did surveys in 1965 and 1967 and those records were housed in Ginger, not in Entebbe. We found the man who had the key to the old store. We tracked him down, took us about two days to find him, about another day to find the key, only to discover that they weren't there and they'd been moved to another part of the hospital in Ginger. Took us another two days to find that person with that key. We get there, we open the door and there's nothing there. He points out to us that two years beforehand they were in fact all burnt, just to make space. Part of this project is being to preserve these original records and find them before they do in fact completely disappear. Other examples, like I say, are in Sudan where we tried desperately to find all the survey data done in the big surveys in the early 60s by the Vernon store for brothers, where they sampled thousands of villages across Sudan and combined Sudan in those days north and south. But only to discover having tried for weeks in all the possible locations that they're probably somewhere in Europe. So there's an example, a bit like the Elgin marbles, that there are original survey data that were done but we just can't track them down. So it's been a long effort and of course it's been helped hugely by the very, very large number of malaria scientists working today across the continent. Over 900 malariaologists working in the whole of Africa actually have been incredibly generous and shared their data with us. This is raw data. It's often published but in an aggregate form and they've disaggregated it by village to share with us as part of that project. Once we've got access to this original material or published material we then extract from that report where the village is and this takes a lot of effort actually because names change over time and we have to provide a precise longitude and latitude for each of the villages. How many people were surveyed, the month and year of the survey and how many were positive for Plasmodium falcibrum which is the main parasite that causes a majority of diseases in Africa. This then goes into a large database and we attach to that every single PDF, an electronic digital copy of the original materials. Now these have now been archived and we've shared them with the World Health Organization's global malaria programme recently. So in fact there is a legacy of these data and there is an institutionally legitimate partner to houses so they are now with the WHO in Geneva. So once we have all the data, of course it took 21 years to assemble it all you need to try and understand what does it mean. So our main objective for a very long time now has been what has been the long term history of malaria in Africa. Many people who have published lots of work recently have focused on only 2000 to 2015 and many of them have shown that malaria has indeed dropped but actually that doesn't give us that lens of what did happen before 2000. What did malaria look like in Africa before then? So this big assembly of 115 years worth of data now has over 50,000 survey points geolocated and nearly 30,000 villages gives us a unique opportunity to try and understand what has happened over 100 years. To do this we didn't want to over model it I mean one of the temptations is to create very very complicated models which include lots of layers of information on how climate has changed how intervention has changed and you build it all together and you try and use those what they call covariates to predict what malaria is in any given location. Rather than do that we've decided to actually just let the data themselves tell the story. So we haven't used any covariates rather what we've done is take each of the individual survey points and displayed them over 520 administrative units across Africa and these are largely administrative units quite large ones and Madagascar Madagascar being the largest of the offshore islands we haven't included the other smaller islands so it's just mainland sub-Saharan Africa and Madagascar divided into 520 units and then we've tried a simple statistical model which smooths the data in space and in time borrowing the information from each of the points in each of those administrative areas to give us a prediction of malaria based on the data in each of those units for one of 16 time points starting in 1900, ending in 2010, 2015 so we've segmented time and we've segmented space and then we summarise all that data just by having the median estimate for the whole of Africa and Madagascar over those 16 time periods. Now what these data show when you actually summarise it is that first of all there was a huge amount of survey data collected in the 1950s and 1960s in preparation for a malaria eradication so Africa was part of the global malaria eradication era so there was lots and lots of survey effort done during that period and there's a lot of data more recently during the period of the rollback malaria initiative and the new investment by the global fund so there's a lot more survey data then so our periods of greatest data are in the 50s, 60s and more recently since 2005 Nevertheless there is quite an awful lot of data actually available to make some predictions throughout the rest of the time periods and what these data show is that malaria probably affected 40% of children in 1900 to 1920 Maybe the parasite prevalence rates were in the 40s, 50s 40% and 50% and so every other child was carrying the malaria parasite Now over time that has dropped it's dropped quite considerably actually to about 24% so it's gone from 40% to today, 2010, 2015 to about 24% and that's a significant drop but that actually doesn't tell the whole story because if you look at the data there have been troughs and there have been peaks and these peaks are probably explained by a coincidence of excessive rainfall the worst El Nino rainfall that hit Africa happened in the 1990s, late 1990s and the emergence of chlorachon resistance so you had these congruence of two factors which led to the perfect storm and actually malaria prevalence rose quite rapidly to a very very high level in the late 90s, early 2000s but it was slightly less easy to explain lull before that and that lull was coincidental with a drought in the Sahara no rainfall, no mosquitoes, no malaria so that's kind of how one might understand it but it was also a period when everybody was taking chloroquine and chloroquine was an incredibly effective drug and every single fever was treated with this drug and therefore parasite prevalence is likely to have been suppressed by to all intents and purposes mass drug administration of chloroquine and of course that will then lead to that explanation of that massive rise when chloroquine began to fail there was a big drop before then and that big drop did coincide with the introduction of new tools from malaria and in the 1990 after the Second World War that was chloroquine but it was also DDT used for indoor residual house springs so you had these two so-called magic bullets that were introduced to Africa in the late 40s, early 50s began to be used more widely across the continent and you did see that big drop from the high levels of the 1900s, 1920s, 1930s and of course if you now fast forward to the roll-back malaria era we had two other magic bullets we had insecticide treated bed nets and Artemisinin based combination therapy to replace failing chloroquine and failing solvodoxyne parameter and again, there we saw from about 2005 to 2010 one of the biggest drops that Africa has ever witnessed so that gives us an understanding of it but it's not as straightforward as people might imagine people like to think that linear things are associated with linear linear rises are associated with linear declines so in Valkyrie there is a very large body of research that suggests that global warming has affected malaria and it has, I mean global warming does affect malaria at the margins does affect the sea surface temperatures in the Pacific it does actually lead to excessive rain for it it's not to deny the climate's important it's just that that linear association between increasing land surface temperatures and an increasing malaria can't it be explained by our data on its own nor can that for that matter increasing economic development Africa has witnessed a huge increase in GDP or almost all the countries not universally but most countries have witnessed a very large increase in GDP there's been an increasing percentage of girls going to school there's lots of development things that have happened but that can't explain that epidemic that we witnessed in the late 90s and early 2000s so what this all tells us of course is that things are complicated and that doesn't really help donors and it doesn't really help people wanting to project the future of malaria in Africa but they are complicated things can't be explained by interventions alone they can't be explained by climate alone they can't be explained by development alone they are congruence and a composite of all of these things and actually that is one lesson of this paper is that we need to understand things in its entirety and don't make too many assumptions there are some things though that we might be able to predict for the future and the first is that resistance is an absolute killer for malaria and the cycles of malaria on the continent I mean if drug resistance Danovo Artemis and drug resistance was to hit Africa if pyrethroid resistance was to escalate to the point where insecticide treated bednets were no longer effective and we had a sort of another El Nino crisis I think we will see another epidemic that we saw in the 90s and early 2000s the other thing if you look at the map distribution of malaria over time is that there is one thing that jumps out at you there is a central belt of Africa running from below the Gambia sort of from Guinea-Bissau all the way through West Africa Ghana, Nigeria, Burkina Faso all the way through central Africa down to the southern part of Mozambique where in actual fact malaria intensity hasn't changed the prevalence of P-fold siperum infection prevalence in the communities that occupy that area hasn't changed as much as it has at the margins as one probably might expect this is an area that's home to an awfulies can't be censored strict to which is the most efficient vector that we know on the planet but it does beg the question as to whether or not we will achieve global eradication in our lifetimes which is a quote that is often used because essentially it might be possible to remove those last residual numbers of cases in the Solomon Islands or Saudi Arabia but focusing your attention on global eradication and elimination at the margins ignores the fact that you have this belt that's remained pretty much the same for 100 years in Africa that's millions and millions of people who continue to suffer from the disease and for which actually the tools that we have at our disposal now which is prompt treatment with effective medicines insecticide treated bed nets some attempts at indoor residual house spraying aren't enough so we need new tools so if two things we can't ignore that central part of Africa and secondly we need some new tools in our toolkit to tackle that burden in some ways I'm somebody who doesn't necessarily buy into the whole sort of elimination notion for Africa over the next 30 years I think we need to change the narrative change the language to the point where bearing in mind that for 100 or so years we haven't made that much of a dent in that middle bit is that one thing that we can probably promise and probably can guarantee is that no child should die of malaria or nobody should die of malaria so zero deaths is an achievable ambition over the next 30 to 50 years and I think actually trying to shrink the map in Africa as shown by the paper that was published this week and eliminate malaria transmission in that central belt is almost an impossible dream certainly within our lifetimes