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      Estimating the Number of Paediatric Fevers Associated with Malaria Infection Presenting to Africa's Public Health Sector in 2007

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          Peter Gething and colleagues compute the number of fevers likely to present to public health facilities in Africa and the estimated number of these fevers likely to be infected with Plasmodium falciparum malaria parasites.



          As international efforts to increase the coverage of artemisinin-based combination therapy in public health sectors gather pace, concerns have been raised regarding their continued indiscriminate presumptive use for treating all childhood fevers. The availability of rapid-diagnostic tests to support practical and reliable parasitological diagnosis provides an opportunity to improve the rational treatment of febrile children across Africa. However, the cost effectiveness of diagnosis-based treatment polices will depend on the presumed numbers of fevers harbouring infection. Here we compute the number of fevers likely to present to public health facilities in Africa and the estimated number of these fevers likely to be infected with Plasmodium falciparum malaria parasites.

          Methods and Findings

          We assembled first administrative-unit level data on paediatric fever prevalence, treatment-seeking rates, and child populations. These data were combined in a geographical information system model that also incorporated an adjustment procedure for urban versus rural areas to produce spatially distributed estimates of fever burden amongst African children and the subset likely to present to public sector clinics. A second data assembly was used to estimate plausible ranges for the proportion of paediatric fevers seen at clinics positive for P. falciparum in different endemicity settings. We estimated that, of the 656 million fevers in African 0–4 y olds in 2007, 182 million (28%) were likely to have sought treatment in a public sector clinic of which 78 million (43%) were likely to have been infected with P. falciparum (range 60–103 million).


          Spatial estimates of childhood fevers and care-seeking rates can be combined with a relational risk model of infection prevalence in the community to estimate the degree of parasitemia in those fevers reaching public health facilities. This quantification provides an important baseline comparison of malarial and nonmalarial fevers in different endemicity settings that can contribute to ongoing scientific and policy debates about optimum clinical and financial strategies for the introduction of new diagnostics. These models are made publicly available with the publication of this paper.

          Please see later in the article for the Editors' Summary

          Editors' Summary


          Malaria —an infectious parasitic disease transmitted to people through the bite of an infected mosquito —kills about one million people (mainly children living in sub-Saharan Africa) every year. Although several parasites cause malaria, Plasmodium falciparum is responsible for most of these deaths. For the past 50 years, the main treatments for P. falciparum malaria have been chloroquine and sulfadoxine/pyrimethamine. Unfortunately, parasitic resistance to these “monotherapies” is now widespread and there has been a global upsurge in the illness and deaths caused by P. falciparum. To combat this increase, the World Health Organization recommends artemisinin combination therapy (ACT) for P. falciparum malaria in all regions with drug-resistant malaria. In ACT, artemisinin derivatives (new, fast-acting antimalarial drugs) are used in combination with another antimalarial to reduce the chances of P. falciparum becoming resistant to either drug.

          Why Was This Study Done?

          All African countries at risk of P. falciparum have now adopted ACT as first-line therapy for malaria in their public clinics. However, experts are concerned that ACT is often given to children who don't actually have malaria because, in many parts of Africa, health care workers assume that all childhood fevers are malaria. This practice, which became established when diagnostic facilities for malaria were very limited, increases the chances of P. falciparum becoming resistant to ACT, wastes limited drug stocks, and means that many ill children are treated inappropriately. Recently, however, rapid diagnostic tests for malaria have been developed and there have been calls to expand their use to improve the rational treatment of African children with fever. Before such an expansion is initiated, it is important to know how many African children develop fever each year, how many of these ill children attend public clinics, and what proportion of them is likely to have malaria. Unfortunately, this type of information is incompletely or unreliably collected in many parts of Africa. In this study, therefore, the researchers use a mathematical model to estimate the number of childhood fevers associated with malaria infection that presented to Africa's public clinics in 2007 from survey data.

          What Did the Researchers Do and Find?

          The researchers used survey data on the prevalence (the proportion of a population with a specific disease) of childhood fever and on treatment-seeking behavior and data on child populations to map the distribution of fever among African children and the likelihood of these children attending public clinics for treatment. They then used a recent map of the distribution of P. falciparum infection risk to estimate what proportion of children with fever who attended clinics were likely to have had malaria in different parts of Africa. In 2007, the researchers estimate, 656 million cases of fever occurred in 0–4-year-old African children, 182 million were likely to have sought treatment in a public clinic, and 78 million (just under half of the cases that attended a clinic with fever) were likely to have been infected with P. falciparum. Importantly, there were marked geographical differences in the likelihood of children with fever presenting at public clinics being infected with P. falciparum. So, for example, whereas nearly 60% of the children attending public clinics with fever in Burkino Faso were likely to have had malaria, only 15% of similar children in Kenya were likely to have had this disease.

          What Do These Findings Mean?

          As with all mathematical models, the accuracy of these findings depends on the assumptions included in the model and on the data fed into it. Nevertheless, these findings provide a map of the prevalence of malarial and nonmalarial childhood fevers across sub-Saharan Africa and an indication of how many of the children with fever reaching public clinics are likely to have malaria and would therefore benefit from ACT. The finding that in some countries more than 80% of children attending public clinics with fever probably don't have malaria highlights the potential benefits of introducing rapid diagnostic testing for malaria. Furthermore, these findings can now be used to quantify the resources needed for and the potential clinical benefits of different policies for the introduction of rapid diagnostic testing for malaria across Africa.

          Additional Information

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          Impact of Artemisinin-Based Combination Therapy and Insecticide-Treated Nets on Malaria Burden in Zanzibar

          Introduction The increased malaria-related morbidity and mortality, especially in children under the age of 5 y (“under five”), due to emerging resistance of Plasmodium falciparum to conventional antimalarial drugs calls for immediate actions to “Roll Back Malaria” in sub-Saharan Africa. This need has been clearly recognized in the Millennium Development Goals “to halt and begin to reverse malaria incidence” [1] as well as in the Abuja Declaration objective to halve malaria mortality in Africa by 2010 through implementation of combined control strategies [2]. In the year 2000, the overall treatment failure of chloroquine was found to be 60% in a 14-d efficacy trial; consequently the Zanzibar Ministry of Health and Social Welfare decided in November 2001 to change both first- and second-line treatment guidelines for uncomplicated malaria from chloroquine and sulfadoxine-pyrimethamine to artemisinin-based combination therapies (ACT) [3]. The ACT policy was implemented in September 2003, when Zanzibar became one of the first regions in sub-Saharan Africa to recommend routine use of ACT. This action was followed by strengthened vector control, culminating in a nation-wide distribution campaign of long-lasting insecticidal nets (LLINs) from early 2006. Both ACT and vector control measures have independently proven to be efficacious malaria control strategies. Ecological studies have credited ACT with enhancing treatment efficacy, reducing malaria transmission, and possibly forestalling drug resistance in low-endemicity areas [4,5]. Moreover, specific African trials have indicated that the use of insecticide-treated nets (ITNs) or indoor residual spraying can reduce mortality of children under five in Africa [6–9]. This is, however, to our knowledge the first study to examine the public health impact of wide-scale deployment of ACTs alone and combined with ITNs through the general health structure/channels on malaria indices and general health parameters in an endemic area in sub-Saharan Africa. Methods Study Site The study was conducted in North A District, Zanzibar, situated just off the coast of mainland Tanzania. The district is rural and has a population of about 85,000. Subsistence farming and fishing are the main occupations. Plasmodium falciparum is the predominant malaria species and Anopheles gambiae complex is considered the main vector. Malaria transmission is stable with seasonal peaks related to rainfall in March–May and October–December. Malaria transmission in the district prior to the interventions has been reported to be high, but specific entomological data are not available to allow a precise characterization of malaria transmission intensity. However, during the screening process of a major antimalarial drug trial conducted in 2002–2003, a P. falciparum prevalence exceeding 30% was observed in febrile children under five [10], suggesting that North A District had been a high transmission area prior to ACT implementation in September 2003. North A District has one Primary Health Care Centre, which includes a hospital with inpatient and laboratory services, e.g., blood transfusion and malaria microscopy services. Basic medical treatment services without laboratory support are provided in 12 Primary Health Care Units located in different shehias (the smallest political administrative unit in Zanzibar). Drugs, including conventional and artemisinin monotherapies, are also available in private shops throughout the district. Malaria Control Interventions Figure 1 illustrates time of implementation of the two malaria control interventions. Figure 1 Malaria Interventions, Cross-Sectional Surveys, Monthly Rainfall, and Reported Clinical Malaria Diagnoses in Children under 5 Years of Age in North A District, Zanzibar (A) Start of the implementation of artemisinin-based combination therapy for treatment of uncomplicated malaria in September 2003. (B) Introduction of LLINs in February 2006. Promotion of ITNs started in January 2004; the use of conventional ITNs, however, remained low, until the introduction of LLINs. Outpatient data for 2006 are up to June. First intervention—ACT. A loose combination of artesunate and amodiaquine (AS+AQ; from various suppliers with preapproval from WHO) and a fixed combination of artemether–lumefantrine (Coartem; Novartis, Basel, Switzerland), were implemented as first- and second-line treatment, respectively, for uncomplicated malaria in all public health facilities from September 2003. In a pre-implementation assessment of the new treatment policy, partly conducted in North A District 2002–2003, both AS+AQ and artemether–lumefantrine were highly efficacious with PCR-adjusted cure rates by day 28 above 90% [10]. Quinine remained the drug of choice for severe malaria and sulfadoxine-pyrimethamine for intermittent preventive treatment during pregnancy. From September 2003, chloroquine was withdrawn from all health facilities and replaced by free provision of ACT to all malaria patients. Total treatment courses of AS+AQ dispensed in North A 2004 and 2005 were 34,724 and 12,819, respectively. The supply of ACT has been uninterrupted, with no reports of AS+AQ being out of stock from any public health facility in the district during 2003–2006 (unpublished data). ACTs were purchased with support from African Development Bank and Global Fund to Fight AIDS, Tuberculosis and Malaria (GFATM). Second intervention—vector control. A policy to distribute conventional ITNs to the most vulnerable groups—children under five and pregnant women—free of charge through antenatal clinics or local shehia leaders was officially launched in 2004. However, ITN coverage and use remained low in North A District 2004 and 2005 due to limited number of ITNs distributed, 4,026 and 1,550, respectively. A mass campaign was therefore initiated early 2006, with distribution of 23,000 LLINs to the two most vulnerable groups in North A. This campaign was supported by GFATM and the US Agency for International Development. Cross-Sectional Surveys Three cross-sectional surveys with the primary objective to determine P. falciparum prevalences were conducted in North A District between 2003 and 2006. A two-stage cluster sample technique was used. First shehias and then the households were randomly selected from the sampling frame obtained from the Office of Chief Government Statistician, Zanzibar. The sampling frame was updated before each survey. The first exploratory survey, conducted in May 2003, included 625 households and provided baseline data prior to ACT and widespread ITN implementation. Sample size calculations for the follow-up surveys conducted in May 2005 and 2006 were based on the proportion of children under five with malaria parasitemia in 2003, about 9%, and an assumed relative error of 20%. The calculated number of households to be included was 490 after adjusting for a design effect of 2. Trained interviewers visited all selected households. Interviews and blood sample collection were initiated upon written consent from head of each household and proxy consent from the mother or guardian of each child. Information was recorded using a structured questionnaire on recent febrile illness, mosquito net use, and care-seeking behavior from each individual present in the household at the time of the survey. We did not replace households in which residents were not present at time of survey, could not be located, or refused to participate. Thick blood films were collected from all consenting participants, stained with 5% Giemsa for 30 min, and examined by experienced microscopists for presence and density of P. falciparum parasites. If fewer than ten parasites were detected per 200 white blood cells, examinations were extended to 500 white blood cells. Blood slides were considered negative if no asexual parasites were found in 200 high-power fields. High-density parasitemia was defined as presence of ≥ 5,000 parasites/μl [11]. Quality control was conducted for all positive slides and 10% of the negative slides [12]. Health Facility Records Malaria-related indicators, i.e., outpatient attendances, hospital admissions and blood transfusions, from all 13 public health facilities in North A District were obtained from the Health Management and Information System (HMIS) records of the Zanzibar Ministry of Health and Social Welfare. The existing HMIS records were about 90% complete for the period 2000–2004. Data were validated and missing information retrieved by retrospective review of source documents from all 13 health facilities. This confirmed the HMIS records and resolved missing or inconsistent data, which increased the completeness to nearly 100%. A database of malaria-related indicators was created on the basis of this retrospective review. Data from 2005 were abstracted on quarterly basis. Vital Statistics Records of vital events, i.e., births and deaths, for the period 1998–2005 were obtained from the District Commissioner's Office (DCO) in North A. Annual crude mortalities of children under five were estimated from these data. Demographic estimates were obtained from Tanzania National Population and Housing Census 2002. Rainfall Complete records of monthly rainfall during 1999–2005 were obtained from official registers of the Tanzania Metrological Agency of the Ministry of Communications and Transport. On Unguja island, rainfall is centrally measured in one weather station, situated 26 km (radially) from North A District. The mean annual rainfalls recorded in 2003, 2004, 2005, and 2006 were 702, 1,934, 1,231, and 1,214 mm, respectively. The corresponding mean seasonal rainfall (March–May) between 2003 and 2006 was 285, 786, 890, and 613 mm, respectively. During the post-ACT intervention period (2004–2006) the mean annual and seasonal rainfall was 8%–12% lower than the pre-ACT intervention period (2000–2002). However, the only year with a marked reduction in the mean annual and seasonal rainfalls was the year 2003 with two- to three-fold lower rainfall, as compared to both the preceding and subsequent 3 y. Data Processing and Analysis Data were entered and validated using Microsoft Access and Excel. Statistical analyses for cross-sectional surveys, health facility records, vital statistics, and rainfall data were performed using Stata version 8. Analysis for the surveys was corrected for multi-stage sampling errors using the Rao-Scott second order correction [13]. A logistic regression model with robust standard errors (robust cluster) was used to adjust for the effect of age, sex, sleeping under a mosquito-net, and asset index on asexual P. falciparum prevalence and gametocyte carriage across the study years. Households were the primary sampling units in the surveys and were defined as clusters. Wald test was used to assess the fit of the model and interactions between covariates incorporated in the model. Odds ratios were adjusted for the complex sampling design and covariates listed above. Pearson correlation coefficients were calculated to assess the linear relationships between monthly rainfall and outpatient malaria diagnosis, and malaria-attributed deaths. Ethical Approval Protocols for the household surveys were reviewed and approved by the Medical Research Coordinating Committee of the Tanzanian Commission on Science and Technology, the Zanzibar Health Research Council and the institutional review board of US Centers for Disease Control and Prevention. Results Cross-Sectional Surveys The timings of the cross-sectional surveys in relation to start of each malaria control intervention and seasonal rainfalls are presented in Figure 1. The number of households enrolled and participant characteristics in the respective surveys are shown in Table 1. Over 95% of all participants agreed to both answer questionnaires and provide blood samples in the respective surveys. Table 1 Number of Households Surveyed and Characteristics of Survey Participants The parasite prevalences and odds ratios (ORs) of asexual P. falciparum parasitemia and gametocyte carriage at the time of cross-sectional surveys are shown in Table 2. Between 2003 and 2005 the parasite prevalence was reduced by about 50% in children under five. A further 10-fold decrease in P. falciparum prevalence was observed between 2005 and 2006, following mass distribution of LLINs specifically targeting this age group. Concomitant reductions of parasite prevalence were observed in children over the age of 5 y, although only by about 3-fold, between 2005 and 2006 (OR 0.41, 95% confidence interval [CI] 0.13–1.21), p = 0.08). Table 2 Parasite Prevalence and ORs of P. falciparum Asexual Parasitemia and Gametocytemia in Children 0–14 Years of Age in North A District, Zanzibar, in May 2003, 2005, and 2006 High-density parasitemia (≥5,000/μl) was found in 14 (2.7%) and 2 (0.6%) children under five in 2003 and 2005, respectively. No child carried high-density parasitemia in 2006. Reported fever within 14 d prior to the survey was similar in 2003 and 2006 among children under five (2003, 13% [95% CI 11–17]; 2006, 12% [95% CI 9–16]), whereas care-seeking at public health facilities by recently febrile children under five increased significantly (2003 was reference year; 2005, OR 3.91 [95% CI 0.85–17.9]; 2006, OR 5.5 [95% CI 2.3–13.3]; p-value for trend < 0.001). The proportions of children under five sleeping under effective ITNs were below 10% in both 2003 and 2005 (Table 1), whereas in 2006, 90% were reported sleeping under an LLIN on the night before survey. Health Facility Surveillance All reported clinical outpatient malaria diagnoses in North A District between January 1999 and June 2006 among children under five are shown by month in Figure 1 and by year in Table 3. Between 2002 and 2005 the total number of out-patient malaria diagnoses decreased by 77%. The annual incidences of malaria diagnoses standardized per 1,000 children under five in North A District were 843, 786, and 233 in 2003, 2004, and 2005, respectively. The total number of children under five attending public health facilities for any cause during 1999 and 2005 remained relatively constant, ranging from 31,069 to 39,374 annually. Up to 2003 malaria accounted for about 50% of all outpatient diagnoses in this age group, whereas in 2005 this proportion had decreased to 13%. Table 3 Outpatient Malaria Diagnoses, Hospital Admissions, Blood Transfusions, and Malaria-Attributed Deaths in North A District, Zanzibar, between 2000 and 2005 Malaria-related hospital admissions, non-malaria admissions, and blood transfusions in children under five between 2000 and 2005 are also shown in Table 3. From 2002 to 2005, malaria-related admissions, blood transfusions, and malaria-attributed mortality decreased by 77%, 67%, and 75%, respectively. Crude Mortality Data A total of 23,200 live births and 1,032 deaths in children under five (49% females) were registered between January 1998 and December 2005. The annual mortality figures for children under five, children (1–4 y), and infants (0–1 y) are shown in Table 4. Between 2002 and 2005, crude under five, infant, and child mortality decreased by 52%, 33%, and 71%, respectively. Table 4 Mortality of Children under 5 Years of Age in North A District, Zanzibar between 1998 and 2005 Relationships between Rainfall and Malaria Diagnosis and Deaths In the pre-ACT intervention period (2000–2002), significant positive correlations were found between monthly rainfall and both outpatient malaria diagnoses (Pearson correlation coefficient [r p] = 0.59, p < 0.001) and malaria-attributed deaths (r p = 0.75, p < 0.001), when data were adjusted to allow for a 1-mo lag between rainfall and malaria diagnoses and deaths. However, in the post-ACT intervention period (2003–2005), no significant correlations were found between monthly rainfall and outpatient malaria diagnosis (r p = −0.05; p = 0.75) or malaria-attributed deaths (rp = 0.23; p = 0.20). Discussion Malaria burden in Zanzibar, as in most parts of sub-Saharan Africa, has remained high and in many areas even increased during the last 10–20 y, a major reason being rapid spread of resistance to commonly used monotherapies against malaria. This problem has necessitated urgent implementation of new and effective control strategies to “Roll Back Malaria.” Two main cornerstones in this effort are the introduction of ACTs for treatment of uncomplicated malaria and the promotion of ITN use. The targets for the implementation of these new strategies have been defined by the UN Millennium Development Goals [1] and the Abuja Declaration [2], to be achieved by the years 2015 and 2010, respectively. Deployment of ACTs The ACTs were dispensed free of charge to all patients in the study area through public health facilities from September 2003 onwards. The ACT implementation and deployment was very rapid, effective, and with high coverage. Monitoring of drug supplies confirmed that ACTs were available throughout the study period in all 13 public health care settings in North A District. This outcome also indicates that estimates were adequate of the needed and thus deployed numbers of ACT treatments in the district. This result was accomplished despite an apparent two-fold increase in care seeking among children under the age of 5 y at public health facilities as observed in the cross-sectional surveys. We believe that the observed shift in treatment-seeking behavior at public facilities may be related to availability of free, effective ACTs. A previous study in Zanzibar showed that people's attitudes towards health seeking at public health facilities (biomedical practices) are negatively influenced by the distribution of ineffective antimalarial drugs [14]. High ACT coverage was rapidly achieved in malaria patients despite availability of other drugs in the private sector. This achievement was probably influenced both by comprehensive information to the public and health care staff and by the strong commitment of the Zanzibar government to rapidly ensure free coverage of the ACTs. Also, in North A District, as well as in Zanzibar generally, the entire population has relatively easy access to public health facilities, which are located within 5 km from any community and are served by good transport links. However, the absence of co-formulation or even of co-blistering of the two compounds in the first-line treatment, artesunate and amodiaquine, may have resulted in some degree of monotherapy with either compound. Mortality Impact Our study provides the first, to our knowledge, observation of a reduction in mortality of children under five following introduction of ACTs solely in a stable malaria-endemic setting. The highly significant reduction of 52% in crude under-five mortality according to vital statistics between 2002 and 2005 also highlights the importance of malaria as a major cause of death among children in malaria-endemic areas. The 71% reduction among children aged 1–4 y indicates that the relative contribution of malaria to crude mortality is particularly important in this age group. Major reductions in crude under-five mortality has also been observed in previous randomized intervention studies with ITNs [6,7] and community-based malaria treatment [15,16], but the reduction rates (between 25% and 40%) have been less pronounced than those in our study in Zanzibar. We believe our findings are valid and represent a true picture of the effects of ACT deployment in North A District, Zanzibar. No other major political, socioeconomic, or health-care change with the potential to halve mortality in children under five occurred in Zanzibar after 2002. This includes Expanded Programme on Immunization coverage, which remained constantly above 80% in the district during 1999–2005. Furthermore, there was no significant change in rainfall that may have contributed to the observed reduction in malaria transmission. Indeed, the only year with reduced rainfall with potential influence on vector capacity occurred before the introduction of ACTs—in 2003. Increased use of ITNs may also represent a potential confounding factor in our study. However, the ITN use was below 10% during 2004 and 2005 as reported and observed during the cross-sectional surveys. A significant improvement in ITN coverage was only achieved in 2006 after the introduction of LLINs (see further below) and only affected the 2006 cross-sectional results. We chose 2002 as reference year in our analyses of health facility surveillance and under-five mortality, because 2002 represents the last complete year before ACT introduction in September 2003. Routinely collected mortality statistics may underestimate the true values. However, such data have been shown to provide valid mortality trends [17,18]. Morbidity Impact A significant reduction was found with regard to hospitalization of malaria patients and incidence of blood transfusions, which may be considered proxy indicators of severe malaria. The reduction of severe malaria showing a similar pattern thus supports the under-five mortality trends. This health impact probably represents effects of improved case management of uncomplicated malaria with ACT, thus preventing the development of severe manifestations of the disease. The decrease in malaria morbidity (and mortality) at health facilities between 2003 and 2005 confirms the therapeutic efficacy of ACT [10], but the reduction in outpatient malaria diagnoses may also reflect some transmission blocking effect of artemisinin derivatives through its gametocytocidal activity. Reduction in transmission potential has been suggested after the introduction of artemisinin derivatives (before vector control) for routine treatment in a low and seasonal malaria transmission setting in Thailand [4]. Data obtained from routine health facility records have inherent potential pitfalls and need to be interpreted cautiously. However, the fact that they all show the same downward trend after improved coverage of malaria prevention and treatment interventions, and with no change in the climatic conditions that are favorable for malaria transmission, supports the plausible conclusion that enhanced malaria control interventions contributed to the observed public health benefits. Deployment of ITNs The deployment of LLINs in early 2006 provided a high coverage, i.e., over 90% reported use in children under five in the cross-sectional survey in May 2006. Importantly, this high mosquito-net use was observed after strong government commitment and after free LLIN distribution to children under five and pregnant women. The most significant decrease in prevalence of asymptomatic parasitemia was achieved in 2006, when LLINs were widely used by the children under five, whereas the major impact on the under-five mortality was achieved earlier with ACT use only. Strengthened vector control and the use of ACT also resulted in marked and sustained malaria control in South Africa [5]. The similar public health benefits observed in North A supports the concomitant use of vector control and ACT for malaria control. However, it should be emphasized that our study captures short-term trends in malaria control in North A, which may be too short to generalize long-term trends in the burden of malaria. Sustained coverage and use of LLINs by vulnerable groups is yet to be demonstrated, especially under declining malaria endemicity and if the free LLIN distribution scheme were to be changed. Conclusions The declining under-five mortality, malaria morbidity, and malaria prevalence observed in our study is the first comprehensive evidence supporting the major public health benefits of ACT and ITNs in a stable endemic malaria transmission setting in sub-Saharan Africa. The findings suggest that ACTs with high coverage of ITN use may potentially even eliminate malaria as a public health problem in highly endemic areas of sub-Saharan Africa. High community uptake of the two interventions is probably required but indeed achievable if, as in our study, they are easily available free of charge. The UN Millennium Development Goals to alleviate malaria as a major public health problem and substantially reduce the under-five mortality in sub-Saharan Africa are thus achievable even in settings with historically intense malaria transmission. The sustainability of these efforts as well as surveillance to prevent resurgence of malaria represent key research and programmatic follow-up issues of malaria control in Africa.
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            The Limits and Intensity of Plasmodium falciparum Transmission: Implications for Malaria Control and Elimination Worldwide

             Carlos Guerra,  David Smith (corresponding) ,  Priscilla W Gikandi (2008)
            Introduction The magnitude of the public health burden posed by malaria worldwide [1] and its connection to poverty [2] has galvanized the international donor community to put malaria control high on the development agenda and helped leverage unprecedented additional financing for malaria endemic countries [3]. Progress toward agreed targets of intervention coverage has been slow [4–6], but recent evidence indicates a precipitous increase in access to effective drugs and prevention strategies in several countries [7–10]. In part, this renaissance in malaria control has served as a catalyst to revisit the possibility of malaria elimination in many regions and countries [11–14]. A changing malaria landscape requires an accurate spatial and dynamic description of malaria risk that maps the spatial extent and need for control and elimination over the coming decades. Such a map is conspicuous by its absence [15]. Here, we present the first detailed description of the global distribution of P. falciparum risk in 40 y [16,17] by using geopositioned assemblies of national surveillance of malaria risk, medical intelligence, biological models of transmission suitability, and surveys of parasite prevalence. The paper focuses on detailing the data sources and their adaptation for the malaria cartography necessary to guide current disease control, with an emphasis on how we define the spatial limits of stable and unstable P. falciparum risk worldwide. Methods Using Medical Intelligence to Define the Limits of P. falciparum Risk Many countries have information assembled from medical intelligence on the distribution of malaria risk within their national borders. This information is documented primarily in reports from national health information systems that define the annual numbers of confirmed parasite-specific local malaria infections by geographic unit, referred to classically as the annual parasite incidence (API) [18–21]. The API is generated from various combinations of active (fever surveys in communities where every person presenting with a fever is tested for parasite infection) and passive (reports from febrile patients attending the local health services) case detection, and usually expresses the combined results as the number infected per 1,000 people per annum (pa) [18–21]. The precision of these estimates of malaria incidence are highly variable, and with the exception of some countries where case identification is a primary control tool [22], these data cannot be used confidently to derive the public health burden posed by malaria [1,23–26]. They can, however, be a useful indicator of where local parasite species-specific malaria risk is likely or absent, and are particularly plausible when triangulated with other sources of medical intelligence, reported in international travel health guidelines or by national malaria control programmes. Malaria coordinating officers in the regional offices of the World Health Organization (WHO), responsible for the collation of national API data from member countries were contacted to obtain data reported nationally to the highest possible geographic administrative unit level on populations at risk and numbers of confirmed P. falciparum cases, for as many years as were available between 2002 and 2006. Among the countries in the American Regional Office, P. falciparum–specific API (PfAPI) data from national surveillance systems in Brazil, Colombia, Peru, and Honduras were obtained directly from personal communication with malaria specialists. The reported cases of confirmed P. falciparum malaria per 1,000 resident population were computed for each year by administrative level and averaged over the number of reporting years. Summary data were categorized as no autochthonous P. falciparum cases reported, <0.1 autochthonous P. falciparum cases per 1,000 people pa, and ≥0.1 autochthonous P. falciparum cases per 1,000 people pa. The threshold around 0.1 cases per thousand pa was used to provide some indication of unstable conditions versus more stable transmission. This threshold is consistent with previous uses of PfAPI during the Global Malaria Eradication Programme [27] and balanced against the confidence in the precision of reported PfAPI values (Protocol S1). Each PfAPI summary estimate was mapped by matching it to its corresponding first-, second-, or third-level administrative unit in a geographic information system (GIS; ArcView GIS 3.2, ESRI, 1999). Mapped PfAPI data were then compared to other sources of medical intelligence, notably national malaria control presentations at regional malaria meetings obtained from regional WHO malaria coordinators and from Web sites, published sources that described national malaria epidemiology, and international travel and health guidelines [28,29]. These combined approaches were particularly useful to identify mapped descriptions of risk defined at higher spatial resolution than those described by the PfAPI reported across large first-level administrative units. Details of all sources used are provided in Protocol S1. Defining the Biological Limits of P. falciparum Transmission Within the limits of risk described through PfAPI, environmental conditions suitable for transmission vary enormously. These variations can be captured at much higher spatial resolution than it is possible to define by stratifying risk at administrative unit levels. Climate-based determinants of parasite and vector development and survival were developed that impose biological constraints on the geographical limits of P. falciparum transmission. First, we used a combination of the temperature-dependant relationship between P. falciparum sporogony and the longevity of the main dominant vectors to estimate the proportion of vectors surviving parasite development (Protocol S2). Using mean monthly temperature records from a 30-arcsec (∼1 km) spatial resolution climate surface [30], the duration of P. falciparum sporogony was estimated for each synoptic calendar month, and those pixels where the duration of sporogony was 31 d or less were identified. The exception was small areas that potentially support the longer-lived Anopheles sergentii and A. superpictus, where 62 d were considered more appropriate biologically (Protocol S2). This resulted in 12 images with a binary outcome: P. falciparum sporogony could or could not be completed in the month. These images were then combined to identify the number of suitable months for P. falciparum transmission in a synoptic year. All pixels where the duration of sporogony exceeded 1 mo, or 2 mo for areas within the range of A. sergentii and A. superpictus, were masked since it was highly unlikely that transmission would occur. Second, there are areas within several malaria endemic countries where, despite temperature being suitable for sporogony, arid conditions restrict Anopheles development and survival [31]. Limited surface water reduces the availability of water bodies for oviposition. Moreover, low ambient humidity in arid environments further affects egg and adult survival through the process of desiccation [32]. The ability of adult vectors to survive long enough to contribute to parasite transmission and of preadult stages to ensure minimum population abundance is, therefore, dependent on the levels of aridity and species-specific resilience to arid conditions. To capture the influence of aridity on transmission we used the enhanced vegetation index (EVI) derived from the bidirectional reflectance-corrected MODerate-resolution Imaging Spectroradiometer (MODIS) sensor imagery, available at approximately 1-km spatial resolution [33,34] (Protocol S2). Temporal Fourier–processed, monthly EVI images were used to develop 12 monthly surfaces that reclassified EVI ≤ 0.1, assuming this corresponded to a good proxy for arid conditions [35,36]. Pixels were classified as suitable for transmission if their EVI values were higher than 0.1 for at least two consecutive months in an average year. This definition was based on the biological requirement, at optimum temperatures, of at least 12 d to complete vector development from egg to adult [37] and on the assumption that a second month is required for a sufficient vector population to establish and transmit malaria [38]. These reclassified aridity images were then overlaid in a GIS to produce 12 paired images. The 12 pairs were then combined to define pixels where conditions were suitable for transmission. The aridity mask was treated differently from the temperature-limiting mask to allow for the possibility, in arid environments, of highly over-dispersed transmission due to man-made water collection points and nomadic human populations transporting vectors and parasites [39–41]. A more conservative approach was taken, therefore, which down-regulated PfAPI risk by one class. In other words, extremely arid areas defined originally as at stable risk were stepped down to unstable risk and those classified initially as unstable to malaria free. Estimating Populations at P. falciparum Transmission Risk in 2007 The Global Rural Urban Mapping Project alpha version provides gridded population counts and population density estimates for the years 1990, 1995, and 2000, both adjusted and unadjusted to the United Nations' national population estimates [42]. We used the adjusted population counts for the year 2000 and projected them to 2007 by applying national, medium variant, intercensal growth rates by country [43], using methods previously described [44]. This resulted in a contemporary population density surface of approximately 1-km spatial resolution, which was combined with the climate-adjusted PfAPI risk surface to extract population at risk estimates using ArcView GIS 3.2 (ESRI, 1999). Describing Global Patterns of Parasite Prevalence We have described previously the rigorous process of identifying, assembling, and geolocating community-based survey estimates of parasite prevalence undertaken since 1985 [45]. These data were used here to define the ranges of P. falciparum parasite prevalence rates (PfPR) in areas of stable and unstable malaria risk by WHO region. We acknowledge that these geopolitical boundaries do not necessarily conform to ecological or biological spatial representations of malaria [46,47]. They do, however, represent coherent regions of collective planning and cooperation for malaria control. In an attempt to minimize epidemiologically unrealistic divides for summary purposes, we have combined the Southeast Asian (SEARO) and Western Pacific (WPRO), as well as the Eastern Mediterranean (EMRO) and European (EURO) regions. The American WHO region (AMRO) and the African WHO region (AFRO) were considered separately. PfPR estimates were reported in various age groupings. To standardize to a single, representative age range of 2–10 y, we applied an algorithm based on catalytic conversion models first adapted for malaria by Pull and Grab [48] and described in detail elsewhere [49]. The geolocated and age-standardized prevalence data (PfPR2−10) [45] were overlaid on the PfAPI risk surface to extract a corresponding PfAPI value. Results PfAPI Data and Medical Intelligence to Define Spatial Limits of Transmission The PfAPI data identified 87 countries at risk of P. falciparum transmission between 2002 and 2006, which we now consider as P. falciparum endemic countries (PfMEC) in 2007 (Protocol S1). PfAPI data were mapped to first, second, or third administrative level units across 41 PfMECs covering a total of 8,789 unique polygons. These data incorporate complete years between 2002 and 2006, including summaries of three consecutive years for 16 countries, two consecutive years for eight countries, and the most recent complete year for 17 countries (Protocol S1). No information was available for 46 countries; mostly those in Africa. The spatial representation of no risk, unstable (PfAPI < 0.1 per 1,000 people pa), and stable risk (PfAPI ≥ 0.1 per 1,000 people pa) of P. falciparum transmission globally is shown in Figure 1, top panel. Figure 1 P. falciparum Malaria Risk Defined by Annual Parasite Incidence (top), Temperature, and Aridity (bottom) Areas were defined as stable (dark-red areas, where PfAPI ≥ 0.1 per thousand pa), unstable (pink areas, where PfAPI < 0.1 per thousand pa), or no risk (light grey). The few areas for which no PfAPI data could be obtained, mainly found in India, are coloured in dark grey. The borders of the 87 countries defined as P. falciparum endemic are shown. Highland areas where risk was excluded due to temperature appear in light grey. The aridity mask excluded risk in a step-wise fashion, reflected mainly in the larger extents of unstable (pink) areas compared to the top panel, particularly in the Sahel and southwest Asia (southern Iran and Pakistan). Temperature and Aridity Masks to Constrain Limits of Transmission Within the PfAPI limits of stable transmission (PfAPI ≥ 0.1 per 1,000 pa) on the African continent, the areas with no temperature-suitable months for transmission were congruent with the high altitude areas in Ethiopia, Eritrea, western Kenya, eastern Tanzania, Rwanda, Burundi, eastern Democratic Republic of the Congo, the Malagasy highlands, Mount Cameroon, and the eastern highland ranges in Zimbabwe (Figure 1, bottom panel). Outside of Africa, there was a close correspondence between the areas masked by the absence of reported autochthonous cases and areas classified as unsuitable for transmission based on low temperature in Andean and Himalayan areas (Figure 1, bottom panel). The application of the temperature mask provided a finer spatial resolution constraint to PfAPI data, particularly for the island of New Guinea and the highlands neighbouring the city of Sana'a, Yemen. Important reductions in the spatial areas of risk were also evident in some administrative units in Afghanistan, Bhutan, China, India, and Kyrgyzstan. The aridity mask constrained the mapped P. falciparum transmission risk to small pockets in large administrative boundaries from southern areas of Hilmand and Kandahar, in Afghanistan, the municipality of Djibouti, in Djibouti, and the south-eastern provinces of Iran. The risk areas along the Red Sea coast of Saudi Arabia were also reduced further using the aridity mask. Additional areas constrained within their spatial margins to no risk using the aridity mask included administrative units in India (n = 4), Pakistan (n = 9), Peru (n = 3), Kyrgyzstan (n = 2), Tajikistan (n = 1), and the low risk areas of Namibia bordering the Namib desert. Large areas covered by the aridity mask were reduced from stable (PfAPI ≥ 0.1 per 1,000 pa) to unstable risk (PfAPI < 0.1 per 1,000 pa) in the Sahel. The transmission reducing effects of aridity were also evidenced in Djibouti, Eritrea, northwest Kenya, northeast Ethiopia, northern Somalia, central and coastal areas of Yemen, and southern Pakistan. Importantly, these areas retained small pockets of higher, more-suitable transmission conditions, corresponding to river tributaries and irrigated land where higher transmission risk is supported [50]. Populations at Risk Table 1 provides a summary of the spatial extents and the projected 2007 populations at risk (PAR) within areas of assumed unstable (PfAPI < 0.1 per 1,000 pa) and stable P. falciparum transmission (PfAPI ≥ 0.1 per 1,000 pa) globally and by WHO region. Country PAR estimations are also provided (Table S1). We estimate that there are 2.37 billion people at risk of P. falciparum transmission worldwide, 26% located in the AFRO region and 62% in the combined SEARO-WPRO regions (Table 1). The definition of unstable risk outlined here is the predominant feature of exposure to transmission in the EMRO-EURO region (Table 1). Low-risk areas in AFRO were also coincident with arid, low population density areas. Globally, 42% of the population exposed to some risk of P. falciparum was classified as inhabiting areas of unstable transmission; the total population in these areas was 0.98 billion people. Table 1 Area and Population at Risk of P. falciparum Malaria in 2007 Global and Regional Summary of P. falciparum Parasite Prevalence The summary data on age-corrected PfPR are presented without adjustments for biological and climatic covariates, urbanization, congruence with dominant Anopheles vector species, or any sampling issues inherent in an opportunistic sample of this kind. This is the subject of ongoing work. The summarized data, however, do provide important new insights into the ranges of infection prevalence reported between regions of the world within the P. falciparum spatial limits of stable and unstable transmission. A total of 4,278 spatially unique cross-sectional survey estimates of PfPR were assembled as part of the activities of the Malaria Atlas Project (MAP) by 01 September 2007. These included 186 (4.4%) surveys that were not possible to geolocate and are not considered further in the analysis. Of the positioned survey data, 3,700 (90.4%) were derived from individual communities (about 10 km2 or less), 131 from wide areas (more than about 10 km2 and about 25 km2 or less), 145 from small polygons (more than about 25 km2 and about 100 km2 or less), and 116 from large polygons (more than about 100 km2) [45]. A total of 406 surveys were undertaken outside the defined spatial limits of P. falciparum transmission, of which 46 reported presence of P. falciparum infection in the populations surveyed and 360 reported zero prevalence after allowing for a 10-km buffer around the limits. Thus, the overall sensitivity adjusting for plausible positioning errors [51] was 98.5%. There were 611 surveys falling inside the limits that reported zero prevalence. Even using the 10-km buffer the specificity of the limits was low (37.1%). This reflects the difficulties in estimating zero prevalence without large sample sizes [52], as well as the over-dispersed nature of infection risks between communities within small spatial scales [53]. The global diversity of the age-corrected PfPR2–10 estimates within the limits of transmission is shown in Figures 2–5. A total of 253 surveys reported zero prevalence among 2,121 surveys undertaken in AFRO (Figure 2). Outside of Africa, 358 surveys reported zero prevalence among 1,565 surveys undertaken within the defined limits of transmission. Over 92% and 95% of surveys reporting PfPR2–10 ≥ 50% and ≥ 75%, respectively, were located in AFRO and concentrated mostly between 15° latitude north and south, areas inhabited by Anopheles gambiae s.s. [54] (Figure 2). Conversely lower estimates of PfPR2–10 were described among those surveys conducted in areas occupying the A. arabiensis–dominant regions along the Sahel, horn, and southern areas of Africa [54] (Figure 2). In AMRO (Figure 3) and EMRO-EURO (Figure 4), 87% and 65% of surveys reported PfPR2–10 below 10%, respectively, referred to classically as hypoendemic. Over 65% of PfPR2–10 survey estimates in the combined SEARO-WPRO region reported infection prevalence below 10% (Figure 5), including 218 surveys reporting zero prevalence. Figure 2 Community Surveys of P. falciparum Prevalence Conducted between 1985 and 2007 in AFRO Other regions are shown in Figures 3–5. Of the 4,278 surveys reported globally, 4,092 could be geopositioned of which 3,686, shown in these figures, fell within the predicted limits of P. falciparum malaria risk. A total of 406 records, not shown in the figures, were found outside the limits, of which 46 reported presence of P. falciparum. Data shown are age-standardized (PfPR2–10) and represented as a continuum from zero to 100%. Table 2 and Figure 6 present detailed descriptive statistics for these data. Figure 3 Community Surveys of P. falciparum Prevalence Conducted between 1985 and 2007 in AMRO Figure 4 Community Surveys of P. falciparum Prevalence Conducted between 1985 and 2007 in EMRO-EURO Figure 5 Community Surveys of P. falciparum Prevalence Conducted between 1985 and 2007 in SEARO-WPRO Table 2 Summaries of the P. falciparum Parasite Rate Data Reported between 1985 and 2007 and Mapped within the Spatial Limits of P. falciparum Malaria Figure 6 Box and Whisker Plots of PfPR2–10 by Period and WHO Regions Thick black lines are the medians, and the light-blue boxes represent interquartile ranges; whiskers show extreme, non-outlier observations. Empty circles represent mild and/or extreme outliers. Sample sizes correspond to those shown in Table 2. Despite notable gaps in the coverage of PfPR2–10 data in many areas (Figures 2–5), a summary of the ranges of prevalence survey estimates is provided in Table 2 and Figure 6. These data are presented for the whole time period (Figure 6, top panel) and stratified by time (Figure 6, middle and bottom panels). We stress that these data are not spatially congruent and therefore should not be viewed as representing secular changes in PfPR2–10 estimates by WHO region. The data used for the bottom panel of Figure 6 are potentially of greater value, however, when describing the endemicity characteristics of malaria within the spatial limits shown in Figure 1, as they represent the most contemporary summary of malaria endemicity judged by PfPR2–10. Discussion We have triangulated as much information as we could assemble from exhaustive searches to provide an improved evidence-based description of the limits of P. falciparum transmission globally. The spatial referencing of health statistics, medical intelligence, and national expert opinion represents, to our knowledge, the most complete, current framework to understand the global distribution of P. falciparum risk in 2007. The use of plausible biological constraints upon transmission, based on long-term temperature data and remotely sensed correlates of vegetation cover, improved the spatial precision of the limits and categories of risk. We estimate that there were 2.37 billion people at risk of P. falciparum worldwide in 2007, and 40.1 million km2 of the world might be able to support P. falciparum transmission. Assembling geographic information on disease risk is an iterative process, building on new data and identifying gaps in our knowledge. We have presented previously the distribution of P. falciparum using historical descriptions of risk [1,16] and through the reconciliation of information in multiple travel advisories [55,56]. None have been perfect representations of contemporary malaria distributions worldwide, but such work has initiated a dialogue on the importance of providing an evidence base to malaria cartography and in the sharing of this information [15]. We have not considered the spatial distribution of P. vivax in this paper for a number of methodological reasons. First, the accuracy of health reporting systems for P. vivax clinical cases in areas of coincidental P. falciparum risk is notoriously poor [57]. Second, the climatic constraints on parasite–vector survival are less well defined and thus harder to predict using standardized regional-specific vector bionomics [58]. Third, the combined effects of a prolonged liver stage and the consequences upon natural and drug-resistant recrudescence make the interpretation of prevalence data considerably harder for P. vivax compared to P. falciparum [59]. We are acutely aware that the spatial extent and disease burden of P. vivax merits more attention than it has received, but to achieve an informed evidence-based map similar to that of P. falciparum demands a more fundamental construction of the basic biology of transmission and clinical epidemiology before this can be attempted effectively. We have been cautious in the use of the PfAPI data reported at national levels, recognizing the inadequacies and incompleteness of malaria surveillance [1,23–26]. The intention has been to identify administrative reporting areas that had not detected cases of P. falciparum malaria between 2002 and 2006. It was also recognized that there existed a wide range of reported PfAPI estimates, from one case per 100,000 people pa to reports of confirmed cases in almost 50% of the population every year, which presents a problem for the classification of risk. We therefore applied threshold criteria that would distinguish areas of low clinical risk (i.e., those areas reporting few cases and likely to support unstable transmission conditions) from areas with higher reported case incidence and probably more stable in their P. falciparum transmission characteristics. Our use of a distinction between unstable and stable transmission at 0.1 per thousand pa, while conservative is not without precedent. During the era of the Global Malaria Eradication Programme, epidemiologists proposed a variety of criteria to describe malaria risk in concert with preparatory, active, consolidation, and maintenance phases of elimination and ultimate “eradication” [60–63]. Parasite prevalence was the metric of choice for defining baseline endemicity in the preparatory phase and was useful as an indicator of control progress in the attack phase [52,64], until it became impossible to measure with cost-efficient sampling at very low levels of endemicity. At this juncture, it was proposed that malaria risk be measured through incidence metrics such as the PfAPI [65]. We identified very few PfPR surveys (n = 233) undertaken in areas where reported PfAPI was below 0.1 per thousand pa, 70 (30%) of which reported zero prevalence (Figures 2–5); and the median parasite prevalence was 1.4% (Table 2). It seems appropriate, practical, and feasible to consider multiple metrics during the assembly of malaria risk maps, and we have combined two common malariometric measures of risk: the PfAPI and PfPR. The mathematical relationship between these measures and other traditional epidemiological measures, such as the basic reproduction rate of infection and the entomological inoculation rate, is the subject of ongoing research [61]. Stratification of these risk areas by dominant vector species to enable a more informed assessment of the appropriate suites of intervention measures is also being pursued actively [15]. The PfPR data have been assembled from peer-reviewed literature, unpublished ministry of health sources, postgraduate theses and provision of raw data from malaria scientists in all malaria endemic regions [45]. They do not derive from nationally representative, random-sample surveys. Their coverage might, therefore, be subject to bias toward areas thought to be more malarious. The inclusion of 971 geopositioned surveys reporting zero prevalence (including 523 [53.8%] from Africa), however, does not support this view. Future investigation of the ecological and climatic covariates of PfPR2–10 will need to move from the categorical descriptions of over-dispersed endemicity data presented here, to geostatistically robust estimates of risk that are cognisant of the many potential biases in these data across the entire limits of stable transmission shown in Figure 1. We note, however, that as infection prevalence responds to increased intervention coverage and access to effective medicines, the use of traditional biological covariates might prove less effective in predicting the distribution of P. falciparum transmission intensity. Spatial models of PfPR distribution are being developed and tested as part of MAP's ongoing research to more accurately reflect the ranges of malaria transmission intensity within the margins of stable endemicity. Moreover, the PfAPI and PfPR data described in the present paper will change with time, and future data assemblies need to be maintained in a world with a rapidly changing malaria epidemiology. The supporting geostatistical models used to predict the spatial distribution of endemicity must also therefore facilitate rapid updates. The annual revision of the spatial limits of stable and unstable malaria, based upon new medical intelligence, PfAPI summaries, and the increasingly available contemporary PfPR information will iteratively redefine the cartography of malaria and be hosted on the MAP website ( as a public domain resource [15]. Assuming some degree of fidelity in the descriptions of unstable malaria used here, we estimate that one quarter (∼26%) of the malaria-endemic areas of the world are exposed to some degree of unstable P. falciparum transmission and home to approximately one (0.98) billion people. Even within the regions with more stable transmission, the available empirical evidence from contemporary PfPR2–10 survey data is that outside of AFRO, the intensity of transmission is best described as hypoendemic [66] (Figure 6). This observation has important implications for how we view malaria control and broader development goals at a global scale over the next decade. The provisional categorical descriptions of global P. falciparum malaria risk are shown in Figure 1 and suggest that, at a global scale, an aggressive approach to P. falciparum elimination might be reconsidered as a more ambitious and achievable objective in many areas. Regional initiatives aimed at elimination have begun [11–14]. In the Americas, elimination is considered in the most recent 5-y regional strategic plan [12]. In the European region, the two PfMECs (Tajikistan and Kyrgyzstan) are targeted for P. falciparum elimination within the next 5 y [11,13]. Detailed plans have been developed in the Eastern Mediterranean region to consider targeted P. falciparum elimination strategies in Iran and Saudi Arabia, while strengthening maintenance phases of elimination in currently P. falciparum–free countries [14]. With the exception of EURO, detailed maps of the spatial extents of risk in these various regions are not available. Where elimination is considered a viable strategy, resource requirements, targets, and maps become a regional and sub-regional public good and are no longer solely national concerns. Saudi Arabia is providing substantial financial support for the elimination of malaria in its neighbour, Yemen [67]. If this plan is successful, the reportedly high rates of population inflow from Somalia [68] will pose a continued concern due to the potential reintroduction of the parasite. This situation further highlights the need for a reproducible and evidence-based global map of malaria risk that is maintained as a dynamic platform to estimate and predict cross-border risk. Maintaining the detail necessary to map the spatial extent of malaria risk is paramount to the future of malaria control outside of Africa over the next 5 y. We would also argue, however, that Africa has been labelled inappropriately as a vast expanse of holoendemic transmission, intractable to control. Less than a third of all surveys retrieved from AFRO (29%) reported parasite prevalence above 50%, and, as has been described, these results followed closely the distribution of A. gambiae s.s. [54]. The conditions of hypoendemic and mesoendemic transmission were common in surveys conducted outside of this belt (which are not subject to the ravages of this most efficient vector) and are likely to benefit from approaches to prevention and control specific to the underlying ecologic and epidemiologic conditions [15,69,70]. The descriptions of transmission intensity are dynamic and the PfPR2–10 estimates in Africa (Figure 2) do not correspond to levels of endemicity described four decades ago [17]. In the AFRO region, there has been a recent expansion of insecticide-treated net coverage and provision of effective medicines. These programmatic successes are showing tangible impacts on mortality [8,9,71] and morbidity [8,9,72], and it would seem entirely plausible that similar effects will be operating at the level of transmission. If Africa is undergoing a malaria epidemiological transition, capturing this dynamic through mapped information on infection prevalence, and planning accordingly, should be high on the control agenda. The current focus of the Roll Back Malaria movement is, appropriately, in Africa, as this continent bears the brunt of malaria morbidity and mortality [73,74] and the descriptions presented here reinforce this view. P. falciparum transmission is a global problem, however, requiring a global strategy with regional targets and approaches tailored to what can be achieved within defined intervention periods [61]. This strategic planning demands an epidemiologically consistent map that is constantly updated. The assembly of risk data presented here represents the first attempt to combine disparate sources of malariometric data that should serve as a dynamic platform to define a global strategy and map its progress over the coming decades. The maps and national levels of population at unstable and stable risk are released in the public domain, with the publication of this paper, to further that global effort (MAP, Supporting Information Protocol S1 Sources and Descriptions of Medical Intelligence Used to Describe the PfAPI (346 KB DOC) Click here for additional data file. Protocol S2 Developing Global Biological Limits for P. falciparum Transmission (1.3 MB DOC) Click here for additional data file. Table S1 National Estimates of Population at Risk of P. falciparum Malaria in 2007 (231 KB DOC) Click here for additional data file.
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              Malaria misdiagnosis: effects on the poor and vulnerable.

              Effective and affordable treatment is recommended for all cases of malaria within 24 h of the onset of illness. Most cases of "malaria" (ie, fever) are self-diagnosed and most treatments, and deaths, occur at home. The most ethical and cost-effective policy is to ensure that newer drug combinations are only used for true cases of malaria. Although it is cost effective to improve the accuracy of malaria diagnosis, simple, accurate, and inexpensive methods are not widely available, particularly in poor communities where they are most needed. In a recent study in Uganda, Karin Kallander and colleagues emphasise the difficulty in making a presumptive diagnosis of malaria, and highlight the urgent need for improved diagnostic tools that can be used at community and primary-care level, especially in poorer populations (Acta Trop 2004; 90: 211-14). WHERE NEXT? Health systems need strengthening at referral and community level, so that rapid accurate diagnosis and effective treatment is available for those who are least able to withstand the consequences of illness. Indirect evidence strongly suggests that misdiagnosis of malaria contributes to a vicious cycle of increasing ill-health and deepening poverty. Much better direct evidence is needed about why and how misdiagnosis affects the poor and vulnerable.

                Author and article information

                Role: Academic Editor
                PLoS Med
                PLoS Medicine
                Public Library of Science (San Francisco, USA )
                July 2010
                July 2010
                6 July 2010
                : 7
                : 7
                [1 ]Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, United Kingdom
                [2 ]Malaria Public Health and Epidemiology Group, Centre for Geographic Medicine, KEMRI–University of Oxford–Wellcome Trust Collaborative Programme, Nairobi, Kenya
                [3 ]Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
                London School of Hygiene and Tropical Medicine, United Kingdom
                Author notes

                ICMJE criteria for authorship read and met: PWG VCK VAA EAO AMN RWS. Agree with the manuscript's results and conclusions: PWG VCK VAA EAO AMN RWS. Designed the experiments/the study: PWG RWS. Analyzed the data: PWG VAA AMN RWS. Collected data/did experiments for the study: PWG VAA EAO AMN RWS. Wrote the first draft of the paper: PWG RWS. Contributed to the writing of the paper: PWG VCK VAA AMN RWS.

                Gething et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 12
                Research Article
                Evidence-Based Healthcare/Health Services Research and Economics
                Infectious Diseases/Epidemiology and Control of Infectious Diseases
                Public Health and Epidemiology/Health Policy



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