Background. Absence of acquired protective immunity in endemic areas children leads to higher susceptibility to severe malaria. To investigate the involvement of regulatory process related to self-reactivity, we evaluated potent changes in auto-antibody reactivity profiles in children and older subjects living in malaria-endemic zones comparatively to none-exposed healthy controls. Methods. Analysis of IgG self-reactive footprints was performed using Western blotting against healthy brain antigens. Plasmas of 102 malaria exposed individuals (MEIs) from endemic zone, with or without cerebral malaria (CM) were compared to plasmas from non-endemic controls (NECs). Using linear discriminant and principal component analysis, immune footprints were compared by counting the number, the presence or absence of reactive bands. We identified the most discriminant bands with respect to age and clinical status. Results. A higher number of bands were recognized by IgG auto-antibodies in MEI than in NEC. Characteristic changes in systemic self-IgG-reactive repertoire were found with antigenic bands that discriminate Plasmodium falciparum infections with or without CM according to age. 8 antigenic bands distributed in MEI compared with NEC were identified while 6 other antigenic bands were distributed within MEI according to the age and clinical status. Such distortion might be due to evolutionary processes leading to pathogenic/protective events. Plasmodium falciparum infection remains a major cause of death in most of developing countries, particularly in sub-Saharan Africa [n Africa . It genen Africa  or severn Africa , 4. Thesn Africa , 4, and,n Africa . Thus, un Africa .It is postulated that partial protective immunity can be induced after iterative infection through triggering the action of the immune response, particularly the humoral response , 7. ReceIn healthy subjects, despite of interindividual differences, the human serum self-IgG response is thought to be well conserved and restricted to the recognition of a few self-antigens in autologous tissues . In contIn the present study, we aimed to evaluate the impact of the environment and self-reactive natural and acquired antibody repertoires on humoral immune profiles. The findings of numerous epidemiological and clinical studies suggest that the risk of allergic and autoimmune diseases is related to the hygiene hypothesis . ParasitPlasmodium falciparum carriers) neurological symptoms. Nonimmune individuals living in countries free of malaria were tested as controls. Our data revealed the presence of antigenic bands specifically targeted by plasma IgG collected in patients of a well-defined clinical status and age range. The pathophysiological significance of such new biomarkers is discussed.To further evaluate the relationships between environmental factors, autoimmune profiles, and the clinical status of malaria, the natural and acquired self-IgG antibody responses were analyzed in subjects of different age brackets living in endemic zones of parasitic transmission. Immune profiles were compared between malaria patients with  and without , and from healthy subjects living in European nonendemic areas, termed nonendemic controls .Plasma self-IgG reactivity against brain tissue antigens was evaluated in 119 subjects. Blood samples were collected from subjects exposed to malaria parasite, termed malaria-exposed individuals . The other subgroup was termed MEI without neurological symptoms  and was comprised of parasite carriers with classical symptoms of malaria but without other complications and asymptomatic carriers (without any detectable symptoms). MEIs with symptoms  were recruited from the Emergency Department of the University Hospital of Cocody-Abidjan (Côte d'Ivoire). Using available data bases, plasma was classified on the basis of World Health Organization (WHO) guidelines. Thus, MEI with neurological symptoms included patients with a Blantyre Coma scale ≤2 (concerning the children), a modified Glasgow coma scale ≤9 (concerning the adult), the occurrence of at least one convulsive episode during the 24 h before admission to the emergency department, and Plasmodium falciparum-positive thin blood smears. As expected, all of these patients were cured after quinine therapy.The MEI group was divided into two subgroups. One subgroup consisted of patients with neurological symptoms, usually termed cerebral malaria .For the MEI group, the samples were taken on the day of admission . Venous blood was collected into EDTA sterile vacutainers (5 mL). Plasma was isolated after centrifugation at 500 ×g for 15 minutes and stored at −40°C at the “Laboratoire d'Immunologie of CHU Cocody-Abidjan” before being sent the EA 2686 Research Group (Lille-France).Parasitemia was assessed at the department of “Parasitologie-Mycologie, Faculté de Médecine d'Abidjan-Cocody-Côte d'Ivoire” as follows.Plasmodium falciparum and for parasite counts. Parasitemia is expressed as the percentage of infected red blood cells.Giemsa-stained thick and thin blood films were prepared for detection and identification of Plasmodium falciparum strain 3D7 was used as antigen using indirect immunofluorescence. Briefly, sera were diluted 1/100, 1/200, 1/400, 1/800, 1/1600, and 1/3200 in phosphate-buffered saline (Ref 77511 Biomerieux). Diluted serum was incubated with acetone-fixed Plasmodium falciparum at 37°C for 30 mn. The secondary antibody used was fluorescein-conjugated goat anti-human IgG, IgM, IgA, Heavy and Light chains-H, and L-(Ref 74511 Diagnostic Pasteur) in Bleu Evans solution (Ref 75491 Biomerieux). Any fluorescence in Fluopep (Ref 75521 Biomerieux) obtained at a dilution 1/100 was considered negative. Quantification was expressed by the titre of total antifalciparum antibodies.Anti-falciparum total antibodies detection and quantification were performed at the “Laboratoire de Parasitologie Mycologie-Centre de Biologie, de Pathologie-CHRU de Lille-France.” Acetone-fixed Brain samples were obtained as previously described , 21. BriμL of this lysate was loaded onto a 10–20% gradient polyacrylamide gel (Navix Tris-Glycine Gels-Invitrogen), beside a well of 15 μL of molecular mass marker (Amersham Pharmacia Biotech). Just before 1-dimension electrophoresis (1D), the homogenates were reduced for 10 min with 10 mM DTT (Sigma-Aldrich) at 100°C. Then electrophoresis was run in Laemmli buffer using the following conditions: run time 2 h at constant 125 V and 30–40 mA/gel (start); 8–12 mA/gel (end).The brain samples were homogenized in a Tris buffer containing 5% SDS at a final concentration of 10 mg/mL and heated at 95°C for 10 min. 100 2 and later saturated with 5% fat-free dried milk. Nitrocellulose membrane was cut into 15–20 strips, 3 to 4 mm wide. Western blotting was conducted with total sera, diluted 1/100 in TNT  and 5% fat-free dried milk. Reaction IgG antibodies were revealed with an anti-human Fcγ HRP-conjugated antibody  after overnight incubation at 4°C. Fluorograms were prepared using an enhanced chemiluminescence kit (Amersham Pharmacia Biotech Europe). Immune profiles were analyzed when 2 independent assays had produced identical patterns. Image analysis was performed on a Molecular Imager GS-800 Calibrated Densitometer (Bio-Rad) to localize and compare the IgG immune profile patterns. Band detection, alignment, and matching of the antibody reactivities were performed using Phoretix 1D and 1D Pro software version 10  and validated by two operators. We performed comparative analyses using detection-band parameters that allowed us to consider each band intensity that was >13% higher than the global background intensity of the gel to be significant. To calibrate and more accurately define the alignment of antibody reactivities, molecular weight marker protein standards  as well as internal reference standards were used. The level to which each molecular standard migrates is called relative front of migration (RF). A function curve defined by RF values on the X axis and standard molecular weight on the Y axis allowed the molecular weight of each antigenic band to be determined by extrapolation because the reactive band align on its RF.Proteins were transferred onto ECL nitrocellulose membranes (Amersham Pharmacia Biotech) at 0.8 mA/cmData were expressed in binary mode (0 = absence of an antigenic band and 1 = presence of an antigenic band) for submission of IgG antibody patterns for analysis using either the chi-square test or Fisher's exact test. This approach allowed us to select the most relevant antigens that qualitatively supported different types of immune recognition. We then used linear discriminant analysis (LDA) to balance the discriminating antigens between the populations of individuals, as described previously , 23. UsiThe calculated scores were then represented graphically. A threshold value was determined using a receiver operating characteristic curve, and the sensitivity and specificity of this approach were evaluated. When the number of patients was too small to apply LDA, chi-square and Fisher's exact tests were performed to retain the most discriminant band. To compare the number of bands between the different groups of subjects, we used the chi-square test. The frequency of each discriminant self-reactive band has been calculated determining its percentage of its presence within the group of subjects.Using principal component analysis (PCA) and nonparametric test of Kruskal-Wallis, we evaluated the relationship between the discriminant band and the clinical status.Self-IgG reactivity against human brain was compared between patterns obtained with plasma samples from the MEI group, with or without neurological symptoms (subjects from 1 to 86 years old), and those obtained with samples from the NEC group . Self-Ign = 102, mean ± SD: 14.9 ± 3.9) than in NEC group . Comparison of subjects within the MEI group did not reveal any significant differences . Furthermore, no correlation was found between the number of protein bands within MEI and the titre of antifalciparum antibodies evaluated by the procedure described in materials and methods . Quantifiable data were given after the mapping and alignment of all patterns which revealed 4 to 19 bands according to the strips. When all of the strips were considered, there were more antigenic bands in the MEI (n = 42) was evaluated on each strip. Despite interindividual differences, some conserved sets of protein bands were found. As indicated in For qualitative analysis, the presence or the absence of each protein band for all bands identified in the 119 strips  showed a different distribution in MEI Age is already known to influence the course of malaria infection . We therP < 0.250) per age group . As shown in P < 0.05) of band frequencies showed no discriminatory bands to be coexpressed in two age groups. Therefore, this excludes frequency changes related to age and clinical status. Only the p94 and p74 antigenic bands . To confirm a tight relationship between MEI with neurological symptoms or CM, a complementary LDA was performed which accounts for the occurrence of CM irrespective of the age of MEI. Three bands including p94, p140, and p145 were then identified (data not shown) to discriminate between CM (1–5 years old), CM (6–15 years old), and CM (16–30 years old). The 2-dimensional PCA shown in Plasmodium falciparum underlies most cases of severe and fatal malaria. Among the complications of this preeminent tropical parasitic disease, CM and severe anemia are the most common causes of death, especially in children under the age of five years, and in pregnant women and malaria-naïve individuals [ividuals . Althougividuals , the lacividuals . These dividuals , 27 althividuals . In contividuals . The exaPlasmodium falciparum has been shown to have considerable genetic diversity, which is facilitated by the haploid state of all plasmodial stages in the human host. This genotypic variability is expressed by a microgeographical heterogeneity of the parasite [Plasmodium falciparum antigens evaluating IgG but also IgA and IgM isotypes); such data suggest a possible involvement of natural and/or acquired autoantibody responses in the observed patterns. The participation of the natural autoantibody repertoire is also suggested by some protein bands commonly recognized by all tested plasmas (MEI and NEC groups). Previous data underlined the presence of such consensual immune patterns of self-recognition defined as immunological homunculus [A comparative analysis of all patterns obtained regardless of the subjects' age (range from 1 to 86 years old) allows us to first discuss the significance of observed quantitative changes. The MEI group showed a higher number of antigenic bands detected by plasma IgG compared with the NEC group. This could be due to a higher external antigenic stimulation in MEI with a polyclonal B cell activation induced by parasites acting as mitogens , 30 withparasite . In CM, parasite , 33. In parasite –37 and cparasite , we founparasite . In our munculus –41.A comparative analysis of all patterns, obtained whatever the age of the subjects, allows us to also discuss the significance of observed qualitative changes. Indeed, high interindividual differences in autoreactivity are found among all tested subjects. There is an additional problem linked to the genetic control of such a response, thus, causing a huge variability in terms of population genetics. Nevertheless, in spite of such degree of heterogeneity with regard to the number and the nature of the protein bands recognized, the statistic analysis of such qualitative changes allowed us to clearly differentiate the three groups of tested subjects (MEI with or without CM and NEC) with high sensitivities and specificities. Thus, we defined 8 brain antigens differentially represented in the MEI group compared to the NEC group; and 6 other brain antigens differentially represented inside the MEI group in relation, the age (before 30 years old) and to the clinical status (with or without CM). Such distortion of the global systemic self-IgG-reactive repertoire might be caused by variable events inducing changes in natural or adaptive tolerance. Indeed, humoral innate responses with natural autoantibodies, detected in absence of known immunization , 40, proTo more precisely define the factors involved in the changes, the two MEI subgroups (MEI with or without CM), we considered the parameter of age using an arbitrary distinction of 4 age brackets . Age influences the severity of the infection since it is known that malaria in children living in endemic zones is often severe. They are the first victims of CM because of their unprotected immune status , 44. In Plasmodium falciparum that underlie recurrent infections. Indeed, in malaria-endemic zones, acquired protective immunity  induced by parasitic diversity is strengthened with increasing age [In our work, some specific antigenic bands, presented as a peculiar intragroup self-reactivity pattern, are expressed according to each age group in different proportions in MEI with or without CM. In children aged 1 to 15 years, discriminant antigenic bands were identified . However, they are not good bio-markers for CM, as they were low in frequency within each age group of MEI with CM. In contrast, in MEI subjects aged from 16 to 30 years, significant discriminatory bands were found. Subjects of this group displayed singular self-immune reactivity—characterized by only two discriminatory self-reactive antigenic bands—p94 and p74—when the presence or absence of CM is taken into account. This appears stable in all subjects since they were immunized against almost all prevalent parasitic strains encountered in the area , 53. Whesing age –57. Conssing age , or by rsing age , 15, 59,The present work is focused on the age-related evolution of the self-immune patterns. Therefore, the characterization of the nature and structure of identified antigenic bands of interest (such as p94) will be assessed in future studies requiring mass-spectrometry analysis. Their presence in malaria infection may be of prognostic interest as in other infections where some auto-antibodies reveal a new repertoire that heralds susceptibility to future autoimmune diseases . Self-re


The Malaria Eradication Research Agenda  Consultative Group on Diagnoses and Diagnostics outline a research and development agenda to provide the diagnosis and diagnostic tools required for malaria eradication. Plasmodium parasites is essential, therefore, to guide case management. Improved diagnostic tools are required to enable targeted treatment of infected individuals. In addition, field-ready diagnostic tools for mass screening and surveillance that can detect asymptomatic infections of very low parasite densities are needed to monitor transmission reduction and ensure elimination. Antibody-based tests for infection and novel methods based on biomarkers need further development and validation, as do methods for the detection and treatment of Plasmodium vivax. Current rapid diagnostic tests targeting P. vivax are generally less effective than those targeting Plasmodium falciparum. Moreover, because current drugs for radical cure may cause serious side effects in patients with glucose-6-phosphate dehydrogenase (G6PD) deficiency, more information is needed on the distribution of G6PD-deficiency variants as well as tests to identify at-risk individuals. Finally, in an environment of very low or absent malaria transmission, sustaining interest in elimination and maintaining resources will become increasingly important. Thus, research is required into the context in which malaria diagnostic tests are used, into diagnostics for other febrile diseases, and into the integration of these tests into health systems.Many of malaria's signs and symptoms are indistinguishable from those of other febrile diseases. Detection of the presence of  New and improved screening tools and strategies are required for detection and management of very low-density parasitemia in the fieldImproved quality control is required for rapid diagnostic tests (RDTs) and microscopy in the field, to ensure confidence in diagnosis for case managementPlasmodium vivax for case managementMore sensitive tests are required for P. vivax liver stages are neededField-ready glucose-6-phosphate dehydrogenase (G6PD) deficiency tests and strategies for use to allow safe use of drugs against New strategies to manage parasite-negative individuals are needed to justify the continued inclusion of malaria diagnostics in febrile disease management in very low transmission areas.As malaria transmission declines across much of its range and the possibility of elimination  is increasingly considered Plasmodium in the blood of asymptomatic individuals  who may contribute to continuing malaria transmission However, the very low levels of transmission now being attained in many countries present new challenges that will demand new diagnostic tools and strategies, in particular, a change from passive case detection to “active” case detection. That is, as the elimination agenda is increasingly followed Plasmodium infections can persist at low densities for different lengths of time with no significant symptoms P. vivax and Plasmodium ovale, as a latent stage in the liver that is not directly detectable. The contributions of these unseen reservoirs to the maintenance of transmission will depend on the success of detection and management of new cases and the coverage of vector and other control measures in the area More specifically, to avoid onward transmission, elimination programs for malaria will increasingly need to focus on detecting the highest possible fraction of infections in the general population through active rather than passive case detection. This change of focus will be essential because Countries with successful “sustained control,”  P. falciparum and P. vivax are the most prevalent plasmodia, the following discussion concentrates on these species, which most commonly present as mono-species infections. However, as P. falciparum infections decline, P. ovale may become relatively more prominent in areas where it is endemic, with implications for detection and management similar to those for P. vivax. Similarly, only time will tell whether transmission of Plasmodium malariae, which is transmitted across a broad geographical range, but at low prevalence, can be reduced using the measures applied to P. falciparum, or whether it will require specific strategies and tools. Notably, however, elimination of the zoonotic Plasmodium knowlesi is likely to require unique strategies  in sub-Saharan Africa is lacking, but experience from other areas suggests that resource requirements may be prohibitive and long-term maintenance of very low transmission and prevention of rebound unachievable using conventional management Once malaria is eliminated in a given area, considerable resources will be required to detect reintroduction through surveillance and to maintain capacity for rapid management and investigation of any cases found, as long as the risk factors that support transmission are still in place. Screening of migrant populations, screening of populations around detected cases, and case management tools for screening suspected patients, such as recent travelers or geographical associates of malaria cases may be needed. The tools to achieve these activities must be readily available in an environment where technicians are likely to be unskilled in the use of malaria diagnostic tests, particularly microscopy In settings where there is risk of autochthonous or imported malaria, diagnostics must be capable of rapidly and accurately detecting and quantifying parasitemia in febrile patients, and identifying species. In addition, highly sensitive diagnostic tools are needed for passive case detection and case management at health care facilities (public or private) that report to the national health information or disease surveillance systems. The issues around diagnostics in both case management and surveillance and control settings have a large impact on, and are impacted by, monitoring and evaluation requirements and health systems implementation issues such as the development of improved supply lines and logistics management, reporting of results and commodity consumption, and adherence of health workers and patients to management consistent with diagnostic results. These are all important areas where pooling of knowledge and sometimes operational research is required to maximize the impact of the diagnostic tools discussed below Plasmodium parasites with sufficient rapidity for case management in most settings. It remains the operational gold standard in both control and elimination settings. However, the quality of light microscopy in the field is often inadequate When performed to a high standard, light microscopy is capable of accurately identifying and quantifying Plasmodium parasites and other pathogens. Although these digital techniques have the potential to improve field detection of malaria parasites, field-ready versions are not yet available, and it is not known whether these tools will meet the requirements for use in resource-poor settings.Computer-assisted analysis of Giemsa-stained slides (possibly combined with automated staining), or digitized image transfer  to a reference centre for review by an expert microscopist may enable greater consistency in parasite detection Fluorescent-assisted microscopy (FAM)-based methods—for example, the quantitative buffy coat (QBC) method RDTs based on the detection of specific parasite antigens that use a platform design of lateral immunochromatographic flow (dipsticks or plastic cassettes) have started to change the way malaria is diagnosed in endemic settings. RDTs are increasingly being used at the community level and in control programs for case management and in prevalence surveys. Good RDTs reliably detect parasitemia down to 100–200 parasites/µl, which is comparable to the sensitivity of routine well-performed light microscopy P. falciparum but detectable antigen frequently persists after parasite clearance. The presence of HRP2 deletions in areas of South America also limits the use of these tests Plasmodium lactate dehydrogenase (pLDH) have yielded variable results and, in general, have less potential to detect low parasite densities and greater susceptibility to deterioration under storage at high temperature than HRP2-based tests P. falciparum and P. vivax) and pan Plasmodium species-specific pLDH-based tests are available. Finally, tests targeting pan-specific parasite aldolase have shown inadequate detection thresholds in recent comparative trials, possibly because of the low concentrations of this target antigen in parasites Three parasite antigen types are targeted by currently available RDTs. Histidine-rich protein 2 (HRP2)-detecting tests have high sensitivity and specificity for P. vivax) and address some of the deficiencies of the current RDTs. In particular, current tests for P. vivax, which lack consistency in sensitivity and stability, might benefit from the use of monoclonal antibodies that target new antigens or improved manufacturing standards.The development of RDTs targeting other antigens may improve species identification  genes by PCR assays represent the overall gold standard of malaria diagnostics. When sample concentration methods are used, 0.5 parasite/µl unconcentrated blood or lower can be detected. Quantitative PCR can be used to determine the concentration of circulating DNA and therefore estimate the density of circulating parasites. Survey and testing techniques, including pooling of samples, can reduce costs At present, the application of PCR-based methods is restricted to well-equipped laboratories with specially trained technicians, partly because the need to avoid contamination  requires a very high standard of laboratory practice. PCR capacity is consequently limited in resource-poor malaria-endemic countries, where considerable investment would be required to establish and maintain it. PCR capacity-building programs are underway in several African countries through the Malaria Clinical Trials Alliance (MCTA). However, its restriction to well-equipped laboratories limits the applicability of PCR for surveillance and asymptomatic parasitemia case finding because timely feedback to allow the treatment of identified cases is impossible in most endemic areas. The development and field demonstration of high-throughput field-applicable PCR technologies is therefore needed to allow wider use of PCR in endemic settings.Another molecular detection method based on DNA amplification is loop-attenuated isothermal amplification (LAMP). This method, which amplifies DNA  with a single thermal cycle, has the potential to reduce the training and infrastructure requirements of molecular diagnosis Plasmodium metabolism, can be detected through refraction/absorbance of laser light of certain frequencies, and has been used to detect malaria and to determine species. Current field-ready technologies are based on flow cytometers. Their application is limited to screening, however, because of low sensitivity at low parasite densities Hemozoin, a by-product of Current antigen-detecting RDTs (see earlier for details) are likely to miss a significant proportion of asymptomatic cases in low-transmission settings P. falciparum infections in which the blood-stage parasite density has fallen below the limits of light microscopy or antigen-detecting RDTs P. vivax hypnozoites (evidence of infection) Antibody detection see also  is curreBecause antibody-detecting tests can identify parasite-infected individuals who are undetectable by antigen detection or light microscopy because of low parasite density, they could be used to screen populations such as migrants or blood donors to identify asymptomatic individuals at risk of transmitting malaria. They could also be used for identifying foci of recent transmission in areas that are otherwise malaria free and to determine the presence or absence of recent malaria transmission in specific populations, such as young children. They therefore have potential applications in confirming areas free of transmission during a defined period, provided they are further refined and developed in terms of sensitivity and specificity.P. vivax detection and management will become increasingly important as control measures reduce P. falciparum transmission. In many programs, P. vivax already causes the majority of clinical malaria episodes. Because P. vivax can remain latent in the liver but produces relapse, its effective management normally requires the use of 8-aminoquinolones to clear hypnozoites from the liver. No current diagnostic technique is capable of detecting P. vivax hypnozoites, and none are in development, although tests that can detect the presence of hypnozoites are a key research and development need wherever and whenever elimination has a chance of becoming a realistic goal. While symptomatic cases of P. vivax can be assumed to harbor liver stages and managed accordingly, a method for detecting hypnozoites would enable populations in P. vivax-endemic areas to be screened during the nontransmission season for asymptomatic individuals likely to have relapses who could then be treated before they become symptomatic and transmit in the following transmission season. Screening could therefore reduce the use of 8-aminoquinolones in mass-treatment programs in P. vivax-endemic areas, which would reduce the probability of drug-related severe side effects in glucose-6-phosphate dehydrogenase (G6PD)-deficient individuals (see next section). At present, compliance issues with the long course of primaquine  have limited the broad application of this approach, and therefore the need for a diagnostic test for hypnozoites Potential biomarkers to detect hypnozoites include direct markers of metabolic activity, released antigens, markers of host immune response, and indirect serological markers of other stages . A lack of known markers of hypnozoite metabolic activity and markers of immunity limits the potential to assess the likely gains from investment in this area, and more knowledge of the biology of hypnozoites, perhaps through the development of liver-stage cultures, is required to determine whether such tests can be developed P. vivax infection is primaquine, and the only investigational drug showing promise is tafenoquine, Both these 8-aminoquinolones cause hemolysis in G6PD-deficient individuals, the clinical importance of which varies with the particular G6PD-deficiency phenotype, and the starting hemoglobin concentration, and may depend on how the drugs are administered The only drug currently licensed for the radical cure of P. vivax reservoirs will probably involve the use of a hypnozoiticidal drug P. vivax. The requirements for such a test differ somewhat from those of parasite-detecting RDTs, because testing should only be required once in a lifetime and is not urgently required; the use of hypnozoiticidal drugs can be delayed if necessary. So, for example, a G6PD test does not have the stability requirements of an antigen-detecting RDT. Current tests for G6PD deficiency nevertheless have limitations regarding storage requirements and the complexity of the procedure, so research is needed to develop new tests. Importantly, addressing G6PD deficiency will also involve research into test implementation—how should samples be tested, where should tests be done, and how should results be recorded to facilitate retrieval? Moreover, to decide whether further development of field-applicable G6PD tests is needed also requires more data on the distribution of G6PD phenotypes and on the efficacy and safety of alternatives to the standard hypnozoiticidal primaquine regimen.Because eliminating Current RDTs detect antigen in peripheral blood samples obtained by finger prick. This method is generally acceptable for case management in the formal health care sector, but it presents some logistical challenges at the community level and in some private sector settings, particularly with regard to the potential risks of blood-borne infection. In addition, invasive tests may not be fully accepted in some settings, particularly when taking samples from asymptomatic individuals, which could diminish access to malaria diagnosis, treatment, and surveillance. Noninvasive sampling  has the potential to overcome these impediments but, at present, the limitations of sensitivity of nonblood sampling are even greater than the limitations of blood sampling combined with antigen-detecting RDTs for screening and surveillance Multiple diagnoses from one assay or “multiplexing” is made possible by, for example, the inclusion of multiple PCR-based nucleic acid probes in a single test or the inclusion of antibodies specific for nonmalarial diseases or of pathological markers of disease severity. The inclusion of antibodies targeting nonmalarial diseases in RDTs in their common format  increases the technical challenge of achieving the stability needed for sufficient shelf life and makes interpretation of results more complex. The usefulness of such tests is also limited by the ability of the health system to provide appropriate management for each etiological agent that may be identified, and the highly variable prevalence of potential target differential diagnoses within malaria-endemic areas.However, as malaria rates drop through successful control programs, the overall fever rate may not change significantly. Accordingly, it will be increasingly important to integrate management of malaria with that of other febrile diseases, at the point of diagnosis, if the program is to remain credible and sustainable see also . NonmalaResearch and development needs for multiplexing include the development of field-ready multiplex tests for malaria and nonmalarial diseases, which are not currently widely available, and research into the inclusion of markers for inflammation or severe disease in malaria tests, which would offer the potential to guide the referral of patients who require urgent management see also . FinallyP. falciparum. The resource needs to achieve genotyping are massive, and the long feedback time for results is likely to reduce the exercise to one of academic interest only. Genotyping could be useful for P. vivax infections to determine whether a blood-stage infection is new or a relapse. However, it has not yet been possible to develop methods that will reliably distinguish between relapse, recrudescence, and reinfection because of the multiplicity of hypnozoite genotypes present in P. vivax-infected individuals. Genotyping might, however, be useful in suspected outbreak or in new foci of transmission to determine the source of parasites, particularly when elimination in an area is being confirmed Three other potential research priorities were discussed by the Consultative Group, but the consensus was that research into pooling samples, gametocyte detection, and genotyping was less urgent. Thus, although the idea of pooling individual samples to detect parasitemia in very low transmission settings is intrinsically appealing and could result in cost savings using currently available tests, the Consultative Group felt that the limited quantity of antigen or DNA in pooled samples would severely limit the sensitivity of this approach. Similarly, the group decided that the development of a detection test for gametocytes should not be viewed as a high priority requirement. Finally, although WHO guidelines recommend genotyping of parasites during elimination phases The central importance of active case detection in each programmatic stage towards elimination has been comprehensively dealt with by several of the other malERA Consultative Groups Importantly, when malaria is rare and no longer perceived by local health services and the community to be of significant public health concern, ways must be found to maintain the resources needed to test febrile cases for parasitemia to prevent resurgence of infection. Because malaria parasite detection will be competing for resources with other disease priorities with higher mortality, it will be necessary to target diagnostics to those cases more likely to be malaria rather than necessarily screening whole populations  parasite density likely to cause symptoms in low-transmission settings with variable or waning immunity, and (ii) transmission potential of cases with parasitemia below the threshold of microscopy and RDTsDiagnostic tests for nonmalarial febrile illness in malaria-endemic and malaria-elimination settingsDistribution of severe G6PD variantsHigh priorityStable tests for case management in low-training, low-technology settings with sensitivity sufficient for community-level case management, including:Antigen-detecting RDTsP. falciparum detection, particularly in the case of nonpersistent antigensGreater consistency in -P. falciparum parasitesMore sensitive and stable tests to detect nonClarification of the programmatic/implementation requirements that will ensure good impact in the fieldStandardized low-cost positive controls for antigen-detecting RDTs suitable for field useSustainable tools for quality control of RDTs at a country level.Further investigation of nonblood sampling to determine the potential for detecting recoverable antigen in these samples.More consistent, reliable staining methods for microscopyG6PD deficiency mapping and identification (if 8-amino-quinolones are to be used)Medium priorityMultiplexing: Other diseases, markers of severityP. vivax relapse preventionField G6PD detection (may be more important if tafenoquine approved), or raised priorities for Tools to standardize and improve microscopy interpretationLow priorityHypnozoite detection .High priorityField-applicable tools for detection of low-density parasitemia in a high-throughput manner, suitable for surveys and active detection of parasite carriage in time to allow management of positive casesTools for minimally invasive, very rapid detection of low-density parasite infections suitable for screening of migrants/travelersInnovation with potential for major operational impactNoninvasive, low-density parasite detectionHigh-throughput field molecular detection, capable of use at district level or belowPositive control methods for RDTsBecause malaria generally occurs in low-resource settings, the profits likely to be made from malaria diagnostic development and manufacture, particularly in the face of low mortality, are limited. The current market place for malaria rapid tests is dominated by small to medium-sized manufacturers, who are unlikely to be able to make the major investments needed to address these priorities alone. Thus, the role of donor agencies and product development partnerships and research institutions in enabling research and development and in providing the expertise and field access necessary to shape products to meet program needs will be an essential element of diagnostics development. Critically strong and focused, mainly public-private, partnerships will need to built and nurtured.


Malaria transmission is spatially heterogeneous. This reduces the efficacy of control strategies, but focusing control strategies on clusters or ‘hotspots’ of transmission may be highly effective. Among 1500 homesteads in coastal Kenya we calculated (a) the fraction of febrile children with positive malaria smears per homestead, and (b) the mean age of children with malaria per homestead. These two measures were inversely correlated, indicating that children in homesteads at higher transmission acquire immunity more rapidly. This inverse correlation increased gradually with increasing spatial scale of analysis, and hotspots of febrile malaria were identified at every scale. We found hotspots within hotspots, down to the level of an individual homestead. Febrile malaria hotspots were temporally unstable, but 4 km radius hotspots could be targeted for 1 month following 1 month periods of surveillance.DOI:http://dx.doi.org/10.7554/eLife.02130.001 Malaria remains a formidable threat to public health in tropical regions. The parasite that causes the disease is transmitted to humans by bites from infected mosquitoes, and the complicated lifecycle of the parasite makes developing vaccines difficult. However, preventive strategies are effective at reducing the spread of malaria. The two most widely used and effective strategies are the use of pesticide-treated bed nets to create a barrier between sleeping families and biting mosquitoes, and indoor residual spraying to reduce the numbers of mosquitoes biting sleeping families in homesteads. Other potential preventive strategies include killing mosquito larvae in breeding sites and mass anti-malarial drug treatment for infected humans.Targeting preventive efforts to malaria hotspots—the areas where the risk of malaria transmission is greatest—may help to eliminate malaria more efficiently. Unfortunately, identifying hotspots is complicated as there are many different factors that affect how malaria spreads. These factors range from ecological conditions such as rainfall and soil type, to human effects like population density and migration.Bejon et al. have examined the patterns of malaria transmission in Kenya over 9 years. Over this period, 54% of children who went to health clinics with a fever tested positive for the parasite that causes malaria. Infected children from areas with the highest rate of malaria infection were, on average, younger than those from less infected regions. This makes sense as in highly affected areas children have a greater chance of encountering the parasite at an early age. They are therefore more likely to get malaria when younger and, as exposure to the parasite can provide some immunity to a child, they are also less likely to get infected again when older.In addition, mapping the spread of malaria reveals hotspots at different geographical scales. Bejon et al. could see hotspots within hotspots, and in some cases could go as far as identifying the individual homesteads most at risk of malaria. Public health workers could potentially use these analyses to identify areas that are likely to be hotspots and then target preventive measures there for the next month. However, the constantly changing locations of the hotspots means workers would have to reanalyse the data and retarget their interventions at the end of each month.DOI:http://dx.doi.org/10.7554/eLife.02130.002 The transmission of infectious disease often shows substantial heterogeneity . MalariaWe have previously identified hotspots of malaria using active surveillance . Others We present data from demographic surveillance linked to passive case detection in Pingilikani dispensary in Kilifi District, coastal Kenya. Data are collected from 1500 homesteads within an 8 km radius followed for 9 years. We analyse the spatial heterogeneity of malaria cases in order to determine the temporal and spatial scales of case clustering so as to inform targeting in malaria control programmes. We also excluded visits with specific symptoms such as skin infections or cutaneous abscesses, otitis media, and gastroenteritis (>4 episodes diarrhoea per day) that might have been the primary motivation for seeking health care rather than fever per se.Plasmodium falciparum on blood smear examination. Using homestead as our unit of analysis, we found that the incidence of dispensary attendance declined with distance from the dispensary (on average −0.040 (95%CI 0.036–0.044) and −0.041 (95%CI 0.037–0.046) episodes per child year for each km for malaria smear positive and negative attendees, respectively). MPF was not found to vary significantly by distance of residence from the dispensary .Among ∼20,000 remaining febrile presentations from ∼1500 different residences, 54% were positive for The spatio-temporal distribution of MPF by homestead is shown in s) = −0.16, p<0.0001 . We examined the effect of spatial scale at which this correlation occurred by imposing grids of increasing cell size on the study area, calculating rs within each cell of the grid, and then estimating the mean rs at each scale of grid  would measure transmission intensity without the offsetting of acquired immunity, and that unstable transmission would result in higher risk of malaria in older children. To test this hypothesis, we calculated the mean MPF<1yr and the variance in MPF<1yr for each homestead over the 9 years of follow up and tested the relationships between these metrics and risk of malaria in older children in multivariable linear regression models.We also examined temporal trends for individual homesteads . There w<1yr was strongly correlated with MPFs in children in the 1- to 2-year-old and 2- to 3-year-old age group, but progressively less strongly correlated with MPF in older children  or with the variance in MPF<1yr . Hence, ITNs provided personal protection from malaria, but we were unable to show that they explained the spatial micro-epidemiological patterns.Mass distributions of Insecticide Treated Nets (ITNs) in the area began in 2006. ITN use was surveyed in 2009 and 2010. We found that children using ITNs had a reduced risk of malaria by logistic regression , in keeping with previous literature on the personal protection provided by ITN use . On the We found that malaria cases were spatially heterogeneous in an 8-km radius area of coastal Kenya. The strongly significant inverse correlation between the malaria positive fraction (MPF) and average age of children presenting with malaria suggests variable acquisition of immunity between homesteads. Homesteads at high transmission intensity have a high MPF and a young average age of malaria (with older children becoming immune and therefore not presenting to the dispensary) whereas homesteads at low transmission intensity have a low MPF but an older average age of malaria since older children are not becoming immune as rapidly. In theory, this inverse correlation might have arisen because of heterogeneity at various spatial scales. For instance, there might have been a block of homesteads all at high transmission in one half of the study area (thus with high MPF and low average age) and a second block of homesteads at low transmission in the other half (with low MPF and high average age). On the other hand, the inverse correlation might have arisen because of a random distribution of ‘high’ and ‘low’ transmission intensity homesteads throughout the study area.To determine at which spatial scale transmission was heterogeneous, we conducted an analysis where correlation coefficient was recalculated within each cell of a grid superimposed on the study area. The mean correlation coefficient of all cells was then presented as the cell size of the grid used was increased . This anThe pattern of spatial heterogeneity is relevant to malaria control, since targeted disease control is predicted to be highly effective . SpatialWe therefore simulated the accuracy with which hotspots could be targeted using varying spatial scales and varying time periods of surveillance. We found that using data aggregated over 1 month of surveillance to define 4 to 8 km diameter hotspots would provide greatest accuracy, but this information is only relevant for 1 month before temporal instability necessitates further surveillance. One might therefore consider a continuous programme of parallel surveillance and targeting, where the surveillance data are examined at the end of each month to determine the location to be targeted for the following month. Continuous surveillance would allow adaptive targeting of hotspots for the following month. Such a strategy might be employed all year round, or for a limited period of the year depending on local seasonality.  TargetinThere are some caveats to this recommendation. Our observations are from a single site. Other sites should examine their local data to determine whether a similar targeting strategy is appropriate. Furthermore, some hotspots did show temporal stability. For instance, we identified a 6 km diameter hotspot south east of the dispensary that maintained a 30–60% increase in MPF compared with the surrounding area throughout the 9-year surveillance.Children with positive microscopy slides for malaria presenting at the dispensary may have genuine febrile malaria, or alternatively may have chronic asymptomatic parasitaemia with co-incident non-malarial fever. Previous studies estimating malaria attributable fractions in the locality suggest 61% of the children in our analysis would have malaria as the proximate cause of their illness, with the other 39% having chronic asymptomatic parasitaemia with co-incident fever from another cause . We haveFurthermore MPF is not a comprehensive indicator of transmission intensity. Homesteads with consistently low average ages of febrile malaria are likely to be stable high transmission homesteads , and 21.7 infective bites per person per year in 2010 (2). Between 2003 and 2011, data were collected on all children  attending the dispensary.Demographic surveillance is conducted for the 240,000 people in a 900 square kilometre area in Kilifi County. Four-monthly enumeration rounds were conducted to identify births, deaths, and migration (3). Each inhabitant is described by their family relationships and their homestead of residence, with geospatial coordinates, and assigned a unique personal identifier. These details were used to link children visiting Pingilikani dispensary to geospatial coordinates for the homestead of residence. During enumeration rounds in 2009–2011 ITN use per individual was established during visits to the homestead, as reported by a homestead representative.We restrict analysis to within an 8 km radius of the dispensary, which accounted for >96% of all visits to the dispensary and excluded visits with specific symptoms such as skin infections or cutaneous abscesses, otitis media, and gastroenteritis (>4 episodes diarrhoea per day) that might have been the primary motivation for seeking health care rather than fever per se. These latter exclusions combined accounted for 14% of all visits.Plasmodium falciparum parasites. 100 fields were examined before slides could be considered negative. Amodiaquine was the first-line anti-malarial from 2003 to 2005, when policy changed to Co-artemether.All children presenting for assessment (except those with trauma as their only concern) had finger-prick blood samples examined for malaria parasites. Thick and thin blood smears were stained with 10% Giemsa and examined at x1000 magnification for asexual Fever was defined as either reported fever by the parents or measured fever, that is, axilliary temperature ≥37.5°C . The mals seen in the real data. In the second round of simulations, we varied the Signal:Noise Ratio as shown in individual panels, and in the third round of simulations we introduced a gradient over which the correlation emerged, where the factor applied to MPF and average age was tapered in a uniform way towards 1 beginning at the edge of the simulated block.The average age of febrile malaria was calculated as the arithmetic mean age at which children visited the dispensary with fever and malaria parasites. Correlations between average age of febrile malaria and MPF per homestead were calculated using spearman's rank correlation coefficient. Grids of gradually increasing cell size were calculated using longitude and latitude coordinates. Simulations were done using the distribution of homesteads identified in our study. We applied a factor to MPF (positive) and average age (negative) to the homesteads within a block of varying size to induce the appearance of clustering at a given spatial scale. Random noise was added to these simulations using a gamma distribution. In the first round of simulations we set the Signal:Noise ratio  to reproduce the rwww.satscan.org. The version used in this analysis was downloaded in November 2012, as v9.1 for a 64-bit system. The spatial scan statistic uses a scanning window that moves across space. The scanning windows are circles centred on each homestead, with a radius varied from inclusion of only the single homestead it is centred on through to 30% of the population size. When using the Bernoulli model, the software calculates the fraction of cases/controls inside vs outside the each possible scanning window, and selects the window giving the highest probability of a case within the scanning window compared with the probability of a case outside the window. In our application of the Bernoulli model, cases were febrile children with parasitaemia and controls were febrile children without parasitaemia. The test of significance needs to take into account the whole process of selecting the optimal window rather than simply the comparison of inside vs outside the optimal window. This is achieved by running random permutations of the case/control data over the spatial co-ordinates of homesteads and determining the log-likelihood statistic for the model fit by the optimal window for each random permutation. The log-likelihood statistic for the real data is then compared with the statistics on the random permutations to derive a p value. We used 9999 replications in our study. The maximum hotspot size was set at 30% of the population, and the inference level for significance was set at 0.05. The main analysis was done without adjustment for covariates, and a secondary analysis was conducted for the 2009/2010 data with and without ITN use as a covariate. Kernel smoothing with a 1 km radius is used for spatial display graphs, but all analyses of correlation are conducted on raw data without smoothing.Hotspots were defined using SaTScan software to calculate the spatial scan statistic . The sofSemivariograms, Moran's I and linear regression models were run in Stata version 12 . Semivariograms were constructed using 0.1 km intervals between 0.1 km and 10 km. Moran's I was assessed globally using cumulative bands of <0.1, <0.5, <1 and <2 and <5 kms. review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent  The claim on the self-similarity of the patterns and the lack of a characteristic scale needs to be substantiated further for the analyses to be convincing. In particular, it is not clear that the results of the correlation analyses at different spatial resolutions could not arise from the combination of a characteristic scale and the increasing noise from fewer data as the resolution increases. The randomization test addresses the fewer homesteads for a random pattern but not for one with a characteristic scale. It would be valuable to impose a pattern with such a scale on the distribution of homesteads in the landscape and show that this does indeed create a 'shoulder'. Additional motivation and description of the methods is needed: how were the grids constructed? Why would randomly reassigning spatial co-ordinates to homesteads lead to a correlation that declines very rapidly with grid sizes, rather than remaining constant? The choice of analysis to demonstrate hotspots at every scale is unusual in the sense of involving a correlation between two quantities and how this changes with resolution. It is important that the expectations of different kinds of patterns be clear and that the significance of the observed pattern be established.2) The title and Introduction emphasize the 'fractal' nature of the patterns. This term implies self-similarity in a stronger sense than the lack of an identifiable characteristic scale over some range of resolutions. In this sense, the calculation of a fractal dimension is important but has been relegated here to the Discussion with no actual evidence presented to demonstrate the dimension and the range of scales over which this number was obtained. This plot and the strength of the evidence for a fractal pattern need to be included.3) The authors need to say where they obtained the SaTScan software, what version (or when downloaded). They also need a more detailed overview of how this method finds hot spots.4) The possibility of conflation with mean age of infection should be considered. Mean age of infection results from the interaction between infection risk, reporting risk, and the mean age of children present. Age of children present could be an important confounder of the studied relationship: areas with younger children might have higher malaria rates and lower mean age of infection even if there is no signal from the direct causal relationship between them. Ideally, the authors would construct a statistic that measures age in the malarious population relative to the control population at each spatial scale. This issue must at least be carefully discussed.5) The discussion of ITN use is not entirely convincing. Is there a way to include ITN use in the analysis, and thus really control for it? How much may the use of impregnated bednets be spatially or temporally heterogeneous? The correlation with variance in MPF seems like a red herring, and should be dropped.6) It would be helpful to readers to know if, within the approximately 16 km diameter of the reported area, there are any obvious geographical differences – e.g., of altitude or ground water/foliage, that might affect malaria transmission. In the Discussion the authors state that 'Accurate characterization of these patterns will inform optimized surveillance and control policies'. Is it possible that such characterization within the study area would have produced results comparable with (and more easily obtained) than the data utilized from clinic records?7) The investigators have data on the parasitaemia prevalence among children presenting without fever (and without trauma). The suggestion here is not that the authors repeat their analysis using parasitaemia prevalence in the non-febrile but that they discuss whether similar results might have been obtained. Alternatively, were parasite densities measured on blood films, so that the likelihood that a fever is actually due to malaria could be estimated?8) The practical implications could be written more clearly. The principal suggestion is that “the use of one month cycles of surveillance to target 4 to 8 km diameter hotspots would be optimal” – some expansion on what is meant by “cycles” and “surveillance” - is it recommended that parasitaemia prevalences among febrile children should be the instrument of surveillance? And how frequently should the one-month surveys be carried out?9) The authors need to be more careful throughout about “negative inference”. The null hypothesis is rarely true, and never confirmed. For example: the wording at the end of the second paragraph of the Introduction is far too strong – the authors should argue that this bias is likely to be small, not that it is unlikely to exist; similarly the “cannot be used” result is presumably a lack of statistical significance and does not imply there is no difference in subjective fever experience ; in the first paragraph of the Results, the authors should say MPF “was not found” to vary ; in the Results section “ITN use and spatial variation in risk”, the distribution was not “random” – the authors found no significant pattern, similarly they did not find a significant correlation with variance. The authors should be aware of this point when addressing the issue of non-malarial fevers, as well. 1) The claim on the self-similarity of the patterns and the lack of a characteristic scale needs to be substantiated further for the analyses to be convincing. In particular, it is not clear that the results of the correlation analyses at different spatial resolutions could not arise from the combination of a characteristic scale and the increasing noise from fewer data as the resolution increases. The randomization test addresses the fewer homesteads for a random pattern but not for one with a characteristic scale. It would be valuable to impose a pattern with such a scale on the distribution of homesteads in the landscape and show that this does indeed create a 'shoulder'. Additional motivation and description of the methods is needed: how werethe grids constructed?s) similar to that observed in our real data. We then analysed these simulated datasets in the same way as we had analysed our real data .We have done such simulations, using a variety of characteristic scales and signal:noise ratios, which are added to our revised manuscript as Supplementary Figures 1 and 2. We conducted these simulations by using the distributions of homesteads observed in the study area, and simulating an increase in malaria positive fraction (MPF) and decrease in age of children with febrile malaria with particular characteristic scale, and additional simulating a degree of random noise using a gamma distribution. We scaled the Signal:Noise ratio in each case to provide a Spearman’s rank correlation coefficient  becomes more difficult to discern as the Signal:Noise ratio falls. However, spikes in rs on varying the cell size of the grid can still be noted up until the point at which the Signal:Noise ratio completely obscures any correlation.We then investigated whether the ratio of signal to noise in the presence of a pattern at a characteristic scale might produce plots similar to those we observed in the real data. The results are shown in Furthermore, we investigated the effect of adding a gradient at the edge of the block of characteristic scale over which the clustering emerges (as a proportion of the block size). The results are shown in However, we recognise that simulations of noise and gradients are necessarily artificial and real-world data are likely to contain many other more complex sources of variation. We may expect less distinct peaks in such circumstances. Nevertheless these simulations all show marked discontinuities in the correlation between age of malaria and MPF over varying cell size of a superimposed grid. We suggest that a gradual emerging of the correlation between MPF and average age of malaria is not readily explained by clustering at a single spatial scale even in the presence of random variation or gradients.Taking these findings together with the findings of a) hotspots at multiple spatial scales and b) the findings from the semi-variogram and log-log plot used to calculate a fractal dimension (see response below), we conclude that our findings are indeed the result of spatial clustering of transmission varying consistently at every scale examined.We have therefore edited the text throughout to read “spikes” instead of “shoulders” and added text to the Results, Discussion, and Methods.Why would randomly reassigning spatial co-ordinates to homesteads lead to a correlation that declines very rapidly with grid sizes, ratherthan remaining constant?s below a cell size of 0.5 km, but this is at a point where the confidence intervals of our estimate are quite wide (as a result of having few data points in each cell). It is the correlation in the observed data (shown in blue) that declines rapidly with reducing cell size.Our reading of The choice of analysis to demonstrate hotspots at every scale is unusual in the sense of involving a correlation between two quantities and how this changes with resolution. It is important that the expectations of different kinds of patterns be clear and that the significance of the observed pattern be established.The results from simulations described above demonstrate the expectations with different kinds of pattern, and support the conclusion that that an inverse correlation between age and malaria positive fraction was present at every geographical scale examined within our study. This led us to predict that hotspots will occur at every scale, a conclusion that we empirically tested and confirmed as shown in Figure 2–figure supplement 1(see point 2 below), suggests spatial clustering of febrile malaria cases at every spatial scale examined. Hence our conclusion of spatial clustering at every scale does not depend only on the inverse correlation between age and MPF, but on two further analyses  The title and Introduction emphasize the 'fractal' nature of the patterns. This term implies self-similarity in a stronger sense than the lack of an identifiable characteristic scale over some range of resolutions. In this sense, the calculation of a fractal dimension is important but has been relegated here to the Discussion with no actual evidence presented to demonstrate the dimension and the range of scales over which this number was obtained. This plot and the strength of the evidence for a fractal pattern need to be included.We have added the semivariogram plot and log-log semivariogram plot used to calculate the fractal dimension is shown in 3) The authors need to say where they obtained the SaTScan software, what version (or when downloaded). They also need a more detailed overview of how this method finds hot spots.SaTScan software is free to download from the SaTScan website. Further details have been added to the relevant paragraph in the Methods section.4) The possibility of conflation with mean age of infection should be considered. Mean age of infection results from the interaction between infection risk, reporting risk, and the mean age of children present. Age of children present could be an important confounder of the studied relationship: areas with younger children might have higher malaria rates and lower mean age of infection even if there is no signal from the direct causal relationship between them. Ideally, the authors would construct a statistic that measures age in the malarious population relative to the control population at each spatial scale. This issue must at least be carefully discussed.s=-0.02, p=0.4). We normalized age of febrile malaria for age of children with non-malarial fever by calculating the absolute difference between the two and found that there was still a negative correlation with MPF . However, the correlation is not as strong as that seen without normalization (rs) =-0.16, p<0.0001), partly because the normalization requires data in each homestead to calculate average age for children with and without malaria and therefore observations are dropped , and partly because normalizing according to the average age of non-malarial fever likely adds noise to the statistic. We therefore include the former results in the manuscript as reassurance that the studied relationship between MPF and average age of febrile malaria is unlikely to be confounded by spatial variation in average age of children in the community, but prefer to retain the use of average age of febrile malaria as our metric for the more detailed analysis according to spatial scale presented in the main body of the paper. We have added text to the Results section accordingly.The average age of children with non-malarial fever did not show any spatial clustering  and was not associated with MPF (r5) The discussion of ITN use is not entirely convincing. Is there a way to include ITN use in the analysis, and thus reallycontrol for it?ITN use can indeed be included as a covariate in the SaTScan analysis. Using the data from 2009 and 2010, we re-ran the hotspot analysis using SaTScan with and without the inclusion of ITN use as a covariate. The addition of ITN use as a covariate changed the location of the hotspot by 120m, and changed the predicted radius of the hotspot from 5.4 to 5.2km. On re-analysis of the homesteads within the 5.4km hotspot, a further 0.87km hotspot was identified the position and radius of which were not altered by the inclusion of ITN use as a covariate. Finally, within this 0.87km hotspot the same 7 homesteads were identified as a hotspot irrespective of the inclusion of ITN use as a covariate.How much may the useof impregnated bednets be spatially or temporally heterogeneous?ITN use showed a random spatial distribution . The Spearman’s rank correlation for proportion of homesteads using an ITN between these two years was 0.35 (p<0.0001) indicating that homestead use varied between years. Hence ITN use did not show an auto-correlation indicating non-random spatial heterogeneity, but was temporally heterogeneous. ITNs provided personal protection , but adjusting for them did not appear to alter the location of hotspots (as described above).The correlation with variance in MPF seems like a red herring, and should be dropped.Indeed it was not our intention to imply that the correlation with variance in MPF was significant, and we have revised our wording to clarify this, and provide some context to our findings on personal protection of ITNs with regard to previous literature. Taking the three points above together, we have revised the paragraph on ITN use in the Results section.6) It would be helpful to readers to know if, within the approximately 16 km diameter of the reported area, there are any obvious geographical differences – e.g., of altitude or ground water/foliage, that might affect malaria transmission. In the Discussion the authors state that 'Accurate characterization of these patterns will inform optimized surveillance and control policies'. Is it possible that such characterization within the study area would have produced results comparablewith (and more easily obtained) than the data utilized from clinic records?There is only modest variation in altitude within the study area, from 30 to 180 metres above sea level (IQR 49-99 metres). Nevertheless, regarding the general point raised there is a previous literature that we now reference. Malaria transmission has been shown to vary by geographical features such as altitude , cultivation practices , streams and dams . Ecological models have been developed using frequentist techniques , Bayesian approaches  and fuzzy logic . However, the same ecological factor may act inconsistently in different geographical areas . Hence although there is obvious scope for analysis of our data in relation to geographical features, we believe this would be an appropriate topic for a further publication rather than an additional analysis to include here. On the other hand, there are some general points that we add to the discussion in response.We identify a fractal pattern with clustering at multiple geographical scales. It therefore follows that in order to develop a model based on geographical features one would either need to identify a key feature that can be mapped on multiple geographical scales, or a combination of geographical features that can exist across multiple scales. For instance, we note a river in the Eastern part of the study area running North to South, and the main hotspot is associated with this river . However7) The investigators have data on the parasitaemia prevalence among children presenting without fever (and without trauma). The suggestion here is not that the authors repeat their analysis using parasitaemia prevalence in the non-febrile but that they discuss whether similar results might have been obtained. Alternatively, were parasite densities measured on blood films, so that the likelihood that a fever isactually due to malaria could be estimated?An analysis of asymptomatic parasitaemia would likely yield different results from an analysis of febrile parasitaemia, as we demonstrated in a previous study  The practical implications could be written more clearly. The principal suggestion is that “the use of one month cycles of surveillance to target 4 to 8 km diameter hotspots would be optimal” – some expansion on what is meant by “cycles” and “surveillance” - is it recommended that parasitaemia prevalences among febrile children should be the instrument of surveillance? And how frequently should the one-month surveysbe carried out?We have re-written this section for clarity. We did indeed intend that monitoring parasitaemia among febrile children would be the instrument of surveillance. We intended that this would be done in cycles, with one month of monitoring, followed by one month of targeted intervention . These could in theory be undertaken throughout the year, or to conserve resources could be undertaken during the rainy season. We have revised the Discussion accordingly.9) The authors need to be more careful throughout about “negative inference”. The null hypothesis is rarely true, and never confirmed. For example: the wording at the end of the second paragraph of the Introduction is far too strong – the authors should argue that this bias is likely to be small, not that it is unlikely to exist; similarly the “cannot be used” result is presumably a lack of statistical significance and does not imply there is no difference in subjective fever experience ; in the first paragraph of the Results, the authors should say MPF “was not found” to vary ; in the Results section “ITN use and spatial variation in risk”, the distribution was not “random” – the authors found no significant pattern, similarly they did not find a significant correlation with variance. The authors should be aware of this point when addressing the issue of non-malarial fevers, as well.We accept this point and the necessary edits have been made throughout.


An effective malaria vaccine, deployed in conjunction with other malaria interventions, is likely to substantially reduce the malaria burden. Efficacy against severe malaria will be a key driver for decisions on implementation. An initial study of an RTS, S vaccine candidate showed promising efficacy against severe malaria in children in Mozambique. Further evidence of its protective efficacy will be gained in a pivotal, multi-centre, phase III study. This paper describes the case definitions of severe malaria used in this study and the programme for standardized assessment of severe malaria according to the case definition.Case definitions of severe malaria were developed from a literature review and a consensus meeting of expert consultants and the RTS, S Clinical Trial Partnership Committee, in collaboration with the World Health Organization and the Malaria Clinical Trials Alliance. The same groups, with input from an Independent Data Monitoring Committee, developed and implemented a programme for standardized data collection.Plasmodium falciparum parasite density threshold is introduced, in order to maximize the specificity of the case definition. Secondary case definitions allow inclusion of co-morbidities and/or allow for the presence of parasitaemia at any density. The programmatic implementation of standardized case assessment included a clinical algorithm for evaluating seriously sick children, improvements to care delivery and a robust training and evaluation programme for clinicians.The case definitions developed reflect the typical presentations of severe malaria in African hospitals. Markers of disease severity were chosen on the basis of their association with poor outcome, occurrence in a significant proportion of cases and on an ability to standardize their measurement across research centres. For the primary case definition, one or more clinical and/or laboratory markers of disease severity have to be present, four major co-morbidities  are excluded, and a The case definition developed for the pivotal phase III RTS, S vaccine study is consistent with WHO recommendations, is locally applicable and appropriately balances sensitivity and specificity in the diagnosis of severe malaria. Processes set up to standardize severe malaria data collection will allow robust assessment of the efficacy of the RTS, S vaccine against severe malaria, strengthen local capacity and benefit patient care for subjects in the trial.NCT00866619Clinicaltrials.gov  Malaria remains a considerable burden despite progress in implementation of malaria control policies. It is estimated that malaria causes 709,000 deaths every year in Africa; 85% in children less than five years of age . Used inPlasmodium falciparum circumsporozoite surface antigen. This vaccine is formulated with new proprietary Adjuvant Systems - AS01 or AS02 [P. falciparum, and in areas of stable endemicity is mainly a disease of children under five years of age [The malaria vaccine at the most advanced stage of development is RTS, S, a pre-erythrocytic vaccine candidate containing  or AS02 ,4 and RT or AS02 . In addi or AS02 . Severe s of age .Efficacy against severe malaria is a key factor that will determine evidence-based decisions on the implementation of new malaria control tools ,8. EvidePrevious multi-centre studies on severe malaria have demonstrated that standardized assessment of cases is challenging . SuccessThe current, internationally accepted definition of severe malaria in children is based on the need for prompt treatment of children with a medical history and clinical presentation compatible with severe malaria, given the high complication and fatality rate of this condition ,14. In cThe results of phase II studies led to a decision to employ the RTS, S/AS01 vaccine formulation for the pivotal phase III trial. The objectives and design of the phase III RTS, S/AS01 study are described in a companion paper . This paThe case definitions of severe malaria were developed prospectively through a literature review and consensus meeting of the Clinical Trial Partnership Committee (CTPC) severe malaria working group and expert consultants, in collaboration with representatives of the WHO and the Malaria Clinical Trials Alliance (MCTA). The CTPC includes representatives of all the research centres collaborating on the RTS, S clinical development programme, GlaxoSmithKline and the Malaria Vaccine Initiative.The main objective of this discussion was the development of a primary case definition which balanced sensitivity and specificity, reflecting true paediatric malaria cases at risk of an adverse outcome, usually needing hospital admission, taking into account the fact that symptoms often overlap with other diseases, and that other co-morbidities can be present.A retrospective study of 1,361 children admitted to a Kenyan District hospital and 4,583 community controls showed how the specificity of a case definition for severe malaria varied depending upon the intensity of transmission, the parasite density threshold applied, the markers of severity that were included and upon how co-morbidities were dealt with during analysis. Among children under two years old who presented with symptoms compatible with severe malaria, logistic regression models showed that the malaria-attributable fraction of these cases was only 85%. This increased to 89% when children with identified co-morbidities (similar to those proposed here) were excluded and to 95% when a threshold of 2500 parasites/μL was also applied .Table Table P. falciparum malaria showed that coma, seizures, lactic acidaemia, respiratory distress and hypoglycaemia were independent predictors of death [Many studies have investigated the value of various clinical and laboratory markers as prognostic indicators of mortality and sequelae in malaria. In 1995, Marsh and colleagues showed that impaired consciousness, respiratory distress and severe anaemia were three central markers of disease severity associated with adverse outcome, especially when present together [of death . The higof death .Neurological impairment is a frequent marker of disease severity, and can result in long-term neurological sequelae . In a reProstration was included in the case definition of severe malaria as an important sign that will allow capture of many of the children that need hospital admission, surveillance, and prompt treatment to prevent further complications. Prostration is defined as the inability to perform a previously-acquired motor function, such as standing, sitting or, in very young children, the ability to suck, and is assessed in a child who is calm and awake. The trial algorithm for evaluating prostration is shown in Figure The Blantyre coma score provides a way of measuring conscious levels that is relatively easy to standardize across different sites. A low Blantyre coma score is associated with a high risk of an adverse outcome in malaria ,27. The Respiratory distress is also an important predictor of mortality in severe malaria ,25,28-30Metabolic complications are common in severe malaria, particularly hypoglycaemia and acidosis . HypoglyAcidosis, associated with lactic acidaemia and a low serum bicarbonate or base excess, has also been shown to be associated with an increased risk of mortality in patients with malaria ,31,33-36Severe malaria anaemia is a frequently overlooked contributor to overall malaria mortality, especially in young children. Studies have reported case fatality rates from severe malaria anaemia varying between 5.6% and 16%, with over 50% of deaths occurring within 24 hours of admission ,27. HoweMarkers of disease severity included in the case definition were chosen on the basis of their association with poor outcome, occurrence in a significant fraction of cases and an ability to standardize their measurement across sites. The selected markers also minimized data redundancy. For example, although circulatory collapse and delayed capillary refill time predicts mortality in children with severe malaria , it was P. falciparum parasitaemia and remain seemingly healthy, children admitted to hospital with P. falciparum parasitaemia often have an associated illness with symptoms which overlap with those of severe malaria [While children in areas of intense malaria transmission may have  malaria ,11,50,51Several studies have demonstrated the difficulty of distinguishing between severe malaria and pneumonia, both of which are frequently associated with fever, tachypnoea and respiratory distress ,52,53. T6/L, a positive culture of an organism known to cause meningitis, or a positive Hib, pneumococcal or meningococcal latex agglutination antigen detection test will be excluded from the primary case definition of severe malaria  or a bacteria that could be either a pathogen or a contaminant is isolated within 48 hours of incubation  [Bacteraemia is common, and associated with a high mortality, in children admitted to hospital in sub-Saharan Africa . Severalaecalis) .For the purposes of the trial, gastroenteritis with severe dehydration will be defined as a history of three or more loose or watery stools in the previous 24 hours and an observed watery stool with decreased skin turgor  , a blood sample is taken for the evaluation of haemoglobin, glucose, lactate, base excess, parasitaemia and blood culture, and that a case report form is completed. The decision to perform a lumbar puncture or chest X-ray will be made according to specific indications for each procedure and, in addition, if the clinician judges such an investigation likely to be useful to guide management. As far as possible, procedures and evaluations will be carried out in a child-friendly, relaxed environment, in the presence of a parent. Lumbar puncture will be indicated when children present with prostration, meningism (stiff neck or bulging fontanel), reduced conscious level , or seizure other than a simple, generalized febrile seizure defined as one associated with fever, lasting ≤ 5 minutes, followed by no neurological abnormalities other than post-ictal sleep, and occurring in a child ≥ 6 months with full recovery within 1 hour. If there are signs of raised intracranial pressure, if there is no access to the puncture point or if lumbar puncture would compromise the child's respiratory efforts, then lumbar puncture will be delayed until after the patient's condition has stabilized. A chest X-ray will be done if there is tachypnoea or respiratory distress, especially lower chest wall in-drawing or abnormally deep breathing.Implementation of standardized patient assessment is supported by a rigorous training and accreditation programme for all clinicians involved in patient care, including regular monitoring and evaluation during the trial. An online training and accreditation resource will be available to facilitate new staff training or refresher training of accredited staff if necessary.Other provisions for optimizing general patient care, which were implemented in preparation of the trial, are summarized in Table The severe malaria case definitions described in this paper have been adopted for evaluation of vaccine efficacy against severe malaria at the trial analysis stage, and their use will not compromise the ability of study physicians to treat study children who present unwell with malaria, regardless of whether the criteria of standardized trial case definition are met, according to international guidelines and national recommendations. These are reviewed in one of the modules in the training and accreditation programme for investigators, covering aspects such as triage, nursing, emergency care, treatment of hypoglycaemia, convulsions, acidosis and anaemia (including precautions for blood transfusion), and use of antibiotics and anti-malarials.The infrastructure of study centres has been improved to ensure that patients have standardized access to the assessment and diagnostic techniques needed for the study. This required patient access to care to be facilitated, wards to be refurbished and the introduction or strengthening of radiological and microbiological capacities Table . These iSevere malaria has been identified by a WHO expert study group as an important endpoint for trials of malaria vaccines . Its pubIn the present study, the primary and secondary case definitions reflect the presentation of severe malaria that typically leads to hospitalization of young children in Africa. Furthermore, they are in accordance with the recommendations of the WHO , are locJV and AL are employees of GSK Biologicals and hold stock options in GSK Biologicals. JV, KM, BG, AL, KPA, DA, JE, JS, PB, NS, PN, and SG declare their institution received a grant from PATH-MVI for the clinical trial described in this manuscript. JV and AL declare their institution has received grants from PATH-MVI for previous clinical trials. PB and PN declare their institution has grants pending from PATH-MVI. KM, BG, KPA, JE, JS, PB, NS, PN, MJH, SG, and DS declare receiving travel funds from PATH-MVI for travel related to this clinical trial. KPA declares his institution receiving a consultancy fee from PATH-MVI. JE and SG declare they or their institution receive financial compensation from PATH-MVI for administrative support. DS is employed by PATH-MVI. WK, SS, PK, and WO declare no potential conflicts of interest.The following authors worked on behalf of the Clinical Trials Partnership Committee;Kevin Marsh, Brian Greenwood, Amanda Leach, Kwaku Poku Asante, Daniel Ansong, Jennifer Evans, Jahit Sacarlal, Philip Bejon, Patricia Njuguna, Mary J Hamel and Samwel Gesase.All authors contributed to the development of this manuscript through discussions and document review. JV led the writing of the manuscript coordinating the incorporation of all reviewer comments. JV and DS coordinated the input of the PATH-MVI team. All authors critically contributed to the development of the case definitions of malaria and developed methods to standardize data collection through critical discussions and review of the protocol. KM, WK, SS, KPA, DA, JE, JS, PB, PK, NS, PN, MJH, WO, and SG contributed to the further development and implementation of the trial methodology at their research sites. All authors read and approved the final manuscript.